A method and system for constructing an energy tube pile

Abstract

The application discloses a kind of energy pipe pile construction simulation method and system, it is related to energy pipe pile optimization design field, including obtaining past energy pipe pile engineering data, obtains multi-source data set by analyzing past engineering data;Feature extraction is carried out to multi-source data set and time-dependent characteristic is captured, and physical constraint type energy pipe pile model is constructed by fusing mechanical residual error, thermal residual error;Acquire target engineering construction deployment requirement, generate energy pipe pile construction strategy in physical constraint type energy pipe pile model according to current deployment requirement;Energy pipe pile construction strategy is imported into digital twin platform to simulate and obtain simulation result, and the target energy pipe pile construction strategy is obtained by correcting energy pipe pile construction strategy according to simulation result.The application satisfies multi-objective requirement by using the above-mentioned energy pipe pile construction simulation method, realizes the optimization construction of energy pipe pile, and then improves work efficiency.

Description

Technical Field

[0001] This invention relates to the field of energy pipe pile optimization design, and in particular to a construction simulation method and system for energy pipe piles. Background Technology

[0002] Energy pile technology is an important means of extracting and utilizing shallow geothermal energy. By installing heat exchange pipes within the building's pile foundation, the foundation itself also serves to extract and utilize geothermal energy. Underground soil can be divided into three layers based on temperature distribution: a variable-temperature layer, a constant-temperature layer, and a warming layer. The constant-temperature layer maintains a relatively stable temperature throughout the year. The principle of energy pile technology is to utilize the relatively stable temperature of the underground soil or water source in the constant-temperature zone. In summer, circulating fluid in the heat exchange pipes transfers excess heat from the building to the soil layer for cooling; in winter, it extracts heat energy from the soil layer and transfers it to the building for heating.

[0003] Currently, energy pile technology has been widely researched and applied, but it is still difficult to apply it to the design and optimization of energy pile schemes in actual engineering projects. The installation efficiency of energy piles in engineering applications still needs further research and improvement to promote the development of green energy systems.

[0004] Therefore, there is an urgent need for a method and system for simulating the construction of energy pipe piles. Summary of the Invention

[0005] To address the aforementioned issues, this application proposes a method and system for simulating the construction of energy pipe piles, the details of which are as follows: A method for simulating the construction of energy pipe piles includes the following steps: S1. Obtain past engineering data of energy pipe piles and analyze the past engineering data to obtain a multi-source dataset; S2. Extract features from multi-source datasets and capture time-dependent characteristics, then integrate mechanical and thermal residuals to construct a physically constrained energy pipe pile model. S3. Obtain the construction deployment requirements of the target project, and generate an energy pipe pile construction strategy in the physical constraint type energy pipe pile model based on the current deployment requirements; S4. Import the energy pipe pile construction strategy into the digital twin platform for simulation to obtain simulation results. Based on the simulation results, modify the energy pipe pile construction strategy to obtain the target energy pipe pile construction strategy.

[0006] Preferably, in S1, the engineering data of past energy pipe piles is obtained, and the specific content of the multi-source dataset obtained by analyzing the past engineering data includes: The engineering data of the past energy pipe piles includes key dynamic parameters, geotechnical parameters, and construction and operation data; The key dynamic parameters include pipe wall temperature distribution, heat exchange medium flow rate, inlet and outlet temperature difference, and pile stress-strain state. The geotechnical parameters include soil thermal conductivity, density, water content, and groundwater seepage velocity. The construction and operation data includes energy pile design parameters, operational performance data, and fault mode data. Noise processing and normalization were performed on past energy pipe pile engineering data to obtain a multi-source dataset.

[0007] Preferably, the specific content of extracting features from multi-source datasets and capturing time-dependent characteristics, and fusing mechanical residuals and thermal residuals to construct a physically constrained energy pipe pile model is as follows: Features were extracted from the soil and soil mechanics parameters to obtain the characteristics of soil thermal conductivity, density, water content and groundwater seepage velocity. The above features were matched and recombined to obtain several pairs of soil and soil mechanics feature data. Based on the geotechnical mechanics characteristic data pairs, match the corresponding key dynamic parameters and construction and maintenance data of the geotechnical mechanics characteristic data pairs; Extract energy pile design parameters and operational performance data from construction and operation data to establish an initial energy pipe pile model; A dynamic energy pipe pile model is obtained by performing time-series analysis on key dynamic parameters and simulating the process on the energy pipe pile model. By configuring a loss function for the dynamic energy pipe pile model, a physically constrained energy pipe pile model is obtained.

[0008] Preferably, the specific details of configuring the loss function for the dynamic energy pipe pile model include: Configure data fitting terms according to the performance index requirements of the dynamic energy pipe pile model; The physical constraint loss is obtained by calculating the residuals of the heat conduction equation and the mechanical equilibrium equation and configuring the residual weight coefficients respectively. Configure target optimization terms based on the multi-objective requirements of the dynamic energy pipe pile model; Configure regularization terms for the dynamic energy pipe pile model; The loss function is obtained by assigning weights to the data fitting term, physical constraint loss, and objective optimization term.

[0009] Preferably, the expression for the loss function is: ; in, , , , , These are the weighting selection coefficients, Output values ​​for performance metrics. Here, represents the actual value of the performance metric, and i represents different performance metrics. For mechanical residuals, For thermal residual, As a constraint on the goal, These are the model parameters.

[0010] Preferably, the specific content of obtaining the target project's construction deployment requirements and generating an energy pipe pile construction strategy in the physically constrained energy pipe pile model based on the current deployment requirements is as follows: Obtain the construction deployment requirements of the target project, which include the current geotechnical mechanics parameters and current target constraints, including energy efficiency and cost. Feature extraction is performed on the current geotechnical parameters to obtain geotechnical feature data pairs. These geotechnical feature data pairs are then constrained in a physically constrained energy pipe pile model to obtain an initial construction strategy. Substituting the target energy efficiency and target cost into the target constraints, we obtain a combination of energy pile design parameters, which yields several candidate energy pipe pile construction strategies. The key dynamic parameters corresponding to several candidate energy pipe pile construction strategies are evaluated to obtain strategy evaluation values, and the candidate energy pipe pile construction strategies are evaluated from high to low based on the strategy evaluation values. The candidate energy pipe pile construction strategy with the highest evaluation value is selected as the energy pipe pile construction strategy.

[0011] Preferably, the energy pipe pile construction strategy is imported into a digital twin platform to conduct operational simulations under different environmental conditions, and the simulation results are obtained. Based on the simulation results, the energy pipe pile construction strategy is modified to obtain the specific content of the target energy pipe pile construction strategy: The energy pipe pile construction strategy is input into the dynamic energy pipe pile model for simulation to obtain the simulated dynamic parameters. The parameter fluctuation range is obtained by integrating key dynamic parameters from past energy pipe pile engineering data; If the simulated dynamic parameters do not exceed the parameter fluctuation range, then the current energy pipe pile construction strategy is the target energy pipe pile construction strategy. If the simulated dynamic parameters exceed the parameter fluctuation range, the second-ranked candidate energy pipe pile construction strategy is selected for simulation until the simulated dynamic parameters do not exceed the parameter fluctuation range. This energy pipe pile construction strategy is then defined as the target energy pipe pile construction strategy.

[0012] A simulation system for constructing energy pipe piles, comprising: Data acquisition unit: acquires past engineering data of energy pipe piles, and analyzes the past engineering data to obtain multi-source datasets; Model building unit: extracts features from multi-source datasets and captures time-dependent characteristics, and integrates mechanical residuals and thermal residuals to build a physically constrained energy pipe pile model; Strategy Generation Unit: Obtains the construction deployment requirements of the target project and generates an energy pipe pile construction strategy in the physically constrained energy pipe pile model based on the current deployment requirements; Simulation correction unit: The energy pipe pile construction strategy is imported into the digital twin platform for simulation to obtain simulation results. Based on the simulation results, the energy pipe pile construction strategy is corrected to obtain the target energy pipe pile construction strategy.

[0013] An electronic device includes a memory and a processor, wherein the memory stores a computer program, and the processor invokes the computer program in the memory to implement the content of the energy pipe pile construction simulation method.

[0014] A storage medium storing computer-executable instructions, which, when loaded and executed by a processor, implement the content of the energy pipe pile construction simulation method.

[0015] In summary, the energy pipe pile construction simulation method and system of the present invention, compared with traditional technology, integrates multi-source engineering data with mechanical and thermal residuals to construct a physically constrained energy pipe pile model, improves strategy generation efficiency, sets multi-objective constraints to flexibly cope with different geological conditions, climate environments and energy demand scenarios of pipe pile deployment, maximizes the heat exchange advantages of buried pipes, makes full use of soil thermal energy, reduces power consumption, and helps to improve the construction efficiency of engineering projects.

[0016] The technical method of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0017] Figure 1 This is a step diagram illustrating the construction simulation method of an energy pipe pile according to the present invention; Figure 2 This is a schematic diagram of a construction simulation system for an energy pipe pile according to the present invention. Detailed Implementation

[0018] The technical method of the present invention will be further described below with reference to the accompanying drawings and embodiments. It should be noted that, unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of this application.

[0019] The following description of at least one exemplary embodiment is merely illustrative and is in no way intended to limit the scope of this application and its application or use.

[0020] Techniques, systems, and equipment known to those skilled in the art may not be discussed in detail, but where appropriate, they should be considered part of the instruction manual.

[0021] In all the examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values.

[0022] Unless otherwise defined, the technical or scientific terms used in this invention shall have the ordinary meaning as understood by one of ordinary skill in the art to which this invention pertains.

[0023] This invention provides a method for simulating the construction of energy pipe piles, such as... Figure 1 As shown, it includes the following steps: S1. Obtain past engineering data of energy pipe piles and analyze the past engineering data to obtain a multi-source dataset; Furthermore, S1 acquires past engineering data on energy pipe piles, and analyzes this past engineering data to obtain the following specific contents of the multi-source dataset: The engineering data of the past energy pipe piles includes key dynamic parameters, geotechnical parameters, and construction and operation data; The key dynamic parameters include pipe wall temperature distribution, heat exchange medium flow rate, inlet and outlet temperature difference, and pile stress-strain state. The geotechnical parameters include soil thermal conductivity, density, water content, and groundwater seepage velocity. The construction and operation data includes energy pile design parameters, operational performance data, and fault mode data. Noise processing and normalization were performed on past energy pipe pile engineering data to obtain a multi-source dataset.

[0024] Understandably, key parameters can be extracted by retrieving design drawings (CAD / BIM files), construction logs, material testing reports, acceptance records, and other documents from the company's historical projects through internal engineering archives, or by exporting operational data from the IoT platform and correlating it with environmental data.

[0025] During the analysis of past project data, unstructured text (construction logs, acceptance reports) is processed using NLP technology to extract key entities (such as "pile length 30m" and "concrete C40") and converted into structured tables. A standardized unit format is then used, along with multiple interpolation (MICE) and mode imputation techniques, to fill in missing values ​​and categories.

[0026] In addition, by associating time series data with static attributes, a spatial coordinate system is further designed in a hierarchical manner to construct a multi-source dataset.

[0027] S2. Extract features from multi-source datasets and capture time-dependent characteristics, then integrate mechanical and thermal residuals to construct a physically constrained energy pipe pile model. Furthermore, the specific content of extracting features from multi-source datasets and capturing time-dependent characteristics, and fusing mechanical and thermal residuals to construct a physically constrained energy pipe pile model is as follows: Features were extracted from the soil and soil mechanics parameters to obtain the characteristics of soil thermal conductivity, density, water content and groundwater seepage velocity. The above features were matched and recombined to obtain several pairs of soil and soil mechanics feature data. Based on the geotechnical mechanics characteristic data pairs, match the corresponding key dynamic parameters and construction and maintenance data of the geotechnical mechanics characteristic data pairs; Extract energy pile design parameters and operational performance data from construction and operation data to establish an initial energy pipe pile model; A dynamic energy pipe pile model is obtained by performing time-series analysis on key dynamic parameters and simulating the process on the energy pipe pile model. By configuring a loss function for the dynamic energy pipe pile model, a physically constrained energy pipe pile model is obtained.

[0028] Furthermore, the specific details of configuring the loss function for the dynamic energy pipe pile model include: Configure data fitting terms according to the performance index requirements of the dynamic energy pipe pile model; The physical constraint loss is obtained by calculating the residuals of the heat conduction equation and the mechanical equilibrium equation and configuring the residual weight coefficients respectively. Configure target optimization terms based on the multi-objective requirements of the dynamic energy pipe pile model; Configure regularization terms for the dynamic energy pipe pile model; The loss function is obtained by assigning weights to the data fitting term, physical constraint loss, and objective optimization term.

[0029] Furthermore, the expression for the loss function is: ; in, , , , , These are the weighting selection coefficients, Output values ​​for performance metrics. Here, represents the actual value of the performance metric, and i represents different performance metrics. For mechanical residuals, For thermal residual, As a constraint on the goal, These are the model parameters.

[0030] Understandably, to avoid the physical inconsistencies inherent in purely data-driven models, the heat conduction equation and structural mechanics equilibrium equation are embedded as soft constraints into the neural network loss function. By calculating the residuals of the model's predicted temperature and stress fields relative to the physical equations and assigning weight factors to them, the model output is forced to satisfy energy conservation and mechanical equilibrium. This type of physically constrained neural network can both utilize data to compensate for the parameter simplification deficiencies of traditional numerical simulations and prevent non-physical predictions caused by overfitting.

[0031] S3. Obtain the construction deployment requirements of the target project, and generate an energy pipe pile construction strategy in the physical constraint type energy pipe pile model based on the current deployment requirements; Furthermore, the specific content of the energy pipe pile construction strategy generated in the physically constrained energy pipe pile model based on the current deployment requirements and the acquisition of the target project's construction deployment requirements is as follows: Obtain the construction deployment requirements of the target project, which include the current geotechnical mechanics parameters and current target constraints, including energy efficiency and cost. Feature extraction is performed on the current geotechnical parameters to obtain geotechnical feature data pairs. These geotechnical feature data pairs are then constrained in a physically constrained energy pipe pile model to obtain an initial construction strategy. Substituting the target energy efficiency and target cost into the target constraints, we obtain a combination of energy pile design parameters, which yields several candidate energy pipe pile construction strategies. The key dynamic parameters corresponding to several candidate energy pipe pile construction strategies are evaluated to obtain strategy evaluation values, and the candidate energy pipe pile construction strategies are evaluated from high to low based on the strategy evaluation values. The candidate energy pipe pile construction strategy with the highest evaluation value is selected as the energy pipe pile construction strategy.

[0032] S4. Import the energy pipe pile construction strategy into the digital twin platform for simulation to obtain simulation results. Based on the simulation results, modify the energy pipe pile construction strategy to obtain the target energy pipe pile construction strategy.

[0033] Furthermore, the energy pipe pile construction strategy is imported into a digital twin platform for simulation to obtain simulation results. Based on the simulation results, the energy pipe pile construction strategy is modified to obtain the specific content of the target energy pipe pile construction strategy: The energy pipe pile construction strategy is input into the dynamic energy pipe pile model to obtain simulation dynamic parameters under different environmental conditions. The parameter fluctuation range is obtained by integrating key dynamic parameters from past energy pipe pile engineering data; If the simulated dynamic parameters do not exceed the parameter fluctuation range, then the current energy pipe pile construction strategy is the target energy pipe pile construction strategy. If the simulated dynamic parameters exceed the parameter fluctuation range, the second-ranked candidate energy pipe pile construction strategy is selected for simulation until the simulated dynamic parameters do not exceed the parameter fluctuation range. This energy pipe pile construction strategy is then defined as the target energy pipe pile construction strategy.

[0034] Understandably, digital twin platforms enable predictive simulation of strategies, providing a real-time and reliable virtual testing environment for strategy optimization.

[0035] like Figure 2 As shown, a simulation system for constructing energy pipe piles includes: Data acquisition unit: acquires past engineering data of energy pipe piles, and analyzes the past engineering data to obtain multi-source datasets; Model building unit: extracts features from multi-source datasets and captures time-dependent characteristics, and integrates mechanical residuals and thermal residuals to build a physically constrained energy pipe pile model; Strategy Generation Unit: Obtains the construction deployment requirements of the target project and generates an energy pipe pile construction strategy in the physically constrained energy pipe pile model based on the current deployment requirements; Simulation correction unit: The energy pipe pile construction strategy is imported into the digital twin platform for simulation to obtain simulation results. Based on the simulation results, the energy pipe pile construction strategy is corrected to obtain the target energy pipe pile construction strategy.

[0036] An electronic device includes a memory and a processor, wherein the memory stores a computer program, and the processor invokes the computer program in the memory to implement the content of a method for simulating the construction of energy pipe piles.

[0037] A storage medium storing computer-executable instructions, which, when loaded and executed by a processor, implement the content of a method for simulating the construction of energy pipe piles.

[0038] Finally, it should be noted that the above embodiments are only used to illustrate the technical methods of the present invention and not to limit them. Although the present invention has been described in detail with reference to preferred embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the technical methods of the present invention, and these modifications or equivalent substitutions cannot cause the modified technical methods to deviate from the spirit and scope of the technical methods of the present invention.

Claims

1. A method for simulating the construction of energy pipe piles, characterized in that, Includes the following steps: S1. Obtain past engineering data of energy pipe piles and analyze the past engineering data to obtain a multi-source dataset; S2. Extract features from multi-source datasets and capture time-dependent characteristics, then integrate mechanical and thermal residuals to construct a physically constrained energy pipe pile model. S3. Obtain the construction deployment requirements of the target project, and generate an energy pipe pile construction strategy in the physical constraint type energy pipe pile model based on the current deployment requirements; S4. Import the energy pipe pile construction strategy into the digital twin platform for simulation to obtain simulation results. Based on the simulation results, modify the energy pipe pile construction strategy to obtain the target energy pipe pile construction strategy. The specific content of extracting features from multi-source datasets, capturing time-dependent characteristics, and constructing a physically constrained energy pipe pile model by fusing mechanical and thermal residuals is as follows: Features were extracted from the soil and soil mechanics parameters to obtain the characteristics of soil thermal conductivity, density, water content and groundwater seepage velocity. The above features were matched and recombined to obtain several pairs of soil and soil mechanics feature data. Based on the geotechnical mechanics characteristic data pairs, match the corresponding key dynamic parameters and construction and maintenance data of the geotechnical mechanics characteristic data pairs; Extract energy pile design parameters and operational performance data from construction and operation data to establish an initial energy pipe pile model; A dynamic energy pipe pile model is obtained by performing time-series analysis on key dynamic parameters and simulating the process on the energy pipe pile model. By configuring a loss function for the dynamic energy pipe pile model, a physically constrained energy pipe pile model is obtained. The specific details of configuring the loss function for the dynamic energy pipe pile model include: Configure data fitting terms according to the performance index requirements of the dynamic energy pipe pile model; The physical constraint loss is obtained by calculating the residuals of the heat conduction equation and the mechanical equilibrium equation and configuring the residual weight coefficients respectively. Configure target optimization terms based on the multi-objective requirements of the dynamic energy pipe pile model; Configure regularization terms for the dynamic energy pipe pile model; The loss function is obtained by assigning weights and selecting coefficients to the data fitting term, physical constraint loss, and objective optimization term; The expression for the loss function is: ； in, , , , , These are the weighting selection coefficients, Output values ​​for performance metrics. Here, represents the actual value of the performance metric, and i represents different performance metrics. For mechanical residuals, For thermal residual, As a constraint on the goal, These are the model parameters.

2. The method for simulating the construction of an energy pipe pile according to claim 1, characterized in that, S1 obtains past engineering data on energy pipe piles, and the analysis of this past engineering data yields a multi-source dataset containing the following: The engineering data of the past energy pipe piles includes key dynamic parameters, geotechnical parameters, and construction and operation data; The key dynamic parameters include pipe wall temperature distribution, heat exchange medium flow rate, inlet and outlet temperature difference, and pile stress-strain state. The geotechnical parameters include soil thermal conductivity, density, water content, and groundwater seepage velocity. The construction and operation data includes energy pile design parameters, operational performance data, and fault mode data. Noise processing and normalization were performed on past energy pipe pile engineering data to obtain a multi-source dataset.

3. The method for simulating the construction of an energy pipe pile according to claim 2, characterized in that, The specific content of obtaining the target project's construction deployment requirements and generating an energy pipe pile construction strategy in a physically constrained energy pipe pile model based on the current deployment requirements is as follows: Obtain the construction deployment requirements of the target project, which include the current geotechnical mechanics parameters and current target constraints, including energy efficiency and cost. Feature extraction is performed on the current geotechnical parameters to obtain geotechnical feature data pairs. These geotechnical feature data pairs are then constrained in a physically constrained energy pipe pile model to obtain an initial construction strategy. Substituting the target energy efficiency and target cost into the target constraints, we obtain a combination of energy pile design parameters, which yields several candidate energy pipe pile construction strategies. The key dynamic parameters corresponding to several candidate energy pipe pile construction strategies are evaluated to obtain strategy evaluation values, and the candidate energy pipe pile construction strategies are evaluated from high to low based on the strategy evaluation values. The candidate energy pipe pile construction strategy with the highest evaluation value is selected as the energy pipe pile construction strategy.

4. The method for simulating the construction of an energy pipe pile according to claim 3, characterized in that, The energy pipe pile construction strategy is imported into a digital twin platform for simulation to obtain simulation results. Based on the simulation results, the energy pipe pile construction strategy is modified to obtain the specific content of the target energy pipe pile construction strategy: The energy pipe pile construction strategy is input into the dynamic energy pipe pile model to obtain simulation dynamic parameters under different environmental conditions. The parameter fluctuation range is obtained by integrating key dynamic parameters from past energy pipe pile engineering data; If the simulated dynamic parameters do not exceed the parameter fluctuation range, then the current energy pipe pile construction strategy is the target energy pipe pile construction strategy. If the simulated dynamic parameters exceed the parameter fluctuation range, the second-ranked candidate energy pipe pile construction strategy is selected for simulation until the simulated dynamic parameters do not exceed the parameter fluctuation range. This energy pipe pile construction strategy is then defined as the target energy pipe pile construction strategy.

5. A simulation system for constructing energy pipe piles, characterized in that, include: Data acquisition unit: acquires past engineering data of energy pipe piles, and analyzes the past engineering data to obtain multi-source datasets; Model building unit: extract features from multi-source datasets and capture time-dependent characteristics, and integrate mechanical residuals and thermal residuals to build a physically constrained energy pipe pile model; Strategy Generation Unit: Obtains the construction deployment requirements of the target project and generates an energy pipe pile construction strategy in the physically constrained energy pipe pile model based on the current deployment requirements; Simulation correction unit: The energy pipe pile construction strategy is imported into the digital twin platform for simulation to obtain simulation results. Based on the simulation results, the energy pipe pile construction strategy is corrected to obtain the target energy pipe pile construction strategy. The specific content of extracting features from multi-source datasets, capturing time-dependent characteristics, and constructing a physically constrained energy pipe pile model by fusing mechanical and thermal residuals is as follows: Features were extracted from the soil and soil mechanics parameters to obtain the characteristics of soil thermal conductivity, density, water content and groundwater seepage velocity. The above features were matched and recombined to obtain several pairs of soil and soil mechanics feature data. Based on the geotechnical mechanics characteristic data pairs, match the corresponding key dynamic parameters and construction and maintenance data of the geotechnical mechanics characteristic data pairs; Extract energy pile design parameters and operational performance data from construction and operation data to establish an initial energy pipe pile model; A dynamic energy pipe pile model is obtained by performing time-series analysis on key dynamic parameters and simulating the process on the energy pipe pile model. By configuring a loss function for the dynamic energy pipe pile model, a physically constrained energy pipe pile model is obtained. The specific details of configuring the loss function for the dynamic energy pipe pile model include: Configure data fitting terms according to the performance index requirements of the dynamic energy pipe pile model; The physical constraint loss is obtained by calculating the residuals of the heat conduction equation and the mechanical equilibrium equation and configuring the residual weight coefficients respectively. Configure target optimization terms based on the multi-objective requirements of the dynamic energy pipe pile model; Configure regularization terms for the dynamic energy pipe pile model; The loss function is obtained by assigning weights and selecting coefficients to the data fitting term, physical constraint loss, and objective optimization term; The expression for the loss function is: ； in, , , , , These are the weighting selection coefficients, Output values ​​for performance metrics. Here, represents the actual value of the performance metric, and i represents different performance metrics. For mechanical residuals, For thermal residual, As a constraint on the goal, These are the model parameters.

6. An electronic device, characterized in that, It includes a memory and a processor, wherein the memory stores a computer program, and the processor, when calling the computer program in the memory, implements the construction simulation method for energy pipe piles as described in any one of claims 1 to 4.

7. A storage medium, characterized in that, The storage medium stores computer-executable instructions, which, when loaded and executed by a processor, implement the construction simulation method for energy pipe piles as described in any one of claims 1 to 4.

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