BIM (Building Information Modeling)-based carbon emission dynamic evaluation and prediction system

Abstract

The invention relates to the technical field of carbon emission evaluation, in particular to a BIM-based carbon emission dynamic evaluation and prediction system, which comprises a data extraction and matching module, a carbon emission calculation module, a full life cycle analysis module and a result visualization module. According to the method, data of the building materials are automatically extracted and are in butt joint with the carbon emission database, so that the capacity of accurately matching the attributes and the number of the materials is achieved, calculation of the carbon emission is more detailed, the method further has the personalized analysis capacity, each material and each construction activity are independently calculated, more detailed data support is provided, and the calculation efficiency is improved. Carbon emission of the whole life cycle is monitored and predicted in real time, the practicability of data is enhanced, environmental changes can be responded more quickly, effective carbon emission reduction measures are implemented, a data visualization technology is applied, carbon emission information becomes more intuitive and understandable, information propagation and application efficiency is enhanced, and the cognition and participation degree of the public and professionals to environmental protection problems is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon emission assessment, and in particular to a carbon emission dynamic assessment and prediction system based on BIM. Background Art

[0002] The field of carbon emission assessment technology focuses on quantifying, monitoring and analyzing carbon emissions to achieve environmental protection goals, using a variety of methods and tools to assess the overall carbon footprint of individuals, organizations or systems within a specific period of time, with a focus on high-emission industries such as construction, transportation and industry. Carbon assessment technologies include life cycle assessment (LCA), cloud-based monitoring systems, AI and big data analysis, etc., to provide accurate and dynamic emission data, which not only helps achieve carbon reduction goals, but also promotes policy formulation and optimization of sustainable development strategies.

[0003] Among them, BIM's building carbon emission dynamic assessment and prediction system combines the detailed building data of BIM technology and the methodology of carbon emission assessment. Through this system, the carbon emissions of construction projects can be monitored and predicted in real time, helping project managers and decision makers make more environmentally friendly choices during the design, construction and operation process. Its main uses include optimizing building design to reduce environmental impact, monitoring carbon emissions during the construction process, and evaluating energy efficiency and carbon footprint during the building operation stage, thereby supporting the goals of green buildings and sustainable urban development.

[0004] Existing technologies can usually only provide static or one-time carbon footprint data, and lack a quick response to real-time changes. This technical limitation leads to insufficient real-time and accuracy of carbon emission monitoring in actual operations, especially in the building and construction stages. For example, when traditional methods monitor carbon emissions during construction, data updates are often delayed, resulting in inconsistencies between estimated data and actual emissions, affecting the timeliness and effectiveness of carbon reduction measures, making it difficult to accurately assess the specific contribution of each stage to total carbon emissions, and may lead to inefficiency and waste of resources in strategy formulation and implementation. Summary of the invention

[0005] The purpose of the present invention is to solve the shortcomings in the prior art and propose a carbon emission dynamic assessment and prediction system based on BIM.

[0006] In order to achieve the above object, the present invention adopts the following technical solution: The carbon emission dynamic assessment and prediction system based on BIM includes:

[0007] The data extraction and matching module automatically extracts the type and quantity of building materials based on BIM, connects BIM data with the database associated with carbon emissions, verifies and matches the corresponding material properties and quantities, and generates project-level carbon emission metadata;

[0008] The carbon emission calculation module uses the project-level carbon emission metadata to perform data classification processing, divides the data according to differentiated material types and construction activities, independently calculates the carbon emission standard factor for each data item based on the division results, and summarizes and organizes the calculation results to form itemized carbon emission information;

[0009] The full life cycle analysis module receives the itemized carbon emission information, summarizes the relevant data according to the building stage, integrates the analysis stage data through time series analysis, calculates the contribution rate of each stage to the total carbon emission based on the integration results, and makes trend predictions, comprehensively evaluates the building's full life cycle carbon emissions, and outputs an overview of the building's full life cycle carbon emissions;

[0010] The result visualization module calculates the carbon emission proportion of each construction stage based on the overview of the building's full-cycle carbon emissions, converts the data into charts through data visualization technology, determines the carbon emission change trend of each construction stage based on the conversion results, and generates carbon emission visual analysis results.

[0011] As a further solution of the present invention, the steps for obtaining the project-level carbon emission metadata are:

[0012] Scan the BIM model, identify and record the type and corresponding quantity of each building material, and use the formula,

[0013]

[0014] Calculate the total amount of material N i , get the total material list, where x ij is the quantity of material i included in the jth component in the model, and k represents the total number of components;

[0015] Based on the total material list, matching with the database, using the formula,

[0016] C i =N i ×e i ×(1+δ i )

[0017] Calculate the estimated carbon emission C of the i-th material i , generate material carbon emission estimates, where e i is the unit carbon emission factor, δ i is the adjustment factor based on the environment in which the material is used;

[0018] Using the estimated carbon emissions of the materials, combined with the project scale and material usage frequency, the formula is used:

[0019]

[0020] Calculate the total carbon emissions M of the entire project and obtain the project-level carbon emissions metadata, where w i is the weight adjusted according to the project characteristics, and n represents the type of material.

[0021] As a further solution of the present invention, the steps of dividing the differentiated material types and construction activities are:

[0022] extracting data from the project-level carbon emission metadata, identifying material types and construction activity characteristics, performing preliminary classification operations, and generating preliminary classification information;

[0023] Using the preliminary classification information, the data is classified into detailed categories using complexity analysis, using the formula,

[0024]

[0025] Calculate the weighted classification value D and output the refined classification result, where S j The classified data points obtained for preliminary classification information, d j is the weight coefficient, emphasizing the classification accuracy of the data item, and m represents the number of categories in the preliminary classification information;

[0026] Based on the refined classification results, normalization processing is performed using the formula:

[0027]

[0028] Calculate the normalized value F, build and output the classification framework, where D q is the output of the refined classification result, It represents the sum of all classified data and is used for normalization. p represents the number of data points.

[0029] As a further solution of the present invention, the steps for obtaining the itemized carbon emission information are:

[0030] Based on the classification framework, a separate calculation is performed for each classification using the carbon emission standard factor, using the formula,

[0031]

[0032] Calculate the classified carbon emissions E, where F i is the normalized data item in the classification framework, f i is the carbon emission standard factor, which is used to enhance the accuracy of factor application. U represents the data item F i the number of

[0033] Based on the above classified carbon emissions, combined with national standards, the formula is adopted:

[0034]

[0035] Calculate and generate adjusted carbon emission data A, where E j represents the carbon emissions of different categories, ξ j is the adjustment factor used to meet national standards, r represents E j The classification type;

[0036] The adjusted carbon emission data are summarized and sorted to compile itemized carbon emission information.

[0037] As a further solution of the present invention, the steps of performing the integrated analysis phase data by time series analysis are:

[0038] Receive the itemized carbon emission information, collect carbon emission data for each stage of the building, preliminarily organize the data and store them in a database to generate a preliminarily organized data set;

[0039] Based on the preliminary collated data set, it is classified and summarized according to the construction stage, using the formula,

[0040]

[0041] The generation stage classifies and summarizes the data S, where K j is the data point in stage j, u j is the classification coefficient, indicating the importance of the difference stage;

[0042] By using the classified and aggregated data of the above stages, time series analysis is performed, and the trend of data changes is integrated and analyzed. The formula is used.

[0043]

[0044] Calculate the integrated carbon emission data T and generate time series analysis results, where S t represents the summary data of the tth category, a t is the weighting coefficient in time series analysis, used to ensure accurate representation of time dependence, and L represents the number of categories.

[0045] As a further solution of the present invention, the steps for obtaining the overview of carbon emissions throughout the building life cycle are:

[0046] Based on the time series analysis results, the formula is adopted:

[0047]

[0048] Calculate the weighted contribution rate G of the construction phase to the total carbon emissions and generate the phase carbon emission contribution rate data, where T t is the time series result of the tth stage, b t is the contribution evaluation coefficient;

[0049] Using the carbon emission contribution rate data of the above stage, the future carbon emission trend is predicted, using the formula:

[0050]

[0051] Calculate the predicted value P of the future total carbon emission trend and generate the trend prediction result, where G t is the carbon emission contribution rate of the stage, γ m and α are prediction parameters used to ensure the accuracy and adaptability of the prediction, and exp(·) represents the natural exponential function;

[0052] Integrate the trend forecast results, evaluate the carbon emissions throughout the life cycle, and organize and generate an overview of the carbon emissions throughout the life cycle.

[0053] As a further solution of the present invention, the steps of converting the data into a chart are:

[0054] Based on the overview of the building’s full-cycle carbon emissions, collect and record the carbon emissions of each building stage z1, z2, ..., z n , forming the carbon emission data set Z = {z1, z2, z i , ..., z H}, where z i represents the carbon emissions in the i-th stage;

[0055] Based on the carbon emission data set of the said stage, the formula is adopted:

[0056]

[0057] Calculate the carbon emission ratio B in the i-th stage i , output the carbon emission ratio set, where Y i is the carbon emission coefficient of the building type or material used in stage i, and H represents the number of data points in the stage carbon emission data set;

[0058] Based on the carbon emission ratio set, data visualization technology is applied to convert the data into charts to generate data visualization results.

[0059] As a further solution of the present invention, the steps for obtaining the carbon emission visual analysis results are:

[0060] Based on the data visualization results, trend information is extracted and the carbon emission trend of each stage is analyzed. The formula is used.

[0061]

[0062] Calculate the stage trend deviation value V and generate preliminary trend analysis results, where: is the average value of the carbon emission ratio set; using the preliminary trend analysis results, the carbon emission trend is deeply analyzed, using the formula,

[0063]

[0064] Calculate the standardized coefficient of variation R to obtain detailed trend confirmation results, where σ represents the standard deviation, which enhances the flexibility and sensitivity of trend analysis;

[0065] According to the detailed trend confirmation results, significant trend changes are highlighted, the carbon emission trends in each stage are reflected, and the carbon emission visual analysis results are generated.

[0066] Compared with the prior art, the advantages and positive effects of the present invention are:

[0067] In the present invention, by automatically extracting the data of building materials and connecting with the carbon emission database, the ability to accurately match material properties and their quantities is achieved, so that the calculation of carbon emissions is not only more detailed, but also has personalized analysis capabilities. Each material and construction activity is calculated independently to provide more detailed data support, real-time monitoring and prediction of carbon emissions throughout the life cycle, and enhanced data practicability. It can respond to environmental changes more quickly and implement effective carbon emission reduction measures. Through the application of data visualization technology, carbon emission information becomes more intuitive and easy to understand, which enhances the efficiency of information dissemination and application, thereby enhancing the public and professionals' awareness and participation in environmental issues. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 is a system flow chart of the present invention;

[0069] Figure 2 A flowchart for obtaining project-level carbon emission metadata of the present invention;

[0070] Figure 3 A flow chart for the division of differentiated material types and construction activities of the present invention;

[0071] Figure 4 This is a flowchart for obtaining itemized carbon emission information of the present invention;

[0072] Figure 5 It is an execution flow chart of the present invention integrating the analysis phase data through time series analysis;

[0073] Figure 6 A flowchart for obtaining an overview of the carbon emissions of a building throughout its life cycle according to the present invention;

[0074] Figure 7 A flowchart of the implementation of converting data into a chart for the present invention;

[0075] Figure 8This is a flow chart for obtaining the visual analysis results of carbon emissions according to the present invention. DETAILED DESCRIPTION

[0076] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0077] In the description of the present invention, it should be understood that the terms "length", "width", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate positions or positional relationships based on the positions or positional relationships shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, in the description of the present invention, "multiple" means two or more, unless otherwise clearly and specifically defined.

[0078] See also Figure 1 The BIM-based carbon emission dynamic assessment and prediction system includes:

[0079] The data extraction and matching module automatically extracts the type and quantity of building materials based on BIM, connects BIM data with the database associated with carbon emissions, verifies and matches the corresponding material properties and quantities, and generates project-level carbon emission metadata;

[0080] The carbon emission calculation module uses project-level carbon emission metadata to classify data, divide it according to differentiated material types and construction activities, and independently calculate the carbon emission standard factor for each data based on the division results, and summarize and organize the calculation results to form itemized carbon emission information;

[0081] The full life cycle analysis module receives itemized carbon emission information, summarizes relevant data according to the building stage, integrates the analysis stage data through time series analysis, calculates the contribution rate of each stage to the total carbon emission based on the integration results, and makes trend forecasts, comprehensively evaluates the carbon emissions of the building throughout its life cycle, and outputs an overview of the carbon emissions of the building throughout its life cycle;

[0082] The result visualization module is based on the overview of carbon emissions throughout the building cycle, calculates the carbon emission ratio of each construction stage, converts the data into charts through data visualization technology, determines the carbon emission change trend of each construction stage based on the conversion results, and generates carbon emission visual analysis results.

[0083] Project-level carbon emission metadata includes material type and material quantity. Itemized carbon emission information includes classification processing results, independent calculation results and summary data. The overview of carbon emissions throughout the building cycle includes stage classification summary, total contribution rate calculation results and trend forecast results. The visual analysis results of carbon emissions include carbon emission ratio charts and change trend charts.

[0084] See also Figure 2 , the steps to obtain project-level carbon emission metadata are:

[0085] Scan the BIM model, identify and record the type and corresponding quantity of each building material, and use the formula,

[0086]

[0087] Calculate the total amount of material N i , get the total material list, where x ij is the quantity of material i included in the jth component in the model, and k represents the total number of components;

[0088] Based on the total material list, match it with the database and use the formula,

[0089] C i =N i ×e i ×(1+δ i )

[0090] Calculate the estimated carbon emission C of the i-th material i , generate material carbon emission estimates, where e i is the unit carbon emission factor, δ i is the adjustment factor based on the environment in which the material is used;

[0091] Using the material carbon emission estimation results, combined with the project scale and material use frequency, the formula is adopted.

[0092]

[0093] Calculate the total carbon emissions M of the entire project and obtain the project-level carbon emissions metadata, where w i is the weight adjusted according to the project characteristics, and n represents the type of material.

[0094] Assume that a BIM model includes 3 components, and the quantities of material i in these 3 components are 5, 3 and 2 respectively.

[0095] but:

[0096] N i =x i1 +x i2 +x i3=5+3+2=10

[0097] Indicates that the element of material i is used 10 times in the BIM model of the entire building project, providing a quantitative basis to assess the contribution of the use of this material to the entire building structure. For example, if material i is concrete, this number can be used to assess the need for structural strength and stability, and is also the basis for subsequent carbon emissions calculations.

[0098] Assume that the unit carbon emission factor of material i is e i 0.5kg (CO2 per unit), environmental adjustment factor δ i is 0.1, combined with the above calculation results N i =10, then:

[0099] C i =10×0.5×(1+0.1)=10×0.5×1.1=5.5

[0100] This value represents the total carbon emissions of 5.5 kg (CO2 per unit) from production to transportation to use of the material i, taking into account the quantity of the material and the carbon emission factor per unit of material, and reflecting the carbon emission impact under specific environmental conditions through the environmental adjustment factor.

[0101] Assume that there are only two materials (n=2), and the carbon emissions have been calculated to be 5.5 kg and 3 kg.

[0102] Assuming the weight factors w1=1 and w2=1, substituting into the formula, we get:

[0103] M=(5.5×1)+(3×1)=5.5+3=8.5

[0104] The result M = 8.5 kg is the total carbon emissions of the entire project. This result takes into account the carbon emission contributions of all materials used and the weighted average reflects the frequency and importance of different materials in the project.

[0105] See also Figure 3 , the steps for differentiating material types and construction activities are:

[0106] Extract data from project-level carbon emission metadata, identify material types and construction activity characteristics, perform preliminary classification operations, and generate preliminary classification information;

[0107] Using the preliminary classification information, complexity analysis is applied to refine the data classification, using the formula,

[0108]

[0109] Calculate the weighted classification value D and output the refined classification result, where Sj The classified data points obtained for preliminary classification information, d j is the weight coefficient, emphasizing the classification accuracy of the data item, and m represents the number of categories in the preliminary classification information;

[0110] Based on the refined classification results, normalization is performed using the formula:

[0111]

[0112] Calculate the normalized value F, build and output the classification framework, where D q is the output of the refined classification result, It represents the sum of all classified data and is used for normalization. p represents the number of data points.

[0113] Assume that the preliminary classification information can be divided into two categories, and the data of each category are as follows:

[0114] S1=15

[0115] S2=11

[0116] The weight coefficient is set as:

[0117] d1=0.7

[0118] d2=0.3

[0119] Substituting into the formula, we get:

[0120] D=0.7×15 2 +0.3×11 2

[0121] =0.7×225+0.3×121=157.5+36.3=193.8

[0122] D = 193.8 means that under more detailed classification standards, the data is reweighted and squared to emphasize the importance of differences. This value is used for further data processing or decision analysis, such as deciding which materials or construction activities should be regulated.

[0123] Assume that the output in the previous calculation is two data points:

[0124] D1=193.8

[0125] D2=106.2

[0126] Substituting into the formula, we get:

[0127]

[0128] F = 1.0 means that the normalized data can equally reflect the contribution of each classification and support further decision-making or report production without bias. The results illustrate the relative importance of each component in the classification process and ensure the consistency and comparability of the final analysis.

[0129] See also Figure 4 , the steps to obtain itemized carbon emission information are:

[0130] Based on the classification framework, the carbon emission standard factor is calculated independently for each classification using the formula,

[0131]

[0132] Calculate the classified carbon emissions E, where F i is the normalized data item in the classification framework, f i is the carbon emission standard factor, which is used to enhance the accuracy of factor application. U represents the data item F i the number of

[0133] Based on the classified carbon emissions, combined with national standards, the formula is adopted.

[0134]

[0135] Calculate and generate adjusted carbon emission data A, where E j represents the carbon emissions of different categories, ξ j is the adjustment factor used to meet national standards, r represents E j The classification type;

[0136] The adjusted carbon emission data are summarized and collated to compile item-by-item carbon emission information.

[0137] Assume that there are two types of material data, obtained according to the aforementioned classification framework:

[0138] F1 = 0.646 (more environmentally sensitive material).

[0139] F2=0.354 (material with less environmental impact).

[0140] The carbon emission standard factor is set as:

[0141] f1=1.2

[0142] f2=0.8

[0143] Substituting into the formula, we get:

[0144] E=1.2×0.75 3 +0.8×0.25 3

[0145] =1.2×0.421875+0.8×0.015625

[0146] =0.50625+0.0125=0.51875

[0147] E = 0.51875 represents the total carbon emissions after considering the weight of the material environmental impact. The value reflects the total carbon emissions of different materials or construction activities weighted by their environmental sensitivity, which helps to formulate more effective environmental protection policies.

[0148] Assume that the carbon emissions calculated above are adjusted in two parts:

[0149] E1=0.4

[0150] E2=0.11875

[0151] The adjustment factor is set as:

[0152] ξ1=1.05

[0153] ξ2=0.95

[0154] Substituting into the formula, we get:

[0155]

[0156] A=0.566 means that the comprehensive carbon emission data calculated under the adjustment factor of the national standard is used for reporting or further environmental action planning to ensure that the project complies with regulatory requirements.

[0157] See also Figure 5 ,The execution steps of integrating the analysis phase data through time series analysis are:

[0158] Receive itemized carbon emission information, collect carbon emission data for each stage of the building, preliminarily organize the data and store it in the database to generate a preliminary organized data set;

[0159] Based on the preliminary collated data set, the data were classified and summarized according to the construction stage, using the formula,

[0160]

[0161] The generation stage classifies and summarizes the data S, where K j is the data point in the jth stage, u j is the classification coefficient, indicating the importance of the difference stage;

[0162] Use stage classification to summarize data, conduct time series analysis, integrate and analyze data change trends, and use formulas.

[0163]

[0164] Calculate the integrated carbon emission data T and generate time series analysis results, where S t represents the summary data of the tth category, a t is the weighting coefficient in time series analysis, used to ensure accurate representation of time dependence, and L represents the number of categories.

[0165] Assume there are 3 data points, and the classification coefficients are:

[0166] u1=1.0,K1=100kgCO2

[0167] u2=0.5,K2=150kgCO2

[0168] u3=1.5,K3=200kgCO2

[0169] Substitute into the formula and calculate:

[0170]

[0171] S≈285kg shows the normalized carbon emission data, taking into account the importance of the stage and the amount of carbon emissions, providing preparation for time series analysis.

[0172] Combining the above calculation results and assuming the weights of the three stages

[0173] a1=0.3

[0174] a2=0.4

[0175] a3=0.3

[0176] To simplify the process, assume that the three stages are the same:

[0177] S1=285, S2=285, S3=285

[0178] Substitute into the formula and calculate:

[0179]

[0180] T = 285 kgCO2 represents the integrated carbon emission data after time weighting, which reflects the average carbon emission trend of the entire construction project stage, providing a basis for further prediction and evaluation. This value is used to quantify the environmental impact of the construction project during the entire construction period.

[0181] See also Figure 6 , the steps to obtain an overview of the building's full-cycle carbon emissions are:

[0182] Based on the time series analysis results, the formula is used.

[0183]

[0184] Calculate the weighted contribution rate G of the construction phase to the total carbon emissions and generate the phase carbon emission contribution rate data, where T t is the time series result of the tth stage, b t is the contribution evaluation coefficient;

[0185] Use the data of carbon emission contribution rate in the current stage to predict the trend of future carbon emissions, and adopt the formula:

[0186]

[0187] Calculate the predicted value P of the future total carbon emission trend and generate the trend prediction result, where G t is the carbon emission contribution rate of the stage, γ m and α are prediction parameters used to ensure the accuracy and adaptability of the prediction, and exp(·) represents the natural exponential function;

[0188] Integrate trend forecast results, evaluate carbon emissions throughout the entire life cycle, and organize and generate an overview of carbon emissions throughout the entire life cycle.

[0189] Assume that the time series analysis data (T value) and contribution evaluation coefficient of the three stages are:

[0190] T1=100, T2=150, T3=200

[0191] b1=0.2, b2=0.5, b3=0.3

[0192] Substituting into the formula, we get:

[0193]

[0194] The result G ≈ 0.348 shows the contribution rate after weighted average, reflecting the contribution of different construction stages to the total carbon emissions according to their importance and carbon emissions.

[0195] Assumption γ m =1 and α=0.05, combined with the above calculation result G≈0.348, then:

[0196]

[0197] P≈3.054 represents the value of predicting the trend of total carbon emissions in the future based on current data. This value indicates that carbon emissions are increasing over time and can be used for further strategic planning and resource allocation.

[0198] See also Figure 7 , the execution steps to convert data into a chart are:

[0199] Based on the overview of carbon emissions throughout the building life cycle, the carbon emissions of each building stage are collected and recorded z1, z2, ..., z n , forming the carbon emission data set Z = {z1, z2, z i , ..., z H}, where z i represents the carbon emissions in the i-th stage;

[0200] According to the stage carbon emission data set, the formula is used:

[0201]

[0202] Calculate the carbon emission ratio B in the i-th stage i , output the carbon emission ratio set, where Y i is the carbon emission coefficient of the building type or material used in stage i, and H represents the number of data points in the stage carbon emission data set;

[0203] Based on the carbon emission ratio set, data visualization technology is applied to convert the data into charts and generate data visualization results.

[0204] Assumed values:

[0205] z1=100kgCO2, initial construction stage.

[0206] z2=300kgCO2, usage stage.

[0207] z3=200kgCO2, demolition stage.

[0208] Assuming coefficients:

[0209] Y1=1.0, initial construction stage.

[0210] Y2=0.8, usage stage.

[0211] Y3=1.2, demolition stage.

[0212] Calculate weighted carbon emissions:

[0213]

[0214] Carbon emission ratio at each stage:

[0215]

[0216] The calculation results show that carbon emissions in the initial construction phase account for 17.24% of the total emissions, while the use phase accounts for 41.38% and the demolition phase also accounts for 41.38%, which means that the use phase and demolition phase contribute more to the total carbon emissions.

[0217] See also Figure 8 , the steps to obtain the carbon emission visual analysis results are:

[0218] Based on the data visualization results, trend information is extracted and the carbon emission trend of each stage is analyzed. The formula is used.

[0219]

[0220] Calculate the stage trend deviation value V and generate preliminary trend analysis results, where: is the average value of the carbon emission ratio set; using the preliminary trend analysis results, the carbon emission trend is deeply analyzed, using the formula,

[0221]

[0222] Calculate the standardized coefficient of variation R to obtain detailed trend confirmation results, where σ represents the standard deviation, which enhances the flexibility and sensitivity of trend analysis;

[0223] Based on the detailed trend confirmation results, key change points are identified, significant trend changes are highlighted, the carbon emission trends in each stage are reflected, and carbon emission visual analysis results are generated.

[0224] Combined with the above calculation results:

[0225] B1=17.24%

[0226] B2=41.38%

[0227] B3=41.38%

[0228] but:

[0229]

[0230] Variance calculation:

[0231]

[0232] The calculated result of 129.5 represents the average variance between the carbon emission ratio and the mean value during the construction phase. A larger variance value indicates significant differences, indicating that the distribution of carbon emissions fluctuates significantly at different stages, which is crucial for evaluating the effectiveness of carbon emission policies at each stage.

[0233] Combined with the above calculation results, the standard deviation is:

[0234]

[0235] Substituting into the formula, we get:

[0236]

[0237] The calculated result of 0.999 indicates that the standardized coefficient of variation between the carbon emission ratio in each stage and the average value is close to 1, which shows that the fluctuation of carbon emissions in each stage is uniform relative to the standard deviation and the difference is small, which helps to accurately adjust and optimize carbon emission policies.

[0238] The above are only preferred embodiments of the present invention and are not intended to limit the present invention in other forms. Any technician familiar with the profession may use the technical contents disclosed above to change or modify them into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution of the present invention still falls within the protection scope of the technical solution of the present invention.

Claims

1. Carbon emission dynamic assessment and prediction system based on BIM, characterized by: The system comprises: The data extraction and matching module automatically extracts the type and quantity of building materials based on BIM, connects BIM data with the database associated with carbon emissions, verifies and matches the corresponding material properties and quantities, and generates project-level carbon emission metadata; The carbon emission calculation module uses the project-level carbon emission metadata to perform data classification processing, divides the data according to differentiated material types and construction activities, independently calculates the carbon emission standard factor for each data item based on the division results, and summarizes and organizes the calculation results to form itemized carbon emission information; The full life cycle analysis module receives the itemized carbon emission information, summarizes the relevant data according to the building stage, integrates the analysis stage data through time series analysis, calculates the contribution rate of each stage to the total carbon emission based on the integration results, and makes trend predictions, comprehensively evaluates the building's full life cycle carbon emissions, and outputs an overview of the building's full life cycle carbon emissions; The result visualization module calculates the carbon emission proportion of each construction stage based on the overview of the building's full-cycle carbon emissions, converts the data into charts through data visualization technology, determines the carbon emission change trend of each construction stage based on the conversion results, and generates carbon emission visual analysis results.

2. The carbon emission dynamic assessment and prediction system based on BIM according to claim 1 is characterized in that: The steps for obtaining the project-level carbon emission metadata are as follows: Scan the BIM model, identify and record the type and corresponding quantity of each building material, and use the formula, Calculate the total amount of material N i , get the total material list, where x ij is the quantity of material i included in the jth component in the model, and k represents the total number of components; Based on the total material list, matching with the database, using the formula, C i =N i ×e i ×(1+δ i ) Calculate the estimated carbon emission C of the i-th material i , generate material carbon emission estimates, where e i is the unit carbon emission factor, δ i is the adjustment factor based on the environment in which the material is used; Using the estimated carbon emissions of the materials, combined with the project scale and material usage frequency, the formula is used: Calculate the total carbon emissions M of the entire project and obtain the project-level carbon emissions metadata, where w i is the weight adjusted according to the project characteristics, and n represents the type of material.

3. The carbon emission dynamic assessment and prediction system based on BIM according to claim 2 is characterized in that: The steps for dividing the differentiated material types and construction activities are as follows: extracting data from the project-level carbon emission metadata, identifying material types and construction activity characteristics, performing preliminary classification operations, and generating preliminary classification information; Using the preliminary classification information, the data is classified into detailed categories using complexity analysis, using the formula, Calculate the weighted classification value D and output the refined classification result, where S j The classified data points obtained for preliminary classification information, d j is the weight coefficient, emphasizing the classification accuracy of the data item, and m represents the number of categories in the preliminary classification information; Based on the refined classification results, normalization processing is performed using the formula: Calculate the normalized value F, build and output the classification framework, where D q is the output of the refined classification result, It represents the sum of all classified data and is used for normalization. p represents the number of data points.

4. The carbon emission dynamic assessment and prediction system based on BIM according to claim 3 is characterized by: The steps for obtaining the itemized carbon emission information are as follows: Based on the classification framework, a separate calculation is performed for each classification using the carbon emission standard factor, using the formula, Calculate the classified carbon emissions E, where F i is the normalized data item in the classification framework, f i is the carbon emission standard factor, which is used to enhance the accuracy of factor application. U represents the data item F i the number of Based on the above classified carbon emissions, combined with national standards, the formula is adopted: Calculate and generate adjusted carbon emission data A, where E j represents the carbon emissions of different categories, ξ j is the adjustment factor used to meet national standards, r represents E j The classification type; The adjusted carbon emission data are summarized and sorted to compile itemized carbon emission information.

5. The carbon emission dynamic assessment and prediction system based on BIM according to claim 4 is characterized in that: The steps for performing the data integration analysis phase through time series analysis are: Receive the itemized carbon emission information, collect carbon emission data for each stage of the building, preliminarily organize the data and store them in a database to generate a preliminarily organized data set; Based on the preliminary collated data set, it is classified and summarized according to the construction stage, using the formula, The generation stage classifies and summarizes the data S, where K j is the data point in stage j, u j is the classification coefficient, indicating the importance of the difference stage; By using the classified and aggregated data of the above stages, time series analysis is performed, and the trend of data changes is integrated and analyzed. The formula is used. Calculate the integrated carbon emission data T and generate time series analysis results, where S t represents the summary data of the tth category, a t is the weighting coefficient in time series analysis, used to ensure accurate representation of time dependence, and L represents the number of categories.

6. The carbon emission dynamic assessment and prediction system based on BIM according to claim 5 is characterized in that: The steps for obtaining the overview of the building's full-cycle carbon emissions are as follows: Based on the time series analysis results, the formula is adopted: Calculate the weighted contribution rate G of the construction phase to the total carbon emissions and generate the phase carbon emission contribution rate data, where T t is the time series result of the tth stage, b t is the contribution evaluation coefficient; Using the carbon emission contribution rate data of the above stage, the future carbon emission trend is predicted, using the formula: Calculate the predicted value P of the future total carbon emission trend and generate the trend prediction result, where G t is the carbon emission contribution rate of the stage, γ m and α are prediction parameters used to ensure the accuracy and adaptability of the prediction, and exp(·) represents the natural exponential function; Integrate the trend forecast results, evaluate the carbon emissions throughout the life cycle, and organize and generate an overview of the carbon emissions throughout the life cycle.

7. The BIM-based carbon emission dynamic assessment and prediction system according to claim 6 is characterized by: The steps for converting data into a chart are: Based on the overview of the building’s full-cycle carbon emissions, collect and record the carbon emissions of each building stage z1, z2, ..., z n , forming the carbon emission data set Z = {z1, z2, z i , ..., z H }, where z i represents the carbon emissions in the i-th stage; Based on the carbon emission data set of the said stage, the formula is adopted: Calculate the carbon emission ratio B in the i-th stage i , output the carbon emission ratio set, where Y i is the carbon emission coefficient of the building type or material used in stage i, and H represents the number of data points in the stage carbon emission data set; Based on the carbon emission ratio set, data visualization technology is applied to convert the data into charts to generate data visualization results.

8. The BIM-based carbon emission dynamic assessment and prediction system according to claim 7 is characterized in that: The steps for obtaining the carbon emission visual analysis results are as follows: Based on the data visualization results, trend information is extracted and the carbon emission trend of each stage is analyzed. The formula is used. Calculate the stage trend deviation value V and generate preliminary trend analysis results, where: is the average value of the carbon emission ratio set; Using the preliminary trend analysis results, an in-depth analysis of carbon emission trends was conducted using the formula: Calculate the standardized coefficient of variation R to obtain detailed trend confirmation results, where σ represents the standard deviation, which enhances the flexibility and sensitivity of trend analysis; According to the detailed trend confirmation results, significant trend changes are highlighted, the carbon emission trends in each stage are reflected, and the carbon emission visual analysis results are generated.

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