Prediction of surface roughness in the end milling machining using Artificial Neural Network

AM Zain, H Haron, S Sharif - Expert Systems with Applications, 2010 - Elsevier
This paper presents the ANN model for predicting the surface roughness performance
measure in the machining process by considering the Artificial Neural Network (ANN) as the …

A machine learning based optimization method towards removing undesired deformation of energy-absorbing structures

Z Li, W Ma, S Yao, P Xu, L Hou, G Deng - Structural and Multidisciplinary …, 2021 - Springer
Optimization for the energy-absorbing structures can achieve their better crashworthiness
and lightweight performance. However, traditional optimization methods cannot handle …

Replacing the internal standard to estimate micropollutants using deep and machine learning

SS Baek, Y Choi, J Jeon, JC Pyo, J Park, KH Cho - Water Research, 2021 - Elsevier
Similar to the worldwide proliferation of urbanization, micropollutants have been involved in
aquatic and ecological environmental systems. These pollutants have the propensity to …

Estimation of the minimum machining performance in the abrasive waterjet machining using integrated ANN-SA

AM Zain, H Haron, S Sharif - Expert Systems with Applications, 2011 - Elsevier
In this study, Artificial Neural Network (ANN) and Simulated Annealing (SA) techniques were
integrated labeled as integrated ANN-SA to estimate optimal process parameters in …

Constitutive description of 7075 aluminum alloy during hot deformation by apparent and physically-based approaches

H Mirzadeh - Journal of Materials Engineering and Performance, 2015 - Springer
Hot flow stress of 7075 aluminum alloy during compressive hot deformation was correlated
to the Zener-Hollomon parameter through constitutive analyses based on the apparent …

Constitutive modelling for elevated temperature flow behaviour of AA7075

D Trimble, GE O'donnell - Materials & Design, 2015 - Elsevier
Isothermal hot compression tests were conducted on a Gleeble-3800 mechanical simulator
over a wide processing domain of temperatures (523–723 K) and strain-rates (0.001–100 s …

The deformation behavior and processing maps in the isothermal compression of 7A09 aluminum alloy

J Luo, MQ Li, DW Ma - Materials Science and Engineering: A, 2012 - Elsevier
Isothermal compression tests of 7A09 aluminum alloy were carried out on a Gleeble-1500
simulator at the deformation temperatures ranging from 633K to 733K, the strain rates …

Predicting flow stress behavior of an AA7075 alloy using machine learning methods

J Decke, A Engelhardt, L Rauch, S Degener… - Crystals, 2022 - mdpi.com
The present work focuses on the prediction of the hot deformation behavior of thermo-
mechanically processed precipitation hardenable aluminum alloy AA7075. The data …

Investigation on the grain structure evolution and abnormal stress increase of Al–Mg–Si alloy during hot deformation

Q Zhao, F Li, E Zhu, KR Gopi, S Farah, X An… - Metals and Materials …, 2024 - Springer
Abstract Al–Mg–Si alloys are widely used in many fields due to their excellent
comprehensive performance, but medium strength. In order to study the hot deformation …

Exit burr height mechanistic modeling and experimental validation for low-frequency vibration-assisted drilling of aluminum 7075-T6 alloy

S Li, D Zhang, C Liu, H Tang - Journal of Manufacturing Processes, 2020 - Elsevier
The burr influences the surface quality and the performance of the part. Nowadays, vibration-
assisted drilling (VAD) is used to decrease the exit burr size. However, further analysis of the …