Energy system optimization has become crucial for enhancing efficiency and environmental sustainability.This comprehensive review examines the synergistic application of Artificial Neural Networks(ANN)and Taguchi meth...Energy system optimization has become crucial for enhancing efficiency and environmental sustainability.This comprehensive review examines the synergistic application of Artificial Neural Networks(ANN)and Taguchi methods in optimizing diverse energy systems.While previous reviews have focused on these methods separately,this paper presents the first integrated analysis of both approaches across multiple energy applications.We systematically analyze their implementation in:Internal combustion engines,Thermal energy storage systems,Solar energy systems,Wind and tidal turbines,Heat exchangers,and hybrid energy systems.Our findings reveal that ANN models consistently achieve prediction accuracies exceeding 90%when compared to experimental data,while Taguchi-based methods combined with Grey Relational Analysis(GRA)or TOPSIS can improve system performance by up to 20%30%in multi-objective optimization scenarios.The review introduces novel frameworks for combining these methods and provides critical insights into their complementary strengths.Key statistical metrics,including determination coefficients and error analyses,validate the superior performance of integrated approaches.This work serves as a foundational reference for researchers and practitioners in energy system optimization,offering structured methodologies and future research directions.展开更多
Understanding the complex interaction between heat and mass transfer in non-Newtonian microflows is essential for the development and optimization of efficient microfluidic and thermal management systems.This study in...Understanding the complex interaction between heat and mass transfer in non-Newtonian microflows is essential for the development and optimization of efficient microfluidic and thermal management systems.This study investigates the magnetohydrodynamic(MHD)thermosolutal convection of a Casson fluid within an inclined,porous microchannel subjected to convective boundary conditions.The nonlinear,coupled equations governing momentum,energy,and species transport are solved numerically using the MATLAB bvp4c solver,ensuring high numerical accuracy and stability.To identify the dominant parameters influencing flow behavior and to optimize transport performance,a comprehensive hybrid optimization framework—combining a modified Taguchi design,Grey Relational Analysis(GRA),and Principal Component Analysis(PCA)—is proposed.This integrated strategy enables the simultaneous assessment of skin friction,Nusselt number,and Sherwood number,providing a rigorous multi-objective evaluation of system performance.Comparative validation with benchmark results from the literature confirms the accuracy and reliability of the present formulation and its numerical implementation.The results highlight the intricate coupling among flow slip,buoyancy effects,and convective transport mechanisms.Increased slip flow enhances axial velocity,while a higher solutal Biot number intensifies concentration gradients near the channel walls.Conversely,a lower thermal Biot number diminishes the temperature field,indicating weaker heat transfer across the boundaries.PCA results reveal that the first principal component(PC1)accounts for most of the system variance,demonstrating the dominant influence of coupled flow and transport parameters on overall system performance.展开更多
文摘Energy system optimization has become crucial for enhancing efficiency and environmental sustainability.This comprehensive review examines the synergistic application of Artificial Neural Networks(ANN)and Taguchi methods in optimizing diverse energy systems.While previous reviews have focused on these methods separately,this paper presents the first integrated analysis of both approaches across multiple energy applications.We systematically analyze their implementation in:Internal combustion engines,Thermal energy storage systems,Solar energy systems,Wind and tidal turbines,Heat exchangers,and hybrid energy systems.Our findings reveal that ANN models consistently achieve prediction accuracies exceeding 90%when compared to experimental data,while Taguchi-based methods combined with Grey Relational Analysis(GRA)or TOPSIS can improve system performance by up to 20%30%in multi-objective optimization scenarios.The review introduces novel frameworks for combining these methods and provides critical insights into their complementary strengths.Key statistical metrics,including determination coefficients and error analyses,validate the superior performance of integrated approaches.This work serves as a foundational reference for researchers and practitioners in energy system optimization,offering structured methodologies and future research directions.
文摘Understanding the complex interaction between heat and mass transfer in non-Newtonian microflows is essential for the development and optimization of efficient microfluidic and thermal management systems.This study investigates the magnetohydrodynamic(MHD)thermosolutal convection of a Casson fluid within an inclined,porous microchannel subjected to convective boundary conditions.The nonlinear,coupled equations governing momentum,energy,and species transport are solved numerically using the MATLAB bvp4c solver,ensuring high numerical accuracy and stability.To identify the dominant parameters influencing flow behavior and to optimize transport performance,a comprehensive hybrid optimization framework—combining a modified Taguchi design,Grey Relational Analysis(GRA),and Principal Component Analysis(PCA)—is proposed.This integrated strategy enables the simultaneous assessment of skin friction,Nusselt number,and Sherwood number,providing a rigorous multi-objective evaluation of system performance.Comparative validation with benchmark results from the literature confirms the accuracy and reliability of the present formulation and its numerical implementation.The results highlight the intricate coupling among flow slip,buoyancy effects,and convective transport mechanisms.Increased slip flow enhances axial velocity,while a higher solutal Biot number intensifies concentration gradients near the channel walls.Conversely,a lower thermal Biot number diminishes the temperature field,indicating weaker heat transfer across the boundaries.PCA results reveal that the first principal component(PC1)accounts for most of the system variance,demonstrating the dominant influence of coupled flow and transport parameters on overall system performance.
