Building construction parameter optimization method and system

Abstract

The application is suitable for the technical field of building construction, and particularly relates to a building construction parameter optimization method and system. The building construction parameter optimization method comprises the following steps: obtaining building construction associated parameters; performing standardized analysis and classification on the building construction associated parameters based on a building construction standard parameter framework to obtain identification fields and core performance parameters of each building construction associated parameter; merging the identification fields to obtain a target performance constraint type corresponding to a reorganized identification; performing collaborative optimization on core performance parameters of each type by identifying the target performance constraint type, generating optimal construction parameters adapted to construction, and generating adaptive metadata synchronized with the optimal construction parameters by restoring adaptive boundary conditions of the optimal construction parameters. The method greatly improves the adaptive accuracy of construction parameters and construction scenes.

Description

Technical Field

[0001] This application belongs to the field of building construction technology, and in particular relates to a method and system for optimizing building construction parameters. Background Technology

[0002] With the deep integration of industrialized building and green building concepts, prefabricated buildings, with their core advantages of factory-prefabricated components and on-site assembly, have become the mainstream direction for promoting high-quality development in the construction industry. Building structural parameters, as the core foundation for the construction and performance assurance of prefabricated buildings, cover the entire chain of processes, including component production, material supply, construction site, and construction technology. These parameters include production parameters such as dimensional tolerances and concrete strength grades during component production; performance parameters such as thermal conductivity, compressive strength, and durability of materials; environmental parameters such as temperature, humidity, wind speed, and soil bearing capacity at the construction site; and construction technology parameters such as hoisting speed, grouting pressure, and curing time. These parameters are scattered, varied in format, and interconnected; their processing quality directly affects the structural safety, construction efficiency, and overall performance of the building.

[0003] In the current process of processing and applying structural parameters for prefabricated buildings, there are significant differences in the units of measurement, data formats, and expressions of parameters provided by different manufacturers and at different stages. This leads to a large amount of manpower being required for manual conversion and verification before construction, which is not only inefficient but also prone to data deviation due to human error. Various parameters are scattered and independent, lacking an effective correlation and integration mechanism, making it difficult to quickly clarify the performance requirements corresponding to the parameters. This results in a lack of responsiveness in matching parameters with multiple constraints such as seismic resistance, thermal insulation, structural stability, and construction adaptability. Summary of the Invention

[0004] This application provides a method and system for optimizing building structural parameters, which can solve the problem that it is difficult to quickly determine the performance requirements corresponding to the parameters in the current process of processing and applying prefabricated building structural parameters.

[0005] In a first aspect, embodiments of this application provide a method for optimizing building structural parameters, including: Obtain building structure-related parameters; wherein, the building structure-related parameters include component production parameters, material performance parameters, site environment parameters, and construction process parameters; Based on the standard parameter framework for building construction, the associated parameters of the building construction are standardized and classified to obtain the identification fields and core performance parameters of each associated parameter of the building construction. The identification fields are merged to obtain the target performance constraint type corresponding to the recombined identification; wherein, the target performance constraint type includes seismic performance constraint, thermal insulation constraint, structural stability constraint and construction adaptability constraint; By identifying the target performance constraint type, collaborative optimization is performed on the core performance parameters of each type to generate optimal construction parameters suitable for construction. By restoring the adaptation boundary conditions of the optimal construction parameters, adaptation metadata synchronized with the optimal construction parameters is generated. The adaptation metadata includes parameter adjustment criteria, performance verification indicators, and construction fault tolerance range.

[0006] The technical solutions described in this application embodiment have at least the following technical effects: The building structural parameter optimization method provided in this application first standardizes and classifies the parameters of multi-source heterogeneous component production, material properties, site environment, and construction technology through a standard building structural parameter framework. This transforms fragmented parameters into standardized identifier fields and core performance parameters. Then, by merging these identifier fields, a recombinant identifier is obtained, accurately identifying target performance constraint types such as seismic resistance, thermal insulation, structural stability, and construction adaptability. This effectively reduces optimization bias driven by a single constraint, ensuring that parameter optimization always aligns with multiple compliance requirements and actual needs. Based on this, collaborative optimization is performed on each core performance parameter for the target performance constraint type, breaking the limitations of isolated adjustments in a single dimension. This fully considers the coupling relationship between parameters, significantly improving the accuracy of structural parameter adaptation to the construction scenario. Finally, by restoring the optimal structural parameter adaptation boundary conditions and generating synchronized adaptation metadata, clear parameter adjustment criteria, performance verification indicators, and construction tolerance ranges are provided for dynamic changes at the construction site. This achieves a leap from static optimization to dynamic adaptation, comprehensively ensuring construction quality and structural safety, and contributing to the industrialization and high-quality development of prefabricated buildings.

[0007] Secondly, embodiments of this application provide a building structural parameter optimization system, including: The first acquisition module is used to acquire building structure related parameters; wherein, the building structure related parameters include component production parameters, material performance parameters, site environment parameters, and construction process parameters; The classification module is used to perform standardized parsing and classification of the building structure-related parameters based on the building structure standard parameter framework, so as to obtain the identification field and core performance parameters of each building structure-related parameter; The second acquisition module is used to merge the identification fields to obtain the target performance constraint type corresponding to the recombined identification; wherein, the target performance constraint type includes seismic performance constraint, thermal insulation constraint, structural stability constraint and construction adaptability constraint; The optimization module is used to identify the target performance constraint type, perform collaborative optimization on the core performance parameters of each type, generate optimal construction parameters adapted to construction, and generate adaptation metadata synchronized with the optimal construction parameters by restoring the adaptation boundary conditions of the optimal construction parameters; wherein, the adaptation metadata includes parameter adjustment criteria, performance verification indicators and construction fault tolerance range.

[0008] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described in the first aspect above.

[0009] Fourthly, embodiments of this application provide a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method described in the first aspect above.

[0010] Fifthly, embodiments of this application provide a computer program product that, when run on an electronic device, causes the electronic device to execute the building structure parameter optimization method described in the first aspect above.

[0011] It is understood that the beneficial effects of the second to fifth aspects mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here. Attached Figure Description

[0012] To more clearly illustrate the technical solutions in the embodiments of this application, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0013] Figure 1 This is a flowchart illustrating the building structure parameter optimization method provided in an embodiment of this application; Figure 2 This is a schematic diagram of standardized analytical classification in the building structural parameter optimization method provided in the embodiments of this application; Figure 3 This is a schematic diagram of the building construction parameter optimization system provided in the embodiments of this application; Figure 4 This is a schematic diagram of the structure of the control device of the electronic device provided in the embodiments of this application. Detailed Implementation

[0014] In the following description, specific details such as particular system architectures and techniques are set forth for illustrative purposes and not for limitation, in order to provide a thorough understanding of the embodiments of this application. However, those skilled in the art will understand that this application may also be implemented in other embodiments without these specific details. In other instances, detailed descriptions of well-known systems, apparatuses, circuits, and methods have been omitted so as not to obscure the description of this application with unnecessary detail.

[0015] It should be understood that, when used in this application specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or a collection thereof.

[0016] It should also be understood that the term “and / or” as used in this application specification and the appended claims means any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0017] As used in this application specification and the appended claims, the term "if" may be interpreted, depending on the context, as "when," "once," "in response to determination," or "in response to detection." Similarly, the phrases "if determination" or "if the described condition or event is detected" may be interpreted, depending on the context, as "once determination," "in response to determination," "once the described condition or event is detected," or "in response to the detection of the described condition or event."

[0018] Furthermore, in the description of this application and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0019] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of this application include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0020] In the current process of processing and applying structural parameters for prefabricated buildings, there are significant differences in the units of measurement, data formats, and expressions of parameters provided by different manufacturers and at different stages. This leads to a large amount of manpower being required for manual conversion and verification before construction, which is not only inefficient but also prone to data deviation due to human error. Various parameters are scattered and independent, lacking an effective correlation and integration mechanism, making it difficult to quickly clarify the performance requirements corresponding to the parameters. This results in a lack of responsiveness in matching parameters with multiple constraints such as seismic resistance, thermal insulation, structural stability, and construction adaptability.

[0021] To address the aforementioned issues, this application provides a method and system for optimizing building structural parameters. The method first standardizes and classifies multi-source heterogeneous component production, material properties, site environment, and construction process parameters using a standard building structural parameter framework. Fragmented parameters are then uniformly transformed into standardized identifier fields and core performance parameters. Next, by merging these identifier fields, a recombinant identifier is obtained, accurately identifying target performance constraint types such as seismic resistance, thermal insulation, structural stability, and construction adaptability. This effectively reduces optimization bias driven by a single constraint, ensuring that parameter optimization always aligns with multiple compliance requirements and actual needs. Based on this, collaborative optimization is performed on each core performance parameter for the target performance constraint type, breaking the limitations of isolated adjustments in a single dimension. This fully considers the coupling relationship between parameters, significantly improving the accuracy of structural parameter adaptation to the construction scenario. Finally, by restoring the optimal structural parameter adaptation boundary conditions and generating synchronized adaptation metadata, clear parameter adjustment criteria, performance verification indicators, and construction tolerance ranges are provided for dynamic changes at the construction site. This achieves a leap from static optimization to dynamic adaptation, comprehensively ensuring construction quality and structural safety, and contributing to the industrialization and high-quality development of prefabricated buildings.

[0022] The building structure parameter optimization method provided in this application embodiment can be applied to electronic devices. In this case, the electronic device is the executing subject of the building structure parameter optimization method provided in this application embodiment. This application embodiment does not impose any restrictions on the specific type of electronic device.

[0023] For example, electronic devices can be mobile phones, tablets, wearable devices, augmented reality (AR) / virtual reality (VR) devices, laptops, ultra-mobile personal computers (UMPCs), netbooks, personal digital assistants (PDAs), desktop computers, smart screens, smart TVs, and other terminal devices; handheld devices with wireless communication capabilities; computing devices or other processing devices connected to a wireless modem; Internet of Things (IoT) terminals; computers; laptops; handheld communication devices; handheld computing devices; satellite wireless devices; wireless modem cards; set-top boxes (STBs); customer premises equipment (CPEs); and / or other devices used for communication over wireless systems, as well as next-generation communication systems, such as mobile terminals in 5G networks or mobile terminals in future evolved Public Land Mobile Networks (PLMNs).

[0024] To better understand the building structure parameter optimization method provided in the embodiments of this application, the specific implementation process of the building structure parameter optimization method provided in the embodiments of this application will be described by way of example below.

[0025] Figure 1 A schematic flowchart of a building structural parameter optimization method provided in an embodiment of this application is shown. The building structural parameter optimization method includes: S100, obtain building structure related parameters; among which, building structure related parameters include component production parameters, material performance parameters, site environment parameters and construction process parameters.

[0026] It is understandable that building construction parameters are a collection of core data throughout the entire lifecycle of prefabricated buildings, covering key stages from factory prefabrication to on-site assembly, aligning with the core characteristics of prefabricated building components + on-site assembly. Component production parameters focus on key production indicators for prefabricated components (including precast concrete components, steel structure components, precast wall panels, etc.), specifically including component type (such as precast composite slabs, precast stairs, steel columns, precast integrated insulation wall panels), geometric dimensional parameters (length, width, thickness and corresponding tolerances, such as a length tolerance of ±3mm for precast composite slabs), material proportioning parameters (aggregate gradation and water-cement ratio for precast concrete components, steel grade and alloy composition ratio for steel structure components), and factory quality inspection parameters (component appearance flatness, crack width, rebar protective layer thickness, weld flaw detection results for steel structure components), etc. These parameters can be collected in real time through factory production management systems and automated testing equipment (such as laser rangefinders and ultrasonic flaw detectors), or digitized from paper documents such as component factory certificates of conformity and test reports.

[0027] Material performance parameters cover the key performance indicators of core materials required for prefabricated buildings (including raw materials for prefabricated components, connecting materials, thermal insulation and waterproofing materials, etc.). These parameters are provided by material suppliers and verified by third-party testing institutions. Specifically, they include the compressive strength grade of concrete (e.g., C30, C40, conforming to GB 50010 "Code for Design of Concrete Structures") and axial tensile strength; the yield strength, tensile strength, and elongation of reinforcing steel (conforming to GB / T 1499 series standards for reinforcing steel for concrete structures); the yield strength, impact toughness, and corrosion resistance of steel used in steel structures; the thermal conductivity, combustion performance rating (conforming to GB 8624 "Classification of Combustion Performance of Building Materials and Products"), and compressive strength of thermal insulation materials (e.g., extruded polystyrene board, rigid polyurethane foam); the tensile bond strength and weather resistance of sealants; and the flowability and compressive strength of grouting materials (conforming to GB 50666 "Code for Construction of Prefabricated Concrete Structures"). Data sources may include material testing report numbers, specific performance values, testing dates, and supplier qualification codes.

[0028] On-site environmental parameters can be collected in real time by a multi-dimensional sensor group deployed on the construction site, focusing on environmental factors that affect the assembly quality of precast components and construction safety. Specifically, these parameters can include ambient temperature and humidity (accuracy ±0.5℃, ±5%RH, collection frequency once every 60 minutes), precipitation (monitoring whether it affects concrete pouring and grouting construction), and soil bearing capacity (obtained according to the testing methods specified in the "Code for Design of Building Foundations" GB 50007).

[0029] Construction process parameters can be obtained from real-time monitoring of construction equipment and process execution records, focusing on the core procedures of on-site assembly of precast components. Specifically, these parameters may include the hoisting speed (e.g., 0.5 m / s), hoisting weight, and hoisting angle of the hoisting equipment (to ensure accurate positioning of precast components); the grouting pressure (e.g., 1.2 MPa), grouting volume, and grouting speed of the grouting equipment (to ensure the tightness of joint connections); the control value of the splicing gap of precast components and the bolt tightening torque (e.g., the pre-tightening force of M24 high-strength bolts ≥ 205 kN); the erection spacing and support strength of the formwork support (to ensure the stability of components during assembly); and the curing time and curing temperature (for the strength development of on-site poured concrete and grouting materials), etc.

[0030] It should be noted that after obtaining the building structure-related parameters, preliminary preprocessing is required to address the heterogeneity of the multi-source data: First, data format conversion, unifying the Excel and PDF test reports and equipment monitoring data from different manufacturers into a unified format (such as JSON); second, outlier removal, filtering invalid data (such as temperature and humidity data exceeding the range, and material strength data below design requirements) by setting thresholds (such as sensor range or the qualified range of parameters specified by national standards); third, data timestamp alignment, matching parameters collected from different acquisition devices and at different times according to the construction process progress (such as component hoisting period or grouting period); and fourth, data integrity verification, checking whether each type of parameter is missing (such as whether the factory test parameters of precast components are complete, and whether the material test reports are complete), in order to form a structured set of building structure-related parameters.

[0031] S200 standardizes and classifies the building structure-related parameters based on the building structure standard parameter framework, and obtains the identification fields and core performance parameters of each building structure-related parameter.

[0032] It can be understood that the standard parameter framework for building construction refers to a unified, scalable, and standardized parameter processing system built to address industry pain points such as heterogeneous formats, inconsistent definitions, and loose correlations of multi-source structural parameters (component production, material properties, site environment, construction technology) in prefabricated buildings. Based on current national standards and specifications for the construction industry, prefabricated building construction processes, and quality control requirements, it supports the normalization, structured classification, and correlation mapping of multi-source parameters. This framework is not an isolated parameter list, but a structured system encompassing core dimensions such as classification logic, field specifications, validation rules, and correlation mapping. Its establishment follows the principles of compliance priority, practicality adaptation, and scalability compatibility, fully aligning with the entire process characteristics of prefabricated buildings, which involves factory prefabrication and on-site assembly.

[0033] Identification fields refer to field specifications based on the standard parameter framework of building construction. They are standardized codes formed by extracting core attribute information from the associated parameters of building construction and arranging them in a fixed format. They are identity identifiers that represent the source of parameters, compliance basis, and constraint association. Its core function is to break down information barriers between parameters from different sources and of different types, enabling parameters to be traceable, associative, and verifiable. Specifically, it can include four types of core information: First, the parameter source code (such as component manufacturer number, material supplier qualification code, sensor number, construction equipment model code, following the region-year-serial number or industry-unified coding rules); second, the compliance standard code (corresponding to the national standard number and specific clauses on which the parameter is based, such as GB / T 51231-2016-6.3.2, GB 50666-2011-7.2.3, clarifying the compliance basis of the parameter); third, the constraint association code (a mapping code to the target performance constraint type, such as JG-KZ-01 corresponding to seismic performance constraints, GN-BW-02 corresponding to thermal insulation constraints, establishing the association through a frame association mapping table); and fourth, the check code (a check code that can be generated using algorithms such as CRC16, used to verify the integrity and accuracy of the identification field, preventing data tampering during transmission or storage). The identification field is arranged in a fixed format of type-specific prefix + source code - standard code - association code - check code. For example, the identification field of component production-concrete precast component is GJ-HNT-CS-2025-008-GB / T51231-2016-6.3.2-JG-WD-01-7A3F.

[0034] Core performance parameters refer to standardized data that, after stripping away redundant and decorative information from building construction-related parameters, focus on the core technical indicators of the parameters and meet the core performance requirements of the building construction standard parameter framework. Their selection is based on a pre-defined list of core performance items for each type of attribute (first-level category + second-level sub-category) within the framework, ensuring direct relevance to the structural safety, functional realization, and construction adaptability of prefabricated buildings. For example, core performance items for component production parameters include geometric dimensions and tolerances, material strength grade, steel reinforcement protective layer thickness, and surface smoothness; core performance items for material performance parameters include thermal conductivity, compressive strength, fire performance rating, and tensile bond strength; core performance items for site environment parameters include ambient temperature and humidity, wind speed, soil bearing capacity, and precipitation; and core performance items for construction process parameters include hoisting speed, grouting pressure, bolt preload, and curing time.

[0035] For example, feature extraction can be performed on various building structure-related parameters to obtain feature keywords. Then, the feature keywords are compared with the classification dimensions of the building structure-related parameters to determine the type attributes of each building structure-related parameter. Based on the type attributes, the corresponding identification fields and core performance parameters of the building structure-related parameters can be extracted. Alternatively, the preset parameter-field mapping template in the building structure standard parameter framework can be directly called to perform template matching extraction on structured raw parameters (such as standardized data exported from the factory production management system and formatted data uploaded by sensors in real time). For example, the component model data of precast composite slab 6000×1200×120, tolerance: ±3mm, strength grade: C40 in the precast component production system can be directly matched with the mapping template of component production category - precast concrete component in the framework to automatically extract the identification fields (including manufacturer number, GB / T51231 standard code, structural stability constraint association code) and core performance parameters (length: 6000mm, width: 1200mm, thickness: 120mm, tolerance: ±3mm, strength grade: C40).

[0036] In one possible implementation, please refer to Figure 2 In step S200, based on the standard parameter framework for building construction, the associated parameters of building construction are standardized, parsed, and classified to obtain the identifier fields and core performance parameters of each associated parameter, including: S210, feature extraction is performed on the associated parameters of each building structure to obtain feature keywords.

[0037] It is understandable that feature extraction is a prerequisite for achieving accurate classification of multi-source heterogeneous parameters in prefabricated buildings. Its core objective is to extract redundant information from the original parameter data and extract core keywords that can characterize the essential attributes of the parameters and are consistent with the classification dimensions of the standard parameter framework for building construction.

[0038] By leveraging the unique characteristics of prefabricated building parameters, a triple extraction strategy combining semantic parsing, contextual association, and industry standard mapping can be employed to extract features from building construction-related parameters. For example, for textual raw parameters (such as the prefabricated composite slab length tolerance ±3mm in component production parameters, the extruded polystyrene board thermal conductivity of 0.028W / (m・K) in material performance parameters, and the M24 high-strength bolt preload of 205kN in construction process parameters), semantic segmentation is first performed using natural language processing (such as NLP models) technology to identify core nouns, technical indicator terms, and key attribute words: the prefabricated composite slab length tolerance ±3mm is segmented into prefabricated composite slab (component type) and length tolerance (technical indicator); the extruded polystyrene board thermal conductivity of 0.028W / (m・K) is segmented into extruded polystyrene board (material type) and thermal conductivity (technical indicator); and the M24 high-strength bolt preload of 205kN is segmented into high-strength bolt (connection material type) and preload (technical indicator). Meanwhile, for complex text parameters containing multiple attributes (such as the appearance flatness of precast concrete stairs ≤5mm / m and crack width ≤0.3mm), keywords corresponding to each technical indicator can be extracted, namely precast concrete stairs, appearance flatness, and crack width.

[0039] For numerical raw parameters (such as hoisting speed 0.5m / s, grouting pressure 1.2MPa, and ambient temperature 25℃), keywords can be extracted by combining the contextual information such as the acquisition scenario and equipment labels: hoisting speed 0.5m / s combined with the acquisition equipment being a tower crane, add tower crane hoisting (process type) as a keyword to finally obtain tower crane hoisting and hoisting speed; grouting pressure 1.2MPa combined with the construction process being node connection, add node grouting (process type) to obtain node grouting and grouting pressure; ambient temperature 25℃ combined with the sensor deployment location being the construction site, add construction site (environmental scenario) to obtain construction site and ambient temperature.

[0040] S220 compares the feature keywords with the classification dimensions of the building construction standard parameter framework to determine the type attributes of each building construction related parameter.

[0041] It is understandable that the identification comparison is the core step in establishing the correspondence between feature keywords and framework classification dimensions. Its essence is to use a precise matching algorithm to map the extracted feature keywords to the first-level category + second-level sub-category system of the building construction standard parameter framework, and to clarify the type attribute of each original parameter. For example, the feature keywords are fully compared with the names of the second-level subcategories, their unique identifiers, and core terms in the framework's classification dimensions. The framework's first-level categories (component production, material performance, site environment, and construction technology) and second-level subcategories all have pre-defined unique identifiers and core terminology databases. For instance, the identifier for the component production category—precast concrete components—is GJ-HNT, and its core terms include precast composite slabs, precast stairs, precast concrete components, dimensional tolerances, and the thickness of the reinforcing steel protective layer; the identifier for the material performance category—functional materials—is CL-GN, and its core terms include extruded polystyrene board, rigid polyurethane foam, thermal conductivity, and combustion performance rating; the identifier for the construction technology category—lifting technology—is GY-DZ, and its core terms include tower crane lifting, lifting speed, and lifting angle; and the identifier for the site environment category—meteorological environment—is HJ-QX, and its core terms include ambient temperature, relative humidity, and wind speed. If the feature keyword is completely consistent with the core term of a certain second-level subclass (e.g., the keywords "precast composite slab" and "dimensional tolerance" completely match the core term of the GJ-HNT subclass), then the type attribute of the parameter is directly determined to be the component production category - precast concrete component subclass, and associated with its exclusive identification code GJ-HNT; if the keywords "thermal conductivity" and "extruded polystyrene board" completely match the core term of the CL-GN subclass, then it is determined to be the material performance category - functional material subclass, and associated with the identification code CL-GN.

[0042] S230, extract the identifier field and core performance parameters of the corresponding building structure association parameters based on the type attribute.

[0043] It is understandable that the extraction process based on type attributes is the core step in further standardizing and structuring the categorized parameters. Its core is to strictly adhere to the field specifications and validation rules of the standard parameter framework for building construction, accurately extracting identifier fields and core performance parameters from parameters of different type attributes. This achieves parameter redundancy removal, standardization, and structuring, providing high-quality data support for subsequent identifier merging and collaborative optimization. For example, core elements of the corresponding building construction-related parameters can be extracted based on type attributes, and then arranged based on these core elements to obtain identifier fields. Simultaneously, based on the performance parameter requirements corresponding to the type attributes, core performance indicators of the corresponding building construction-related parameters can be extracted, and quantitative constraints can be applied to these core performance indicators to obtain core performance parameters.

[0044] Alternatively, a framework template matching + dynamic verification extraction method can be used. This involves calling the parameter-field mapping templates preset for each secondary subclass in the building construction standard parameter framework (e.g., the precast concrete composite slab template includes identifier fields such as manufacturer number, GB / T51231 standard code, structural stability constraint association code, and core performance items such as dimensions, tolerances, and strength grades). The structured raw data (e.g., Excel data exported from the precast component factory production system, JSON data uploaded by sensors in real time) is automatically matched with the templates, and the identifier fields and core performance parameters are directly extracted and filled. For unstructured data (e.g., scanned text of paper test reports, manually entered natural language descriptions), it can first be converted into text data using optical character recognition (OCR) technology, and then keyword matching can be performed based on the core terminology library of the secondary subclass in the framework (e.g., precast composite slab, thermal conductivity, hoisting speed). After locating the type attributes, the identifier fields and core performance parameters are extracted according to the template, and so on, but not limited to this.

[0045] This setup first extracts invalid modifiers from the original parameters through feature extraction, refining core keywords that fit the framework's classification dimensions. Then, by comparing these keywords with the identifiers of the building construction standard parameter framework's classification dimensions, a precise matching mechanism clarifies the type attributes of each parameter, improving the accuracy of type attribute determination. Finally, based on the type attributes, standardized identifier fields and core performance parameters are extracted, transforming heterogeneous parameters into traceable, associative, and computable structured data. This solves the problem of inconsistent parameter formats across different manufacturers and stages (such as differences in dimensional tolerance annotation methods and material strength descriptions), significantly reducing the time cost of manual parameter conversion and verification. At the same time, the framework specifications ensure data compliance and accuracy, laying a solid foundation for subsequent identifier field merging, target performance constraint type identification, and core parameter collaborative optimization, effectively guaranteeing the accuracy and efficiency of the entire parameter optimization process.

[0046] In one possible implementation, step S230 involves extracting the identifier field and core performance parameters of the corresponding building structure association parameters based on the type attribute, including: S231, extract the core elements of the fields corresponding to the building structure association parameters based on the type attribute.

[0047] It is understandable that extracting the core elements of a field is the fundamental prerequisite for generating standardized identification fields. Its core objective is to accurately extract key information that can uniquely represent the source of the parameter, the basis for compliance, and the constraints from the original parameters and related context information, based on the specific type attributes (including primary categories and secondary subcategories) of the four major categories of parameters for prefabricated buildings (component production, material performance, site environment, and construction technology), so as to provide complete and compliant core materials for the subsequent standardized arrangement of identification fields.

[0048] For example, for component production - related parameters (such as secondary sub - categories like precast concrete composite slabs, precast steel structure columns, prefabricated integrated thermal insulation wall panels, etc.), the extraction of the core elements of the field focuses on the source of component production and structural safety compliance: First, the parameter source code, which extracts the registration number of the component manufacturer (following the unified industry rule of region abbreviation - year - serial number, such as CS - Yue - 2025 - 018, where Yue represents the province where the manufacturer is located, 2025 is the production year, and 018 is the manufacturer's annual registration serial number); Second, the compliance standard code, which matches the national standard number and specific clauses in the framework association mapping table according to the component type. For example, the size parameters of precast concrete composite slabs correspond to Article 6.3.2 of the Technical Standard for Assembled Concrete Buildings GB / T 51231 - 2016, and the welding parameters of precast steel structure columns correspond to Article 7.4.3 of the Technical Standard for Assembled Steel Structure Buildings GB / T 51232 - 2016; Third, the constraint association code, based on the functional positioning of the component in the building, matches the corresponding target performance constraint type code through the framework mapping table. For example, load - bearing prefabricated components (beams, columns) match JG - WD - 02 (structural stability constraint), components in seismic fortification areas match JG - KZ - 01 (seismic performance constraint), and prefabricated integrated thermal insulation wall panels match GN - BW - 01 (thermal insulation constraint).

[0049] S232, arrange based on the core elements of the field to obtain the identification field.

[0050] It can be understood that the arrangement of the core elements of the field is the key step in transforming scattered elements into a standardized and unique identification field. Its core goal is to follow the fixed format + unified rule preset by the building construction standard parameter framework, and orderly splice the parameter source code, compliance standard code, constraint association code, and verification code to generate a parameter identity code with traceability, resolvability, and associativity characteristics. This process can execute the arrangement logic of type - specific prefix + orderly splicing of elements + verification code as a backup, so that the identification field formats of parameters of different types and sources are unified and the structures are standardized.

[0051] First, determine the type-specific prefix. The framework presets a unique exclusive prefix for each type of secondary subclass. The prefix is composed of the abbreviation of the major class + the abbreviation of the subclass, so that the parameter type can be quickly determined from the first paragraph of the identification field: for the component production category - the prefix for precast concrete components is GJ-HNT-, for precast steel structure components is GJ-GG-, and for precast integrated thermal insulation wall panels is GJ-BW-; for the material property category - for structural materials is CL-JG-, for functional materials is CL-GN-, and for connection materials is CL-LJ-; for the on-site environment category - for meteorological environment is HJ-QX-, for geological environment is HJ-DZ-, and for construction site environment is HJ-CD-; for the construction technology category - for hoisting technology is GY-DZ-, for grouting technology is GY-GJ-, and for support technology is GY-ZH-. Then, splice the core elements in a fixed order. The arrangement order is defined as the type-specific prefix + parameter source code - compliance standard code - constraint association code, and a "-" is used as the separator between each element: the parameter source code directly uses the extracted standardized code (such as CS-Guangdong-2025-018, CL-Shanghai-2025-042); the compliance standard code needs to remove the spaces and slashes in the national standard number (such as GB / T51231-2016-6.3.2, GB50666-2011-7.3.4); the constraint association code directly uses the extracted standardized code (such as JG-WD-02, SP-SZ-01). For example, the core elements of the component production category - precast concrete composite slab are spliced as GJ-HNT-CS-Guangdong-2025-018-GB / T51231-2016-6.3.2-JG-WD-02, the splicing of the material property category - thermal insulation material is CL-GN-CL-Shanghai-2025-042-GB50176-2016-4.2.1-GN-BW-01, and the splicing of the construction technology category - hoisting technology is GY-DZ-GY-Tower Crane-QTZ63-027-GB50666-2011-7.2.3-SP-SZ-01.

[0052] S233, based on the performance parameter requirements corresponding to the type attributes, extract the core performance indicators of the corresponding building structure association parameters, and perform quantitative constraints on the core performance indicators to obtain the core performance parameters.

[0053] It can be understood that the extraction and quantitative constraint of the core performance indicators are the key links to ensure that the parameters have the characteristics of being computable, comparable, and optimizable. The core goal is to strictly screen out the key technical indicators directly related to building structure safety, function realization, and construction adaptation from the original parameters according to the core performance item list preset for each secondary subclass by the building structure standard parameter framework for the parameters of different type attributes of prefabricated buildings, and then through quantitative constraint processing with unified units and standardized precisions, eliminate redundant information and abnormal data, and form standardized core performance parameters.

[0054] First, core performance indicators are precisely selected based on type and attribute. For example, for component production-type precast concrete components, the core performance item list focuses on structural safety and installation compatibility. The selected indicators include geometric dimensions (length, width, thickness), dimensional tolerances, concrete strength grade, reinforcement cover thickness, appearance flatness, and crack width. These indicators directly determine the load-bearing capacity and assembly accuracy of the component. For example, excessive dimensional tolerances will lead to excessive gaps between component splices, affecting the overall structural integrity; substandard concrete strength grade will reduce the component's seismic resistance and load-bearing capacity. Then, strict quantitative constraints were applied to the core performance indicators. For example, from the original parameters of precast composite slab length 6000mm, tolerance ±3mm, concrete strength grade C40, steel reinforcement protective layer thickness 25mm, and flatness ≤5mm / m, after screening and quantifying the core performance indicators, the core performance parameters were obtained as follows: length: 6000mm, length tolerance: ±3mm, concrete strength grade: C40, steel reinforcement protective layer thickness: 25mm, and flatness: ≤5mm / m. From the original parameters of extruded polystyrene board thermal conductivity 0.028W / (m・K), fire performance grade A, compressive strength 0.3MPa, and water absorption rate 2%, the core performance parameters were obtained as follows: thermal conductivity: 0.028W / (m・K), fire performance grade: A, compressive strength: 0.3MPa, and water absorption rate: 2%.

[0055] This setup, through a meticulous step-by-step design involving extracting core field elements, arranging identifier fields, and quantifying core performance parameters, precisely addresses the deep-seated pain points of prefabricated buildings, such as difficulty in tracing the sources of multi-source parameters, inconsistent formats, and ambiguous core indicators. The typological extraction of core field elements allows identifier fields to integrate information related to parameter source qualifications, compliance with national standards, and constraints, assigning each parameter a unique and traceable identification code. This enables full-process data traceability from component production and material supply to construction execution, significantly reducing the cost of quality traceability and compliance verification. The standardized arrangement of identifier fields unifies different types and sources. The parameter format structure breaks down information barriers between manufacturers and processes, providing an efficient adaptation foundation for subsequent cross-type identifier merging and constraint type parsing. The precise selection and quantitative constraints of core performance indicators (unified units, standardized precision, and verification range) strip away redundant information and eliminate abnormal data, transforming heterogeneous original parameters into standardized data that can be calculated, compared, and optimized. This reduces optimization deviations caused by inconsistent parameter formats and provides high-quality, highly reliable computational input for subsequent multi-objective collaborative optimization, thereby improving the accuracy, efficiency, and feasibility of the building structure parameter optimization process.

[0056] S300, merge the various identifier fields to obtain the target performance constraint type corresponding to the recombined identifier; among which, the target performance constraint type includes seismic performance constraint, thermal insulation constraint, structural stability constraint and construction adaptability constraint.

[0057] It is understandable that merging the identifier fields and obtaining the target performance constraint type is the core step in establishing the association between parameters and performance requirements. Essentially, it involves integrating the identifier field information of different parameters to identify the multiple performance constraints that the building structure must meet, thus clarifying the direction for subsequent collaborative optimization. For example, the merged identifier fields can be recombined according to performance association priority to obtain recombined identifiers, and then the target performance constraint type can be obtained by parsing the constraint fields of the recombined identifiers. Alternatively, constraint association codes can be extracted from all identifier fields, clustered according to constraint type (seismic performance, structural stability, thermal insulation, construction adaptability), and the frequency of occurrence of each constraint association code can be counted. Constraint types with a frequency ≥ 1 are initially included in the candidate set. Then, for conflicting constraints (such as one parameter being associated with a structural stability constraint, and another parameter being associated with a thermal insulation constraint that conflicts with construction space), coordination is carried out according to the principle of prioritizing structural safety and secondarily functional adaptability, retaining the core constraints and marking the adaptation boundaries of secondary constraints, ultimately forming the target performance constraint type, and so on, but not limited to these methods.

[0058] In one possible implementation, in step S300, the identifier fields are merged to obtain the target performance constraint type corresponding to the recombined identifier, including: S310, the merged identifier fields are reorganized according to performance association priority to obtain the reorganized identifier.

[0059] Performance correlation priority can be understood as an ordered ranking rule based on the core value logic of prefabricated buildings (safety first, functional adaptability, construction feasibility), combined with the mandatory requirements of current national standards and key needs of engineering practice. This rule categorizes various target performance constraints (seismic performance constraints, structural stability constraints, thermal insulation constraints, construction adaptability constraints) that building structures must meet, according to their weight, importance, and constraint attributes (mandatory / recommended) throughout the building's entire lifecycle (design, construction, use, operation and maintenance). The performance correlation priority can be determined through methods such as the constraint hierarchy of national standards, the severity of risk impact, on-site measurement and monitoring, and past experience. After obtaining the data, it is organized, classified, and archived to extract useful information and patterns to arrive at the performance correlation priority.

[0060] This step is a crucial bridge connecting the merging of identifier fields and the parsing of constraint types. Its core objective is to prioritize and structurally reorganize the identifier fields of the merged multi-source parameters, based on the fundamental principle of prioritizing structural safety and secondary functional adaptability in prefabricated buildings. This clarifies the importance of different performance constraints and reduces the risk of missing core requirements due to disordered constraint order during subsequent analysis. The merged identifier fields contain constraint association codes, standard codes, and source codes for multiple parameters (e.g., JG-WD-02 for component production parameters, GN-BW-01 for material performance parameters, and SP-SZ-01 for construction process parameters). These constraint association codes correspond to different target performance constraint types; an disordered arrangement would make it difficult to distinguish between core and secondary constraints during subsequent analysis. The essence of the reorganization is to sort the constraint association codes according to performance association priority and integrate the corresponding standard and source code information to generate a structurally clear and prioritized reorganized identifier. This ensures that subsequent analysis prioritizes core constraints such as seismic performance and structural stability, while also considering functional constraints such as thermal insulation and construction adaptability, perfectly aligning with the design and construction logic of prefabricated buildings that prioritizes safety while also considering functionality.

[0061] For example, the merged identifier fields can be constrained to obtain a set of constraint association codes. Then, the constraint association codes can be sorted and reorganized according to performance association priority to obtain a reorganized identifier. Alternatively, the merged identifier fields can be grouped according to the type attributes of building construction association parameters (component production, material performance, site environment, construction technology), so that the parameter constraints of the same stage are presented in a concentrated manner (e.g., component production identifier fields are grouped into one group, and material performance fields are grouped into another group). Then, constraint association codes are extracted from each group, duplicate codes are removed, and the constraint association codes of each group are integrated into a unified ordered sequence according to the rule of first-level priority (seismic resistance, structural stability) first and second-level priority (thermal insulation, construction adaptability) next. Finally, the standard code subset and source code subset corresponding to each group are supplemented, and the reorganized identifier is obtained by structural reorganization according to the first-level constraint association code sequence - second-level constraint association code sequence - type attribute grouping mark - standard code set - source code set - priority weight, etc., but not limited to these.

[0062] In one possible implementation, in step S310, the merged identifier field is reorganized according to performance association priority to obtain a reorganized identifier, including: S311, perform constraint identification on the merged identifier fields to obtain a set of constraint association codes.

[0063] It can be understood that constraint identification is the basic step of accurately extracting core constraint information from the merged identifier field. Its core is to use the standardized structure of the identifier field (such as type-specific prefix + source code - standard code - constraint association code - check code) to quickly locate and extract the constraint association code part, forming a set containing all parameter constraint information.

[0064] S312. Reorder and reorganize the merged identification fields according to the performance association priority based on the constraint association code set to obtain a reorganized identification.

[0065] It can be understood that the core of this step is to transform the unordered multi-source identification field set into a reorganized identification with clear priorities, regular structure, and complete information. Its essence is to globally sort all the merged identification fields and retain the complete core information (source code, standard code, constraint association code, check code) of each identification field. First, traverse each merged identification field, extract its constraint association code, and mark the corresponding priority level for each identification field according to the performance association priority rules (Level 1: earthquake resistance, structural stability; Level 2: thermal insulation, construction adaptability) (for example, the identification field containing JG-KZ-01 is marked as Level 1, and the one containing GN-BW-01 is marked as Level 2). Subsequently, sort all the identification fields in the order that Level 1 priority identification fields come first and Level 2 priority identification fields come second; within the same priority, further sort them in the secondary order of earthquake resistance performance constraint > structural stability constraint, thermal insulation constraint > construction adaptability constraint (for example, the identification field containing JG-KZ-01 is ranked before the identification field containing JG-WD-02); after sorting, reorganize and integrate them in the fixed structure of Level 1 identification field cluster - Level 2 identification field cluster - global standard code set - global source code set - priority weight: The Level 1 identification field cluster contains all the sorted Level 1 priority identification fields (retaining the original structure intact, such as GJ-HNT-...-JG-KZ-01-7A3F, GJ-GG-...-JG-WD-02-8B4D); the Level 2 identification field cluster contains all the sorted Level 2 priority identification fields (such as CL-GN-...-GN-BW-01-3D8B, GY-DZ-...-SP-SZ-01-9E5C); the global standard code set extracts the standard codes of all identification fields and removes duplicates (such as GB50011-2010, GB50009-2012, GB50176-2016); the global source code set extracts the source codes of all identification fields and removes duplicates (such as CS-粤-2025-018, CL-沪-2025-042); the priority weight is marked as Level 1 weight 0.7 + Level 2 weight 0.3, and finally a complete reorganized identification is formed (such as [GJ-HNT-...-JG-KZ-01-7A3F,GJ-GG-...-JG-WD-02-8B4D]-[CL-GN-...-GN-BW-01-3D8B, GY-DZ-...-SP-SZ-01-9E5C]-GB50011-2010, GB50009-2012, GB50176-2016-CS-粤-2025-018, CL-沪-2025-042-0.7,0.3).

[0066] This setup first uses constraint identification to accurately extract all constraint association codes from the merged identifier fields and form a deduplicated set, ensuring that no key constraints from multiple stages such as component production, material performance, and construction technology are missed, while reducing the use of parsing resources by duplicate constraints. Then, based on performance association priority (core safety constraints take precedence, functional adaptation constraints are secondary), the merged identifier fields are globally sorted and reorganized, so that the identifier fields corresponding to first-priority constraints such as seismic performance and structural stability are clustered and placed at the front, while the identifier fields corresponding to second-priority constraints such as thermal insulation and construction adaptability are placed in an orderly manner at the back, clarifying the primary and secondary logic of constraints. During the reorganization process, the core information such as the source code, standard code, and check code of each original identifier field are fully preserved, without severing the connection between parameters and manufacturers, national standards, and monitoring equipment, ensuring the traceability of parameters throughout the entire chain. The final reorganized identifier has a high degree of structure, and the constraint type can be directly extracted in cluster order during subsequent parsing without having to judge the priority one by one.

[0067] S320, the target performance constraint type is obtained by parsing the constraint field of the reorganization identifier.

[0068] For example, one can match a unique code to the constraint field of the recombined identifier, and then obtain the target performance constraint type based on the unique code; alternatively, one can first extract each standard code (such as GB50011-2010, GB50176-2016) from the global standard code set of the recombined identifier, and then directly convert the standard code into the corresponding constraint type (such as GB50011-2010 corresponding to seismic performance constraint, GB50176-2016 corresponding to thermal insulation constraint) through the preset mapping table of standard code-target performance constraint type of the building construction standard parameter framework; then extract the constraint association code sequence in the recombined identifier, and convert it into the constraint type according to the same framework mapping table, and so on, but not limited to these.

[0069] This setup first reorganizes the merged identifier fields according to performance-related priorities (core safety constraints first, functional adaptation constraints second), so that the identifier fields corresponding to key constraints such as seismic performance and structural stability are clustered and placed at the front, while auxiliary constraints such as thermal insulation and construction adaptability are placed in an orderly manner at the back. This not only firmly safeguards the bottom line of building structural safety, but also clarifies the primary and secondary logic of constraints. Then, based on the reorganized and structured constraint fields, parsing is performed. There is no need to process disordered information, and the target performance constraint type can be quickly extracted by focusing on the core constraints.

[0070] In one possible implementation, in step S320, the target performance constraint type is obtained by parsing the constraint field of the reorganization identifier, including: S321, Match the specific code based on the constraint field of the recombinant identifier.

[0071] It is understandable that the constraint field of the recombinant identifier is a sequence of constraint association codes ordered by priority (such as JG-KZ-01, JG-WD-02-GN-BW-01, SP-SZ-01). The building construction standard parameter framework has clearly defined the exclusive code corresponding to each type of constraint association code (such as JG-KZ-01 corresponding to exclusive code KZ-001, JG-WD-02 corresponding to WD-002, GN-BW-01 corresponding to BW-001, SP-SZ-01 corresponding to SZ-001). The exclusive code adopts the format of constraint type abbreviation + serial number. The matching process is performed one by one according to the sorting order of the constraint association codes in the recombinant identifier: first, the first-level priority association codes (JG-KZ-01→KZ-001, JG-WD-02→WD-002) are matched, and then the second-level priority association codes (GN-BW-01→BW-001, SP-SZ-01→SZ-001) are matched, forming an ordered exclusive coding sequence (such as [KZ-001, WD-002, BW-001, SZ-001]).

[0072] S322, the target performance constraint type is obtained based on dedicated coding.

[0073] It is understandable that the standard parameter framework for building construction predefines a fixed correspondence between exclusive codes and target performance constraint types (e.g., KZ-001 corresponds to seismic performance constraints, WD-002 to structural stability constraints, BW-001 to thermal insulation constraints, and SZ-001 to construction adaptability constraints). The conversion process is executed sequentially according to the order of the exclusive code sequence, forming a constraint type sequence with the same priority as the code sequence (e.g., [seismic performance constraints, structural stability constraints, thermal insulation constraints, construction adaptability constraints]). Subsequently, the constraint type sequence is integrated: duplicate types are eliminated (e.g., only one is retained when multiple associated codes map to the same constraint type), and conflicting types are coordinated (following the principle that first-priority constraints take precedence over second-priority constraints; for example, when seismic performance constraints and construction adaptability constraints conflict, seismic performance constraints are retained first, and the adaptability boundaries of construction adaptability constraints are marked), ultimately forming a set of target performance constraint types. For example, if the exclusive coding sequence is [KZ-001, WD-002, BW-001], then the integrated constraint type set is {seismic performance constraint, structural stability constraint, thermal insulation constraint}; if there are conflicting KZ-001 and SZ-001 in the sequence, then it is integrated into {seismic performance constraint (core), structural stability constraint, thermal insulation constraint, construction adaptability constraint (adaptability boundary: optimization under the premise of meeting seismic requirements)}.

[0074] This setup uses dedicated codes as a standardized intermediary between constraint fields and target performance constraint types. Through the pre-defined mapping relationship of the building construction standard parameter framework, it achieves unambiguous conversion of constraint information, reducing potential type misjudgments that may occur when directly parsing constraint fields (such as confusion of similar constraint association codes). Relying on standardized mapping logic, the parsing process can be automated, significantly reducing time costs and human error. The parsing process follows the priority order of recombinant identifiers, ensuring that core constraint types such as seismic performance and structural stability are prioritized, while auxiliary constraint types such as thermal insulation and construction adaptability are prioritized in an orderly manner. This ensures that the target performance constraint types retain a clear primary and secondary logic while comprehensively covering the needs of multiple stages. At the same time, the design of dedicated codes has strong scalability. When a new constraint type (such as green building evaluation constraint) is added, it can be quickly adapted simply by supplementing the mapping relationship between constraint field-dedicated code-constraint type. This perfectly matches the iterative needs of prefabricated building technology, providing accurate, consistent, and efficient directional guidance for subsequent multi-constraint collaborative optimization, and improving the standardization and reliability of the entire parameter optimization process.

[0075] S400 identifies the target performance constraint type, performs collaborative optimization on the core performance parameters of each type, generates the optimal construction parameters adapted to construction, and generates adaptation metadata synchronized with the optimal construction parameters by restoring the adaptation boundary conditions of the optimal construction parameters. The adaptation metadata includes parameter adjustment criteria, performance verification indicators, and construction fault tolerance range.

[0076] It is understandable that the essence of this step is a closed-loop process of precise multi-constraint adaptation, global parameter optimization, and construction implementation assurance, which aligns with the core characteristics of standardized prefabrication in prefabricated factories and flexible on-site assembly in prefabricated buildings. Its core logic is to first prioritize the target performance constraint types (core safety constraints first, functional adaptation constraints second), and then perform targeted collaborative optimization of core performance parameters to reduce the disadvantages caused by optimizing a single constraint (such as pursuing structural safety while ignoring construction feasibility). Next, by restoring and adapting the boundary conditions, the theoretically optimal construction parameters are transformed into a practical, executable, and adjustable solution for the field. Finally, the adaptation metadata clarifies how to adjust, how to verify, and what the tolerances are, ensuring that the optimization results do not deviate from the actual construction scenario.

[0077] For example, when the target performance constraint type is identified as seismic performance constraint and structural stability constraint, the key structural indicators in the core performance parameters are obtained, and the key structural indicators are collaboratively optimized according to the structural constraint standard to generate the optimal construction parameters that meet the structural safety requirements. When the target performance constraint type is identified as thermal insulation constraint and construction adaptability constraint, the adaptation boundary identifier used to indicate the parameter adaptation boundary is obtained, and the adaptation boundary conditions of the optimal construction parameters are restored based on the adaptation boundary identifier and the compliance range of the core performance parameters to generate adaptation metadata synchronized with the optimal construction parameters.

[0078] Alternatively, one can first identify the complete set of target performance constraint types (which may simultaneously include primary priority seismic / structural stability constraints and secondary priority insulation / construction compatibility constraints), establish a multi-objective optimization model, and take maximizing structural safety factor, minimizing building energy consumption, and optimizing construction efficiency as collaborative objectives. Core performance parameters (key structural indicators, insulation material indicators, process parameters, etc.) are used as optimization variables, and corresponding national standards (GB 50011, GB 50176, GB / T51231) are used as hard constraints. Through multi-objective optimization algorithms such as NSGA-Ⅲ, preliminary optimal structural parameters that take into account multiple constraints are generated (e.g., precast beams using C45 concrete + seismic bolt joints + composite insulation layer, hoisting speed 0.5m / s). Then, the adaptation requirements are split into two stages: factory prefabrication and on-site assembly, and the adaptation boundary conditions are restored in stages: the factory prefabrication stage focuses on production accuracy adaptation boundaries (e.g., matching component dimensional tolerances with production line accuracy, and material compatibility with prefabrication processes); the on-site assembly stage focuses on the cyclic... The environmental-space-process adaptation boundary (such as the influence of temperature and humidity on the strength of grouting material, hoisting path and avoidance of on-site obstacles); finally, adaptation metadata is generated for the two stages respectively. The metadata of the factory stage clarifies the allowable range of production error of precast components and the prohibition of material matching. The metadata of the on-site stage clarifies the parameter adjustment plan when the environment fluctuates and the fault tolerance range of construction operation. At the same time, the stage connection verification is used to ensure that the precast components in the factory and the on-site assembly process are seamlessly adapted (such as the position of the reserved hole of the precast component and the operating space of the on-site grouting equipment), etc., but not limited to this.

[0079] In one possible implementation, in step S400, by identifying the target performance constraint type, collaborative optimization is performed on the core performance parameters of each type to generate optimal construction parameters suitable for construction. Furthermore, by restoring the adaptation boundary conditions of the optimal construction parameters, adaptation metadata synchronized with the optimal construction parameters is generated, including: S410, when the target performance constraint type is identified as seismic performance constraint and structural stability constraint, obtain the key structural indicators in the core performance parameters; among them, the key structural indicators include the compressive strength of components, the stiffness of node connections, and the dimensional tolerance range.

[0080] It's understandable that when the objective constraints focus on seismic resistance and structural stability, the core logic for extracting key structural indicators is to prioritize major aspects and focus on the core weaknesses in the structural safety of prefabricated buildings. These indicators directly determine the building's load-bearing capacity and overall stability under external forces such as earthquakes and wind loads, and are non-negotiable primary constraint indicators. The compressive strength of components is the fundamental guarantee of the bearing capacity of prefabricated components, directly determining whether the component can withstand the stress under vertical loads and seismic action. Its extraction can differentiate between component type (beams, columns, wall panels) and material (concrete, steel structure): for prefabricated concrete components, the standard value of cubic compressive strength is extracted (e.g., 30MPa for C40), with data sources including factory test reports and on-site test block verification; for steel structure components, the yield strength is extracted (e.g., 355MPa for Q355 steel), which can be linked to the steel quality certificate. Node connection stiffness is crucial for structural force transmission in prefabricated buildings. Nodes (such as bolted connections and post-cast concrete joints) are weak points in force transmission; insufficient stiffness can lead to excessive structural deformation and decreased seismic performance. Extracted indicators include the node anti-slip coefficient (≥0.45 for friction-type high-strength bolted nodes) and the bond strength of post-cast concrete (≥3.0MPa). Data can be obtained from node-specific testing reports. Dimensional tolerance range ensures assembly accuracy and structural integrity. Excessive dimensional deviations in precast components can lead to uneven splicing gaps and unbalanced force transmission at nodes, thus affecting structural stability. Extracted indicators must comply with the "Standard for Acceptance of Quality of Precast Concrete Components" GB / T 50204, such as a precast beam length tolerance of ±3mm and a wall panel thickness tolerance of ±2mm. Data can be obtained from factory inspection and on-site measurements.

[0081] S420 performs collaborative optimization on key structural indicators based on structural constraint standards to generate optimal construction parameters that meet structural safety requirements.

[0082] It is understandable that the core of this step is multi-index balance optimization, rather than maximizing a single index. Essentially, it generates optimal structural parameters that are safe, feasible to construct, and economically reasonable by coordinating the inherent contradictions among key structural indicators, based on structural constraint standards (such as GB 50011, GB 50010, and GB / T 51231). For example, a multi-objective optimization model can be established: with the objective functions of maximizing the structural safety factor, minimizing the component self-weight, and minimizing construction difficulty; with key structural indicators (component compressive strength, node connection stiffness, and dimensional tolerances) as optimization variables; and with structural constraint standards as hard constraints. For example, the compressive strength of structural members must meet the bearing capacity requirements under a seismic fortification intensity of 8 degrees (GB 50011-2010, Clause 5.4.1), the stiffness of joint connections must ensure that the inter-story displacement is ≤H / 500 (H is the building height), and the dimensional tolerances must comply with the ±3mm limit of GB / T 50204. Then, the NSGA-Ⅲ multi-objective optimization algorithm can be used to generate a Pareto optimal solution set through iterative calculation. Finally, the optimal structural parameters are selected by combining the actual engineering conditions (such as material supply and equipment capacity). For example, the final optimization result is: precast beam: C45 concrete, cross-section 550×250mm, length tolerance ±3mm; joint: M24 high-strength bolts, spacing 120mm, anti-slip coefficient ≥0.48.

[0083] S430, when the target performance constraint type is identified as thermal insulation constraint and construction adaptability constraint, obtain the adaptation boundary identifier used to indicate the parameter adaptation boundary.

[0084] It is understandable that the core characteristics of thermal insulation and construction adaptability constraints are their strong dynamic nature and high correlation with site conditions. Thermal insulation performance is affected by ambient temperature and humidity, while construction adaptability depends on site space and equipment conditions. Therefore, it is necessary to clarify the applicable scope of parameters through adaptability boundary markers to avoid theoretically optimized parameters deviating from actual scenarios. Adaptability boundary markers are a set of pre-defined boundary information strongly correlated with core performance parameters. In essence, they are a standardized description of the applicable conditions of the parameters, derived from the standard parameter framework of building construction, construction plans, and industry specifications. For example, regarding thermal insulation constraints, environmental boundary markers related to the performance of thermal insulation materials are extracted (such as the environmental temperature and humidity threshold of 5℃-35℃, outside which the thermal conductivity of the insulation material will change significantly), and material compatibility markers (such as prohibiting the use of highly corrosive sealants to avoid material reactions that lead to a decrease in thermal insulation performance). Regarding construction adaptability constraints, physical boundary markers related to on-site construction are extracted (such as the minimum operating space of 800mm and the hoisting path avoidance range of 1.5m), equipment capacity markers (such as the tower crane's rated load of 10t), and process adaptability markers (such as the grouting material's fluidity adaptability range of 180mm-220mm).

[0085] S440 recovers the adaptation boundary conditions of the optimal construction parameters based on the adaptation boundary identifier and the compliance range of the core performance parameters, so as to generate adaptation metadata synchronized with the optimal construction parameters.

[0086] It is understandable that the core of this step is the practical transformation of theoretical parameters. Essentially, it involves performing an intersection operation between the adaptation boundary identifier (on-site dynamic conditions) and the compliance range of core performance parameters (theoretical requirements) to clarify the actual applicable boundary of the optimal construction parameters, and then transforming the boundary conditions into adaptation metadata that can be directly used by construction personnel.

[0087] For example, the environmental adaptation boundary of the optimal structural parameters can be determined based on the environmental temperature and humidity thresholds in the adaptation boundary identifiers, combined with the compliance ranges of material strength and component connection reliability in the core performance parameters. Simultaneously, the physical adaptation boundary is restored based on the construction space limitations in the adaptation boundary identifiers. Material adaptation boundaries are established by combining the material compatibility requirements in the adaptation boundary identifiers with the compliance standards of material thermal conductivity and durability in the core performance parameters. Then, adaptation metadata synchronized with the optimal structural parameters is generated based on the environmental adaptation boundary, physical adaptation boundary, and material compatibility requirements. Alternatively, the scattered adaptation boundary identifiers (environmental temperature and humidity thresholds, construction space limitations, material compatibility requirements, etc.) can be integrated into a unified boundary identifier set according to construction impact weights. Duplicate and conflicting boundary information is eliminated (e.g., when construction space limitation values ​​from different sources are inconsistent, the stringent data from actual on-site surveys takes precedence), and construction impact weights are labeled for each boundary item (e.g., environmental temperature and humidity weight 0.4, construction space weight 0.35, material compatibility weight 0.25), clearly defining the core and secondary impact boundaries. Next, the integrated boundary identifier set and the compliance range of core performance parameters are subjected to full-dimensional threshold verification. A correlation matrix of boundary item-performance index-compliance threshold is established to clarify the dynamic adjustment rules of the corresponding core performance parameter compliance range when each boundary item changes (e.g., when the construction space shrinks to the lower limit of the threshold, the compliance range of component splicing gap needs to be narrowed synchronously). The performance compliance of the optimal construction parameters under each boundary scenario is verified through this matrix, and parameter combinations that cannot meet the core performance compliance requirements under boundary conditions are eliminated to lock the effective adaptation boundary range of the optimal construction parameters. Finally, content is generated layer by layer according to the three core modules of the adaptation metadata. First, differentiated parameter adjustment criteria are formulated based on the correlation matrix (differentiating different solutions for a single boundary item exceeding the threshold and multiple boundary items exceeding the threshold simultaneously). Then, the performance verification indicators under each scenario are clarified according to the adjustment criteria (always consistent with the basic compliance range of the core performance parameters to ensure that the performance is not reduced). Finally, combined with the practical accuracy and equipment capabilities of on-site construction, a reasonable construction error tolerance range is set for each boundary item and performance index, etc., but not limited to this.

[0088] This approach, by implementing differentiated parameter processing strategies for different target performance constraint types, precisely addresses the core pain points of safety and function imbalance and the disconnect between theoretical parameters and on-site construction in the multi-constraint collaborative optimization of prefabricated buildings. The categorized differentiated processing logic aligns with the design and construction principles of prefabricated buildings, prioritizing core safety and supplementing with functional adaptation. It eliminates the need for indiscriminate optimization of all parameters, significantly improving the accuracy and efficiency of parameter optimization. Furthermore, the optimal structural parameters and adaptation metadata are generated simultaneously, achieving the dual effect of precise optimization of structural safety parameters and clear and explicit construction implementation guidance. It adapts to the full-process characteristics of prefabricated buildings, from factory prefabrication to on-site assembly, effectively improving construction execution efficiency and quality control levels. This provides practical technical support for the standardized and efficient optimization of structural parameters in prefabricated buildings.

[0089] In one possible implementation, the adaptation boundary identifier includes environmental temperature and humidity thresholds, construction space limitations, and material compatibility requirements. In step S440, the adaptation boundary conditions of the optimal construction parameters are restored based on the adaptation boundary identifier and the compliance range of the core performance parameters to generate adaptation metadata synchronized with the optimal construction parameters, including: S441, based on the environmental temperature and humidity thresholds in the adaptation boundary identifier, and combined with the compliance ranges of material strength and component connection reliability in the core performance parameters, determine the environmental adaptation boundary of the optimal construction parameters.

[0090] It is understandable that ambient temperature and humidity are key dynamic factors affecting the construction quality and material performance of prefabricated buildings. Low temperatures will slow down the strength development of concrete and grout, while high humidity will reduce the reliability of component connections (such as bolt corrosion and reduced bond strength). Therefore, the core of environmental adaptability boundary is to clarify the matching relationship between temperature and humidity and the core performance parameters so that the optimal structural parameters can still meet the requirements under specific environmental conditions. By combining core performance parameters, a joint model of temperature and humidity-performance is established. For example, when the ambient temperature is 5℃-35℃ and the relative humidity is 40%-70%, the 7-day compressive strength of the grout can stably reach 35MPa-45MPa (covering the acceptable range), and the component connection reliability is ≥0.92. When the temperature is below 5℃, the strength development rate of the grout decreases by 50%, and the 7-day compressive strength is only 25MPa (below the lower limit of the acceptable range). When the relative humidity is above 80%, the risk of bolt corrosion increases, and the connection reliability drops to 0.85 (below the lower limit of the acceptable range). Based on this model, the environmental adaptation boundary is determined: ambient temperature 5℃-35℃ and relative humidity 40%-70%, and the performance degradation law outside the boundary is clarified. Based on this, the core content of the adapted metadata is as follows: When the temperature is below 5℃, heat preservation and curing measures (such as covering with heat preservation blankets) are adopted, and the curing time is extended by 50%; when the relative humidity is above 80%, anti-corrosion treatment is carried out on the bolts (such as applying anti-rust grease); the performance verification indicators are that the 7-day compressive strength of the grouting material after curing is ≥35MPa, and the reliability of the bolt connection is ≥0.9; the construction tolerance range is that the temperature is allowed to fluctuate by ±2℃ and the humidity is allowed to fluctuate by ±5%RH.

[0091] S442, based on the construction space limitations in the adaptation boundary identifier, restore the physical adaptation boundary, wherein the physical adaptation boundary includes the minimum operating space for component installation and the operable range for node connection.

[0092] It is understandable that construction space constraints are a physical prerequisite for on-site assembly of prefabricated buildings. Insufficient space will prevent components from being positioned and node connections from being made operational. Therefore, the core of the physical adaptation boundary is to transform abstract spatial constraints into specific, measurable physical ranges so that the geometric dimensions of the optimal structural parameters and installation methods can be adapted to the on-site space conditions. The construction space constraints extracted from the adaptation boundary markers (derived from on-site survey data and construction plans) include: for example, a clear height of ≥3.5m in the component installation area and a width of ≥0.8m for the node connection operation surface. Subsequently, based on the compliance range of core performance parameters (such as the compliance range of component size "precast wall panel width 600mm-1200mm, node bolt spacing 100mm-150mm"), the physical adaptation boundaries are restored: Minimum operating space for component installation: refers to the minimum space required for workers to install and adjust components, which is determined by combining the component size and the space requirements of operating tools (such as wrenches, grouting guns). For example, if the width of the precast wall panel is 1000mm, the operating tools need to occupy 300mm of space, so the minimum operating space is ≥300mm on each side of the wall panel and ≥500mm in front; Operable area for node connection: refers to the effective space for workers to perform node bolt tightening, grouting, and other operations, which is determined by combining the node structure and operation method (such as manual tightening requiring ≥200mm operating depth). For example, for M24 bolt nodes, wrench operation requires ≥250mm depth and ≥150mm width, so the operable area is node operating surface depth ≥250mm and width ≥150mm.

[0093] S443, combining the material compatibility requirements in the adaptation boundary identifier, and comparing them with the compliance standards of material thermal conductivity and durability in the core performance parameters, establishes the material adaptation boundary; wherein, the material adaptation boundary is used to indicate and specify the prohibited combinations of different material combinations and the recommended adaptation ratio.

[0094] It is understandable that material compatibility is the core guarantee for the long-term functionality of prefabricated buildings. If there are compatibility issues between different materials such as insulation materials and sealants, grouting materials and concrete, and anti-corrosion coatings and steel, it will lead to the degradation of material performance (such as increased thermal conductivity and decreased bonding strength) and reduced durability (such as accelerated corrosion and aging), ultimately affecting the insulation effect and structural life. Therefore, the core of material compatibility boundary is to clarify what is permissible and impermissible in material combination, so that the material selection in the optimal structural parameters can meet functional requirements and have long-term stability. First, two core inputs are identified: one is the material compatibility requirements in the compatibility boundary marking (derived from compatibility reports provided by material suppliers and national standards such as GB 50176 and GB / T14683, for example, extruded polystyrene boards are prohibited from being used with solvent-based sealants, and grouting materials must match the strength grade of concrete); the other is the compliance standards for core performance parameters (such as thermal conductivity ≤0.040W / (m・K), durability grade ≥D150); then, material compatibility boundaries are established, focusing on clarifying three types of core information: prohibited combinations: referring to material combinations that will lead to significant performance degradation, verified through compatibility test data. For example, when extruded polystyrene board is used with solvent-based sealant, the solvent in the sealant will corrode the insulation material, causing the thermal conductivity to increase from 0.028 W / (m·K) to 0.050 W / (m·K) (exceeding the standard), so this combination is prohibited. When the strength grade of the grout is lower than that of the concrete (such as C30 grout used with C40 concrete), it will lead to insufficient joint bonding strength and reduced durability, so this combination is also prohibited. Recommended matching ratio: refers to the optimal ratio of material combinations to achieve optimal synergy. For example, the matching ratio of insulation material (extruded polystyrene board) to sealant is 100:5 (5L of compatible sealant per 100㎡ of insulation board), which can ensure the sealing effect and reduce material waste. The matching ratio of grout to admixture is 100:2.5, which can improve the fluidity (meeting construction requirements) without reducing the compressive strength (standard ≥35MPa).

[0095] S444 generates adaptation metadata synchronized with the optimal construction parameters based on environmental adaptation boundaries, physical adaptation boundaries, and material compatibility requirements.

[0096] Understandably, the core of this step is multi-boundary integration and practical transformation. Essentially, it involves systematically integrating the core requirements of the three adaptation boundaries—environment, physics, and materials—into three modules of adaptation metadata: parameter adjustment criteria, performance verification indicators, and construction tolerance range. This forms a complete set of data that can directly guide construction. First, the requirements of the three boundaries are cross-validated to eliminate contradictions (e.g., the environmental adaptation boundary requirement of "insulation is required at low temperatures" and the material adaptation boundary requirement of "insulation materials should avoid high temperatures" are not conflicting and can be directly integrated). Second, the adjustment criteria are integrated according to priority (adjustments related to core safety come first, followed by those related to functional optimization, such as "insulation measures for temperatures below 5℃" taking precedence over "adjustment of material adaptation ratios"). Finally, the abstract boundary requirements are transformed into specific, quantifiable practical indicators (e.g., "minimum operating space ≥ 800mm" is transformed into "adjusting component width when construction space is insufficient").

[0097] The specific generation logic of the three modules for adapting metadata is as follows: Parameter Adjustment Criteria: Integrating solutions for the three major boundaries, clarifying under what conditions adjustments are made, what to adjust, and how to adjust. For example, the environmental adaptation boundary "temperature below 5℃" corresponds to "thermal insulation and curing + extending curing time by 50%"; the physical adaptation boundary "construction space less than 800mm" corresponds to "adjusting component width from 1000mm to 800mm"; the material adaptation boundary "no recommended sealant" corresponds to "replacing with water-based sealant." All adjustment measures have clearly defined operation steps and parameters. Performance Verification Indicators: Integrating acceptance standards for the three major boundaries, clarifying how to verify after adjustment, what to verify, and what the pass / fail standards are. For example, after environmental adjustment... Verify that "the 7-day compressive strength of the grouting material is ≥35MPa"; verify that "the component positioning deviation is ≤5mm" after physical adjustment; verify that "the thermal conductivity is ≤0.028W / (m・K)" after material adjustment. All verification indicators correspond to national standards or optimization targets. Construction tolerance range: Integrate the allowable fluctuation range of the three major boundaries, clarify how much the parameters can fluctuate and whether adjustments are needed after fluctuation. For example, the ambient temperature and humidity are allowed to fluctuate by ±2℃ and ±5%RH, the physical space is allowed to fluctuate by ±100mm, and the material ratio is allowed to fluctuate by ±0.5%. No adjustment is needed if the fluctuation is within the range, and the corresponding adjustment criteria are implemented if it exceeds the range. This not only reserves flexible space for construction, but also reduces the performance failure caused by excessive fluctuation. The final generated adaptation metadata corresponds one-to-one with the optimal construction parameters. For example, the optimal construction parameters are: precast wall panel: extruded polystyrene board (thermal conductivity 0.028W / (m・K)), width 1000mm; nodes: C40 grouting material, M24 bolts. The corresponding adaptation metadata includes low-temperature insulation measures, width adjustment when space is insufficient, and sealant replacement requirements.

[0098] This setup ensures that the three adaptation boundaries comprehensively cover the core variables of on-site construction. Combined with the core performance parameter compliance standards, it forms a scientific and complete adaptation system. The generated adaptation metadata is more targeted and practical, providing construction personnel with clear guidance on parameter adjustment, performance verification, and tolerance range. At the same time, it strictly conforms to national industry standards and specifications, which not only improves the accuracy and reliability of the adaptation boundary determination, but also further strengthens the on-site implementation of the optimal structural parameters, reduces construction errors and quality risks, and adapts to the entire process requirements of prefabrication in prefabricated buildings and on-site assembly. It provides comprehensive boundary support for the refined and efficient implementation of building structural parameter optimization schemes.

[0099] In one possible implementation, the method further includes: S500 performs performance simulation verification on the optimal construction parameters to obtain the performance simulation verification results; among them, the performance simulation verification adopts the finite element analysis model of the building structure and the dynamic simulation model of the construction process.

[0100] The core objective is to use simulation models to perform full-scenario, high-precision verification of the optimal structural parameters generated through collaborative optimization from both static structural safety and dynamic construction operation dimensions. This reduces the problem of parameters being feasible on paper but unusable in practice due to relying solely on theoretical calculations, thus laying a solid foundation for parameter reliability in subsequent metadata generation. The finite element analysis model of the building structure focuses on core safety constraints such as seismic performance and structural stability. By simulating the structural response of the building under conditions such as seismic loads, wind loads, and dead and live loads, it calculates key indicators such as component stress, node deformation, and inter-story displacement, verifying whether the optimal structural parameters meet the mandatory requirements of national structural standards and specifications. The dynamic simulation model of the construction process recreates the entire on-site construction process of prefabricated buildings, including key procedures such as component hoisting, splicing, node grouting, and curing. Through three-dimensional dynamic simulation, it verifies the adaptability of the optimal structural parameters in actual construction, such as whether there are collisions in the component hoisting path, whether the installation operation space is sufficient, and whether the grouting process matches the component size. The two models work together to achieve dual verification of the structural safety feasibility and construction execution feasibility of the optimal structural parameters.

[0101] S600, when the performance simulation verification result of the optimal construction parameters is qualified, restores the adaptation boundary conditions of the optimal construction parameters based on the adaptation boundary identifier and the compliance range of the core performance parameters, so as to generate adaptation metadata synchronized with the optimal construction parameters.

[0102] It is understandable that when the performance simulation verification result of the optimal construction parameters is unqualified, the specific deviation data fed back by the performance simulation verification can be used to iterate back to the collaborative optimization stage of the core performance parameters, make targeted adjustments to the key structural indicators or adaptation-related parameters, and regenerate new optimal construction parameters. The newly generated optimal construction parameters are then sent back to S500 to perform performance simulation verification, forming a closed-loop correction logic of parameter optimization-simulation verification-iterative adjustment, until the performance simulation verification result of the optimal construction parameters reaches the qualified standard, and then the related operations of adaptation boundary condition recovery and adaptation metadata generation are initiated.

[0103] This setup generates adaptive metadata based on verified optimal structural parameters, ensuring the reliability and operability of the metadata from the source. It further enhances the on-site implementation of optimal structural parameters, improves the rigor, scientificity, and controllability of the entire building structural parameter optimization process, and adapts to the full-process characteristics of prefabricated buildings in factories and assembled on-site.

[0104] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of this application.

[0105] Corresponding to the building structural parameter optimization method described in the above embodiments, this application also provides a building structural parameter optimization system, the various modules of which can implement the various steps of the building structural parameter optimization method. Figure 3 The diagram shows a structural block diagram of the building construction parameter optimization system provided in the embodiments of this application. For ease of explanation, only the parts related to the embodiments of this application are shown.

[0106] Reference Figure 3 The building structural parameter optimization system includes: The first acquisition module is used to acquire building structure-related parameters, including component production parameters, material performance parameters, site environment parameters, and construction process parameters.

[0107] The classification module is used to perform standardized parsing and classification of building structure-related parameters based on the standard parameter framework for building construction, and to obtain the identification fields and core performance parameters of each building structure-related parameter.

[0108] The second acquisition module is used to merge the various identifier fields to obtain the target performance constraint type corresponding to the recombined identifier; among which, the target performance constraint type includes seismic performance constraint, thermal insulation constraint, structural stability constraint and construction adaptability constraint.

[0109] The optimization module is used to identify the target performance constraint type, perform collaborative optimization on the core performance parameters of each type, generate the optimal construction parameters adapted to the construction, and generate adaptation metadata synchronized with the optimal construction parameters by restoring the adaptation boundary conditions of the optimal construction parameters. The adaptation metadata includes parameter adjustment criteria, performance verification indicators and construction fault tolerance range.

[0110] It should be noted that the information interaction and execution process between the above modules are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, which will not be repeated here.

[0111] Those skilled in the art will understand that, for the sake of convenience and brevity, the above-described module division is merely an example. In practical applications, the above functions can be assigned to different modules as needed, that is, the internal structure of the system can be divided into different modules to complete all or part of the functions described above. The modules in the embodiments can be integrated into one processing unit, or each module can exist physically separately, or two or more modules can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0112] This application also provides an electronic device. Figure 4 This is a schematic diagram of the structure of an electronic device 6 provided in an embodiment of this application. Figure 4 As shown, the electronic device 6 of this embodiment includes: at least one processor 60 ( Figure 4 Only one is shown in the image), at least one memory 61 ( Figure 4 (Only one is shown in the image) and a computer program 62 stored in the at least one memory 61 and executable on the at least one processor 60, wherein when the processor 60 executes the computer program 62, it causes the electronic device 6 to perform the steps in any of the above-described building construction parameter optimization method embodiments, or causes the electronic device 6 to perform the functions of each module in the above-described system embodiments.

[0113] For example, the computer program 62 may be divided into one or more modules / units, which are stored in the memory 61 and executed by the processor 60 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 62 in the electronic device 6.

[0114] The electronic device 6 can be a desktop computer, laptop, handheld computer, cloud server, or other computing device. The electronic device 6 may include, but is not limited to, a processor 60 and a memory 61. Those skilled in the art will understand that... Figure 4 This is merely an example of electronic device 6 and does not constitute a limitation on electronic device 6. It may include more or fewer components than shown, or combine certain components, or different components, such as input / output devices, network access devices, buses, etc.

[0115] The processor 60 can be a Central Processing Unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0116] In some embodiments, the memory 61 may be an internal storage unit of the electronic device 6, such as a hard disk or memory of the electronic device 6. In other embodiments, the memory 61 may be an external storage device of the electronic device 6, such as a plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, etc., equipped on the electronic device 6. Furthermore, the memory 61 may include both internal and external storage units of the electronic device 6. The memory 61 is used to store the operating system, applications, bootloader, data, and other programs, such as the program code of the computer program. The memory 61 can also be used to temporarily store data that has been output or will be output.

[0117] This application also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0118] This application provides a computer program product that, when run on an electronic device 6, causes the electronic device 6 to perform the steps in any of the above-described method embodiments.

[0119] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to an electronic device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0120] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0121] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0122] In the embodiments provided in this application, it should be understood that the disclosed electronic devices and systems can be implemented in other ways. For example, the building structure parameter optimization system embodiments described above are merely illustrative. For instance, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or modules, and may be electrical, mechanical, or other forms.

[0123] The modules described as separate components may or may not be physically separate. The components shown as modules may or may not be physical modules; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0124] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method for optimizing building structural parameters, characterized in that, include: Obtain building structure-related parameters; wherein, the building structure-related parameters include component production parameters, material performance parameters, site environment parameters, and construction process parameters; Based on the standard parameter framework for building construction, the associated parameters of the building construction are standardized and classified to obtain the identification fields and core performance parameters of each associated parameter of the building construction. The identification fields are merged to obtain the target performance constraint type corresponding to the recombined identification; wherein, the target performance constraint type includes seismic performance constraint, thermal insulation constraint, structural stability constraint and construction adaptability constraint; By identifying the target performance constraint type, collaborative optimization is performed on the core performance parameters of each type to generate optimal construction parameters suitable for construction. By restoring the adaptation boundary conditions of the optimal construction parameters, adaptation metadata synchronized with the optimal construction parameters is generated. The adaptation metadata includes parameter adjustment criteria, performance verification indicators, and construction fault tolerance range.

2. The method for optimizing building structural parameters as described in claim 1, characterized in that, The standardized parsing and classification of the building structure-related parameters based on the building structure standard parameter framework yields the identifier fields and core performance parameters of each building structure-related parameter, including: Feature keywords are obtained by extracting features from the associated parameters of each of the building structures. The feature keywords are compared with the classification dimensions of the building construction standard parameter framework to determine the type attributes of each building construction related parameter; Based on the type attribute, extract the corresponding identification field and core performance parameters of the building structure association parameters.

3. The method for optimizing building structural parameters as described in claim 2, characterized in that, The step of extracting the identifier field and core performance parameters of the building structure association parameters based on the type attribute includes: Based on the type attribute, extract the core elements of the corresponding building structure association parameters. Based on the core elements of the aforementioned fields, the identification field is obtained; Based on the performance parameter requirements corresponding to the type attributes, the core performance indicators of the corresponding building structure-related parameters are extracted, and the core performance indicators are quantitatively constrained to obtain the core performance parameters.

4. The method for optimizing building structural parameters as described in claim 1, characterized in that, The merging of the various identifier fields to obtain the target performance constraint type corresponding to the recombined identifier includes: The merged identifier fields are reorganized according to performance-related priorities to obtain the reorganized identifier; The target performance constraint type is obtained by parsing the constraint field of the reorganization identifier.

5. The method for optimizing building structural parameters as described in claim 4, characterized in that, The step of recombining the merged identifier fields according to performance-related priorities to obtain a recombined identifier includes: Constraint identification is performed on the merged identifier fields to obtain a set of constraint association codes; Based on the constraint association code set, the merged identifier fields are sorted and reorganized according to performance association priority to obtain the reorganized identifier.

6. The method for optimizing building structural parameters as described in claim 4, characterized in that, The step of parsing the constraint field of the reorganization identifier to obtain the target performance constraint type includes: Match the unique code according to the constraint field of the recombinant identifier; The target performance constraint type is obtained based on the proprietary encoding.

7. The method for optimizing building structural parameters as described in claim 1, characterized in that, The process involves identifying the target performance constraint type, performing collaborative optimization on the core performance parameters for each type to generate optimal construction parameters for adaptation, and generating adaptation metadata synchronized with the optimal construction parameters by restoring the adaptation boundary conditions of the optimal construction parameters. This includes: When the target performance constraint type is identified as the seismic performance constraint and the structural stability constraint, the key structural indicators in the core performance parameters are obtained; wherein, the key structural indicators include the compressive strength of the components, the stiffness of the node connections, and the dimensional tolerance range; Based on structural constraint standards, the key structural indicators are collaboratively optimized to generate optimal construction parameters that meet structural safety requirements. When the target performance constraint type is identified as the thermal insulation constraint and the construction adaptability constraint, an adaptation boundary identifier is obtained to indicate the parameter adaptation boundary. Based on the adaptation boundary identifier and the compliance range of the core performance parameters, the adaptation boundary conditions of the optimal construction parameters are restored to generate adaptation metadata synchronized with the optimal construction parameters.

8. The method for optimizing building structural parameters as described in claim 7, characterized in that, The method further includes: The optimal construction parameters are subjected to performance simulation verification to obtain performance simulation verification results; wherein, the performance simulation verification adopts a finite element analysis model of building structure and a dynamic simulation model of construction process. When the performance simulation verification result of the optimal construction parameters is qualified, the adaptation boundary conditions of the optimal construction parameters are restored based on the adaptation boundary identifier and the compliance range of the core performance parameters, so as to generate adaptation metadata synchronized with the optimal construction parameters.

9. The method for optimizing building structural parameters as described in claim 7, characterized in that, The adaptation boundary identifier includes environmental temperature and humidity thresholds, construction space limitations, and material compatibility requirements. The adaptation boundary conditions for restoring the optimal construction parameters based on the adaptation boundary identifier and the compliance range of the core performance parameters are used to generate adaptation metadata synchronized with the optimal construction parameters, including: Based on the environmental temperature and humidity thresholds in the adaptation boundary identifier, and combined with the compliance ranges of material strength and component connection reliability in the core performance parameters, the environmental adaptation boundary of the optimal construction parameters is determined. Based on the construction space constraints in the adaptation boundary identifier, the physical adaptation boundary is restored, wherein the physical adaptation boundary includes the minimum operating space for component installation and the operable range for node connection; Based on the material compatibility requirements in the adaptation boundary identifier, and in accordance with the compliance standards for material thermal conductivity and durability in the core performance parameters, a material adaptation boundary is established; wherein, the material adaptation boundary is used to indicate and specify prohibited combinations of different materials and recommended adaptation ratios; Based on the environmental adaptation boundary, the physical adaptation boundary, and the material compatibility requirements, adaptation metadata synchronized with the optimal construction parameters is generated.

10. A building structural parameter optimization system, characterized in that, include: The first acquisition module is used to acquire building structure related parameters; wherein, the building structure related parameters include component production parameters, material performance parameters, site environment parameters, and construction process parameters; The classification module is used to perform standardized parsing and classification of the building structure-related parameters based on the building structure standard parameter framework, so as to obtain the identification field and core performance parameters of each building structure-related parameter; The second acquisition module is used to merge the identification fields to obtain the target performance constraint type corresponding to the recombined identification; wherein, the target performance constraint type includes seismic performance constraint, thermal insulation constraint, structural stability constraint and construction adaptability constraint; The optimization module is used to identify the target performance constraint type, perform collaborative optimization on the core performance parameters of each type, generate optimal construction parameters adapted to construction, and generate adaptation metadata synchronized with the optimal construction parameters by restoring the adaptation boundary conditions of the optimal construction parameters; wherein, the adaptation metadata includes parameter adjustment criteria, performance verification indicators and construction fault tolerance range.

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