Determination of dynamic flow stress equation based on discrete experimental data: Part 1 Methodology and the dependence of dynamic flow stress on strain-rate

Xianglin Huang, Q. M. Li*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

In this study, a framework to determine the dynamic flow stress equation of materials based on the discrete data of varied (or instantaneous) strain-rate from split Hopkinson pressure bar (SHPB) experiments is proposed. The conventional constant strain-rate requirement in SHPB test is purposely relaxed to generate rich dynamic flow stress data (FSD) which are widely and diversely distributed in the plastic strain and strain-rate space. Data qualification criteria were proposed to screen the raw FSD, with which qualified FSD (a coarsely filled matrix) were obtained. The qualified FSD were used to train the Artificial Neural Network (ANN) to obtain finely filled FSD, which were decomposed using Singular Value Decomposition (SVD) method. The flow stress equation can be obtained from the SVD results with high accuracy. In addition, the flow stress equation based on the conventional method was established and evaluated. Five uncertainties inherent in the conventional method in the determination of the flow stress equation were identified. The comparison between the proposed and the conventional flow stress equations demonstrates the effectiveness and reliability of the flow stress equation obtained from the proposed method.

Original languageEnglish
Article number105403
JournalInternational Journal of Impact Engineering
Volume206
DOIs
Publication statusPublished - Dec 2025
Externally publishedYes

Keywords

  • Artificial neural network (ANN)
  • Dynamic flow stress
  • Singular value decomposition (SVD)
  • Split Hopkinson pressure bar (SHPB)

Fingerprint

Dive into the research topics of 'Determination of dynamic flow stress equation based on discrete experimental data: Part 1 Methodology and the dependence of dynamic flow stress on strain-rate'. Together they form a unique fingerprint.

Cite this