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http://dx.doi.org/10.12989/sem.2021.78.2.145

High-velocity powder compaction: An experimental investigation, modelling, and optimization  

Mostofi, Tohid Mirzababaie (Faculty of Mechanical Engineering, University of Eyvanekey)
Sayah-Badkhor, Mostafa (Faculty of Mechanical Engineering, University of Eyvanekey)
Rezasefat, Mohammad (Faculty of Mechanical Engineering, University of Eyvanekey)
Babaei, Hashem (Faculty of Mechanical Engineering, University of Guilan)
Ozbakkaloglu, Togay (Ingram School of Engineering, Texas State University)
Publication Information
Structural Engineering and Mechanics / v.78, no.2, 2021 , pp. 145-161 More about this Journal
Abstract
Dynamic compaction of Aluminum powder using gas detonation forming technique was investigated. The experiments were carried out on four different conditions of total pre-detonation pressure. The effects of the initial powder mass and grain particle size on the green density and strength of compacted specimens were investigated. The relationships between the mentioned powder design parameters and the final features of specimens were characterized using Response Surface Methodology (RSM). Artificial Neural Network (ANN) models using the Group Method of Data Handling (GMDH) algorithm were also developed to predict the green density and green strength of compacted specimens. Furthermore, the desirability function was employed for multi-objective optimization purposes. The obtained optimal solutions were verified with three new experiments and ANN models. The obtained experimental results corresponding to the best optimal setting with the desirability of 1 are 2714 kg·m-3 and 21.5 MPa for the green density and green strength, respectively, which are very close to the predicted values.
Keywords
aluminum powder; artificial neural network; high-velocity compaction; modelling; optimization; response surface methodology;
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