This work was focused on the model-based design method of two-axis four-actuator(TAFA) fast steering mirror system(FSM), in order to improve the design efficiency. The structure and operation principle commonality of ...This work was focused on the model-based design method of two-axis four-actuator(TAFA) fast steering mirror system(FSM), in order to improve the design efficiency. The structure and operation principle commonality of normal TAFA FSM were investigated. Based on the structure and the commonality, the conditions of single-axis idea, high-frequency resonance and coupling were modeled gradually. Combining these models, a holonomic system model was established to reflect and predict the performance of TAFA FSM. A model-based design method was proposed based on the holonomic system model. The design flow and design concept of the method were described. In accordance with the method, a TAFA FSM was designed. Simulations and experiments of the FSM were done, and the results of them were compared. The compared results indicate that the holonomic system model can well reflect and predict the performance of TAFA FSM. The bandwidth of TAFA FSM is more than 250 Hz; adjust time is less than 15 ms;overshoot is less than 8%; position accuracy is better than 10 μrad; the FSM prototype can satisfy the requirements.展开更多
This paper presents a Model-Based Design(MBD)approach for the design and control of a customized manipulator intended for drilling and position-ing of dental implants accurately with minimal human intervention.While p...This paper presents a Model-Based Design(MBD)approach for the design and control of a customized manipulator intended for drilling and position-ing of dental implants accurately with minimal human intervention.While performing an intra-oral surgery for a prolonged duration within a limited oral cavity,the tremor of dentist's hand is inevitable.As a result,wielding the drilling tool and inserting the dental implants safely in accurate position and orientation is highly challenging even for experienced dentists.Therefore,we introduce a customized manipulator that is designed ergonomically by taking in to account the dental chair specifications and anthropomorphic data such that it can be readily mounted onto the existing dental chair.The manipulator can be used to drill holes for dental inserts and position them with improved accuracy and safety.Further-more,a thorough multi-body motion analysis of the manipulator was carried out by creating a virtual prototype of the manipulator and simulating its controlled movements in various scenarios.The overall design was prepared and validated in simulation using Solid works,MATLAB and Simulink through Model Based Design(MBD)approach.The motion simulation results indicate that the manipulator could be built as a prototype readily.展开更多
For several years now, electric vehicles (EVs) have been expected to become widely available in the micro-mobility field. However, the insufficiency of such vehicles’ battery-charging and discharging performance has ...For several years now, electric vehicles (EVs) have been expected to become widely available in the micro-mobility field. However, the insufficiency of such vehicles’ battery-charging and discharging performance has limited their practical use. A hybrid energy storage system, which comprises a capacitor and battery, is a promising solution to this problem;however, to apply model-based designs, which are indispensable to embedded systems, such as the electronic control units used in EVs, a simple and accurate capacitor model is required. Within this framework, a lithium-ion capacitor (LIC) model is proposed, and its charging and discharging performances are evaluated against an actual LIC. The model corresponds accurately to the actual LIC, and the results indicate that the proposed LIC model will work well when used with Model-Based Design (MBD).展开更多
Unlike traditional propeller-driven underwater vehicles,blended-wing-body underwater gliders(BWBUGs)achieve zigzag gliding through periodic adjustments of their net buoyancy,enhancing their cruising capabilities while...Unlike traditional propeller-driven underwater vehicles,blended-wing-body underwater gliders(BWBUGs)achieve zigzag gliding through periodic adjustments of their net buoyancy,enhancing their cruising capabilities while mini-mizing energy consumption.However,enhancing gliding performance is challenging due to the complex system design and limited design experience.To address this challenge,this paper introduces a model-based,multidisciplinary system design optimization method for BWBUGs at the conceptual design stage.First,a model-based,multidisciplinary co-simulation design framework is established to evaluate both system-level and disciplinary indices of BWBUG performance.A data-driven,many-objective multidisciplinary optimization is subsequently employed to explore the design space,yielding 32 Pareto optimal solutions.Finally,a model-based physical system simulation,which represents the design with the largest hyper-volume contribution among the 32 final designs,is established.Its gliding perfor-mance,validated by component behavior,lays the groundwork for constructing the entire system’s digital prototype.In conclusion,this model-based,multidisciplinary design optimization method effectively generates design schemes for innovative underwater vehicles,facilitating the development of digital prototypes.展开更多
Cobalt phosphide has been successfully used as a catalyst in the production of ammonia from nitric acid.Substituting appropriate atoms is expected to further improve its catalytic performance.Owing to the diversity of...Cobalt phosphide has been successfully used as a catalyst in the production of ammonia from nitric acid.Substituting appropriate atoms is expected to further improve its catalytic performance.Owing to the diversity of substituting elements,substitution sites,adsorption sites,and adsorption configurations,extensive time-consuming simulation calculations are required for the high-throughput screening method.Additionally,multi-objective attributes should be considered simultaneously in catalytic design.To tackle this challenge,this paper suggests a multi-objective cobalt phosphide catalytic material design method based on surrogate models.And the effectiveness of the proposed method was validated through comparative experiments.The proposed method led to the discovery of fifteen promising cobalt phosphide catalyst configurations.This study provides a new avenue for expediting the design of catalyst,with the potential for application in other systems.展开更多
High fidelity analysis are utilized in modern engineering design optimization problems which involve expensive black-box models.For computation-intensive engineering design problems,efficient global optimization metho...High fidelity analysis are utilized in modern engineering design optimization problems which involve expensive black-box models.For computation-intensive engineering design problems,efficient global optimization methods must be developed to relieve the computational burden.A new metamodel-based global optimization method using fuzzy clustering for design space reduction(MGO-FCR) is presented.The uniformly distributed initial sample points are generated by Latin hypercube design to construct the radial basis function metamodel,whose accuracy is improved with increasing number of sample points gradually.Fuzzy c-mean method and Gath-Geva clustering method are applied to divide the design space into several small interesting cluster spaces for low and high dimensional problems respectively.Modeling efficiency and accuracy are directly related to the design space,so unconcerned spaces are eliminated by the proposed reduction principle and two pseudo reduction algorithms.The reduction principle is developed to determine whether the current design space should be reduced and which space is eliminated.The first pseudo reduction algorithm improves the speed of clustering,while the second pseudo reduction algorithm ensures the design space to be reduced.Through several numerical benchmark functions,comparative studies with adaptive response surface method,approximated unimodal region elimination method and mode-pursuing sampling are carried out.The optimization results reveal that this method captures the real global optimum for all the numerical benchmark functions.And the number of function evaluations show that the efficiency of this method is favorable especially for high dimensional problems.Based on this global design optimization method,a design optimization of a lifting surface in high speed flow is carried out and this method saves about 10 h compared with genetic algorithms.This method possesses favorable performance on efficiency,robustness and capability of global convergence and gives a new optimization strategy for engineering design optimization problems involving expensive black box models.展开更多
The selection of phase change material(PCM)plays an important role in developing high-efficient thermal energy storage(TES)processes.Ionic liquids(ILs)or organic salts are thermally stable,non-volatile,and non-flammab...The selection of phase change material(PCM)plays an important role in developing high-efficient thermal energy storage(TES)processes.Ionic liquids(ILs)or organic salts are thermally stable,non-volatile,and non-flammable.Importantly,researchers have proved that some ILs possess higher latent heat of fusion than conventional PCMs.Despite these attractive characteristics,yet surprisingly,little research has been performed to the systematic selection or structural design of ILs for TES.Besides,most of the existing work is only focused on the latent heat when selecting PCMs.However,one should note that other properties such as heat capacity and thermal conductivity could affect the TES performance as well.In this work,we propose a computer-aided molecular design(CAMD)based method to systematically design IL PCMs for a practical TES process.The effects of different IL properties are simultaneously captured in the IL property models and TES process models.Optimal ILs holding a best compromise of all the properties are identified through the solution of a formulated CAMD problem where the TES performance of the process is maximized.[MPyEtOH][TfO]is found to be the best material and excitingly,the identified top nine ILs all show a higher TES performance than the traditional PCM paraffin wax at 10 h thermal charging time.展开更多
Numerous clustering algorithms are valuable in pattern recognition in forest vegetation,with new ones continually being proposed.While some are well-known,others are underutilized in vegetation science.This study comp...Numerous clustering algorithms are valuable in pattern recognition in forest vegetation,with new ones continually being proposed.While some are well-known,others are underutilized in vegetation science.This study compares the performance of practical iterative reallocation algorithms with model-based clustering algorithms.The data is from forest vegetation in Virginia(United States),the Hyrcanian Forest(Asia),and European beech forests.Practical iterative reallocation algorithms were applied as non-hierarchical methods and Finite Gaussian mixture modeling was used as a model-based clustering method.Due to limitations on dimensionality in model-based clustering,principal coordinates analysis was employed to reduce the dataset’s dimensions.A log transformation was applied to achieve a normal distribution for the pseudo-species data before calculating the Bray-Curtis dissimilarity.The findings indicate that the reallocation of misclassified objects based on silhouette width(OPTSIL)with Flexible-β(-0.25)had the highest mean among the tested clustering algorithms with Silhouette width 1(REMOS1)with Flexible-β(-0.25)second.However,model-based clustering performed poorly.Based on these results,it is recommended using OPTSIL with Flexible-β(-0.25)and REMOS1 with Flexible-β(-0.25)for forest vegetation classification instead of model-based clustering particularly for heterogeneous datasets common in forest vegetation community data.展开更多
This paper studies the problem of designing a modelbased decentralized dynamic periodic event-triggering mechanism(DDPETM)for networked control systems(NCSs)subject to packet losses and external disturbances.Firstly,t...This paper studies the problem of designing a modelbased decentralized dynamic periodic event-triggering mechanism(DDPETM)for networked control systems(NCSs)subject to packet losses and external disturbances.Firstly,the entire NCSs,comprising the triggering mechanism,packet losses and output-based controller,are unified into a hybrid dynamical framework.Secondly,by introducing dynamic triggering variables,the DDPETM is designed to conserve network resources while guaranteeing desired performance properties and tolerating the maximum allowable number of successive packet losses.Thirdly,some stability conditions are derived using the Lyapunov approach.Differing from the zero-order-hold(ZOH)case,the model-based control sufficiently exploits the model information at the controller side.Between two updates,the controller predicts the plant state based on the models and received feedback information.With the model-based control,less transmission may be expected than with ZOH.Finally,numerical examples and comparative experiments demonstrate the effectiveness of the proposed method.展开更多
This paper discusses the model-based predictive controller design of networked nonlinear systems with communica- tion delay and data loss. Based on the analysis of the closed-loop networked predictive control systems,...This paper discusses the model-based predictive controller design of networked nonlinear systems with communica- tion delay and data loss. Based on the analysis of the closed-loop networked predictive control systems, the model-based networked predictive control strategy can compensate for communication delay and data loss in an active way. The designed model-based predictive controller can also guarantee the stability of the closed-loop networked system. The simulation re- suits demonstrate the feasibility and efficacy of the proposed model-based predictive controller design scheme.展开更多
This paper proposes a wireframe model-based method for automated internal design. The method is used to extract geometric structure of an internal wireframe model and find out all loop structures of furniture models. ...This paper proposes a wireframe model-based method for automated internal design. The method is used to extract geometric structure of an internal wireframe model and find out all loop structures of furniture models. The wireframe models are classified as the multiple independent sub-models according to the geometric structure by statistical analysis. The corresponding models are selected from a 3D model database to build an internal scene based on characteristic points of furniture wireframe models. In the experiments 3D database via manually selected 268 3D furniture models from Google 3D warehouse is built up. The experiments show that the method can construct 3D scenes in 1.1×103 ms. This method costs less time compared with traditional hierarchical method and depth-sensing camera method in the same experimental conditions. The method can be also used for 3D visualization either with complex backgrounds.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
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
The challenge of transitioning from temporary humanitarian settlements to more sustainable human settlements is due to a significant increase in the number of forcibly displaced people over recent decades, difficultie...The challenge of transitioning from temporary humanitarian settlements to more sustainable human settlements is due to a significant increase in the number of forcibly displaced people over recent decades, difficulties in providing social services that meet the required standards, and the prolongation of emergencies. Despite this challenging context, short-term considerations continue to guide their planning and management rather than more integrated, longer-term perspectives, thus preventing viable, sustainable development. Over the years, the design of humanitarian settlements has not been adapted to local contexts and perspectives, nor to the dynamics of urbanization and population growth and data. In addition, the current approach to temporary settlement harms the environment and can strain limited resources. Inefficient land use and ad hoc development models have compounded difficulties and generated new challenges. As a result, living conditions in settlements have deteriorated over the last few decades and continue to pose new challenges. The stakes are such that major shortcomings have emerged along the way, leading to disruption, budget overruns in a context marked by a steady decline in funding. However, some attempts have been made to shift towards more sustainable approaches, but these have mainly focused on vague, sector-oriented themes, failing to consider systematic and integration views. This study is a contribution in addressing these shortcomings by designing a model-driving solution, emphasizing an integrated system conceptualized as a system of systems. This paper proposes a new methodology for designing an integrated and sustainable human settlement model, based on Model-Based Systems Engineering and a Systems Modeling Language to provide valuable insights toward sustainable solutions for displaced populations aligning with the United Nations 2030 agenda for sustainable development.展开更多
To address the challenges of high-precision optical surface defect detection,we propose a novel design for a wide-field and broadband light field camera in this work.The proposed system can achieve a 50°field of ...To address the challenges of high-precision optical surface defect detection,we propose a novel design for a wide-field and broadband light field camera in this work.The proposed system can achieve a 50°field of view and operates at both visible and near-infrared wavelengths.Using the principles of light field imaging,the proposed design enables 3D reconstruction of optical surfaces,thus enabling vertical surface height measurements with enhanced accuracy.Using Zemax-based simulations,we evaluate the system’s modulation transfer function,its optical aberrations,and its tolerance to shape variations through Zernike coefficient adjustments.The results demonstrate that this camera can achieve the required spatial resolution while also maintaining high imaging quality and thus offers a promising solution for advanced optical surface defect inspection.展开更多
Recent years have witnessed transformative changes brought about by artificial intelligence(AI)techniques with billions of parameters for the realization of high accuracy,proposing high demand for the advanced and AI ...Recent years have witnessed transformative changes brought about by artificial intelligence(AI)techniques with billions of parameters for the realization of high accuracy,proposing high demand for the advanced and AI chip to solve these AI tasks efficiently and powerfully.Rapid progress has been made in the field of advanced chips recently,such as the development of photonic computing,the advancement of the quantum processors,the boost of the biomimetic chips,and so on.Designs tactics of the advanced chips can be conducted with elaborated consideration of materials,algorithms,models,architectures,and so on.Though a few reviews present the development of the chips from their unique aspects,reviews in the view of the latest design for advanced and AI chips are few.Here,the newest development is systematically reviewed in the field of advanced chips.First,background and mechanisms are summarized,and subsequently most important considerations for co-design of the software and hardware are illustrated.Next,strategies are summed up to obtain advanced and AI chips with high excellent performance by taking the important information processing steps into consideration,after which the design thought for the advanced chips in the future is proposed.Finally,some perspectives are put forward.展开更多
The widespread proliferation of modern wireless devices coupled with overlapping power emissions has brought about electromagnetic(EM)pollution issues,posing many challenges to environment and human health.Therefore,t...The widespread proliferation of modern wireless devices coupled with overlapping power emissions has brought about electromagnetic(EM)pollution issues,posing many challenges to environment and human health.Therefore,the development of EM shielding devices with high green shielding index(gs)is essential,as they offer absorption-dominant protection that minimizes reflections and safeguards both health and electronics.MXene,with its intrinsic ultra-high electrical conductivity,liquid-phase tunable surface chemistry,low density,large specific surface area,thermal stability,and mechanical stability,has become the leading two-dimensional(2D)material driving the development of green EM shielding devices.In this review we emphasize device-level strategies with engineered architectures for MXene-based green EM shielding.We first examine MXene’s crystal and electronic structure and the fundamental attenuation mechanisms in MXene-based devices.Then we survey fabrication and assembly methods,analyzing three device-level strategies for MXene-based green EM shielded devices:3D architectures,metastructure/meta-surfaces,and external stimulus.Throughout,we highlight how MXene’s distinguished properties enable green EM interference(EMI)shielding devices that minimize secondary interference.Finally,we discuss the challenges faced in the effective utilization of MXene-based in green EM shielding devices,provide insights into these challenges,and offer guidelines for developing the solutions of next-generation green MXene-based EM shielding devices.展开更多
To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capabl...To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.展开更多
基金Projects(51135009)supported by the National Natural Science Foundation of China
文摘This work was focused on the model-based design method of two-axis four-actuator(TAFA) fast steering mirror system(FSM), in order to improve the design efficiency. The structure and operation principle commonality of normal TAFA FSM were investigated. Based on the structure and the commonality, the conditions of single-axis idea, high-frequency resonance and coupling were modeled gradually. Combining these models, a holonomic system model was established to reflect and predict the performance of TAFA FSM. A model-based design method was proposed based on the holonomic system model. The design flow and design concept of the method were described. In accordance with the method, a TAFA FSM was designed. Simulations and experiments of the FSM were done, and the results of them were compared. The compared results indicate that the holonomic system model can well reflect and predict the performance of TAFA FSM. The bandwidth of TAFA FSM is more than 250 Hz; adjust time is less than 15 ms;overshoot is less than 8%; position accuracy is better than 10 μrad; the FSM prototype can satisfy the requirements.
文摘This paper presents a Model-Based Design(MBD)approach for the design and control of a customized manipulator intended for drilling and position-ing of dental implants accurately with minimal human intervention.While performing an intra-oral surgery for a prolonged duration within a limited oral cavity,the tremor of dentist's hand is inevitable.As a result,wielding the drilling tool and inserting the dental implants safely in accurate position and orientation is highly challenging even for experienced dentists.Therefore,we introduce a customized manipulator that is designed ergonomically by taking in to account the dental chair specifications and anthropomorphic data such that it can be readily mounted onto the existing dental chair.The manipulator can be used to drill holes for dental inserts and position them with improved accuracy and safety.Further-more,a thorough multi-body motion analysis of the manipulator was carried out by creating a virtual prototype of the manipulator and simulating its controlled movements in various scenarios.The overall design was prepared and validated in simulation using Solid works,MATLAB and Simulink through Model Based Design(MBD)approach.The motion simulation results indicate that the manipulator could be built as a prototype readily.
文摘For several years now, electric vehicles (EVs) have been expected to become widely available in the micro-mobility field. However, the insufficiency of such vehicles’ battery-charging and discharging performance has limited their practical use. A hybrid energy storage system, which comprises a capacitor and battery, is a promising solution to this problem;however, to apply model-based designs, which are indispensable to embedded systems, such as the electronic control units used in EVs, a simple and accurate capacitor model is required. Within this framework, a lithium-ion capacitor (LIC) model is proposed, and its charging and discharging performances are evaluated against an actual LIC. The model corresponds accurately to the actual LIC, and the results indicate that the proposed LIC model will work well when used with Model-Based Design (MBD).
基金supported by the Postdoctoral Fellowship Program of CPSF(Grant No.GZC20242194)the National Natural Science Foundation of China(Grant Nos.52175251 and 52205268)+1 种基金the Industry Key Technology Research Fund Project of Northwestern Polytechnical University(Grant No.HYGJXM202318)the National Basic Scientific Research Program(Grant No.JCKY2021206B005).
文摘Unlike traditional propeller-driven underwater vehicles,blended-wing-body underwater gliders(BWBUGs)achieve zigzag gliding through periodic adjustments of their net buoyancy,enhancing their cruising capabilities while mini-mizing energy consumption.However,enhancing gliding performance is challenging due to the complex system design and limited design experience.To address this challenge,this paper introduces a model-based,multidisciplinary system design optimization method for BWBUGs at the conceptual design stage.First,a model-based,multidisciplinary co-simulation design framework is established to evaluate both system-level and disciplinary indices of BWBUG performance.A data-driven,many-objective multidisciplinary optimization is subsequently employed to explore the design space,yielding 32 Pareto optimal solutions.Finally,a model-based physical system simulation,which represents the design with the largest hyper-volume contribution among the 32 final designs,is established.Its gliding perfor-mance,validated by component behavior,lays the groundwork for constructing the entire system’s digital prototype.In conclusion,this model-based,multidisciplinary design optimization method effectively generates design schemes for innovative underwater vehicles,facilitating the development of digital prototypes.
基金supported by the Jiangxi Provincial Natural Science Foundation(No.20224BAB212022)Science and Technology Project of Education Department of Jiangxi Province(No.GJJ211435)+3 种基金the National Key Research and Development Program of China(No.2021YFA1400204)the Project of China Postdoctoral Science Foundation(No.2022M712909)the Natural Science Foundation of China(No.21603109)the Henan Joint Fund of the National Natural Science Foundation of China(No.U1404216)。
文摘Cobalt phosphide has been successfully used as a catalyst in the production of ammonia from nitric acid.Substituting appropriate atoms is expected to further improve its catalytic performance.Owing to the diversity of substituting elements,substitution sites,adsorption sites,and adsorption configurations,extensive time-consuming simulation calculations are required for the high-throughput screening method.Additionally,multi-objective attributes should be considered simultaneously in catalytic design.To tackle this challenge,this paper suggests a multi-objective cobalt phosphide catalytic material design method based on surrogate models.And the effectiveness of the proposed method was validated through comparative experiments.The proposed method led to the discovery of fifteen promising cobalt phosphide catalyst configurations.This study provides a new avenue for expediting the design of catalyst,with the potential for application in other systems.
基金supported by National Natural Science Foundation of China(Grant No.51105040)Aeronautic Science Foundation of China(Grant No.2011ZA72003)Excellent Young Scholars Research Fund of Beijing Institute of Technology(Grant No.2010Y0102)
文摘High fidelity analysis are utilized in modern engineering design optimization problems which involve expensive black-box models.For computation-intensive engineering design problems,efficient global optimization methods must be developed to relieve the computational burden.A new metamodel-based global optimization method using fuzzy clustering for design space reduction(MGO-FCR) is presented.The uniformly distributed initial sample points are generated by Latin hypercube design to construct the radial basis function metamodel,whose accuracy is improved with increasing number of sample points gradually.Fuzzy c-mean method and Gath-Geva clustering method are applied to divide the design space into several small interesting cluster spaces for low and high dimensional problems respectively.Modeling efficiency and accuracy are directly related to the design space,so unconcerned spaces are eliminated by the proposed reduction principle and two pseudo reduction algorithms.The reduction principle is developed to determine whether the current design space should be reduced and which space is eliminated.The first pseudo reduction algorithm improves the speed of clustering,while the second pseudo reduction algorithm ensures the design space to be reduced.Through several numerical benchmark functions,comparative studies with adaptive response surface method,approximated unimodal region elimination method and mode-pursuing sampling are carried out.The optimization results reveal that this method captures the real global optimum for all the numerical benchmark functions.And the number of function evaluations show that the efficiency of this method is favorable especially for high dimensional problems.Based on this global design optimization method,a design optimization of a lifting surface in high speed flow is carried out and this method saves about 10 h compared with genetic algorithms.This method possesses favorable performance on efficiency,robustness and capability of global convergence and gives a new optimization strategy for engineering design optimization problems involving expensive black box models.
基金the financial support from Max Planck Society,Germany,for the Computer-Aided Material and Process Design(CAMPD)project
文摘The selection of phase change material(PCM)plays an important role in developing high-efficient thermal energy storage(TES)processes.Ionic liquids(ILs)or organic salts are thermally stable,non-volatile,and non-flammable.Importantly,researchers have proved that some ILs possess higher latent heat of fusion than conventional PCMs.Despite these attractive characteristics,yet surprisingly,little research has been performed to the systematic selection or structural design of ILs for TES.Besides,most of the existing work is only focused on the latent heat when selecting PCMs.However,one should note that other properties such as heat capacity and thermal conductivity could affect the TES performance as well.In this work,we propose a computer-aided molecular design(CAMD)based method to systematically design IL PCMs for a practical TES process.The effects of different IL properties are simultaneously captured in the IL property models and TES process models.Optimal ILs holding a best compromise of all the properties are identified through the solution of a formulated CAMD problem where the TES performance of the process is maximized.[MPyEtOH][TfO]is found to be the best material and excitingly,the identified top nine ILs all show a higher TES performance than the traditional PCM paraffin wax at 10 h thermal charging time.
基金financially supported by the vice chancellor for research and technology of Urmia University
文摘Numerous clustering algorithms are valuable in pattern recognition in forest vegetation,with new ones continually being proposed.While some are well-known,others are underutilized in vegetation science.This study compares the performance of practical iterative reallocation algorithms with model-based clustering algorithms.The data is from forest vegetation in Virginia(United States),the Hyrcanian Forest(Asia),and European beech forests.Practical iterative reallocation algorithms were applied as non-hierarchical methods and Finite Gaussian mixture modeling was used as a model-based clustering method.Due to limitations on dimensionality in model-based clustering,principal coordinates analysis was employed to reduce the dataset’s dimensions.A log transformation was applied to achieve a normal distribution for the pseudo-species data before calculating the Bray-Curtis dissimilarity.The findings indicate that the reallocation of misclassified objects based on silhouette width(OPTSIL)with Flexible-β(-0.25)had the highest mean among the tested clustering algorithms with Silhouette width 1(REMOS1)with Flexible-β(-0.25)second.However,model-based clustering performed poorly.Based on these results,it is recommended using OPTSIL with Flexible-β(-0.25)and REMOS1 with Flexible-β(-0.25)for forest vegetation classification instead of model-based clustering particularly for heterogeneous datasets common in forest vegetation community data.
基金supported by the National Natural Science Foundation of China(U21A20477,61722302,61573069,61903290)the Fundamental Research Funds for the Central Universities(DUT19ZD218).
文摘This paper studies the problem of designing a modelbased decentralized dynamic periodic event-triggering mechanism(DDPETM)for networked control systems(NCSs)subject to packet losses and external disturbances.Firstly,the entire NCSs,comprising the triggering mechanism,packet losses and output-based controller,are unified into a hybrid dynamical framework.Secondly,by introducing dynamic triggering variables,the DDPETM is designed to conserve network resources while guaranteeing desired performance properties and tolerating the maximum allowable number of successive packet losses.Thirdly,some stability conditions are derived using the Lyapunov approach.Differing from the zero-order-hold(ZOH)case,the model-based control sufficiently exploits the model information at the controller side.Between two updates,the controller predicts the plant state based on the models and received feedback information.With the model-based control,less transmission may be expected than with ZOH.Finally,numerical examples and comparative experiments demonstrate the effectiveness of the proposed method.
基金Project supported by the Key Program for the National Natural Science Foundation of China(Grant No.61333003)the General Program for the National Natural Science Foundation of China(Grant No.61273104)
文摘This paper discusses the model-based predictive controller design of networked nonlinear systems with communica- tion delay and data loss. Based on the analysis of the closed-loop networked predictive control systems, the model-based networked predictive control strategy can compensate for communication delay and data loss in an active way. The designed model-based predictive controller can also guarantee the stability of the closed-loop networked system. The simulation re- suits demonstrate the feasibility and efficacy of the proposed model-based predictive controller design scheme.
基金Suppported by the National Natural Science Foundation of China(61303214)
文摘This paper proposes a wireframe model-based method for automated internal design. The method is used to extract geometric structure of an internal wireframe model and find out all loop structures of furniture models. The wireframe models are classified as the multiple independent sub-models according to the geometric structure by statistical analysis. The corresponding models are selected from a 3D model database to build an internal scene based on characteristic points of furniture wireframe models. In the experiments 3D database via manually selected 268 3D furniture models from Google 3D warehouse is built up. The experiments show that the method can construct 3D scenes in 1.1×103 ms. This method costs less time compared with traditional hierarchical method and depth-sensing camera method in the same experimental conditions. The method can be also used for 3D visualization either with complex backgrounds.
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.
文摘The challenge of transitioning from temporary humanitarian settlements to more sustainable human settlements is due to a significant increase in the number of forcibly displaced people over recent decades, difficulties in providing social services that meet the required standards, and the prolongation of emergencies. Despite this challenging context, short-term considerations continue to guide their planning and management rather than more integrated, longer-term perspectives, thus preventing viable, sustainable development. Over the years, the design of humanitarian settlements has not been adapted to local contexts and perspectives, nor to the dynamics of urbanization and population growth and data. In addition, the current approach to temporary settlement harms the environment and can strain limited resources. Inefficient land use and ad hoc development models have compounded difficulties and generated new challenges. As a result, living conditions in settlements have deteriorated over the last few decades and continue to pose new challenges. The stakes are such that major shortcomings have emerged along the way, leading to disruption, budget overruns in a context marked by a steady decline in funding. However, some attempts have been made to shift towards more sustainable approaches, but these have mainly focused on vague, sector-oriented themes, failing to consider systematic and integration views. This study is a contribution in addressing these shortcomings by designing a model-driving solution, emphasizing an integrated system conceptualized as a system of systems. This paper proposes a new methodology for designing an integrated and sustainable human settlement model, based on Model-Based Systems Engineering and a Systems Modeling Language to provide valuable insights toward sustainable solutions for displaced populations aligning with the United Nations 2030 agenda for sustainable development.
基金supported by the Jilin Science and Technology Development Plan(20240101029JJ)the following study:synchronized high-speed detection of surface shape and defects in the grinding stage of complex surfaces(KLMSZZ202305)+3 种基金for the high-precision wide dynamic large aperture optical inspection system for fine astronomical observation by the National Major Research Instrument Development Project(62127901)for ultrasmooth manufacturing technology of large diameter complex curved surface by the National Key R&D Program(2022YFB3403405)for research on the key technology of rapid synchronous detection of surface shape and subsurface defects in the grinding stage of large diameter complex surfaces by the International Cooperation Project(2025010157)The Key Laboratory of Optical System Advanced Manufacturing Technology,Chinese Academy of Sciences(2022KLOMT02-04)also supported this study.
文摘To address the challenges of high-precision optical surface defect detection,we propose a novel design for a wide-field and broadband light field camera in this work.The proposed system can achieve a 50°field of view and operates at both visible and near-infrared wavelengths.Using the principles of light field imaging,the proposed design enables 3D reconstruction of optical surfaces,thus enabling vertical surface height measurements with enhanced accuracy.Using Zemax-based simulations,we evaluate the system’s modulation transfer function,its optical aberrations,and its tolerance to shape variations through Zernike coefficient adjustments.The results demonstrate that this camera can achieve the required spatial resolution while also maintaining high imaging quality and thus offers a promising solution for advanced optical surface defect inspection.
基金supported by the Hong Kong Polytechnic University(1-WZ1Y,1-W34U,4-YWER).
文摘Recent years have witnessed transformative changes brought about by artificial intelligence(AI)techniques with billions of parameters for the realization of high accuracy,proposing high demand for the advanced and AI chip to solve these AI tasks efficiently and powerfully.Rapid progress has been made in the field of advanced chips recently,such as the development of photonic computing,the advancement of the quantum processors,the boost of the biomimetic chips,and so on.Designs tactics of the advanced chips can be conducted with elaborated consideration of materials,algorithms,models,architectures,and so on.Though a few reviews present the development of the chips from their unique aspects,reviews in the view of the latest design for advanced and AI chips are few.Here,the newest development is systematically reviewed in the field of advanced chips.First,background and mechanisms are summarized,and subsequently most important considerations for co-design of the software and hardware are illustrated.Next,strategies are summed up to obtain advanced and AI chips with high excellent performance by taking the important information processing steps into consideration,after which the design thought for the advanced chips in the future is proposed.Finally,some perspectives are put forward.
基金the National Natural Science Foundation of China(No.62304020)supported by the National Key R&D Program of China(No.2023YFB3811300)the National Natural Science Foundation of China(No.52202370).
文摘The widespread proliferation of modern wireless devices coupled with overlapping power emissions has brought about electromagnetic(EM)pollution issues,posing many challenges to environment and human health.Therefore,the development of EM shielding devices with high green shielding index(gs)is essential,as they offer absorption-dominant protection that minimizes reflections and safeguards both health and electronics.MXene,with its intrinsic ultra-high electrical conductivity,liquid-phase tunable surface chemistry,low density,large specific surface area,thermal stability,and mechanical stability,has become the leading two-dimensional(2D)material driving the development of green EM shielding devices.In this review we emphasize device-level strategies with engineered architectures for MXene-based green EM shielding.We first examine MXene’s crystal and electronic structure and the fundamental attenuation mechanisms in MXene-based devices.Then we survey fabrication and assembly methods,analyzing three device-level strategies for MXene-based green EM shielded devices:3D architectures,metastructure/meta-surfaces,and external stimulus.Throughout,we highlight how MXene’s distinguished properties enable green EM interference(EMI)shielding devices that minimize secondary interference.Finally,we discuss the challenges faced in the effective utilization of MXene-based in green EM shielding devices,provide insights into these challenges,and offer guidelines for developing the solutions of next-generation green MXene-based EM shielding devices.
基金funded by the Science and Technology Projects of State Grid Corporation of China(Project No.J2024136).
文摘To ensure an uninterrupted power supply,mobile power sources(MPS)are widely deployed in power grids during emergencies.Comprising mobile emergency generators(MEGs)and mobile energy storage systems(MESS),MPS are capable of supplying power to critical loads and serving as backup sources during grid contingencies,offering advantages such as flexibility and high resilience through electricity delivery via transportation networks.This paper proposes a design method for a 400 V–10 kV Dual-Winding Induction Generator(DWIG)intended for MEG applications,employing an improved particle swarmoptimization(PSO)algorithmbased on a back-propagation neural network(BPNN).A parameterized finite element(FE)model of the DWIG is established to derive constraints on its dimensional parameters,thereby simplifying the optimization space.Through sensitivity analysis between temperature rise and electromagnetic loss of the DWIG,the main factors influencing the machine’s temperature are identified,and electromagnetic loss is determined as the optimization objective.To obtain an accurate fitting function between electromagnetic loss and dimensional parameters,the BPNN is employed to predict the nonlinear relationship between the optimization objective and the parameters.The Latin hypercube sampling(LHS)method is used for random sampling in the FE model analysis for training,testing,and validation,which is then applied to compute the cost function in the PSO.Based on the relationships obtained by the BPNN,the PSO algorithm evaluates the fitness and cost functions to determine the optimal design point.The proposed optimization method is validated by comparing simulation results between the initial design and the optimized design.
