[HTML][HTML] Enhancing property prediction and process optimization in building materials through machine learning: A review
K Stergiou, C Ntakolia, P Varytis, E Koumoulos… - Computational Materials …, 2023 - Elsevier
Abstract Analysis and design, as the most critical components in material science, require a
highly rigorous approach to assure long-term success. Due to a recent increase in the …
highly rigorous approach to assure long-term success. Due to a recent increase in the …
Thermo-mechanical optimization of thermoelectric generators using deep learning artificial intelligence algorithms fed with verified finite element simulation data
C Maduabuchi - Applied Energy, 2022 - Elsevier
The rising levels of global warming in the environment owing to emissions from fossil-fuel-
based engines has increased the search for efficient clean energy systems. Thermoelectric …
based engines has increased the search for efficient clean energy systems. Thermoelectric …
Deep neural networks for quick and precise geometry optimization of segmented thermoelectric generators
To solve the problems of the current optimization methods for solar segmented
thermoelectric generator performance based on numerical methods, this paper applied …
thermoelectric generator performance based on numerical methods, this paper applied …
Effect of nonuniform solar radiation on the performance of solar thermoelectric generators
Z Xuan, M Ge, C Zhao, Y Li, S Wang, Y Zhao - Energy, 2024 - Elsevier
Solar radiation must be concentrated before irradiating hot sides in solar thermoelectric
generators (STEGs) to increase the temperature difference between hot and cold sides and …
generators (STEGs) to increase the temperature difference between hot and cold sides and …
Backpropagated neural network modeling for the non-fourier thermal analysis of a moving plate
The present article mainly focuses on the transient thermal dispersal within a moving plate
using the non-Fourier heat flux model. Furthermore, the innovative, sophisticated artificial …
using the non-Fourier heat flux model. Furthermore, the innovative, sophisticated artificial …
[HTML][HTML] A prediction model for the performance of solar photovoltaic-thermoelectric systems utilizing various semiconductors via optimal surrogate machine learning …
H Alghamdi, C Maduabuchi, A Albaker, I Alatawi… - … Science and Technology …, 2023 - Elsevier
This research focuses on finding the best surrogate performance prediction model for a solar
photovoltaic-thermoelectric (PV-TE) module with different semiconductor materials. The …
photovoltaic-thermoelectric (PV-TE) module with different semiconductor materials. The …
[HTML][HTML] Machine learning-based optimization of segmented thermoelectric power generators using temperature-dependent performance properties
Segmented thermoelectric generators (STEGs) provide an excellent platform for thermal
energy harvesting devices because they improve power generation performance across a …
energy harvesting devices because they improve power generation performance across a …
Machine Learning for Next Generation Thermoelectrics
Thermoelectricity offers a ground-breaking solution for capturing waste heat and
transforming it into valuable electricity. Despite its promise, the quest for high-performance …
transforming it into valuable electricity. Despite its promise, the quest for high-performance …
Performance prediction and optimization of annular thermoelectric generators based on a comprehensive surrogate model
A traditional system-level thermoelectric model requires enormous computing power and
time for simulation analysis, especially when multiple optimization algorithms are combined …
time for simulation analysis, especially when multiple optimization algorithms are combined …
Machine learning model for transient exergy performance of a phase change material integrated-concentrated solar thermoelectric generator
H Alghamdi, C Maduabuchi, DS Mbachu… - Applied Thermal …, 2023 - Elsevier
Despite the merits of incorporating phase change materials in concentrating solar
thermoelectric generating systems, the following research gaps still need to be filled to make …
thermoelectric generating systems, the following research gaps still need to be filled to make …