CN111027247B - A step-by-step incremental dynamic analysis and data processing method based on OpenSees and MATLAB - Google Patents

A step-by-step incremental dynamic analysis and data processing method based on OpenSees and MATLAB Download PDF

Info

Publication number
CN111027247B
CN111027247B CN201911246875.9A CN201911246875A CN111027247B CN 111027247 B CN111027247 B CN 111027247B CN 201911246875 A CN201911246875 A CN 201911246875A CN 111027247 B CN111027247 B CN 111027247B
Authority
CN
China
Prior art keywords
analysis
command
matlab
opensees
writing
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201911246875.9A
Other languages
Chinese (zh)
Other versions
CN111027247A (en
Inventor
刘赛
顾冬生
罗国胜
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Jiangnan University
Original Assignee
Jiangnan University
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Jiangnan University filed Critical Jiangnan University
Priority to CN201911246875.9A priority Critical patent/CN111027247B/en
Publication of CN111027247A publication Critical patent/CN111027247A/en
Application granted granted Critical
Publication of CN111027247B publication Critical patent/CN111027247B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Geophysics And Detection Of Objects (AREA)

Abstract

本发明公开了一种基于OpenSees与MATLAB的逐步增量动力分析与数据处理方法。本发明一种基于OpenSees与MATLAB的逐步增量动力分析与数据处理方法,包括:根据结构设计参数,建立OpenSees结构有限元分析模型;地震波文件名称命名,编写地震波列表;编写目标调幅峰值列表和地震动时间间隔列表;编写OpenSees输出的数据文件名称命令流;编写OpenSees加载地震波命令流;编写在计算不收敛时自动切换算法命令流;编写在倒塌临界状态分析终止命令流;编写MATLAB软件读取OpenSees软件输出数据并写入到Excel表格中的命令流。本发明的有益效果:本发明提出了一种基于OpenSees与MATLAB的逐步增量动力快速分析与数据处理方法,解决了在地震波切换、地震动峰值进行调幅时。

Figure 201911246875

The invention discloses a step-by-step incremental dynamic analysis and data processing method based on OpenSees and MATLAB. The present invention is a step-by-step incremental dynamic analysis and data processing method based on OpenSees and MATLAB. Time interval list; write the command stream of the data file name output by OpenSees; write the command stream of OpenSees to load seismic waves; write the command stream of automatic switching algorithm when the calculation does not converge; write the command stream to terminate the analysis in the critical state of collapse; write the MATLAB software to read the OpenSees The software outputs the data and writes it to the command stream in the Excel table. Beneficial effects of the present invention: The present invention proposes a step-by-step incremental dynamic fast analysis and data processing method based on OpenSees and MATLAB, which solves the problem of amplitude modulation during seismic wave switching and ground motion peak value.

Figure 201911246875

Description

Stepwise incremental dynamic analysis and data processing method based on OpenSees and MATLAB
Technical Field
The invention relates to the field of engineering, in particular to a step-by-step incremental dynamic analysis and data processing method based on OpenSees and MATLAB.
Background
Modern theory of seismic design has been built since the beginning of the 20 th century. With the continuous deepening of understanding of earthquake dynamic characteristics and structural dynamic characteristics, the structural earthquake-proof design theory develops from an initial static force stage and a reaction spectrum stage to a dynamic stage and a current earthquake-proof design theory stage based on Performance (PBSD). An Incremental Dynamic Analysis (IDA) method is based on Dynamic elastoplasticity time course Analysis, and the basic idea is that for a specific seismic motion input, a series of monotonically increasing seismic intensity indexes IM (intensity measure) are set, and structural elastoplasticity time course Analysis is performed on the seismic input under each seismic intensity index to obtain a series of structural elastoplasticity seismic response indexes DM (Damage measure), so that an IM-DM curve (IDA curve) is formed. Compared with a static elastoplasticity analysis method, the IDA method is used for simulating the dynamic response of the structure under the earthquake, so that the problem caused by simplification of the static elastoplasticity analysis can be avoided. The whole reaction process from elasticity to elastoplasticity to structural dynamic instability is covered, the earthquake demand capability and the whole collapse resistance capability of the structure under earthquakes of different strength grades can be reflected, and the change process of the strength, the rigidity and the deformation of the structure can be reflected.
The traditional technology has the following technical problems:
at present, commercial software such as PKPM, encyclopedia, SAP2000, and Perform3D can Perform time course analysis, but the incremental step dynamic analysis cannot be performed in batch. Commercial software can only analyze one seismic wave at a time, and can analyze the next wave after the analysis of the previous wave is finished. While the gradual incremental dynamic analysis needs tens of log seismic waves and each seismic wave is amplitude-modulated for tens of times for analysis, for example, 20 seismic waves and each seismic wave is amplitude-modulated for 20 times, 400 times of analysis is needed, which is very complicated in workload and wastes a lot of time and energy for commercial software if one seismic wave is manually input. In addition, the data output is complicated, and thousands of output files are piled up, so that valuable data indexes cannot be found quickly.
Disclosure of Invention
The invention aims to provide a step-by-step incremental dynamic analysis and data processing method based on OpenSees and MATLAB.
In order to solve the technical problems, the invention provides a step-by-step incremental dynamic analysis and data processing method based on openses and MATLAB, which comprises the following steps:
establishing an OpenSees structure finite element analysis model according to the structure design parameters;
naming the seismic wave file name, and compiling a seismic wave list;
compiling a target amplitude modulation peak list and a seismic oscillation time interval list;
writing a data file name command stream output by OpenSees;
writing an OpenSees earthquake wave loading command stream;
compiling an automatic switching algorithm command stream when the calculation is not converged;
the command stream of the terminal is analyzed and written in the collapse critical state;
writing a command stream of MATLAB software reading OpenSees software output data and writing the data into an Excel table.
In another embodiment, the "establishing an openses structural finite element analysis model according to the structural design parameters" specifically includes:
the end part of the beam-column unit adopts an IMK corner spring unit, and the upper unit adopts an elastic beam column Element which is connected with the IMK corner spring unit in series; the specific parameters of the IMK corner spring are calculated according to a formula according to the design parameters of the section; because the component is formed by connecting an IMK corner spring and an elastic BeamColumn Element in series, the upper elastic BeamColumn Element needs to be corrected for the flexural rigidity, and the calculation formula is as follows:
Figure BDA0002307895720000031
the node adopts Joint2D Element;
and (3) adopting rayleigh damping, respectively giving a rigidity proportionality coefficient and a mass proportionality coefficient to the elastic unit and the node with mass by using a region command, and adopting initial rigidity in the calculation process.
In another embodiment, the "name of seismic wave file name, writing seismic wave list" specifically includes:
because the input seismic waves are several or even dozens of seismic waves, each seismic wave to be analyzed is named, the name of an output data file is determined by the name of each seismic wave, the name is also the file name searched during MATLAB post-processing, and Arabic numerals 1,2 and 3 are named for simplicity;
a list of seismic wave names, denoted as AA, is written in openses for the foreach loop.
In one embodiment, the "writing a list of target amplitude modulation peaks and a list of seismic motion time intervals" specifically includes:
writing a target amplitude modulation peak list in an OpenSees model, recording the target amplitude modulation peak list as BB, and using the BB for foreach circulation;
writing and reading each seismic wave time interval array by using a list command in an OpenSees model, and marking the array as dt _ AA, wherein the dt _ AA is used for identifying the time interval of each seismic wave.
In one embodiment, writing a data file name command stream output by openses specifically includes:
naming each seismic wave name as an output data folder, and creating a folder for analyzing seismic wave output files by using a filemkdir command;
and naming each seismic oscillation name and the target amplitude modulation peak value as output data files.
In one embodiment, "writing openses load seismic wave command stream" specifically includes:
firstly, opening a seismic oscillation file by using an open command; reading data in the earthquake motion file by using a read command, sequencing earthquake motion data by using an lsort command according to an increasing sequence, acquiring an earthquake motion peak value by using a lindex command, and acquiring a total earthquake motion step number by using a llength command.
In one embodiment, writing a command stream for automatically switching algorithms when the computation does not converge specifically includes:
when the calculation is not converged, firstly, reducing the analysis step time, adjusting the analysis step time to 0.5 time, and transmitting the analysis step time to an algorithm for analysis; when the convergence is not reached again, the integration method is automatically switched: performing (Newton iteration method Krylov Newton of Krylov accelerated convergence) - (Newton iteration method Newton) in the following sequence, wherein the initial stiffness is adopted in the first step, then Newton-initial ThernCurrent is adopted in the Newton iteration method Newton-initial ThernCurrent of the current stiffness, and Linear Newton iteration method Newton LineSearch of solving the nonlinear residual equation (modified Newton iteration method ModifiedNewton) - (Linear iteration method Linear);
if the switching integration method still does not converge, the structure is judged to reach the collapse critical point, and the analysis is terminated.
In one embodiment, the "writing of the analysis termination command stream in the collapse critical state" specifically includes:
if the collapse critical state is judged to be reached, analyzing for one step to finish time course analysis; opening the output file by using an open-r command, writing a puts command into 0.20.2, covering records before analysis unconvergence, taking the records as an analysis unconvergence mark, and closing the file by using close;
the file mkdir FailRecord creates an analysis failure record folder, and the open-w command creates a new txt file, which records the analysis unconverged seismic wave name and the target amplitude at this time.
In one embodiment, writing a command stream in which MATLAB software reads openses software output data and writes the data into an Excel table specifically includes:
reading output file data by utilizing a sprintf command in MATLAB, searching a damage index maximum value and an xlswrite function by a max function, and writing the earthquake motion name, a target peak value and the damage index maximum value into a specified position in an Excel table.
Based on the same inventive concept, the present application also provides a computer device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the steps of any of the methods when executing the program.
Based on the same inventive concept, the present application also provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of any of the methods.
Based on the same inventive concept, the present application further provides a processor for executing a program, wherein the program executes to perform any one of the methods.
The invention has the beneficial effects that:
the invention provides a step-by-step incremental dynamic rapid analysis and data processing method based on OpenSees and MATLAB, which solves the complex steps of manually changing seismic oscillation peak values, seismic oscillation step numbers and scaling information when seismic oscillation peak values are switched and amplitude modulated; under the conditions of no shutdown and no manual intervention, the problem that the dynamic elastoplasticity time course analysis cannot be carried out in batches is solved, the model calculation efficiency is greatly improved, and software and hardware resources are fully utilized; meanwhile, in the aspect of data post-processing, the MATLAB is used for rapidly reading the output data file and writing the data file into an Excel table, so that the data processing efficiency is greatly improved, the tedious and time-consuming analysis becomes simple and feasible, the boring manual workload and the possibility of writing errors are greatly reduced, and scientific research personnel can spend more energy on parameter analysis. The method for rapidly analyzing and processing the data based on the step-by-step incremental power of OpenSees and MATLAB quickly and accurately solves the problems of batch analysis and data post-processing. The OpenSees is called an Open System for Earthquake Engineering Simulation (Open System) in its entirety. The Earthquake simulation system is an open program software system which is more comprehensive and continuously developed and is mainly developed by American National Science Foundation (NSF) funding, Pacific Earth Engineering Research Center (PEER) of western university alliance and Berkeley university of California and is used for simulating Earthquake response in structural and geotechnical aspects. MATLAB is a commercial mathematical software produced by MathWorks corporation, usa, a software for advanced technical computing languages and interactive environments for algorithm development, data visualization, data analysis, and numerical computation.
Drawings
FIG. 1 is a flow chart of a step-by-step incremental dynamic analysis and data processing method based on OpenSees and MATLAB in the invention
FIG. 2 is a series diagram of IMK corner springs and elastic Beam column elements in the OpenSees and MATLAB based incremental step-by-step power analysis and data processing method of the present invention.
Fig. 3 is a schematic diagram of an IMK corner spring skeleton curve and a hysteresis law in the stepwise incremental dynamic analysis and data processing method based on openses and MATLAB of the present invention.
Fig. 4 is a schematic diagram of a Joint2D unit in the method for step-by-step incremental dynamic analysis and data processing based on openses and MATLAB.
FIG. 5 is a graph of Rayleigh damping versus frequency, mass, and stiffness in a step-by-step incremental dynamics analysis and data processing method based on OpenSees and MATLAB of the present invention.
FIG. 6 is a schematic diagram of IDA curves in the step-by-step incremental dynamic analysis and data processing method based on OpenSees and MATLAB of the present invention.
Detailed Description
The present invention is further described below in conjunction with the following figures and specific examples so that those skilled in the art may better understand the present invention and practice it, but the examples are not intended to limit the present invention.
A step-by-step incremental power rapid analysis and data processing method based on OpenSees and MATLAB comprises the following steps:
step 1, establishing an OpenSees structure finite element analysis model according to structure design parameters;
step 2, naming the seismic wave file name, and compiling a seismic wave list;
step 3, compiling a target amplitude modulation peak value list and a seismic oscillation time interval list;
step 4, compiling a data file name command stream output by OpenSees;
step 5, writing an OpenSees earthquake wave loading command stream;
step 6, compiling an automatic switching algorithm command stream when the calculation is not converged;
step 7, compiling an analysis termination command stream in a collapse critical state;
step 8, writing a command stream in which MATLAB software reads OpenSees software output data and writes the OpenSees software output data into an Excel table;
by using MATLAB software, reading a data file output by OpenSees software, and writing data into a specified position in an Excel table, such as a maximum interlayer displacement angle (damage index, DM) and a spectral acceleration (intensity index, IM).
The invention has the beneficial effects that:
the invention provides a step-by-step incremental dynamic rapid analysis and data processing method based on OpenSees and MATLAB, which solves the complex steps of manually changing seismic oscillation peak values, seismic oscillation step numbers and scaling information when seismic oscillation peak values are switched and amplitude modulated; under the conditions of no shutdown and no manual intervention, the problem that the dynamic elastoplasticity time course analysis cannot be carried out in batches is solved, the model calculation efficiency is greatly improved, and software and hardware resources are fully utilized; meanwhile, in the aspect of data post-processing, the MATLAB is used for rapidly reading the output data file and writing the data file into an Excel table, so that the data processing efficiency is greatly improved, the tedious and time-consuming analysis becomes simple and feasible, the boring manual workload and the possibility of writing errors are greatly reduced, and scientific research personnel can spend more energy on parameter analysis.
In another embodiment, the method for establishing the openses structure finite element analysis model according to the structure design parameters specifically comprises the following steps:
1. the end part of the beam-column unit adopts an IMK corner spring unit, and the upper unit adopts an elastic beam column Element which is connected with the IMK corner spring unit in series; the specific parameters of the IMK corner spring are calculated according to a formula according to the design parameters of the section; because the component is formed by connecting an IMK corner spring and an elastic BeamColumn Element in series, the upper elastic BeamColumn Element needs to be corrected for the flexural rigidity, and the calculation formula is as follows:
Figure BDA0002307895720000081
FIG. 2 is a series schematic diagram, and an IMK corner spring skeleton curve and a hysteresis law are shown in FIG. 3;
2. the node adopts Joint2D Element, and FIG. 4 is a schematic diagram of a Joint2D unit;
3. and (3) adopting rayleigh damping, respectively giving a rigidity proportionality coefficient and a mass proportionality coefficient to the elastic unit and the node with mass by using a region command, and adopting initial rigidity in the calculation process.
In another embodiment, the names of seismic wave files are named, and a seismic wave list is written; the method specifically comprises the following steps:
1. because the input seismic waves are several or even dozens of seismic waves, each seismic wave to be analyzed is named, the name of an output data file is determined by the name of each seismic wave, the name is also the file name searched during MATLAB post-processing, and Arabic numerals 1,2 and 3 are named for simplicity;
2. a list of seismic wave names, denoted as AA, is written in openses for the foreach loop.
In one embodiment, a target amplitude modulation peak list and a seismic motion time interval list are written; the method specifically comprises the following steps:
1. writing a target amplitude modulation peak list in an OpenSees model, recording the target amplitude modulation peak list as BB, and using the BB for foreach circulation;
2. writing and reading each seismic wave time interval array by using a list command in an OpenSees model, and marking the array as dt _ AA, wherein the dt _ AA is used for identifying the time interval of each seismic wave.
In one embodiment, the data file name command stream output by openses is written. The method specifically comprises the following steps:
1. naming each seismic wave name as an output data folder, and creating a folder for analyzing seismic wave output files by using a filemkdir command. If the name of the earthquake wave being analyzed is 1, creating a folder with the name of 1, and storing all output files with the name of the earthquake wave being 1 in the folder;
2. naming each seismic oscillation name and target amplitude modulation peak value as output data files, and if the seismic oscillation name under analysis is 1 and the target amplitude modulation peak value is 2.0, then naming the output data files as 1-2-drift (i), wherein the drift is a damage index, the interlayer displacement angle is a damage index, and i is the number of floors.
In one embodiment, an openses load seismic command stream is written. The method specifically comprises the following steps:
firstly, opening a seismic oscillation file by using an open command; reading data in the earthquake motion file by using a read command, sequencing earthquake motion data by using an lsort command according to an increasing sequence, acquiring an earthquake motion peak value by using a lindex command, and acquiring a total earthquake motion step number by using a llength command.
In one embodiment, an automatic switching algorithm command stream is written when the computation does not converge. The method specifically comprises the following steps:
1. when the calculation is not converged, firstly, reducing the analysis step time, adjusting the analysis step time to 0.5 time, and transmitting the analysis step time to an algorithm for analysis; when the convergence is not reached again, the integration method is automatically switched: performing (Newton iteration method Krylov Newton of Krylov accelerated convergence) - (Newton iteration method Newton) in the following sequence, wherein the initial stiffness is adopted in the first step, then Newton-initial ThernCurrent is adopted in the Newton iteration method Newton-initial ThernCurrent of the current stiffness, and Linear Newton iteration method Newton LineSearch of solving the nonlinear residual equation (modified Newton iteration method ModifiedNewton) - (Linear iteration method Linear);
2. if the switching integration method still does not converge, the structure is judged to reach the collapse critical point, and the analysis is terminated.
In one embodiment, the analysis termination command stream in the collapse critical state is written. The method specifically comprises the following steps:
1. if the collapse critical state is judged to be reached, analyzing for one step to finish time course analysis; opening the output file by using an open-r command, writing a puts command into 0.20.2, covering records before analysis unconvergence, taking the records as an analysis unconvergence mark, and closing the file by using close;
and 2, creating an analysis failure record folder by using filemkdir FailRecord, creating a new txt file by using an open-w command, and recording the name of the analysis unconverged seismic wave and the target amplitude at the moment.
In one embodiment, MATLAB software is written as a command stream that reads openses software output data and writes into an Excel table. The method specifically comprises the following steps:
reading output file data by utilizing a sprintf command in MATLAB, searching a damage index maximum value and an xlswrite function by a max function, and writing the earthquake motion name, a target peak value and the damage index maximum value into a specified position in an Excel table.
A specific application scenario is described below:
FIG. 1 shows the steps of the present invention. Performing IDA analysis, namely firstly respectively forming a list of seismic wave interception, a target amplitude modulation peak value and a seismic motion time interval, performing traversal search by using a foreach command, and automatically identifying seismic motion information, such as the peak value and the seismic motion record number, by OpenSees. Firstly, opening a seismic oscillation file by using an open command; reading data in the earthquake motion file by using a read command, sequencing earthquake motion data by using an lsort command according to an increasing sequence, acquiring an earthquake motion peak value by using a lindex command, and acquiring a total earthquake motion step number by using a llength command. And outputting analysis files in the analysis process, and creating a folder for analyzing seismic wave output files by using a file mkdir command. If the name of the earthquake wave being analyzed is 1, creating a folder with the name of 1, and storing all output files with the name of the earthquake wave being 1 in the folder; naming each seismic oscillation name and target amplitude modulation peak value as output data files, and if the seismic oscillation name under analysis is 1 and the target amplitude modulation peak value is 2.0, then naming the output data files as 1-2-drift (i), wherein the drift is a damage index, the interlayer displacement angle is a damage index, and i is the number of floors. And after each cycle is finished, clearing the model, releasing the memory, and reestablishing the model according to the seismic oscillation information of the next cycle until the foreach sentence is finished, wherein manual intervention is not needed in the middle, and the model is automatically switched.
Building a first list: list of seismic waves, AA for short
A second list is established: list of target amplitude modulations, abbreviated as BB
A third list is built: list of seismic intervals, dt _ AA for short
Starting a foreach statement
foreach seismic wave list AA { foreach target amplitude modulation list BB { OpenSees finite element analysis model, lindex command finding seismic time interval FIG. 1}
For example: AA contains A1, A2 and A3 parameters
For example: BB comprises B1, B2 and B3 parameters
For example: dt _ AA comprises parameters of C1, C2 and C3
The calculation sequence is as follows:
cycle 1: the A1, B1 and C1 parameters are transmitted to the model for calculation
Cycle 2: the A1, B2 and C1 parameters are transmitted to the model for calculation
Cycle 3: the A1, B3 and C1 parameters are transmitted to the model for calculation
Cycle 4: the A2, B1 and C2 parameters are transmitted to the model for calculation
Cycle 5: the A2, B2 and C2 parameters are transmitted to the model for calculation
Cycle 6: the A2, B3 and C3 parameters are transmitted to the model for calculation
7, circulation: the A3, B1 and C3 parameters are transmitted to the model for calculation
Cycle 8: the A3, B2 and C3 parameters are transmitted to the model for calculation
Cycle 9: the A3, B3 and C3 parameters are transmitted to the model for calculation
And (3) automatically calculating 9 models, and automatically switching until 9 cycles are finished without manual additional intervention, so that the efficiency is greatly improved, and the time is saved.
The OpenSees calculation result data is output in a text format, and a user can define the name of output content and files. Here the output file is named with the seismic event name at the time, the target amplitude modulation peak and the floor number using the command replaced by the variable, see fig. 1, code: AA- $ BB-dry (i) $ out. For example, the earthquake motion at this time is 1, and the target amplitude modulation peak value is 2.0, then the file name of 1-2-drift (i).
Openses outputs a large amount of data, and then the data needs to be collated to extract useful data so as to facilitate parameter analysis, and the implementation flowchart is shown in fig. 1.
Examples are: the maximum interlayer displacement angles of all model nonlinear analyses are all extracted, and are arranged according to the sequence of seismic wave names, target amplitude modulation peak values and the maximum interlayer displacement angles, as shown in table 1:
Figure BDA0002307895720000121
TABLE 1
This results in a plurality of IDA curves of seismic waves, as shown in FIG. 6.
According to the method, under the condition of no shutdown, the non-linear time-course analysis can be automatically carried out according to the input earthquake motion without manually modifying the earthquake motion peak value, the earthquake motion time interval, the earthquake motion step number and the target amplitude modulation peak value; the structural damage limit state can be customized according to the analysis requirement, the maximum value data of the limit state is extracted from massive data through MATLAB, seismic oscillation information and the maximum value data of the limit state are written into an Excel table according to the analysis requirement, and the data are analyzed conveniently. The model calculation efficiency and the data post-processing efficiency are greatly improved, and software and hardware resources are fully utilized; the method fully realizes the computerization process, makes the analysis which is tedious and time-consuming become simple and feasible, greatly reduces the tedious manual workload and the possibility of errors in writing the manual change data, and makes scientific research personnel capable of spending more energy on parameter analysis.
The invention provides a step-by-step incremental dynamic rapid analysis and data processing method based on OpenSees and MATLAB, which solves the complex steps of manually changing seismic oscillation peak values, seismic oscillation step numbers and scaling information when seismic oscillation peak values are switched and amplitude modulated; under the conditions of no shutdown and no manual intervention, the problem that the dynamic elastoplasticity time course analysis cannot be carried out in batches is solved, the model calculation efficiency is greatly improved, and software and hardware resources are fully utilized; meanwhile, in the aspect of data post-processing, the MATLAB is used for rapidly reading the output data file and writing the data file into an Excel table, so that the data processing efficiency is greatly improved, the tedious and time-consuming analysis becomes simple and feasible, the boring manual workload and the possibility of writing errors are greatly reduced, and scientific research personnel can spend more energy on parameter analysis. With the improvement of the computer processing speed and the maturity of the IDA analysis theory, the IDA analysis is an important tool for structural performance analysis, and the method realizes the quick IDA analysis and data processing.
The above-mentioned embodiments are merely preferred embodiments for fully illustrating the present invention, and the scope of the present invention is not limited thereto. The equivalent substitution or change made by the technical personnel in the technical field on the basis of the invention is all within the protection scope of the invention. The protection scope of the invention is subject to the claims.

Claims (9)

1. A stepwise incremental dynamic analysis and data processing method based on OpenSees and MATLAB is characterized by comprising the following steps:
establishing an OpenSees structure finite element analysis model according to the structure design parameters;
naming the seismic wave file name, and compiling a seismic wave list;
compiling a target amplitude modulation peak list and a seismic oscillation time interval list;
writing a data file name command stream output by OpenSees;
writing an OpenSees earthquake wave loading command stream;
compiling an automatic switching algorithm command stream when the calculation is not converged;
the command stream of the terminal is analyzed and written in the collapse critical state;
writing a command stream in which MATLAB software reads OpenSees software output data and writes the data into an Excel table;
the "establishing an openses structure finite element analysis model according to the structure design parameters" specifically includes:
the end part of the beam-column unit adopts an IMK corner spring unit, and the upper unit adopts an elastic beam column Element which is connected with the IMK corner spring unit in series; the specific parameters of the IMK corner spring are calculated according to a formula according to the design parameters of the section; because the component is formed by connecting an IMK corner spring and an elastic BeamColumn Element in series, the upper elastic BeamColumn Element needs to be corrected for the flexural rigidity, and the calculation formula is as follows:
Figure FDA0003095467010000011
the node adopts Joint2D Element;
and (3) adopting rayleigh damping, respectively giving a rigidity proportionality coefficient and a mass proportionality coefficient to the elastic unit and the node with mass by using a region command, and adopting initial rigidity in the calculation process.
2. The openses and MATLAB-based step-by-step incremental dynamical analysis and data processing method of claim 1, wherein the naming of the seismic wave file name and the writing of the seismic wave list specifically comprises:
because the input seismic waves are several or even dozens of seismic waves, each seismic wave to be analyzed is named, the name of an output data file is determined by the name of each seismic wave, the name is also the file name searched during MATLAB post-processing, and Arabic numerals 1,2 and 3 are named for simplicity;
a list of seismic wave names, denoted as AA, is written in openses for the foreach loop.
3. The openses and MATLAB-based step-by-step incremental dynamical analysis and data processing method of claim 1, wherein writing the target amplitude modulation peak list and the seismic interval list specifically comprises:
writing a target amplitude modulation peak list in an OpenSees model, recording the target amplitude modulation peak list as BB, and using the BB for foreach circulation;
writing and reading each seismic wave time interval array by using a list command in an OpenSees model, and marking the array as dt _ AA, wherein the dt _ AA is used for identifying the time interval of each seismic wave.
4. The openses and MATLAB-based step-by-step incremental dynamical analysis and data processing method of claim 1, wherein writing openses seismic wave loading command streams specifically comprises:
firstly, opening a seismic oscillation file by using an open command; reading data in the earthquake motion file by using a read command, sequencing earthquake motion data by using an lsort command according to an increasing sequence, acquiring an earthquake motion peak value by using a lindex command, and acquiring a total earthquake motion step number by using a llength command.
5. The openses and MATLAB-based step-by-step incremental power analysis and data processing method of claim 1, wherein writing an analysis termination command stream in a collapse critical state specifically comprises:
if the collapse critical state is judged to be reached, analyzing for one step to finish time course analysis; opening the output file by using an open-r command, writing a puts command into 0.20.2, covering records before analysis unconvergence, taking the records as an analysis unconvergence mark, and closing the file by using close;
the file mkdir FailRecord creates an analysis failure record folder, and the open-w command creates a new txt file, which records the analysis unconverged seismic wave name and the target amplitude at this time.
6. The openses and MATLAB-based step-by-step incremental dynamic analysis and data processing method of claim 1, wherein writing a command stream for MATLAB software to read openses software output data and write the openses software output data into an Excel table specifically comprises:
reading output file data by utilizing a sprintf command in MATLAB, searching a damage index maximum value and an xlswrite function by a max function, and writing the earthquake motion name, a target peak value and the damage index maximum value into a specified position in an Excel table.
7. The openses and MATLAB-based step-by-step incremental power analysis and data processing method of claim 1, wherein writing a data file name command stream output by openses specifically comprises:
naming each seismic wave name as an output data folder, and creating a folder for analyzing seismic wave output files by using a file mkdir command;
and naming each seismic oscillation name and the target amplitude modulation peak value as output data files.
8. The openses and MATLAB-based step-by-step incremental dynamic analysis and data processing method of claim 1, wherein writing a command stream for automatically switching an algorithm when computation does not converge specifically comprises:
when the calculation is not converged, firstly, reducing the analysis step time, adjusting the analysis step time to 0.5 time, and transmitting the analysis step time to an algorithm for analysis; when the convergence is not reached again, the integration method is automatically switched: performing (Newton iteration method Krylov Newton of Krylov accelerated convergence) - (Newton iteration method Newton) in the following sequence, wherein the initial stiffness is adopted in the first step, then Newton-initial ThernCurrent is adopted in the Newton iteration method Newton-initial ThernCurrent of the current stiffness, and Linear Newton iteration method Newton LineSearch of solving the nonlinear residual equation (modified Newton iteration method ModifiedNewton) - (Linear iteration method Linear);
if the switching integration method still does not converge, the structure is judged to reach the collapse critical point, and the analysis is terminated.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method of any one of claims 1 to 8.
CN201911246875.9A 2019-12-09 2019-12-09 A step-by-step incremental dynamic analysis and data processing method based on OpenSees and MATLAB Active CN111027247B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201911246875.9A CN111027247B (en) 2019-12-09 2019-12-09 A step-by-step incremental dynamic analysis and data processing method based on OpenSees and MATLAB

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201911246875.9A CN111027247B (en) 2019-12-09 2019-12-09 A step-by-step incremental dynamic analysis and data processing method based on OpenSees and MATLAB

Publications (2)

Publication Number Publication Date
CN111027247A CN111027247A (en) 2020-04-17
CN111027247B true CN111027247B (en) 2021-07-27

Family

ID=70204761

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201911246875.9A Active CN111027247B (en) 2019-12-09 2019-12-09 A step-by-step incremental dynamic analysis and data processing method based on OpenSees and MATLAB

Country Status (1)

Country Link
CN (1) CN111027247B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112948943B (en) * 2021-03-22 2022-11-18 西南交通大学 Pre-processing method and post-processing method of OpenSees software for grid-type diaphragm wall foundation

Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105653786A (en) * 2015-12-29 2016-06-08 中国电建集团贵阳勘测设计研究院有限公司 Internal force calculation method considering shear deformation of closed frame and rigid node

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP5481608B1 (en) * 2012-08-16 2014-04-23 株式会社アクション・リサーチ Vibration processing apparatus and method
CN105425288B (en) * 2015-12-10 2017-11-14 哈尔滨工业大学 A kind of Collapse Response Analysis spectrum based on displacement evaluation index
CN106897510B (en) * 2017-02-16 2020-01-07 西南交通大学 A three-dimensional seismic vulnerability analysis method for bridge structures
CN107577890B (en) * 2017-09-19 2020-04-17 河南大学 Method and system for analyzing earthquake collapse resistance of underground structure
CN108549104B (en) * 2018-04-10 2020-05-29 江南大学 An Analysis Method for Oblique Incidence Fluctuations of Seismic Waves in Layered Sites
CN109598089A (en) * 2018-12-21 2019-04-09 江南大学 RC cylindrical cross-section curve limit state rapid analysis method
CN110175426B (en) * 2019-05-31 2022-06-14 中铁二院工程集团有限责任公司 Design method of railway bridge elastic-plastic metal limiting, damping and energy-consuming device

Patent Citations (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105653786A (en) * 2015-12-29 2016-06-08 中国电建集团贵阳勘测设计研究院有限公司 Internal force calculation method considering shear deformation of closed frame and rigid node

Also Published As

Publication number Publication date
CN111027247A (en) 2020-04-17

Similar Documents

Publication Publication Date Title
CN107239392B (en) Test method, test device, test terminal and storage medium
CN105787128B (en) A method of restoring Java and serializes file data
CN111400338A (en) SQ L optimization method, device, storage medium and computer equipment
CN109254959B (en) A data evaluation method, device, terminal device and readable storage medium
CN111027247B (en) A step-by-step incremental dynamic analysis and data processing method based on OpenSees and MATLAB
CN110083880A (en) Combined optimization design method based on MATLAB and ABAQUS
Deitel et al. Visual C# how to program
CN113536308A (en) A binary code traceability method for multi-granularity information fusion from the perspective of software genes
CN101833455B (en) Code splitting method for converting traditional software into rich client software
US20190121848A1 (en) Automatic translation of spreadsheets into scripts
CN108701153B (en) Method, system and computer readable storage medium for responding to natural language query
CN104182596B (en) Wireless data transmission equipment testing data mining system and method based on LabVIEW and Matlab hybrid programming
Shariat Yazdi et al. Synthesizing realistic test models
CN111638926A (en) Method for realizing artificial intelligence in Django framework
CN110909412B (en) Batch processing method of main feature points of force-displacement curve based on MATLAB
Liu et al. Enhancing test reuse with GUI events deduplication and adaptive semantic matching
WO2022159202A1 (en) Efficient creation and/or restatement of database tables
Gómez-Martínez et al. Towards Extensible Structural Analysis of Petri Net Product Lines.
CN118503270B (en) NL2SQL data set construction method, device, equipment and medium
Ferdous et al. Workflow provenance for big data: from modelling to reporting
CN116795725B (en) Automatic library checking method and system of clinical electronic data acquisition system
Hare et al. Adaptive interpolation strategies in derivative-free optimization: a case study
CN113849887B (en) Offshore wind power foundation design input and output optimization method and system
CN110618809B (en) Front-end webpage input constraint extraction method and device
Wu et al. Identification of Microservices through Processed Dynamic Traces and Static Calls

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant