Optimization of Hydrothermal Performance in Industrial Heat Sinks with Innovative Perforated Pin Fin Designs: A Numerical Approach DOI Creative Commons
Fatema-Tuj Zohora, Mohammad Rejaul Haque,

Nabil Mohammad Chowdhury

et al.

Heliyon, Journal Year: 2024, Volume and Issue: 11(1), P. e41496 - e41496

Published: Dec. 26, 2024

Language: Английский

Enhancing Solar Energy Conversion Efficiency: Thermophysical Property Predicting of MXene/Graphene Hybrid Nanofluids via Bayesian-Optimized Artificial Neural Networks DOI Creative Commons
Dheyaa J. Jasim, Husam Rajab,

As’ad Alizadeh

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 24, P. 102858 - 102858

Published: Sept. 7, 2024

Language: Английский

Citations

13
Insights into water-lubricated transport of heavy and extra-heavy oils: Application of CFD, RSM, and metaheuristic optimized machine learning models DOI
Mishal Alsehli, Ali Basem, Dheyaa J. Jasim

et al.

Fuel, Journal Year: 2024, Volume and Issue: 374, P. 132431 - 132431

Published: July 8, 2024

Language: Английский

Citations

11
Optimizing Gaussian process regression (GPR) hyperparameters with three metaheuristic algorithms for viscosity prediction of suspensions containing microencapsulated PCMs DOI Creative Commons
Tao Hai, Ali Basem, As’ad Alizadeh

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Aug. 31, 2024

Abstract Suspensions containing microencapsulated phase change materials (MPCMs) play a crucial role in thermal energy storage (TES) systems and have applications building materials, textiles, cooling systems. This study focuses on accurately predicting the dynamic viscosity, critical thermophysical property, of suspensions MPCMs MXene particles using Gaussian process regression (GPR). Twelve hyperparameters (HPs) GPR are analyzed separately classified into three groups based their importance. Three metaheuristic algorithms, namely genetic algorithm (GA), particle swarm optimization (PSO), marine predators (MPA), employed to optimize HPs. Optimizing four most significant (covariance function, basis standardization, sigma) within first group any algorithms resulted excellent outcomes. All achieved reasonable R-value (0.9983), demonstrating effectiveness this context. The second explored impact including additional, moderate-significant HPs, such as fit method, predict method optimizer. While resulting models showed some improvement over group, PSO-based model exhibited noteworthy enhancement, achieving higher (0.99834). Finally, third was examine potential interactions between all twelve comprehensive approach, employing GA, yielded an optimized with highest level target compliance, reflected by impressive 0.999224. developed cost-effective efficient solution reduce laboratory costs for various systems, from TES management.

Language: Английский

Citations

10
A novel CFD framework for frost-free domestic refrigerators using fan performance curve and radiator model DOI Creative Commons

Amirhossein Ghorbani,

Seyed Mohammad Tabatabaei, Hossein Nasiri

et al.

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 103947 - 103947

Published: Jan. 1, 2025

Language: Английский

Citations

1
Numerical investigation on the thermal performance of perforated and non-perforated twisted fins at different twisting angles DOI Creative Commons

Ambagaha Hewage Dona Kalpani Rasangika,

Mohammad Shakir Nasif, Rafat Al‐Waked

et al.

Results in Engineering, Journal Year: 2024, Volume and Issue: 23, P. 102332 - 102332

Published: June 15, 2024

The present study numerically investigated the effect of variations in twisting angle and perimeter diamond-shaped perforation on heat transfer twisted fin sinks. showed a possible configuration sink design, aiming to improve hydrothermal performance factor (HTPF). ANSYS/FLUENT computational fluid dynamics software was used perform simulations, Reynolds-averaged Navier–Stokes-based k−ε turbulence model used. Results revealed that maximum 46 % enhancement Nusselt number 25 increase (HTPF) could be attained with 540° comparison conventional cylindrical fins. Furthermore, variation at resulted 28 value 36 HTPF fins no perforations. Therefore, this is recommended as optimal configuration.

Language: Английский

Citations

6
Comparative investigation on heat transfer augmentation in a liquid cooling plate for rectangular Li-ion battery thermal management DOI Creative Commons

Ammar Abdulhaleem Abdulqader,

Hayder Mohammad Jaffal

Results in Engineering, Journal Year: 2024, Volume and Issue: unknown, P. 102913 - 102913

Published: Sept. 1, 2024

Language: Английский

Citations

6
Integrating artificial neural networks, multi-objective metaheuristic optimization, and multi-criteria decision-making for improving MXene-based ionanofluids applicable in PV/T solar systems DOI Creative Commons
Tao Hai, Ali Basem,

As’ad Alizadeh

et al.

Scientific Reports, Journal Year: 2024, Volume and Issue: 14(1)

Published: Nov. 27, 2024

Abstract Optimization of thermophysical properties (TPPs) MXene-based nanofluids is essential to increase the performance hybrid solar photovoltaic and thermal (PV/T) systems. This study proposes a approach optimize TPPs Ionanofluids. The input variables are MXene mass fraction (MF) temperature. optimization objectives include three TPPs: specific heat capacity (SHC), dynamic viscosity (DV), conductivity (TC). In proposed approach, powerful group method data handling (GMDH)-type ANN technique used model in terms variables. obtained models integrated into multi-objective particle swarm (MOPSO) exchange (MOTEO) algorithms, forming three-objective problem. final step, TOPSIS technique, one well-known multi-criteria decision-making (MCDM) approaches, employed identify desirable Pareto points. Modeling results showed that developed for TC, DV, SHC demonstrate strong by R-values 0.9984, 0.9985, 0.9987, respectively. outputs MOPSO revealed points dispersed broad range MFs (0-0.4%). However, temperature these optimal was found be constrained within narrow near maximum value (75 °C). scenarios where TC precedes other objectives, recommended utilizing an MF over 0.2%. Alternatively, when DV holds greater importance, decision-makers can opt ranging from 0.15 0.17%. Also, becomes primary concern, advised base fluid without any additive.

Language: Английский

Citations

5
Accurate prediction of the rheological behavior of MWCNT-Al2O3/water-ethylene glycol nanofluid with metaheuristic-optimized machine learning models DOI
Yi Ru,

Ali B.M. Ali,

Karwan Hussein Qader

et al.

International Journal of Thermal Sciences, Journal Year: 2025, Volume and Issue: 211, P. 109691 - 109691

Published: Jan. 13, 2025

Language: Английский

Citations

0
Synergizing Neural Networks with Multi-Objective Thermal Exchange Optimization and PROMETHEE Decision-Making to Improve PCM-based Photovoltaic Thermal Systems DOI Creative Commons

Li Yongxin,

Ali Basem,

As’ad Alizadeh

et al.

Case Studies in Thermal Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 105851 - 105851

Published: Feb. 1, 2025

Language: Английский

Citations

0
Artificial intelligence aided microwave coagulation therapy: Analysis of heat transfer to tumor tissue via hybrid modeling DOI Creative Commons

Zheng Yang,

Kuangyu Dai, Wujun Zhang

et al.

Case Studies in Thermal Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 105927 - 105927

Published: Feb. 1, 2025

Language: Английский

Citations

0