Sponsor
The authors acknowledge the financial support of the Hungarian State and the European Union under the EFOP-3.6.1-16-2016-00010 project and the Hungarian-Japanese bilateral Scientific and Technological (TÉT_16-1-2016-0190) project.
Published In
Materials Performance and Characterization
Document Type
Article
Publication Date
2-2019
Subjects
Particle swarm optimization, Heat transfer, Petroleum products, Palm Oil, Canola oil
Abstract
An inverse solver for the estimation of the temporal-spatial heat transfer coefficients (HTC), without using prior information of the thermal boundary conditions, was used for immersion quenching into palm oil, canola oil, and two commercial petroleum oil quenchants. The particle swarm optimization (PSO) method was used on near-surface temperature-time cooling curve data obtained with the so-called Tensi multithermocouple, and a 12.5 by 45 mm Inconel 600 probe. The fitness function to be minimized by a PSO approach is defined by the deviation of the measured and calculated cooling curves. The PSO algorithm was parallelized and implemented on a graphics accelerator architecture. This article describes, in detail, the PSO methodology used to compare and differentiate the potential quenching properties attainable with vegetable oils versus those attainable with accelerated and conventional petroleum oil quenchant.
DOI
10.1520/MPC20180049
Persistent Identifier
https://archives.pdx.edu/ds/psu/28531
Citation Details
Canale, L. C., Totten, G. E., Viscaino, J. M., Otero, R. L. S., Fried, Z., & Felde, I. (2019). Parallelized Particle Swarm Optimization to Estimate the Heat Transfer Coefficients of Palm Oil, Canola Oil, Conventional, and Accelerated Petroleum Oil Quenchants. Materials Performance and Characterization, 8(2).
Description
This is the Publisher PDF archived here with permission.
Copyright 2019 ASTM International
https://doi.org/10.1520/MPC20180049