Journal Published Online: 24 December 2025
Volume 14, Issue 1

Comparative Analysis on the Phenomenological and Artificial Neural Network Modeling for Flow Curves of a Beta Titanium Alloy

CODEN: MPCACD

Abstract

This study investigates the elevated temperature mechanical behavior of Ti-5V-5Mo-5Cr-4Al alloy through uniaxial tensile experiments conducted at temperatures ranging from room temperature to 550°C and strain rates of 0.001, 0.01, and 0.1 s−1. The results reveal that the dominant softening mechanism is dynamic recovery, whereas dynamic precipitation took place at the lowest rate of deformation and at temperatures ranging from 400°C to 500°C. To predict the mechanical behavior of this recent beta titanium alloy, artificial neural network (ANN) approach and modified Hensel-Spittel (m-HS) model were employed. In the prediction of flow curves using the m-HS model, a correlation coefficient (R) of 0.901 and an average absolute relative error (AARE) of 8.891 % were obtained. In contrast, the ANN approach yielded significantly better results, with an R value of 0.997 and an AARE of 2.3 %. The findings from this study provide routes for determining the hot workability of next-generation metastable beta titanium alloys.

Author Information

Uz, Murat Mert
Turkish Aerospace Industries Inc., Ankara, Türkiye
Sajjadifar, Seyedvahid
Institute of Materials Engineering, University of Kassel, Kassel, Germany Mechanical Engineering Department, Ozyegin University, Istanbul, Türkiye
Yapici, Guney Guven
Mechanical Engineering Department, Ozyegin University, Istanbul, Türkiye Mechanics and Manufacturing of Functional and Structural Materials Laboratory (MEMFIS), Ozyegin University, Istanbul, Türkiye Center for Additive Manufacturing Alloys (KİMTAL), Ozyegin University, Istanbul, Türkiye
Pages: 15
Price: $25.00
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Details
Stock #: MPC20250090
ISSN: 2379-1365
DOI: 10.1520/MPC20250090