The use of carbon-fiber heating cables(CFHC)to achieve effective melting of snow and ice deposited on roads is a method used worldwide.In this study,tensile and compressive tests have been conducted to analyze the mech...The use of carbon-fiber heating cables(CFHC)to achieve effective melting of snow and ice deposited on roads is a method used worldwide.In this study,tensile and compressive tests have been conducted to analyze the mechan-ical properties of the CFHC and assess whether the maximum tensile and compressive strengths can meet the pavement design specifications.In order to study the aging produced by multiple cycles of heating and cooling,in particular,the CFHC was repeatedly heated in a cold chamber with an ambient temperature ranging between-20℃ and+40℃.Moreover,to evaluate how the strength of the pavement is affected by its presence,the CFHC was embedded at different depths and concrete blocks with different curing ages were subjected to relevant com-pression and splitting tensile tests.Numerical simulations based on the ANSYS software have also been performed and compared with the outcomes of the static loading tests.The results show that the CFHC embedded in the concrete does not affect the compressive splitting tensile strengths of the pavement.Overall,the CFHC meets the conditions required for continued use in road ice melting applications.展开更多
In the manufacturing industry,reasonable scheduling can greatly improve production efficiency,while excessive resource consumption highlights the growing significance of energy conservation in production.This paper st...In the manufacturing industry,reasonable scheduling can greatly improve production efficiency,while excessive resource consumption highlights the growing significance of energy conservation in production.This paper studies the problem of energy-efficient distributed heterogeneous permutation flowshop problem with variable processing speed(DHPFSP-VPS),considering both the minimum makespan and total energy consumption(TEC)as objectives.A discrete multi-objective squirrel search algorithm(DMSSA)is proposed to solve the DHPFSPVPS.DMSSA makes four improvements based on the squirrel search algorithm.Firstly,in terms of the population initialization strategy,four hybrid initialization methods targeting different objectives are proposed to enhance the quality of initial solutions.Secondly,enhancements are made to the population hierarchy system and position updating methods of the squirrel search algorithm,making it more suitable for discrete scheduling problems.Additionally,regarding the search strategy,six local searches are designed based on problem characteristics to enhance search capability.Moreover,a dynamic predator strategy based on Q-learning is devised to effectively balance DMSSA’s capability for global exploration and local exploitation.Finally,two speed control energy-efficient strategies are designed to reduce TEC.Extensive comparative experiments are conducted in this paper to validate the effectiveness of the proposed strategies.The results of comparing DMSSA with other algorithms demonstrate its superior performance and its potential for efficient solving of the DHPFSP-VPS problem.展开更多
Selecting suitable materials to adsorb the C_(4)F_(7)N mixtures decomposition products could not only keep the stable operation of the environmentally friendly insulating gas switch cabinet,but also ensure the safety ...Selecting suitable materials to adsorb the C_(4)F_(7)N mixtures decomposition products could not only keep the stable operation of the environmentally friendly insulating gas switch cabinet,but also ensure the safety of operation and maintenance personnel.It is necessary to study the interaction of three types of molecular sieves with the C_(4)F_(7)N mixture and its decomposition products,which could provide a theoretical basis for the selection of adsorbents in the C_(4)F_(7)N gas switch cabinet.In this research,the molecular dynamics simulation was used to study the C_(4)F_(7)N-CO_(2)mixture and its ten kinds of decomposition products CO,CF_(4),C_(2)F_(6),C_(3)F_(6),C_(3)F_(8),CF_(3)H,CF_(3)CN,C_(2)F_(5)CN,C_(2)N_(2),and COF_(2)in three molecular sieves adsorption process(NaA,NaZSM-5,and NaX).The gas concentration distribution curve and interaction energy parameters were obtained by simulation.The interaction energies of C_(3)F_(8)in NaA,C_(4)F_(7)N in NaZSM-5,and C_(3)F_(6)in NaX molecular sieve are the largest,which are−368.35 kJ/mol,−174.93 kJ/mol,and−340.09 kJ/mol respectively.Then,the theoretical results were verified by the fluorocarbon gases adsorption experiment.The adsorption performance of three molecular sieves for all gases was obtained by combining the experimental results and dynamics parameters.The adsorption rate of the NaA molecular sieve for fluorocarbon gas is less than 35%,and its adsorption performance for all gases is weak.NaZSM-5 and NaX molecular sieves show excellent adsorption performance for C_(3)F_(6)and C_(3)F_(8),and the adsorption rates are over 70%.NaZSM-5 molecular sieve shows good adsorption capacity for CF_(3)CN,C_(2)F_(6),C_(2)N_(2),C_(3)F_(6),C_(3)F_(8),C_(4)F_(7)N,and C_(2)F_(5)CN.NaX molecular sieve shows good adsorption capacity for C_(3)F_(6),C_(3)F_(8),C_(4)F_(7)N,and C_(2)F_(5)CN.Both of them have the potential to be used as adsorbents in environmental protection insulated gas switch cabinet.展开更多
Feature Selection(FS)is an important problem that involves selecting the most informative subset of features from a dataset to improve classification accuracy.However,due to the high dimensionality and complexity of t...Feature Selection(FS)is an important problem that involves selecting the most informative subset of features from a dataset to improve classification accuracy.However,due to the high dimensionality and complexity of the dataset,most optimization algorithms for feature selection suffer from a balance issue during the search process.Therefore,the present paper proposes a hybrid Sine-Cosine Chimp Optimization Algorithm(SCChOA)to address the feature selection problem.In this approach,firstly,a multi-cycle iterative strategy is designed to better combine the Sine-Cosine Algorithm(SCA)and the Chimp Optimization Algorithm(ChOA),enabling a more effective search in the objective space.Secondly,an S-shaped transfer function is introduced to perform binary transformation on SCChOA.Finally,the binary SCChOA is combined with the K-Nearest Neighbor(KNN)classifier to form a novel binary hybrid wrapper feature selection method.To evaluate the performance of the proposed method,16 datasets from different dimensions of the UCI repository along with four evaluation metrics of average fitness value,average classification accuracy,average feature selection number,and average running time are considered.Meanwhile,seven state-of-the-art metaheuristic algorithms for solving the feature selection problem are chosen for comparison.Experimental results demonstrate that the proposed method outperforms other compared algorithms in solving the feature selection problem.It is capable of maximizing the reduction in the number of selected features while maintaining a high classification accuracy.Furthermore,the results of statistical tests also confirm the significant effectiveness of this method.展开更多
基金The authors have received financial support from the National Natural Science Foundation of China(No.52078194)the Key Research and Development Program of Hubei Province(No.2021BGD015)the Knowledge Innovation Project of Wuhan(No.2022010801010259).
文摘The use of carbon-fiber heating cables(CFHC)to achieve effective melting of snow and ice deposited on roads is a method used worldwide.In this study,tensile and compressive tests have been conducted to analyze the mechan-ical properties of the CFHC and assess whether the maximum tensile and compressive strengths can meet the pavement design specifications.In order to study the aging produced by multiple cycles of heating and cooling,in particular,the CFHC was repeatedly heated in a cold chamber with an ambient temperature ranging between-20℃ and+40℃.Moreover,to evaluate how the strength of the pavement is affected by its presence,the CFHC was embedded at different depths and concrete blocks with different curing ages were subjected to relevant com-pression and splitting tensile tests.Numerical simulations based on the ANSYS software have also been performed and compared with the outcomes of the static loading tests.The results show that the CFHC embedded in the concrete does not affect the compressive splitting tensile strengths of the pavement.Overall,the CFHC meets the conditions required for continued use in road ice melting applications.
基金supported by the Key Research and Development Project of Hubei Province(Nos.2020BAB114 and 2023BAB094).
文摘In the manufacturing industry,reasonable scheduling can greatly improve production efficiency,while excessive resource consumption highlights the growing significance of energy conservation in production.This paper studies the problem of energy-efficient distributed heterogeneous permutation flowshop problem with variable processing speed(DHPFSP-VPS),considering both the minimum makespan and total energy consumption(TEC)as objectives.A discrete multi-objective squirrel search algorithm(DMSSA)is proposed to solve the DHPFSPVPS.DMSSA makes four improvements based on the squirrel search algorithm.Firstly,in terms of the population initialization strategy,four hybrid initialization methods targeting different objectives are proposed to enhance the quality of initial solutions.Secondly,enhancements are made to the population hierarchy system and position updating methods of the squirrel search algorithm,making it more suitable for discrete scheduling problems.Additionally,regarding the search strategy,six local searches are designed based on problem characteristics to enhance search capability.Moreover,a dynamic predator strategy based on Q-learning is devised to effectively balance DMSSA’s capability for global exploration and local exploitation.Finally,two speed control energy-efficient strategies are designed to reduce TEC.Extensive comparative experiments are conducted in this paper to validate the effectiveness of the proposed strategies.The results of comparing DMSSA with other algorithms demonstrate its superior performance and its potential for efficient solving of the DHPFSP-VPS problem.
基金The National Natural Science Foundation of China,Grant/Award Number:52107145The Natural Science Foundation of Hubei Province,Grant/Award Number:2021CFA025。
文摘Selecting suitable materials to adsorb the C_(4)F_(7)N mixtures decomposition products could not only keep the stable operation of the environmentally friendly insulating gas switch cabinet,but also ensure the safety of operation and maintenance personnel.It is necessary to study the interaction of three types of molecular sieves with the C_(4)F_(7)N mixture and its decomposition products,which could provide a theoretical basis for the selection of adsorbents in the C_(4)F_(7)N gas switch cabinet.In this research,the molecular dynamics simulation was used to study the C_(4)F_(7)N-CO_(2)mixture and its ten kinds of decomposition products CO,CF_(4),C_(2)F_(6),C_(3)F_(6),C_(3)F_(8),CF_(3)H,CF_(3)CN,C_(2)F_(5)CN,C_(2)N_(2),and COF_(2)in three molecular sieves adsorption process(NaA,NaZSM-5,and NaX).The gas concentration distribution curve and interaction energy parameters were obtained by simulation.The interaction energies of C_(3)F_(8)in NaA,C_(4)F_(7)N in NaZSM-5,and C_(3)F_(6)in NaX molecular sieve are the largest,which are−368.35 kJ/mol,−174.93 kJ/mol,and−340.09 kJ/mol respectively.Then,the theoretical results were verified by the fluorocarbon gases adsorption experiment.The adsorption performance of three molecular sieves for all gases was obtained by combining the experimental results and dynamics parameters.The adsorption rate of the NaA molecular sieve for fluorocarbon gas is less than 35%,and its adsorption performance for all gases is weak.NaZSM-5 and NaX molecular sieves show excellent adsorption performance for C_(3)F_(6)and C_(3)F_(8),and the adsorption rates are over 70%.NaZSM-5 molecular sieve shows good adsorption capacity for CF_(3)CN,C_(2)F_(6),C_(2)N_(2),C_(3)F_(6),C_(3)F_(8),C_(4)F_(7)N,and C_(2)F_(5)CN.NaX molecular sieve shows good adsorption capacity for C_(3)F_(6),C_(3)F_(8),C_(4)F_(7)N,and C_(2)F_(5)CN.Both of them have the potential to be used as adsorbents in environmental protection insulated gas switch cabinet.
基金supported by the Key Research and Development Project of Hubei Province(No.2023BAB094)the Key Project of Science and Technology Research Program of Hubei Educational Committee(No.D20211402)the Teaching Research Project of Hubei University of Technology(No.2020099).
文摘Feature Selection(FS)is an important problem that involves selecting the most informative subset of features from a dataset to improve classification accuracy.However,due to the high dimensionality and complexity of the dataset,most optimization algorithms for feature selection suffer from a balance issue during the search process.Therefore,the present paper proposes a hybrid Sine-Cosine Chimp Optimization Algorithm(SCChOA)to address the feature selection problem.In this approach,firstly,a multi-cycle iterative strategy is designed to better combine the Sine-Cosine Algorithm(SCA)and the Chimp Optimization Algorithm(ChOA),enabling a more effective search in the objective space.Secondly,an S-shaped transfer function is introduced to perform binary transformation on SCChOA.Finally,the binary SCChOA is combined with the K-Nearest Neighbor(KNN)classifier to form a novel binary hybrid wrapper feature selection method.To evaluate the performance of the proposed method,16 datasets from different dimensions of the UCI repository along with four evaluation metrics of average fitness value,average classification accuracy,average feature selection number,and average running time are considered.Meanwhile,seven state-of-the-art metaheuristic algorithms for solving the feature selection problem are chosen for comparison.Experimental results demonstrate that the proposed method outperforms other compared algorithms in solving the feature selection problem.It is capable of maximizing the reduction in the number of selected features while maintaining a high classification accuracy.Furthermore,the results of statistical tests also confirm the significant effectiveness of this method.
