Work

Bayesian Parameter Estimation and Model Class Selection for Identification of Spatially Dependent Convective Heat Transfer Coefficients in a Microtube Heat Sink

Year: 2026

Type: article

Abstract: The analysis of heat transfer at the microscale has been widely employed in recent decades due to technological advances in the industry of miniaturized fluid transport systems. This work presents a model class selection approach for the identification of spatially dependent convective heat transfer coefficients in a microtube heat sink. The physical system of interest is the cooling of a heat source simulating a processor through a thermal heat sink with a single microtube. The methodology consists in the application of the Transitional Markov Chain Monte Carlo Method for parameter estimation and model evidence calculation, used in the selection of adopted hypotheses. The methodology is illustrated with numerical examples representing different scenarios, demonstrating the feasibility and robustness of the approach.

Source: International Journal of Applied and Computational Mathematics

DOI: 10.1007/s40819-026-02131-9

Authors: Lucas S. Asth, Diego C. Knupp, Leonardo T. Stutz, Luiz A. S. Abreu, Bruno C. Lugão

Institutions: Universidade do Estado do Rio de Janeiro, Instituto Politécnico do Rio de Janeiro

Language: English

Topic: Heat Transfer and Optimization

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: hybrid

Estimated APC paid: $3,190

Funders: Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, Conselho Nacional de Desenvolvimento Científico e Tecnológico, Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro