Publications

Journal publications

12. Automatic detection of the onset of film boiling using convolutional neural networks and Bayesian statistics
G. M. Hobold, A. K. da Silva, International Journal of Heat and Mass Transfer (Accepted, in press)
11. Visualization-based nucleate boiling heat flux quatification using machine learning
G. M. Hobold, A. K. da Silva, International Journal of Heat and Mass Transfer (Accepted, in press)
10. On the sensitivity to convective heat transfer correlation uncertainties in supercritical fluids
V. K. Scariot, G. M. Hobold, A. K. da Silva, Applied Thermal Engineering, 2018. [publisher link]
9. Machine learning classification of boiling regimes with low speed, direct and indirect visualization
G. M. Hobold, A. K. da Silva, International Journal of Heat and Mass Transfer, vol. 125, p. 1296-1309, 2018. [publisher link]
8. Dimensionless, fluid-independent equations for heat and mass transfer in supercritical fluids
G. M. Hobold, A. K. da Silva, The Journal of Supercritical Fluids, vol. 133.1, p. 17-29, 2018. [publisher link]
7. Critical phenomena and their effect on thermal energy storage in supercritical fluids
G. M. Hobold, A. K. da Silva, Applied Energy, vol. 205, p. 1447-1458, 2017. [publisher link]
6. A generalized multifluid optimal pressure for heat exchangers operating with supercritical fluid
G. M. Hobold, A. K. da Silva, Numerical Heat Transfer, Part A: Applications, vol. 72, p. 345-354, 2017. [publisher link]
5. Two-dimensional porosity optimization of saturated porous media for maximal thermal performance under forced convection
G. M. Hobold, A. K. da Silva, International Journal of Heat and Mass Transfer, vol. 108, p. 1689-1701, 2017. [publisher link]
4. Performance optimization of a channel flow problem using shape functions
G. M. Hobold, A. K. da Silva, International Journal of Heat and Mass Transfer, vol. 101, p. 303-312, 2016. [publisher link]
3. Thermal behavior of supercritical fluids near the critical point
G. M. Hobold, A. K. da Silva, Numerical Heat Transfer, Part A: Applications, vol. 69, p. 545-557, 2016. [publisher link]
2. A methodology for predicting solar power incidence on airfoils and their optimization for solar-powered airplanes
G. M. Hobold, R. K. Agarwal, Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, vol. 229.7, p. 1267-1279, 2015. [publisher link]
1. Prediction and optimization of fuel cell performance using a multi-objective genetic algorithm
G. M. Hobold, R. K. Agarwal, International Journal of Energy and Environment, vol. 4.5, p. 721-742, 2013. [publisher link]

 

Conferences

3. Analysis of neural network architecture for pool boiling regime identification
The 10th International Conference on Boiling & Condensation Heat Transfer (ICBCHT 2018), Nagasaki, Japan, 2018.
2. Application of the Force Cone Method in topology optimization: a case study on truss design
A. P. da Veiga, G. M. Hobold, R. C. Lambert, 23rd ABCM International Congress of Mechanical Engineering (COBEM 2015), Rio de Janeiro, Brazil, 2015.
1. A Methodology for Predicting Solar Power Incidence on Airfoils and their Optimization for Solar Powered Airplanes
G. M. Hobold, R. K. Agarwal, SAE 2013 AeroTech Congress & Exhibition, Montreal, Canada, 2013.