Due to the small size,active mobility,and intrinsic softness,miniature soft robots hold promising po-tentials in reaching the deep region inside living bodies otherwise inaccessible with compelling agility,adaptabilit...Due to the small size,active mobility,and intrinsic softness,miniature soft robots hold promising po-tentials in reaching the deep region inside living bodies otherwise inaccessible with compelling agility,adaptability and safety.Various materials and actuation strategies have been developed for creating soft robots,among which,ferromagnetic soft materials that self-actuate in response to external magnetic fields have attracted worldwide attention due to their remote controllability and excellent compatibil-ity with biological tissues.This review presents comprehensive and systematic research advancements in the design,fabrication,and applications of ferromagnetic soft materials for miniature robots,providing in-sights into their potential use in biomedical fields and beyond.The programming strategies of ferromag-netic soft materials are summarized and classified,including mold-assisted programming,3D printing-assisted programming,microassembly-assisted programming,and magnetization reprogramming.Each approach possesses unique advantages in manipulating the magnetic responsiveness of ferromagnetic soft materials to achieve outstanding actuation and deformation performances.We then discuss the biomedi-cal applications of ferromagnetic soft material-based soft robots(e.g.,minimally invasive surgery,targeted delivery,and tissue engineering),highlighting their potentials in revolutionizing biomedical technologies.This review also points out the current challenges and provides insights into future research directions,which we hope can serve as a useful reference for the development of next-generation adaptive miniature robots.展开更多
G protein coupled receptor kinase 2 (GRK2) is a kinase that regulates cardiac signaling activity. Inhibiting GRK2 is a promising mechanism for the treatment of heart failure (HF). Further development and optimization ...G protein coupled receptor kinase 2 (GRK2) is a kinase that regulates cardiac signaling activity. Inhibiting GRK2 is a promising mechanism for the treatment of heart failure (HF). Further development and optimization of inhibitors targeting GRK2 are highly meaningful. Therefore, in order to design GRK2 inhibitors with better performance, the most active molecule was selected as a reference compound from a data set containing 4-pyridylhydrazone derivatives and triazole derivatives, and its scaffold was extracted as the initial scaffold. Then, a powerful optimization-based framework for de novo drug design, guided by binding affinity, was used to generate a virtual molecular library targeting GRK2. The binding affinity of each virtual compound in this dataset was predicted by our developed deep learning model, and the designed potential compound with high binding affinity was selected for molecular docking and molecular dynamics simulation. It was found that the designed potential molecule binds to the ATP site of GRK2, which consists of key amino acids including Arg199, Gly200, Phe202, Val205, Lys220, Met274 and Asp335. The scaffold of the molecule is stabilized mainly by H-bonding and hydrophobic contacts. Concurrently, the reference compound in the dataset was also simulated by docking. It was found that this molecule also binds to the ATP site of GRK2. In addition, its scaffold is stabilized mainly by H-bonding and π-cation stacking interactions with Lys220, as well as hydrophobic contacts. The above results show that the designed potential molecule has similar binding modes to the reference compound, supporting the effectiveness of our framework for activity-focused molecular design. Finally, we summarized the interaction characteristics of general GRK2 inhibitors and gained insight into their molecule-target binding mechanisms, thereby facilitating the expansion of lead to hit compound.展开更多
Chiral metamaterials are manmade structures with extraordinary mechanical properties derived from their special geometric design instead of chemical composition.To make the mechanical deformation programmable,the non-...Chiral metamaterials are manmade structures with extraordinary mechanical properties derived from their special geometric design instead of chemical composition.To make the mechanical deformation programmable,the non-uniform rational B-spline(NURBS)curves are taken to replace the traditional ligament boundaries of the chiral structure.The Neural networks are innovatively inserted into the calculation of mechanical properties of the chiral structure instead of finite element methods to improve computational efficiency.For the problem of finding structure configuration with specified mechanical properties,such as Young’s modulus,Poisson’s ratio or deformation,an inverse design method using the Neural network-based proxy model is proposed to build the relationship between mechanical properties and geometric configuration.To satisfy some more complex deformation requirements,a non-homogeneous inverse design method is proposed and verified through simulation and experiments.Numerical and test results reveal the high computational efficiency and accuracy of the proposed method in the design of chiral metamaterials.展开更多
Advanced programmable metamaterials with heterogeneous microstructures have become increasingly prevalent in scientific and engineering disciplines attributed to their tunable properties.However,exploring the structur...Advanced programmable metamaterials with heterogeneous microstructures have become increasingly prevalent in scientific and engineering disciplines attributed to their tunable properties.However,exploring the structure-property relationship in these materials,including forward prediction and inverse design,presents substantial challenges.The inhomogeneous microstructures significantly complicate traditional analytical or simulation-based approaches.Here,we establish a novel framework that integrates the machine learning(ML)-encoded multiscale computational method for forward prediction and Bayesian optimization for inverse design.Unlike prior end-to-end ML methods limited to specific problems,our framework is both load-independent and geometry-independent.This means that a single training session for a constitutive model suffices to tackle various problems directly,eliminating the need for repeated data collection or training.We demonstrate the efficacy and efficiency of this framework using metamaterials with designable elliptical holes or lattice honeycombs microstructures.Leveraging accelerated forward prediction,we can precisely customize the stiffness and shape of metamaterials under diverse loading scenarios,and extend this capability to multi-objective customization seamlessly.Moreover,we achieve topology optimization for stress alleviation at the crack tip,resulting in a significant reduction of Mises stress by up to 41.2%and yielding a theoretical interpretable pattern.This framework offers a general,efficient and precise tool for analyzing the structure-property relationships of novel metamaterials.展开更多
Every year, around the world, between 250,000 and 500,000 people suffer a spinal cord injury(SCI). SCI is a devastating medical condition that arises from trauma or disease-induced damage to the spinal cord, disruptin...Every year, around the world, between 250,000 and 500,000 people suffer a spinal cord injury(SCI). SCI is a devastating medical condition that arises from trauma or disease-induced damage to the spinal cord, disrupting the neural connections that allow communication between the brain and the rest of the body, which results in varying degrees of motor and sensory impairment. Disconnection in the spinal tracts is an irreversible condition owing to the poor capacity for spontaneous axonal regeneration in the affected neurons.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
During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive...During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h^(2)/(4√2),where h is the piecewise length.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
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
Subcritical reactors(SCRs)or subcritical assemblies(SCAs)are the main infrastructure for designing power reactors.These reactors are widely used for training and research because of their high level of inherent safety...Subcritical reactors(SCRs)or subcritical assemblies(SCAs)are the main infrastructure for designing power reactors.These reactors are widely used for training and research because of their high level of inherent safety.The objective of this study is to design a subcritical reactor using a pressurized water reactor(PWR)conventional fuel following two safety points.In the first approach,deeply placed SCR cores with an infinite multiplication factor(k_(∞))of less than unity were identified using the DRAGON lattice code.In the second approach,subcritical reactor cores with an effective multiplication factor(k_(eff))of less than unity were determined by coupling the cell calculations of the DRAGON lattice code and core calculations of the DONJON code.For the deeply subcritical reactor design,it was found that the reactor would remain inherently subcritical while using fuel rods with ^(235)U enrichment of up to 0.9%,regardless of the pitch of the fuel rods.In the second approach,the optimal pitches(1.3 to 2.3 cm)were determined for different fuel enrichment values from 1 to 5%.Subsequently,the k_(eff) was obtained for a fuel rod arrangement of 8×8 to 80×80,and the states in which the reactor would be subcritical were determined for different fuel enrichments at the corresponding optimal pitch.To validate the models used in the DRAGON and DONJON codes,the k_(eff) of the Isfahan Light Water Subcritical Reactor(LWSCR)was experimentally measured and compared with the results of the calculations.Finally,the effects of fuel and moderator temperature changes were investigated to ensure that the designed assemblies remained in the subcritical state at all operational temperatures.展开更多
The importance and complexity of prioritizing construction projects (PCP) in urban road network planning lead to the necessity to develop an aided decision making program (ADMP). Cost benefit ratio model and stage rol...The importance and complexity of prioritizing construction projects (PCP) in urban road network planning lead to the necessity to develop an aided decision making program (ADMP). Cost benefit ratio model and stage rolled method are chosen as the theoretical foundations of the program, and then benefit model is improved to accord with the actuality of urban traffic in China. Consequently, program flows, module functions and data structures are designed, and particularly an original data structure of road ...展开更多
Frequency sampling is one of the popular methods in FIR digital filter design. In the frequency sampling method the value of transition band samples, which are usually obtained by consulting a table, must be determi...Frequency sampling is one of the popular methods in FIR digital filter design. In the frequency sampling method the value of transition band samples, which are usually obtained by consulting a table, must be determined in order to make the attenuation within the stopband maximal. However, the value obtained by searching for table can not be ensured to be optimal. Evolutionary programming (EP), a multi agent stochastic optimization technique, can lead to global optimal solutions for complex problems. In this paper a new application of EP to frequency sampling method is introduced. Two examples of lowpass and bandpass FIR filters are presented, and the steps of EP realization and experimental results are given. Experimental results show that the value of transition band samples obtained by EP can be ensured to be optimal and the performance of the filter is improved.展开更多
In order to make a business English training course cost effective, the course is to be designed based on certain language teaching theories and principles involving needs analysis to identify learners' needs and ...In order to make a business English training course cost effective, the course is to be designed based on certain language teaching theories and principles involving needs analysis to identify learners' needs and wants, appropriate teaching approaches and during-and-after evaluation of the training effects.展开更多
Overseas three-month intra-university training program is rear in Yunnan,China.Using adult learning and social con-structivism as theoretical basis,the author,introduces the background of the program and the course de...Overseas three-month intra-university training program is rear in Yunnan,China.Using adult learning and social con-structivism as theoretical basis,the author,introduces the background of the program and the course design,highlighting the inten-tion for the program and similar programs.展开更多
In order to improve the design results for the reconfigurable frequency response masking FRM filters an improved design method based on second-order cone programming SOCP is proposed.Unlike traditional methods that se...In order to improve the design results for the reconfigurable frequency response masking FRM filters an improved design method based on second-order cone programming SOCP is proposed.Unlike traditional methods that separately design the proposed method takes all the desired designing modes into consideration when designing all the subfilters. First an initial solution is obtained by separately designing the subfilters and then the initial solution is updated by iteratively solving a SOCP problem. The proposed method is evaluated on a design example and simulation results demonstrate that jointly designing all the subfilters can obtain significantly lower minimax approximation errors compared to the conventional design method.展开更多
When signal-to-interference ratio is low, the energy of strong interference leaked from the side lobe of beam pattern will infect the detection of weak target. Therefore, the beam pattern needs to be op...When signal-to-interference ratio is low, the energy of strong interference leaked from the side lobe of beam pattern will infect the detection of weak target. Therefore, the beam pattern needs to be optimized. The existing Dolph-Chebyshev weighting method can get the lowest side lobe level under given main lobe width, but for the other non-uniform circular array and nonlinear array, the low side lobe pattern needs to be designed specially. The second order cone programming optimization （SOCP） algorithm proposed in the paper transforms the optimization of the beam pattern into a standard convex optimization problem. Thus there is a paradigm to follow for any array formation, which not only achieves the purpose of Dolph-Chebyshev weighting, but also solves the problem of the increased side lobe when the signal is at end fire direction The simulation proves that the SOCP algorithm can detect the weak target better than the conventional beam forming.展开更多
Off-line programming （OLP） system becomes one of the most important programming modules for the robotic belt grinding process, however there lacks research on increasing the grinding dexterous space depending on the...Off-line programming （OLP） system becomes one of the most important programming modules for the robotic belt grinding process, however there lacks research on increasing the grinding dexterous space depending on the OLP system. A new type of grinding robot and a novel robotic belt grinding workcell are forwarded, and their features are briefly introduced. An open and object-oriented off-line programming system is developed for this robotic belt grinding system. The parameters of the trimmed surface are read from the initial graphics exchange specification （IGES） file of the CAD model of the workpiece. The deBoor-Cox basis function is used to sample the grinding target with local contact frame on the workpiece. The numerical formula of inverse kinematics is set up based on Newton＇s iterative procedure, to calculate the grinding robot configurations corresponding to the grinding targets. After the grinding path is obtained, the OLP system turns to be more effective than the teach-by-showing system. In order to improve the grinding workspace, an optimization algorithm for dynamic tool frame is proposed and performed on the special robotic belt grinding system. The initial tool frame and the interval of neighboring tool frames are defined as the preparation of the algorithm. An optimized tool local frame can be selected to grind the complex surface for a maximum dexterity index of the robot. Under the optimization algorithm, a simulation of grinding a vane is included and comparison of grinding workspace is done before and after the tool frame optimization. By the algorithm, the grinding workspace can be enlarged. Moreover the dynamic tool frame can be considered to add one degree-of-freedom to the grinding kinematical chain, which provides the theoretical support for the improvement of robotic dexterity for the complex surface grinding.展开更多
基金the National Key R&D Program of China(No.2023YFE0208700)National Natural Sci-ence Foundation of China(No.92163109 and 52072095)+7 种基金Shenzhen Science and Technology Program(No.RCJC20231211090000001,GXWD20231129101105001)the National Natural Science Foundation of China(No.52205590)the Natural Science Foundation of Jiangsu Province(No.BK20220834)the Start-up Research Fund of Southeast University(No.RF1028623098)the State Key Laboratory of Robotics and Systems(HIT)(No.SKLRS-2024-KF-11)National Natural Science Foundation of China(No.52202348)Guangdong Basic and Applied Basic Research Foundation(No.2023A1515011491)Shenzhen Science and Technology Program(Nos.GXWD20220818224716001,KJZD20231023100302006).
文摘Due to the small size,active mobility,and intrinsic softness,miniature soft robots hold promising po-tentials in reaching the deep region inside living bodies otherwise inaccessible with compelling agility,adaptability and safety.Various materials and actuation strategies have been developed for creating soft robots,among which,ferromagnetic soft materials that self-actuate in response to external magnetic fields have attracted worldwide attention due to their remote controllability and excellent compatibil-ity with biological tissues.This review presents comprehensive and systematic research advancements in the design,fabrication,and applications of ferromagnetic soft materials for miniature robots,providing in-sights into their potential use in biomedical fields and beyond.The programming strategies of ferromag-netic soft materials are summarized and classified,including mold-assisted programming,3D printing-assisted programming,microassembly-assisted programming,and magnetization reprogramming.Each approach possesses unique advantages in manipulating the magnetic responsiveness of ferromagnetic soft materials to achieve outstanding actuation and deformation performances.We then discuss the biomedi-cal applications of ferromagnetic soft material-based soft robots(e.g.,minimally invasive surgery,targeted delivery,and tissue engineering),highlighting their potentials in revolutionizing biomedical technologies.This review also points out the current challenges and provides insights into future research directions,which we hope can serve as a useful reference for the development of next-generation adaptive miniature robots.
基金supported by the National Natural Science Foundation of China Excellent Young Scientist Fund(22422801)the National Natural Science Foundation of China General Project(22278053)+1 种基金the National Natural Science Foundation of China General Project(22078041)Dalian High-level Talents Innovation Support Program(2023RQ059).
文摘G protein coupled receptor kinase 2 (GRK2) is a kinase that regulates cardiac signaling activity. Inhibiting GRK2 is a promising mechanism for the treatment of heart failure (HF). Further development and optimization of inhibitors targeting GRK2 are highly meaningful. Therefore, in order to design GRK2 inhibitors with better performance, the most active molecule was selected as a reference compound from a data set containing 4-pyridylhydrazone derivatives and triazole derivatives, and its scaffold was extracted as the initial scaffold. Then, a powerful optimization-based framework for de novo drug design, guided by binding affinity, was used to generate a virtual molecular library targeting GRK2. The binding affinity of each virtual compound in this dataset was predicted by our developed deep learning model, and the designed potential compound with high binding affinity was selected for molecular docking and molecular dynamics simulation. It was found that the designed potential molecule binds to the ATP site of GRK2, which consists of key amino acids including Arg199, Gly200, Phe202, Val205, Lys220, Met274 and Asp335. The scaffold of the molecule is stabilized mainly by H-bonding and hydrophobic contacts. Concurrently, the reference compound in the dataset was also simulated by docking. It was found that this molecule also binds to the ATP site of GRK2. In addition, its scaffold is stabilized mainly by H-bonding and π-cation stacking interactions with Lys220, as well as hydrophobic contacts. The above results show that the designed potential molecule has similar binding modes to the reference compound, supporting the effectiveness of our framework for activity-focused molecular design. Finally, we summarized the interaction characteristics of general GRK2 inhibitors and gained insight into their molecule-target binding mechanisms, thereby facilitating the expansion of lead to hit compound.
基金supported by the National Natural Science Foundation of China(grant numbers 11972287 and 12072266)the State Key Laboratory of Structural Analysis,Optimization and CAE Software for Industrial Equipment(GZ23106)+1 种基金the National Key Laboratory of Aircraft Configuration Design(No.2023-JCJQ-LB-070)the Fundamental Research Funds for the Central Universities.
文摘Chiral metamaterials are manmade structures with extraordinary mechanical properties derived from their special geometric design instead of chemical composition.To make the mechanical deformation programmable,the non-uniform rational B-spline(NURBS)curves are taken to replace the traditional ligament boundaries of the chiral structure.The Neural networks are innovatively inserted into the calculation of mechanical properties of the chiral structure instead of finite element methods to improve computational efficiency.For the problem of finding structure configuration with specified mechanical properties,such as Young’s modulus,Poisson’s ratio or deformation,an inverse design method using the Neural network-based proxy model is proposed to build the relationship between mechanical properties and geometric configuration.To satisfy some more complex deformation requirements,a non-homogeneous inverse design method is proposed and verified through simulation and experiments.Numerical and test results reveal the high computational efficiency and accuracy of the proposed method in the design of chiral metamaterials.
基金supported by the National Natural Science Foundation of China (Grant Nos.12102021,12372105,12172026,and 12225201)the Fundamental Research Funds for the Central Universities and the Academic Excellence Foundation of BUAA for PhD Students.
文摘Advanced programmable metamaterials with heterogeneous microstructures have become increasingly prevalent in scientific and engineering disciplines attributed to their tunable properties.However,exploring the structure-property relationship in these materials,including forward prediction and inverse design,presents substantial challenges.The inhomogeneous microstructures significantly complicate traditional analytical or simulation-based approaches.Here,we establish a novel framework that integrates the machine learning(ML)-encoded multiscale computational method for forward prediction and Bayesian optimization for inverse design.Unlike prior end-to-end ML methods limited to specific problems,our framework is both load-independent and geometry-independent.This means that a single training session for a constitutive model suffices to tackle various problems directly,eliminating the need for repeated data collection or training.We demonstrate the efficacy and efficiency of this framework using metamaterials with designable elliptical holes or lattice honeycombs microstructures.Leveraging accelerated forward prediction,we can precisely customize the stiffness and shape of metamaterials under diverse loading scenarios,and extend this capability to multi-objective customization seamlessly.Moreover,we achieve topology optimization for stress alleviation at the crack tip,resulting in a significant reduction of Mises stress by up to 41.2%and yielding a theoretical interpretable pattern.This framework offers a general,efficient and precise tool for analyzing the structure-property relationships of novel metamaterials.
基金financially supported by Ministerio de Ciencia e Innovación projects SAF2017-82736-C2-1-R to MTMFin Universidad Autónoma de Madrid and by Fundación Universidad Francisco de Vitoria to JS+2 种基金a predoctoral scholarship from Fundación Universidad Francisco de Vitoriafinancial support from a 6-month contract from Universidad Autónoma de Madrida 3-month contract from the School of Medicine of Universidad Francisco de Vitoria。
文摘Every year, around the world, between 250,000 and 500,000 people suffer a spinal cord injury(SCI). SCI is a devastating medical condition that arises from trauma or disease-induced damage to the spinal cord, disrupting the neural connections that allow communication between the brain and the rest of the body, which results in varying degrees of motor and sensory impairment. Disconnection in the spinal tracts is an irreversible condition owing to the poor capacity for spontaneous axonal regeneration in the affected neurons.
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 Natural Sci‐ence Foundation of China(Grant No.62306325)。
文摘During the use of robotics in applications such as antiterrorism or combat,a motion-constrained pursuer vehicle,such as a Dubins unmanned surface vehicle(USV),must get close enough(within a prescribed zero or positive distance)to a moving target as quickly as possible,resulting in the extended minimum-time intercept problem(EMTIP).Existing research has primarily focused on the zero-distance intercept problem,MTIP,establishing the necessary or sufficient conditions for MTIP optimality,and utilizing analytic algorithms,such as root-finding algorithms,to calculate the optimal solutions.However,these approaches depend heavily on the properties of the analytic algorithm,making them inapplicable when problem settings change,such as in the case of a positive effective range or complicated target motions outside uniform rectilinear motion.In this study,an approach employing a high-accuracy and quality-guaranteed mixed-integer piecewise-linear program(QG-PWL)is proposed for the EMTIP.This program can accommodate different effective interception ranges and complicated target motions(variable velocity or complicated trajectories).The high accuracy and quality guarantees of QG-PWL originate from elegant strategies such as piecewise linearization and other developed operation strategies.The approximate error in the intercept path length is proved to be bounded to h^(2)/(4√2),where h is the piecewise length.
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.
文摘Subcritical reactors(SCRs)or subcritical assemblies(SCAs)are the main infrastructure for designing power reactors.These reactors are widely used for training and research because of their high level of inherent safety.The objective of this study is to design a subcritical reactor using a pressurized water reactor(PWR)conventional fuel following two safety points.In the first approach,deeply placed SCR cores with an infinite multiplication factor(k_(∞))of less than unity were identified using the DRAGON lattice code.In the second approach,subcritical reactor cores with an effective multiplication factor(k_(eff))of less than unity were determined by coupling the cell calculations of the DRAGON lattice code and core calculations of the DONJON code.For the deeply subcritical reactor design,it was found that the reactor would remain inherently subcritical while using fuel rods with ^(235)U enrichment of up to 0.9%,regardless of the pitch of the fuel rods.In the second approach,the optimal pitches(1.3 to 2.3 cm)were determined for different fuel enrichment values from 1 to 5%.Subsequently,the k_(eff) was obtained for a fuel rod arrangement of 8×8 to 80×80,and the states in which the reactor would be subcritical were determined for different fuel enrichments at the corresponding optimal pitch.To validate the models used in the DRAGON and DONJON codes,the k_(eff) of the Isfahan Light Water Subcritical Reactor(LWSCR)was experimentally measured and compared with the results of the calculations.Finally,the effects of fuel and moderator temperature changes were investigated to ensure that the designed assemblies remained in the subcritical state at all operational temperatures.
文摘The importance and complexity of prioritizing construction projects (PCP) in urban road network planning lead to the necessity to develop an aided decision making program (ADMP). Cost benefit ratio model and stage rolled method are chosen as the theoretical foundations of the program, and then benefit model is improved to accord with the actuality of urban traffic in China. Consequently, program flows, module functions and data structures are designed, and particularly an original data structure of road ...
文摘Frequency sampling is one of the popular methods in FIR digital filter design. In the frequency sampling method the value of transition band samples, which are usually obtained by consulting a table, must be determined in order to make the attenuation within the stopband maximal. However, the value obtained by searching for table can not be ensured to be optimal. Evolutionary programming (EP), a multi agent stochastic optimization technique, can lead to global optimal solutions for complex problems. In this paper a new application of EP to frequency sampling method is introduced. Two examples of lowpass and bandpass FIR filters are presented, and the steps of EP realization and experimental results are given. Experimental results show that the value of transition band samples obtained by EP can be ensured to be optimal and the performance of the filter is improved.
文摘In order to make a business English training course cost effective, the course is to be designed based on certain language teaching theories and principles involving needs analysis to identify learners' needs and wants, appropriate teaching approaches and during-and-after evaluation of the training effects.
文摘Overseas three-month intra-university training program is rear in Yunnan,China.Using adult learning and social con-structivism as theoretical basis,the author,introduces the background of the program and the course design,highlighting the inten-tion for the program and similar programs.
基金The National Natural Science Foundation of China(No.61231002,61273266,61375028)the Ph.D.Programs Foundation of Ministry of Education of China(No.20110092130004)
文摘In order to improve the design results for the reconfigurable frequency response masking FRM filters an improved design method based on second-order cone programming SOCP is proposed.Unlike traditional methods that separately design the proposed method takes all the desired designing modes into consideration when designing all the subfilters. First an initial solution is obtained by separately designing the subfilters and then the initial solution is updated by iteratively solving a SOCP problem. The proposed method is evaluated on a design example and simulation results demonstrate that jointly designing all the subfilters can obtain significantly lower minimax approximation errors compared to the conventional design method.
基金Special Item of National Major Scientific Apparatus Development(No.2013YQ140431)
文摘When signal-to-interference ratio is low, the energy of strong interference leaked from the side lobe of beam pattern will infect the detection of weak target. Therefore, the beam pattern needs to be optimized. The existing Dolph-Chebyshev weighting method can get the lowest side lobe level under given main lobe width, but for the other non-uniform circular array and nonlinear array, the low side lobe pattern needs to be designed specially. The second order cone programming optimization （SOCP） algorithm proposed in the paper transforms the optimization of the beam pattern into a standard convex optimization problem. Thus there is a paradigm to follow for any array formation, which not only achieves the purpose of Dolph-Chebyshev weighting, but also solves the problem of the increased side lobe when the signal is at end fire direction The simulation proves that the SOCP algorithm can detect the weak target better than the conventional beam forming.
基金supported by National Hi-tech Research and Development Program of China (863 Program, Grant No. 2007AA04Z2443)State Key Laboratory for Man ufacturing Systems Engineering of Xi’an Jiaotong University of China
文摘Off-line programming （OLP） system becomes one of the most important programming modules for the robotic belt grinding process, however there lacks research on increasing the grinding dexterous space depending on the OLP system. A new type of grinding robot and a novel robotic belt grinding workcell are forwarded, and their features are briefly introduced. An open and object-oriented off-line programming system is developed for this robotic belt grinding system. The parameters of the trimmed surface are read from the initial graphics exchange specification （IGES） file of the CAD model of the workpiece. The deBoor-Cox basis function is used to sample the grinding target with local contact frame on the workpiece. The numerical formula of inverse kinematics is set up based on Newton＇s iterative procedure, to calculate the grinding robot configurations corresponding to the grinding targets. After the grinding path is obtained, the OLP system turns to be more effective than the teach-by-showing system. In order to improve the grinding workspace, an optimization algorithm for dynamic tool frame is proposed and performed on the special robotic belt grinding system. The initial tool frame and the interval of neighboring tool frames are defined as the preparation of the algorithm. An optimized tool local frame can be selected to grind the complex surface for a maximum dexterity index of the robot. Under the optimization algorithm, a simulation of grinding a vane is included and comparison of grinding workspace is done before and after the tool frame optimization. By the algorithm, the grinding workspace can be enlarged. Moreover the dynamic tool frame can be considered to add one degree-of-freedom to the grinding kinematical chain, which provides the theoretical support for the improvement of robotic dexterity for the complex surface grinding.
