An environmental impact prediction system and method thereof

Abstract

The application discloses an environmental impact prediction system and method thereof, relates to the technical field of environmental impact prediction, and comprises the following steps: in response to a design change event, real-time capture of component information; characteristic parameter mapping processing is performed to obtain calibrated input parameters; the whole life cycle comprehensive environmental impact index is calculated and compared with the initial construction cost of the project; in response to the predicted whole life cycle comprehensive environmental impact index being greater than the compliance baseline, constraint optimization decision processing is performed to generate an optimized design scheme; the predicted whole life cycle comprehensive environmental impact index and the predicted initial construction cost of the project are visually presented; and the optimized design scheme is visually presented on the user interface of a computer-aided design environment. The application pre-positions environmental and cost considerations and integrates them into instantaneous design decisions, solves the problems of disconnection between design and evaluation and feedback lag through real-time prediction and intelligent optimization.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of environmental impact prediction, and in particular to an environmental impact prediction system and a method thereof. BACKGROUND

[0002] In the computer-aided design (CAD) process of large and complex industrial projects, any subtle adjustment of the design scheme, such as the material selection or process change of core components, can have a significant and nonlinear impact on the comprehensive environmental impact index of the whole life cycle. The current technical system generally treats design creation and environmental impact assessment as two independent and serial steps. After the design work such as three-dimensional modeling is completed in the CAD environment, the data containing complete design information need to be exported and then imported into professional life cycle assessment (LCA) software for static and comprehensive simulation analysis. This evaluation process aims to quantify the potential impact of products on the environment throughout the whole life cycle from raw material acquisition, production and processing, transportation, use to disposal, and is a key analysis means adopted by modern manufacturing industry in response to increasingly stringent environmental regulations and corporate social responsibility requirements.

[0003] However, this traditional "after-the-fact" evaluation paradigm has fundamental defects. First, the separation of design and evaluation leads to a serious time lag. A complete life cycle assessment analysis often takes several hours or even days, which means that the designer cannot immediately know the environmental consequences of a change. This delay forms a huge gap between design and feedback, making design iteration slow and inefficient. Second, this lag directly leads to a core contradiction: in order to ensure that the environmental impact index of the final product is stable below the compliance baseline, the design team has to go through multiple rounds of design modification and evaluation cycles. Conversely, if the evaluation is relaxed in order to catch up with the project schedule, and the environmental impact is found to be inconsistent with the regulations or market requirements in the later stage of the project, it may lead to disastrous design rework, project cycle extension and budget overrun. SUMMARY

[0004] The purpose of the present application is to provide an environmental impact prediction system and a method thereof, which solves the problems in the background art.

[0005] To solve the above technical problems, the present application provides an environmental impact prediction method, comprising:

[0006] S1, in response to a design change event monitored in a computer-aided design environment, capturing component information corresponding to the design change event in real time;

[0007] S2, based on the component information and a preset environmental cost database, performing feature parameter mapping processing to obtain standardized quantitative input parameters;

[0008] S3, performing coupling prediction model processing based on the quantitative input parameters to synchronously solve a predicted life cycle comprehensive environmental impact index and a predicted initial project construction cost;

[0009] S4, comparing the predicted life cycle comprehensive environmental impact index with a preset compliance baseline;

[0010] S5, in response to the predicted life cycle comprehensive environmental impact index being greater than the compliance baseline, performing constraint optimization decision processing to generate an optimized design scheme;

[0011] S6, visualizing the predicted life cycle comprehensive environmental impact index and the predicted initial project construction cost on a user interface of a computer-aided design environment;

[0012] S7, in response to generating the optimized design scheme, visualizing the optimized design scheme on the user interface of the computer-aided design environment.

[0013] Preferably, the characteristic parameter mapping processing comprises:

[0014] querying an environmental cost database and converting component information into quantitative input parameters; the component information comprises geometric parameters, material properties and process information.

[0015] Preferably, the coupling prediction model processing comprises:

[0016] inputting the quantitative input parameters into a life cycle comprehensive environmental impact index prediction model to calculate the predicted life cycle comprehensive environmental impact index, and inputting the quantitative input parameters into an initial project construction cost prediction model to calculate the predicted initial project construction cost.

[0017] Preferably, the calculation of the life cycle comprehensive environmental impact index prediction model comprises:

[0018] calculating the predicted life cycle comprehensive environmental impact index based on the mass of the component, the unit mass environmental load factor of the selected material, the unit mass environmental load factor of the selected process, the material influence global weight coefficient and the process influence global weight coefficient by using a linear combination model.

[0019] Preferably, the calculation of the initial project construction cost prediction model comprises:

[0020] determining a material cost based on the mass of the component and the unit mass procurement cost of the selected material, determining a process cost based on the core process base duration, the unit time benchmark cost of the selected process and the design complexity coefficient, and adding the material cost and the process cost to calculate the predicted initial project construction cost.

[0021] Preferably, the constraint optimization decision processing comprises:

[0022] constructing a comprehensive cost function in an embedded penalty function method; solving with the objective of minimizing the comprehensive cost function to generate an optimized design scheme; the optimized design scheme comprises an alternative material or process combination that satisfies the compliance baseline constraint.

[0023] Preferably, solving with the objective of minimizing the comprehensive cost function comprises:

[0024] searching in the available material library and process library of the component corresponding to the design change event; if modifying only the component is insufficient to make the predicted full life cycle comprehensive environmental impact index satisfy the compliance baseline constraint, then according to a preset component correlation physical rule, expanding the search range to strongly correlated components.

[0025] Also provided is an environmental impact prediction system, comprising:

[0026] a real-time data acquisition module, configured to capture component information corresponding to a design change event in real time in response to a monitored design change event in a computer-aided design environment;

[0027] a core prediction module, configured to perform feature parameter mapping processing based on the component information and a preset environmental cost database to obtain standardized quantitative input parameters; and configured to perform coupled prediction model processing based on the quantitative input parameters to simultaneously solve a predicted full life cycle comprehensive environmental impact index and a predicted project initial construction cost;

[0028] a constraint optimization decision module, configured to compare the predicted full life cycle comprehensive environmental impact index with a preset compliance baseline; and configured to perform constraint optimization decision processing to generate an optimized design scheme in response to the predicted full life cycle comprehensive environmental impact index being greater than the compliance baseline;

[0029] an interactive feedback module, configured to visually present the predicted full life cycle comprehensive environmental impact index and the predicted project initial construction cost; and configured to visually present the optimized design scheme in response to the constraint optimization decision module generating the optimized design scheme.

[0030] Advantages

[0031] Compared with the prior art, the present application has the following advantages:

[0032] 1. The present application realizes parallel real-time processing of design behavior and evaluation analysis by deeply integrating the environmental impact prediction system into the operating environment of computer-aided design software. Any modification operation, such as changing the material or process of components, can instantly trigger the background synchronous calculation, and quantitative feedback on the two key dimensions of life cycle environmental impact and initial project construction cost can be obtained immediately. This instant feedback mechanism changes the environmental and cost considerations from a lagging review step to an inherent property that can be perceived in real time throughout the design process, thereby promoting integrated consideration of environmental sustainability and economic feasibility at the design source.

[0033] 2. The present application breaks through the limitation of traditional evaluation tools that can only passively provide evaluation values, and upgrades to intelligent guidance that can actively provide optimization directions. When it is monitored that a certain design change causes the predicted environmental impact index to exceed the preset compliance baseline, not only an alarm is issued, but also a constraint optimization decision module is automatically activated. This module can search in the available material library and process library and automatically generate an optimized design scheme that considers compliance and economy, providing intelligent decision support for design personnel with engineering feasibility and freeing them from tedious trial-and-error cycles.

[0034] 3. The present application couples the prediction model to closely link the two dimensions of environmental impact and economic cost, which have usually been considered in isolation. Any decision-induced chain reaction will be quantified and visualized on both the environmental impact index and the initial construction cost, which changes the design decision logic from pursuing local optimization of a single target to seeking global balance under multiple target constraints. This decision-making mode is closer to the actual needs of complex industrial projects and helps to lock in an environmentally friendly and cost-controllable comprehensive optimal design path at the initial stage of the project. BRIEF DESCRIPTION OF DRAWINGS

[0035] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the prior art, a brief introduction of the drawings needed to be used in the embodiments or prior art description will be given below. Obviously, the drawings in the following description only some embodiments of the present application, and for those skilled in the art, other drawings can also be obtained without creative labor on the basis of these drawings;

[0036] Figure 1 The flowchart of the environmental impact prediction method of the present application;

[0037] Figure 2 The logic diagram of the environmental impact prediction system of the present application. DETAILED DESCRIPTION

[0038] With reference to the drawings of the embodiments of the present application, the technical solutions in the embodiments of the present application will be described clearly and completely. Obviously, the described embodiments are only a part of the embodiments of the present application, and not all the embodiments. Based on the embodiments of the present application, all the other embodiments obtained by a person of ordinary skill in the art without creative work are within the protection scope of the present application.

[0039] Embodiment 1

[0040] Please refer to Figure 1 The present application provides an environmental impact prediction method, characterized in that comprising:

[0041] S1, in response to a design change event monitored in a computer-aided design environment, capturing component information corresponding to the design change event in real time;

[0042] S2, based on the component information and a preset environmental cost database, performing feature parameter mapping processing to obtain standardized quantitative input parameters;

[0043] S3, based on the quantitative input parameters, performing coupling prediction model processing to synchronously solve a predicted full-life-cycle comprehensive environmental impact index and a predicted initial construction cost of a project;

[0044] S4, comparing the predicted full-life-cycle comprehensive environmental impact index with a preset compliance baseline;

[0045] S5, in response to the predicted full-life-cycle comprehensive environmental impact index being greater than the compliance baseline, performing constraint optimization decision processing to generate an optimized design scheme;

[0046] S6, visualizing the predicted full-life-cycle comprehensive environmental impact index and the predicted initial construction cost of the project on a user interface of the computer-aided design environment;

[0047] S7, in response to generating the optimized design scheme, visualizing the optimized design scheme on the user interface of the computer-aided design environment;

[0048] In one specific embodiment, the environmental impact prediction method of the present application is deeply integrated into a computer-aided design software; when a design scheme of a high-pressure turbine blade assembly is modified, the method runs continuously in the background; when it is monitored that the material properties of the blade are changed, a design change event is identified to occur, the real-time data acquisition function of the system is triggered immediately, and the assembly information related to the blade is captured, including the updated material brand, the geometric model of the blade, and the established processing technology; this instant capture lays a data foundation for subsequent real-time prediction; the captured information is transmitted to a core prediction module, which performs feature parameter mapping and coupled prediction model processing, and instantly calculates the changed comprehensive environmental impact index of the whole life cycle and the initial construction cost of the project; the calculation result is compared with a preset compliance baseline, which can be derived from industry standards or enterprise internal environmental targets; if the calculated environmental impact index exceeds the baseline, a constraint optimization decision module will be activated to automatically generate a new design scheme that takes into account compliance and economy; all prediction values and optimization suggestions are presented in a visual way on the user interface of the computer-aided design without delay, so that the designer can weigh the environmental and cost impacts caused by his choice at the moment of decision, thereby fundamentally eliminating the delay and rework cost caused by the separation of traditional design and evaluation processes.

[0049] Embodiment 2:

[0050] The feature parameter mapping process includes querying the environmental cost database and converting the assembly information into quantitative input parameters; the assembly information includes geometric parameters, material properties, and process information;

[0051] The coupled prediction model processing includes inputting the quantitative input parameters into the whole life cycle comprehensive environmental impact index prediction model to calculate the predicted whole life cycle comprehensive environmental impact index; inputting the quantitative input parameters into the initial construction cost prediction model of the project to calculate the predicted initial construction cost of the project;

[0052] In the design change scenario of the turbine blade, the feature parameter mapping process is responsible for converting the original design information into standardized mathematical input; the captured assembly information, such as the surface geometry data of the blade, the selected specific high-temperature alloy material properties, and the specific vacuum investment casting process information, is mapped by querying a preset environmental cost database; the working principle of the database is composed of a relational data structure, which pre-stores a large amount of standardized material and process basic data; this query operation converts unstructured design information into a series of standardized quantitative input parameters, such as the blade mass calculated from the geometric model and material density, the unit mass environmental load factor and procurement cost associated with the material brand, and the unit mass environmental load factor and unit time benchmark cost associated with the process type;

[0053] Specifically, the environmental cost database contains at least a material table and a process table; the material table takes material brand as the primary key, and contains fields such as "material density" (unit: kg / m 3 ), "unit mass environmental load factor" (unit: point / kg), "unit mass procurement cost" (unit: monetary unit / kg), etc.; the process table takes process type as the primary key, and contains fields such as "unit mass environmental load factor" (unit: point / kg), "unit time reference cost" (unit: monetary unit / h), "standard work hour quota" (unit: h / kg or h / m 2 ), etc.; the mapping processing is to query and match in the database according to the material brand and process type selected by the changed component, and directly extract or obtain the corresponding quantitative parameters after simple calculation;

[0054] The coupling prediction model processing receives this series of parameters, and drives two independent prediction models in parallel in a unified calculation framework, realizing the synchronous calculation of the two dimensions of environmental impact and construction cost; this processing mechanism ensures that any single design change can immediately trigger the linkage prediction of the two core indicators of environment and cost, providing complete and real-time decision basis for designers.

[0055] Embodiment 3:

[0056] The calculation of the full life cycle comprehensive environmental impact index prediction model includes: based on the mass of the component, the unit mass environmental load factor of the selected material, the unit mass environmental load factor of the selected processing process, the material influence global weight coefficient and the process influence global weight coefficient, the predicted full life cycle comprehensive environmental impact index is calculated by a linear combination model;

[0057] The prediction and calculation of the full life cycle comprehensive environmental impact index is performed by a mathematical model constructed for real-time evaluation; the model is constructed based on the classical life cycle assessment theory and specific to the instantaneous calculation demand in the computer-aided design environment; its technical goal is to create a linear combination model with low calculation overhead and direct association with design parameters, to instantly convert the selection of materials and processes into a quantifiable, full life cycle environmental impact score; the calculation of the predicted full life cycle comprehensive environmental impact index Λ is realized by the following linear combination model:

[0058]

[0059] Λ is the predicted full life cycle comprehensive environmental impact index, which is a comprehensive score, and its unit is "point";

[0060] N is the total number of components in the project;

[0061] i is the index of the component;

[0062] m i is the mass of component i in kilograms (kg), which is automatically calculated by computer-aided design software based on the geometric model of the component and the density of the selected material;

[0063] μ i is the unit mass environmental load factor of the selected material for component i in points per kilogram (point / kg), which is obtained from an environmental cost database by querying the material grade. The "point" here is a comprehensive measurement unit obtained by standardizing and weighting various environmental impact categories based on life cycle assessment theory;

[0064] π i is the unit mass environmental load factor of the selected processing technology for component i in points per kilogram (point / kg), which is obtained from the same database by querying the technology type;

[0065] α and β are global weight coefficients for material influence and process influence, respectively, both dimensionless and satisfying the constraint α + β = 1. These two coefficients are preset adjustable strategy parameters, and their setting principle is: in the project start-up stage, technical experts set them according to the environmental focus of a specific project, thereby embodying the project-level environmental protection strategy orientation;

[0066] For example, if the project is located in a water resource sensitive area, the weight of the environmental impact category related to water resource consumption in the life cycle assessment model will be adjusted higher when calculating the unit mass environmental load factor μ i and π i ; Similarly, for a project that pays more attention to carbon emissions, more emphasis will be placed on categories related to global warming potential. The setting of global weight coefficients α and β reflects the relative importance of the project to the environmental impact of material selection and processing technology; For example, in a project that uses rare metals as the main material, the environmental impact of materials is crucial, and the value of α may be set to 0.7, while β is 0.3;

[0067] When the designer changes the material of the turbine blade, the system automatically obtains the density of the new material to update the mass m i , and retrieves the environmental load factor μ i corresponding to the new material from the database; The model immediately recalculates the Λ value using the updated parameters, thereby condensing the potential long-term environmental impact caused by a specific design decision into a single, intuitive and real-time feedback value, making environmental impact an engineering parameter that can be accurately perceived and actively managed in the design process.

[0068] Example 4:

[0069] The calculation of the project initial construction cost prediction model includes: determining the material cost based on the quality of the components and the unit mass procurement cost of the selected material; determining the process cost based on the core process base duration, the unit time benchmark cost of the selected process, and the design complexity coefficient; and adding the material cost and the process cost to calculate the predicted project initial construction cost;

[0070] The prediction calculation of the project initial construction cost is performed by a cost accounting model that introduces a design complexity correction; the model is based on the mature cost accounting method of the manufacturing industry, and by introducing a design complexity coefficient directly related to the geometric feature and accurately limiting its scope to the process cost item, it aims to improve the accuracy of the cost prediction of non-standard complex parts; the calculation of the predicted project initial construction cost C is realized by the following cost accumulation model:

[0071]

[0072] C is the predicted project initial construction cost, measured in monetary units;

[0073] m i N, i are defined as in the previous formula;

[0074] γ i is the unit mass procurement cost of the selected material for component i, measured in monetary units per kilogram, and its data is derived from the environmental cost database;

[0075] τ i is the core process base duration required for component i, measured in hours (h), and is estimated from the process information of the computer-aided design model combined with the standard work hour quota in the database for standard complexity;

[0076] δ i is the unit time benchmark cost of the selected process for component i, measured in monetary units per hour;

[0077] κ i is the design complexity coefficient of component i, which is a dimensionless parameter greater than or equal to 1; the preset working principle of this coefficient is determined by a rule engine: a reference geometric body, such as a cube, has κ i set to 1.0; the system increases its value based on a set of pre-set accumulation rules based on historical project manufacturing cost data regression analysis, according to the geometric features automatically extracted from the computer-aided design model, such as the number and type of high-precision curved surfaces, dense hole systems, or complex flow channel topologies;

[0078] The rule engine can be implemented as a function:

[0079] κ i = f(geomi )

[0080] geom i is the geometry feature vector of component i;

[0081] For example, its accumulation rule can be formalized as:

[0082]

[0083] j represents a specific complex geometry feature (such as free-form surface, small size hole, thin-walled structure, etc.), and M is the total number of preset complex features;

[0084] w j is the complexity weight coefficient of the jth feature, which is obtained by statistical analysis of historical manufacturing cost data;

[0085] N j is the number of the jth feature automatically detected and counted from the CAD model;

[0086] For example, the weight w1 of a free-form surface can be 0.15, and the weight w2 of a small hole (diameter < 3mm) can be 0.05; if a blade contains 2 free-form surfaces and 10 small holes, its complexity coefficient κ i = 1.0 + 0.15 x 2 + 0.05 x 10 = 1.8;

[0087] When the designer adds complex internal cooling structure to the turbine blade, its design complexity coefficient κ i will increase due to the recognition of the newly added geometry feature by the rule engine, and the cost model will be recalculated based on the increased κ i value. The cost prediction model and the aforementioned environmental impact prediction model are coupled through the shared component parameters, ensuring that any design change can output a corresponding (Λ, C) value pair in real time, providing quantitative input for subsequent constraint optimization.

[0088] Embodiment 5:

[0089] The constraint optimization decision processing includes: constructing a comprehensive cost function based on the embedded penalty function method; solving the minimum comprehensive cost function to generate an optimized design scheme; the optimized design scheme includes alternative material or process combination that meets the compliance baseline constraint;

[0090] Solving the minimum comprehensive cost function includes:

[0091] Search in the available material library and process library of the component corresponding to the design change event; if modifying the component alone is insufficient to make the predicted full life cycle comprehensive environmental impact index meet the compliance baseline constraint, then according to the preset component correlation physical rule, the search range is expanded to the strongly correlated components;

[0092] Constraint optimization decision processing, using the penalty function method in optimization theory, converts a constrained engineering problem into an unconstrained mathematical optimization problem; the internal logic is to construct a unified, differentiable comprehensive cost function, internalize the environmental compliance hard constraint as part of the function, and then use mature unconstrained optimization algorithms to efficiently search the design space; when a design change results in a predicted environmental index Λ ′ that exceeds the preset compliance baseline Λ ref , the system solves with the goal of minimizing the comprehensive cost function Ω; this function is constructed as:

[0093] minΩ=C ′ +η·max(0,Λ ′ -Λ ref ) 2

[0094] Ω is the comprehensive cost function, which is the goal of system optimization, and its dimension is consistent with the cost C ′ ;

[0095] C ′ is the predicted initial construction cost of the changed design scheme;

[0096] Λ ′ is the predicted full life cycle comprehensive environmental impact index of the changed design scheme;

[0097] Λ ref is the compliance baseline of the environmental index, which is a preset threshold with a unit of "points", and its setting basis can be industry regulations or enterprise internal environmental targets;

[0098] η is the penalty factor, which is a large positive number with a unit of currency per point squared;

[0099] The value of η should ensure that when the environmental index exceeds the standard, the penalty term η·(Λ ′ -Λ ref ) 2 is significantly larger in numerical value than the typical cost C ′ of the design scheme;

[0100] Its physical meaning is that by setting a large enough η value, any violation of the environmental compliance constraint (i.e. Λ ′ >Λ refThe behavior of any of these components will cause the integrated cost function Ω to increase sharply, thus driving the optimization algorithm to prefer solutions that satisfy the constraints; for example, if a component's typical cost is in the order of 10 3 currency units, and an environmental index that is off by 1 point is unacceptable, then the value of η should be set to 10 4 or higher to ensure that even the smallest deviation will incur a decisive penalty in the integrated cost;

[0101] These component association physical rules are stored in the system background in the form of a weighted directed graph G = (V, E); the node set V represents all components in the project, and the edge set E represents the association between components; each edge e ij ∈ E points from component i to component j, and its weight w ij quantifies the strength of the association between the two (such as the size of the contact area, the efficiency of force transmission, the size of the heat flux, etc.); when it is necessary to expand the search range, the system will start from the current component node and perform a breadth-first search along the edges in the graph whose weights are higher than a preset threshold, and the components corresponding to the adjacent nodes found in the search will be included in the optimization range; for example, the association rule of a turbine blade can point to the downstream blade disc mortise, because the material change of the blade (which affects the centrifugal force) will directly affect the structural stress requirements of the mortise.

[0102] Embodiment 6:

[0103] Referring to Figure 2 , the application further provides an environmental impact prediction system, comprising:

[0104] a real-time data acquisition module, configured to capture component information corresponding to a design change event in real time in response to a monitored design change event in a computer-aided design environment;

[0105] a core prediction module, configured to perform feature parameter mapping processing based on the component information and a preset environmental cost database to obtain standardized quantitative input parameters, and to perform coupled prediction model processing based on the quantitative input parameters to synchronously solve a predicted integrated environmental impact index for the whole life cycle and a predicted initial construction cost of the project;

[0106] a constraint optimization decision module, configured to compare the predicted integrated environmental impact index for the whole life cycle with a preset compliance baseline, and to perform constraint optimization decision processing to generate an optimized design scheme in response to the predicted integrated environmental impact index for the whole life cycle being greater than the compliance baseline;

[0107] an interactive feedback module, configured to visually present the predicted integrated environmental impact index for the whole life cycle and the predicted initial construction cost of the project, and to visually present the optimized design scheme in response to the constraint optimization decision module generating the optimized design scheme;

[0108] The environmental impact prediction system of the present application realizes the method through its modular functional structure; the real-time data acquisition module is integrated with the kernel application program interface of the computer-aided design software, and responds to any design change event to capture the relevant component information; the core prediction module receives the collected information, performs characteristic parameter mapping and coupled prediction model processing, and synchronously calculates the environmental impact index Λ and the construction cost C; the constraint optimization decision module continuously compares the output Λ of the core prediction module with the compliance baseline Λ ref and activates when it exceeds the standard, performs constraint optimization decision processing to generate an optimized design scheme containing alternative materials or processes; the interactive feedback module serves as the interface for information exchange between the system and the user, and presents the real-time values of Λ and C, as well as the optimized scheme generated by the constraint optimization decision module when necessary, in the form of charts or highlights, to the user interface of the computer-aided design; these modules work together to form a complete closed loop from data input, model calculation, optimization decision to result presentation, providing designers with a tool that can instantly understand the long-term environmental and immediate cost impact of their design behavior, thereby integrating environmental sustainability and economic feasibility at the design source.

[0109] The above is only a preferred embodiment of the present application, and does not limit the form of the present application in other forms. Any skilled person in the art can use the disclosed technical content to make changes or modifications to equivalent embodiments applied to other fields, but any simple modification, equivalent change and modification made in accordance with the technical essence of the present application to the above embodiments without departing from the technical solution content of the present application shall still fall within the protection scope of the present application.

Claims

1. A method of environmental impact prediction, characterized by, The method comprises the following steps: S1, in response to a design change event monitored in a computer-aided design environment, capturing component information corresponding to the design change event in real time; S2, based on the component information and a preset environmental cost database, performing feature parameter mapping processing to obtain standardized quantitative input parameters; S3, based on the quantitative input parameters, performing coupled prediction model processing to synchronously solve a predicted full life cycle comprehensive environmental impact index and a predicted initial construction cost of the project; S4, comparing the predicted full life cycle comprehensive environmental impact index with a preset compliance baseline; S5, in response to the predicted full life cycle comprehensive environmental impact index being greater than the compliance baseline, performing constraint optimization decision processing to generate an optimized design scheme; S6, visualizing the predicted full life cycle comprehensive environmental impact index and the predicted initial construction cost of the project on a user interface of the computer-aided design environment; S7, in response to the optimized design scheme being generated, visualizing the optimized design scheme on the user interface of the computer-aided design environment; The feature parameter mapping processing comprises: querying the environmental cost database and converting the component information into quantitative input parameters; the component information includes geometric parameters, material properties and process information; The coupled prediction model processing comprises: inputting the quantitative input parameters into a full life cycle comprehensive environmental impact index prediction model to calculate the predicted full life cycle comprehensive environmental impact index; inputting the quantitative input parameters into an initial construction cost of the project prediction model to calculate the predicted initial construction cost of the project; The calculation of the full life cycle comprehensive environmental impact index prediction model comprises: based on the mass of the component, the unit mass environmental load factor of the selected material, the unit mass environmental load factor of the selected processing technology, the material influence global weight coefficient and the process influence global weight coefficient, the predicted full life cycle comprehensive environmental impact index is calculated by a linear combination model; The calculation of the initial construction cost of the project prediction model comprises: based on the mass of the component and the unit mass procurement cost of the selected material, the material cost is determined; based on the core process basic time length, the unit time benchmark cost of the selected process and the design complexity coefficient, the process cost is determined; the material cost and the process cost are added to calculate the predicted initial construction cost of the project.

2. The environmental impact prediction method of claim 1, wherein, The constraint optimization decision processing comprises: building a comprehensive cost function based on the embedded penalty function method; solving the minimum comprehensive cost function as the target to generate an optimized design scheme; the optimized design scheme includes alternative material or process combination that meets the compliance baseline constraint.

3. A method of environmental impact prediction according to claim 2, wherein, Solving the minimum comprehensive cost function as the target comprises: searching in the available material library and process library of the component corresponding to the design change event; if only modifying the component is not enough to make the predicted full life cycle comprehensive environmental impact index meet the compliance baseline constraint, the search range is expanded to the strongly related components according to the preset component correlation physical rules.

4. An environmental impact prediction system for use in an environmental impact prediction method according to any one of claims 1 to 3, characterized by The method comprises: a real-time data acquisition module for capturing component information corresponding to a design change event in real time in response to a design change event monitored in a computer-aided design environment; The core prediction module is configured to perform feature parameter mapping processing based on the component information and a preset environmental cost basis database to obtain standardized quantitative input parameters, and perform coupling prediction model processing based on the quantitative input parameters to synchronously solve a predicted full life cycle comprehensive environmental impact index and a predicted initial construction cost of the project. The constraint optimization decision module is configured to compare the predicted full life cycle comprehensive environmental impact index with a preset compliance baseline. The constraint optimization decision module is configured to compare the predicted full life cycle comprehensive environmental impact index with a preset compliance baseline. The interactive feedback module is configured to visually present the predicted full life cycle comprehensive environmental impact index and the predicted initial construction cost of the project, and visually present the optimized design scheme in response to the constraint optimization decision module generating the optimized design scheme.

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