The Effect of Hot Forming–Quenching and Heat Treatment Processes on the Mechanical Properties of AA6016 Aluminum Alloy Sheets

Author:

Lu Jiahong12,Liu Baitong12ORCID,Huang Shiyao12,Bao Zuguo12,Yang Yutong2,Li Xilin23,Zhan Zhenfei3,Liu Qing12

Affiliation:

1. College of Materials Science and Engineering, Nanjing Tech University, Nanjing 211816, China

2. Yangtze Delta Region Institute of Advanced Materials, Suzhou 215133, China

3. College of Mechanical and Vehicle Engineering, Chongqing Jiaotong University, Chongqing 400074, China

Abstract

This study explored the impact of Hot Forming–Quenching (HFQ) and heat treatment processes on the mechanical properties of AA6016 sheets. The experimental findings demonstrated that at high-temperature pre-straining (HT-PS) of 15%, the strength performance of the AA6016 sheet exhibited enhancement, with a progressive increase in both the heat treatment temperature and duration. Conversely, under HT-PS conditions of 3% and 7%, the heat treatment process exhibited a relatively modest impact on the mechanical properties of the AA6016 sheet. Differential scanning calorimetry (DSC) was employed to understand the influence of different process conditions on the precipitated phases. By comparing the precipitation peaks of the β″ phase at HT-PS of 3% and 15%, it was observed that the precipitation peak of the β″ phase decreased with an increase in HT-PS. This indicated that HT-PS promoted the precipitation of the β″ phase. In order to forecast the mechanical performance of the AA6016 sheets after applying various pre-straining and heat treatment parameters, two models were used: a backpropagation (BP) neural network and a genetic algorithm (GA)-BP neural network. These models were evaluated for their fitting and predictive capabilities. The research findings demonstrated that the GA-BP neural network model exhibited superior fitting and predictive accuracy compared to the BP neural network model.

Funder

Nanjing Tech University

Publisher

MDPI AG

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