In spite of the numerous advances in the development of H_(2)and O_(2)evolutions upon water splitting,the separation of H_(2)from O_(2)still remains a severe challenge.Herein,the novel dual-functional nanocatalysts Pd...In spite of the numerous advances in the development of H_(2)and O_(2)evolutions upon water splitting,the separation of H_(2)from O_(2)still remains a severe challenge.Herein,the novel dual-functional nanocatalysts Pd/carbon nanosphere(CNS),obtained via immobilization of ultrafine Pd nanoparticles onto CNS,are developed and employed for both selective H_(2)generation from HCOOH dehydrogenation and O_(2)evolution from H_(2)O_(2)decomposition.In these reactions,the highest activities for Pd/CNS-800(i.e.,calcinated at 800℃)are 2478 h−1 and 993 min^(−1)for H_(2)and O_(2)evolution,respectively.The highly efficient and selective“on-off”switch for selective H_(2)generation from HCOOH is successfully realized by pH adjustment.This novel and highly efficient nanocatalyst Pd/CNS-800 not only provides new approaches for the promising application of HCOOH and H_(2)O_(2)as economic and safe H_(2)and O_(2)carriers,respectively,for fuel cells,but also promotes the development of“on-off”switch for on-demand H_(2)evolution.展开更多
A variant constrained genetic algorithm （VCGA） for effective tracking of conditional nonlinear optimal perturbations （CNOPs） is presented. Compared with traditional constraint handling methods, the treatment of th...A variant constrained genetic algorithm （VCGA） for effective tracking of conditional nonlinear optimal perturbations （CNOPs） is presented. Compared with traditional constraint handling methods, the treatment of the constraint condition in VCGA is relatively easy to implement. Moreover, it does not require adjustments to indefinite pararneters. Using a hybrid crossover operator and the newly developed multi-ply mutation operator, VCGA improves the performance of GAs. To demonstrate the capability of VCGA to catch CNOPS in non-smooth cases, a partial differential equation, which has ＂on off＂ switches in its forcing term, is employed as the nonlinear model. To search global CNOPs of the nonlinear model, numerical experiments using VCGA, the traditional gradient descent algorithm based on the adjoint method （ADJ）, and a GA using tournament selection operation and the niching technique （GA-DEB） were performed. The results with various initial reference states showed that, in smooth cases, all three optimization methods are able to catch global CNOPs. Nevertheless, in non-smooth situations, a large proportion of CNOPs captured by the ADJ are local. Compared with ADJ, the performance of GA-DEB shows considerable improvement, but it is far below VCGA. Further, the impacts of population sizes on both VCGA and GA-DEB were investigated. The results were used to estimate the computation time of ~CGA and GA-DEB in obtaining CNOPs. The computational costs for VCGA, GA-DEB and ADJ to catch CNOPs of the nonlinear model are also compared.展开更多
With more and more improvements of atmosphere or ocean models,a growing number of physical processes in the form of parameterization are incorporated into the models,which,on the one hand,makes the models capable of d...With more and more improvements of atmosphere or ocean models,a growing number of physical processes in the form of parameterization are incorporated into the models,which,on the one hand,makes the models capable of describing the at-mospheric or oceanic movement more precisely,and on the other hand,introduces non-smoothness in the form of "on-off" switches into the models."On-off" switches enhance the nonlinearity of the models and finally result in the loss of the effec-tiveness of variational data assimilation(VDA) based on the conventional adjoint method(ADJ).This study,in virtue of the optimization ability of a genetic algorithm(GA) for non-smooth problems,presents a new GA(referred to as GA NEW) to solve the problems of the VDA with discontinuous "on-off" processes.In the GA-NEW,adaptive selection and mutation oper-ators,blend crossover operator,and elitist strategy are combined in application.In order to verify the effectiveness and feasi-bility of the GA NEW in VDA,an idealized model of partial differential equation with discontinuous "on-off" switches in the forcing term is adopted as the governing equation.By comparison with the ADJ,it is shown that the GA NEW in VDA is more effective and can yield better assimilation retrievals.In addition,VDA experiments demonstrate that the performance of a GA is greatly related to the configuration of genetic operators(selection,crossover and mutation operators) and much better results may be attained with more proper genetic operations.Furthermore,the robustness of the GA NEW to observational noise,model errors and observation density is investigated,and the results show that the GA NEW has stronger robustness than the ADJ with respect to all the three observation noises,model errors,and sparse observation.展开更多
基金National Natural Science Foundation of China,Grant/Award Number:21805166111 Project of China,Grant/Award Number:D20015+1 种基金Ministryof Education,Hubei province,China,Grant/Award Number:T2020004Foundation of Science and Technology Bureau of Yichang City,Grant/Award Number:A21‐3‐012。
文摘In spite of the numerous advances in the development of H_(2)and O_(2)evolutions upon water splitting,the separation of H_(2)from O_(2)still remains a severe challenge.Herein,the novel dual-functional nanocatalysts Pd/carbon nanosphere(CNS),obtained via immobilization of ultrafine Pd nanoparticles onto CNS,are developed and employed for both selective H_(2)generation from HCOOH dehydrogenation and O_(2)evolution from H_(2)O_(2)decomposition.In these reactions,the highest activities for Pd/CNS-800(i.e.,calcinated at 800℃)are 2478 h−1 and 993 min^(−1)for H_(2)and O_(2)evolution,respectively.The highly efficient and selective“on-off”switch for selective H_(2)generation from HCOOH is successfully realized by pH adjustment.This novel and highly efficient nanocatalyst Pd/CNS-800 not only provides new approaches for the promising application of HCOOH and H_(2)O_(2)as economic and safe H_(2)and O_(2)carriers,respectively,for fuel cells,but also promotes the development of“on-off”switch for on-demand H_(2)evolution.
基金supported by the National Natural Science Foundation of China(Grant No.40975063)the National Natural Science Foundation of China(Grant No.41331174)
文摘A variant constrained genetic algorithm （VCGA） for effective tracking of conditional nonlinear optimal perturbations （CNOPs） is presented. Compared with traditional constraint handling methods, the treatment of the constraint condition in VCGA is relatively easy to implement. Moreover, it does not require adjustments to indefinite pararneters. Using a hybrid crossover operator and the newly developed multi-ply mutation operator, VCGA improves the performance of GAs. To demonstrate the capability of VCGA to catch CNOPS in non-smooth cases, a partial differential equation, which has ＂on off＂ switches in its forcing term, is employed as the nonlinear model. To search global CNOPs of the nonlinear model, numerical experiments using VCGA, the traditional gradient descent algorithm based on the adjoint method （ADJ）, and a GA using tournament selection operation and the niching technique （GA-DEB） were performed. The results with various initial reference states showed that, in smooth cases, all three optimization methods are able to catch global CNOPs. Nevertheless, in non-smooth situations, a large proportion of CNOPs captured by the ADJ are local. Compared with ADJ, the performance of GA-DEB shows considerable improvement, but it is far below VCGA. Further, the impacts of population sizes on both VCGA and GA-DEB were investigated. The results were used to estimate the computation time of ~CGA and GA-DEB in obtaining CNOPs. The computational costs for VCGA, GA-DEB and ADJ to catch CNOPs of the nonlinear model are also compared.
基金supported by National Natural Science Foundation of China (Grant Nos.40975063 and 40830955)
文摘With more and more improvements of atmosphere or ocean models,a growing number of physical processes in the form of parameterization are incorporated into the models,which,on the one hand,makes the models capable of describing the at-mospheric or oceanic movement more precisely,and on the other hand,introduces non-smoothness in the form of "on-off" switches into the models."On-off" switches enhance the nonlinearity of the models and finally result in the loss of the effec-tiveness of variational data assimilation(VDA) based on the conventional adjoint method(ADJ).This study,in virtue of the optimization ability of a genetic algorithm(GA) for non-smooth problems,presents a new GA(referred to as GA NEW) to solve the problems of the VDA with discontinuous "on-off" processes.In the GA-NEW,adaptive selection and mutation oper-ators,blend crossover operator,and elitist strategy are combined in application.In order to verify the effectiveness and feasi-bility of the GA NEW in VDA,an idealized model of partial differential equation with discontinuous "on-off" switches in the forcing term is adopted as the governing equation.By comparison with the ADJ,it is shown that the GA NEW in VDA is more effective and can yield better assimilation retrievals.In addition,VDA experiments demonstrate that the performance of a GA is greatly related to the configuration of genetic operators(selection,crossover and mutation operators) and much better results may be attained with more proper genetic operations.Furthermore,the robustness of the GA NEW to observational noise,model errors and observation density is investigated,and the results show that the GA NEW has stronger robustness than the ADJ with respect to all the three observation noises,model errors,and sparse observation.
