Vollständiger Abstract
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Abstract In the present work, SUP9 spring steel specimens were reheated to 1000 °C in a controlled muffle furnace to obtain a homogeneous austenitic structure. The specimens were then cooled at different rates (0.1, 5, 100, 375, and 650 °C) to generate varied microstructures. Increasing the cooling rate refined the pearlitic microstructure, resulting in a finer and more uniform grain structure. These heat-treated specimens were then subjected to the wear test to study the influence of cooling rate ( dT/dt ), load ( F ), and sliding speed ( v ) on the response (wear rate). The wear tests were performed under varying conditions of applied load (10, 20, and 30 N) and sliding speed (0.5, 1, and 1.5 m/s) to assess wear behaviour under different operating conditions. A response surface methodology (RSM) model was developed to predict wear rate as a function of cooling rate, applied load, and sliding speed, achieving a good fit with a coefficient of determination ( R ²) of 94.65%. Among the variables, sliding speed had the strongest influence on wear rate, followed by load and cooling rate, while interaction effects were also significant, especially between cooling rate and sliding speed. Contour analysis further showed that the lowest wear rate occurs at high cooling rates combined with low load and low sliding speed, confirming strong interaction effects.
Bibliografischer Nachweis
Publikationsdaten
- Autor:innen
- Mamookho Elizabeth Makhatha, Sergei Sherbakov, Daria Podgayskaya, Pawan Kumar
- Quelle
- Interactions
- Publikation
- 2026-01-01
- Band / Ausgabe
- Nicht angegeben
- Seiten
- Nicht angegeben
- ISSN / ISBN
- 3005-0731
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Zitierfähiger Nachweis
Mamookho Elizabeth Makhatha, Sergei Sherbakov, Daria Podgayskaya, Pawan Kumar (2026). Predictive analysis of wear rate in SUP9 spring steel under controlled heat treatment cooling rates. Interactions. https://doi.org/10.1007/s10751-026-02732-2
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