Title

DETERMINATION METHODOLOGY OF STRESS-STRAIN CURVE FOR DIFFERENT HARDENING MODELS AND INSTANTANEOUS STRAIN HARDENING EXPONENT VIA PYTHON

DETERMINATION METHODOLOGY OF STRESS-STRAIN CURVE FOR DIFFERENT HARDENING MODELS AND INSTANTANEOUS STRAIN HARDENING EXPONENT VIA PYTHON

Authorship

Ferreira, Jetson Lemos; Pereira Neto Durval; Souza Marden Valente; Souza Roan Sampaio; Gonoring Tiago Britts

Ferreira, Jetson Lemos; Pereira Neto Durval; Souza Marden Valente; Souza Roan Sampaio; Gonoring Tiago Britts

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DOI

10.5151/2594-5297-40003

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Abstract

Widely studied properties, and properties with great potential for studies, bring to light the importance of fast data processing and visualization. Given this, a software application was developed using Python that has the capability to process large volumes of data. It also features a user-friendly graphical user interface (GUI), which can present data in the form of graphs and related information, making it easy to comprehend and analyze. For the present study, the properties addressed were strain-hardening models, given their great demand regarding numerical simulations, and the instantaneous strain-hardening exponent (n(εpl)), due to the potential for studies that have not yet been explored. With the joint analysis of multiple materials, visual analysis is facilitated, and with the aid of statistical metrics, it becomes possible to determine which strain-hardening model would be the appropriate choice for a given material, in addition to satisfactorily expressing the behavior of n(εpl) in relation to the true strain. A software application that enables the analysis of properties through input data alone, without the requirement of prior knowledge of any software or algorithm, can simplify processes and democratize data analysis for a broader audience. By streamlining data analysis, this software has the potential to enhance the understanding of how such properties influence the behavior of materials subjected to deformation.

Widely studied properties, and properties with great potential for studies, bring to light the importance of fast data processing and visualization. Given this, a software application was developed using Python that has the capability to process large volumes of data. It also features a user-friendly graphical user interface (GUI), which can present data in the form of graphs and related information, making it easy to comprehend and analyze. For the present study, the properties addressed were strain-hardening models, given their great demand regarding numerical simulations, and the instantaneous strain-hardening exponent (n(εpl)), due to the potential for studies that have not yet been explored. With the joint analysis of multiple materials, visual analysis is facilitated, and with the aid of statistical metrics, it becomes possible to determine which strain-hardening model would be the appropriate choice for a given material, in addition to satisfactorily expressing the behavior of n(εpl) in relation to the true strain. A software application that enables the analysis of properties through input data alone, without the requirement of prior knowledge of any software or algorithm, can simplify processes and democratize data analysis for a broader audience. By streamlining data analysis, this software has the potential to enhance the understanding of how such properties influence the behavior of materials subjected to deformation.

Keywords

Strain Hardening Models; Instantaneous Strain Hardening Exponent; Software Development;Data AnalysiS

Strain Hardening Models; Instantaneous Strain Hardening Exponent; Software Development;Data AnalysiS