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 minimized 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.

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