The thermal conductivity of nanofluids is an important property that influences the heat transfer capabilities of nanofluids.Researchers rely on experimental investigations to explore nanofluid properties,as it is a n...The thermal conductivity of nanofluids is an important property that influences the heat transfer capabilities of nanofluids.Researchers rely on experimental investigations to explore nanofluid properties,as it is a necessary step before their practical application.As these investigations are time and resource-consuming undertakings,an effective prediction model can significantly improve the efficiency of research operations.In this work,an Artificial Neural Network(ANN)model is developed to predict the thermal conductivity of metal oxide water-based nanofluid.For this,a comprehensive set of 691 data points was collected from the literature.This dataset is split into training(70%),validation(15%),and testing(15%)and used to train the ANN model.The developed model is a backpropagation artificial neural network with a 4–12–1 architecture.The performance of the developed model shows high accuracy with R values above 0.90 and rapid convergence.It shows that the developed ANN model accurately predicts the thermal conductivity of nanofluids.展开更多
The analysis of spliced column has been carried out to detect optimum location of providing splices in the column.In the present work,static and dynamic(free vibration)analyses of spliced column have been done by rand...The analysis of spliced column has been carried out to detect optimum location of providing splices in the column.In the present work,static and dynamic(free vibration)analyses of spliced column have been done by randomising the location of splicing.A symmetrical four storey steel framed building has been modelled,analysed and designed for loads(dead,live and earthquake loads)recommended by Indian Codal provisions using Staad.Pro.The critical column at each floor level is identified based on axial force(AF),bending moment(BM)and shear force(SF).The total 16 models of spliced columns have been designed and then modelled in a 3D CAD Design tool(SOLIDWORKS)and then imported in the finite element tool(ANSYSWorkbench 14.0)for detailed analysis.The variation of stress,strain and deflection of the spliced column are shown in the form of contour.Further,the modal analysis is performed to determine the natural frequencies.The results of static and dynamic analyses are compared for each modelled spliced column to obtain the optimum location for providing splices in the column.The dynamic analysis of spliced column is of utmost importance in the region where dynamic loadings like earthquake,cyclones etc.are more frequent,and mere static analysis does not account for the safety of the structure.This study will help the engineers to select directly the optimum size and location of the splices in the column of a steel framed building.展开更多
The technological,economic,and environmental benefits of photovoltaic(PV)systems have led to their wide-spread adoption in recent years as a source of electricity generation.However,precisely identifying a PV system’...The technological,economic,and environmental benefits of photovoltaic(PV)systems have led to their wide-spread adoption in recent years as a source of electricity generation.However,precisely identifying a PV system’s maximum power point(MPP)under normal and shaded weather conditions is crucial to conserving the maximum generated power.One of the biggest concerns with a PV system is the existence of partial shading,which produces multiple peaks in the P–V characteristic curve.In these circumstances,classical maximum power point tracking(MPPT)approaches are prone to getting stuck on local peaks and failing to follow the global maximum power point(GMPP).To overcome such obstacles,a new Lyapunov-based Robust Model Reference Adaptive Controller(LRMRAC)is designed and implemented to reach GMPP rapidly and ripple-free.The proposed controller also achieves MPP accurately under slow,abrupt and rapid changes in radiation,temperature and load profile.Simulation and OPAL-RT real-time simulators in various scenarios are performed to verify the superiority of the proposed approach over the other state-of-the-art methods,i.e.,ANFIS,INC,VSPO,and P&O.MPP and GMPP are accomplished in less than 3.8 ms and 10 ms,respectively.Based on the results presented,the LRMRAC controller appears to be a promising technique for MPPT in a PV system.展开更多
基金supported by Basic Science Research Program through the National Research Foundation of Korea(NRF)funded by the Ministry of Education(2021R1A6A1A10044950).
文摘The thermal conductivity of nanofluids is an important property that influences the heat transfer capabilities of nanofluids.Researchers rely on experimental investigations to explore nanofluid properties,as it is a necessary step before their practical application.As these investigations are time and resource-consuming undertakings,an effective prediction model can significantly improve the efficiency of research operations.In this work,an Artificial Neural Network(ANN)model is developed to predict the thermal conductivity of metal oxide water-based nanofluid.For this,a comprehensive set of 691 data points was collected from the literature.This dataset is split into training(70%),validation(15%),and testing(15%)and used to train the ANN model.The developed model is a backpropagation artificial neural network with a 4–12–1 architecture.The performance of the developed model shows high accuracy with R values above 0.90 and rapid convergence.It shows that the developed ANN model accurately predicts the thermal conductivity of nanofluids.
文摘The analysis of spliced column has been carried out to detect optimum location of providing splices in the column.In the present work,static and dynamic(free vibration)analyses of spliced column have been done by randomising the location of splicing.A symmetrical four storey steel framed building has been modelled,analysed and designed for loads(dead,live and earthquake loads)recommended by Indian Codal provisions using Staad.Pro.The critical column at each floor level is identified based on axial force(AF),bending moment(BM)and shear force(SF).The total 16 models of spliced columns have been designed and then modelled in a 3D CAD Design tool(SOLIDWORKS)and then imported in the finite element tool(ANSYSWorkbench 14.0)for detailed analysis.The variation of stress,strain and deflection of the spliced column are shown in the form of contour.Further,the modal analysis is performed to determine the natural frequencies.The results of static and dynamic analyses are compared for each modelled spliced column to obtain the optimum location for providing splices in the column.The dynamic analysis of spliced column is of utmost importance in the region where dynamic loadings like earthquake,cyclones etc.are more frequent,and mere static analysis does not account for the safety of the structure.This study will help the engineers to select directly the optimum size and location of the splices in the column of a steel framed building.
文摘The technological,economic,and environmental benefits of photovoltaic(PV)systems have led to their wide-spread adoption in recent years as a source of electricity generation.However,precisely identifying a PV system’s maximum power point(MPP)under normal and shaded weather conditions is crucial to conserving the maximum generated power.One of the biggest concerns with a PV system is the existence of partial shading,which produces multiple peaks in the P–V characteristic curve.In these circumstances,classical maximum power point tracking(MPPT)approaches are prone to getting stuck on local peaks and failing to follow the global maximum power point(GMPP).To overcome such obstacles,a new Lyapunov-based Robust Model Reference Adaptive Controller(LRMRAC)is designed and implemented to reach GMPP rapidly and ripple-free.The proposed controller also achieves MPP accurately under slow,abrupt and rapid changes in radiation,temperature and load profile.Simulation and OPAL-RT real-time simulators in various scenarios are performed to verify the superiority of the proposed approach over the other state-of-the-art methods,i.e.,ANFIS,INC,VSPO,and P&O.MPP and GMPP are accomplished in less than 3.8 ms and 10 ms,respectively.Based on the results presented,the LRMRAC controller appears to be a promising technique for MPPT in a PV system.
