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
In order to enhance the dynamic control precision of inertial stabilization platform(ISP),a disturbance sliding mode observer(DSMO)is proposed in this paper suppressing disturbance torques inherent within the system.T...In order to enhance the dynamic control precision of inertial stabilization platform(ISP),a disturbance sliding mode observer(DSMO)is proposed in this paper suppressing disturbance torques inherent within the system.The control accuracy of ISP is fundamentally circumscribed by various disturbance torques in rotating shaft.Therefore,a dynamic model of ISP incorporating composite perturbations is established with regard to the stabilization of axis in the inertial reference frame.Subsequently,an online estimator for control loop uncertainties based on the sliding mode control algorithm is designed to estimate the aggregate disturbances of various parameters uncertainties and other unmodeled disturbances that cannot be accurately calibrated.Finally,the proposed DSMO is integrated into a classical proportional-integral-derivative(PID)control scheme,utilizing feedforward approach to compensate the composite disturbance in the control loop online.The effectiveness of the proposed disturbance observer is validated through simulation and hardware experimentation,demonstrating a significant improvement in the dynamic control performance and robustness of the classical PID controller extensively utilized in the field of engineering.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
In mixture experiments,the observed response is determined by the relative proportions of the components,consequently rendering the experimental region a simplex.This paper focuses primarily on the optimal designs of ...In mixture experiments,the observed response is determined by the relative proportions of the components,consequently rendering the experimental region a simplex.This paper focuses primarily on the optimal designs of mixture experiments that involve process variables.Prior research has extensively delved into optimal orthogonal block designs for some classic mixture models with process variables.Based on the framework of general blending models,this paper proposes a class of symmetric linear mixture models,which can be regarded as a generalization of many existing ones.Under the orthogonal blocking conditions,orthogonal block designs are devised through Latin squares in the presence of process variables.TheD-,A-,and E-optimality criteria are utilized to obtain optimal designs at the boundary of the simplex in the case of 3 components.As the values of the exponents change,numerically derived optimal design points are presented to illustrate the pattern of their variations,and to verify the consistency of the results with previous research on some specific symmetric general blending models.展开更多
The objective of the current study is to investigate an adaptive predictive observer-based autopilot for a skid-to-turn(STT)missile model with uncertainties and unknown dynamic equations.A predictive control for the S...The objective of the current study is to investigate an adaptive predictive observer-based autopilot for a skid-to-turn(STT)missile model with uncertainties and unknown dynamic equations.A predictive control for the STT missile is designed based on nonlinear model predictive control(NMPC)using Taylor series expansion,after which,via a neural network(NN),unknown functions are approximated.The present study also evaluates an adaptive optimal observer of a new strategy-based nonlinear system.Specifically,to estimate the missile states such as normal acceleration and its derivatives for the future,originally the Taylor series states expansion was gained to any specified order,based on their receding horizons.To address the problem of prediction error,an analytic solution was prepared that led to a closed form regarding the nonlinear optimal observer.Out of the gains resulting from the analytic solution,as developed for the problem of prediction error,the selection of the proposed observer gain was optimally conducted to meet the stability condition.Thus,combining the adaptive predictive autopilot and the adaptive optimal observer scheme was implemented to secure the performance,which needed only estimated normal acceleration and its derivatives.Meanwhile,no angular velocity measurement or wind angle estimation was required.Ultimately,the proposed technique was found effective,as confirmed by the qualitative simulation results.展开更多
In this paper,we provide a comprehensive examination of the evolution of graphics Application Programming Interfaces(APIs).We begin by exploring traditional graphics APIs,elucidating their distinct features and inhere...In this paper,we provide a comprehensive examination of the evolution of graphics Application Programming Interfaces(APIs).We begin by exploring traditional graphics APIs,elucidating their distinct features and inherent challenges.This sets the stage for a detailed exploration of modern graphics APIs,with a focus on four critical design principles.These principles are further analyzed through specific case studies and categorical examinations.The paper then introduces MoerEngine,a bespoke rendering engine,as a practical case to demonstrate the real-world application of these modern principles in software engineering.In conclusion,the study offers insights into the potential future trajectory of graphics APIs,spotlighting emerging design patterns and technological innovations.It also ventures to predict the development trends and capabilities of next-generation graphics APIs.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
This paper investigates the consensus tracking control problem for high order nonlinear multi-agent systems subject to non-affine faults,partial measurable states,uncertain control coefficients,and unknown external di...This paper investigates the consensus tracking control problem for high order nonlinear multi-agent systems subject to non-affine faults,partial measurable states,uncertain control coefficients,and unknown external disturbances.Under the directed topology conditions,an observer-based finite-time control strategy based on adaptive backstepping and is proposed,in which a neural network-based state observer is employed to approximate the unmeasurable system state variables.To address the complexity explosion problem associated with the backstepping method,a finite-time command filter is incorporated,with error compensation signals designed to mitigate the filter-induced errors.Additionally,the Butterworth low-pass filter is introduced to avoid the algebraic ring problem in the design of the controller.The finite-time stability of the closed-loop system is rigorously analyzed with the finite-time Lyapunov stability criterion,validating that all closed-loop signals of the system remain bounded within a finite time.Finally,the effectiveness of the proposed control strategy is verified through a simulation example.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
Both large-scale prospective randomized controlled trials(RCTs)and smaller investigator-initiated trials are essential for evaluating the efficacy and safety of medical interventions.Robust protocols and statistical d...Both large-scale prospective randomized controlled trials(RCTs)and smaller investigator-initiated trials are essential for evaluating the efficacy and safety of medical interventions.Robust protocols and statistical designs ensure the reliability of trial outcomes and improve the credibility of research findings.By reviewing the statistical approaches used in the TORCHLIGHT,NCC2167,and NeoTENNIS trials,this article illustrates the principles underlying large-sample confirmatory RCTs,small-sample exploratory adaptive designs,and single-arm two-stage designs.This discussion is aimed at helping researchers apply these design methods more effectively,to increase the likelihood of success in clinical studies.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
High-entropy materials(HEMs)have attracted extensive attention in the field of electrocatalysis due to their high performance enabled by their multi-component,tunable structural characteristics and excellent stability...High-entropy materials(HEMs)have attracted extensive attention in the field of electrocatalysis due to their high performance enabled by their multi-component,tunable structural characteristics and excellent stability.HEMs are usually composed of five or more metal elements,and have core advantages such as high configurational entropy,lattice distortion and multi-element synergistic effect,which provide new possibilities for composition regulation and performance optimization of catalysts.Especially at the nanoscale,HEMs show a larger specific surface area,abundant active sites and higher catalytic reaction efficiency,further expanding their application potential in electrochemical reactions.This paper systematically reviews the classification,structure construction and regulation strategies of HEMs,and focuses on their research progress in critical electrocatalytic reactions including water splitting(HER,OER),hydrogen oxidation(HOR),oxygen reduction(ORR),carbon dioxide reduction(CO_(2)RR),nitrate reduction(NO_(3)-RR)and electrooxidation of organics(EOO).In addition,the preparation methods of HEMs,the structure-performance relationship and the entropy regulation mechanism in the catalytic process are analyzed.Finally,this paper proposes the key challenges currently faced by HEMs in electrocatalytic applications and looks forward to their future development direction,providing a theoretical basis and design ideas for building a new generation of efficient and sustainable electrocatalysts.展开更多
All-soluble all-iron flow batteries are considered a promising technology for low-cost and large-scale energy storage.In the past few years,efforts have been taken to design various iron chelates to enhance the cyclin...All-soluble all-iron flow batteries are considered a promising technology for low-cost and large-scale energy storage.In the past few years,efforts have been taken to design various iron chelates to enhance the cycling stability of negative electrolytes,while ignoring the kinetic mismatch and the corresponding battery design strategies,which greatly limited the performance of all-soluble all-iron flow batteries.In this regard,combining experimental analysis and numerical simulation,this work analyzed the kinetic performance of iron chelates on the negative side and conducted further investigations on battery asymmetric structure design to balance mass transport and electrochemical reactions within the battery.Results show that the reaction rate constant of the Fe(Ⅱ)(BIS-TRIS)^(2-)/Fe(Ⅲ)(BIS-TRIS)^(-)redox couple is 1:48×10^(-5)cm s^(-1),significantly lower than that of the positive electrolyte(6.0×10^(-5)cm s^(−1)),which limits the performance of the battery.Utilizing an asymmetric electrode design to increase active reaction sites and enhance convection is a critical strategy in achieving balanced mass transport and reaction activity between the positive and negative electrolytes.More notably,the battery with asymmetric geometric characteristics demonstrates a remarkable energy efficiency reaching up to 80.17%at 80 mA cm^(−2),which is 7.95%higher than that of the symmetric structure.This research provides theoretical guidance for the structural design of key components of batteries and reduces the cost of trial and error.展开更多
This paper investigates the adaptive optimal tracking control(AOTC)for underactuated surface vessels(USVs).Compared to the majority of existing studies,the control strategy in this paper innovatively combines an exten...This paper investigates the adaptive optimal tracking control(AOTC)for underactuated surface vessels(USVs).Compared to the majority of existing studies,the control strategy in this paper innovatively combines an extended state observer(ESO)with reinforcement learning(RL).The designed ESO has high estimation accuracy and robust disturbance rejection capabilities for the unmeasurable information for USVs.To obtain the AOTC,the actor–critic(AC)networks based on RL are constructed to solve the Hamilton–Jacobi–Bellman(HJB)equations.Due to the uncertainties,it is challenging to obtain the optimal controller by directly solving the HJB equations.To address this issue,this paper employs neural networks(NNs)to approximate the uncertainties and solves the optimal controller via AC-RL and ESO.In addition,the adaptive parameters of the optimal controller is trained in parallel with AC networks,which can ensure that the trained networks can further improve tracking performance.The boundedness of AOTC for USVs is shown by Lyapunov stability theorem.Finally,simulation results demonstrate the effectiveness of the proposed algorithm.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
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supported by the National Natural Science Foundation of China(61803015).
文摘In order to enhance the dynamic control precision of inertial stabilization platform(ISP),a disturbance sliding mode observer(DSMO)is proposed in this paper suppressing disturbance torques inherent within the system.The control accuracy of ISP is fundamentally circumscribed by various disturbance torques in rotating shaft.Therefore,a dynamic model of ISP incorporating composite perturbations is established with regard to the stabilization of axis in the inertial reference frame.Subsequently,an online estimator for control loop uncertainties based on the sliding mode control algorithm is designed to estimate the aggregate disturbances of various parameters uncertainties and other unmodeled disturbances that cannot be accurately calibrated.Finally,the proposed DSMO is integrated into a classical proportional-integral-derivative(PID)control scheme,utilizing feedforward approach to compensate the composite disturbance in the control loop online.The effectiveness of the proposed disturbance observer is validated through simulation and hardware experimentation,demonstrating a significant improvement in the dynamic control performance and robustness of the classical PID controller extensively utilized in the field of engineering.
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 Natural Science Foundation of China[grant numbers 12071329,12471246].
文摘In mixture experiments,the observed response is determined by the relative proportions of the components,consequently rendering the experimental region a simplex.This paper focuses primarily on the optimal designs of mixture experiments that involve process variables.Prior research has extensively delved into optimal orthogonal block designs for some classic mixture models with process variables.Based on the framework of general blending models,this paper proposes a class of symmetric linear mixture models,which can be regarded as a generalization of many existing ones.Under the orthogonal blocking conditions,orthogonal block designs are devised through Latin squares in the presence of process variables.TheD-,A-,and E-optimality criteria are utilized to obtain optimal designs at the boundary of the simplex in the case of 3 components.As the values of the exponents change,numerically derived optimal design points are presented to illustrate the pattern of their variations,and to verify the consistency of the results with previous research on some specific symmetric general blending models.
文摘The objective of the current study is to investigate an adaptive predictive observer-based autopilot for a skid-to-turn(STT)missile model with uncertainties and unknown dynamic equations.A predictive control for the STT missile is designed based on nonlinear model predictive control(NMPC)using Taylor series expansion,after which,via a neural network(NN),unknown functions are approximated.The present study also evaluates an adaptive optimal observer of a new strategy-based nonlinear system.Specifically,to estimate the missile states such as normal acceleration and its derivatives for the future,originally the Taylor series states expansion was gained to any specified order,based on their receding horizons.To address the problem of prediction error,an analytic solution was prepared that led to a closed form regarding the nonlinear optimal observer.Out of the gains resulting from the analytic solution,as developed for the problem of prediction error,the selection of the proposed observer gain was optimally conducted to meet the stability condition.Thus,combining the adaptive predictive autopilot and the adaptive optimal observer scheme was implemented to secure the performance,which needed only estimated normal acceleration and its derivatives.Meanwhile,no angular velocity measurement or wind angle estimation was required.Ultimately,the proposed technique was found effective,as confirmed by the qualitative simulation results.
基金supported by ZTE Industry-University-Institute Cooperation Funds under Grant No.IA20230921014。
文摘In this paper,we provide a comprehensive examination of the evolution of graphics Application Programming Interfaces(APIs).We begin by exploring traditional graphics APIs,elucidating their distinct features and inherent challenges.This sets the stage for a detailed exploration of modern graphics APIs,with a focus on four critical design principles.These principles are further analyzed through specific case studies and categorical examinations.The paper then introduces MoerEngine,a bespoke rendering engine,as a practical case to demonstrate the real-world application of these modern principles in software engineering.In conclusion,the study offers insights into the potential future trajectory of graphics APIs,spotlighting emerging design patterns and technological innovations.It also ventures to predict the development trends and capabilities of next-generation graphics APIs.
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.
基金supported in part by the Beijing Natural Science Foundation under Grant 4252050in part by the National Science Fund for Distinguished Young Scholars under Grant 62425304in part by the Basic Science Center Programs of NSFC under Grant 62088101.
文摘This paper investigates the consensus tracking control problem for high order nonlinear multi-agent systems subject to non-affine faults,partial measurable states,uncertain control coefficients,and unknown external disturbances.Under the directed topology conditions,an observer-based finite-time control strategy based on adaptive backstepping and is proposed,in which a neural network-based state observer is employed to approximate the unmeasurable system state variables.To address the complexity explosion problem associated with the backstepping method,a finite-time command filter is incorporated,with error compensation signals designed to mitigate the filter-induced errors.Additionally,the Butterworth low-pass filter is introduced to avoid the algebraic ring problem in the design of the controller.The finite-time stability of the closed-loop system is rigorously analyzed with the finite-time Lyapunov stability criterion,validating that all closed-loop signals of the system remain bounded within a finite time.Finally,the effectiveness of the proposed control strategy is verified through a simulation example.
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supported by a grant from the National Science and Technology Major Project(Grant No.2024ZD0519800).
文摘Both large-scale prospective randomized controlled trials(RCTs)and smaller investigator-initiated trials are essential for evaluating the efficacy and safety of medical interventions.Robust protocols and statistical designs ensure the reliability of trial outcomes and improve the credibility of research findings.By reviewing the statistical approaches used in the TORCHLIGHT,NCC2167,and NeoTENNIS trials,this article illustrates the principles underlying large-sample confirmatory RCTs,small-sample exploratory adaptive designs,and single-arm two-stage designs.This discussion is aimed at helping researchers apply these design methods more effectively,to increase the likelihood of success in clinical studies.
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supported by the National Natural Science Foundation of China(22378247 and 22078187)China-CEEC University Joint Education Project(2021099)+1 种基金the International Joint Research Center for Biomass Chemistry and Materials,the Shaanxi International Science and Technology Cooperation Base(2018GHJD-19)Ning Wei and Xue Yao are grateful to Innovative Talents International Cooperative Training Project from China Scholarship Council(Grant No.202310470014 and 202310470013).
文摘High-entropy materials(HEMs)have attracted extensive attention in the field of electrocatalysis due to their high performance enabled by their multi-component,tunable structural characteristics and excellent stability.HEMs are usually composed of five or more metal elements,and have core advantages such as high configurational entropy,lattice distortion and multi-element synergistic effect,which provide new possibilities for composition regulation and performance optimization of catalysts.Especially at the nanoscale,HEMs show a larger specific surface area,abundant active sites and higher catalytic reaction efficiency,further expanding their application potential in electrochemical reactions.This paper systematically reviews the classification,structure construction and regulation strategies of HEMs,and focuses on their research progress in critical electrocatalytic reactions including water splitting(HER,OER),hydrogen oxidation(HOR),oxygen reduction(ORR),carbon dioxide reduction(CO_(2)RR),nitrate reduction(NO_(3)-RR)and electrooxidation of organics(EOO).In addition,the preparation methods of HEMs,the structure-performance relationship and the entropy regulation mechanism in the catalytic process are analyzed.Finally,this paper proposes the key challenges currently faced by HEMs in electrocatalytic applications and looks forward to their future development direction,providing a theoretical basis and design ideas for building a new generation of efficient and sustainable electrocatalysts.
基金supported by the National Natural Science Foundation of China(No.52106265)Natural Science Foundation of Tianjin Province,China(No.23JCZDJC01090)+1 种基金Guangdong Major Project of Basic and Applied Basic Research(2023B0303000002)High level of special funds(G03034K001).
文摘All-soluble all-iron flow batteries are considered a promising technology for low-cost and large-scale energy storage.In the past few years,efforts have been taken to design various iron chelates to enhance the cycling stability of negative electrolytes,while ignoring the kinetic mismatch and the corresponding battery design strategies,which greatly limited the performance of all-soluble all-iron flow batteries.In this regard,combining experimental analysis and numerical simulation,this work analyzed the kinetic performance of iron chelates on the negative side and conducted further investigations on battery asymmetric structure design to balance mass transport and electrochemical reactions within the battery.Results show that the reaction rate constant of the Fe(Ⅱ)(BIS-TRIS)^(2-)/Fe(Ⅲ)(BIS-TRIS)^(-)redox couple is 1:48×10^(-5)cm s^(-1),significantly lower than that of the positive electrolyte(6.0×10^(-5)cm s^(−1)),which limits the performance of the battery.Utilizing an asymmetric electrode design to increase active reaction sites and enhance convection is a critical strategy in achieving balanced mass transport and reaction activity between the positive and negative electrolytes.More notably,the battery with asymmetric geometric characteristics demonstrates a remarkable energy efficiency reaching up to 80.17%at 80 mA cm^(−2),which is 7.95%higher than that of the symmetric structure.This research provides theoretical guidance for the structural design of key components of batteries and reduces the cost of trial and error.
基金supported by the National Natural Science Foundation of China under Grants 62203338,62173259 and U1913602Zhejiang Provincial Natural Science Foundation of China under Grant LZ24F0390006the Postdoctoral Science Foundation of China under Grant 2022M722485.
文摘This paper investigates the adaptive optimal tracking control(AOTC)for underactuated surface vessels(USVs).Compared to the majority of existing studies,the control strategy in this paper innovatively combines an extended state observer(ESO)with reinforcement learning(RL).The designed ESO has high estimation accuracy and robust disturbance rejection capabilities for the unmeasurable information for USVs.To obtain the AOTC,the actor–critic(AC)networks based on RL are constructed to solve the Hamilton–Jacobi–Bellman(HJB)equations.Due to the uncertainties,it is challenging to obtain the optimal controller by directly solving the HJB equations.To address this issue,this paper employs neural networks(NNs)to approximate the uncertainties and solves the optimal controller via AC-RL and ESO.In addition,the adaptive parameters of the optimal controller is trained in parallel with AC networks,which can ensure that the trained networks can further improve tracking performance.The boundedness of AOTC for USVs is shown by Lyapunov stability theorem.Finally,simulation results demonstrate the effectiveness of the proposed algorithm.
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.
