Machine learning-based optimization and 4E analysis of renewable-based polygeneration system by integration of GT-SRC-ORC-SOFC-PEME-MED-RO using multi-objective grey wolf optimization algorithm and neural networks

Renewable and Sustainable Energy Reviews, Год журнала: 2024, Номер 200, С. 114616 - 114616

Опубликована: Июнь 3, 2024

Язык: Английский

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A comprehensive thermodynamic, economic, and environmental analysis of a novel parabolic trough solar-driven multigeneration system for generating power, hydrogen, and freshwater

Process Safety and Environmental Protection, Год журнала: 2024, Номер 184, С. 227 - 247

Опубликована: Янв. 30, 2024

Язык: Английский

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Proposal of a geothermal-driven multigeneration system for power, cooling, and fresh water: Thermoeconomic assessment and optimization

Energy, Год журнала: 2024, Номер 301, С. 131667 - 131667

Опубликована: Май 18, 2024

Язык: Английский

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Design and thermo-enviro-economic analyses of a novel thermal design process for a CCHP-desalination application using LNG regasification integrated with a gas turbine power plant

Energy, Год журнала: 2024, Номер 295, С. 131003 - 131003

Опубликована: Март 24, 2024

Язык: Английский

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Thermoeconomic analysis of a novel cogeneration system for cascade recovery of waste heat from exhaust flue gases

Applied Thermal Engineering, Год журнала: 2024, Номер 247, С. 123034 - 123034

Опубликована: Март 23, 2024

Язык: Английский

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Performance optimization for an optimal operating condition for a shell and heat exchanger using a multi-objective genetic algorithm approach

PLoS ONE, Год журнала: 2024, Номер 19(6), С. e0304097 - e0304097

Опубликована: Июнь 10, 2024

In this study, shell and heat exchangers are optimized using an integrated optimization framework. research, A structured Design of Experiments (DOE) comprising 16 trials was first conducted to systematically determine the essential parameters, including mass flow rates (mh, mc), temperatures (T1, t1, T2, t2), transfer coefficients (€, TR, U). By identifying four principal components, PCA able 87.7% variance, thereby reducing dimensionality problem. Performance-related aspects system focus approach. Key outcomes U) were predicted by 99% R-squared RSM models. Multiple factors, such as rate inlet temperature, considered during design process. The maximizing efficiency, thermal resistance, utility achieved considering these factors. genetic algorithms, Pareto front solutions that meet requirements decision-makers can be found. combination tube produced better results than expected. Engineering designers gain practical insight into rate, key responses if they quantify improvements in Despite importance it has several potential limitations, specific experimental conditions need validate other situations well. Future research could investigate factors influence performance. holistic framework improve engineering future. As a result foundation for innovative advancements field been laid with tangible improvements. study exceeded expectations optimizing exchanger systems approach, contributing significantly advancement field.

Язык: Английский

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The modeling of rotational effect on the purge flow cooling coverage of a blade platform

International Journal of Thermal Sciences, Год журнала: 2025, Номер 212, С. 109723 - 109723

Опубликована: Фев. 5, 2025

Язык: Английский

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Efficient Biomass Utilization for Power, Cooling, and Hydrogen: A Multi-Generation Approach with Environmental and Economic Assessment

Renewable Energy, Год журнала: 2025, Номер unknown, С. 122645 - 122645

Опубликована: Фев. 1, 2025

Язык: Английский

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Comprehensive evaluation of a gas turbine-based multi-generation system for power, heating, cooling, freshwater, hydrogen and ammonia: 4E assessment and multi-objective optimization with RSM desirability approach

Renewable Energy, Год журнала: 2025, Номер unknown, С. 122900 - 122900

Опубликована: Март 1, 2025

Язык: Английский

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Optimization of Ex/Energy Efficiencies in an Integrated Compressed Air Energy Storage System (CAES) using Machine Learning Algorithms: A Multi-Objective Approach based on Analysis of Variance

Energy, Год журнала: 2025, Номер unknown, С. 135675 - 135675

Опубликована: Март 1, 2025

Язык: Английский

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