Parallelized Particle Swarm Optimization to Estimate the Heat Transfer Coefficients of a Series of Vegetable Oils in Comparison with Typical Fast Petroleum Quench Oil Quenchant

Rosa L. Simencio Otero, Sándor Szénási, Zoltán Fried, Imre Felde, Jônatas M. Viscaino, Lauralice C.F. Canale, George E. Totten
2019 Heat Treat 2019: Proceedings from the 30th Heat Treating Society Conference and Exposition   unpublished
An inverse solver for the estimation of the temporospacial heat transfer coefficients (HTCs), without using prior information of the thermal boundary conditions, was used for immersion quenching into a series of vegetable oils and two commercial petroleum oil quenchants. The Particle Swarm Optimization method was used on near-surface temperature-time cooling curve data obtained with the so-called Tensi multithermocouple 12.5 mm diameter x 45 mm Inconel 600 probe. The fitness function to be
more » ... ized by a particle swarm optimization (PSO) approach is defined by the deviation of the measured and calculated cooling curves. The PSO algorithm was parallelized and implemented on a Graphics Processing Unit architecture. This paper describes in detail the PSO methodology to compare and differentiate the potential quenching properties attainable with a series of vegetable oils including: cottonseed, peanut, canola, coconut, palm, sunflower, corn and a soybean oil vs a typical accelerated petroleum oil quenchant.
doi:10.31399/asm.cp.ht2019p0260 fatcat:4vfqfmvbb5cfrdutgkh4r7cvh4