RC frame structure anti-seismic performance analysis and evaluation method integrated with Revit software

Abstract

The invention discloses an RC frame structure anti-seismic performance analysis and evaluation method integrated on Revit software, and relates to the technical field of civil engineering. Comprising the following steps: automatically acquiring model parameters required by capability spectrum analysis through a RevitAPI, starting an RTO program to carry out model data conversion on a Revit model, and calling OpenSEES software to carry out Pushover analysis; a large amount of selected seismic oscillation data is adopted, OpenSEES software is repeatedly called to carry out excitation step-by-step increasing elastoplasticity time history analysis, and IDA average data is obtained; according to the IDA average data and interaction parameters of a set multi-level anti-seismic performance target, multi-level anti-seismic performance determinacy evaluation based on the IDA data is carried out; carrying out earthquake vulnerability analysis on the whole structure and the beam column component in Revit software by adopting RevitAPI; and establishing a probability-based damage uncertainty analysis method of the structure through a Monte Carlo simulation algorithm. According to the method, the anti-seismic performance analysis and evaluation of the RC frame structure directly based on the BIM platform are realized.

Description

Technical Field

[0001] The invention relates to the technical field of civil engineering, and in particular to a seismic performance analysis and evaluation method for a RC frame structure integrated in Revit software. Background Art

[0002] my country is located in the Pacific Rim and the Eurasian seismic belt, where earthquake activity is widespread, strong and frequent. Earthquakes have brought great disasters to the Chinese people, and earthquake mitigation work is important and urgent. With the deepening of people's understanding of earthquake motion characteristics and structural dynamic characteristics, the theory and method of seismic design of building structures have developed from the initial static stage and response spectrum stage to the dynamic stage, and then to the current performance-based seismic design stage.

[0003] With the advent of the information age, Building Information Model (BIM) technology has received widespread attention. The traditional construction industry has low engineering efficiency, weak informationization, and lacks a full life cycle management method, which can no longer meet the current needs. BIM technology is committed to achieving collaborative management and information sharing in different fields throughout the life cycle of a building, and is one of the important foundations for the new generation of information technology to be combined with the construction field.

[0004] The application value of BIM technology is reflected in the information sharing and information data conversion throughout the entire life cycle of the building. In the integrated research and application of BIM technology and building structure design and analysis software, the data conversion problem brought about by structural analysis affects the better combination of BIM platform and structural analysis software. In recent years, some scholars have explored BIM-based seismic design and analysis methods for building structures, using the information superiority of BIM to predict building damage, economic losses and casualties caused by earthquakes. However, at present, there is a lack of relevant research and application in the integration of BIM technology and performance-based earthquake engineering, and there is a lot of room for improvement. Summary of the invention

[0005] The purpose of the present invention is to provide a method for analyzing and evaluating the seismic performance of RC frame structures integrated in Revit software, thereby realizing the analysis and evaluation of the seismic performance of RC frame structures directly based on a BIM platform.

[0006] To achieve the above objectives, this application proposes a seismic performance analysis and evaluation method for RC frame structures integrated into Revit software, such as Figure 1 As shown, including:

[0007] Capacity spectrum analysis and seismic performance evaluation based on Revit model: The model parameters required for capacity spectrum analysis are automatically obtained through Revit API, and the RTO (Revit to OpenSEES) program developed in the previous research is started to convert the model data of the Revit model and call the OpenSEES software for Pushover analysis. The Pushover analysis results, related structural model parameters, and interactive parameters for setting multi-level performance targets are used as basic data to implement capacity spectrum analysis functions such as capacity spectrum curve conversion, demand spectrum curve conversion, and performance point iterative calculation in Revit software, and then deterministic evaluation and fuzzy evaluation are performed for different seismic performance targets;

[0008] Incremental dynamic analysis (IDA) and seismic performance evaluation based on Revit model: Develop IDA function in RTO program, perform model data conversion, and repeatedly call OpenSEES software to perform elastic-plastic time-history analysis with step-by-step excitation for a large amount of selected seismic motion data to obtain IDA average data; perform deterministic and fuzzy evaluation of multi-level seismic performance based on IDA data according to the IDA average data and the interactive parameters of multi-level performance targets;

[0009] Earthquake vulnerability analysis based on Revit model: Develop IDA function in RTO program, and use RevitAPI to perform seismic damage limit state probability analysis on structures and components in Revit software according to the earthquake vulnerability analysis model; and establish an analysis method for uncertainty of overall structural damage through Monte Carlo simulation algorithm.

[0010] Furthermore, when analyzing the capacity spectrum and evaluating the seismic performance, the structure is first subjected to a Pushover analysis, and then the top displacement-base shear (U n -V b ) format curve is converted into spectral displacement-spectral acceleration (S d -S a ) format:

[0011]

[0012] Where M1 * is the equivalent mass of the first vibration mode of the structure, τ1 is the vibration mode participation coefficient of the first vibration mode; Φ n1 is the vibration mode value of the top layer of the structure. Generally, the first vibration mode is normalized, so Φ n1 =1; V b is the maximum shear force value of the structural base;

[0013] The demand spectrum curve is converted into the earthquake acceleration response spectrum (TS) according to the earthquake influence coefficient curve (T-α) with a damping ratio of 5% in the "Code for Seismic Design of Buildings". a ), and then use formula (2) to convert TS a The response spectrum in S format is converted into d -S a The demand spectrum of the format:

[0014]

[0015] Where T is the basic period of the structure;

[0016] S d -S a Capacity spectrum curve and S d -S a The demand spectrum curve in the same coordinate system is plotted in the same format, and the performance points of the structure under a given earthquake intensity are obtained according to the ATC-40 method.

[0017] Furthermore, the specific implementation methods of capacity spectrum analysis and seismic performance evaluation are as follows:

[0018] 1) Setting multiple levels of seismic performance targets

[0019] The earthquake levels specified in the Code for Seismic Design of Buildings are refined and divided into frequent earthquakes (small earthquakes), sub-basic earthquakes (sub-moderate earthquakes), basic earthquakes (moderate earthquakes), sub-rare earthquakes (sub-large earthquakes), and rare earthquakes (large earthquakes). According to FEMA-356, the earthquake damage level of the entire structure is divided into operating normally (OP), habitable (IO), life safe (LS), and not collapsed (CP).

[0020] Through UI interaction, the corresponding earthquake damage levels expected to be achieved by the structure under various earthquake levels are set, thereby determining the multi-level seismic performance targets of the structure.

[0021] 2) Determine performance points

[0022] The Revit model is converted into a TCL command stream readable by the OpenSEES software through the RTO program developed in the previous research (see the patent application with publication number CN114707377A), and the OpenSEES software is started in RTO to perform pushover analysis to obtain the base shear force-vertex displacement data.

[0023] The representative value of the gravity load and vibration mode data of the model structure are obtained through the RTO program, and the base shear-apex displacement capacity curve is converted into a capacity spectrum. The design earthquake grouping, fortification intensity and site category are selected to automatically establish the demand spectrum. Multiple iterative calculations are performed on the intersecting capacity spectrum curve and demand spectrum curve to obtain the performance point, which is converted into the target displacement of the structure.

[0024] 3) Earthquake resistance evaluation

[0025] The inter-story displacement angle, top-floor displacement and other data obtained by Pushover analysis are stored in the running directory file; the inter-story displacement angle of the structure corresponding to the performance point is compared with the inter-story displacement angle limit to draw a conclusion on the seismic performance evaluation.

[0026] Furthermore, the implementation of incremental dynamic analysis IDA is as follows: IDA is essentially a dynamic elastoplastic time-history analysis of the gradual increase of seismic excitation. Through IDA, it is generally necessary to establish an IDA curve with the ordinate being the earthquake intensity index (IM for short) and the abscissa being the structural engineering demand parameter (EDP for short). The specific steps are as follows:

[0027] 1) Establish finite element analysis model;

[0028] 2) Determine the earthquake intensity index IM and the structural engineering demand parameter EDP;

[0029] The indicators generally used by EDP include the maximum inter-story displacement angle, the maximum displacement of the top floor of the structure, and the damage index. The indicators generally used by IM include the peak acceleration of earthquake (PGA for short), spectral acceleration S a wait.

[0030] 3) Performing step-by-step amplitude modulation on a piece of seismic motion data to obtain a series of seismic motion data;

[0031] 4) Perform dynamic time-history analysis on the structure to obtain a series of (EDP, IM) coordinate points, and connect each discrete point to obtain the IDA curve.

[0032] 5) Use different earthquake motion parameters to excite the structure, repeat steps 3) to 4) to obtain the IDA curve cluster.

[0033] Furthermore, the specific implementation methods of incremental dynamic analysis IDA and seismic performance evaluation are as follows:

[0034] 1) Incremental elastoplastic analysis

[0035] Develop the IDA function in the RTO program. The developed RTO program can be based on the Revit model, form a TCL command stream that can perform IDA through parameter setting and seismic wave selection, and then call the OpenSEES software to perform incremental loop calculation to obtain IDA data;

[0036] 2) Seismic performance evaluation based on IDA

[0037] According to the PGA target value of a selected earthquake level and the set seismic performance level, the performance target of the structure is determined, and then the structural response data or damage data of the target state is located from the IDA average curve according to the PGA target value, and these data are compared with the limit value of the performance target to determine whether the structure meets the set seismic performance target requirements.

[0038] Furthermore, earthquake vulnerability analysis refers to calculating the probability of conditional failure of a structure reaching or exceeding a certain limit state under the action of earthquakes of different intensity indicators. By drawing vulnerability curves and structural vulnerability matrices, the probability of various levels of damage and destruction of the structure under the action of earthquakes of different levels is predicted.

[0039] Under the action of a certain earthquake intensity IM, the conditional failure probability that the EDP reflecting the structural damage reaches or exceeds the limit value [EDP] is expressed as P f ; When EDP and [EDP] both obey lognormal distribution, P f It is obtained from the following formula:

[0040]

[0041] Where Φ{·} is the probability distribution function of the standard normal random variable; μ [EDP] is the average value of [EDP], σ EDPm and σ [EDP] EDP m and the logarithmic standard deviation of [EDP], where EDP m is the maximum value of EDP; where a and b are regression parameters, which can be obtained by formula (4).

[0042] ln(μ Dm )=a+bln(IM) (4)

[0043] In the formula, μ EDPm is the EDP obtained using multiple ground motion data m By adjusting the size of IM, we can get a series of (IM, μ EDPm ), and then the regression analysis method can be used to obtain the parameters a and b.

[0044] Furthermore, the seismic vulnerability analysis of the entire structure is carried out: EDP uses the maximum inter-story displacement angle θ m As the judgment index of the overall structural damage, IM uses PGA to divide the overall structural damage level into four levels: OP, IO, LS and CP. The damage judgment criteria are shown in Table 1. OP ,θ IO,θ LS and θ CP are θ corresponding to the four structural damage states. m The limits are 0.2%, 1%, 2% and 4% respectively; thus, the IDA of multiple ground motion data can be used to obtain θ m -PGA relationship, and then use formulas (4) and (3) to establish PGA-P corresponding to different damage levels f Format structure overall seismic vulnerability curve.

[0045] Table 1 Based on θ m The overall damage judgment standard of RC frame structure

[0046]

[0047] Seismic fragility analysis of beams and columns: EDP uses the maximum rotation angle β of the components m As the component damage determination index, IM still uses PGA; according to the "Building Seismic Resilience Evaluation Standard", the damage status of beams and columns is divided into five levels: intact (level 0), slightly damaged (level 1), slightly damaged (level 2), moderately damaged (level 3) and severely damaged (level 4); based on the maximum rotation angle β m The damage judgment criteria are shown in Table 2. y , β IO , β P and β u are the rotation limits corresponding to the nominal yield point, performance point, peak point and limit point of beam and column components respectively; therefore, the PGA-β of beam and column components can be obtained through IDA of multiple ground motion data. m The average data of the relationship is substituted into the seismic vulnerability analysis model to obtain the seismic vulnerability curves of components corresponding to different damage levels.

[0048] Table 2 Based on β m The criterion for judging the normal section damage of beam-column components in RC frame structures

[0049]

[0050]

[0051] Furthermore, the analysis method of damage uncertainty is as follows: Figure 2As shown, according to the given PGA, four dividing points P1, P2, P3 and P4 can be obtained on the seismic fragility curve. A number R is randomly generated, R∈[0,1]; if R belongs to the interval [P1,100%], the damage level of the structure is OP; if R belongs to the interval [P2,P1), the damage level of the structure is IO; if R belongs to the interval [P3,P2), the damage level of the structure is LS; if R belongs to the interval [P4,P3), the damage level of the structure is CP, if R belongs to the interval [0,P4), the damage level of the structure is collapse or near collapse;

[0052] The present invention adopts Monte Carlo simulation algorithm to carry out uncertainty analysis of earthquake damage of the whole structure; based on a given θ m , the corresponding PGA value is obtained through the IDA average curve, and the PGA value is substituted into the fragility curve to divide the five damage areas (such as Figure 2 As shown in Figure 2), 1000 numbers R are randomly generated and the structure is obtained by statistical frequency calculation at a given θ. m The probability distribution results of different damage levels.

[0053] As a further step, Figure 3 As shown, the Revit model includes:

[0054] Interaction layer: Contains the user interfaces of various functional modules of the system, such as the seismic performance target setting interface, the structural information setting interface, the data loading interface, etc.; it is used to carry the interactive data content between the user and the system, pass parameters to the logic layer, and after processing by the logic layer, the data access layer calls the data operation process and provides data content.

[0055] Logic layer: corresponds to the logic implementation of each functional module of the system, which is the core function of the system. In the logic layer, various functional scheduling such as model conversion and spectrum curve conversion are processed, specific logical operation processing is performed, and the functional scheduling of data access in the data access layer is performed, so that user needs can be realized in the system.

[0056] Data access layer: provides a series of methods for data access, responds to the function scheduling of the logic layer, calls stored procedures, directly operates the data layer, and updates the storage or reading of data.

[0057] Data layer: provides storage services for various types of data for the entire system and scheduling by the data access layer. The data mainly includes corresponding data of seismic performance indicators, IDA data, structural model data, etc.

[0058] Compared with the prior art, the above technical solution adopted by the present invention has the following advantages: the present invention takes Revit software as a platform, and for reinforced concrete structure types, establishes a seismic performance analysis and evaluation method for RC frame structures integrated in Revit software, realizes the application of performance-based seismic analysis and evaluation on the BIM platform, and lays a foundation for further realizing its application and information sharing in the entire life cycle of buildings. BRIEF DESCRIPTION OF THE DRAWINGS

[0059] Figure 1 It is a general idea diagram of the seismic performance analysis and evaluation method of RC frame structure integrated in Revit software;

[0060] Figure 2 It is a schematic diagram of the structural seismic vulnerability curve;

[0061] Figure 3 The overall architecture diagram of the RC frame structure seismic performance analysis and evaluation software based on Revit

[0062] Figure 4 The method diagram for converting the capability spectrum into a bilinear capability curve;

[0063] Figure 5 Flow chart of the algorithm for determining the yield point of the capacity spectrum curve;

[0064] Figure 6 Flow chart of the algorithm for determining the performance points of the capability spectrum curve;

[0065] Figure 7 Set up interface diagrams for earthquake parameters and multi-level seismic performance targets;

[0066] Figure 8 This is the analysis interface diagram of the capability spectrum method;

[0067] Fig. 9 Display interface diagram for IDA parameter settings and TCL command flow;

[0068] Fig.10 This is the IDA analysis interface diagram;

[0069] Fig.11 Flow chart for drawing seismic vulnerability curves of structural components;

[0070] Fig.12 Flow chart of the Monte Carlo simulation algorithm for structural damage probability distribution;

[0071] Fig.13 Interface diagram for structural seismic vulnerability analysis;

[0072] Fig.14 Interface diagram for component seismic vulnerability analysis;

[0073] Fig.15 This is the interface diagram for earthquake damage uncertainty analysis. DETAILED DESCRIPTION

[0074] In order to make the purpose, technical solutions and advantages of the present application more clearly understood, the present application 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 application and are not used to limit the present application, that is, the embodiments described are only part of the embodiments of the present application, not all of the embodiments.

[0075] Therefore, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the present application for which protection is sought, but merely represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0076] This embodiment provides a method for analyzing and evaluating the seismic performance of an RC frame structure integrated in Revit software. The specific implementation method includes:

[0077] S1. Functional realization of capacity spectrum analysis and seismic evaluation

[0078] S1.1 Capacity spectrum curve establishment

[0079] 1) Define the method of transferring values ​​between forms and user controls, use the ReadAllLines() method of the File class to read the Pushover file, floor quality file, and structural vibration file loaded by the user, and load the read data into the instantiated Datatable class to facilitate data storage and subsequent data query and positioning.

[0080] 2) After obtaining the above data, store it in a double type collection, bring in the initial value through a for loop, and loop calculation until all data has been converted to S d -S a The two sets of data are stored in the collections named Dlist and Alist respectively, and the ZedGragh control is used to call the data to draw the capacity spectrum curve.

[0081] S1.2 Establishment of demand spectrum curve

[0082] 1) For the maximum value of the seismic influence coefficient determined by the seismic fortification intensity and PGA, and the design characteristic period value determined by the site category and design earthquake grouping, use a two-dimensional array string[,] to store them respectively, using the key-value pair collection class KeyValuePair<int,string> Locate the maximum value of the seismic influence coefficient and the design characteristic period value.

[0083] 2) Define two methods of obtaining piecewise functions, ElasticSpectrum() and DemandSpectrum(). After passing in the corresponding parameters, first call ElasticSpectrum() to calculate the data. The purpose is to first convert the seismic influence coefficient curve into an elastic response spectrum, and then call DemandSpectrum() to convert the elastic response spectrum curve into a demand spectrum curve.

[0084] S1.3 Determination of the equivalent yield point in the capacity spectrum curve

[0085] The method of converting the capability spectrum curve into a bilinear capability curve is as follows Figure 4 The implementation is as follows:

[0086] 1) The method for determining the initial yield point is to read the steel bar strain data output by Pushover analysis, locate the structural base shear force and displacement when the tensile steel bar first reaches the yield strain by traversal and comparison, and correspond to the stored S d and S a In the data table, locate the corresponding point on the capacity spectrum curve when the tensile reinforcement yields for the first time Connect the coordinates (0,0) and Point, get the straight line E(S d ).

[0087] 2) The method for determining the limit point is: E(S d ) is extended to intersect with the demand spectrum curve under a major earthquake, and a vertical line is drawn through the intersection point to intersect with the capacity spectrum curve. The intersection point is the limit point (maxD, maxA), which is denoted as S2.

[0088] 3) Determination of equivalent yield point: Through the equal energy criterion and iterative calculation, the straight line E(S d ) to find the yield point (d y ,a y ), expressed as S1. A bilinear capacity spectrum curve is established with three points (0,0), S1 and (maxD,maxA), so that the integral value of the capacity spectrum after bilinearization is equal to the integral value of the original capacity spectrum. The program flow for determining the yield point is as follows: Figure 5 shown.

[0089] S1.4 Determination of performance points

[0090] like Figure 6 As shown in the figure, the demand spectrum is reduced by assuming a ductility coefficient, and the displacement of the intersection of the capacity spectrum and the demand spectrum is divided by the displacement of the equivalent yield point to obtain the actual ductility coefficient. The two ductility coefficients are compared. When the difference is large, the assumed ductility coefficient is adjusted for iterative calculation. When the two are within the allowable error range, the iterative calculation is stopped and the intersection is determined as the performance point. The implementation method is:

[0091] 1) Using Gaussian fitting algorithm, the capacity spectrum data points (S d ,S a ) is substituted into multiple fitting functions for calculation, and the correlation coefficient R obtained by each function is 2 The degree closest to 1 is selected, and the fitting method is selected to obtain the fitting function equation.

[0092] 2) Determine the intersection of the energy spectrum and the demand spectrum through dichotomy.

[0093] 3) When the intersection point meets the error limit requirement, it is determined to be a performance point, and the horizontal and vertical coordinates of the point are stored as decimal type data respectively.

[0094] 4) If the displacement of the yield point is significantly smaller than the displacement of the intersection point, it means that the structure has entered the plastic response stage, and a finite number of iterations are required to obtain the performance point; if the displacement of the intersection point is not greater than the displacement of the yield point, it means that the structure is still in the elastic response stage, and the first intersection point is directly taken as the performance point without iterative calculation.

[0095] 5) After the coordinates of the performance points are obtained, the top target displacement of the structure can be reversely calculated according to formula (1).

[0096] S1.5 Deterministic evaluation of structural seismic performance

[0097] 1) Obtain the performance target set by the user through the value transfer method between user controls, and quantify the performance target into a specific value.

[0098] 2) Get the data in the target displacement text box, match it with the Pushover file data stored in the Datatable class, locate the position coordinates of the data, and obtain the maximum inter-story displacement angle of the building structure at the performance point through the position coordinates corresponding to the Influence-Datatable class table.

[0099] 3) Compare the maximum value with the above quantitative value to evaluate whether the structure meets the target requirements of seismic performance at that level.

[0100] 4) The same method can be used to evaluate other levels of seismic performance targets, and ultimately evaluate multiple levels of seismic performance targets.

[0101] S1.7 Capability spectrum analysis program developed

[0102] The basic operation process of the developed capacity spectrum analysis program is as follows: Pushover and other data loading → capacity spectrum determination → setting of seismic performance targets → demand spectrum determination → determination of performance points and analysis data display → deterministic evaluation of seismic performance.

[0103] Figure 7The interface for setting earthquake parameters and seismic performance targets includes: loading of pushover analysis data, structural vibration mode data and structural quality data; selection of design earthquake grouping, fortification intensity and site category; setting of earthquake impact level and corresponding performance level (damage level). After completing the settings of this interface, you can conduct capacity spectrum analysis. Figure 8 This is the analysis interface of the capacity spectrum method. The interface displays the capacity spectrum and demand spectrum curves used to determine the target performance point, and gives the performance point coordinates obtained by analysis and the converted top-level target displacement.

[0104] S2. Implementation of IDA and seismic evaluation functions

[0105] S2.1 Implementation of IDA functions based on RTO program

[0106] The Revit model is converted into a TCL command stream that can be read by the OpenSEES software through the RTO program. On this basis, RTO is improved and a program that is integrated into the Revit software and can generate a TCL command stream for IDA is developed. The implementation method is:

[0107] 1) Store the seismic wave data, target amplitude modulation peak value and seismic wave data time interval through the collection of DataList, AimPeakList and DtList, call the InsertIDATCL() method, and add the selected analysis records and these three data to the command stream output method of this program according to the logic of TCL code operation.

[0108] 2) Add the above method flow to the foreach nested loop to facilitate repeated analysis.

[0109] 3) Since OpenSEES outputs the analysis results once for each analysis, in order to distinguish the data output under different amplitude modulation peak values ​​for each seismic motion data and ensure that the output storage of the result file is not overwritten, the data file naming method defined in the program is: "directory name containing the application + seismic motion sequence number + target peak value + analysis item name". First, the loaded seismic motion data are uniformly numbered in the program, and then the numbered data are stored in OrderList, and then the data in AimPeakList is obtained to implement the loop for the i-th time, and the data with subscript i is obtained from the collection to participate in the file path naming method, and finally the InsertIDATCL() method is called to add the process to the command stream output method.

[0110] 4) Call the command stream output method to output the TCL command stream of IDA, and finally call OpenSEES to start analysis.

[0111] S2.2 Draw the IDA mean curve

[0112] 1) Use the Directory.GetFiles() method to read the IDA data, and write a method to obtain the maximum inter-story displacement angle to obtain the maximum inter-story displacement angle value of each floor of the building structure under different PGAs, and store it in the static properties.

[0113] 2) Take out the fixed-length data in the collection and compare them to determine the unique maximum inter-story displacement angle and the floor where the displacement angle is located under the same PGA for each earthquake motion; at the same time, store the maximum inter-story displacement angle under each earthquake motion in the Angledata attribute field of the DataBase class to facilitate the call of the data access layer.

[0114] 3) Based on PGA, classify the data in Angledata, calculate the average of the maximum interlayer displacement angles of all seismic waves under the same PGA, and store them in the generic collection of the double class.

[0115] 4) Obtain the mean maximum interlayer displacement angle under each PGA, store it in double[]X, store the PGA data in double[]Y, and use the ZedGraphe control to draw the IDA mean curve.

[0116] S2.3 Data post-processing

[0117] The result data of IDA is large and complicated. The analysis data obtained based on different earthquake motions are classified and stored in different folders, and then different PGA data are subdivided in each folder. The present invention outputs files according to the above naming method, and all file data are uniformly stored in the "ExitRecorder" folder under the program running directory for easy search. The FileStream class and StreamWriter class are mainly used to read and write files, and the ExportExcelFile() and WriteFile() methods are used to realize the output file in the out, txt and other format types.

[0118] S2.4 Deterministic evaluation of structural seismic performance

[0119] First, the seismic performance target is set to determine the performance level that the structure should meet when reaching a certain PGA, and the quantitative limit is automatically determined; then the GetMeanresult() method is used to obtain the maximum inter-story displacement angle mean data that has been calculated and stored in the static properties under the target PGA, and all the located mean data are stored in an array of double type; finally, the size of each quantitative limit is compared with the above mean data in turn, and the array length is used as the number of loops. The evaluation results under each level of seismic performance target are obtained by repeated judgment.

[0120] IDA program developed by S2.6

[0121] The basic operation process of the developed IDA program is as follows: IDA parameter setting, seismic wave selection → generation of TCL command stream → starting IDA, automatic drawing of IDA mean curve → setting seismic performance target → deterministic evaluation of seismic performance.

[0122] Fig. 9 It is an interface for IDA parameter setting and TCL command flow display, including seismic wave selection, seismic wave peak amplitude modulation and time interval setting, performance index selection, etc. In addition, this interface also displays IDA's TCL command flow for inspection and modification. Fig.10 This is the IDA analysis interface, through which you can start IDA, draw the IDA mean curve, and export IDA analysis data.

[0123] Functional implementation of S3 earthquake vulnerability analysis

[0124] With the help of the structural performance parameters provided by IDA as sample analysis data, the seismic vulnerability analysis of the structure is carried out, and the structural vulnerability curve and component vulnerability curve are drawn. Based on the seismic vulnerability curve, the probability of the structure achieving various levels of seismic performance targets is predicted by the Monte Carlo algorithm.

[0125] S3.1 Calculation of Damage Exceedance Probability

[0126] The external parameters provided by the user are obtained through UI interaction and stored as a collection class; according to the engineering requirement parameters of the structure and components, the matching structural performance parameters are obtained from the data calculated and sorted by the IDA analysis module; the two types of data are brought into the seismic vulnerability analysis model for calculation to obtain the probability P of the structure and components being in or exceeding different limit states f .

[0127] S3.2 Interaction between user and system

[0128] A modal main window is started. When performing component vulnerability analysis, the user needs to interact with the Revit model and start a non-modal window. The present invention adopts Revit secondary development to realize the interactive function, opens an interactive event with the model, and mainly uses the PickObject() method to realize the user's selection of the target component, and returns the selected model data to the system for storage. When the target component obtains the command, the exceedance probability data of the corresponding component in the memory can be determined by locating the ID of the structural unit.

[0129] S3.3 Drawing the vulnerability curve

[0130] For the structure, the point coordinates (PGA, P f), the structural fragility curve can be drawn. For components, data matching is required through the interaction between the model and the system to further draw the component fragility curve. The specific process is as follows Fig.11 shown.

[0131] S3.4 Realization of earthquake damage uncertainty analysis function

[0132] The seismic damage of components is divided into five levels: OP, IO, LS, CP and collapse (or near collapse). Therefore, the fragility curve is divided into five regions along the longitudinal direction. Using the Monte Carlo simulation algorithm, 1000 random numbers from 0 to 1 are generated and assigned to P f If the target PGA is used as the horizontal coordinate, 1000 point coordinates are generated. The frequency of them falling in different damage areas is counted, which is approximately the probability distribution of damage. This can reflect the uncertainty of earthquake effects and structural resistance, and predict the probability of the structure achieving various levels of seismic performance targets. The specific process is as follows: Fig.12 The key to implementing this method is to generate random numbers and determine the critical value of each damaged area.

[0133] 1) Generate random numbers

[0134] If the default method is used to generate random number seeds, continuous calls in a short period of time will result in the generation of the same random number, resulting in poor simulation effect. Therefore, the present invention uses Guid.NewGuid().GetHashCode() to generate seeds, thereby improving the uniformity and non-repetitiveness of the obtained data.

[0135] 2) Determine the critical value of the damaged area

[0136] Based on the seismic fragility curve and the maximum inter-story displacement angle θ of the structure input by the user m , through coordinate transformation and linear interpolation method, the critical value for dividing the damage level area is obtained.

[0137] Seismic vulnerability analysis program developed by S3.5

[0138] The basic operation process of the developed seismic vulnerability analysis program is:

[0139] 1) Structural seismic vulnerability analysis: Input the maximum inter-story displacement angle θ m The standard deviation and limit [θ] of the program → start the vulnerability analysis, automatically draw the vulnerability analysis curve → export the analysis data. The program operation interface is as follows Fig.13 shown.

[0140] 2) Component seismic vulnerability analysis: Load the beam-column component rotation angle β mLimit data → Select the component to be analyzed → Start component vulnerability analysis, automatically draw vulnerability curve → Export analysis data. The program operation interface is as follows Fig.14 shown.

[0141] 3) Earthquake damage uncertainty analysis: Input θ m or β m → Start the analysis → Get the normalized frequency corresponding to each damage level. The program interface is as follows Fig.15 shown.

[0142] The foregoing description of specific exemplary embodiments of the present invention is for the purpose of illustration and demonstration. These descriptions are not intended to limit the present invention to the precise form disclosed, and it is clear that many changes and variations can be made based on the above teachings. The purpose of selecting and describing the exemplary embodiments is to explain the specific principles of the present invention and its practical application, so that those skilled in the art can realize and utilize various different exemplary embodiments of the present invention and various different selections and changes. The scope of the present invention is intended to be limited by the claims and their equivalents.

Claims

1. A method for analyzing and evaluating the seismic performance of RC frame structures integrated into Revit software, characterized in that: include: Capacity spectrum analysis and seismic performance evaluation based on Revit model: The model parameters required for capacity spectrum analysis are automatically obtained through Revit API, and the RTO program is started to convert the model data of the Revit model and call OpenSEES software for Pushover analysis. The Pushover analysis results, related structural model parameters, and interactive parameters for setting multi-level performance targets are used as basic data to implement the capacity spectrum curve conversion, demand spectrum curve conversion, and performance point iterative calculation capacity spectrum analysis functions in Revit software, and then a deterministic evaluation is performed for different seismic performance targets; Incremental dynamic analysis (IDA) and seismic performance evaluation based on Revit model: Develop IDA function in RTO program, perform model data conversion, and repeatedly call OpenSEES software to perform elastic-plastic time-history analysis with step-by-step excitation for a large amount of selected seismic motion data to obtain IDA average data; perform deterministic seismic performance evaluation based on IDA data according to the IDA average data and the interactive parameters of setting multi-level performance targets; Seismic vulnerability analysis based on Revit model: Develop IDA function in RTO program, and use Revit API to perform seismic damage limit state probability analysis on structures and components in Revit software according to the seismic vulnerability analysis model; and Through the Monte Carlo simulation algorithm, an analysis method for uncertainty of overall structural damage is established.

2. The method for analyzing and evaluating the seismic performance of a RC frame structure integrated into Revit software according to claim 1, characterized in that: When analyzing the capacity spectrum and evaluating the seismic performance, the structure is first subjected to a Pushover analysis, and then the top displacement-base shear (U n -V b ) format curve is converted into spectral displacement-spectral acceleration (S d -S a ) format: Where M1 * is the equivalent mass of the first vibration mode of the structure, τ1 is the vibration mode participation coefficient of the first vibration mode; Φ n1 is the vibration mode value of the top layer of the structure. Generally, the first vibration mode is normalized, so Φ n1 =1; V b is the maximum shear force value of the structural base; The demand spectrum curve is converted into the earthquake acceleration response spectrum (TS) according to the earthquake influence coefficient curve (T-α) with a damping ratio of 5% in the "Code for Seismic Design of Buildings". a ), and then use formula (2) to convert TS a The response spectrum in S format is converted into d -S a The demand spectrum of the format: Where T is the basic period of the structure; S d -S a Capacity spectrum curve and S d -S a The demand spectrum curve in the same coordinate system is plotted in the same format, and the performance points of the structure under a given earthquake intensity are obtained according to the ATC-40 method.

3. A method for analyzing and evaluating the seismic performance of RC frame structures integrated into Revit software according to claim 1 or 2, characterized in that: The specific implementation methods of capacity spectrum analysis and seismic performance evaluation are as follows: 1) Setting multiple levels of seismic performance targets Through UI interaction, set the corresponding earthquake damage level expected to be achieved by the structure under various earthquake intensities, and then determine the multi-level seismic performance targets of the structure; 2) Determine performance points The Revit model is converted into a TCL command stream that can be read by the OpenSEES software through the RTO program, and the OpenSEES software is started in the RTO to perform a pushover analysis to obtain the base shear-vertex displacement data; The RTO program obtains the representative value of the gravity load and vibration mode data of the model structure, converts the base shear-apex displacement capacity curve into a capacity spectrum; selects the design earthquake group, fortification intensity and site category, and automatically establishes a demand spectrum; performs multiple iterative calculations on the intersecting capacity spectrum curve and demand spectrum curve to obtain the performance point, and converts it into the target displacement of the structure; 3) Earthquake resistance evaluation The inter-story displacement angle and top-floor displacement data obtained by Pushover analysis are stored in the running directory file; the inter-story displacement angle of the structure corresponding to the performance point is compared with the inter-story displacement angle limit value to draw the seismic performance evaluation conclusion.

4. The method for analyzing and evaluating the seismic performance of a RC frame structure integrated into Revit software according to claim 1, characterized in that: The implementation of incremental dynamic analysis IDA is as follows: 1) Establish finite element analysis model; 2) Determine the earthquake intensity index IM and the structural engineering demand parameter EDP; 3) Performing step-by-step amplitude modulation on a piece of seismic motion data to obtain a series of seismic motion data; 4) Perform dynamic time history analysis on the structure to obtain a series of (EDP, IM) coordinate points, and connect each discrete point to obtain the IDA curve; 5) Use different seismic data to excite the structure, repeat steps 3) to 4) to obtain the IDA curve cluster.

5. A method for analyzing and evaluating the seismic performance of RC frame structures integrated into Revit software according to claim 1 or 4, characterized in that: The specific implementation methods of incremental dynamic analysis IDA and seismic performance evaluation are as follows: 1) Incremental elastoplastic analysis Develop the IDA function in the RTO program, automatically form a TCL command flow for IDA through parameter setting and seismic data selection, and then call the OpenSEES software to perform incremental loop calculation to obtain IDA data; 2) Seismic performance evaluation based on IDA The performance target of the structure is determined based on the seismic peak acceleration PGA of a selected earthquake intensity and the set seismic performance level. Then, based on the PGA target value, the structural response data or damage data of the target state is located from the IDA average curve. These data are compared with the limit values ​​of the performance target to determine whether the structure meets the set seismic performance target requirements.

6. The method for analyzing and evaluating the seismic performance of RC frame structures integrated into Revit software according to claim 1, characterized in that: Seismic vulnerability analysis refers to calculating the probability of failure of a structure reaching or exceeding a certain limit state under earthquakes of different intensity indicators. By drawing vulnerability curves and structural vulnerability matrices, the probability of damage and destruction of the structure under different levels of earthquakes can be predicted. Under the action of a certain earthquake intensity IM, the conditional failure probability that the EDP reflecting the structural damage reaches or exceeds the limit value [EDP] is expressed as P f ; When EDP and [EDP] both obey lognormal distribution, P f It is obtained from the following formula: Where Φ{·} is the probability distribution function of the standard normal random variable; μ [EDP] is the average value of [EDP], σ EDPm and σ [EDP] EDP m and the logarithmic standard deviation of [EDP], where EDP m is the maximum value of EDP; where a and b are regression parameters, which can be obtained by formula (4). ln(μ Dm )=a+bln(IM) (4) In the formula, μ EDPm is the EDP obtained using multiple ground motion data m By adjusting the size of IM, we can get a series of (IM, μ EDPm ), and then the regression analysis method can be used to obtain the parameters a and b.

7. The method for analyzing and evaluating the seismic performance of RC frame structures integrated into Revit software according to claim 1, characterized in that: Seismic vulnerability analysis of the entire structure: EDP uses the maximum inter-story displacement angle θ m As the judgment index of the overall structural damage, IM uses PGA to divide the overall structural damage level into four levels: OP, IO, LS and CP. The damage judgment criteria are shown in Table 1. OP ,θ IO ,θ LS and θ CP are θ corresponding to the four structural damage states. m The limits are 0.2%, 1%, 2% and 4% respectively; thus, the IDA of multiple ground motion data can be used to obtain θ m -PGA relationship, and then use formulas (4) and (3) to establish PGA-P corresponding to different damage levels f Format structure overall seismic vulnerability curve; Table 1 Based on θ m The overall damage judgment standard of RC frame structure Seismic fragility analysis of beams and columns: EDP uses the maximum rotation angle β of the components m As a criterion for component damage, IM still uses PGA; According to the "Evaluation Standard for Seismic Resilience of Buildings", the damage status of beams and columns is divided into five levels: intact (level 0), slightly damaged (level 1), slightly damaged (level 2), moderately damaged (level 3) and severely damaged (level 4); Based on the maximum rotation angle β m The damage judgment criteria are shown in Table 2. y , β IO , β P and β u are the rotation limits corresponding to the nominal yield point, performance point, peak point and limit point of beam and column components respectively; therefore, the PGA-β of beam and column components can be obtained through IDA of multiple ground motion data. m Substituting the average data of the relationship into the seismic vulnerability analysis model, we can obtain the seismic vulnerability curves of components corresponding to different damage levels. Table 2 Based on β m The criterion for judging the normal section damage of beam-column components in RC frame structures 8. The method for analyzing and evaluating the seismic performance of RC frame structures integrated into Revit software according to claim 1, characterized in that: The specific analysis method of damage uncertainty is as follows: in the coordinate system of the seismic vulnerability curve of the entire structure, a line perpendicular to the horizontal axis is drawn according to the given PGA, and the line intersects with the seismic vulnerability curves of different damage levels to obtain four points P1, P2, P3 and P4; a number R is randomly generated, R∈[0,1]; if R belongs to the interval [P1,100%], the damage level of the structure is OP; if R belongs to the interval [P2,P1), the damage level of the structure is IO; if R belongs to the interval [P3,P2), the damage level of the structure is LS; if R belongs to the interval [P4,P3), the damage level of the structure is CP, and if R belongs to the interval [0,P4), the damage level of the structure is collapse or near collapse; The Monte Carlo simulation algorithm is used to analyze the uncertainty of seismic damage of the entire structure; based on a given θ m , the corresponding PGA value is obtained by the IDA average curve, and the PGA value is substituted into the fragility curve to divide the five damage regions. 1000 numbers R are randomly generated, and the structure is obtained by statistical frequency calculation at a given θ m The probability distribution results of different damage levels.

9. The method for analyzing and evaluating the seismic performance of RC frame structures integrated into Revit software according to claim 1, characterized in that: The Revit model includes: Interaction layer: used to carry the interactive data content between users and systems, pass parameters to the logic layer, and after being processed by the logic layer, the data access layer calls the data operation process and provides data content; Logic layer: handles model conversion, spectrum curve conversion and various function scheduling, performs specific logic operation processing, and functions scheduling for data access in the data access layer; Data access layer: responds to the function scheduling of the logic layer, calls the stored procedure, directly operates the data layer, and updates the storage or reading of data; Data layer: for data access layer scheduling, including seismic performance index corresponding data, IDA data, and structural model data.

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