Potential of explainable artificial intelligence in advancing renewable energy: challenges and prospects

VN Nguyen, W Tarełko, P Sharma, AS El-Shafay… - Energy & …, 2024 - ACS Publications
Modern machine learning (ML) techniques are making inroads in every aspect of renewable
energy for optimization and model prediction. The effective utilization of ML techniques for …

Model-prediction and optimization of the performance of a biodiesel–Producer gas powered dual-fuel engine

P Sharma, AK Sharma, D Balakrishnan, A Manivannan… - Fuel, 2023 - Elsevier
Diesel engines have been blamed for harming the environment owing to toxic emissions
that raise glasshouse gas (GHG) levels. This study intends to model-forecast and improve …

Surrogate modeling of parameterized multi-dimensional premixed combustion with physics-informed neural networks for rapid exploration of design space

K Liu, K Luo, Y Cheng, A Liu, H Li, J Fan… - Combustion and …, 2023 - Elsevier
Parametric optimization is a critical component in designing and prototyping combustion
systems. However, existing parametric optimization methods often suffer from either …

A numerical solution of fractional reaction–convection–diffusion for modeling PEM fuel cells based on a meshless approach

VR Hosseini, AA Mehrizi, H Karimi-Maleh… - … Analysis with Boundary …, 2023 - Elsevier
The purpose of this contribution is to present or implement generalized finite difference
method (GFDM) for the first time in order to solve the reaction convection Diffusion equation …

Fish processing discards: A plausible resource for valorization to renewable fuels production, optimization, byproducts and challenges

A Saravanan, D Yuvaraj, PS Kumar, S Karishma… - Fuel, 2023 - Elsevier
Considering the petroleum and fuel prices in India for the past ten years, it can be concluded
that there is a huge need for alternative sources of energy. The fuels that are currently used …

[HTML][HTML] Predicting physical properties of oxygenated gasoline and diesel range fuels using machine learning

HA AlNazr, N Ahmad, U Ahmed, B Mohan… - Alexandria Engineering …, 2023 - Elsevier
Understanding the physical properties of distillate petroleum fuels like gasoline and diesel is
very critical to ensure the normal operation of internal combustion (IC) engines with regards …

Application of an optimized PSO-BP neural network to the assessment and prediction of underground coal mine safety risk factors

DM Mulumba, J Liu, J Hao, Y Zheng, H Liu - Applied Sciences, 2023 - mdpi.com
Coal has played an important role in the economies of many countries worldwide, which has
resulted in increased surface and underground mining in countries with large coal reserves …

[HTML][HTML] Machine vision based damage detection for conveyor belt safety using Fusion knowledge distillation

X Guo, X Liu, P Gardoni, A Glowacz, G Królczyk… - Alexandria Engineering …, 2023 - Elsevier
A belt conveyor system is one of the essential equipment in coal mining. The damages to
conveyor belts are hazardous because they would affect the stable operation of a belt …

Anthropogenic emissions from coal-water slurry combustion: Influence of component composition and registration methods

VV Dorokhov, GS Nyashina, PA Strizhak - Environmental research, 2023 - Elsevier
The flue gas composition is often measured using a combination of techniques that differ in
terms of both physical operation principle and type of output. Gas analyzers, FTIR …

Flow prediction of heterogeneous nanoporous media based on physical information neural network

L Zhou, H Sun, D Fan, L Zhang, G Imani, S Fu… - Gas Science and …, 2024 - Elsevier
The simulation and prediction of fluid flow in porous media play a profoundly significant role
in today's scientific and engineering domains, particularly in gaining a deeper …