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 …
Artificial neural network enabled accurate geometrical design and optimisation of thermoelectric generator
The ever-increasing demand for renewable energy and zero carbon dioxide emission have
been the driving force for the development of thermoelectric generators with better power …
been the driving force for the development of thermoelectric generators with better power …
Predicting the optimal performance of a concentrated solar segmented variable leg thermoelectric generator using neural networks
The production of high-performing thermoelectrics is limited by the high computational
energy and time required by the current finite element method solvers that are used to …
energy and time required by the current finite element method solvers that are used to …
Combinatory finite element and artificial neural network model for predicting performance of thermoelectric generator
Thermoelectric generators (TEGs) are rapidly becoming the mainstream technology for
converting thermal energy into electrical energy. The rise in the continuous deployment of …
converting thermal energy into electrical energy. The rise in the continuous deployment of …
Fast and accurate performance prediction and optimization of thermoelectric generators with deep neural networks
P Wang, K Wang, L Xi, R Gao… - Advanced Materials …, 2021 - Wiley Online Library
Predicting the performance of thermoelectric generators (TEGs) is an essential part of
designing high‐performance TEGs. However, due to the complexity of the TEG system, the …
designing high‐performance TEGs. However, due to the complexity of the TEG system, 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 …
Comprehensive modeling for geometric optimization of a thermoelectric generator module
H He, Y Wu, W Liu, M Rong, Z Fang, X Tang - Energy conversion and …, 2019 - Elsevier
This paper develops a one-dimensional simulation model of a thermoelectric module aiming
at its characteristic exploration and output performance prediction. Almost all related effects …
at its characteristic exploration and output performance prediction. Almost all related effects …
Accurate prophecy of photovoltaic-segmented thermoelectric generator's performance using a neural network that feeds on finite element-generated data
To further enhance the photovoltaic–thermoelectric system efficiency, this paper proposes a
new hybrid system design comprising a segmented thermoelectric generator and aluminum …
new hybrid system design comprising a segmented thermoelectric generator and aluminum …
[HTML][HTML] Segmented thermoelectric generator modelling and optimization using artificial neural networks by iterative training
Renewable energy technologies are central to emissions reduction and essential to achieve
net-zero emission. Segmented thermoelectric generators (STEG) facilitate more efficient …
net-zero emission. Segmented thermoelectric generators (STEG) facilitate more efficient …
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 …