opstool：用于OpenSeesPy分析自动化的Python库，简化了预处理和后处理，增强了数据可视化

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX Pub Date : 2025-03-18 DOI:10.1016/j.softx.2025.102126

Yexiang Yan , Yazhou Xie

{"title":"opstool：用于OpenSeesPy分析自动化的Python库，简化了预处理和后处理，增强了数据可视化","authors":"Yexiang Yan , Yazhou Xie","doi":"10.1016/j.softx.2025.102126","DOIUrl":null,"url":null,"abstract":"<div><div>This paper presents opstool, a Python package designed to enhance the pre- and post-processing capabilities of OpenSees and OpenSeesPy. It simplifies structural analysis workflows by automating tasks such as mesh generation, data management, and data visualization. The package efficiently manages large-scale simulation results, enabling the structured extraction of system, nodal, and element responses. In addition, it integrates adaptive iteration algorithms to improve convergence issues in nonlinear static and dynamic response analyses. By reducing manual modeling effort and enhancing model accuracy, opstool improves workflow efficiency and enables researchers and practitioners to conduct more effective computational simulations using OpenSees and OpenSeesPy, which further supports various task forces in earthquake engineering, such as performance-based design of new structures and regional seismic risk assessment of existing infrastructure systems.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"30 ","pages":"Article 102126"},"PeriodicalIF":2.4000,"publicationDate":"2025-03-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"opstool: A Python library for OpenSeesPy analysis automation, streamlined pre- and post-processing, and enhanced data visualization\",\"authors\":\"Yexiang Yan , Yazhou Xie\",\"doi\":\"10.1016/j.softx.2025.102126\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This paper presents opstool, a Python package designed to enhance the pre- and post-processing capabilities of OpenSees and OpenSeesPy. It simplifies structural analysis workflows by automating tasks such as mesh generation, data management, and data visualization. The package efficiently manages large-scale simulation results, enabling the structured extraction of system, nodal, and element responses. In addition, it integrates adaptive iteration algorithms to improve convergence issues in nonlinear static and dynamic response analyses. By reducing manual modeling effort and enhancing model accuracy, opstool improves workflow efficiency and enables researchers and practitioners to conduct more effective computational simulations using OpenSees and OpenSeesPy, which further supports various task forces in earthquake engineering, such as performance-based design of new structures and regional seismic risk assessment of existing infrastructure systems.</div></div>\",\"PeriodicalId\":21905,\"journal\":{\"name\":\"SoftwareX\",\"volume\":\"30 \",\"pages\":\"Article 102126\"},\"PeriodicalIF\":2.4000,\"publicationDate\":\"2025-03-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"SoftwareX\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2352711025000937\",\"RegionNum\":4,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, SOFTWARE ENGINEERING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"SoftwareX","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352711025000937","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}

引用次数: 0

摘要

本文介绍了opstool，一个Python包，旨在增强OpenSees和OpenSeesPy的预处理和后处理能力。它通过自动化网格生成、数据管理和数据可视化等任务，简化了结构分析工作流程。该软件包有效地管理大规模模拟结果，使系统，节点和元素响应的结构化提取成为可能。此外，它还集成了自适应迭代算法，以改善非线性静态和动态响应分析中的收敛问题。通过减少人工建模工作量和提高模型准确性，opstool提高了工作流程效率，使研究人员和从业人员能够使用OpenSees和OpenSeesPy进行更有效的计算模拟，从而进一步支持地震工程中的各种任务小组，例如基于性能的新结构设计和现有基础设施系统的区域地震风险评估。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

opstool: A Python library for OpenSeesPy analysis automation, streamlined pre- and post-processing, and enhanced data visualization

This paper presents opstool, a Python package designed to enhance the pre- and post-processing capabilities of OpenSees and OpenSeesPy. It simplifies structural analysis workflows by automating tasks such as mesh generation, data management, and data visualization. The package efficiently manages large-scale simulation results, enabling the structured extraction of system, nodal, and element responses. In addition, it integrates adaptive iteration algorithms to improve convergence issues in nonlinear static and dynamic response analyses. By reducing manual modeling effort and enhancing model accuracy, opstool improves workflow efficiency and enables researchers and practitioners to conduct more effective computational simulations using OpenSees and OpenSeesPy, which further supports various task forces in earthquake engineering, such as performance-based design of new structures and regional seismic risk assessment of existing infrastructure systems.

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.50

自引率

2.90%

发文量

184

审稿时长

9 weeks

期刊介绍： SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.