An integrated analysis method for multi-level early warning and damage assessment of building structures under explosion

Abstract

The application discloses a kind of building structure explosion multistage early warning and damage assessment integrated analysis method, it is related to building structure safety field, including BIM-FEM model conversion module, FEM explosion response and damage assessment module, Internet of Things gas sensor acquisition module, early warning analysis and hierarchical early warning module and data storage module;Develop an efficient BIM and the automatic model conversion interface between FEM.Develop the interface will realize the two-way data conversion between BIM model and finite element analysis model;In finite element analysis software, gas explosion load is applied, the dynamic response and damage of each component under gas explosion load are studied by numerical simulation, and the blast damage resistance evaluation attribute of each component is formed.The problem of low efficiency of complex structure modeling in finite element analysis software is effectively solved, and the automatic data extraction, model mapping and result backwriting between BIM model and FEM model are realized.

Description

Technical Field

[0001] This invention relates to the field of building structural safety, and in particular to an integrated analysis method for multi-level early warning and damage assessment of building structures in the event of an explosion.

[0002] Background Method

[0003] With rapid societal development and intensified urbanization, building structures have become increasingly crucial in supporting human activities. Existing building safety early warning systems, in the event of a gas explosion, typically only detect gas leaks and struggle to predict the explosion's impact on the structure in a timely and accurate manner. Therefore, there is an urgent need for an analytical method capable of accurately assessing and warning of building structural explosion risks. This method would provide effective alerts before gas leaks or explosion hazards occur, helping people evacuate quickly, reducing casualties, buying valuable time for emergency response, and maximizing the protection of building structures and public life and property.

[0004] Meanwhile, building structure projects often involve complex engineering activities and numerous stakeholders. However, the current engineering management model in the civil engineering industry leads to inefficient information transfer from upstream to downstream, resulting in frequent duplication of work, increased project costs, and wasted time. Achieving efficient two-way flow of structural data between Building Information Modeling (BIM) and Structural Analysis Model (FEM) has become crucial for improving the efficiency of the construction industry. With the widespread use of finite element analysis software, the demand for joint analysis and comparison using multiple structural analysis software is constantly increasing. However, the model information between these software programs is often incompatible, forcing engineers to model separately in multiple software programs. This leads to low modeling efficiency, inconsistent analysis models, repetitive work, and easily biased results, affecting project quality and the reliability of decision-making.

[0005] Existing building safety early warning systems have significant limitations in gas explosion scenarios, lacking both functionality and data support. Current systems typically only detect gas leaks, failing to accurately predict the impact of explosion loads on building structures or provide quantitative assessments of a building's capacity to withstand explosion loads. Furthermore, they cannot provide post-explosion damage data or classify building damage based on explosion intensity, issuing only a single alarm signal and failing to differentiate between different damage states. These issues not only increase the difficulty of structural damage assessment and management but also affect the effectiveness of emergency response, potentially causing delays in evacuation and decision-making. In addition, Building Information Modeling (BIM) primarily manages geometric, material, and construction information, making it difficult to directly perform complex structural mechanics analyses. While Finite Element Modeling (FEM) can perform detailed structural mechanics analyses, its data is difficult to exchange with BIM models, resulting in independent analysis systems and increased complexity in data conversion and management. Existing technologies cannot quickly calculate the specific impact of a gas explosion on the structure or delineate the potentially affected areas. This computational deficiency makes it difficult to quickly assess the damage to the building structure after an explosion, impacting emergency decision-making.

[0006] Therefore, an integrated analysis method for multi-level early warning and damage assessment of building structure explosions is provided to solve the above problems. Summary of the Invention

[0007] The purpose of this invention is to provide an integrated analysis method for multi-level early warning and damage assessment of building structures in the event of explosion. By developing a BIM-FEM bidirectional automatic conversion interface, it not only makes up for the disadvantages of BIM technology in structural analysis, but also effectively solves the problem of low efficiency in complex structure modeling in finite element analysis software. It realizes automated data extraction, model mapping and result writing between BIM models and FEM models, thereby significantly reducing the time of manual operation and improving the conversion accuracy and efficiency. It is particularly suitable for the rapid analysis needs of complex building structures.

[0008] To achieve the above objectives, this invention provides an integrated analysis method for multi-level early warning and damage assessment of building structure explosions, including a BIM-FEM model conversion module, a FEM explosion response and damage assessment module, an IoT gas sensor acquisition module, an early warning analysis and graded early warning module, and a data storage module; specifically, it includes the following steps:

[0009] S1: The BIM-FEM model conversion module sets up an automated model conversion interface between Building Information Model (BIM) and Finite Element Analysis Model (FEM) to realize bidirectional data conversion between BIM and FEM models;

[0010] S2: In the FEM explosion response and damage assessment module, the gas explosion load calculated based on sensor data is numerically simulated. The dynamic response and damage of the component under the gas explosion load are studied through numerical simulation, and the dynamic response and damage index of the component are obtained, and the explosion-resistant damage assessment attributes of the component are formed.

[0011] S3: The IoT gas sensor acquisition module receives real-time gas concentration and environmental parameters collected by the gas sensor, and accurately maps the data collected by the gas sensor to the corresponding components or spatial units in the BIM model according to the spatial location.

[0012] S4: The early warning analysis and graded early warning module performs algorithm evaluation based on the data in S3, the FEM model analysis results in S2, and preset thresholds to provide graded early warnings.

[0013] S5: The data storage module is used to store raw sensor data, environmental parameters, rapidly calculated explosion loads, structural component stress states, component damage level attributes, and graded early warning records output by FEM model analysis.

[0014] Preferably, the automated model conversion interface in S1 extracts the geometric shape and material properties of building structural components, converting the data in the BIM model into the format required by the FEM model analysis software, specifically including geometric data, material properties, and boundary conditions.

[0015] Preferably, the bidirectional data conversion in S1 specifically includes:

[0016] The component blast damage assessment attributes obtained from FEM model analysis are synchronized to the BIM model database. When changes occur in the building structure information, the changes in the BIM model are fed back and the FEM model is updated.

[0017] Preferably, the bidirectional data conversion and synchronization in S1 specifically includes the following steps:

[0018] S11: After completing the FEM model analysis, synchronize the component blast damage assessment attributes in the finite element analysis software to the BIM model database;

[0019] S12: Based on the changes in the building structure throughout its entire life cycle, the building structure information is automatically fed back to the FEM model to form a BIM model database that includes the blast resistance performance of the building structure.

[0020] S13: Visualize the analysis results of the BIM model to support the automatic feedback of subsequent modifications to the BIM model to the FEM model.

[0021] Preferably, S4 specifically includes the following steps:

[0022] S41: After the gas sensor in S3 detects the gas concentration, it transmits the data to the central control module. The early warning analysis and graded early warning module in S4 processes the collected data in real time.

[0023] S42: Set first-level, second-level, and third-level thresholds, conduct preliminary risk assessments of buildings using algorithms, and visualize the different levels of risk using BIM models to maintain real-time monitoring;

[0024] S43: When the gas concentration reaches the level three threshold, the building is judged to have entered a low-risk state, the graded early warning module is activated, and the BIM model is used to flash green warning lights to indicate that there is a risk of exceeding the standard, and the assessment is mild damage;

[0025] S44: When the gas concentration rises to the secondary threshold, the building is calculated to be in a moderate danger. The graded early warning module upgrades the alarm, the warning light in the BIM model turns to a continuous orange, accompanied by a beeping sound, and the assessment is moderate damage.

[0026] S45: When the gas concentration rises to the first-level threshold, the building is judged to be in a severely dangerous state. The graded early warning module issues the highest level alarm, the warning light in the BIM model is red, accompanied by an emergency evacuation prompt, and the assessment is severe damage.

[0027] S46: The graded early warning module stores the monitored data and program analysis results into the data storage module.

[0028] Preferably, the BIM software includes Revit, PKPM-BIM, or YJK; the finite element analysis software includes ABAQUS, ANSYS, or LS-DYNA.

[0029] Preferably, Revit is used as the BIM modeling software and ABAQUS as the finite element analysis software. A Revit-ABAQUS model data conversion interface is provided, and the implementation steps are as follows:

[0030] Step 1: Run the model data conversion interface in Revit and select the model to be converted in the interface;

[0031] Step 2: Automatically traverse Revit model components and filter out structural components based on component type name;

[0032] Step 3: Automatically extract the spatial location information, cross-sectional dimension information, material properties, and floor information of structural components, and save them as a .txt file;

[0033] Step 4: Automatically generate the finite element model using a Python script based on ABAQUS;

[0034] Step 5: The script reads the spatial location, cross-sectional dimensions, material properties, boundary and load data of the model components extracted from Revit, and automatically creates the model components;

[0035] Step Six: The script automatically assigns material properties and cross-sectional orientation to the component, automatically meshes the component, establishes the analysis step, and automatically applies boundary conditions and loads.

[0036] Therefore, the integrated analysis method for multi-level early warning and damage assessment of building structures using the above-mentioned structure has the following beneficial effects:

[0037] (1) By developing a BIM-FEM bidirectional automatic conversion interface, this invention not only makes up for the disadvantages of BIM technology in structural analysis, but also effectively solves the problem of low efficiency in complex structural modeling in finite element analysis software. It realizes automated data extraction, model mapping and result writing between BIM model and FEM model, thereby significantly reducing the time of manual operation and improving the conversion accuracy and efficiency. It is particularly suitable for the rapid analysis needs of complex building structures.

[0038] (2) This invention introduces a near real-time analysis mechanism based on a pre-calculated parametric FEM model, and applies a gas explosion load in the finite element analysis software to obtain the dynamic response time history and damage index of the components. Based on the damage index, the components are classified for explosion-resistant damage. By bidirectionally synchronizing the FEM analysis results and the explosion-resistant properties of the components back to the BIM, and combining the real-time concentration information of the gas sensor based on the Internet of Things, a closed-loop process of gas concentration-explosion load-structural damage-risk classification-visualized early warning is realized, providing structured data support for building explosion early warning and post-disaster damage assessment, which is conducive to rapid decision-making and operation and maintenance.

[0039] (3) This invention studies the dynamic response and damage of components under gas explosion load through FEM numerical simulation, and obtains the dynamic response and damage assessment attributes of components, providing data support for early warning of building structure explosion and damage assessment of post-disaster structures.

[0040] (4) The present invention uses BIM technology to form a BIM model database containing explosion load information and component damage assessment criteria.

[0041] (5) The present invention provides a gas sensor based on the Internet of Things for real-time monitoring. By combining the real-time data of the sensor, the potential damage to the building under different gas concentrations and explosion conditions can be predicted, which effectively improves the safety performance of the building.

[0042] (6) After detecting a gas leak, the present invention can transmit the gas leak concentration back to the building structure operation and maintenance platform. Based on the data of the explosion resistance performance of the building structure in the BIM system, it can realize the rapid calculation of the explosion load and the division and early warning of the building structure's impact area, thereby improving the early warning capability of building explosion events and contributing to the safety management of the entire building life cycle.

[0043] (7) This invention is not only applicable to gas explosions, but can also be flexibly applied to protect against other types of loads. It has good scalability and is applicable not only to building construction, but also to structures such as bridges, tunnels, and industrial plants. It has a wide range of applications.

[0044] (8) This invention improves building safety, reduces potential damage and casualties, and contributes to public safety and social stability. It effectively reduces losses caused by gas explosions, reduces subsequent repair and emergency costs, and improves the long-term return on investment for buildings.

[0045] The method of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0046] Figure 1 This is a flowchart illustrating the building structure explosion early warning analysis method of the present invention;

[0047] Figure 2 This is a flowchart illustrating the BIM-FEM model data conversion interface in this invention.

[0048] Figure 3 This is a conversion example diagram of the BIM-FEM model data conversion interface provided in this embodiment of the invention;

[0049] Figure 4 This is a schematic diagram of the dynamic response model of explosion load based on BIM model database in an embodiment of the invention. Detailed Implementation

[0050] The method of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0051] Unless otherwise defined, the methodological 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.

[0052] The terms "comprising" or "including" as used in this invention mean that the element preceding the term encompasses the element listed after the term, and do not exclude the possibility of encompassing other elements. Terms such as "inner," "outer," "upper," and "lower" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings, and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on the invention. When the absolute position of the described object changes, the relative positional relationship may also change accordingly. In this invention, unless otherwise explicitly specified and limited, the term "attached" and similar terms should be interpreted broadly. For example, it can refer to a fixed connection, a detachable connection, or an integral part; it can refer to a direct connection or an indirect connection through an intermediate medium; it can refer to the internal communication of two elements or the interaction relationship between two elements. Those skilled in the art can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0053] Example

[0054] like Figure 1 As shown, this invention provides an integrated analysis method for multi-level early warning and damage assessment of building structure explosions, including a BIM-FEM model conversion module, a FEM explosion response and damage assessment module, an IoT gas sensor acquisition module, an early warning analysis and graded early warning module, and a data storage module; specifically, it includes the following steps:

[0055] S1: The BIM-FEM model conversion module includes an automated model conversion interface between Building Information Modeling (BIM) and Finite Element Analysis (FEM) models. This interface enables bidirectional data conversion between the two models, supporting automated data extraction and synchronization, significantly improving work efficiency, reducing manual intervention, and ensuring data consistency and accuracy. The automated model conversion interface in S1 extracts the geometric shape and material properties of building structural components, converting the data from the BIM model into the format required by the FEM model analysis software, specifically including geometric data, material properties, and boundary conditions. It is then necessary to ensure that this interface can convert the data from the BIM model into the format required by the finite element structural analysis software, including geometric data, material properties, and boundary conditions. This model data conversion interface requires detailed testing to ensure data accuracy and completeness.

[0056] The bidirectional data transformation in S1 specifically includes:

[0057] The component blast damage assessment attributes obtained from FEM model analysis are synchronized to the BIM model database. When changes occur in the building structure information, the changes in the BIM model are fed back and the FEM model is updated.

[0058] The bidirectional data conversion and synchronization in S1 specifically includes the following steps:

[0059] S11: After completing the FEM model analysis, synchronize the component blast damage assessment attributes in the finite element analysis software to the BIM model database;

[0060] S12: Based on the changes in the building structure throughout its entire life cycle, the building structure information is automatically fed back to the FEM model to form a BIM model database that includes the blast resistance performance of the building structure.

[0061] S13: Visualize the analysis results of the BIM model to support the automatic feedback of subsequent modifications to the BIM model to the FEM model.

[0062] This enables bidirectional model data transfer between BIM and FEM, creating a BIM model database that can be used in subsequent operation, maintenance, and management. For example, dynamic updates: during the operation and maintenance phase of a building structure, any modifications, reinforcements, or repairs to the structure can be updated through the BIM model and transferred to finite element structural analysis software for real-time analysis.

[0063] BIM software includes Revit, PKPM-BIM, or YJK; finite element analysis software includes ABAQUS, ANSYS, or LS-DYNA.

[0064] S2: In the FEM explosion response and damage assessment module, the gas explosion load calculated based on sensor data is numerically simulated. The dynamic response and damage of the component under the gas explosion load are studied through numerical simulation, and the dynamic response and damage index of the component are obtained, and the explosion-resistant damage assessment attributes of the component are formed.

[0065] S3: The IoT gas sensor acquisition module receives real-time gas concentration and environmental parameters collected by gas sensors, and accurately maps the data collected by the gas sensors to the corresponding components or spatial units in the BIM according to their spatial location; based on the data of the explosion resistance performance of the building structure in the BIM model, it realizes rapid calculation of explosion load and division and early warning of the building structure's impact area.

[0066] S4: The early warning analysis and tiered early warning module performs algorithmic evaluation based on the data in S3, the FEM model analysis results in S2, and preset thresholds to generate tiered early warnings; for example... Figure 4As shown, to achieve real-time monitoring of gas concentration, suitable sensors (such as IoT-based gas sensors) need to be selected and installed appropriately. The sensors should possess high sensitivity and rapid response characteristics to ensure timely detection of potential risks. By installing IoT-based gas sensors to detect gas concentration, upon detecting a gas leak, the gas leak concentration is transmitted back to the building structure operation and maintenance platform. Based on the explosion-resistant performance data of the building structure in the BIM model, rapid calculation of explosion loads and delineation and early warning of the building structure's impact zone are achieved. This enhances the early warning capability for building explosion events and contributes to the safety management of the building throughout its entire lifecycle. Furthermore, the sensor installation locations should be rationally laid out according to the building's structural characteristics and potential gas leak points, ensuring that the gas leak concentration is transmitted back to the building structure operation and maintenance platform after a gas leak is detected. Specifically, S4 includes the following steps:

[0067] S41: After the gas sensor in S3 detects the gas concentration, it transmits the data to the central control module. The early warning analysis and graded early warning module in S4 processes the collected data in real time.

[0068] S42: Set first-level, second-level, and third-level thresholds, conduct preliminary risk assessments of buildings using algorithms, and visualize the different levels of risk using BIM models to maintain real-time monitoring;

[0069] S43: When the gas concentration reaches the level three threshold, the building is judged to have entered a low-risk state, the graded early warning module is activated, and the BIM model is used to flash green warning lights to indicate that there is a risk of exceeding the standard, and the assessment is mild damage;

[0070] S44: When the gas concentration rises to the secondary threshold, the building is calculated to be in a moderate danger. The graded early warning module upgrades the alarm, the warning light in the BIM model turns to a continuous orange, accompanied by a beeping sound, and the assessment is moderate damage.

[0071] S45: When the gas concentration rises to the first-level threshold, the building is judged to be in a severely dangerous state. The graded early warning module issues the highest level alarm, the warning light in the BIM model is red, accompanied by an emergency evacuation prompt, and the assessment is severe damage.

[0072] S46: The graded early warning module stores the monitored data and program analysis results into the data storage module.

[0073] S5: The data storage module is used to store raw sensor data, environmental parameters, rapidly calculated explosion loads, structural component stress states, component damage level attributes, and graded early warning records output by FEM analysis.

[0074] Example 1

[0075] like Figures 2-3 As shown, using Revit as the BIM modeling software and ABAQUS as the finite element analysis software, a Revit-ABAQUS model data conversion interface is presented, and the implementation steps are as follows:

[0076] Step 1: Run the model data conversion interface in Revit and select the model to be converted in the interface;

[0077] Step 2: Automatically traverse Revit model components and filter out structural components based on component type name;

[0078] Step 3: Automatically extract the spatial location information, cross-sectional dimension information, material properties, and floor information of structural components, and save them as a .txt file;

[0079] Step 4: Automatically generate the finite element model using a Python script based on ABAQUS;

[0080] Step 5: The script reads the spatial location, cross-sectional dimensions, material properties, boundary and load data of the model components extracted from Revit, and automatically creates the model components;

[0081] Step Six: The script automatically assigns material properties and cross-sectional orientation to the component, automatically meshes the component, establishes the analysis step, and automatically applies boundary conditions and loads.

[0082] Therefore, the present invention adopts the above-mentioned integrated analysis method for multi-level early warning and damage assessment of building structure explosion, which effectively solves the problem of low modeling efficiency of complex structures in finite element analysis software, realizes automated data extraction, model mapping and result writing between BIM model and FEM model, thereby significantly reducing the time of manual operation and improving the conversion accuracy and efficiency, and is particularly suitable for the rapid analysis needs of complex building structures.

[0083] Finally, it should be noted that the above embodiments are only used to illustrate the method of the present invention and not to limit it. 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 method of the present invention, and these modifications or equivalent substitutions should not cause the modified method to deviate from the spirit and scope of the method of the present invention.

Claims

1. An integrated analysis method for multi-level early warning and damage assessment of building structures in the event of an explosion, characterized in that: It includes a BIM-FEM model conversion module, a FEM explosion response and damage assessment module, an IoT gas sensor acquisition module, an early warning analysis and graded early warning module, and a data storage module; specifically, it includes the following steps: S1: The BIM-FEM model conversion module sets up an automated model conversion interface between Building Information Model (BIM) and Finite Element Analysis Model (FEM) to achieve bidirectional data conversion between BIM and FEM models. S2: In the FEM explosion response and damage assessment module, the gas explosion load calculated based on sensor data is numerically simulated. The dynamic response and damage of the component under the gas explosion load are studied through numerical simulation, and the dynamic response and damage index of the component are obtained, and the explosion-resistant damage assessment attributes of the component are formed. S3: The IoT gas sensor acquisition module receives real-time gas concentration and environmental parameters collected by the gas sensor, and accurately maps the data collected by the gas sensor to the corresponding components or spatial units in the BIM model according to the spatial location. S4: The early warning analysis and graded early warning module performs algorithm evaluation based on the data in S3, the FEM model analysis results in S2, and preset thresholds to provide graded early warnings. S5: The data storage module is used to store raw sensor data, environmental parameters, rapidly calculated explosion loads, structural component stress states, component damage level attributes, and graded early warning records output by FEM analysis.

2. The integrated analysis method for multi-level early warning and damage assessment of building structures according to claim 1, characterized in that, The automated model conversion interface in S1 extracts the geometry and material properties of building structural components, converting data from the BIM model into the format required by the FEM model analysis software, specifically including geometric data, material properties, and boundary conditions.

3. The integrated analysis method for multi-level early warning and damage assessment of building structure explosions as described in claim 2, characterized in that, The bidirectional data transformation in S1 specifically includes: The component blast damage assessment attributes obtained from FEM model analysis are synchronized to the BIM model database. When changes occur in the building structure information, the changes in the BIM model are fed back and the FEM model is updated.

4. The integrated analysis method for multi-level early warning and damage assessment of building structures according to claim 3, characterized in that, The bidirectional data conversion in S1 specifically includes the following steps: S11: After completing the FEM model analysis, synchronize the component blast damage assessment attributes in the finite element analysis software to the BIM model database; S12: Based on the changes in the building structure throughout its entire life cycle, the building structure information is automatically fed back to the FEM model to form a BIM model database that includes the blast resistance performance of the building structure. S13: Visualize the analysis results of the BIM model to support the automatic feedback of subsequent modifications to the BIM model to the FEM model.

5. The integrated analysis method for multi-level early warning and damage assessment of building structures according to claim 1, characterized in that, S4 specifically includes the following steps: S41: After the gas sensor in S3 detects the gas concentration, it transmits the data to the central control module. The early warning analysis and graded early warning module in S4 processes the collected data in real time. S42: Set first-level, second-level, and third-level thresholds, conduct preliminary risk assessments of buildings using algorithms, and visualize the different levels of risk using BIM models to maintain real-time monitoring; S43: When the gas concentration reaches the level three threshold, the building is judged to have entered a low-risk state, the graded early warning module is activated, and the BIM model is used to flash green warning lights to indicate that there is a risk of exceeding the standard, and the assessment is mild damage; S44: When the gas concentration rises to the secondary threshold, the building is calculated to be in a moderate danger. The graded early warning module upgrades the alarm, the warning light in the BIM model turns to a continuous orange, accompanied by a beeping sound, and the assessment is moderate damage. S45: When the gas concentration rises to the first-level threshold, the building is judged to be in a severely dangerous state. The graded early warning module issues the highest level alarm, the warning light in the BIM model is red, accompanied by an emergency evacuation prompt, and the assessment is severe damage. S46: The graded early warning module stores the monitored data and program analysis results into the data storage module.

6. The integrated analysis method for multi-level early warning and damage assessment of building structures according to claim 1, characterized in that, BIM software includes Revit, PKPM-BIM, or YJK; finite element analysis software includes ABAQUS, ANSYS, or LS-DYNA.

7. The integrated analysis method for multi-level early warning and damage assessment of building structures according to claim 6, characterized in that, Using Revit as the BIM modeling software and ABAQUS as the finite element analysis software, a Revit-ABAQUS model data conversion interface is described below, with the following implementation steps: Step 1: Run the model data conversion interface in Revit and select the model to be converted in the interface; Step 2: Automatically traverse Revit model components and filter out structural components based on component type name; Step 3: Automatically extract the spatial location information, cross-sectional dimension information, material properties, and floor information of structural components, and save them as a .txt file; Step 4: Automatically generate the finite element model using a Python script based on ABAQUS; Step 5: The script reads the spatial location, cross-sectional dimensions, material properties, boundary and load data of the model components extracted from Revit, and automatically creates the model components; Step Six: The script automatically assigns material properties and cross-sectional orientation to the component, automatically meshes the component, establishes the analysis step, and automatically applies boundary conditions and loads.

Images