The existing third-order tracker known as α-β-γ-δ filter has been used for target tracking and predicting for years. The filter can track the target＇s position and velocity, but not the acceleration. To extend it...The existing third-order tracker known as α-β-γ-δ filter has been used for target tracking and predicting for years. The filter can track the target＇s position and velocity, but not the acceleration. To extend its capability, a new fourth-order target tracker called α-β-γ-δ filter is proposed. The main objective of this study was to find the optimal set of filter parameters that leads to minimum position tracking errors. The tracking errors between using the α-β-γ-δ filter and the α-β-γ-δ filter are compared. As a result, the new filter exhibits significant improvement in position tracking accuracy over the existing third-order filter, but at the expense of computational time in search of the optimal filter. To reduce the computational time, a simulation-based optimization technique via Taguchi method is introduced.展开更多
Objectives:The objective of this study is to evaluate the effect of simulation-based education(SBE)on the knowledge and skills of nursing students in managing childhood epileptic seizures.Materials and Methods:A quasi...Objectives:The objective of this study is to evaluate the effect of simulation-based education(SBE)on the knowledge and skills of nursing students in managing childhood epileptic seizures.Materials and Methods:A quasi-experimental design was conducted among 160 third-year B.Sc.nursing students at a SUM nursing college in Bhubaneswar,India.The experimental group(n=80)participated in a structured simulation-based session,while the control group(n=80)received routine lecture-demonstration sessions.Knowledge was measured using a 20-item multiple-choice questionnaire and skills were assessed through an Objective Structured Clinical Examination checklist.Results:The experimental group demonstrated significant improvements in posttest knowledge(13.15±1.40 vs.9.56±2.10;t=11.24,P<0.001)and skill scores(17.28±1.82 vs.12.42±2.18;t=10.96,P<0.001)compared with the control group.Ranked data analysis further confirmed higher postintervention knowledge and skill levels(Z=−-6.42 and−-6.55,respectively;P<0.001).These results indicated that SBE produced substantial gains in both cognitive and psychomotor domains.Conclusion:SBE significantly enhances nursing students’knowledge and skills in managing childhood epileptic seizures compared to traditional teaching.Incorporating structured simulation modules into pediatric nursing curricula can improve clinical competence,reduce anxiety,and bolster patient safety in pediatric emergency care.展开更多
When designing an arctic cargo ship, it is necessary to consider multiple stochastic factors. This paper evaluates the merits of a simulation-based probabilistic design method specifically developed to deal with this...When designing an arctic cargo ship, it is necessary to consider multiple stochastic factors. This paper evaluates the merits of a simulation-based probabilistic design method specifically developed to deal with this challenge. The outcome of the paper indicates that the incorporation of simulations and probabilistic design parameters into the design process enables more informed design decisions. For instance, it enables the assessment of the stochastic transport capacity of an arctic ship, as well as of its long-term ice exposure that can be used to determine an appropriate level of ice-strengthening. The outcome of the paper also indicates that significant gains in transport system cost-efficiency can be obtained by extending the boundaries of the design task beyond the individual vessel. In the case of industrial shipping, this allows for instance the consideration of port-based cargo storage facilities allowing for temporary shortages in transport capacity and thus a reduction in the required fleet size / ship capacity.展开更多
Fluxgate current sensors(FGCSs)are increasingly employed in power systems due to their high-precision characteristics,yet their measurement flexibility remains constrained by conventional closed-core designs.To addres...Fluxgate current sensors(FGCSs)are increasingly employed in power systems due to their high-precision characteristics,yet their measurement flexibility remains constrained by conventional closed-core designs.To address this limitation,we proposed a split-core sensor structure comprising four magnetic core strips,which achieved non-intrusive current measurement while maintaining detection accuracy.An analytical model of the induced electromotive force was established based on the probe’s geometric configuration,followed by finite element simulations to optimize key parameters including core radius,core width,excitation coil turns,and sensing coil configuration.A complete prototype integrating the measurement probe,excitation circuit,and signal processing circuitry was developed and experimentally validated.The experimental results show a sensitivity of 0.1099 V/A,a hysteresis error of 0.559%,and a repeatability error of 1.574%over a measurement range of±10 A.After polynomial fitting-based error compensation,the nonlinearity error was reduced to 0.208%,achieving performance comparable to closed-core sensors.This work provided a practical solution for applications demanding both high measurement accuracy and installation flexibility.展开更多
Purpose-Interface management is the process of managing communications,responsibilities and coordination of project parties,phases or physical entities which are dependent on one another.Interface management is a cruc...Purpose-Interface management is the process of managing communications,responsibilities and coordination of project parties,phases or physical entities which are dependent on one another.Interface management is a crucial part of managing any construction project-but particularly important for high-speed railway projects that often have several contractual parties and stakeholders,very long project timelines and huge upfront cost overlays.This paper discusses how various project interfaces were managed during the design and construction of the civil engineering infrastructure for the High Speed Two(HS2)project in the United Kingdom.Design/methodology/approach-The paper uses the case study methodology.Key interfaces on the HS2 project are grouped into various categories and the paper discusses how they were managed within the Area North Integrated Project Team(IPT)of the HS2 project made up of contractor Balfour Beatty VINCI(BBV),the Mott MacDonald SYSTRA Design Joint Venture(DJV)and client HS2 Ltd.3 different case studies drawn from across the IPT are used,each of them highlighting different interfaces and how these interfaces were managed.Findings-The paper shows how innovative technical designs and modern methods of construction were used to address some of the unique and peculiar challenges of designing a brand-new railway in the United Kingdom.Addressing the contrasting and often competing requirements of different stakeholders,coupled with challenging physical constraints of the very limited land available for the project and the use of a rarely used Act of Parliament in the delivery of the project required different approach to interface management.Collaboration and proactive stakeholder engagement are necessary for successful interface management on megaprojects.The authors posit that adopting an integrated approach to engineering and construction management is an essential ingredient for the successful delivery of high-speed railway projects.Originality/value-With many high-speed railway projects around the world coming up in the next few years,understanding the context and challenges for each country will help engineering and design managers adopt appropriate approaches for their projects.The lessons learned on the HS2 project are also transferable to other mega infrastructure projects with complex project interfaces.展开更多
Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon...Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon neutrality goals.The hydrogenation of CO_(2)to methanol not only enables carbon sequestration and recycling,but also provides a route to produce high value-added fuels and basic chemical feedstocks,holding significant environmental and economic potential.However,this conversion process is thermodynamically and kinetically limited,and traditional catalyst systems(e.g.,Cu/ZnO/Al_(2)O_(3))exhibit inadequate activity,selectivity,and stability under mild conditions.Therefore,the development of novel high-performance catalysts with precisely tunable structures and functionalities is imperative.Metal-organic frameworks(MOFs),as crystalline porous materials with high surface area,tunable pore structures,and diverse metal-ligand compositions,have the great potential in CO_(2)hydrogenation catalysis.Their structural design flexibility allows for the construction of well-dispersed active sites,tailored electronic environments,and enhanced metal-support interactions.This review systematically summarizes the recent advances in MOF-based and MOF-derived catalysts for CO_(2)hydrogenation to methanol,focusing on four design strategies:(1)spatial confinement and in situ construction,(2)defect engineering and ion-exchange,(3)bimetallic synergy and hybrid structure design,and(4)MOF-derived nanomaterial synthesis.These approaches significantly improve CO_(2)conversion and methanol selectivity by optimizing metal dispersion,interfacial structures,and reaction pathways.The reaction mechanism is further explored by focusing on the three main reaction pathways:the formate pathway(HCOO*),the RWGS(Reverse Water Gas Shift reaction)+CO*hydrogenation pathway,and the trans-COOH pathway.In situ spectroscopic studies and density functional theory(DFT)calculations elucidate the formation and transformation of key intermediates,as well as the roles of active sites,metal-support interfaces,oxygen vacancies,and promoters.Additionally,representative catalytic performance data for MOFbased systems are compiled and compared,demonstrating their advantages over traditional catalysts in terms of CO_(2)conversion,methanol selectivity,and space-time yield.Future perspectives for MOF-based CO_(2)hydrogenation catalysts will prioritize two main directions:structural design and mechanistic understanding.The precise construction of active sites through multi-metallic synergy,defect engineering,and interfacial electronic modulation should be made to enhance catalyst selectivity and stability.In addition,advanced in situ characterization techniques combined with theoretical modeling are essential to unravel the detailed reaction mechanisms and intermediate behaviors,thereby guiding rational catalyst design.Moreover,to enable industrial application,challenges related to thermal/hydrothermal stability,catalyst recyclability,and cost-effective large-scale synthesis must be addressed.The development of green,scalable preparation methods and the integration of MOF catalysts into practical reaction systems(e.g.,flow reactors)will be crucial for bridging the gap between laboratory research and commercial deployment.Ultimately,multi-scale structure-performance optimization and catalytic system integration will be vital for accelerating the industrialization of MOF-based CO_(2)-to-methanol technologies.展开更多
The electrochemical oxidation of biomass-derived platform molecule 5-hydroxymethylfurfural(HMF)represents a crucial pathway for green transformation into high-value chemicals,yet its reaction pathway selectivity,effic...The electrochemical oxidation of biomass-derived platform molecule 5-hydroxymethylfurfural(HMF)represents a crucial pathway for green transformation into high-value chemicals,yet its reaction pathway selectivity,efficiency,and catalyst stability are strongly dependent on the electrolyte pH environment.Under alkaline conditions,high OH−concentration facilitates preferential aldehyde group oxidation and efficient deprotonation,enabling highly efficient synthesis of 2,5-furandicarboxylic acid,but simultaneously induces HMF self-degradation and complicates product separation.As pH decreases,the reaction mechanism shifts toward enhanced hydroxymethyl oxidation,leading to intermediate accumulation(such as 5-hydroxymethyl-2-furancarboxylic acid,2,5-diformylfuran,and 5-formyl-2-furancarboxylic acid)with challenging selectivity control and significantly slowed reaction kinetics.This review comprehensively examines the systematic differences in HMF oxidation pathways and surface catalytic mechanisms across the full pH range from alkaline to acidic conditions.Addressing the distinct reaction characteristics and core challenges in alkaline,near-neutral,and acidic media,we systematically evaluate design strategies for high-efficiency electrocatalysts and explore reactor design aspects.Future research should focus on process integration(with tailored reactor design)for energy consumption reduction in alkaline systems,targeted synthesis of diverse oxidation products in near-neutral systems,and innovative catalyst development for acidic systems,thereby advancing the efficiency,selectivity,and practical application of HMF electrooxidation technologies across the entire pH spectrum through synergistic optimization of catalyst,reactor,and process.展开更多
Memristors have emerged as a transformative technology in the realm of electronic devices,offering unique advantages such as fast switching speeds,low power consumption,and the ability to sensor-memory-compute.The app...Memristors have emerged as a transformative technology in the realm of electronic devices,offering unique advantages such as fast switching speeds,low power consumption,and the ability to sensor-memory-compute.The applications span across non-volatile memory,neuromorphic computing,hardware security,and beyond,prompting memristors to become a versatile solution for next-generation computing and data storage systems.Despite enormous potential of memristors,the transition from laboratory prototypes to large-scale applications is challenging in terms of material stability,device reproducibility,and array scalability.This review systematically explores recent advancements in high-performance memristor technologies,focusing on performance enhancement strategies through material engineering,structural design,pulse protocol optimization,and algorithm control.We provide an in-depth analysis of key performance metrics tailored to specific applications,including non-volatile memory,neuromorphic computing,and hardware security.Furthermore,we propose a co-design framework that integrates device-level optimizations with operational-level improvements,aiming to bridge the gap between theoretical models and practical implementations.展开更多
Compact size,high brightness,and wide field of view(FOV)are key requirements for long-wave infrared imagers used in military surveillance or night navigation.However,to meet the imaging requirements of high resolution...Compact size,high brightness,and wide field of view(FOV)are key requirements for long-wave infrared imagers used in military surveillance or night navigation.However,to meet the imaging requirements of high resolution and wide FOV,infrared optical systems often adopt complex optical lens groups,which will increase the size and weight of the optical system.In this paper,a strategy based on wavefront coding(WFC)is proposed to design a compact wide-FOV infrared imager.A cubic phase mask is inserted into the pupil plane of the infrared imager to correct the aberration.The simulated results show that,the WFC infrared imager has good imaging quality in a wide FOV of±16°.In addition,the WFC infrared imager achieves compactness with its 40 mm×40 mm×40 mm size.A fast focal ratio of 1 combined with an entrance pupil diameter of 25 mm ensures brightness.This work is of significance for designing a compact wide-FOV infrared imager.展开更多
In recent years,the use of deep learning to replace traditional numerical methods for electromagnetic propagation has shown tremendous potential in the rapid design of photonic devices.However,most research on deep le...In recent years,the use of deep learning to replace traditional numerical methods for electromagnetic propagation has shown tremendous potential in the rapid design of photonic devices.However,most research on deep learning has focused on single-layer grating couplers,and the accuracy of multi-layer grating couplers has not yet reached a high level.This paper proposes and demonstrates a novel deep learning network-assisted strategy for inverse design.The network model is based on a multi-layer perceptron(MLP)and incorporates convolutional neural networks(CNNs)and transformers.Through the stacking of multiple layers,it achieves a high-precision design for both multi-layer and single-layer raster couplers with various functionalities.The deep learning network exhibits exceptionally high predictive accuracy,with an average absolute error across the full wavelength range of 1300–1700 nm being only 0.17%,and an even lower predictive absolute error below 0.09%at the specific wavelength of 1550 nm.By combining the deep learning network with the genetic algorithm,we can efficiently design grating couplers that perform different functions.Simulation results indicate that the designed single-wavelength grating couplers achieve coupling efficiencies exceeding 80%at central wavelengths of 1550 nm and 1310 nm.The performance of designed dual-wavelength and broadband grating couplers also reaches high industry standards.Furthermore,the network structure and inverse design method are highly scalable and can be applied not only to multi-layer grating couplers but also directly to the prediction and design of single-layer grating couplers,providing a new perspective for the innovative development of photonic devices.展开更多
In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honey...In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honeycomb cells,was created by constructing arrangement matrices to achieve structural lightweight.The machine learning(ML)framework consisted of a neural network(NN)forward regression model for predicting impact resistance and a multi-objective optimization algorithm for generating high-performance designs.The surrogate of the local design space was initially realized by establishing the NN in the small sample dataset,and the active learning strategy was used to continuously extended the local optimal design until the model converged in the global space.The results indicated that the active learning strategy significantly improved the inference capability of the NN model in unknown design domains.By guiding the iteration direction of the optimization algorithm,lightweight designs with high impact resistance were identified.The energy absorption capacity of the optimal design reached 94.98%of the EARE honeycomb,while the initial peak stress and mass decreased by 28.85%and 19.91%,respectively.Furthermore,Shapley Additive Explanations(SHAP)for global explanation of the NN indicated a strong correlation between the arrangement mode of HCS and its impact resistance.By reducing the stiffness of the cells at the top boundary of the structure,the initial impact damage sustained by the structure can be significantly improved.Overall,this study proposed a general lightweight design method for array structures under impact loads,which is beneficial for the widespread application of honeycomb-based protective structures.展开更多
Cellulose,the dominant natural polymer on Earth,features a distinct molecular structure with extraordinary mechanical properties and tunable characteristics,making it attractive for gel systems.Although significant pr...Cellulose,the dominant natural polymer on Earth,features a distinct molecular structure with extraordinary mechanical properties and tunable characteristics,making it attractive for gel systems.Although significant progress has been made,challenges remain in fully leveraging their functional potential and broadening practical applications.This review systematically examines the properties of cellulose and cellulose gels,exploring novel reinforcement strategies—across molecular,supramolecular network,and macroscale structure levels—to enhance mechanical,electrical,and thermal performance,while coordinating these properties for practical implementations.These advancements are exemplified in emerging fields such as flexible robotics,electronic skins,flexible energy storage devices,and human-machine interaction systems.This article thoroughly investigates the fundamental characteristics,multi-scale design approaches,performance enhancement mechanisms,and cutting-edge implementations of cellulose-based gels across diverse domains.It provides a comprehensive overview of these advanced materials and offers strategic insights and recommendations for future research and innovation.展开更多
Cognitive unmanned aerial vehicle(UAV)is promising to tackle the spectrum scarcity problem faced by UAV communications.However,the secure information transmission is challenging due to the open nature of the spectrum ...Cognitive unmanned aerial vehicle(UAV)is promising to tackle the spectrum scarcity problem faced by UAV communications.However,the secure information transmission is challenging due to the open nature of the spectrum sharing.In order to tackle this issue,a cognitive UAV network with cooperative jamming is studied in this paper.A robust resource allocation and trajectory joint optimization problem is formulated by considering the practical case that the channel state information(CSI)cannot be accurately obtained.An iterative algorithm is proposed to address this challenging non-convex problem.Simulation results demonstrate that the worst case robust resource allocation design can realize the secure communications even under the imperfect CSI.Moreover,compared with other benchmark schemes,the proposed scheme can achieve secure performance improvement.展开更多
With the rapid development of artificial intelligence,the intelligence level of software is increasingly improving.Intelligent software,which is widely applied in crucial fields such as autonomous driving,intelligent ...With the rapid development of artificial intelligence,the intelligence level of software is increasingly improving.Intelligent software,which is widely applied in crucial fields such as autonomous driving,intelligent customer service,and medical diagnosis,is constructed based on complex technologies like machine learning and deep learning.Its uncertain behavior and data dependence pose unprecedented challenges to software testing.However,existing software testing courses mainly focus on conventional contents and are unable to meet the requirements of intelligent software testing.Therefore,this work deeply analyzed the relevant technologies of intelligent software testing,including reliability evaluation indicator system,neuron coverage,and test case generation.It also systematically designed an intelligent software testing course,covering teaching objectives,teaching content,teaching methods,and a teaching case.Verified by the practical teaching in four classes,this course has achieved remarkable results,providing practical experience for the reform of software testing courses.展开更多
Local resonant acoustic metamaterials have broad applications in sound insulation,yet their single-configuration designs often exhibit limited and discontinuous bandgap widths,hindering full-frequency noise attenuatio...Local resonant acoustic metamaterials have broad applications in sound insulation,yet their single-configuration designs often exhibit limited and discontinuous bandgap widths,hindering full-frequency noise attenuation across the human auditory range.This study presents a double-phase fidget-spinner-shaped acoustic metamaterial(DFAM),specifically designed to achieve an ultra-broad,low-frequency continuous bandgap by means of synergistic structural optimization,enabling effective and robust control of audible noise.Based on Bloch's theorem and the finite element method,the dispersion relation of the DFAM structure is calculated and verified by the transmission loss curves.The propagation characteristics of sound waves within the structure are further analyzed for noise frequencies that fall within the passband.The influence of the geometric and physical parameters on the bandgap is investigated,and the corresponding transmission loss in the propagation direction is further calculated.A hybrid collaborative design strategy,leveraging multi-parameter optimization and bandgap complementarity,is developed to construct a metastructure with continuous bandgap coverage from 20 Hz to 1000 Hz.The resulting metastructure demonstrates exceptional broadband noise attenuation,achieving a total bandgap width of 876.3 Hz(87.63% of the target range)with the transmission loss up to-762.78 d B in a three-periodic arrangement.The simulation and experimental results for the transmission loss of the DFAM metastructure show strong agreement in the low-frequency range.This work provides a novel framework for designing ultra-wide low-frequency continuous bandgap metastructures,offering significant potential for noise mitigation in complex environments.展开更多
In recent years,there have been fewer missions to detect neutrons in low Earth orbits(LEO),and the data obtained have been extremely limited.Studying the distribution of the neutron energy spectrum in LEO satellites t...In recent years,there have been fewer missions to detect neutrons in low Earth orbits(LEO),and the data obtained have been extremely limited.Studying the distribution of the neutron energy spectrum in LEO satellites through detection can help solve three major scientific problems:the source of particles in the inner radiation belt,information on solar-accelerated particles,and the proportion of neutrons from different sources in near-Earth space.The detection efficiency and accuracy of neutrons are affected by charged and primary particles in the environment and secondary neutrons produced by the spacecraft itself,which has been a hot research topic.The neutron spectrometer developed in this study adopts two combinations of 15 silicon detectors in terms of detector type and arrangement,which are used for neutron detection via the nuclear reaction method and recoil proton method,respectively,in which a 27μm-thick^(6)LiF conversion layer is used for thermal neutron detection up to 0.4 eV and a 300μm-thick high-density polyethylene conversion layer is used for fast-neutron detection up to 14 MeV and below.The design of the detector set can also remove the influence of primary charged particles and secondary neutrons in the detection environment to a certain extent,thereby improving the accuracy of neutron detection.In this study,the neutron spectrometer hardware,firmware,software design,and basic performance of the front-end readout chip SKIROC2A were tested.The readout circuit of each channel baseline ADC code was less than 17;thus,the channel consistency was good.The RMS noise of the channel baseline was only 7.1 mV and exhibited good stability.The maximum number of events that could be processed per second is 75.The overall power consumption was 3 W,the weight was 792 g,and the volume was less than 1 dm^(3).Furthermore,the neutron spectrometer was tested for principle and detection efficiency using various neutron sources,such as ^(241)Am-Be neutron source,2.5 MeV neutron beam,and 14 MeV neutron beam,and the experiments were analyzed with corresponding simulations.The experimental data and simulation results were in good agreement and met the design requirements.The intrinsic detection efficiency of the probes used in the neutron spectrometer was 1.05%for 14 MeV fast neutrons.展开更多
文摘The existing third-order tracker known as α-β-γ-δ filter has been used for target tracking and predicting for years. The filter can track the target＇s position and velocity, but not the acceleration. To extend its capability, a new fourth-order target tracker called α-β-γ-δ filter is proposed. The main objective of this study was to find the optimal set of filter parameters that leads to minimum position tracking errors. The tracking errors between using the α-β-γ-δ filter and the α-β-γ-δ filter are compared. As a result, the new filter exhibits significant improvement in position tracking accuracy over the existing third-order filter, but at the expense of computational time in search of the optimal filter. To reduce the computational time, a simulation-based optimization technique via Taguchi method is introduced.
文摘Objectives:The objective of this study is to evaluate the effect of simulation-based education(SBE)on the knowledge and skills of nursing students in managing childhood epileptic seizures.Materials and Methods:A quasi-experimental design was conducted among 160 third-year B.Sc.nursing students at a SUM nursing college in Bhubaneswar,India.The experimental group(n=80)participated in a structured simulation-based session,while the control group(n=80)received routine lecture-demonstration sessions.Knowledge was measured using a 20-item multiple-choice questionnaire and skills were assessed through an Objective Structured Clinical Examination checklist.Results:The experimental group demonstrated significant improvements in posttest knowledge(13.15±1.40 vs.9.56±2.10;t=11.24,P<0.001)and skill scores(17.28±1.82 vs.12.42±2.18;t=10.96,P<0.001)compared with the control group.Ranked data analysis further confirmed higher postintervention knowledge and skill levels(Z=−-6.42 and−-6.55,respectively;P<0.001).These results indicated that SBE produced substantial gains in both cognitive and psychomotor domains.Conclusion:SBE significantly enhances nursing students’knowledge and skills in managing childhood epileptic seizures compared to traditional teaching.Incorporating structured simulation modules into pediatric nursing curricula can improve clinical competence,reduce anxiety,and bolster patient safety in pediatric emergency care.
基金Supported by the MAROFF Competence Building ProjectFunded by the Research Council of Norway on "Holistic Risk-Based Design For Sustainable Arctic Sea Transport"
文摘When designing an arctic cargo ship, it is necessary to consider multiple stochastic factors. This paper evaluates the merits of a simulation-based probabilistic design method specifically developed to deal with this challenge. The outcome of the paper indicates that the incorporation of simulations and probabilistic design parameters into the design process enables more informed design decisions. For instance, it enables the assessment of the stochastic transport capacity of an arctic ship, as well as of its long-term ice exposure that can be used to determine an appropriate level of ice-strengthening. The outcome of the paper also indicates that significant gains in transport system cost-efficiency can be obtained by extending the boundaries of the design task beyond the individual vessel. In the case of industrial shipping, this allows for instance the consideration of port-based cargo storage facilities allowing for temporary shortages in transport capacity and thus a reduction in the required fleet size / ship capacity.
基金supported by Yunnan Fundamental Research Projects(No.202301AT070181)Yunnan Fundamental Research Projects(No.202401CF070126)+1 种基金Xingdian Talent Support Program of Yunnan Province(No.KKRD202203070)Yunnan High level Science and Technology Talents and Innovation Team Selection Special Project(No.202405AS350001).
文摘Fluxgate current sensors(FGCSs)are increasingly employed in power systems due to their high-precision characteristics,yet their measurement flexibility remains constrained by conventional closed-core designs.To address this limitation,we proposed a split-core sensor structure comprising four magnetic core strips,which achieved non-intrusive current measurement while maintaining detection accuracy.An analytical model of the induced electromotive force was established based on the probe’s geometric configuration,followed by finite element simulations to optimize key parameters including core radius,core width,excitation coil turns,and sensing coil configuration.A complete prototype integrating the measurement probe,excitation circuit,and signal processing circuitry was developed and experimentally validated.The experimental results show a sensitivity of 0.1099 V/A,a hysteresis error of 0.559%,and a repeatability error of 1.574%over a measurement range of±10 A.After polynomial fitting-based error compensation,the nonlinearity error was reduced to 0.208%,achieving performance comparable to closed-core sensors.This work provided a practical solution for applications demanding both high measurement accuracy and installation flexibility.
文摘Purpose-Interface management is the process of managing communications,responsibilities and coordination of project parties,phases or physical entities which are dependent on one another.Interface management is a crucial part of managing any construction project-but particularly important for high-speed railway projects that often have several contractual parties and stakeholders,very long project timelines and huge upfront cost overlays.This paper discusses how various project interfaces were managed during the design and construction of the civil engineering infrastructure for the High Speed Two(HS2)project in the United Kingdom.Design/methodology/approach-The paper uses the case study methodology.Key interfaces on the HS2 project are grouped into various categories and the paper discusses how they were managed within the Area North Integrated Project Team(IPT)of the HS2 project made up of contractor Balfour Beatty VINCI(BBV),the Mott MacDonald SYSTRA Design Joint Venture(DJV)and client HS2 Ltd.3 different case studies drawn from across the IPT are used,each of them highlighting different interfaces and how these interfaces were managed.Findings-The paper shows how innovative technical designs and modern methods of construction were used to address some of the unique and peculiar challenges of designing a brand-new railway in the United Kingdom.Addressing the contrasting and often competing requirements of different stakeholders,coupled with challenging physical constraints of the very limited land available for the project and the use of a rarely used Act of Parliament in the delivery of the project required different approach to interface management.Collaboration and proactive stakeholder engagement are necessary for successful interface management on megaprojects.The authors posit that adopting an integrated approach to engineering and construction management is an essential ingredient for the successful delivery of high-speed railway projects.Originality/value-With many high-speed railway projects around the world coming up in the next few years,understanding the context and challenges for each country will help engineering and design managers adopt appropriate approaches for their projects.The lessons learned on the HS2 project are also transferable to other mega infrastructure projects with complex project interfaces.
基金Supported by the National Key Research and Development Program of China(2023YFB4104500,2023YFB4104502)the National Natural Science Foundation of China(22138013)the Taishan Scholar Project(ts201712020).
文摘Against the backdrop of escalating global climate change and energy crises,the resource utilization of carbon dioxide(CO_(2)),a major greenhouse gas,has become a crucial pathway for achieving carbon peaking and carbon neutrality goals.The hydrogenation of CO_(2)to methanol not only enables carbon sequestration and recycling,but also provides a route to produce high value-added fuels and basic chemical feedstocks,holding significant environmental and economic potential.However,this conversion process is thermodynamically and kinetically limited,and traditional catalyst systems(e.g.,Cu/ZnO/Al_(2)O_(3))exhibit inadequate activity,selectivity,and stability under mild conditions.Therefore,the development of novel high-performance catalysts with precisely tunable structures and functionalities is imperative.Metal-organic frameworks(MOFs),as crystalline porous materials with high surface area,tunable pore structures,and diverse metal-ligand compositions,have the great potential in CO_(2)hydrogenation catalysis.Their structural design flexibility allows for the construction of well-dispersed active sites,tailored electronic environments,and enhanced metal-support interactions.This review systematically summarizes the recent advances in MOF-based and MOF-derived catalysts for CO_(2)hydrogenation to methanol,focusing on four design strategies:(1)spatial confinement and in situ construction,(2)defect engineering and ion-exchange,(3)bimetallic synergy and hybrid structure design,and(4)MOF-derived nanomaterial synthesis.These approaches significantly improve CO_(2)conversion and methanol selectivity by optimizing metal dispersion,interfacial structures,and reaction pathways.The reaction mechanism is further explored by focusing on the three main reaction pathways:the formate pathway(HCOO*),the RWGS(Reverse Water Gas Shift reaction)+CO*hydrogenation pathway,and the trans-COOH pathway.In situ spectroscopic studies and density functional theory(DFT)calculations elucidate the formation and transformation of key intermediates,as well as the roles of active sites,metal-support interfaces,oxygen vacancies,and promoters.Additionally,representative catalytic performance data for MOFbased systems are compiled and compared,demonstrating their advantages over traditional catalysts in terms of CO_(2)conversion,methanol selectivity,and space-time yield.Future perspectives for MOF-based CO_(2)hydrogenation catalysts will prioritize two main directions:structural design and mechanistic understanding.The precise construction of active sites through multi-metallic synergy,defect engineering,and interfacial electronic modulation should be made to enhance catalyst selectivity and stability.In addition,advanced in situ characterization techniques combined with theoretical modeling are essential to unravel the detailed reaction mechanisms and intermediate behaviors,thereby guiding rational catalyst design.Moreover,to enable industrial application,challenges related to thermal/hydrothermal stability,catalyst recyclability,and cost-effective large-scale synthesis must be addressed.The development of green,scalable preparation methods and the integration of MOF catalysts into practical reaction systems(e.g.,flow reactors)will be crucial for bridging the gap between laboratory research and commercial deployment.Ultimately,multi-scale structure-performance optimization and catalytic system integration will be vital for accelerating the industrialization of MOF-based CO_(2)-to-methanol technologies.
基金supported by the National Key R&D Program of China(2023YFA1507400)the National Natural Science Foundation of China(Grant No.22325805,22441010,22408203)+2 种基金Beijing Natural Science Foundation(Grant No.JQ22003)the Haihe Laboratory of Sustainable Chemical Transformations(24HHWCSS00007)Tsinghua University Dushi Program,and Sinopec Group(PR20232572).
文摘The electrochemical oxidation of biomass-derived platform molecule 5-hydroxymethylfurfural(HMF)represents a crucial pathway for green transformation into high-value chemicals,yet its reaction pathway selectivity,efficiency,and catalyst stability are strongly dependent on the electrolyte pH environment.Under alkaline conditions,high OH−concentration facilitates preferential aldehyde group oxidation and efficient deprotonation,enabling highly efficient synthesis of 2,5-furandicarboxylic acid,but simultaneously induces HMF self-degradation and complicates product separation.As pH decreases,the reaction mechanism shifts toward enhanced hydroxymethyl oxidation,leading to intermediate accumulation(such as 5-hydroxymethyl-2-furancarboxylic acid,2,5-diformylfuran,and 5-formyl-2-furancarboxylic acid)with challenging selectivity control and significantly slowed reaction kinetics.This review comprehensively examines the systematic differences in HMF oxidation pathways and surface catalytic mechanisms across the full pH range from alkaline to acidic conditions.Addressing the distinct reaction characteristics and core challenges in alkaline,near-neutral,and acidic media,we systematically evaluate design strategies for high-efficiency electrocatalysts and explore reactor design aspects.Future research should focus on process integration(with tailored reactor design)for energy consumption reduction in alkaline systems,targeted synthesis of diverse oxidation products in near-neutral systems,and innovative catalyst development for acidic systems,thereby advancing the efficiency,selectivity,and practical application of HMF electrooxidation technologies across the entire pH spectrum through synergistic optimization of catalyst,reactor,and process.
基金supported by the National Key R&D Project from the Minister of Science and Technology(2024YFA1211500)the National Natural Science Foundation of China(Grant Nos.62304130,62405158 and 62574123)+1 种基金the Shanghai youth science and technology star project(24QA2702800)Shanghai Key Laboratory of Chips and Systems for Intelligent Connected Vehicle。
文摘Memristors have emerged as a transformative technology in the realm of electronic devices,offering unique advantages such as fast switching speeds,low power consumption,and the ability to sensor-memory-compute.The applications span across non-volatile memory,neuromorphic computing,hardware security,and beyond,prompting memristors to become a versatile solution for next-generation computing and data storage systems.Despite enormous potential of memristors,the transition from laboratory prototypes to large-scale applications is challenging in terms of material stability,device reproducibility,and array scalability.This review systematically explores recent advancements in high-performance memristor technologies,focusing on performance enhancement strategies through material engineering,structural design,pulse protocol optimization,and algorithm control.We provide an in-depth analysis of key performance metrics tailored to specific applications,including non-volatile memory,neuromorphic computing,and hardware security.Furthermore,we propose a co-design framework that integrates device-level optimizations with operational-level improvements,aiming to bridge the gap between theoretical models and practical implementations.
文摘Compact size,high brightness,and wide field of view(FOV)are key requirements for long-wave infrared imagers used in military surveillance or night navigation.However,to meet the imaging requirements of high resolution and wide FOV,infrared optical systems often adopt complex optical lens groups,which will increase the size and weight of the optical system.In this paper,a strategy based on wavefront coding(WFC)is proposed to design a compact wide-FOV infrared imager.A cubic phase mask is inserted into the pupil plane of the infrared imager to correct the aberration.The simulated results show that,the WFC infrared imager has good imaging quality in a wide FOV of±16°.In addition,the WFC infrared imager achieves compactness with its 40 mm×40 mm×40 mm size.A fast focal ratio of 1 combined with an entrance pupil diameter of 25 mm ensures brightness.This work is of significance for designing a compact wide-FOV infrared imager.
基金sponsored by the National Key Scientific Instrument and Equipment Development Projects of China(Grant No.62027823)the National Natural Science Foun-dation of China(Grant No.61775048).
文摘In recent years,the use of deep learning to replace traditional numerical methods for electromagnetic propagation has shown tremendous potential in the rapid design of photonic devices.However,most research on deep learning has focused on single-layer grating couplers,and the accuracy of multi-layer grating couplers has not yet reached a high level.This paper proposes and demonstrates a novel deep learning network-assisted strategy for inverse design.The network model is based on a multi-layer perceptron(MLP)and incorporates convolutional neural networks(CNNs)and transformers.Through the stacking of multiple layers,it achieves a high-precision design for both multi-layer and single-layer raster couplers with various functionalities.The deep learning network exhibits exceptionally high predictive accuracy,with an average absolute error across the full wavelength range of 1300–1700 nm being only 0.17%,and an even lower predictive absolute error below 0.09%at the specific wavelength of 1550 nm.By combining the deep learning network with the genetic algorithm,we can efficiently design grating couplers that perform different functions.Simulation results indicate that the designed single-wavelength grating couplers achieve coupling efficiencies exceeding 80%at central wavelengths of 1550 nm and 1310 nm.The performance of designed dual-wavelength and broadband grating couplers also reaches high industry standards.Furthermore,the network structure and inverse design method are highly scalable and can be applied not only to multi-layer grating couplers but also directly to the prediction and design of single-layer grating couplers,providing a new perspective for the innovative development of photonic devices.
基金the financial supports from National Key R&D Program for Young Scientists of China(Grant No.2022YFC3080900)National Natural Science Foundation of China(Grant No.52374181)+1 种基金BIT Research and Innovation Promoting Project(Grant No.2024YCXZ017)supported by Science and Technology Innovation Program of Beijing institute of technology under Grant No.2022CX01025。
文摘In this study,an inverse design framework was established to find lightweight honeycomb structures(HCSs)with high impact resistance.The hybrid HCS,composed of re-entrant(RE)and elliptical annular re-entrant(EARE)honeycomb cells,was created by constructing arrangement matrices to achieve structural lightweight.The machine learning(ML)framework consisted of a neural network(NN)forward regression model for predicting impact resistance and a multi-objective optimization algorithm for generating high-performance designs.The surrogate of the local design space was initially realized by establishing the NN in the small sample dataset,and the active learning strategy was used to continuously extended the local optimal design until the model converged in the global space.The results indicated that the active learning strategy significantly improved the inference capability of the NN model in unknown design domains.By guiding the iteration direction of the optimization algorithm,lightweight designs with high impact resistance were identified.The energy absorption capacity of the optimal design reached 94.98%of the EARE honeycomb,while the initial peak stress and mass decreased by 28.85%and 19.91%,respectively.Furthermore,Shapley Additive Explanations(SHAP)for global explanation of the NN indicated a strong correlation between the arrangement mode of HCS and its impact resistance.By reducing the stiffness of the cells at the top boundary of the structure,the initial impact damage sustained by the structure can be significantly improved.Overall,this study proposed a general lightweight design method for array structures under impact loads,which is beneficial for the widespread application of honeycomb-based protective structures.
基金the National Natural Science Foundation of China(Grant No.32371823)the Liaoning Province Xingliao Talents Leading Talent Program(Grant No.XLYC2402043)the Open Foundation of State Key Laboratory of Woody Oil Resources Utilization(Grant No.SKLN EFU202517).
文摘Cellulose,the dominant natural polymer on Earth,features a distinct molecular structure with extraordinary mechanical properties and tunable characteristics,making it attractive for gel systems.Although significant progress has been made,challenges remain in fully leveraging their functional potential and broadening practical applications.This review systematically examines the properties of cellulose and cellulose gels,exploring novel reinforcement strategies—across molecular,supramolecular network,and macroscale structure levels—to enhance mechanical,electrical,and thermal performance,while coordinating these properties for practical implementations.These advancements are exemplified in emerging fields such as flexible robotics,electronic skins,flexible energy storage devices,and human-machine interaction systems.This article thoroughly investigates the fundamental characteristics,multi-scale design approaches,performance enhancement mechanisms,and cutting-edge implementations of cellulose-based gels across diverse domains.It provides a comprehensive overview of these advanced materials and offers strategic insights and recommendations for future research and innovation.
基金National Key R&D Program of China under Grant 2020YFB1807602the National Natural Science Foundation of China under Grant 62222107,Grant 62071223,Grant 62031012Young Elite Scientist Sponsorship Program by CAST。
文摘Cognitive unmanned aerial vehicle(UAV)is promising to tackle the spectrum scarcity problem faced by UAV communications.However,the secure information transmission is challenging due to the open nature of the spectrum sharing.In order to tackle this issue,a cognitive UAV network with cooperative jamming is studied in this paper.A robust resource allocation and trajectory joint optimization problem is formulated by considering the practical case that the channel state information(CSI)cannot be accurately obtained.An iterative algorithm is proposed to address this challenging non-convex problem.Simulation results demonstrate that the worst case robust resource allocation design can realize the secure communications even under the imperfect CSI.Moreover,compared with other benchmark schemes,the proposed scheme can achieve secure performance improvement.
基金Computer Basic Education Teaching Research Project of Association of Fundamental Computing Education in Chinese Universities(Nos.2025-AFCEC-527 and 2024-AFCEC-088)Research on the Reform of Public Course Teaching at Nantong College of Science and Technology(No.2024JGG015).
文摘With the rapid development of artificial intelligence,the intelligence level of software is increasingly improving.Intelligent software,which is widely applied in crucial fields such as autonomous driving,intelligent customer service,and medical diagnosis,is constructed based on complex technologies like machine learning and deep learning.Its uncertain behavior and data dependence pose unprecedented challenges to software testing.However,existing software testing courses mainly focus on conventional contents and are unable to meet the requirements of intelligent software testing.Therefore,this work deeply analyzed the relevant technologies of intelligent software testing,including reliability evaluation indicator system,neuron coverage,and test case generation.It also systematically designed an intelligent software testing course,covering teaching objectives,teaching content,teaching methods,and a teaching case.Verified by the practical teaching in four classes,this course has achieved remarkable results,providing practical experience for the reform of software testing courses.
基金Project supported by the National Natural Science Foundation of China(No.12572020)the Key Project of Natural Science Foundation of Hebei Province of China(No.A2023210064)。
文摘Local resonant acoustic metamaterials have broad applications in sound insulation,yet their single-configuration designs often exhibit limited and discontinuous bandgap widths,hindering full-frequency noise attenuation across the human auditory range.This study presents a double-phase fidget-spinner-shaped acoustic metamaterial(DFAM),specifically designed to achieve an ultra-broad,low-frequency continuous bandgap by means of synergistic structural optimization,enabling effective and robust control of audible noise.Based on Bloch's theorem and the finite element method,the dispersion relation of the DFAM structure is calculated and verified by the transmission loss curves.The propagation characteristics of sound waves within the structure are further analyzed for noise frequencies that fall within the passband.The influence of the geometric and physical parameters on the bandgap is investigated,and the corresponding transmission loss in the propagation direction is further calculated.A hybrid collaborative design strategy,leveraging multi-parameter optimization and bandgap complementarity,is developed to construct a metastructure with continuous bandgap coverage from 20 Hz to 1000 Hz.The resulting metastructure demonstrates exceptional broadband noise attenuation,achieving a total bandgap width of 876.3 Hz(87.63% of the target range)with the transmission loss up to-762.78 d B in a three-periodic arrangement.The simulation and experimental results for the transmission loss of the DFAM metastructure show strong agreement in the low-frequency range.This work provides a novel framework for designing ultra-wide low-frequency continuous bandgap metastructures,offering significant potential for noise mitigation in complex environments.
基金supported by the National Natural Science Foundation of China(NSFC)(Nos.42225405 and U2106202)。
文摘In recent years,there have been fewer missions to detect neutrons in low Earth orbits(LEO),and the data obtained have been extremely limited.Studying the distribution of the neutron energy spectrum in LEO satellites through detection can help solve three major scientific problems:the source of particles in the inner radiation belt,information on solar-accelerated particles,and the proportion of neutrons from different sources in near-Earth space.The detection efficiency and accuracy of neutrons are affected by charged and primary particles in the environment and secondary neutrons produced by the spacecraft itself,which has been a hot research topic.The neutron spectrometer developed in this study adopts two combinations of 15 silicon detectors in terms of detector type and arrangement,which are used for neutron detection via the nuclear reaction method and recoil proton method,respectively,in which a 27μm-thick^(6)LiF conversion layer is used for thermal neutron detection up to 0.4 eV and a 300μm-thick high-density polyethylene conversion layer is used for fast-neutron detection up to 14 MeV and below.The design of the detector set can also remove the influence of primary charged particles and secondary neutrons in the detection environment to a certain extent,thereby improving the accuracy of neutron detection.In this study,the neutron spectrometer hardware,firmware,software design,and basic performance of the front-end readout chip SKIROC2A were tested.The readout circuit of each channel baseline ADC code was less than 17;thus,the channel consistency was good.The RMS noise of the channel baseline was only 7.1 mV and exhibited good stability.The maximum number of events that could be processed per second is 75.The overall power consumption was 3 W,the weight was 792 g,and the volume was less than 1 dm^(3).Furthermore,the neutron spectrometer was tested for principle and detection efficiency using various neutron sources,such as ^(241)Am-Be neutron source,2.5 MeV neutron beam,and 14 MeV neutron beam,and the experiments were analyzed with corresponding simulations.The experimental data and simulation results were in good agreement and met the design requirements.The intrinsic detection efficiency of the probes used in the neutron spectrometer was 1.05%for 14 MeV fast neutrons.
