{"title":"3PB-analyzer: A python-based tool for automated three-point bending analysis","authors":"Yutao He, Xiaodie Fan, Xi Li, Rui Cheng, Bin Wang","doi":"10.1016/j.softx.2025.102177","DOIUrl":null,"url":null,"abstract":"<div><div>This paper presents 3PB-Analyzer, an open-source Python-based software tool developed to simplify and enhance the analysis of three-point bending test data. Three-point bending is a widely used experimental method for evaluating the mechanical properties of materials, such as stiffness, strength, and fracture toughness. In biomechanics, it plays a crucial role in assessing bone quality, understanding the impact of diseases or treatments, and studying material behavior under loading conditions. Despite its significance, many existing data analysis tools are limited in accuracy, flexibility, and ease of use. 3PB-Analyzer addresses these challenges by automating key steps, including locating and importing raw CSV files, generating load-displacement scatter plots, and performing linear regression analysis to calculate critical parameters such as stiffness, yield force, post-yield displacement, and work-to-fracture. Designed for researchers with or without programming expertise, the tool features an intuitive graphical user interface (GUI) that ensures accessibility and ease of operation. Although tailored for bone biomechanics, the 3PB‑Analyzer can be applied to three‑point bending experiments on any material and is fully compatible with four‑point bending tests as well. By combining precision, automation, and versatility, this tool enables researchers to streamline data processing, improve analytical accuracy, and enhance the reproducibility of their results, making it a valuable resource across multiple disciplines.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"30 ","pages":"Article 102177"},"PeriodicalIF":2.4000,"publicationDate":"2025-05-01","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/S235271102500144X","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
Abstract
This paper presents 3PB-Analyzer, an open-source Python-based software tool developed to simplify and enhance the analysis of three-point bending test data. Three-point bending is a widely used experimental method for evaluating the mechanical properties of materials, such as stiffness, strength, and fracture toughness. In biomechanics, it plays a crucial role in assessing bone quality, understanding the impact of diseases or treatments, and studying material behavior under loading conditions. Despite its significance, many existing data analysis tools are limited in accuracy, flexibility, and ease of use. 3PB-Analyzer addresses these challenges by automating key steps, including locating and importing raw CSV files, generating load-displacement scatter plots, and performing linear regression analysis to calculate critical parameters such as stiffness, yield force, post-yield displacement, and work-to-fracture. Designed for researchers with or without programming expertise, the tool features an intuitive graphical user interface (GUI) that ensures accessibility and ease of operation. Although tailored for bone biomechanics, the 3PB‑Analyzer can be applied to three‑point bending experiments on any material and is fully compatible with four‑point bending tests as well. By combining precision, automation, and versatility, this tool enables researchers to streamline data processing, improve analytical accuracy, and enhance the reproducibility of their results, making it a valuable resource across multiple disciplines.
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.