3PB-analyzer: A python-based tool for automated three-point bending analysis
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, an...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-05-01
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| Series: | SoftwareX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S235271102500144X |
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| Summary: | 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. |
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| ISSN: | 2352-7110 |