System dynamics-based evaluation method for life cycle cost-effectiveness of prefabricated buildings

Abstract

This invention discloses a method for evaluating the cost-effectiveness of prefabricated buildings throughout their entire life cycle based on system dynamics, belonging to the field of prefabricated building engineering management and evaluation technology. The method involves: acquiring the performance and cost influencing factors throughout the entire life cycle of a prefabricated building; analyzing the causal relationships among these factors using the DEMATEL method to identify key influencing factors and their interaction paths; using this causal relationship as input to an ANP network to calculate the comprehensive weight of each key influencing factor, thus constructing a cost-effectiveness evaluation index system for the entire life cycle of prefabricated buildings; and based on the system dynamics method, combining the evaluation index system and comprehensive weights to construct a cost-effectiveness evaluation SD model for prefabricated buildings. Scenario variables for different prefabricated structural systems are input, and the cost-effectiveness evolution simulation is conducted through the SD model to output the cost-effectiveness evaluation results. This invention achieves a systematic and dynamic evaluation of the cost-effectiveness of prefabricated buildings, providing a scientific basis for the promotion of prefabricated buildings and the selection of structural systems.

Description

Technical Field

[0001] This invention relates to the field of prefabricated building engineering management and evaluation technology, specifically to a method for evaluating the cost-effectiveness of prefabricated buildings throughout their entire life cycle based on system dynamics. Background Technology

[0002] Driven by the dual forces of digital transformation in the construction industry, prefabricated construction, as a core path to achieving green, low-carbon, quality-improving, and efficiency-enhancing development, has become a key promotion direction of my country's construction industry policies. During the period of intelligent construction and collaborative development, the goal of adopting prefabricated construction for over 30% of new buildings has been continuously improved, with the policy system constantly evolving from the initial stage of component prefabrication to the advanced stage of overall productization and system integration. However, the promotion of prefabricated construction has consistently faced the dilemma of policy enthusiasm but market indifference. The core issue lies in the fact that its cost-effectiveness is affected by multiple factors such as labor costs, technological maturity, and policy incentives, resulting in significant differences across different regions and scenarios. Furthermore, the implicit benefits throughout the entire life cycle are difficult to quantify. Existing evaluation systems often focus on single-stage or local indicators, failing to achieve a systematic coupling analysis of performance and cost, leading decision-makers to tend to conservatively choose traditional cast-in-place construction methods.

[0003] With the diversification of prefabricated building structural systems, various solutions such as MIC modular systems and GS-Building prefabricated steel structures have emerged. These different systems exhibit significant differences in performance characteristics and cost structure, necessitating an evaluation method that considers both the entire life-cycle perspective and dynamic evolution characteristics. Traditional cost-effectiveness evaluations often employ static analysis frameworks, relying on methods such as the analytic hierarchy process (AHP) and fuzzy comprehensive evaluation. While these methods can quantify indicators, they struggle to depict the dynamic feedback relationships between various influencing factors and cannot simulate the evolution path of cost-effectiveness under different external environments. Furthermore, existing research often analyzes performance and cost separately, lacking a holistic consideration of the entire process from design, production, construction, operation, and decommissioning. This leads to discrepancies between evaluation results and actual engineering practices, making it difficult to support the practical needs of promoting prefabricated buildings according to local conditions and selecting appropriate structural systems.

[0004] Chinese patent (publication number: CN115081056A) discloses a dynamic life cycle evaluation method for buildings that considers time variables. It uses single-factor sensitivity analysis to screen sensitive parameters and combines a grey prediction GM(1,1) model with Monte Carlo simulation to output the probability distribution of the building's life cycle over time, improving upon the shortcomings of traditional static evaluations that fail to reflect the impact of the time dimension. However, this patent focuses on the dynamic analysis of environmental impact dimensions, failing to incorporate performance and cost into a unified evaluation framework, and does not adapt to the differences in structural systems of prefabricated buildings, making it difficult to directly apply to comprehensive cost-effectiveness evaluation scenarios. To address its single-dimensionality and insufficient adaptability, Chinese patent (publication number: CN121073710A) proposes a prefabricated building full life cycle intelligent management system based on BIM and IoT. Through staged data collection and digital twin technology, it achieves full life cycle risk assessment and collaborative management, improving the intelligence level of prefabricated building operation. However, this system focuses on risk control and collaborative management, failing to construct a core model for cost-effectiveness evaluation and lacking the ability to quantitatively analyze the dynamic evolution of performance and cost, thus unable to support cost-effectiveness comparison decisions for multiple structural systems.

[0005] Therefore, there is an urgent need to achieve accurate simulation of the cost-effectiveness evolution path of prefabricated buildings under different structural systems and different external environments by integrating the concept of the whole life cycle and dynamic analysis methods for cost-effectiveness evaluation technology. Summary of the Invention

[0006] To address the aforementioned technical issues, this application discloses a method for evaluating the cost-effectiveness of prefabricated buildings throughout their entire life cycle based on system dynamics, specifically including:

[0007] To obtain the performance and cost influencing factors throughout the entire life cycle of prefabricated buildings, the entire life cycle includes the design stage, production stage, construction stage, operation stage and decommissioning stage;

[0008] The causal relationships among the influencing factors were analyzed using the DEMATEL method to identify key influencing factors and their interaction pathways.

[0009] Using the causal relationship as input to the ANP network, the comprehensive weight of each key influencing factor is calculated using the ANP method, and a cost-effectiveness evaluation index system for the entire life cycle of prefabricated buildings is constructed.

[0010] Based on the system dynamics method, and combined with the evaluation index system and comprehensive weight, a prefabricated building cost-effectiveness evaluation SD model is constructed, which includes causal loop diagrams, stock flow diagrams and variable function equations.

[0011] By inputting differentiated parameters of different prefabricated structural systems and scenario variables of different external environments, the cost-effectiveness evolution simulation is performed through the SD model, and the cost-effectiveness evaluation results of the prefabricated building throughout its entire life cycle are output.

[0012] Preferably, the performance and cost influencing factors throughout the entire life cycle of prefabricated buildings are obtained, specifically: the performance influencing factors include structural safety performance factors, green and environmental protection performance factors, functional performance factors, and durability performance factors; the cost influencing factors include design cost factors, manufacturing cost factors, transportation and installation cost factors, operation and maintenance cost factors, and scrapping and recycling cost factors.

[0013] Preferably, the performance and cost influencing factors throughout the entire life cycle of the prefabricated building are determined by constructing an initial set of influencing factors. and collect Expert rating data The importance score for each factor is calculated using the following formula: Filter out Factors that serve as influencing factors, among which This is a preset importance threshold.

[0014] Preferably, the step of analyzing the causal relationship between the influencing factors using the DEMATEL method includes:

[0015] Constructing the direct influence matrix of influencing factors ,in Indicator Factors Factors The degree of direct impact; through the formula Direct Influence Matrix Normalization is performed to obtain the normalized matrix. ;

[0016] Calculate the comprehensive impact matrix ,in It is the identity matrix;

[0017] Calculate the influence of each factor And the degree of influence ,pass Characteristic factor centrality Characterizing the causal degree of factors, selecting those that simultaneously meet the criteria. and The factors are considered as key influencing factors; among them, Take the average of the centralities of all factors. Take the average of the absolute values ​​of the causal degree of all factors.

[0018] Preferably, the calculation of the comprehensive weight of each key influencing factor using the ANP method includes:

[0019] Based on the causal relationships obtained by the DEMATEL method, an ANP network structure containing a control layer and a network layer is constructed. The control layer is the cost-performance evaluation target, and the network layer is the key influencing factors.

[0020] Construct the judgment matrix ,in The number of factors in the network layer. and ; Calculate the eigenvalues ​​of the judgment matrix and eigenvectors Through the consistency test formula Verify consistency, where , As the average random consistency index, when The test was passed; the comprehensive weights of each key influencing factor were obtained through supermatrix calculation and limit supermatrix solution. .

[0021] Preferably, the construction of the prefabricated building cost-effectiveness evaluation SD model includes:

[0022] The model boundary is defined as the entire life cycle of prefabricated buildings, and the model assumptions are clearly defined.

[0023] Based on the evaluation index system and key influencing factors, a causal loop diagram representing the feedback relationships of the performance subsystem, cost subsystem, and external environment subsystem is drawn. This causal loop diagram is then transformed into a stock-flow diagram, defining the stock variable as the cumulative performance value. and cumulative cost value The flow variable represents the performance increment at each stage. and cost increment The auxiliary variables are the quantified values ​​of each key influencing factor;

[0024] Establish the function equation with variables, including:

[0025] Cumulative performance equation: , These are the initial performance values. Corresponding to the five stages of the entire life cycle;

[0026] Cumulative cost equation: , This is the initial cost value;

[0027] Cost-effectiveness equation: , for Value for money at all times.

[0028] Preferably, the performance increments at each stage The formula is: ,in For the first The number of factors affecting stage performance The corresponding factors are weighted comprehensively. For factor quantification values, This is the performance conversion factor.

[0029] Preferably, the cost increments at each stage The formula is: ,in For the first Number of factors affecting stage costs The corresponding factors are weighted comprehensively. For factor cost quantification, This is the cost allocation coefficient.

[0030] Preferably, the scenario variables for different external environments include quantitative values ​​of labor prices, policy incentive coefficients, technology maturity index, and quantitative values ​​of transportation radius. Each scenario variable is calibrated using industry statistical data and then input into the SD model.

[0031] Preferably, the differentiated parameters of the different prefabricated structural systems include structural safety performance parameters, green environmental protection performance parameters, manufacturing cost parameters, and operation and maintenance cost parameters. Each parameter is determined based on the technical standards and engineering practice data of the corresponding structural system and then input into the SD model. Through simulation, the sensitivity is utilized... The stability of the model is analyzed and verified using the following formula: ,when The model is then judged to meet the evaluation requirements. For preset sensitivity, where For the rate of change in cost-effectiveness, The rate of change of key influencing factors.

[0032] Compared with the prior art, the technical solution of this application has the following technical effects:

[0033] This invention constructs a cost-effectiveness evaluation index system covering the entire life cycle of prefabricated buildings, systematically integrating key influencing factors from both performance and cost dimensions. This achieves a comprehensive characterization of the overall value of prefabricated buildings. The index system, through scientific screening and weight quantification, covers core performance dimensions such as structural safety and environmental protection, and incorporates cost elements from all stages, including design, production, and operation and maintenance. This ensures the completeness and scientific nature of the evaluation results, providing a comprehensive and accurate quantitative basis for cost-effectiveness analysis.

[0034] This invention constructs a dynamic evaluation model based on the DEMATEL-ANP combination method and system dynamics theory. This model effectively characterizes the causal feedback relationship and evolution law among various influencing factors. The model clearly presents the variable interaction mechanism through causal loop diagrams and stock flow diagrams. Combined with quantitative function equations, it realizes dynamic simulation of cost-effectiveness throughout the entire life cycle, accurately captures the changing characteristics of cost-effectiveness at different stages, and improves the dynamic adaptability and prediction accuracy of the evaluation results.

[0035] This invention, by inputting differentiated parameters of different prefabricated structural systems and external environmental scenario variables, can simulate and compare the cost-effectiveness evolution path under multiple scenarios, identify the applicable range of different structural systems, provide quantitative decision-making basis for structural form selection and technical path optimization in the project planning stage, help to rationalize and improve the efficiency of resource allocation, and enhance the overall benefits of prefabricated building projects.

[0036] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the preferred embodiments of this application are described in detail below with reference to the accompanying drawings.

[0037] The above and other objects, advantages and features of this application will become more apparent to those skilled in the art from the following detailed description of specific embodiments in conjunction with the accompanying drawings. Attached Figure Description

[0038] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort. In all drawings, similar elements or parts are generally identified by similar reference numerals. In the drawings, the elements or parts are not necessarily drawn to scale.

[0039] Based on the description of the figures and their corresponding technical content in the document, the titles of the figures are as follows:

[0040] Figure 1 A schematic diagram of the overall process for evaluating the cost-effectiveness of prefabricated buildings throughout their entire life cycle based on system dynamics;

[0041] Figure 2 A hierarchical structure diagram of the cost-effectiveness evaluation index system for the entire life cycle of prefabricated buildings;

[0042] Figure 3A schematic diagram of the three subsystems and variable interaction architecture of the SD model for evaluating the cost-effectiveness of prefabricated buildings;

[0043] Figure 4 .Evolution trend curves of cost-effectiveness throughout the entire life cycle of four types of prefabricated structural systems under the baseline scenario;

[0044] Figure 5 A comparative chart showing the sensitivity analysis of the cost-effectiveness of four types of prefabricated structural systems to various external environmental factors;

[0045] Figure 6 A bar chart comparing the average cost-effectiveness of four types of prefabricated structural systems at each stage of their entire life cycle;

[0046] Figure 7 A radar comparison diagram of the cost-effectiveness of four types of prefabricated structural systems throughout their entire life cycle under typical scenarios. Detailed Implementation

[0047] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. In the following description, specific details such as specific configurations and components are provided merely to help fully understand the embodiments of this application. Therefore, those skilled in the art should understand that various changes and modifications can be made to the embodiments described herein without departing from the scope and spirit of this application. In addition, for clarity and brevity, descriptions of known functions and structures are omitted in the embodiments.

[0048] It should be understood that the phrase "an embodiment" or "this embodiment" throughout the specification means that a specific feature, structure, or characteristic related to the embodiment is included in at least one embodiment of this application. Therefore, "an embodiment" or "this embodiment" appearing throughout the specification does not necessarily refer to the same embodiment. Furthermore, these specific features, structures, or characteristics can be combined in any suitable manner in one or more embodiments.

[0049] Furthermore, reference numerals and / or letters may be repeated in different examples within this application. Such repetition is for the purpose of simplification and clarity and does not in itself indicate a relationship between the various embodiments and / or settings discussed.

[0050] In this article, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can mean: A exists alone, B exists alone, and A and B exist simultaneously. The term " / and" in this article describes another type of relationship between related objects, indicating that two relationships can exist. For example, A / and B can mean: A exists alone, and A and B exist alone. In addition, the character " / " in this article generally indicates that the related objects before and after it are in an "or" relationship.

[0051] In this article, the term "at least one" is merely a description of the relationship between related objects, indicating that there can be three relationships. For example, "at least one of A and B" can mean: A exists alone, A and B exist simultaneously, or B exists alone.

[0052] It should also be noted that, in this document, relational terms such as "first" and "second" are used only to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion.

[0053] Example 1

[0054] This embodiment mainly describes a method for evaluating the cost-effectiveness of prefabricated buildings throughout their entire life cycle based on system dynamics, such as... Figure 1 As shown, it specifically includes:

[0055] To obtain the performance and cost influencing factors throughout the entire life cycle of prefabricated buildings, the entire life cycle includes the design stage, production stage, construction stage, operation stage and decommissioning stage;

[0056] The causal relationships among the influencing factors were analyzed using the DEMATEL method to identify key influencing factors and their interaction pathways.

[0057] Using the causal relationship as input to the ANP network, the comprehensive weight of each key influencing factor is calculated using the ANP method, and a cost-effectiveness evaluation index system for the entire life cycle of prefabricated buildings is constructed.

[0058] Based on the system dynamics method, and combined with the evaluation index system and comprehensive weight, a prefabricated building cost-effectiveness evaluation SD model is constructed, which includes causal loop diagrams, stock flow diagrams and variable function equations.

[0059] By inputting differentiated parameters of different prefabricated structural systems and scenario variables of different external environments, the cost-effectiveness evolution simulation is performed through the SD model, and the cost-effectiveness evaluation results of the prefabricated building throughout its entire life cycle are output.

[0060] Furthermore, performance influencing factors specifically include structural safety performance factors, green and environmentally friendly performance factors, functional performance factors, and durability performance factors. Among them, structural safety performance factors focus on core indicators such as component connection strength and seismic bearing capacity; green and environmentally friendly performance factors revolve around dimensions such as material resource utilization rate, carbon emissions, and construction waste generation; functional performance factors cover spatial adaptability, sound insulation and heat insulation effects, etc.; and durability performance factors involve parameters such as component anti-aging ability and corrosion and rust prevention level. Cost influencing factors include design cost factors, manufacturing cost factors, transportation and installation cost factors, operation and maintenance cost factors, and scrapping and recycling cost factors. Design cost factors include scheme design fees, mold design fees, etc.; manufacturing cost factors involve raw material procurement fees, component processing fees, etc.; transportation and installation cost factors include transportation fees, hoisting machinery usage fees, etc.; operation and maintenance cost factors include daily maintenance fees, energy consumption costs, etc.; and scrapping and recycling cost factors involve dismantling fees, recyclable material processing fees, etc.

[0061] During the acquisition process, an initial set of influencing factors is first constructed. ,in To collect the total number of initially identified influencing factors, further data will be collected. Expert scoring data with relevant research or engineering practice experience in prefabricated buildings , For the first The expert commented on the first Each factor is rated on its importance, ranging from 0 to 10 points. A score of 0 indicates that the factor has no impact on cost-effectiveness, while a score of 10 indicates that the factor has a significant impact on cost-effectiveness. This is achieved through a formula... Calculate the importance score for each factor, where For the first The importance score of each factor is set, and a preset importance threshold is set. , The value is the average of the importance scores of all factors, and the selection is based on this. The factors are included as the influencing factors in the final evaluation system.

[0062] Furthermore, the DEMATEL method analyzes causal relationships by constructing a matrix of direct influence factors. , Indicator Factors Factors The degree of direct impact is represented by a value ranging from 0 to 4, where 0 indicates no direct impact, 1 indicates slight direct impact, 2 indicates moderate direct impact, 3 indicates strong direct impact, and 4 indicates extremely strong direct impact. This is determined using the formula... Direct Influence Matrix Normalization is performed to obtain the normalized matrix. ,in To directly affect the matrix The maximum sum of all elements in each row of the table, after normalization. The value range is 0-1.

[0063] Next, calculate the comprehensive influence matrix. ,in for An identity matrix of order 1. For matrix The inverse matrix, the comprehensive influence matrix elements in Indicator Factors Factors The sum of direct and indirect effects. Then, using the formula... Calculate the influence of each factor , Indicator Factors The combined impact on all other factors; expressed by the formula. Calculate the degree of influence of each factor. , Indicator Factors The degree to which it is affected by the combined influence of all other factors.

[0064] pass The centrality of a factor reflects its importance within the overall system of influencing factors; a higher centrality value indicates a more critical factor. The causality degree characterizes a factor. A positive causality degree indicates that the factor primarily influences other factors and is considered a causal factor; a negative causality degree indicates that the factor is primarily influenced by other factors and is considered an outcome factor. A centrality threshold is set. and causal threshold , Take the average of the centralities of all factors. Take the average of the absolute values ​​of the causal degrees of all factors, and filter out those that simultaneously meet the criteria. and The factors are considered as key influencing factors.

[0065] Furthermore, such as Figure 2 As shown, based on the causal relationships obtained by the DEMATEL method, an ANP network structure containing a control layer and a network layer is constructed. The control layer represents the cost-effectiveness evaluation target for the entire life cycle of prefabricated buildings, and the network layer represents the key influencing factors selected by the DEMATEL method. The connections between the key influencing factors are determined based on their causal relationships. Subsequently, a judgment matrix is ​​constructed. ,in The number of key influencing factors in the network layer. Indicates factors under a certain criterion Relative factors The results of the importance comparison and The values ​​are taken according to the 1-9 scale, where 1 represents a factor. With factors Equal importance, 3 indicates factors Comparison Factors Slightly more important, 5 indicates factors Factors Clearly important, 7 indicates factor Factors Strongly important, 9 indicates factor Factors Extremely important, 2, 4, 6, and 8 are the intermediate values ​​of the above adjacent judgments.

[0066] Calculate the largest eigenvalue of the judgment matrix and the corresponding feature vector Through the consistency test formula Verify the consistency of the judgment matrix, where As a consistency indicator, The average random consistency index is determined by the number of factors in the network layer. Confirmed, when hour , hour , hour , hour , hour And so on. When When the judgment matrix satisfies the consistency requirement, the corresponding eigenvectors It can be used as a weight vector; if If so, the elements of the judgment matrix need to be adjusted until the consistency requirement is met.

[0067] The feature vectors that pass the consistency test are used as local weights for each factor in the network layer. Combining the mutual influence relationships between these factors, an unweighted supermatrix is ​​constructed. The unweighted supermatrix is... A weighted matrix is ​​constructed, where each element represents the local weights between corresponding factors, with elements corresponding to factors that have no mutual influence set to 0. Based on the influence ratio of each factor in the network layer, a weighted matrix is ​​also constructed. An dimensional matrix, where each element represents the percentage of influence of a given factor on other factors. The weighted supermatrix is ​​calculated. ,in For weighted matrices, This is an unweighted supermatrix. For a weighted supermatrix... Perform limit processing, i.e., calculate This yields a limiting hypermatrix, where all columns contain equal elements. These elements represent the combined weights of the corresponding key influencing factors. Based on key influencing factors and their comprehensive weights, a hierarchical and weighted evaluation index system for the cost-effectiveness of prefabricated buildings throughout their entire life cycle is constructed. The index system is divided into a target layer, a criterion layer, and an indicator layer. The target layer is the cost-effectiveness of prefabricated buildings throughout their entire life cycle, the criterion layer consists of performance criteria and cost criteria, and the indicator layer consists of various key influencing factors.

[0068] Furthermore, such as Figure 3 As shown, an SD model for evaluating the cost-effectiveness of prefabricated buildings is constructed. The model boundary is defined as the entire lifecycle of the prefabricated building, starting from the design phase, through production, construction, operation, and ending at the end of the lifecycle. The model boundary includes performance subsystems, cost subsystems, and external environment subsystems. Factors outside the model boundary are considered exogenous variables and are not included in the model's internal dynamic feedback analysis. The model's assumptions are clearly defined: the impact of extreme natural disasters, war, and other force majeure events on the cost-effectiveness of prefabricated buildings is ignored; component prices fluctuate according to a preset growth rate during the simulation period, which is determined based on historical industry data and market trend analysis; the technological level of prefabricated buildings remains stable at each stage, with no breakthrough technological changes.

[0069] Based on the evaluation index system and key influencing factors, a causal loop diagram representing the feedback relationships of the performance subsystem, cost subsystem, and external environment subsystem is drawn. This diagram includes reinforcing loops and regulating loops. A reinforcing loop refers to the feedback effects between factors that continuously strengthen the system state, while a regulating loop refers to the feedback effects between factors that cause the system state to stabilize. For example, increased component standardization reduces manufacturing costs, which in turn improves cost-effectiveness. Improved cost-effectiveness promotes the adoption of prefabricated buildings, further driving up component standardization and forming a reinforcing loop. Conversely, increased operation and maintenance costs reduce cost-effectiveness, which prompts companies to optimize operation and maintenance plans, thereby reducing operation and maintenance costs and forming a regulating loop.

[0070] Transform the causal loop diagram into a stock-flow diagram, defining the stock variable as the cumulative performance value. and cumulative cost value Stock variables are the cumulative quantities of system state, reflecting the system's state level at a certain moment; flow variables are the performance increments at each stage. and cost increment , These correspond to the five stages of design, production, construction, operation, and decommissioning. The flow variable is the rate of change of the stock variable per unit time, which determines the trend of the stock variable. The auxiliary variable is the quantified value of each key influencing factor. The auxiliary variable affects the stock variable by influencing the flow variable.

[0071] Establish variable function equations: cumulative performance value equations ,in The initial performance value is 0. For the first Stage at moment The performance increment For the first The phase from the initial time to the time... Cumulative performance increment; performance increment at each stage The formula is ,in For the first The number of factors affecting stage performance For the first Phase 1 The combined weight of each performance influencing factor For the first Phase 1 Individual performance influencing factors at time Quantization value, For the first Phase 1 The performance conversion coefficient of each performance influencing factor is used to convert the quantified value of the factor into a performance increment value of a unified dimension.

[0072] Cumulative cost equation ,in The initial cost value is 0. For the first Stage at moment The cost increment, For the first The phase from the initial time to the time... Cumulative cost increments; cost increments at each stage The formula is ,in For the first The number of factors influencing stage costs For the first Phase 1 The combined weight of each cost influencing factor For the first Phase 1 Each cost influencing factor at time The cost quantification value, For the first Phase 1 The cost allocation coefficient for each cost influencing factor is used to reasonably allocate the cost of that factor to the corresponding stage.

[0073] Cost-effectiveness equation ,in For a moment The cost-effectiveness value of prefabricated buildings throughout their entire life cycle reflects the ratio of the overall performance of the prefabricated building to its cumulative cost at that moment.

[0074] Furthermore, the scenario variables for different external environments include the quantitative value of labor price, policy incentive coefficient, technology maturity index, and transportation radius. The quantitative value of labor price is the labor cost per unit of working hour; the quantitative value of policy incentive for prefabricated buildings is the quantitative value of the degree of policy incentive for prefabricated buildings, with a value range of 0-2, where 0 indicates no policy incentive, 1 indicates moderate policy incentive, and 2 indicates strong policy incentive; the quantitative value of technology maturity is the quantitative value of the maturity of technologies related to prefabricated buildings, with a value range of 0-1, where a larger value indicates more mature technology; and the quantitative value of transportation radius is the distance from the prefabricated component production site to the construction site. Each scenario variable is calibrated using industry statistical data and then input into the SD model.

[0075] Differentiated parameters for various prefabricated structural systems include structural safety performance parameters, green environmental performance parameters, manufacturing cost parameters, and operation and maintenance cost parameters. Structural safety performance parameters include component tensile strength and compressive strength, etc. Green environmental performance parameters include material recycling rate and carbon emission reduction, etc. Manufacturing cost parameters include unit component production cost and mold amortization cost, etc. Operation and maintenance cost parameters include annual maintenance cost per unit area and energy consumption cost, etc. Each parameter is determined based on the technical standards and engineering practice data of the corresponding structural system and then input into the SD model.

[0076] The simulation was implemented using Vensim software, with a simulation step size of one month and a simulation period equal to the design service life of the prefabricated building. During the simulation, sensitivity analysis was used to verify the model's stability. The sensitivity analysis formula is as follows: ,in For the rate of change in cost-effectiveness, Set a preset sensitivity threshold for the rate of change of key influencing factors. ,when The model is then judged to meet stability requirements. After the simulation is completed, the full life cycle cost-effectiveness value and evolution curve of the prefabricated building under different time periods, different prefabricated structural systems, and different external environmental scenarios are output, forming a complete evaluation result.

[0077] This implementation, through the integration of a full life-cycle indicator system and the DEMATEL-ANP-system dynamics model, achieves dynamic quantification and multi-scenario simulation of the cost-effectiveness of prefabricated buildings, characterizes the causal feedback and evolution laws among factors, and provides scientific decision-making support for structural selection and policy formulation.

[0078] Based on Example 1, this example selects publicly available datasets and industry statistics as the empirical basis. The data sources include the "China Prefabricated Building Development Report", the "White Paper on Building Industrialization Industry", and the engineering case database published by the Ministry of Housing and Urban-Rural Development. Through bibliometrics and data cleaning, the full life cycle cost and performance data of 126 prefabricated building projects nationwide from 2018 to 2023 were selected, covering four mainstream structural systems: MIC modular system, GS-Building prefabricated steel structure system, CMC system and aluminum alloy structure system, effectively avoiding the bias caused by a single project or region.

[0079] Based on the selected key influencing factors and the calculated comprehensive weights, a prefabricated building cost-effectiveness evaluation SD model was constructed. The simulation step size was set to 1 month, and the simulation period was 50 years. Differential parameters of four types of structural systems and multiple sets of external environmental scenario variables were input. First, a baseline scenario was set (labor price 85, policy incentive coefficient 1.0, technology maturity index 0.8, transportation radius 15). The cost-effectiveness data of the four types of structural systems throughout their entire life cycle was obtained through model simulation. Data from key time nodes were extracted and compiled into Table 1. As shown in Table 1, the cost-effectiveness of the MIC modular system steadily increased from 1.02 in year 1 to 2.23 in year 50, with a compound annual growth rate (CAGR) of 1.58%; the GS-Building prefabricated steel structure system increased from 1.05 in year 1 to 2.05 in year 50, with a CAGR of 1.42%; the CMC system increased from 1.03 in year 1 to 2.14 in year 50, with a CAGR of 1.51%; and the aluminum alloy structure system increased from 1.01 in year 1 to 2.19 in year 50, with a CAGR of 1.55%. The cost-effectiveness of each system increased rapidly in the first 10 years, with an average increase of 68.3% from year 1 to year 10. The growth rate gradually slowed down thereafter, with an average increase of 32.7% from year 10 to year 50, which is consistent with the evolution of cost and performance throughout the entire life cycle of prefabricated buildings.

[0080] Table 1. Cost-effectiveness of four structural systems throughout their entire lifecycle at key milestones under the baseline scenario.

[0081] To comprehensively analyze the impact of external environmental factors on cost-effectiveness, six different external environmental scenarios were set up, covering a multi-dimensional combination of labor prices (65, 85, 105), policy incentive coefficients (0.6, 1.0, 1.4), technology maturity index (0.6, 0.8, 1.0), and transportation radius (10, 15, 20, 25). Through model simulation, the 50-year average cost-effectiveness, highest cost-effectiveness, lowest cost-effectiveness, and standard deviation of the four structural systems under each scenario were obtained. The results are shown in Table 2. Data shows that Scenario 6 (labor price 65, policy incentive coefficient 1.4, technology maturity index 1.0, transportation radius 10) is the optimal scenario, with the highest average cost-effectiveness across all four systems. The MIC module system ranks first with a score of 2.41, a 21.6% improvement over the baseline scenario (Scenario 3). Scenario 1 (labor price 105, policy incentive coefficient 0.6, technology maturity index 0.6, transportation radius 25) is the worst scenario, with the lowest average cost-effectiveness across all systems. The GS-Building prefabricated steel structure system has a score of only 1.62, a 24.5% decrease from the optimal scenario. From the standard deviation data, the cost-effectiveness of the GS-Building prefabricated steel structure system is most affected by external environmental fluctuations, with a standard deviation of 0.18. The aluminum alloy structure system exhibits the strongest stability, with a standard deviation of 0.13, providing refined data support for structural system selection under different environmental conditions.

[0082] Table 2. Cost-effectiveness statistics of four types of structural systems under different external environmental scenarios.

[0083] To visually represent the lifecycle cost-performance evolution of the four structural systems under the baseline scenario, lifecycle cost-performance evolution curves are plotted, such as... Figure 4 As shown, the four curves correspond to the cost-effectiveness trends of the four structural systems. It is clear from the graph that all four curves showed a rapid upward trend in the first 10 years, the growth rate slowed from the 10th to the 15th year, and the curves gradually stabilized after the 15th year. The curve for the MIC modular system remained at the top, while the curve for the GS-Building prefabricated steel structure system remained at the bottom. The curves for the aluminum alloy structure system and the CMC system intersected in the middle period, and in the later period, the aluminum alloy structure system was slightly higher than the CMC system. The cost-effectiveness gap and evolution trend of the four systems throughout their entire life cycle are visually represented by these curves.

[0084] To analyze the sensitivity of a single external environmental factor to cost-effectiveness in depth, a four-factor sensitivity analysis diagram is drawn, such as... Figure 5 As shown, Figure 5 (a) shows the average cost-effectiveness changes of the four systems when the labor price is 65, 85, and 105; Figure 5 (b) shows the average cost-effectiveness changes of the four systems when the policy incentive coefficients are 0.6, 1.0, and 1.4; Figure 5 (c) is the technology maturity index, showing the average cost-effectiveness changes of the four systems at technology maturity indices of 0.6, 0.8, and 1.0; Figure 5 (d) represents the transportation radius, showing the changes in average cost-effectiveness for the four systems at transportation radii of 10, 15, 20, and 25. As can be seen from the subplot, rising labor costs have the strongest inhibitory effect on the cost-effectiveness of the GS-Building prefabricated steel structure system; for every 20-radius increase, the average cost-effectiveness decreases by approximately 8.3%. Increased policy incentive coefficients have the most significant promoting effect on the GS-Building prefabricated steel structure system; for every 0.4 increase, the average cost-effectiveness improves by approximately 10.5%. Increased technology maturity index has a relatively balanced promoting effect on all systems; for every 0.2 increase, the average cost-effectiveness improves by approximately 4.2%-5.1%. After the transportation radius exceeds 15, the cost-effectiveness of all systems decreases linearly; for every 5-radius increase, the average cost-effectiveness decreases by approximately 3.8%-4.5%, providing data support for targeted optimization of the external environment.

[0085] To compare the cost-effectiveness of the four structural systems at different stages of their entire life cycle, a stage cost-effectiveness comparison chart is drawn, such as... Figure 6 As shown, the entire life cycle is divided into six stages: design-production stage (1-2 years), construction stage (3-4 years), pre-operation stage (5-15 years), mid-operation stage (16-30 years), post-operation stage (31-49 years), and decommissioning stage (50 years). The average cost-effectiveness of various systems in each stage is calculated and presented in a bar chart. As shown in the figure, during the design-production stage, the GS-Building prefabricated steel structure system had the highest average cost-effectiveness (1.29), while the aluminum alloy structure system had the lowest (1.13). During the construction stage, the cost-effectiveness gap between various systems narrowed, with an average cost-effectiveness between 1.42 and 1.48. In the early operation stage, the cost-effectiveness advantage of the MIC modular system began to emerge (1.78). During the mid and late operation stages, the cost-effectiveness of the MIC modular system and the aluminum alloy structure system continued to lead, with average cost-effectiveness reaching 2.01-2.16 and 1.98-2.14, respectively. In the decommissioning stage, the cost-effectiveness of all systems decreased slightly, but remained at a high level, with the MIC modular system ranking first at 1.89. The cost-effectiveness distribution characteristics at each stage provide a clear direction for optimizing the entire life cycle cost and performance.

[0086] To comprehensively present the cost-effectiveness differences of the four types of structural systems under different scenarios, such as Figure 7As shown, three typical scenarios were selected: the baseline scenario, the optimal scenario (Scenario 6), and the worst scenario (Scenario 1). It can be clearly seen from the figure that the radar curve coverage is the largest under the optimal scenario, the smallest under the worst scenario, and the baseline scenario is in the middle. The MIC module system has the longest radius (2.41) under the optimal scenario, while the GS-Building prefabricated steel structure system has the shortest radius (1.62) under the worst scenario. The cost-performance advantages and disadvantages of various systems under different scenarios are clearly presented through the shape differences of the radar chart, providing an intuitive visual basis for the selection of structural systems under multiple scenarios.

[0087] Meanwhile, the above fully verifies that the evaluation method of this application can accurately capture the cost-effectiveness differences of different structural systems at different time points and under different external environments. The evaluation results have quantitative, reliable and visual characteristics, which can provide scientific and comprehensive decision support for the selection of prefabricated building structural systems, regional differentiated promotion and policy formulation.

[0088] The above are merely preferred embodiments of the present invention and are not intended to limit the scope of protection of the present invention. For those skilled in the art, the present invention can have various modifications and variations. Any changes, modifications, substitutions, integrations, and parameter changes made to these embodiments within the spirit and principles of the present invention, without departing from the principles and spirit of the present invention, through conventional substitutions or to achieve the same function, fall within the scope of protection of the present invention.

Claims

1. A prefabricated building full life cycle cost performance evaluation method based on system dynamics, characterized in that, include: To obtain the performance and cost influencing factors throughout the entire life cycle of prefabricated buildings, the entire life cycle includes the design stage, production stage, construction stage, operation stage and decommissioning stage; The causal relationships among the influencing factors were analyzed using the DEMATEL method to identify key influencing factors and their interaction pathways. Using the causal relationship as input to the ANP network, the comprehensive weight of each key influencing factor is calculated using the ANP method, and a cost-effectiveness evaluation index system for the entire life cycle of prefabricated buildings is constructed. Based on the system dynamics method, and combined with the evaluation index system and comprehensive weight, a prefabricated building cost-effectiveness evaluation SD model is constructed, which includes causal loop diagrams, stock flow diagrams and variable function equations. By inputting differentiated parameters of different prefabricated structural systems and scenario variables of different external environments, the cost-effectiveness evolution simulation is performed through the SD model, and the cost-effectiveness evaluation results of the prefabricated building throughout its entire life cycle are output. 2.The system dynamics-based evaluation method of the cost performance of a full life cycle of a fabricated building according to claim 1, characterized in that, The performance and cost influencing factors throughout the entire life cycle of prefabricated buildings are obtained as follows: the performance influencing factors include structural safety performance factors, green and environmental protection performance factors, functional performance factors, and durability performance factors; the cost influencing factors include design cost factors, manufacturing cost factors, transportation and installation cost factors, operation and maintenance cost factors, and scrapping and recycling cost factors.

3. The method for evaluating the cost-effectiveness of prefabricated buildings throughout their entire life cycle based on system dynamics as described in claim 2, characterized in that, The performance and cost influencing factors throughout the entire life cycle of prefabricated buildings are identified by constructing an initial set of influencing factors. and collect Expert rating data The importance score for each factor is calculated using the following formula: Filter out Factors that serve as influencing factors, among which This is a preset importance threshold.

4. The system dynamics-based assembly type building life cycle cost-effectiveness evaluation method according to claim 4, characterized in that, The analysis of the causal relationships among the influencing factors using the DEMATEL method includes: Constructing the direct influence matrix of influencing factors ,in Indicator Factors Factors The degree of direct impact; through the formula Direct Influence Matrix Normalization is performed to obtain the normalized matrix. ; Calculate the comprehensive impact matrix ,in It is the identity matrix; Calculate the influence of each factor And the degree of influence ,pass Characteristic factor centrality Characterizing the causal degree of factors, selecting those that simultaneously meet the criteria. and The factors are considered as key influencing factors; among them, Take the average of the centralities of all factors. Take the average of the absolute values ​​of the causal degree of all factors.

5. The method for evaluating the cost-effectiveness of prefabricated buildings throughout their entire life cycle based on system dynamics as described in claim 1, characterized in that, The calculation of the comprehensive weights of each key influencing factor using the ANP method includes: Based on the causal relationships obtained by the DEMATEL method, an ANP network structure containing a control layer and a network layer is constructed. The control layer is the cost-performance evaluation target, and the network layer is the key influencing factors. Construct the judgment matrix ,in The number of factors in the network layer. and ; Calculate the eigenvalues ​​of the judgment matrix and eigenvectors Through the consistency test formula Verify consistency, where , As the average random consistency index, when The test was passed; the comprehensive weights of each key influencing factor were obtained through supermatrix calculation and limit supermatrix solution. .

6. The method for evaluating the cost-effectiveness of prefabricated buildings throughout their entire life cycle based on system dynamics as described in claim 1, characterized in that, The construction of the prefabricated building cost-effectiveness evaluation SD model includes: The model boundary is defined as the entire life cycle of prefabricated buildings, and the model assumptions are clearly defined. Based on the evaluation index system and key influencing factors, a causal loop diagram representing the feedback relationships of the performance subsystem, cost subsystem, and external environment subsystem is drawn. This causal loop diagram is then transformed into a stock-flow diagram, defining the stock variable as the cumulative performance value. and cumulative cost value The flow variable represents the performance increment at each stage. and cost increment The auxiliary variables are the quantified values ​​of each key influencing factor; Establish the function equation with variables, including: Cumulative performance equation: , These are the initial performance values. Corresponding to the five stages of the entire life cycle; Cumulative cost equation: , This is the initial cost value; Cost-effectiveness equation: , for Value for money at all times.

7. The method for evaluating the cost-effectiveness of prefabricated buildings throughout their entire life cycle based on system dynamics as described in claim 6, characterized in that, The performance increments at each stage The formula is: ,in For the first The number of factors affecting stage performance The corresponding factors are weighted comprehensively. For factor quantification values, This is the performance conversion factor.

8. The method for evaluating the cost-effectiveness of prefabricated buildings throughout their entire life cycle based on system dynamics as described in claim 6, characterized in that, Cost increments at each stage The formula is: ,in For the first Number of factors affecting stage costs The corresponding factors are weighted comprehensively. For factor cost quantification, This is the cost allocation coefficient.

9. The method for evaluating the cost-effectiveness of prefabricated buildings throughout their entire life cycle based on system dynamics as described in claim 1, characterized in that, The scenario variables for different external environments include quantitative values ​​of labor prices, policy incentive coefficients, technology maturity index, and quantitative values ​​of transportation radius. Each scenario variable is calibrated using industry statistical data and then input into the SD model.

10. The method for evaluating the cost-effectiveness of prefabricated buildings throughout their entire life cycle based on system dynamics as described in claim 1, characterized in that, The differentiated parameters for the various prefabricated structural systems include structural safety performance parameters, environmental protection performance parameters, manufacturing cost parameters, and operation and maintenance cost parameters. Each parameter is determined based on the technical standards and engineering practice data of the corresponding structural system and then input into the SD model. These parameters are then used in simulation to assess sensitivity. The stability of the model is analyzed and verified using the following formula: ,when The model is then judged to meet the evaluation requirements. For preset sensitivity, where For the rate of change in cost-effectiveness, The rate of change of key influencing factors.

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