PARALLELIZED PARTICLE SWARM OPTIMIZATION TO ESTIMATE THE HEAT TRANSFER COEFFICIENTS OF A SERIES OF VEGETABLE OILS IN COMPARISON WITH TYPICAL PETROLEUM OIL QUENCHANTS

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 multi-thermocouple 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 vegetable oils vs an accelerated and conventional petroleum oil quenchant.