Scholarly record
GPU-BASED HEAT TRANSFER MODEL
Abstract
This paper presents a novel heat transfer model for the estimation of heat transfer coefficients without any information about the thermal boundary conditions. The massively parallel implementation (using the latest CUDA 8.0 framework and NVIDIA graphics cards) of the model gives the opportunity to use multiple graphics accelerators to execute the heat transfer simulations. This leads to very impressive performance which makes it possible to run thousands of simulations within a reasonable time. There are several problems in the field of material science without any known analytical solution where the only possible way is to use some heuristic searches (Genetic Algorithms, Particle Swarm Optimisation, Fireworks, etc.). For some of these cases, the fitness/cost function calculation needs a heat transfer simulation process to generate a cooling curve, which is usually the most resource consuming part of the algorithm. Using our novel heat transfer model makes it possible to efficiently use these methods.
Publication Impact Profile
Publication details
References16
P. Oksman, S. Yu, H. Kytönen, and S. Louhenkilpi, “The Effective Thermal Conductivity Method in Continuous Casting of Steel,” Acta Polytech. Hungarica, vol. 11, no. 9, 2014.
I. Felde, “Liquid quenchant database: determination of heat transfer coefficient during quenching,” Int. J. Microstruct. Mater. Prop., vol. 11, no. 3/4, pp. 277–287, 2016.
I. Felde, “Hybrid Optimization Approach for Determination of Thermal Boundary Conditions,” in Critical Infrastructure Protection Research: Results of the First Critical Infrastructure Protection Research Project in Hungary, Cham: Springer International Publishing, 2016, pp. 69–77.
O. M. Alifanov, Inverse Heat Transfer Problems. Springer, 1994.
J. V. Beck, B. Blackwell, and C. R. J. St. Clair, Inverse Heat Conduction. New York: Wiley, 1985.
M. J. Colaço, H. R. B. Orlande, and G. S. Dulikravich, “Inverse and optimization problems in heat transfer,” J. Brazilian Soc. Mech. Sci. Eng., vol. 28, no. 1, pp. 1–24, 2006.
E. Ben Alaia, I. H. Dridi, H. Bouchriha, and P. Borne, “Genetic Algorithm for Multi-Criteria Optimization of Multi-Depots Pick-up and Delivery Problems with Time Windows and Multi-Vehicles,” Acta Polytech. Hungarica, vol. 12, no. 8, pp. 155–174, 2015.
S. Szénási and I. Felde, “Configuring Genetic Algorithm to Solve the Inverse Heat Conduction Problem,” in IEEE 15th International Symposium on Applied Machine Intelligence and Informatics, 2017, pp. 387–391.
I. Felde, S. Szénási, A. Kenéz, S. Wei, and R. Colas, “Determination of complex thermal boundary conditions using a Particle Swarm Optimization method,” in 5th International Conference on Distortion Engineering, 2015, pp. 227–236.
J. Kennedy and R. Eberhart, “Particle swarm optimization,” Neural Networks, 1995. Proceedings., IEEE Int. Conf., vol. 4, pp. 1942–1948, 1995.
S. Szénási, I. Felde, and I. Kovács, “Solving One-dimensional IHCP with Particle Swarm Optimization using Graphics Accelerators,” in 10th Jubilee IEEE International Symposium on Applied Computational Intelligence and Informatics, 2015, pp. 365–369.
I. Felde and S. Szénási, “Estimation of temporospatial boundary conditions using a particle swarm optimisation technique,” Int. J. Microstruct. Mater. Prop., vol. 11, no. 3/4, pp. 288–300, 2016.
S. Szénási and I. Felde, “Modified particle swarm optimization method to solve one-dimensional IHCP,” in 16th IEEE International Symposium on Computational Intelligence and Informatics, 2015, pp. 85–88.
G. D. Smith, Numerical Solution of Partial Differential Equations: Finite Difference Methods. Clarendon Press, 1985.
G. Bojtár, B. M. Csizmadia, and J. Égert, “Numerical Estimation Method of Orthotropic Material Properties of a Roving for Reinforcement of Composite Materials,” Acta Polytech. Hungarica, vol. 13, no. 6, pp. 163–182, 2016.
NVIDIA, “CUDA C Programming Guide.” 2014.
View or Download full articleAccess options
SWS access login
Login as SWS Scientific CommitteeLogin as SWS Scientific PartnerLogin as SWS AuthorAuthors and approved SWS contributors will read and export their own linked papers after identity matching by SWS profile, email and SGEM GlobalID.
For librarian assistance: [email protected]
Purchase Instant Access
- Article can be downloaded after successful payment.
- Article may be used according to SWS library access terms.
- Article cannot be redistributed.


