Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus t...Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus the incentives for collaboration cannot be guaranteed.In this paper,we propose a consortium blockchain enabled collaborative edge computing framework,where users can offload computing tasks to ECSs from different operators.To minimize the total delay of users,we formulate a joint task offloading and resource optimization problem,under the constraint of the computing capability of each ECS.We apply the Tammer decomposition method and heuristic optimization algorithms to obtain the optimal solution.Finally,we propose a reputation based node selection approach to facilitate the consensus process,and also consider a completion time based primary node selection to avoid monopolization of certain edge node and enhance the security of the blockchain.Simulation results validate the effectiveness of the proposed algorithm,and the total delay can be reduced by up to 40%compared with the non-cooperative case.展开更多
Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus t...Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus the incentives for collaboration cannot be guaranteed.In this paper,we propose a consortium blockchain enabled collaborative edge computing framework,where users can offload computing tasks to ECSs from different operators.To minimize the total delay of users,we formulate a joint task offloading and resource optimization problem,under the constraint of the computing capability of each ECS.We apply the Tammer decomposition method and heuristic optimization algorithms to obtain the optimal solution.Finally,we propose a reputation based node selection approach to facilitate the consensus process,and also consider a completion time based primary node selection to avoid monopolization of certain edge node and enhance the security of the blockchain.Simulation results validate the effectiveness of the proposed algorithm,and the total delay can be reduced by up to 40%compared with the non-cooperative case.展开更多
The goal of this effort was to provide a static and dynamic collaborative optimization （CO） model for the design of ship hull structure. The CO model integrated with static, mode and dynamic analyses. In the system-...The goal of this effort was to provide a static and dynamic collaborative optimization （CO） model for the design of ship hull structure. The CO model integrated with static, mode and dynamic analyses. In the system-level optimization model, a new objective function was advised, integrating all the subsystem-levels＇ objective functions, so as to eliminate the effects of dimensions and magnitude order. The proposed CO architecture enabled multi-objectives of the system and subsystem-level to be considered at both levels during optimization. A bi-level optimization strategy was advised, using the multi-island genetic algorithm. The proposed model was demonstrated with a deck optimization problem of container ship stern. The analysis progress and results of example show that the CO strategy is not only feasible and reliable, but also well suited for use in actual optimization problems of ship design.展开更多
Improving the efficiency of ship optimization is crucial for modem ship design. Compared with traditional methods, multidisciplinary design optimization （MDO） is a more promising approach. For this reason, Collabora...Improving the efficiency of ship optimization is crucial for modem ship design. Compared with traditional methods, multidisciplinary design optimization （MDO） is a more promising approach. For this reason, Collaborative Optimization （CO） is discussed and analyzed in this paper. As one of the most frequently applied MDO methods, CO promotes autonomy of disciplines while providing a coordinating mechanism guaranteeing progress toward an optimum and maintaining interdisciplinary compatibility. However, there are some difficulties in applying the conventional CO method, such as difficulties in choosing an initial point and tremendous computational requirements. For the purpose of overcoming these problems, optimal Latin hypercube design and Radial basis function network were applied to CO. Optimal Latin hypercube design is a modified Latin Hypercube design. Radial basis function network approximates the optimization model, and is updated during the optimization process to improve accuracy. It is shown by examples that the computing efficiency and robustness of this CO method are higher than with the conventional CO method.展开更多
Aqueous zinc-halogen batteries are promising candidates for large-scale energy storage due to their abundant resources,intrinsic safety,and high theoretical capacity.Nevertheless,the uncontrollable zinc dendrite growt...Aqueous zinc-halogen batteries are promising candidates for large-scale energy storage due to their abundant resources,intrinsic safety,and high theoretical capacity.Nevertheless,the uncontrollable zinc dendrite growth and spontaneous shuttle effect of active species have prohibited their practical implementation.Herein,a double-layered protective film based on zinc-ethylenediamine tetramethylene phosphonic acid(ZEA)artificial film and ZnF2-rich solid electrolyte interphase(SEI)layer has been successfully fabricated on the zinc metal anode via electrode/electrolyte synergistic optimization.The ZEA-based artificial film shows strong affinity for the ZnF2-rich SEI layer,therefore effectively suppressing the SEI breakage and facilitating the construction of double-layered protective film on the zinc metal anode.Such double-layered architecture not only modulates Zn2+flux and suppresses the zinc dendrite growth,but also blocks the direct contact between the metal anode and electrolyte,thus mitigating the corrosion from the active species.When employing optimized metal anodes and electrolytes,the as-developed zinc-(dual)halogen batteries present high areal capacity and satisfactory cycling stability.This work provides a new avenue for developing aqueous zinc-(dual)halogen batteries.展开更多
This review article provides a comprehensive analysis of nesting optimization algorithms in the shipbuilding industry,emphasizing their role in improving material utilization,minimizing waste,and enhancing production ...This review article provides a comprehensive analysis of nesting optimization algorithms in the shipbuilding industry,emphasizing their role in improving material utilization,minimizing waste,and enhancing production efficiency.The shipbuilding process involves the complex cutting and arrangement of steel plates,making the optimization of these operations vital for cost-effectiveness and sustainability.Nesting algorithms are broadly classified into four categories:exact,heuristic,metaheuristic,and hybrid.Exact algorithms ensure optimal solutions but are computationally demanding.In contrast,heuristic algorithms deliver quicker results using practical rules,although they may not consistently achieve optimal outcomes.Metaheuristic algorithms combine multiple heuristics to effectively explore solution spaces,striking a balance between solution quality and computational efficiency.Hybrid algorithms integrate the strengths of different approaches to further enhance performance.This review systematically assesses these algorithms using criteria such as material dimensions,part geometry,component layout,and computational efficiency.The findings highlight the significant potential of advanced nesting techniques to improve material utilization,reduce production costs,and promote sustainable practices in shipbuilding.By adopting suitable nesting solutions,shipbuilders can achieve greater efficiency,optimized resource management,and superior overall performance.Future research directions should focus on integrating machine learning and real-time adaptability to further enhance nesting algorithms,paving the way for smarter,more sustainable manufacturing practices in the shipbuilding industry.展开更多
Phase-matching quantum-key distribution(PM-QKD)has achieved significant results in various practical applications.However,real-time communication requires dynamic adjustment and optimization of key parameters during c...Phase-matching quantum-key distribution(PM-QKD)has achieved significant results in various practical applications.However,real-time communication requires dynamic adjustment and optimization of key parameters during communication.In this letter,we predict the PM-QKD parameters using nature-inspired algorithms(NIAs).The results are obtained from an exhaustive traversal algorithm(ETA),which serves as a benchmark.We mainly study the parameter optimization effects of the two NIAs:ant colony optimization(ACO)and the genetic algorithm(GA).The configuration of the inherent parameters of these algorithms in the decoy-state PM-QKD is also discussed.The simulation results indicate that the parameters obtained by the ACO exhibit superior convergence and stability,whereas the GA results are relatively scattered.Nevertheless,more than 97%of the key rates predicted by both algorithms are highly consistent with the optimal key rate.Moreover,the relative error of the key rates remained below 10%.Furthermore,NIAs maintain power consumption below 8 W and require three orders of magnitude less computing time than ETA.展开更多
Optimizing frequency configurations for qubits and gates in superconducting quantum chips presents a complex NP-complete challenge,critical for mitigating decoherence and crosstalk.This paper introduces a neural netwo...Optimizing frequency configurations for qubits and gates in superconducting quantum chips presents a complex NP-complete challenge,critical for mitigating decoherence and crosstalk.This paper introduces a neural network-based approach,leveraging the network as a surrogate model to predict frequency errors.The method employs a closed-loop Bayesian optimization framework to iteratively refine configurations,guided by the network’s knowledge of nonlinear error mechanisms.By focusing on localized chip windows,the optimization identifies optimal frequency settings that minimize errors.The approach is validated through randomized and cross-entropy benchmarking,showing improved energy calculations when optimizing frequency configurations for a crosstalkaware hardware-efficient ansatz in variational quantum eigensolvers on superconducting quantum chips.展开更多
Na_(3)V_(2)(PO_(4))_(3)(NVP)has garnered great attentions as a prospective cathode material for sodium-ion batteries(SIBs)by virtue of its decent theoretical capacity,superior ion conductivity and high structural stab...Na_(3)V_(2)(PO_(4))_(3)(NVP)has garnered great attentions as a prospective cathode material for sodium-ion batteries(SIBs)by virtue of its decent theoretical capacity,superior ion conductivity and high structural stability.However,the inherently poor electronic conductivity and sluggish sodium-ion diffusion kinetics of NVP material give rise to inferior rate performance and unsatisfactory energy density,which strictly confine its further application in SIBs.Thus,it is of significance to boost the sodium storage performance of NVP cathode material.Up to now,many methods have been developed to optimize the electrochemical performance of NVP cathode material.In this review,the latest advances in optimization strategies for improving the electrochemical performance of NVP cathode material are well summarized and discussed,including carbon coating or modification,foreign-ion doping or substitution and nanostructure and morphology design.The foreign-ion doping or substitution is highlighted,involving Na,V,and PO_(4)^(3−)sites,which include single-site doping,multiple-site doping,single-ion doping,multiple-ion doping and so on.Furthermore,the challenges and prospects of high-performance NVP cathode material are also put forward.It is believed that this review can provide a useful reference for designing and developing high-performance NVP cathode material toward the large-scale application in SIBs.展开更多
A broadband polarization-independent terahertz multifunctional coding metasurface based on topological optimization using liquid crystal(LC)is proposed.The metasurface can achieve reconfigurability for beam steering a...A broadband polarization-independent terahertz multifunctional coding metasurface based on topological optimization using liquid crystal(LC)is proposed.The metasurface can achieve reconfigurability for beam steering and vortex beam generation within a frequency range of 0.68 THz–0.72 THz.Firstly,the metasurface unit is topologically optimized using the non-dominant sequencing genetic algorithms(NSGA-II)multi-objective optimization algorithm.By applying the LC’s electrically tunable refractive index properties,the metasurface unit enables polarization-independent 2-bit coding within a frequency range of 0.68 THz–0.72 THz.Then,based on the designed metasurface unit,the array arrangement of the metasurface is reverse-designed to achieve beam steering and vortex beam generation.The results show that,for beam steering,not only can polarization-independent steering of both single-and multi-beam be achieved within the 35°elevation angle range,but also independent control of the target angle of each beam in the multi-beam steering.For vortex beam generation,the metasurfaces can achieve the generation of single-and multi-vortex beams with topological charges l=±1,±2 within the 35elevation angle range,and the generation angles of each vortex beam in the multi-vortex beam can be independently controlled.This provides flexibility and diversity in the generation of vortex beams.Therefore,the proposed terahertz LC metasurface can realize flexible control of reconfigurable functions and has certain application prospects in terahertz communication,phased array radar,and vortex radar.展开更多
Reliable Cluster Head(CH)selectionbased routing protocols are necessary for increasing the packet transmission efficiency with optimal path discovery that never introduces degradation over the transmission reliability...Reliable Cluster Head(CH)selectionbased routing protocols are necessary for increasing the packet transmission efficiency with optimal path discovery that never introduces degradation over the transmission reliability.In this paper,Hybrid Golden Jackal,and Improved Whale Optimization Algorithm(HGJIWOA)is proposed as an effective and optimal routing protocol that guarantees efficient routing of data packets in the established between the CHs and the movable sink.This HGJIWOA included the phases of Dynamic Lens-Imaging Learning Strategy and Novel Update Rules for determining the reliable route essential for data packets broadcasting attained through fitness measure estimation-based CH selection.The process of CH selection achieved using Golden Jackal Optimization Algorithm(GJOA)completely depends on the factors of maintainability,consistency,trust,delay,and energy.The adopted GJOA algorithm play a dominant role in determining the optimal path of routing depending on the parameter of reduced delay and minimal distance.It further utilized Improved Whale Optimisation Algorithm(IWOA)for forwarding the data from chosen CHs to the BS via optimized route depending on the parameters of energy and distance.It also included a reliable route maintenance process that aids in deciding the selected route through which data need to be transmitted or re-routed.The simulation outcomes of the proposed HGJIWOA mechanism with different sensor nodes confirmed an improved mean throughput of 18.21%,sustained residual energy of 19.64%with minimized end-to-end delay of 21.82%,better than the competitive CH selection approaches.展开更多
The Rydberg atom-based receiver, as a novel type of antenna, demonstrates broad application prospects in the field of microwave communications. However, since Rydberg atomic receivers are nonlinear systems, mismatches...The Rydberg atom-based receiver, as a novel type of antenna, demonstrates broad application prospects in the field of microwave communications. However, since Rydberg atomic receivers are nonlinear systems, mismatches between the parameters of the received amplitude modulation(AM) signals and the system's linear workspace and demodulation operating points can cause severe distortion in the demodulated signals. To address this, the article proposes a method for determining the operational parameters based on the mean square error(MSE) and total harmonic distortion(THD) assessments and presents strategies for optimizing the system's operational parameters focusing on linear response characteristics(LRC) and linear dynamic range(LDR). Specifically, we employ a method that minimizes the MSE to define the system's linear workspace, thereby ensuring the system has a good LRC while maximizing the LDR. To ensure that the signal always operates within the linear workspace, an appropriate carrier amplitude is set as the demodulation operating point. By calculating the THD at different operating points, the LRC performance within different regions of the linear workspace is evaluated, and corresponding optimization strategies based on the range of signal strengths are proposed. Moreover, to more accurately restore the baseband signal, we establish a mapping relationship between the carrier Rabi frequency and the transmitted power of the probe light, and optimize the slope of the linear demodulation function to reduce the MSE to less than 0.8×10^(-4). Finally, based on these methods for determining the operational parameters, we explore the effects of different laser Rabi frequencies on the system performance, and provide optimization recommendations. This research provides robust support for the design of high-performance Rydberg atom-based AM receivers.展开更多
Blades are important parts of rotating machinery such as marine gas turbines and wind turbines,which are exposed to harsh environments during mechanical operations,including centrifugal loads,aerodynamic forces,or hig...Blades are important parts of rotating machinery such as marine gas turbines and wind turbines,which are exposed to harsh environments during mechanical operations,including centrifugal loads,aerodynamic forces,or high temperatures.These demanding working conditions considerably influence the dynamic performance of blades.Therefore,because of the challenges posed by blades in complex working environments,in-depth research and optimization are necessary to ensure that blades can operate safely and efficiently,thus guaranteeing the reliability and performance of mechanical systems.Focusing on the vibration analysis of blades in rotating machinery,this paper conducts a comprehensive literature review on the research advancements in vibration modeling and structural optimization of blades under complex operational conditions.First,the paper outlines the development of several modeling theories for rotating blades,including one-dimensional beam theory,two-dimensional plate-shell theory,and three-dimensional solid theory.Second,the research progress in the vibrational analysis of blades under aerodynamic loads,thermal environments,and crack factors is separately discussed.Finally,the developments in rotating blade structural optimization are presented from material optimization and shape optimization perspectives.The methodology and theory of analyzing and optimizing blade vibration characteristics under multifactorial operating conditions are comprehensively outlined,aiming to assist future researchers in proposing more effective and practical approaches for the vibration analysis and optimization of blades.展开更多
Electron beam fluorescence technology is an advanced non-contact measurement in rarefied flow fields,and the fluorescence signal intensity is positively correlated with the electron beam current.The ion bombardment se...Electron beam fluorescence technology is an advanced non-contact measurement in rarefied flow fields,and the fluorescence signal intensity is positively correlated with the electron beam current.The ion bombardment secondary emission electron gun is suitable for the technology.To enhance the beam current,COMSOL simulations and analyses were conducted to examine plasma density distribution in the discharge chamber under the effects of various conditions and the electric field distribution between the cathode and the spacer gap.The anode shape and discharge pressure conditions were optimized to increase plasma density.Additionally,an improved spacer structure was designed with the dual purpose of enhancing the electric field distribution between the cathode-spacer gaps and improving vacuum differential effects.This design modification aims to increase the pass rate of secondary electrons.Both simulation and experimental results demonstrated that the performance of the optimized electron gun was effectively enhanced.When the electrode voltage remains constant and the discharge gas pressure is adjusted to around 8 Pa,the maximum beam current was increased from 0.9 mA to 1.6 mA.展开更多
Low-earth-orbit(LEO)satellite network has become a critical component of the satelliteterrestrial integrated network(STIN)due to its superior signal quality and minimal communication latency.However,the highly dynamic...Low-earth-orbit(LEO)satellite network has become a critical component of the satelliteterrestrial integrated network(STIN)due to its superior signal quality and minimal communication latency.However,the highly dynamic nature of LEO satellites leads to limited and rapidly varying contact time between them and Earth stations(ESs),making it difficult to timely download massive communication and remote sensing data within the limited time window.To address this challenge in heterogeneous satellite networks with coexisting geostationary-earth-orbit(GEO)and LEO satellites,this paper proposes a dynamic collaborative inter-satellite data download strategy to optimize the long-term weighted energy consumption and data downloads within the constraints of on-board power,backlog stability and time-varying contact.Specifically,the Lyapunov optimization theory is applied to transform the long-term stochastic optimization problem,subject to time-varying contact time and on-board power constraints,into multiple deterministic single time slot problems,based on which online distributed algorithms are developed to enable each satellite to independently obtain the transmit power allocation and data processing decisions in closed-form.Finally,the simulation results demonstrate the superiority of the proposed scheme over benchmarks,e.g.,achieving asymptotic optimality of the weighted energy consumption and data downloads,while maintaining stability of the on-board backlog.展开更多
Trapped ion hardware has made significant progress recently and is now one of the leading platforms for quantum computing.To construct two-qubit gates in trapped ions,experimentalmanipulation approaches for ion chains...Trapped ion hardware has made significant progress recently and is now one of the leading platforms for quantum computing.To construct two-qubit gates in trapped ions,experimentalmanipulation approaches for ion chains are becoming increasingly prevalent.Given the restricted control technology,how implementing high-fidelity quantum gate operations is crucial.Many works in current pulse design optimization focus on ion–phonon and effective ion–ion couplings while ignoring the first-order derivative terms expansion impacts of these two terms brought on by experiment defects.This paper proposes a novel robust quantum control optimization method in trapped ions.By introducing the first-order derivative terms caused by the error into the optimization cost function,we generate an extremely robust Mølmer–Sørensen gate with infidelity below 10−3 under a drift noise range of±10 kHz,the relative robustness achieves a tolerance of±5%,compared to the 200-kHz frequency spacing between phonon modes,and for time noise drift,the tolerance reached to 2%.Our work reveals the vital role of the first-order derivative terms of coupling in trapped ion pulse control optimization,especially the first-order derivative terms of ion–ion coupling.It provides a robust optimization scheme for realizing more efficient entangled states in trapped ion platforms.展开更多
Accurately predicting the powder factor during blasting is essential for sustainable production planning in low-grade mines.This research presents a method for predicting powder factor based on the heterogeneity of ro...Accurately predicting the powder factor during blasting is essential for sustainable production planning in low-grade mines.This research presents a method for predicting powder factor based on the heterogeneity of rock mass rating(RMR).Considering a low-grade metal mine as an example,this study exploited geostatistical methods to obtain independent RMR for each block unit.A three-dimensional spatial distribution model for the powder factor was developed on the basis of the relationships between the RMR and the powder factor.Subsequently,models for blasting cost and mining value were built and employed to optimize the open-pit limit.The multi-variable model based on the RMR performed well in predicting the powder factor,achieving a correlation coefficient of 0.88(root mean square error of 4.3)and considerably outperforming the uniaxial compressive strength model.After model optimization,the mean size and standard deviation of the fragments in the blast pile decreased by 8.5%and 35.1%,respectively,whereas the boulder yield and its standard deviation decreased by 33.3%and 58.8%,respectively.Additionally,optimizing the open-pit limit using this method reduced the amount of rock,increased the amount of ore,and lowered blasting costs,thereby enhancing the economic efficiency of the mine.This study provides valuable insights for blasting design and mining decisions,demonstrating the advantages and potential applications of powder factor prediction based on the heterogeneity of rock mass quality.展开更多
This study integrates the individual photovoltaic(PV)and thermoelectric generator(TEG)systems into a PV-TEG hybrid system to improve its overall power output by reutilizing the waste heat generated during PV power pro...This study integrates the individual photovoltaic(PV)and thermoelectric generator(TEG)systems into a PV-TEG hybrid system to improve its overall power output by reutilizing the waste heat generated during PV power production to enhance its operational relia-bility.However,stochastic environmental conditions often result in partial shading conditions and nonuniform thermal distribution across the PV-TEG modules,which negatively affect the output characteristics of the system,thus presenting a significant challenge to maintaining their optimal performance.To address these challenges,a novel fitness-distance-balance-based beluga whale optimization(FDBBWO)strategy has been devised for maximizing the power output of the PV-TEG hybrid system under dynamic operation scenar-ios.A broader spectrum of complex and authentic operational contexts has been considered in case studies to examine the effectiveness and feasibility of FDBBWO.For this,real-world datasets collected from different seasons in Hong Kong have been used to validate the practical viability of the proposed strategy.Simulation results reveal that the FDBBWO based maximum power point tracking technique outperforms its competing methods by achieving the highest energy output,with a remarkable increase of up to 134.25%with minimal power fluctuations.For instance,the energy obtained by FDBBWO is 47.45%and 58.34%higher than BWO and perturb and observe methods,respectively,in the winter season.展开更多
This paper proposed a new libration decoupling analytical speed function(LD-ASF)in lieu of the classic analytical speed function to control the climber's speed along a partial space elevator to improve libration s...This paper proposed a new libration decoupling analytical speed function(LD-ASF)in lieu of the classic analytical speed function to control the climber's speed along a partial space elevator to improve libration stability in cargo transportation.The LD-ASF is further optimized for payload transportation efficiency by a novel coordinate game theory to balance competing control objectives among payload transport speed,stable end body's libration,and overall control input via model predictive control.The transfer period is divided into several sections to reduce computational burden.The validity and efficacy of the proposed LD-ASF and coordinate game-based model predictive control are demonstrated by computer simulation.Numerical results reveal that the optimized LD-ASF results in higher transportation speed,stable end body's libration,lower thrust fuel consumption,and more flexible optimization space than the classic analytical speed function.展开更多
China has set carbon emission goals for 2030 and 2060.Renewable energy sources,primarily wind and photovoltaic power,are being considered as the future of power generation.The major limitation to the development of ne...China has set carbon emission goals for 2030 and 2060.Renewable energy sources,primarily wind and photovoltaic power,are being considered as the future of power generation.The major limitation to the development of new energies is the limited flexibility of regulations on power system resources,resulting in insufficient consumption capacity.Thus,the flexible resource costs for peak shaving as well as the reasonable coordinated development and operation optimization of regional renewable energy need to be considered.In this study,a renewable energy development layout configuration analysis method was established by considering the composite cost of a power system,comprehensively analyzing the potential of various flexibility regulation resources for the power system and its composite peak shaving cost,and combining renewable energy output characteristics,load forecasting,grid development,and other factors.For the optimization of various flexible resource utilization methods,a peak shaving cost estimation method from the perspective of the entire power system was established by combining the on-grid electricity prices and operating costs of different power sources.A collaborative optimization model of power system operation that aims at the lowest peak shaving cost and satisfies the constraints of operation,safety,and environmental protection was proposed.Finally,a certain area of Gansu Province was used as an example to perform detailed analysis and calculation,which demonstrated that the model has an optimal effect.This model can provide an analysis method for regional renewable energy development layout configurations and system optimization operations.展开更多
基金supported in part by the National Key R&D Program of China under Grant 2020YFB1005900the National Natural Science Foundation of China under Grant 62001220+3 种基金the Jiangsu Provincial Key Research and Development Program under Grants BE2022068the Natural Science Foundation of Jiangsu Province under Grants BK20200440the Future Network Scientific Research Fund Project FNSRFP-2021-YB-03the Young Elite Scientist Sponsorship Program,China Association for Science and Technology.
文摘Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus the incentives for collaboration cannot be guaranteed.In this paper,we propose a consortium blockchain enabled collaborative edge computing framework,where users can offload computing tasks to ECSs from different operators.To minimize the total delay of users,we formulate a joint task offloading and resource optimization problem,under the constraint of the computing capability of each ECS.We apply the Tammer decomposition method and heuristic optimization algorithms to obtain the optimal solution.Finally,we propose a reputation based node selection approach to facilitate the consensus process,and also consider a completion time based primary node selection to avoid monopolization of certain edge node and enhance the security of the blockchain.Simulation results validate the effectiveness of the proposed algorithm,and the total delay can be reduced by up to 40%compared with the non-cooperative case.
基金This work was supported in part by the National Key R&D Program of China under Grant 2020YFB1005900the National Natural Science Foundation of China under Grant 62001220+3 种基金the Jiangsu Provincial Key Research and Development Program under Grants BE2022068the Natural Science Foundation of Jiangsu Province under Grants BK20200440the Future Network Scientific Research Fund Project FNSRFP-2021-YB-03the Young Elite Scientist Sponsorship Program,China Association for Science and Technology.
文摘Collaborative edge computing is a promising direction to handle the computation intensive tasks in B5G wireless networks.However,edge computing servers(ECSs)from different operators may not trust each other,and thus the incentives for collaboration cannot be guaranteed.In this paper,we propose a consortium blockchain enabled collaborative edge computing framework,where users can offload computing tasks to ECSs from different operators.To minimize the total delay of users,we formulate a joint task offloading and resource optimization problem,under the constraint of the computing capability of each ECS.We apply the Tammer decomposition method and heuristic optimization algorithms to obtain the optimal solution.Finally,we propose a reputation based node selection approach to facilitate the consensus process,and also consider a completion time based primary node selection to avoid monopolization of certain edge node and enhance the security of the blockchain.Simulation results validate the effectiveness of the proposed algorithm,and the total delay can be reduced by up to 40%compared with the non-cooperative case.
基金Knowledge-based Ship-design Hyper-integrated Platform(KSHIP) of Ministry of Education and Ministry of Finance,P. R. China(No.200512)
文摘The goal of this effort was to provide a static and dynamic collaborative optimization （CO） model for the design of ship hull structure. The CO model integrated with static, mode and dynamic analyses. In the system-level optimization model, a new objective function was advised, integrating all the subsystem-levels＇ objective functions, so as to eliminate the effects of dimensions and magnitude order. The proposed CO architecture enabled multi-objectives of the system and subsystem-level to be considered at both levels during optimization. A bi-level optimization strategy was advised, using the multi-island genetic algorithm. The proposed model was demonstrated with a deck optimization problem of container ship stern. The analysis progress and results of example show that the CO strategy is not only feasible and reliable, but also well suited for use in actual optimization problems of ship design.
文摘Improving the efficiency of ship optimization is crucial for modem ship design. Compared with traditional methods, multidisciplinary design optimization （MDO） is a more promising approach. For this reason, Collaborative Optimization （CO） is discussed and analyzed in this paper. As one of the most frequently applied MDO methods, CO promotes autonomy of disciplines while providing a coordinating mechanism guaranteeing progress toward an optimum and maintaining interdisciplinary compatibility. However, there are some difficulties in applying the conventional CO method, such as difficulties in choosing an initial point and tremendous computational requirements. For the purpose of overcoming these problems, optimal Latin hypercube design and Radial basis function network were applied to CO. Optimal Latin hypercube design is a modified Latin Hypercube design. Radial basis function network approximates the optimization model, and is updated during the optimization process to improve accuracy. It is shown by examples that the computing efficiency and robustness of this CO method are higher than with the conventional CO method.
基金support from the National Natural Science Foundation of China(22209089,22178187)Natural Science Foundation of Shandong Province(ZR2022QB048,ZR2021MB006)+2 种基金Excellent Youth Science Foundation of Shandong Province(Overseas)(2023HWYQ-089)the Taishan Scholars Program of Shandong Province(tsqn201909091)Open Research Fund of School of Chemistry and Chemical Engineering,Henan Normal University.
文摘Aqueous zinc-halogen batteries are promising candidates for large-scale energy storage due to their abundant resources,intrinsic safety,and high theoretical capacity.Nevertheless,the uncontrollable zinc dendrite growth and spontaneous shuttle effect of active species have prohibited their practical implementation.Herein,a double-layered protective film based on zinc-ethylenediamine tetramethylene phosphonic acid(ZEA)artificial film and ZnF2-rich solid electrolyte interphase(SEI)layer has been successfully fabricated on the zinc metal anode via electrode/electrolyte synergistic optimization.The ZEA-based artificial film shows strong affinity for the ZnF2-rich SEI layer,therefore effectively suppressing the SEI breakage and facilitating the construction of double-layered protective film on the zinc metal anode.Such double-layered architecture not only modulates Zn2+flux and suppresses the zinc dendrite growth,but also blocks the direct contact between the metal anode and electrolyte,thus mitigating the corrosion from the active species.When employing optimized metal anodes and electrolytes,the as-developed zinc-(dual)halogen batteries present high areal capacity and satisfactory cycling stability.This work provides a new avenue for developing aqueous zinc-(dual)halogen batteries.
文摘This review article provides a comprehensive analysis of nesting optimization algorithms in the shipbuilding industry,emphasizing their role in improving material utilization,minimizing waste,and enhancing production efficiency.The shipbuilding process involves the complex cutting and arrangement of steel plates,making the optimization of these operations vital for cost-effectiveness and sustainability.Nesting algorithms are broadly classified into four categories:exact,heuristic,metaheuristic,and hybrid.Exact algorithms ensure optimal solutions but are computationally demanding.In contrast,heuristic algorithms deliver quicker results using practical rules,although they may not consistently achieve optimal outcomes.Metaheuristic algorithms combine multiple heuristics to effectively explore solution spaces,striking a balance between solution quality and computational efficiency.Hybrid algorithms integrate the strengths of different approaches to further enhance performance.This review systematically assesses these algorithms using criteria such as material dimensions,part geometry,component layout,and computational efficiency.The findings highlight the significant potential of advanced nesting techniques to improve material utilization,reduce production costs,and promote sustainable practices in shipbuilding.By adopting suitable nesting solutions,shipbuilders can achieve greater efficiency,optimized resource management,and superior overall performance.Future research directions should focus on integrating machine learning and real-time adaptability to further enhance nesting algorithms,paving the way for smarter,more sustainable manufacturing practices in the shipbuilding industry.
基金supported by the State Key Laboratory of Information Photonics and Optical Communications(Beijing University of Posts and Telecommunications)No.IPOC2021ZT10BUPT Excellent Ph.D.Students Foundation(Grant No.CX2023207)the BUPT innovation and entrepreneurship support program No.2024-YC-A188。
文摘Phase-matching quantum-key distribution(PM-QKD)has achieved significant results in various practical applications.However,real-time communication requires dynamic adjustment and optimization of key parameters during communication.In this letter,we predict the PM-QKD parameters using nature-inspired algorithms(NIAs).The results are obtained from an exhaustive traversal algorithm(ETA),which serves as a benchmark.We mainly study the parameter optimization effects of the two NIAs:ant colony optimization(ACO)and the genetic algorithm(GA).The configuration of the inherent parameters of these algorithms in the decoy-state PM-QKD is also discussed.The simulation results indicate that the parameters obtained by the ACO exhibit superior convergence and stability,whereas the GA results are relatively scattered.Nevertheless,more than 97%of the key rates predicted by both algorithms are highly consistent with the optimal key rate.Moreover,the relative error of the key rates remained below 10%.Furthermore,NIAs maintain power consumption below 8 W and require three orders of magnitude less computing time than ETA.
基金supported by the National Key Research and Development Program of China (Grant No. 2023YFB4502500)。
文摘Optimizing frequency configurations for qubits and gates in superconducting quantum chips presents a complex NP-complete challenge,critical for mitigating decoherence and crosstalk.This paper introduces a neural network-based approach,leveraging the network as a surrogate model to predict frequency errors.The method employs a closed-loop Bayesian optimization framework to iteratively refine configurations,guided by the network’s knowledge of nonlinear error mechanisms.By focusing on localized chip windows,the optimization identifies optimal frequency settings that minimize errors.The approach is validated through randomized and cross-entropy benchmarking,showing improved energy calculations when optimizing frequency configurations for a crosstalkaware hardware-efficient ansatz in variational quantum eigensolvers on superconducting quantum chips.
基金partly supported by the National Natural Science Foundation of China(Grant No.52272225).
文摘Na_(3)V_(2)(PO_(4))_(3)(NVP)has garnered great attentions as a prospective cathode material for sodium-ion batteries(SIBs)by virtue of its decent theoretical capacity,superior ion conductivity and high structural stability.However,the inherently poor electronic conductivity and sluggish sodium-ion diffusion kinetics of NVP material give rise to inferior rate performance and unsatisfactory energy density,which strictly confine its further application in SIBs.Thus,it is of significance to boost the sodium storage performance of NVP cathode material.Up to now,many methods have been developed to optimize the electrochemical performance of NVP cathode material.In this review,the latest advances in optimization strategies for improving the electrochemical performance of NVP cathode material are well summarized and discussed,including carbon coating or modification,foreign-ion doping or substitution and nanostructure and morphology design.The foreign-ion doping or substitution is highlighted,involving Na,V,and PO_(4)^(3−)sites,which include single-site doping,multiple-site doping,single-ion doping,multiple-ion doping and so on.Furthermore,the challenges and prospects of high-performance NVP cathode material are also put forward.It is believed that this review can provide a useful reference for designing and developing high-performance NVP cathode material toward the large-scale application in SIBs.
基金Project supported by the Open Fund of Wuhan National Research Center for Optoelectronics(Grant No.2022WNLOKF012)the National College Students Innovation Innovation and Entrepreneurship Training Program(Grant No.2023102930147).
文摘A broadband polarization-independent terahertz multifunctional coding metasurface based on topological optimization using liquid crystal(LC)is proposed.The metasurface can achieve reconfigurability for beam steering and vortex beam generation within a frequency range of 0.68 THz–0.72 THz.Firstly,the metasurface unit is topologically optimized using the non-dominant sequencing genetic algorithms(NSGA-II)multi-objective optimization algorithm.By applying the LC’s electrically tunable refractive index properties,the metasurface unit enables polarization-independent 2-bit coding within a frequency range of 0.68 THz–0.72 THz.Then,based on the designed metasurface unit,the array arrangement of the metasurface is reverse-designed to achieve beam steering and vortex beam generation.The results show that,for beam steering,not only can polarization-independent steering of both single-and multi-beam be achieved within the 35°elevation angle range,but also independent control of the target angle of each beam in the multi-beam steering.For vortex beam generation,the metasurfaces can achieve the generation of single-and multi-vortex beams with topological charges l=±1,±2 within the 35elevation angle range,and the generation angles of each vortex beam in the multi-vortex beam can be independently controlled.This provides flexibility and diversity in the generation of vortex beams.Therefore,the proposed terahertz LC metasurface can realize flexible control of reconfigurable functions and has certain application prospects in terahertz communication,phased array radar,and vortex radar.
文摘Reliable Cluster Head(CH)selectionbased routing protocols are necessary for increasing the packet transmission efficiency with optimal path discovery that never introduces degradation over the transmission reliability.In this paper,Hybrid Golden Jackal,and Improved Whale Optimization Algorithm(HGJIWOA)is proposed as an effective and optimal routing protocol that guarantees efficient routing of data packets in the established between the CHs and the movable sink.This HGJIWOA included the phases of Dynamic Lens-Imaging Learning Strategy and Novel Update Rules for determining the reliable route essential for data packets broadcasting attained through fitness measure estimation-based CH selection.The process of CH selection achieved using Golden Jackal Optimization Algorithm(GJOA)completely depends on the factors of maintainability,consistency,trust,delay,and energy.The adopted GJOA algorithm play a dominant role in determining the optimal path of routing depending on the parameter of reduced delay and minimal distance.It further utilized Improved Whale Optimisation Algorithm(IWOA)for forwarding the data from chosen CHs to the BS via optimized route depending on the parameters of energy and distance.It also included a reliable route maintenance process that aids in deciding the selected route through which data need to be transmitted or re-routed.The simulation outcomes of the proposed HGJIWOA mechanism with different sensor nodes confirmed an improved mean throughput of 18.21%,sustained residual energy of 19.64%with minimized end-to-end delay of 21.82%,better than the competitive CH selection approaches.
基金Project supported by the National Natural Science Foundation of China (Grant No. U22B2095)the Civil Aerospace Technology Research Project (Grant No. D010103)。
文摘The Rydberg atom-based receiver, as a novel type of antenna, demonstrates broad application prospects in the field of microwave communications. However, since Rydberg atomic receivers are nonlinear systems, mismatches between the parameters of the received amplitude modulation(AM) signals and the system's linear workspace and demodulation operating points can cause severe distortion in the demodulated signals. To address this, the article proposes a method for determining the operational parameters based on the mean square error(MSE) and total harmonic distortion(THD) assessments and presents strategies for optimizing the system's operational parameters focusing on linear response characteristics(LRC) and linear dynamic range(LDR). Specifically, we employ a method that minimizes the MSE to define the system's linear workspace, thereby ensuring the system has a good LRC while maximizing the LDR. To ensure that the signal always operates within the linear workspace, an appropriate carrier amplitude is set as the demodulation operating point. By calculating the THD at different operating points, the LRC performance within different regions of the linear workspace is evaluated, and corresponding optimization strategies based on the range of signal strengths are proposed. Moreover, to more accurately restore the baseband signal, we establish a mapping relationship between the carrier Rabi frequency and the transmitted power of the probe light, and optimize the slope of the linear demodulation function to reduce the MSE to less than 0.8×10^(-4). Finally, based on these methods for determining the operational parameters, we explore the effects of different laser Rabi frequencies on the system performance, and provide optimization recommendations. This research provides robust support for the design of high-performance Rydberg atom-based AM receivers.
基金Supported by the National Natural Science Foundation of China under Grant No.52271309Natural Science Foundation of Heilongjiang Province of China under Grant No.YQ2022E104.
文摘Blades are important parts of rotating machinery such as marine gas turbines and wind turbines,which are exposed to harsh environments during mechanical operations,including centrifugal loads,aerodynamic forces,or high temperatures.These demanding working conditions considerably influence the dynamic performance of blades.Therefore,because of the challenges posed by blades in complex working environments,in-depth research and optimization are necessary to ensure that blades can operate safely and efficiently,thus guaranteeing the reliability and performance of mechanical systems.Focusing on the vibration analysis of blades in rotating machinery,this paper conducts a comprehensive literature review on the research advancements in vibration modeling and structural optimization of blades under complex operational conditions.First,the paper outlines the development of several modeling theories for rotating blades,including one-dimensional beam theory,two-dimensional plate-shell theory,and three-dimensional solid theory.Second,the research progress in the vibrational analysis of blades under aerodynamic loads,thermal environments,and crack factors is separately discussed.Finally,the developments in rotating blade structural optimization are presented from material optimization and shape optimization perspectives.The methodology and theory of analyzing and optimizing blade vibration characteristics under multifactorial operating conditions are comprehensively outlined,aiming to assist future researchers in proposing more effective and practical approaches for the vibration analysis and optimization of blades.
文摘Electron beam fluorescence technology is an advanced non-contact measurement in rarefied flow fields,and the fluorescence signal intensity is positively correlated with the electron beam current.The ion bombardment secondary emission electron gun is suitable for the technology.To enhance the beam current,COMSOL simulations and analyses were conducted to examine plasma density distribution in the discharge chamber under the effects of various conditions and the electric field distribution between the cathode and the spacer gap.The anode shape and discharge pressure conditions were optimized to increase plasma density.Additionally,an improved spacer structure was designed with the dual purpose of enhancing the electric field distribution between the cathode-spacer gaps and improving vacuum differential effects.This design modification aims to increase the pass rate of secondary electrons.Both simulation and experimental results demonstrated that the performance of the optimized electron gun was effectively enhanced.When the electrode voltage remains constant and the discharge gas pressure is adjusted to around 8 Pa,the maximum beam current was increased from 0.9 mA to 1.6 mA.
基金supported by the National Natural Science Foundation of China under Grant 62371098the National Key Laboratory ofWireless Communications Foundation under Grant IFN20230203the National Key Research and Development Program of China under Grant 2021YFB2900404.
文摘Low-earth-orbit(LEO)satellite network has become a critical component of the satelliteterrestrial integrated network(STIN)due to its superior signal quality and minimal communication latency.However,the highly dynamic nature of LEO satellites leads to limited and rapidly varying contact time between them and Earth stations(ESs),making it difficult to timely download massive communication and remote sensing data within the limited time window.To address this challenge in heterogeneous satellite networks with coexisting geostationary-earth-orbit(GEO)and LEO satellites,this paper proposes a dynamic collaborative inter-satellite data download strategy to optimize the long-term weighted energy consumption and data downloads within the constraints of on-board power,backlog stability and time-varying contact.Specifically,the Lyapunov optimization theory is applied to transform the long-term stochastic optimization problem,subject to time-varying contact time and on-board power constraints,into multiple deterministic single time slot problems,based on which online distributed algorithms are developed to enable each satellite to independently obtain the transmit power allocation and data processing decisions in closed-form.Finally,the simulation results demonstrate the superiority of the proposed scheme over benchmarks,e.g.,achieving asymptotic optimality of the weighted energy consumption and data downloads,while maintaining stability of the on-board backlog.
文摘Trapped ion hardware has made significant progress recently and is now one of the leading platforms for quantum computing.To construct two-qubit gates in trapped ions,experimentalmanipulation approaches for ion chains are becoming increasingly prevalent.Given the restricted control technology,how implementing high-fidelity quantum gate operations is crucial.Many works in current pulse design optimization focus on ion–phonon and effective ion–ion couplings while ignoring the first-order derivative terms expansion impacts of these two terms brought on by experiment defects.This paper proposes a novel robust quantum control optimization method in trapped ions.By introducing the first-order derivative terms caused by the error into the optimization cost function,we generate an extremely robust Mølmer–Sørensen gate with infidelity below 10−3 under a drift noise range of±10 kHz,the relative robustness achieves a tolerance of±5%,compared to the 200-kHz frequency spacing between phonon modes,and for time noise drift,the tolerance reached to 2%.Our work reveals the vital role of the first-order derivative terms of coupling in trapped ion pulse control optimization,especially the first-order derivative terms of ion–ion coupling.It provides a robust optimization scheme for realizing more efficient entangled states in trapped ion platforms.
基金supported by the National Key Research and Development Program of China(No.2022YFC2903902)the National Natural Science Foundation of China(Nos.52204080and 52174070)the Fundamental Research Funds for the Central Universities of China(No.2023GFYD17)。
文摘Accurately predicting the powder factor during blasting is essential for sustainable production planning in low-grade mines.This research presents a method for predicting powder factor based on the heterogeneity of rock mass rating(RMR).Considering a low-grade metal mine as an example,this study exploited geostatistical methods to obtain independent RMR for each block unit.A three-dimensional spatial distribution model for the powder factor was developed on the basis of the relationships between the RMR and the powder factor.Subsequently,models for blasting cost and mining value were built and employed to optimize the open-pit limit.The multi-variable model based on the RMR performed well in predicting the powder factor,achieving a correlation coefficient of 0.88(root mean square error of 4.3)and considerably outperforming the uniaxial compressive strength model.After model optimization,the mean size and standard deviation of the fragments in the blast pile decreased by 8.5%and 35.1%,respectively,whereas the boulder yield and its standard deviation decreased by 33.3%and 58.8%,respectively.Additionally,optimizing the open-pit limit using this method reduced the amount of rock,increased the amount of ore,and lowered blasting costs,thereby enhancing the economic efficiency of the mine.This study provides valuable insights for blasting design and mining decisions,demonstrating the advantages and potential applications of powder factor prediction based on the heterogeneity of rock mass quality.
基金supported by National Natural Science Foundation of China(62263014)Yunnan Provincial Basic Research Project(202401AT070344,202301AT070443).
文摘This study integrates the individual photovoltaic(PV)and thermoelectric generator(TEG)systems into a PV-TEG hybrid system to improve its overall power output by reutilizing the waste heat generated during PV power production to enhance its operational relia-bility.However,stochastic environmental conditions often result in partial shading conditions and nonuniform thermal distribution across the PV-TEG modules,which negatively affect the output characteristics of the system,thus presenting a significant challenge to maintaining their optimal performance.To address these challenges,a novel fitness-distance-balance-based beluga whale optimization(FDBBWO)strategy has been devised for maximizing the power output of the PV-TEG hybrid system under dynamic operation scenar-ios.A broader spectrum of complex and authentic operational contexts has been considered in case studies to examine the effectiveness and feasibility of FDBBWO.For this,real-world datasets collected from different seasons in Hong Kong have been used to validate the practical viability of the proposed strategy.Simulation results reveal that the FDBBWO based maximum power point tracking technique outperforms its competing methods by achieving the highest energy output,with a remarkable increase of up to 134.25%with minimal power fluctuations.For instance,the energy obtained by FDBBWO is 47.45%and 58.34%higher than BWO and perturb and observe methods,respectively,in the winter season.
基金funded by the National Natural Science Foundation of China(12102487)Basic and Applied Basic Research Foundation of Guangdong Province,China(2023A1515012339)+1 种基金Shenzhen Science and Technology Program(ZDSYS20210623091808026)the Discovery Grant(RGPIN-2024-06290)of the Natural Sciences and Engineering Research Council of Canada。
文摘This paper proposed a new libration decoupling analytical speed function(LD-ASF)in lieu of the classic analytical speed function to control the climber's speed along a partial space elevator to improve libration stability in cargo transportation.The LD-ASF is further optimized for payload transportation efficiency by a novel coordinate game theory to balance competing control objectives among payload transport speed,stable end body's libration,and overall control input via model predictive control.The transfer period is divided into several sections to reduce computational burden.The validity and efficacy of the proposed LD-ASF and coordinate game-based model predictive control are demonstrated by computer simulation.Numerical results reveal that the optimized LD-ASF results in higher transportation speed,stable end body's libration,lower thrust fuel consumption,and more flexible optimization space than the classic analytical speed function.
基金the National Natural Science Foundation of China(No.71273088).
文摘China has set carbon emission goals for 2030 and 2060.Renewable energy sources,primarily wind and photovoltaic power,are being considered as the future of power generation.The major limitation to the development of new energies is the limited flexibility of regulations on power system resources,resulting in insufficient consumption capacity.Thus,the flexible resource costs for peak shaving as well as the reasonable coordinated development and operation optimization of regional renewable energy need to be considered.In this study,a renewable energy development layout configuration analysis method was established by considering the composite cost of a power system,comprehensively analyzing the potential of various flexibility regulation resources for the power system and its composite peak shaving cost,and combining renewable energy output characteristics,load forecasting,grid development,and other factors.For the optimization of various flexible resource utilization methods,a peak shaving cost estimation method from the perspective of the entire power system was established by combining the on-grid electricity prices and operating costs of different power sources.A collaborative optimization model of power system operation that aims at the lowest peak shaving cost and satisfies the constraints of operation,safety,and environmental protection was proposed.Finally,a certain area of Gansu Province was used as an example to perform detailed analysis and calculation,which demonstrated that the model has an optimal effect.This model can provide an analysis method for regional renewable energy development layout configurations and system optimization operations.
