Data-driven probabilistic machine learning in sustainable smart energy/smart energy systems: Key developments, challenges, and future research opportunities in the …
The current trend indicates that energy demand and supply will eventually be controlled by
autonomous software that optimizes decision-making and energy distribution operations …
autonomous software that optimizes decision-making and energy distribution operations …
Machine learning in aerodynamic shape optimization
Abstract Machine learning (ML) has been increasingly used to aid aerodynamic shape
optimization (ASO), thanks to the availability of aerodynamic data and continued …
optimization (ASO), thanks to the availability of aerodynamic data and continued …
[HTML][HTML] Machine learning for combustion
Combustion science is an interdisciplinary study that involves nonlinear physical and
chemical phenomena in time and length scales, including complex chemical reactions and …
chemical phenomena in time and length scales, including complex chemical reactions and …
Stock exchange trading optimization algorithm: a human-inspired method for global optimization
H Emami - The Journal of Supercomputing, 2022 - Springer
In this paper, a human-inspired optimization algorithm called stock exchange trading
optimization (SETO) for solving numerical and engineering problems is introduced. The …
optimization (SETO) for solving numerical and engineering problems is introduced. The …
DoE-ML guided optimization of an active pre-chamber geometry using CFD
An optimized active pre-chamber geometry was obtained by combining computational fluid
dynamics (CFD) and machine learning (ML). A heavy-duty engine operating with methane …
dynamics (CFD) and machine learning (ML). A heavy-duty engine operating with methane …
Applications of machine learning to the analysis of engine in-cylinder flow and thermal process: A review and outlook
F Zhao, DLS Hung - Applied Thermal Engineering, 2023 - Elsevier
To adequately elucidate the complex in-cylinder flow structures and its underlying effects on
the thermal processes inside an internal combustion engine (ICE) has long been a daunting …
the thermal processes inside an internal combustion engine (ICE) has long been a daunting …
Application of an automated machine learning-genetic algorithm (AutoML-GA) coupled with computational fluid dynamics simulations for rapid engine design …
In recent years, the use of machine learning-based surrogate models for computational fluid
dynamics (CFD) simulations has emerged as a promising technique for reducing the …
dynamics (CFD) simulations has emerged as a promising technique for reducing the …
An automated machine learning-genetic algorithm framework with active learning for design optimization
The use of machine learning (ML)-based surrogate models is a promising technique to
significantly accelerate simulation-driven design optimization of internal combustion (IC) …
significantly accelerate simulation-driven design optimization of internal combustion (IC) …
Multi-objective optimization of micro co-generation spark-ignition engine fueled by biogas with various CH4/CO2 content based on GA-ANN and decision-making …
After the advances in biogas upgrading techniques, the optimization of power and heat
generation engines fueled by biogas with varying compositions has become a necessity …
generation engines fueled by biogas with varying compositions has become a necessity …
Physics-integrated segmented Gaussian process (SegGP) learning for cost-efficient training of diesel engine control system with low cetane numbers
View Video Presentation: https://doi. org/10.2514/6.2023-1283. vid Control model training is
an essential step towards the development of an engine controls system. A robust controls …
an essential step towards the development of an engine controls system. A robust controls …