Deterministic optimization methods are combined with the Pareto front concept to solve multi-criterion design problems. The algorithm and the numerical implementation are applied to aerodynamic designs. Evolutionary a...Deterministic optimization methods are combined with the Pareto front concept to solve multi-criterion design problems. The algorithm and the numerical implementation are applied to aerodynamic designs. Evolutionary algorithms （EAs） and the Pareto front concept are used to solve practical design problems in industry for its robustness in capturing convex, concave, discrete or discontinuous Pareto fronts of multi-objective optimization problems. However, the process is time-consuming. Therefore, deterministic optimization methods are introduced to capture the Pareto front, and the types of the captured Pareto front are explained. Numerical experiments show that the deterministic optimization method is a good alternative to EAs for capturing any convex and some concave Pareto fronts in multi-criterion aerodynamic optimization problems due to its efficiency.展开更多
During the construction process of the construction project,the construction technology management work can improve the overall quality of the project construction.In the context of increasingly fierce competition in ...During the construction process of the construction project,the construction technology management work can improve the overall quality of the project construction.In the context of increasingly fierce competition in the construction market,construction enterprises should strengthen the management of construction technology,enhance their technical level and market competitiveness,and promote the development of the construction market[1].The paper mainly analyzes the optimization methods of build-Keywords:ing construction technology management.展开更多
In this paper, we present a large-update primal-dual interior-point method for symmetric cone optimization（SCO） based on a new kernel function, which determines both search directions and the proximity measure betwe...In this paper, we present a large-update primal-dual interior-point method for symmetric cone optimization（SCO） based on a new kernel function, which determines both search directions and the proximity measure between the iterate and the center path. The kernel function is neither a self-regular function nor the usual logarithmic kernel function. Besides, by using Euclidean Jordan algebraic techniques, we achieve the favorable iteration complexity O（ √r（1/2）（log r）^2 log（r/ ε））, which is as good as the convex quadratic semi-definite optimization analogue.展开更多
In this paper,a linear optimization method(LOM)for the design of terahertz circuits is presented,aimed at enhancing the simulation efficacy and reducing the time of the circuit design workflow.This method enables the ...In this paper,a linear optimization method(LOM)for the design of terahertz circuits is presented,aimed at enhancing the simulation efficacy and reducing the time of the circuit design workflow.This method enables the rapid determination of optimal embedding impedance for diodes across a specific bandwidth to achieve maximum efficiency through harmonic balance simulations.By optimizing the linear matching circuit with the optimal embedding impedance,the method effectively segregates the simulation of the linear segments from the nonlinear segments in the frequency multiplier circuit,substantially improving the speed of simulations.The design of on-chip linear matching circuits adopts a modular circuit design strategy,incorporating fixed load resistors to simplify the matching challenge.Utilizing this approach,a 340 GHz frequency doubler was developed and measured.The results demonstrate that,across a bandwidth of 330 GHz to 342 GHz,the efficiency of the doubler remains above 10%,with an input power ranging from 98 mW to 141mW and an output power exceeding 13 mW.Notably,at an input power of 141 mW,a peak output power of 21.8 mW was achieved at 334 GHz,corresponding to an efficiency of 15.8%.展开更多
Response analysis of structures involving non-probabilistic uncertain parameters can be closely related to optimization.This paper provides a review on optimization-based methods for uncertainty analysis,with focusing...Response analysis of structures involving non-probabilistic uncertain parameters can be closely related to optimization.This paper provides a review on optimization-based methods for uncertainty analysis,with focusing attention on specific properties of adopted numerical optimization approaches.We collect and discuss the methods based on nonlinear programming,semidefinite programming,mixed-integer programming,mathematical programming with complementarity constraints,difference-of-convex programming,optimization methods using surrogate models and machine learning techniques,and metaheuristics.As a closely related topic,we also overview the methods for assessing structural robustness using non-probabilistic uncertainty modeling.We conclude the paper by drawing several remarks through this review.展开更多
Dear Editor,Pose graph optimization(PGO)is a popular optimization approach that plays a crucial role in the simultaneous localization and mapping(SLAM)back-end.However,when incorrect loop closure constraints(referred ...Dear Editor,Pose graph optimization(PGO)is a popular optimization approach that plays a crucial role in the simultaneous localization and mapping(SLAM)back-end.However,when incorrect loop closure constraints(referred to as outliers)are present in the SLAM front-end,the standard PGO algorithm fails catastrophically and can not return an accurate map.To address this issue,this letter proposes a novel algorithm that leverages classical optimization methods to effectively handle outliers.The proposed algorithm introduces a new formulation that incorporates a credibility factor model,which improves the robustness of the optimization process.Additionally,an innovative consistency classification algorithm is developed to detect outliers.Extensive experiments are conducted on multiple benchmark datasets to evaluate the consistency and accuracy of the proposed algorithm.展开更多
The flow ripple caused by an axial piston pump may lead to pipe vibrations and lower hydraulic component reliability,which are of particular concern in hydraulic systems.The valve plate of the pump is considered the p...The flow ripple caused by an axial piston pump may lead to pipe vibrations and lower hydraulic component reliability,which are of particular concern in hydraulic systems.The valve plate of the pump is considered the part most related to flow ripple,and its structural design is an important topic.In this study,an analytical model for the axial piston pump flow ripple was established and verified using a numerical analysis with computational fluid dynamics(CFD)calculations.Moreover,a parametric analysis of the valve plate was performed to investigate the critical parameters and their ranges.A fast optimization method,the rotation vector optimization method(RVOM),was proposed for the valve plate design and compared with the currently used optimization methods to prove its efficiency.As a constant-pressure pump works in different states of swashplate angle,outlet pressure,and pump speed,an optimization principle for the entire working status was proposed to achieve the overall reduction performance.A test rig for an aircraft hydraulic pump was established,and validation experiments were conducted.It was determined that the optimized pump could achieve reduction at multiple working statuses,and the largest pressure pulsation reduction ratios for the typical speed and speed sweep tests reached 64.7%and 71.7%,respectively.The model and method proposed in this study are proven to be effective and accurate.展开更多
Local and global optimization methods are widely used in geophysical inversion but each has its own advantages and disadvantages. The combination of the two methods will make it possible to overcome their weaknesses. ...Local and global optimization methods are widely used in geophysical inversion but each has its own advantages and disadvantages. The combination of the two methods will make it possible to overcome their weaknesses. Based on the simulated annealing genetic algorithm （SAGA） and the simplex algorithm, an efficient and robust 2-D nonlinear method for seismic travel-time inversion is presented in this paper. First we do a global search over a large range by SAGA and then do a rapid local search using the simplex method. A multi-scale tomography method is adopted in order to reduce non-uniqueness. The velocity field is divided into different spatial scales and velocities at the grid nodes are taken as unknown parameters. The model is parameterized by a bi-cubic spline function. The finite-difference method is used to solve the forward problem while the hybrid method combining multi-scale SAGA and simplex algorithms is applied to the inverse problem. The algorithm has been applied to a numerical test and a travel-time perturbation test using an anomalous low-velocity body. For a practical example, it is used in the study of upper crustal velocity structure of the A＇nyemaqen suture zone at the north-east edge of the Qinghai-Tibet Plateau. The model test and practical application both prove that the method is effective and robust.展开更多
The principle of direct method used in optimal control problem is introduced. Details of applying this method to flight trajectory generation are presented including calculation of velocity and controls histories. And...The principle of direct method used in optimal control problem is introduced. Details of applying this method to flight trajectory generation are presented including calculation of velocity and controls histories. And capabilities of flight and propulsion systems are considered also. Combined with digital terrain map technique, the direct method is applied to the three dimensional trajectory optimization for low altitude penetration, and simplex algorithm is used to solve the parameters in optimization. For the small number of parameters, the trajectory can be optimized in real time on board.展开更多
This paper explores the convergence of a class of optimally conditioned self scaling variable metric (OCSSVM) methods for unconstrained optimization. We show that this class of methods with Wolfe line search are glob...This paper explores the convergence of a class of optimally conditioned self scaling variable metric (OCSSVM) methods for unconstrained optimization. We show that this class of methods with Wolfe line search are globally convergent for general convex functions.展开更多
The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often...The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.展开更多
Based on the optimization method, a new modified GM (1,1) model is presented, which is characterized by more accuracy prediction for the grey modeling.
In this paper, a new derivative free trust region method is developed based on the conic interpolation model for the unconstrained optimization. The conic interpolation model is built by means of the quadratic model f...In this paper, a new derivative free trust region method is developed based on the conic interpolation model for the unconstrained optimization. The conic interpolation model is built by means of the quadratic model function, the collinear scaling formula, quadratic approximation and interpolation. All the parameters in this model are determined by objective function interpolation condition. A new derivative free method is developed based upon this model and the global convergence of this new method is proved without any information on gradient.展开更多
Chemical batch processes have become significant in chemical manufacturing. In these processes, large numbers of chemical products are produced to satisfy human demands in daily life. Recently, economy globalization h...Chemical batch processes have become significant in chemical manufacturing. In these processes, large numbers of chemical products are produced to satisfy human demands in daily life. Recently, economy globalization has resulted, in growing worldwide competitions in tradi.tional chemical .process industry. In order to keep competitive in the global marketplace, each company must optimize its production management and set up a reactive system for market fluctuation. Scheduling is the core of production management in chemical processes. The goal of this paper is to review the recent developments in this challenging area. Classifications of batch scheduling problems and optimization methods are introduced. A comparison of six typical models is shown in a general benchmark example from the literature. Finally, challenges and applications in future research are discussed.展开更多
Attempts for higher output power and thermal efficiency of gas turbines make the inlet temperature of turbine to be far beyond the material melting temperature.Therefore,to protect the airfoil in gas turbine from hot ...Attempts for higher output power and thermal efficiency of gas turbines make the inlet temperature of turbine to be far beyond the material melting temperature.Therefore,to protect the airfoil in gas turbine from hot gas and eventually prolong the lifetime of the blade,internal and film cooling structures with better thermal performance and cooling effectiveness are urgently needed.However,the traditional way of proceeding involves numerous simulations,additional experiments,and separate trials.Optimization of turbine cooling structures is an effective way to achieve better structures with higher overall performances while considering the multiple objectives,disciplines or subsystems.In this context,this paper reviews optimization research works on film cooling structures and internal cooling structures in gas turbines by means of various optimization methods.This review covers the following aspects:(A)optimization of film cooling conducted on flat plates and on turbine blades or vanes;(B)optimization of jet impingement cooling structures;(C)optimization of rib shapes,dimple shapes,pin–fin arrays in the cooling channels;(D)optimization of U-bend shaped cooling channels,and internal cooling systems of turbine blades or vanes.The review shows that through a reliable and accurate optimization procedure combined with conjugate heat transfer analysis,higher overall thermal performance can be acquired for single-objective or multi-objectives balanced by other constrained conditions.Future ways forward are pointed out in this review.展开更多
The discontinuous dynamical problem of multi-point contact and collision in multi-body system has always been a hot and difficult issue in this field.Based on the Gauss’principle of least constraint,a unified optimiz...The discontinuous dynamical problem of multi-point contact and collision in multi-body system has always been a hot and difficult issue in this field.Based on the Gauss’principle of least constraint,a unified optimization model for multibody system dynamics with multi-point contact and collision is established.The paper presents the study of the numerical solution scheme,in which particle swarm optimization method is used to deal with the corresponding optimization model.The article also presents the comparison of the Gauss optimization method(GOM)and the hybrid linear complementarity method(i.e.combining differential algebraic equations(DAEs)and linear complementarity problems(LCP)),commonly used to solve the dynamic contact problem of multibody systems with bilateral constraints.The results illustrate that,the GOM has the same advantage of dynamical modelling with LCP and when the redundant constraint exists,the GOM always has a unique solution and so no additional processing is needed,whereas the corresponding DAE-LCP method may have singular cases with multiple solutions or no solutions.Using numerical examples,the GOM is verified to effectively solve the dynamics of multibody systems with redundant unilateral and bilateral constraints without additional redundancy processing.The GOM can also be applied to the optimal control of systems in the future and combined with the parameter optimization of systems to handle dynamic problems.The work given provides the dynamics and control of the complex system with a new train of thought and method.展开更多
Lithium-ion batteries(LIBs)have evolved into the mainstream power source of ene rgy sto rage equipment by reason of their advantages such as high energy density,high power,long cycle life and less pollution.With the e...Lithium-ion batteries(LIBs)have evolved into the mainstream power source of ene rgy sto rage equipment by reason of their advantages such as high energy density,high power,long cycle life and less pollution.With the expansion of their applications in deep-sea exploration,aerospace and military equipment,special working conditions have placed higher demands on the low-temperature performance of LIBs.However,at low temperatures,the severe polarization and inferior electrochemical activity of electrode materials cause the acute capacity fading upon cycling,which greatly hindered the further development of LIBs.In this review,we summarize the recent important progress of LIBs in low-temperature operations and introduce the key methods and the related action mechanisms for enhancing the capacity of the various cathode and anode materials.It aims to promote the development of high-performance electrode materials and broaden the application range of LIBs.展开更多
This paper proposed a reliability design model for composite materials under the mixture of random and interval variables. Together with the inverse reliability analysis technique, the sequential single-loop optimizat...This paper proposed a reliability design model for composite materials under the mixture of random and interval variables. Together with the inverse reliability analysis technique, the sequential single-loop optimization method is applied to the reliability-based design of composites. In the sequential single-loop optimization, the optimization and the reliability analysis are decoupled to improve the computational efficiency. As shown in examples, the minimum weight problems under the constraint of structural reliability are solved for laminated composites. The Particle Swarm Optimization （PSO） algorithm is utilized to search for the optimal solutions. The design results indicate that, under the mixture of random and interval variables, the method that combines the sequential single-loop optimization and the PSO algorithm can deal effectively with the reliability-based design of composites.展开更多
This study investigated total warpage of a type of motorcycle seat support made of polypropylene（PP） during the entire process of injection molding and free-cooling after demolding. Finite element modeling（FEM） an...This study investigated total warpage of a type of motorcycle seat support made of polypropylene（PP） during the entire process of injection molding and free-cooling after demolding. Finite element modeling（FEM） analysis for injection molding and its associated thermal deformation was carried out in the study. The effects of processing parameters on warpage occurring in different stages were analyzed by Taguchi optimization method. It was found that packing pressure is the major factor that affects warpage in the injection stage, whereas cooling time is the major factor in free-cooling stage. From an overall evaluation, melt temperature affects the total warpage most, followed by cooling time, packing pressure, packing time and mold temperature. The result proved that optimum parameters for minimizing final warpage of the injected parts can be obtained only when the deformation in the entire manufacturing process is addressed in both molding and demolding stages.展开更多
In the present work, we investigate the inverse problem of reconstructing the parameter of an integro-differential parabolic equation, which comes from pollution problems in porous media, when the final observation is...In the present work, we investigate the inverse problem of reconstructing the parameter of an integro-differential parabolic equation, which comes from pollution problems in porous media, when the final observation is given. We use the optimal control framework to establish both the existence and necessary condition of the minimizer for the cost func- tional. Furthermore, we prove the stability and the local uniqueness of the minimizer. Some numerical results will be presented and discussed.展开更多
文摘Deterministic optimization methods are combined with the Pareto front concept to solve multi-criterion design problems. The algorithm and the numerical implementation are applied to aerodynamic designs. Evolutionary algorithms （EAs） and the Pareto front concept are used to solve practical design problems in industry for its robustness in capturing convex, concave, discrete or discontinuous Pareto fronts of multi-objective optimization problems. However, the process is time-consuming. Therefore, deterministic optimization methods are introduced to capture the Pareto front, and the types of the captured Pareto front are explained. Numerical experiments show that the deterministic optimization method is a good alternative to EAs for capturing any convex and some concave Pareto fronts in multi-criterion aerodynamic optimization problems due to its efficiency.
文摘During the construction process of the construction project,the construction technology management work can improve the overall quality of the project construction.In the context of increasingly fierce competition in the construction market,construction enterprises should strengthen the management of construction technology,enhance their technical level and market competitiveness,and promote the development of the construction market[1].The paper mainly analyzes the optimization methods of build-Keywords:ing construction technology management.
基金Supported by the Natural Science Foundation of Hubei Province(2008CDZD47)
文摘In this paper, we present a large-update primal-dual interior-point method for symmetric cone optimization（SCO） based on a new kernel function, which determines both search directions and the proximity measure between the iterate and the center path. The kernel function is neither a self-regular function nor the usual logarithmic kernel function. Besides, by using Euclidean Jordan algebraic techniques, we achieve the favorable iteration complexity O（ √r（1/2）（log r）^2 log（r/ ε））, which is as good as the convex quadratic semi-definite optimization analogue.
基金Supported by the Beijing Municipal Science&Technology Commission(Z211100004421012),the Key Reaserch and Development Pro⁃gram of China(2022YFF0605902)。
文摘In this paper,a linear optimization method(LOM)for the design of terahertz circuits is presented,aimed at enhancing the simulation efficacy and reducing the time of the circuit design workflow.This method enables the rapid determination of optimal embedding impedance for diodes across a specific bandwidth to achieve maximum efficiency through harmonic balance simulations.By optimizing the linear matching circuit with the optimal embedding impedance,the method effectively segregates the simulation of the linear segments from the nonlinear segments in the frequency multiplier circuit,substantially improving the speed of simulations.The design of on-chip linear matching circuits adopts a modular circuit design strategy,incorporating fixed load resistors to simplify the matching challenge.Utilizing this approach,a 340 GHz frequency doubler was developed and measured.The results demonstrate that,across a bandwidth of 330 GHz to 342 GHz,the efficiency of the doubler remains above 10%,with an input power ranging from 98 mW to 141mW and an output power exceeding 13 mW.Notably,at an input power of 141 mW,a peak output power of 21.8 mW was achieved at 334 GHz,corresponding to an efficiency of 15.8%.
文摘Response analysis of structures involving non-probabilistic uncertain parameters can be closely related to optimization.This paper provides a review on optimization-based methods for uncertainty analysis,with focusing attention on specific properties of adopted numerical optimization approaches.We collect and discuss the methods based on nonlinear programming,semidefinite programming,mixed-integer programming,mathematical programming with complementarity constraints,difference-of-convex programming,optimization methods using surrogate models and machine learning techniques,and metaheuristics.As a closely related topic,we also overview the methods for assessing structural robustness using non-probabilistic uncertainty modeling.We conclude the paper by drawing several remarks through this review.
基金supported in part by the National Nature Science Foundation of China(62273239,62103283).
文摘Dear Editor,Pose graph optimization(PGO)is a popular optimization approach that plays a crucial role in the simultaneous localization and mapping(SLAM)back-end.However,when incorrect loop closure constraints(referred to as outliers)are present in the SLAM front-end,the standard PGO algorithm fails catastrophically and can not return an accurate map.To address this issue,this letter proposes a novel algorithm that leverages classical optimization methods to effectively handle outliers.The proposed algorithm introduces a new formulation that incorporates a credibility factor model,which improves the robustness of the optimization process.Additionally,an innovative consistency classification algorithm is developed to detect outliers.Extensive experiments are conducted on multiple benchmark datasets to evaluate the consistency and accuracy of the proposed algorithm.
基金Supported by National Natural Science Foundation of China(Grant No.51975025)National Key Research and Development Program of China(Grant No.2019YFB2004500)。
文摘The flow ripple caused by an axial piston pump may lead to pipe vibrations and lower hydraulic component reliability,which are of particular concern in hydraulic systems.The valve plate of the pump is considered the part most related to flow ripple,and its structural design is an important topic.In this study,an analytical model for the axial piston pump flow ripple was established and verified using a numerical analysis with computational fluid dynamics(CFD)calculations.Moreover,a parametric analysis of the valve plate was performed to investigate the critical parameters and their ranges.A fast optimization method,the rotation vector optimization method(RVOM),was proposed for the valve plate design and compared with the currently used optimization methods to prove its efficiency.As a constant-pressure pump works in different states of swashplate angle,outlet pressure,and pump speed,an optimization principle for the entire working status was proposed to achieve the overall reduction performance.A test rig for an aircraft hydraulic pump was established,and validation experiments were conducted.It was determined that the optimized pump could achieve reduction at multiple working statuses,and the largest pressure pulsation reduction ratios for the typical speed and speed sweep tests reached 64.7%and 71.7%,respectively.The model and method proposed in this study are proven to be effective and accurate.
基金supported by the National Natural Science Foundation of China (Grant Nos.40334040 and 40974033)the Promoting Foundation for Advanced Persons of Talent of NCWU
文摘Local and global optimization methods are widely used in geophysical inversion but each has its own advantages and disadvantages. The combination of the two methods will make it possible to overcome their weaknesses. Based on the simulated annealing genetic algorithm （SAGA） and the simplex algorithm, an efficient and robust 2-D nonlinear method for seismic travel-time inversion is presented in this paper. First we do a global search over a large range by SAGA and then do a rapid local search using the simplex method. A multi-scale tomography method is adopted in order to reduce non-uniqueness. The velocity field is divided into different spatial scales and velocities at the grid nodes are taken as unknown parameters. The model is parameterized by a bi-cubic spline function. The finite-difference method is used to solve the forward problem while the hybrid method combining multi-scale SAGA and simplex algorithms is applied to the inverse problem. The algorithm has been applied to a numerical test and a travel-time perturbation test using an anomalous low-velocity body. For a practical example, it is used in the study of upper crustal velocity structure of the A＇nyemaqen suture zone at the north-east edge of the Qinghai-Tibet Plateau. The model test and practical application both prove that the method is effective and robust.
文摘The principle of direct method used in optimal control problem is introduced. Details of applying this method to flight trajectory generation are presented including calculation of velocity and controls histories. And capabilities of flight and propulsion systems are considered also. Combined with digital terrain map technique, the direct method is applied to the three dimensional trajectory optimization for low altitude penetration, and simplex algorithm is used to solve the parameters in optimization. For the small number of parameters, the trajectory can be optimized in real time on board.
文摘This paper explores the convergence of a class of optimally conditioned self scaling variable metric (OCSSVM) methods for unconstrained optimization. We show that this class of methods with Wolfe line search are globally convergent for general convex functions.
基金The researchers would like to thank the Deanship of Graduate Studies and Scientific Research at Qassim University for financial support(QU-APC-2025)。
文摘The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management.Earlier approaches have often advanced one dimension—such as Internet of Things(IoT)-based data acquisition,Artificial Intelligence(AI)-driven analytics,or digital twin visualization—without fully integrating these strands into a single operational loop.As a result,many existing solutions encounter bottlenecks in responsiveness,interoperability,and scalability,while also leaving concerns about data privacy unresolved.This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing,distributed intelligence,and simulation-based decision support.The design incorporates multi-source sensor data,lightweight edge inference through Convolutional Neural Networks(CNN)and Long ShortTerm Memory(LSTM)models,and federated learning enhanced with secure aggregation and differential privacy to maintain confidentiality.A digital twin layer extends these capabilities by simulating city assets such as traffic flows and water networks,generating what-if scenarios,and issuing actionable control signals.Complementary modules,including model compression and synchronization protocols,are embedded to ensure reliability in bandwidth-constrained and heterogeneous urban environments.The framework is validated in two urban domains:traffic management,where it adapts signal cycles based on real-time congestion patterns,and pipeline monitoring,where it anticipates leaks through pressure and vibration data.Experimental results show a 28%reduction in response time,a 35%decrease in maintenance costs,and a marked reduction in false positives relative to conventional baselines.The architecture also demonstrates stability across 50+edge devices under federated training and resilience to uneven node participation.The proposed system provides a scalable and privacy-aware foundation for predictive urban infrastructure management.By closing the loop between sensing,learning,and control,it reduces operator dependence,enhances resource efficiency,and supports transparent governance models for emerging smart cities.
文摘Based on the optimization method, a new modified GM (1,1) model is presented, which is characterized by more accuracy prediction for the grey modeling.
基金This work was supported by the National Natural Science Foundation of China(10071037)
文摘In this paper, a new derivative free trust region method is developed based on the conic interpolation model for the unconstrained optimization. The conic interpolation model is built by means of the quadratic model function, the collinear scaling formula, quadratic approximation and interpolation. All the parameters in this model are determined by objective function interpolation condition. A new derivative free method is developed based upon this model and the global convergence of this new method is proved without any information on gradient.
基金Supported by the National Natural Science Foundation of China （20536020, 20876056）.
文摘Chemical batch processes have become significant in chemical manufacturing. In these processes, large numbers of chemical products are produced to satisfy human demands in daily life. Recently, economy globalization has resulted, in growing worldwide competitions in tradi.tional chemical .process industry. In order to keep competitive in the global marketplace, each company must optimize its production management and set up a reactive system for market fluctuation. Scheduling is the core of production management in chemical processes. The goal of this paper is to review the recent developments in this challenging area. Classifications of batch scheduling problems and optimization methods are introduced. A comparison of six typical models is shown in a general benchmark example from the literature. Finally, challenges and applications in future research are discussed.
基金supported by the National Natural Science Foundation of China (No. 51676163)the National 111 Project, China (No. B18041the Guangdong Basic and Applied Basic Research Foundation, China (No. 2019A1515111146)
文摘Attempts for higher output power and thermal efficiency of gas turbines make the inlet temperature of turbine to be far beyond the material melting temperature.Therefore,to protect the airfoil in gas turbine from hot gas and eventually prolong the lifetime of the blade,internal and film cooling structures with better thermal performance and cooling effectiveness are urgently needed.However,the traditional way of proceeding involves numerous simulations,additional experiments,and separate trials.Optimization of turbine cooling structures is an effective way to achieve better structures with higher overall performances while considering the multiple objectives,disciplines or subsystems.In this context,this paper reviews optimization research works on film cooling structures and internal cooling structures in gas turbines by means of various optimization methods.This review covers the following aspects:(A)optimization of film cooling conducted on flat plates and on turbine blades or vanes;(B)optimization of jet impingement cooling structures;(C)optimization of rib shapes,dimple shapes,pin–fin arrays in the cooling channels;(D)optimization of U-bend shaped cooling channels,and internal cooling systems of turbine blades or vanes.The review shows that through a reliable and accurate optimization procedure combined with conjugate heat transfer analysis,higher overall thermal performance can be acquired for single-objective or multi-objectives balanced by other constrained conditions.Future ways forward are pointed out in this review.
基金This study was funded by the National Natural Science Foundation of China(Grant 11272167).
文摘The discontinuous dynamical problem of multi-point contact and collision in multi-body system has always been a hot and difficult issue in this field.Based on the Gauss’principle of least constraint,a unified optimization model for multibody system dynamics with multi-point contact and collision is established.The paper presents the study of the numerical solution scheme,in which particle swarm optimization method is used to deal with the corresponding optimization model.The article also presents the comparison of the Gauss optimization method(GOM)and the hybrid linear complementarity method(i.e.combining differential algebraic equations(DAEs)and linear complementarity problems(LCP)),commonly used to solve the dynamic contact problem of multibody systems with bilateral constraints.The results illustrate that,the GOM has the same advantage of dynamical modelling with LCP and when the redundant constraint exists,the GOM always has a unique solution and so no additional processing is needed,whereas the corresponding DAE-LCP method may have singular cases with multiple solutions or no solutions.Using numerical examples,the GOM is verified to effectively solve the dynamics of multibody systems with redundant unilateral and bilateral constraints without additional redundancy processing.The GOM can also be applied to the optimal control of systems in the future and combined with the parameter optimization of systems to handle dynamic problems.The work given provides the dynamics and control of the complex system with a new train of thought and method.
基金supported by the National Natural Science Foundation of China(NSFC,Nos.51772205,51572192,51772208,51472179)the General Program of Municipal Natural Science Foundation of Tianjin(Nos.17JCYBJC17000,17JCYBJC22700)。
文摘Lithium-ion batteries(LIBs)have evolved into the mainstream power source of ene rgy sto rage equipment by reason of their advantages such as high energy density,high power,long cycle life and less pollution.With the expansion of their applications in deep-sea exploration,aerospace and military equipment,special working conditions have placed higher demands on the low-temperature performance of LIBs.However,at low temperatures,the severe polarization and inferior electrochemical activity of electrode materials cause the acute capacity fading upon cycling,which greatly hindered the further development of LIBs.In this review,we summarize the recent important progress of LIBs in low-temperature operations and introduce the key methods and the related action mechanisms for enhancing the capacity of the various cathode and anode materials.It aims to promote the development of high-performance electrode materials and broaden the application range of LIBs.
基金the National Natural Science Foundation of China(No.10772070)Ph.D Programs Foundation of Ministry of Education of China(No.20070487064).
文摘This paper proposed a reliability design model for composite materials under the mixture of random and interval variables. Together with the inverse reliability analysis technique, the sequential single-loop optimization method is applied to the reliability-based design of composites. In the sequential single-loop optimization, the optimization and the reliability analysis are decoupled to improve the computational efficiency. As shown in examples, the minimum weight problems under the constraint of structural reliability are solved for laminated composites. The Particle Swarm Optimization （PSO） algorithm is utilized to search for the optimal solutions. The design results indicate that, under the mixture of random and interval variables, the method that combines the sequential single-loop optimization and the PSO algorithm can deal effectively with the reliability-based design of composites.
基金supported by the Fundamental Research Funds for the Central Universities of China(No.CDJZR12110072)
文摘This study investigated total warpage of a type of motorcycle seat support made of polypropylene（PP） during the entire process of injection molding and free-cooling after demolding. Finite element modeling（FEM） analysis for injection molding and its associated thermal deformation was carried out in the study. The effects of processing parameters on warpage occurring in different stages were analyzed by Taguchi optimization method. It was found that packing pressure is the major factor that affects warpage in the injection stage, whereas cooling time is the major factor in free-cooling stage. From an overall evaluation, melt temperature affects the total warpage most, followed by cooling time, packing pressure, packing time and mold temperature. The result proved that optimum parameters for minimizing final warpage of the injected parts can be obtained only when the deformation in the entire manufacturing process is addressed in both molding and demolding stages.
基金supported in part by the CNRST Morocco,the Volkswagen Foundation:Grant number I/79315Hydromed project
文摘In the present work, we investigate the inverse problem of reconstructing the parameter of an integro-differential parabolic equation, which comes from pollution problems in porous media, when the final observation is given. We use the optimal control framework to establish both the existence and necessary condition of the minimizer for the cost func- tional. Furthermore, we prove the stability and the local uniqueness of the minimizer. Some numerical results will be presented and discussed.
