Fabricated shoreline component design optimization system

Abstract

The invention belongs to the technical field of assembly type shoreline component design optimization, and particularly relates to an assembly type shoreline component design optimization system. According to the method, the environmental conditions, biological conditions and future demands of the river and lake shoreline are comprehensively considered, rapid optimization of assembly type shoreline component design is achieved by utilizing an intelligent analysis technology, river and lake condition parameters and biological condition parameters of the target shoreline can be automatically obtained and analyzed, future demand parameters are predicted, and the design efficiency is improved. According to the method, the optimal component material, size and connection mode meeting the target shoreline requirement can be screened out through material optimization and structure optimization, an optimal assembly scheme is generated, in addition, a feedback mechanism is further provided, the optimized component design parameters can be comprehensively evaluated, and the optimal assembly scheme is obtained. And carrying out iterative optimization according to an evaluation result until a preset comprehensive feasibility score and an ecological friendliness index are reached, and outputting a final design scheme.

Description

Technical Field

[0001] The present invention belongs to the technical field of design optimization of prefabricated shoreline components, and in particular relates to a design optimization system for prefabricated shoreline components. Background Art

[0002] Ecological restoration of river and lake shorelines faces complex environmental conditions and diverse ecological demands, posing significant challenges to the design of restoration materials. Traditional restoration methods often struggle to simultaneously meet the requirements of engineering durability and ecological adaptability. In harsh and volatile aquatic environments, how can they withstand physical damage such as sudden temperature fluctuations, freeze-thaw, water erosion, and tidal erosion, adapt to chemical attack such as salinity fluctuations, and at the same time provide a suitable habitat for aquatic life? This presents a complex, systemic challenge. Restoration materials must strike a balance between strength, durability, and eco-friendliness, often at odds with each other. For example, increasing concrete strength may reduce its permeability and biocompatibility, while adding anti-corrosion coatings may hinder biological attachment. Furthermore, the specific environmental conditions and ecological demands of different river and lake shorelines vary, making the rapid design of optimal restoration solutions for each specific scenario a major challenge. Therefore, a system that comprehensively considers various factors and performs intelligent analysis and optimization is needed to achieve customized design of river and lake shoreline restoration materials, ensuring project safety while maximizing ecological restoration and protection. Summary of the Invention

[0003] The purpose of the present invention is to provide a prefabricated shoreline component design optimization system that can comprehensively consider the environmental conditions, biological conditions and future needs of river and lake shorelines, and through intelligent analysis, quickly design the optimal prefabricated shoreline components to meet the dual needs of engineering durability and ecological adaptability.

[0004] The technical solutions adopted by the present invention are as follows:

[0005] A prefabricated shoreline component design optimization system, comprising:

[0006] The database module is used to build a component information database, which includes component material performance parameters, component size parameters and applicable condition parameters;

[0007] An acquisition module is used to obtain regional river and lake condition parameters, biological status parameters, and future demand parameters of the target shoreline;

[0008] A parameter analysis module is used to match and analyze the component material performance parameters, component size parameters, and applicable condition parameters in the component information database based on the regional river and lake condition parameters, biological status parameters, and future demand parameters;

[0009] The optimization module is used to select the optimal component materials, component sizes, and applicable conditions that meet the target shoreline requirements based on the matching analysis results, and generate the optimal assembly plan;

[0010] The feedback module is used to compare the optimal assembly solution with the preset assembly standards and evaluate the feasibility of the optimal assembly solution. If the optimal assembly solution does not meet the assembly standards, it will be fed back to the optimization module for further optimization until the optimal assembly solution that meets the assembly standards is obtained.

[0011] In a preferred embodiment, the component performance parameters include concrete grade parameters, compressive strength parameters, frost resistance grade parameters, air content parameters, admixture type parameters, admixture ratio parameters and anti-corrosion coating parameters; the construction size parameters include component length parameters, component width parameters, component height parameters and expansion joint size parameters reserved at component connections; the applicable condition parameters include applicable temperature range parameters, water flow velocity adaptation parameters, soil type compatibility parameters, eco-friendly index parameters and durability evaluation parameters.

[0012] In a preferred embodiment, the acquisition module includes a sensor deployment unit and a data acquisition unit. The sensor deployment unit is responsible for arranging various sensors in the target shoreline area. The data acquisition unit collects river and lake condition parameters and biological condition parameters in real time through the deployed sensors, and predicts future demand parameters based on the collected river and lake condition parameters and biological condition parameters.

[0013] In a preferred embodiment, the prediction of future demand parameters based on the collected river and lake condition parameters and biological status parameters includes the following steps:

[0014] Normalize the river and lake condition parameters and biological condition parameters and remove abnormal values ​​in them;

[0015] Conduct time series analysis on the normalized river and lake condition parameters and biological status parameters to determine the periodic change trends of river and lake condition parameters and biological status parameters;

[0016] Based on the periodic change trend, a prediction function is constructed, which inputs the normalized river and lake condition parameters and biological status parameters and outputs the future demand parameters.

[0017] In a preferred embodiment, the parameter analysis module includes an adaptability analysis unit, an ecological analysis unit, and a demand matching unit;

[0018] The adaptability analysis unit is used to analyze the anti-freezing performance, anti-scouring performance, chemical erosion resistance and corrosion resistance required by the corresponding components according to the regional river and lake condition parameters;

[0019] The ecological analysis unit is used to analyze the ecological adaptability performance required by the component based on biological condition parameters;

[0020] The demand matching unit is used to compare the results of the adaptability analysis unit and the ecological analysis unit with the component performance parameters, output a matching score, and adjust the component design parameters according to the matching score.

[0021] In a preferred embodiment, the optimization module includes a material optimization unit and a structure optimization unit;

[0022] The material optimization unit is used to screen the best material combination based on component performance parameters and eco-friendliness indicators;

[0023] The structural optimization unit adjusts the geometric dimensions and connection methods of components based on the material combination and demand matching results.

[0024] In a preferred embodiment, the feedback module includes a comparison unit and an evaluation unit;

[0025] The comparison unit is used to compare the optimized component design parameters with the initial design parameters to identify the differences;

[0026] The evaluation unit assigns evaluation weights to component performance and environmental impact based on the difference items, and then calculates a comprehensive feasibility score based on the evaluation weights. It then iteratively optimizes the component design based on the comprehensive feasibility score until the comprehensive feasibility score reaches the preset threshold, and then outputs the final optimization plan.

[0027] In a preferred embodiment, when iteratively optimizing the component design based on the comprehensive feasibility score, an adjustment suggestion vector for each parameter is automatically generated, wherein the adjustment suggestion vector includes an adjustment amount for the material admixture ratio, an adjustment amount for the construction joint size, and an adjustment amount for the anti-corrosion coating thickness;

[0028] The adjustment suggestion vector is input into the optimization module. Based on the feedback from the material optimization unit and the structural optimization unit, the component design parameters are dynamically modified to improve various performance indicators in a balanced manner until the comprehensive feasibility score stably reaches the preset threshold and the eco-friendliness indicator achievement rate reaches the preset standard threshold. Then, the final optimization plan is locked.

[0029] In a preferred embodiment, the feedback module further includes a construction simulation unit, which is used to simulate the installation process of components in actual construction to verify the feasibility of the design solution, including:

[0030] The final optimization plan is imported into the preset 3D riverbank terrain model to simulate the lifting, positioning and connection of components, determine the force distribution of components, identify stress concentration areas, and strengthen the structure in these stress concentration areas;

[0031] Simulate the construction process, predict the construction cycle and mark the process connection nodes. During the simulation, the assembly error of the components is monitored in real time. When the assembly error exceeds the preset allowable threshold, an alarm signal is issued and the reverse optimization instruction is triggered.

[0032] The geometric dimensions and connection methods of the constructed joints are readjusted according to the reverse optimization instructions until the assembly error is reduced to the preset allowable threshold.

[0033] The present invention further provides an electronic device, comprising:

[0034] at least one processor;

[0035] and a memory communicatively coupled to the at least one processor;

[0036] Wherein, the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor to realize the functions of the above-mentioned prefabricated shoreline component design optimization system.

[0037] The technical effects achieved by the present invention are:

[0038] The present invention comprehensively considers the environmental conditions, biological conditions and future needs of river and lake shorelines, and utilizes intelligent analysis technology to achieve rapid optimization of the design of prefabricated shoreline components. The system can automatically obtain and analyze the river and lake condition parameters and biological condition parameters of the target shoreline, predict future demand parameters, and perform component adaptability, ecology, and demand matching analysis based on these parameters. Through material optimization and structural optimization, the system can screen out the optimal component materials, sizes, and connection methods that meet the needs of the target shoreline and generate the optimal assembly plan. In addition, the system also has a feedback mechanism that can comprehensively evaluate the optimized component design parameters and iteratively optimize according to the evaluation results until the preset comprehensive feasibility score and eco-friendliness index are reached. During the construction phase, the actual installation process of the component can be simulated through the construction simulation unit to verify the feasibility of the design plan and ensure construction quality and efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a schematic diagram of the system modules of the present invention;

[0040] Figure 2 It is a schematic structural diagram of an electronic device of the present invention. DETAILED DESCRIPTION

[0041] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0042] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention may also be implemented in other ways different from those described herein. Those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0043] Secondly, the term "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The phrase "in a preferred embodiment" appearing in various places throughout this specification does not necessarily refer to the same embodiment, nor does it constitute a separate or selective embodiment that is mutually exclusive of other embodiments.

[0044] See also Figure 1 As shown, the present invention provides a prefabricated shoreline component design optimization system, comprising:

[0045] The database module is used to build a component information database, which includes component material performance parameters, component size parameters and applicable condition parameters;

[0046] When optimizing the design of components, the system automatically calls the relevant parameters in the database module and conducts a multi-dimensional analysis based on the actual working conditions to ensure that the design scheme not only meets the structural strength requirements but also has good economy and construction convenience. Among them, the database module is responsible for storing and managing various component data and providing corresponding data retrieval and update functions. Specifically, it builds a component information database to store component material performance parameters, component size parameters and applicable condition parameters. Among them, component performance parameters include concrete grade parameters, compressive strength parameters, frost resistance grade parameters, air content parameters, admixture type parameters, admixture ratio parameters and anti-corrosion coating parameters. The constructed size parameters include component length parameters, component width parameters, component height parameters and expansion joint size parameters reserved at component connections. The applicable condition parameters include applicable temperature range parameters, water flow velocity adaptation parameters, soil type compatibility parameters, ecological friendliness index parameters and durability evaluation parameters. Through subsequent comprehensive analysis of various parameters, the optimal design scheme is automatically generated to ensure that the components still have high stability and long life in complex environments, thereby effectively improving the overall quality and safety of the shoreline project.

[0047] An acquisition module is used to obtain regional river and lake condition parameters, biological status parameters, and future demand parameters of the target shoreline;

[0048] The acquisition module is mainly responsible for the regional river and lake condition parameters and biological status parameters of the target coastline, including the water level variation range, water turbulence, riverbed geological structure, etc. The acquisition module mainly includes a sensor deployment unit and a data acquisition unit. The sensor deployment unit is responsible for deploying various sensors in the target coastline area. The data acquisition unit collects river and lake condition parameters and biological status parameters in real time through the deployed sensors, and predicts future demand parameters based on the collected river and lake condition parameters and biological status parameters.

[0049] Specifically, the acquisition module mentioned above is mainly composed of two core parts, namely the sensor deployment unit and the data acquisition unit. The sensor deployment unit is mainly responsible for arranging various sensors in the target shoreline area to ensure that the sensors can cover key monitoring points. The sensors can be used to monitor water quality, capture biological activities, or other types of sensors, which together constitute a multi-dimensional monitoring network. The data acquisition unit is responsible for collecting river and lake condition parameters in real time through the deployed sensors, such as water temperature, pH value, dissolved oxygen content, etc., as well as biological status parameters, such as the activity frequency and population size of specific species, in order to understand the current status of the river and lake ecosystem. In addition, based on the collected river and lake condition parameters and biological status parameters, the data acquisition unit can also use prediction functions to predict future demand parameters, such as future water quality change trends, possible changes in biological populations, etc. The prediction function helps to take protective measures and formulate response strategies in advance.

[0050] It should be noted that the following steps are involved in predicting future demand parameters based on the collected river and lake condition parameters and biological status parameters:

[0051] Normalize the river and lake condition parameters and biological condition parameters and remove abnormal values ​​in them;

[0052] Conduct time series analysis on the normalized river and lake condition parameters and biological status parameters to determine the periodic change trends of river and lake condition parameters and biological status parameters;

[0053] Based on the periodic change trend, a prediction function is constructed, which inputs the normalized river and lake condition parameters and biological status parameters and outputs the future demand parameters;

[0054] In this embodiment, when predicting future demand parameters, the collected river and lake condition parameters and biological condition parameters are first normalized to remove outliers and ensure data accuracy. Then, a time series analysis is performed on the normalized data to reveal its periodic variation pattern, and then a prediction function is constructed. The expression of the prediction function is:

[0055]

[0056] Where Y t represents the predicted future demand parameter at time t, α, β, and χ represent the historical data weight coefficient, the periodic fluctuation amplitude coefficient, and the environmental factor weight coefficient, respectively, and φ i Indicates the contribution weight of the observations at the previous n time points to the current prediction, Y t-i represents the actual observation value at time ti, T represents the cycle length parameter (such as annual cycle, monthly cycle, etc.), X t represents the environmental parameter vector collected in real time, ε t It represents the random error term. By inputting preprocessed data, the interface outputs future demand parameters, thereby providing corresponding data support for ecological protection and resource management.

[0057] The parameter analysis module is used to match and analyze the component material performance parameters, component size parameters, and applicable condition parameters in the component information database based on regional river and lake condition parameters, biological status parameters, and future demand parameters;

[0058] When the parameter analysis module is executed, it will match the regional river and lake condition parameters, biological status parameters, and future demand parameters with the component information database to screen out the component types that meet the requirements. It will also optimize the design parameters based on historical data to ensure the feasibility of the plan. The parameter analysis module includes an adaptability analysis unit, an ecological analysis unit, and a demand matching unit.

[0059] The adaptability analysis unit is used to analyze the anti-freezing performance, anti-scouring performance, chemical erosion resistance and corrosion resistance required by the corresponding components according to the regional river and lake condition parameters;

[0060] The ecological analysis unit is used to analyze the ecological adaptability performance required by the component based on biological condition parameters;

[0061] The demand matching unit is used to compare the results of the adaptability analysis unit and the ecological analysis unit with the component performance parameters, output a matching score, and adjust the component design parameters according to the matching score;

[0062] Specifically, the parameter analysis module is mainly composed of the adaptive analysis unit, the ecological analysis unit and the demand matching unit working together. Through multi-dimensional data fusion, it accurately evaluates the compatibility between component performance and environmental requirements, and then optimizes the design parameters to ensure the stability and sustainability of the components in a complex ecological environment. The adaptive analysis unit evaluates the component's anti-freeze, anti-scouring, chemical erosion and corrosion resistance based on the regional river and lake condition parameters. For example, in the cold northern regions, rivers and lakes freeze in winter, and the expansion of the ice layer will put pressure on the components. Therefore, it is necessary to analyze the component's anti-freeze performance. By adding air-entraining agents, the air content of concrete can be increased, which can effectively improve the frost resistance and avoid component cracking caused by freeze-thaw cycles. At the same time, in areas with faster river flow rates, components need to have higher anti-scouring performance, which can be achieved by increasing the concrete strength grade or optimizing the surface treatment process. For chemical erosion performance, in areas with more industrial wastewater discharge, acid and alkali corrosion-resistant materials need to be selected, such as adding sulfate-resistant cement or using anti-corrosion coatings. Corrosion resistance is targeted at seawater or water bodies with high salt content, and can be improved by using chloride-resistant materials. The ecological analysis unit analyzes the required ecological adaptability of components based on biological parameters. For example, in fish migration areas, component design must consider eco-friendliness to avoid hindering aquatic life. Ecological holes or rough surfaces can be designed on the component surface to provide attachment space for aquatic plants and microorganisms, promoting ecosystem recovery. At the same time, in wetlands or nature reserves, component materials must be non-toxic and environmentally friendly to avoid pollution to surrounding organisms. In addition, component design must also consider the impact on bird habitats. For example, shallows or vegetation belts can be reserved in shoreline design to provide foraging and habitats for birds. The demand matching unit compares the results of the adaptability analysis unit and the ecological analysis unit with the component performance parameters, generates a corresponding matching score report (such as the common cosine similarity algorithm or Pearson correlation coefficient method to calculate the matching score), and adjusts the design based on the score to ensure that the component has both high strength and ecological balance in the specific environment, achieving a harmonious coexistence between environment and engineering.

[0063] The optimization module is used to select the optimal component materials, component sizes, and applicable conditions that meet the target shoreline requirements based on the matching analysis results, and generate the optimal assembly plan;

[0064] The optimization module is responsible for dynamically adjusting design parameters based on the scoring results to improve the overall performance of components. In rainy areas, it focuses on drainage performance to ensure that components can effectively divert water flow and reduce waterlogging pressure. In arid areas, it needs to focus on water retention performance to ensure that components can effectively conserve water resources and improve ecological adaptability. The optimization module includes material optimization units and structural optimization units.

[0065] The material optimization unit is used to screen the best material combination based on component performance parameters and eco-friendliness indicators;

[0066] The structural optimization unit adjusts the geometric dimensions and connection methods of components based on the material combination and demand matching results;

[0067] Specifically, the optimization module is mainly composed of material optimization unit and structure optimization unit. Through the coordinated work of the two, the performance of the component and the ecological environment can be matched. Among them, the core of the material optimization unit is to select the optimal concrete grade, admixture type and proportion, and anti-corrosion coating type according to the matching analysis results. For example, in coastal areas, due to the humid climate and large salinity gradient, concrete is susceptible to corrosion, so it is necessary to select materials with strong corrosion resistance. Through matching analysis, the system will give priority to recommending C35 concrete and recommending the addition of 30% slag and 10% fly ash to reduce hydration heat and improve crack resistance. At the same time, it will recommend coating the concrete surface with an epoxy resin anti-corrosion layer to extend the service life of the component. This optimization not only improves the durability of the material, It also reduces long-term maintenance costs. The structural optimization unit determines the size of the components, the design of expansion joints at the connections, the design of surface ecological holes, and the design of component gaps based on the matching analysis results. For example, in hilly areas, due to the complex terrain and significant influence of tides, the components need to have good adaptability and stability. At this time, it is recommended to select high-strength concrete and increase the density of steel bars to ensure that the components are stable and durable in complex terrain. At the same time, adjustable connection nodes are designed to cope with the stress caused by tidal changes and enhance the flexibility and durability of the overall structure. In addition, ecological holes with a diameter of 50 mm will be designed on the surface of the components to promote the habitat of aquatic organisms and the recovery of the ecosystem, which can not only improve the functionality of the components, but also enhance their coordination with the natural environment.

[0068] The feedback module is used to compare the optimal assembly solution with the preset assembly standards and evaluate the feasibility of the optimal assembly solution. If the optimal assembly solution does not meet the assembly standards, it will be fed back to the optimization module for further optimization until the optimal assembly solution that meets the assembly standards is obtained.

[0069] The feedback module mainly monitors data in real time and dynamically adjusts optimization strategies to ensure the best performance of components in different environments, improve the sustainability and environmental adaptability of the overall project, and provide maintenance suggestions based on actual usage to extend the service life of components. The feedback module includes a comparison unit and an evaluation unit.

[0070] The comparison unit is used to compare the optimized component design parameters with the initial design parameters to identify the differences;

[0071] The evaluation unit assigns evaluation weights to component performance and environmental impact based on the difference items, and then calculates a comprehensive feasibility score based on the evaluation weights. It then iteratively optimizes the component design based on the comprehensive feasibility score until the comprehensive feasibility score reaches the preset threshold, and then outputs the final optimization plan;

[0072] Specifically, the feedback module is composed of a comparison unit and an evaluation unit. The comparison unit is responsible for real-time monitoring of the differences between the data and the preset standards, while the evaluation unit conducts a comprehensive evaluation based on the difference items and quantifies them into a comprehensive feasibility score to determine whether the component design needs to be optimized. It also provides real-time adjustment suggestions during the optimization process to ensure that the component performance continues to meet the expected standards. Through this closed-loop feedback mechanism, the optimization plan can be continuously iterated to effectively improve the adaptability and durability of the components in complex environments. The optimized components not only have stronger corrosion resistance, but also maintain structural stability in a changing environment, effectively reducing the frequency of subsequent maintenance and maximizing the long-term benefits of the project.

[0073] Secondly, when iteratively optimizing the component design based on the comprehensive feasibility score, it automatically generates adjustment suggestion vectors for various parameters. The adjustment suggestion vectors include adjustments to the material admixture ratio, the size of the structural joint, and the thickness of the anti-corrosion coating.

[0074] The adjustment suggestion vector is input into the optimization module. Based on the feedback from the material optimization unit and the structural optimization unit, the component design parameters are dynamically modified to improve various performance indicators in a balanced manner until the comprehensive feasibility score stably reaches the preset threshold and the eco-friendliness indicator achievement rate reaches the preset standard threshold. Then, the final optimization plan is locked.

[0075] In this embodiment, when the component design is iteratively optimized, adjustment suggestion vectors for various parameters are automatically generated. The adjustment suggestion vectors cover everything from slight adjustments to the proportion of material admixtures to changes in the size of component joints, as well as increases or decreases in the thickness of the anti-corrosion coating. After the adjustment suggestion vectors are generated, they are directly connected to the optimization module. The material optimization unit and the structural optimization unit adjust the design parameters of the component accordingly based on the adjustment suggestion vectors. In this process, the selection and proportion of materials are further optimized to ensure that while meeting the strength requirements, the durability and eco-friendliness of the component can be maximized. The geometric dimensions, connection methods, and surface designs of the components are adjusted accordingly according to actual needs, aiming to improve the adaptability and stability of the components in complex environments. After multiple rounds of iterative optimization, the comprehensive feasibility score gradually increases until it stably reaches the preset threshold. At the same time, the eco-friendliness index also reaches the preset standard threshold. At this point, the final optimization plan can be locked, and the end of the design optimization process can be determined.

[0076] Secondly, the feedback module also includes a construction simulation unit, which is used to simulate the installation process of components in actual construction and verify the feasibility of the design scheme, including:

[0077] The final optimization plan is imported into the preset 3D riverbank terrain model to simulate the lifting, positioning and connection of components, determine the force distribution of components, identify stress concentration areas, and strengthen the structure in these stress concentration areas;

[0078] Simulate the construction process, predict the construction cycle and mark the process connection nodes. During the simulation, the assembly error of the components is monitored in real time. When the assembly error exceeds the preset allowable threshold, an alarm signal is issued and the reverse optimization instruction is triggered.

[0079] Re-adjust the geometric dimensions and connection methods of the constructed joints according to the reverse optimization instructions until the assembly error is reduced to the preset allowable threshold;

[0080] In the above, the feedback module also includes a construction simulation unit. The construction simulation unit can simulate the final optimization plan in the actual construction environment to ensure the feasibility of the design plan in actual operation. By importing the optimized component design into the preset three-dimensional riverbank terrain model, the component lifting, positioning and connection process can be intuitively simulated, and then the force distribution of the component in the actual installation can be determined, and the area with stress concentration can be identified. Structural strengthening treatment is carried out in the stress concentration area to improve the stability and safety of the component. In addition, the construction simulation unit can also simulate the construction process, predict the construction period, and mark the connection nodes of each process. During the simulation process, it can be realized The assembly error of the components is monitored in real time. Once the assembly error is found to exceed the preset allowable threshold, an alarm signal will be issued immediately and the reverse optimization instruction will be triggered. At this time, the geometric dimensions and connection methods of the component connections will be readjusted according to the reverse optimization instruction to ensure that the assembly error can be reduced to the preset allowable threshold, thereby ensuring the installation accuracy and overall stability of the components. Based on this method, the construction simulation unit can fully verify and optimize the design plan before actual construction, reduce the risks in the construction process, improve construction efficiency and quality, and also provide strong support for subsequent maintenance and maintenance work, ensuring the long-term stability and reliability of the prefabricated shoreline components in actual use.

[0081] See also Figure 2 , an electronic device, the electronic device comprising:

[0082] at least one processor;

[0083] and a memory communicatively coupled to the at least one processor;

[0084] Among them, the memory stores a computer program that can be executed by at least one processor, and the computer program is executed by at least one processor to realize the functions of the above-mentioned prefabricated shoreline component design optimization system.

[0085] In the above, the processor of the electronic device can be a central processing unit (CPU), a microprocessor, a digital signal processor (DSP), a graphics processing unit (GPU), a microcontroller (MCU), a field programmable gate array (FPGA), etc., or any combination thereof, and realizes the functions of the prefabricated shoreline component design optimization system by executing the computer program stored in the memory, including but not limited to data processing, model construction, parameter analysis, optimization iteration and construction simulation, etc. The memory can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories, wherein the volatile memory can include a random access memory (RAM) and / or a cache memory, etc., and the non-volatile memory can include a read-only memory (ROM), a hard disk, a flash memory, an optical disk, a U disk, a mobile hard disk, a magnetic surface Memory, phase change memory, resistive random access memory (RRAM) and / or magnetoresistive random access memory (MRAM), etc., as a computer storage medium, can be located inside or outside the electronic device, and can be communicated with the processor in various ways, such as wired connection or wireless connection. In addition, the processor can also include an arithmetic unit, input device, output device and network interface, etc. The arithmetic unit can be an arithmetic logic unit (ALU), which is responsible for performing various arithmetic and logical operations; the input device can include a keyboard, a mouse, a touch screen, etc., for receiving user input instructions and data; the output device can include a display, a printer, etc., for displaying processing results and output information; the network interface is used to realize the communication connection between the electronic device and other devices or networks to ensure data transmission and sharing.

[0086] It should be noted that, in this document, the terms "comprises," "includes," or any other variations thereof are intended to encompass non-exclusive inclusion, such that a process, apparatus, article, or method comprising a series of elements includes not only those elements but also other elements not explicitly listed, or elements inherent to such process, apparatus, article, or method. In the absence of further limitations, an element defined by the phrase "comprising a ..." does not exclude the presence of other identical elements in the process, apparatus, article, or method comprising the element.

[0087] The foregoing is merely a preferred embodiment of the present invention. It should be noted that those skilled in the art may make various improvements and modifications without departing from the principles of the present invention, and such improvements and modifications are also within the scope of protection of the present invention. Structures, devices, and operating methods not specifically described or explained herein shall, unless otherwise specified or limited, be implemented in accordance with conventional means in the art.

Claims

1. A prefabricated shoreline component design optimization system, characterized by: include: The database module is used to build a component information database, which includes component material performance parameters, component size parameters and applicable condition parameters; An acquisition module is used to obtain regional river and lake condition parameters, biological status parameters, and future demand parameters of the target shoreline; A parameter analysis module is used to match and analyze the component material performance parameters, component size parameters, and applicable condition parameters in the component information database based on the regional river and lake condition parameters, biological status parameters, and future demand parameters; The optimization module is used to select the optimal component materials, component sizes, and applicable conditions that meet the target shoreline requirements based on the matching analysis results, and generate the optimal assembly plan; The feedback module is used to compare the optimal assembly solution with the preset assembly standards and evaluate the feasibility of the optimal assembly solution. If the optimal assembly solution does not meet the assembly standards, it will be fed back to the optimization module for further optimization until the optimal assembly solution that meets the assembly standards is obtained.

2. The prefabricated shoreline component design optimization system according to claim 1, characterized in that: The component performance parameters include concrete grade parameters, compressive strength parameters, frost resistance grade parameters, air content parameters, admixture type parameters, admixture ratio parameters and anti-corrosion coating parameters; the construction size parameters include component length parameters, component width parameters, component height parameters and expansion joint size parameters reserved at component connections; the applicable condition parameters include applicable temperature range parameters, water flow velocity adaptation parameters, soil type compatibility parameters, eco-friendliness index parameters and durability evaluation parameters.

3. The prefabricated shoreline component design optimization system according to claim 1, characterized in that: The acquisition module includes a sensor deployment unit and a data acquisition unit. The sensor deployment unit is responsible for arranging various sensors in the target shoreline area. The data acquisition unit collects river and lake condition parameters and biological condition parameters in real time through the deployed sensors, and predicts future demand parameters based on the collected river and lake condition parameters and biological condition parameters.

4. The prefabricated shoreline component design optimization system according to claim 3, characterized in that: The process of predicting future demand parameters based on the collected river and lake condition parameters and biological status parameters includes the following steps: Normalize the river and lake condition parameters and biological condition parameters and remove abnormal values ​​in them; Conduct time series analysis on the normalized river and lake condition parameters and biological status parameters to determine the periodic change trends of river and lake condition parameters and biological status parameters; Based on the periodic change trend, a prediction function is constructed, which inputs the normalized river and lake condition parameters and biological status parameters and outputs the future demand parameters.

5. The prefabricated shoreline component design optimization system according to claim 1, characterized in that: The parameter analysis module includes an adaptability analysis unit, an ecological analysis unit, and a demand matching unit; The adaptability analysis unit is used to analyze the anti-freezing performance, anti-scouring performance, chemical erosion resistance and corrosion resistance required by the corresponding components according to the regional river and lake condition parameters; The ecological analysis unit is used to analyze the ecological adaptability performance required by the component based on biological condition parameters; The demand matching unit is used to compare the results of the adaptability analysis unit and the ecological analysis unit with the component performance parameters, output a matching score, and adjust the component design parameters according to the matching score.

6. The prefabricated shoreline component design optimization system according to claim 1, characterized in that: The optimization module includes a material optimization unit and a structure optimization unit; The material optimization unit is used to screen the best material combination based on component performance parameters and eco-friendliness indicators; The structural optimization unit adjusts the geometric dimensions and connection methods of components based on the material combination and demand matching results.

7. The prefabricated shoreline component design optimization system according to claim 1, characterized in that: The feedback module includes a comparison unit and an evaluation unit; The comparison unit is used to compare the optimized component design parameters with the initial design parameters to identify the differences; The evaluation unit assigns evaluation weights to component performance and environmental impact based on the difference items, and then calculates a comprehensive feasibility score based on the evaluation weights. It then iteratively optimizes the component design based on the comprehensive feasibility score until the comprehensive feasibility score reaches the preset threshold, and then outputs the final optimization plan.

8. The prefabricated shoreline component design optimization system according to claim 7, characterized in that: When the component design is iteratively optimized based on the comprehensive feasibility score, an adjustment suggestion vector for each parameter is automatically generated, wherein the adjustment suggestion vector includes an adjustment amount for the proportion of material admixtures, an adjustment amount for the size of the joint, and an adjustment amount for the thickness of the anti-corrosion coating; The adjustment suggestion vector is input into the optimization module. Based on the feedback from the material optimization unit and the structural optimization unit, the component design parameters are dynamically modified to improve various performance indicators in a balanced manner until the comprehensive feasibility score stably reaches the preset threshold and the eco-friendliness indicator achievement rate reaches the preset standard threshold. Then, the final optimization plan is locked.

9. The prefabricated shoreline component design optimization system according to claim 8, characterized in that: The feedback module also includes a construction simulation unit, which is used to simulate the installation process of components in actual construction to verify the feasibility of the design solution, including: The final optimization plan is imported into the preset 3D riverbank terrain model to simulate the lifting, positioning and connection of components, determine the force distribution of components, identify stress concentration areas, and strengthen the structure in these stress concentration areas; Simulate the construction process, predict the construction cycle and mark the process connection nodes. During the simulation, the assembly error of the components is monitored in real time. When the assembly error exceeds the preset allowable threshold, an alarm signal is issued and the reverse optimization instruction is triggered. The geometric dimensions and connection methods of the constructed joints are readjusted according to the reverse optimization instructions until the assembly error is reduced to the preset allowable threshold.

10. An electronic device, characterized in that: The electronic device comprises: at least one processor; and a memory communicatively coupled to the at least one processor; Wherein, the memory stores a computer program that can be executed by the at least one processor, and the computer program is executed by the at least one processor to realize the function of the prefabricated shoreline component design optimization system described in any one of claims 1 to 9.

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