Optimization of SiC-based shear thickening fluids behavior using a mathematical approach


Sofuğlu M. A., SAĞIR M.

Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, cilt.238, sa.7, ss.2841-2847, 2024 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 238 Sayı: 7
  • Basım Tarihi: 2024
  • Doi Numarası: 10.1177/09544062231203093
  • Dergi Adı: Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Aerospace Database, Applied Science & Technology Source, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Sayfa Sayıları: ss.2841-2847
  • Anahtar Kelimeler: experimental design, optimization, regression equation, Shear thickening fluids (STF), SiC, viscosity
  • Eskişehir Osmangazi Üniversitesi Adresli: Evet

Özet

The study focuses on an optimization study motivated by the increasing significance of shear-thickening fluids (STFs). We investigated the effects of parameters like additive surface area, additive ratio, and suspension temperature on outputs such as viscosity, thickening ratio, critical shear rate and thickening period of STFs using SiC as the additive. Enhancing STFs with SiC betters their stability and mechanical properties, ideal for industrial and defense applications. Our methodology has two steps. In the first step we developed a regression equation for each output by using some experimental data, then as the second step, each regression equation is used as an objective function and mathematical models are developed where the constraints represent the lower and upper bounds of the related inputs such as the surface area, amount of additive and, the surface area. Therefore, we want to obtain the best value of each input for each objective. The model’s results vary depending on the specific data and parameters used. This is a pioneering study employing both regression equations and mathematical models for this analysis.