In this paper,an adaptive cubic regularisation algorithm based on affine scaling methods(ARCBASM)is proposed for solving nonlinear equality constrained programming with nonnegative constraints on variables.From the op...In this paper,an adaptive cubic regularisation algorithm based on affine scaling methods(ARCBASM)is proposed for solving nonlinear equality constrained programming with nonnegative constraints on variables.From the optimality conditions of the problem,we introduce appropriate affine matrix and construct an affine scaling ARC subproblem with linearized constraints.Composite step methods and reduced Hessian methods are applied to tackle the linearized constraints.As a result,a standard unconstrained ARC subproblem is deduced and its solution can supply sufficient decrease.The fraction to the boundary rule maintains the strict feasibility(for nonnegative constraints on variables)of every iteration point.Reflection techniques are employed to prevent the iterations from approaching zero too early.Under mild assumptions,global convergence of the algorithm is analysed.Preliminary numerical results are reported.展开更多
Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion...Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.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
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
The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly comple...The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.展开更多
Purpose–The study aims to build a high-precision longitudinal dynamics model for heavy-haul trains and validate it with line test data,present an optimization method for multi-stage cyclic brakes based on the model a...Purpose–The study aims to build a high-precision longitudinal dynamics model for heavy-haul trains and validate it with line test data,present an optimization method for multi-stage cyclic brakes based on the model and conduct a multi-objective detailed evaluation of the driver’s manipulation during cyclic braking.Design/methodology/approach–The high-precision longitudinal train dynamics model was established and verified by the cyclic braking test data of the 20,000 t heavy-haul combination train on the long and steep downgrade.Then the genetic algorithm is employed for optimization subsequent to decoupling multiple cyclic braking procedures,with due consideration of driver operation rules.For evaluation,key manipulation assessments in the scenario are prioritized,supplemented by multi-objective evaluation requirements,and the computational model is employed for detailed evaluation analysis.Findings–Based on the model,experimental data reveal that the probability of longitudinal force error being less than 64.6 kN is approximately 68%,95%for less than 129.2 kN and 99.7%for less than 193.8 kN.Upon optimizing manipulations during the cyclic braking,the maximum reduction in coupler force spans from 21%∼23.9%.Andtheevaluation scoresimply that a proper elevationof the releasingspeed favorssafety.A high electric braking force,although beneficial to some extent for energy-saving,is detrimental to reducing coupler force.Originality/value–The results will provide a theoretical basis and practical guidance for further ensuring the safety and energy-efficient operation of heavy haul trains on long downhill sections and improving the operational quality of heavy-haul trains.展开更多
Modern aircraft tend to use fuel thermal management systems to cool onboard heat sources.However,the design of heat transfer architectures for fuel thermal management systems relies on the experience of the engineers ...Modern aircraft tend to use fuel thermal management systems to cool onboard heat sources.However,the design of heat transfer architectures for fuel thermal management systems relies on the experience of the engineers and lacks theoretical guidance.This paper proposes a concise graph representation method based on graph theory for fuel thermal management systems,which can represent all possible connections between subsystems.A generalized optimization algorithm is proposed for fuel thermal management system architecture to minimize the heat sink.This algorithm can autonomously arrange subsystems with heat production differences and efficiently utilize the architecture of the fuel heat sink.At the same time,two evaluation indices are proposed from the perspective of subsystems.These indices intuitively and clearly show that the reason for the high efficiency of heat sink utilization is the balanced and moderate cooling of each subsystem and verify the rationality of the architecture optimization method.A set of simulations are also conducted,which demonstrate that the fuel tank temperature has no effect on the performance of the architecture.This paper provides a reference for the architectural design of aircraft fuel thermal management systems.The metrics used in this paper can also be utilized to evaluate the existing architecture.展开更多
In this paper,a topology optimization method for coordinated stiffness and strength design is proposed under mass constraints,utilizing the Solid Isotropic Material with Penalization approach.Element densities are reg...In this paper,a topology optimization method for coordinated stiffness and strength design is proposed under mass constraints,utilizing the Solid Isotropic Material with Penalization approach.Element densities are regulated through sensitivity filtering tomitigate numerical instabilities associatedwith stress concentrations.Ap-norm aggregation function is employed to globalize local stress constraints,and a normalization technique linearly weights strain energy and stress,transforming the multi-objective problem into a single-objective formulation.The sensitivity of the objective function with respect to design variables is rigorously derived.Three numerical examples are presented,comparing the optimized structures in terms of strain energy,mass,and stress across five different mathematical models with varying combinations of optimization objectives.The results validate the effectiveness and feasibility of the proposed method for achieving a balanced design between structural stiffness and strength.This approach offers a new perspective for future research on stiffness-strength coordinated structural optimization.展开更多
The application of multi-material topology optimization affords greater design flexibility compared to traditional single-material methods.However,density-based topology optimization methods encounter three unique cha...The application of multi-material topology optimization affords greater design flexibility compared to traditional single-material methods.However,density-based topology optimization methods encounter three unique challenges when inertial loads become dominant:non-monotonous behavior of the objective function,possible unconstrained characterization of the optimal solution,and parasitic effects.Herein,an improved Guide-Weight approach is introduced,which effectively addresses the structural topology optimization problem when subjected to inertial loads.Smooth and fast convergence of the compliance is achieved by the approach,while also maintaining the effectiveness of the volume constraints.The rational approximation of material properties model and smooth design are utilized to guarantee clear boundaries of the final structure,facilitating its seamless integration into manufacturing processes.The framework provided by the alternating active-phase algorithm is employed to decompose the multi-material topological problem under inertial loading into a set of sub-problems.The optimization of multi-material under inertial loads is accomplished through the effective resolution of these sub-problems using the improved Guide-Weight method.The effectiveness of the proposed approach is demonstrated through numerical examples involving two-phase and multi-phase materials.展开更多
Aiming at the missile avoidance problem of the unmanned aerial vehicle(UAV)in complex obstacle environments,this work proposes a collision-avoidance method based on receding horizon optimization.The proposed method ge...Aiming at the missile avoidance problem of the unmanned aerial vehicle(UAV)in complex obstacle environments,this work proposes a collision-avoidance method based on receding horizon optimization.The proposed method generated a specific trajectory for the UAV to effectively induce the proportional navigation missile to successfully intercept the obstacle,thereby accomplishing the evasive maneuver.The evasive maneuver was divided into two distinct stages,namely the collision-inducing phase and the fast departure phase.The obstacle potential field-based target selection algorithm was employed to identify the most appropriate target obstacle,while the induced trajectory was determined through a combination of receding horizon optimization and the hp-adaptive pseudo-spectral method.Simulation experiments were carried out under three different types of obstacle environments and one multiobstacle environment,and the simulation results show that the method proposed in this paper greatly improves the success rate of UAV evasive maneuvers,proving the effectiveness of this method.展开更多
Parameterized level-set method(PLSM)has been proposed and developed for many years,and is renowned for its efficacy in ad-dressing topology optimization challenges associated with intricate boundaries and nucleation o...Parameterized level-set method(PLSM)has been proposed and developed for many years,and is renowned for its efficacy in ad-dressing topology optimization challenges associated with intricate boundaries and nucleation of new holes.However,most pertinent investigations in the field rely predominantly on fixed background mesh,which is never remeshed.Consequently,the mesh element partitioned by material interface during the optimization process necessitates approximation by using artificial interpolation models to obtain its element stiffness or other properties.This paper introduces a novel approach to topology op-timization by integrating the PLSM with body-fitted adaptive mesh and Helmholtz-type filter.Primarily,combining the PLSM with body-fitted adaptive mesh enables the regeneration of mesh based on the zero level-set interface.This not only precludes the direct traversal of the material interface through the mesh element during the topology optimization process,but also improves the accuracy of calculation.Additionally,the incorporation of a Helmholtz-type partial differential equation filter,relying solely on mesh information essential for finite element discretization,serves to regulate the topological complexity and the minimum feature size of the optimized structure.Leveraging these advantages,the topology optimization program demonstrates its versa-tility by successfully addressing various design problems,encompassing the minimum mean compliance problem and minimum energy dissipation problem.Ultimately,the result of numerical example indicates that the optimized structure exhibits a dis-tinct and smooth boundary,affirming the effective control over both topological complexity and the minimum feature size of the optimized structure.展开更多
The traditional topology optimization method of continuum structure generally uses quadrilateral elements as the basic mesh.This approach often leads to jagged boundary issues,which are traditionally addressed through...The traditional topology optimization method of continuum structure generally uses quadrilateral elements as the basic mesh.This approach often leads to jagged boundary issues,which are traditionally addressed through post-processing,potentially altering the mechanical properties of the optimized structure.A topology optimization method of Movable Morphable Smooth Boundary(MMSB)is proposed based on the idea of mesh adaptation to solve the problem of jagged boundaries and the influence of post-processing.Based on the ICM method,the rational fraction function is introduced as the filtering function,and a topology optimization model with the minimum weight as the objective and the displacement as the constraint is established.A triangular mesh is utilized as the base mesh in this method.The mesh is re-divided in the optimization process based on the contour line,and a smooth boundary parallel to the contour line is obtained.Numerical examples demonstrate that the MMSB method effectively resolves the jagged boundary issues,leading to enhanced structural performance.展开更多
Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanism...Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanisms in these multi-layer composites is essential,as it offers intuitive insights into parametric influences and facilitates enhanced structural performance.This paper employs an improved transfer matrix method to address the limitations of existing theoretical approaches for analyzing multi-layer composite structures.By establishing a twodimensional composite pavement model,it investigates load transfer characteristics and validates the accuracy through finite element simulation.The proposed method offers a straightforward analytical approach for examining internal interactions between structural layers.Case studies indicate that the concrete surface layer is the main load-bearing layer for most vertical normal and shear stresses.The soil base layer reduces the overall mechanical response of the substructure,while horizontal actions increase the risk of interfacial slip and cracking.Structural optimization analysis demonstrates that increasing the thickness of the concrete surface layer,enhancing the thickness and stiffness of the soil base layer,or incorporating gradient layers can significantly mitigate these risks of interfacial slip and cracking.The findings of this study can guide the optimization design,parameter analysis,and damage prevention of multi-layer composite structures.展开更多
In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to ...In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.展开更多
The quasi-rectangular tunnel represents a novel cross-section design,intended to supersede the traditional circular and rectangular tunnel formats.Due to the limited capacity of the tunnel vault to withstand vertical ...The quasi-rectangular tunnel represents a novel cross-section design,intended to supersede the traditional circular and rectangular tunnel formats.Due to the limited capacity of the tunnel vault to withstand vertical loads,an interior column is often installed at the center to enhance its load-bearing capacity.This study aims to develop a hyperstatic reaction method(HRM)for the analysis of deformation and structural integrity in this specific tunnel type.The computational model is validated through comparison with the corresponding finite element method(FEM)analysis.Following comprehensive validation,an ensemble machine learning(ML)model is proposed,using numerical benchmark data,to facilitate real-time design and optimization.Subsequently,three widely used ensemble models,i.e.random forest(RF),gradient boosting decision tree(GBDT),and extreme gradient boosting(XGBoost)are compared to identify the most efficient ML model for replacing the HRM model in the design optimization process.The performance metrics,such as the coefficient of determination R2 of about 0.999 and the mean absolute percentage error(MAPE)of about 1%,indicate that XGBoost outperforms the others,exhibiting excellent agreement with the HRM analysis.Additionally,the model demonstrates high computational efficiency,with prediction times measured in seconds.Finally,the HRM-XGBoost model is integrated with the well-known particle swarm optimization(PSO)for the real-time design optimization of quasi-rectangular tunnels,both with and without the interior column.A feature importance assessment is conducted to evaluate the sensitivity of design input features,enabling the selection of the most critical features for the optimization task.展开更多
In this paper,we develop an advanced computational framework for the topology optimization of orthotropic materials using meshless methods.The approximation function is established based on the improved moving least s...In this paper,we develop an advanced computational framework for the topology optimization of orthotropic materials using meshless methods.The approximation function is established based on the improved moving least squares(IMLS)method,which enhances the efficiency and stability of the numerical solution.The numerical solution formulas are derived using the improved element-free Galerkin(IEFG)method.We introduce the solid isotropic microstructures with penalization(SIMP)model to formulate a mathematical model for topology opti-mization,which effectively penalizes intermediate densities.The optimization problem is defined with the numerical solution formula and volume fraction as constraints.The objective function,which is the minimum value of flexibility,is optimized iteratively using the optimization criterion method to update the design variables efficiently and converge to an optimal solution.Sensitivity analysis is performed using the adjoint method,which provides accurate and efficient gradient information for the optimization algorithm.We validate the proposed framework through a series of numerical examples,including clamped beam,cantilever beam,and simply supported beam made of orthotropic materials.The convergence of the objective function is demonstrated by increasing the number of iterations.Additionally,the stability of the iterative process is analyzed by examining the fluctuation law of the volume fraction.By adjusting the parameters to an appropriate range,we achieve the final optimization results of the IEFG method without the checkerboard phenomenon.Comparative studies between the Element-Free Galerkin(EFG)and IEFG methods reveal that both methods yield consistent optimization results under identical parameter settings.However,the IEFG method significantly reduces computational time,highlighting its efficiency and suitability for orthotropic materials.展开更多
To establish the optimal reference trajectory for a near-space vehicle under free terminal time,a time-optimal model predictive static programming method is proposed with adaptive fish swarm optimization.First,the mod...To establish the optimal reference trajectory for a near-space vehicle under free terminal time,a time-optimal model predictive static programming method is proposed with adaptive fish swarm optimization.First,the model predictive static programming method is developed by incorporating neighboring terms and trust region,enabling rapid generation of precise optimal solutions.Next,an adaptive fish swarm optimization technique is employed to identify a sub-optimal solution,while a momentum gradient descent method with learning rate decay ensures the convergence to the global optimal solution.To validate the feasibility and accuracy of the proposed method,a near-space vehicle example is analyzed and simulated during its glide phase.The simulation results demonstrate that the proposed method aligns with theoretical derivations and outperforms existing methods in terms of convergence speed and accuracy.Therefore,the proposed method offers significant practical value for solving the fast trajectory optimization problem in near-space vehicle applications.展开更多
The process of including renewable energy sources in power networks is moving quickly,so the need for innovative configuration solutions for grid-side ESS has grown.Among the new methods presented in this paper is GA-...The process of including renewable energy sources in power networks is moving quickly,so the need for innovative configuration solutions for grid-side ESS has grown.Among the new methods presented in this paper is GA-OCESE,which stands for Genetic Algorithm-based Optimization Configuration for Energy Storage in Electric Networks.This is one of the methods suggested in this study,which aims to enhance the sizing,positioning,and operational characteristics of structured ESS under dynamic grid conditions.Particularly,the aim is to maximize efficiency.A multiobjective genetic algorithm,the GA-OCESE framework,considers all these factors simultaneously.Besides considering cost-efficiency,response time,and energy use,the system also considers all these elements simultaneously.This enables it to effectively react to load uncertainty and variations in inputs connected to renewable sources.Results of an experimental assessment conducted on a standardized grid simulation platform indicate that by increasing energy use efficiency by 17.6%and reducing peak-load effects by 22.3%,GA-OCESE outperforms previous heuristic-based methods.This was found by contrasting the outcomes of the assessment with those of the evaluation.The results of the assessment helped to reveal this.The proposed approach will provide utility operators and energy planners with a decision-making tool that is both scalable and adaptable.This technology is particularly well-suited for smart grids,microgrid systems,and power infrastructures that heavily rely on renewable energy.Every technical component has been carefully recorded to ensure accuracy,reproducibility,and relevance across all power systems engineering software uses.This was done to ensure the program’s relevance.展开更多
Red-green-blue(RGB)beam combiners are widely used in scenarios such as augmented reality/virtual reality(AR/VR),laser projection,biochemical detection,and other fields.Optical waveguide combiners have attracted extens...Red-green-blue(RGB)beam combiners are widely used in scenarios such as augmented reality/virtual reality(AR/VR),laser projection,biochemical detection,and other fields.Optical waveguide combiners have attracted extensive attention due to their advantages of small size,high multiplexing efficiency,convenient mass production,and low cost.An RGB beam combiner based on directional couplers is designed,with a core-cladding relative refractive index difference of 0.75%.The RGB beam combiner is optimized from the perspective of parameter optimization.Using the beam propagation method(BPM),the relationship between the performance of the RGB beam combiner and individual parameters is studied,achieving preliminary optimization of the device’s performance.The key parameters of the RGB beam combiner are optimized using the entropy weight-technique for order preference by similarity to an ideal solution TOPSIS method,establishing the optimal parameter scheme and further improving the device’s performance indicators.The results show that after optimization,the multiplexing efficiencies for red,green,and blue lights,as well as the average multiplexing efficiency,reached 99.17%,99.76%,96.63%and 98.52%,respectively.The size of the RGB beam combiner is 4.768 mm×0.062 mm.展开更多
Obtaining residual stress is crucial for controlling the machining deformation in annular parts,and can directly influence the performance and stability of key components in advanced equipment.Since existing research ...Obtaining residual stress is crucial for controlling the machining deformation in annular parts,and can directly influence the performance and stability of key components in advanced equipment.Since existing research has achieved global residual stress field inference for components by using the deformation force-based method where the deformation force is monitored during the machining process,reliable acquisition of deformation force stll remains a significant challenge under complex machining conditions.This paper proposes a hierarchical optimization method for the layout of deformation force monitoring of annular parts.The proposed method establishes two optimization objectives by analyzing the relationship between the deformation force and the residual stress in annular parts,i.e.,equivalence and ilconditioning of solving process.Specifically,the equivalence of the monitored deformation force and residual stress in terms of effect on caused machining deformation is evaluated by local deformation,and the illconditioning is also optimized to enhance the stability of residual stress inference.Verification is implemented in both simulation and actual machining experiments,demonstrating effectiveness of the proposed layout optimization method in inferring residual stress field of annular parts with deformation force.展开更多
基金Supported by the National Natural Science Foundation of China(12071133)Natural Science Foundation of Henan Province(252300421993)Key Scientific Research Project of Higher Education Institutions in Henan Province(25B110005)。
文摘In this paper,an adaptive cubic regularisation algorithm based on affine scaling methods(ARCBASM)is proposed for solving nonlinear equality constrained programming with nonnegative constraints on variables.From the optimality conditions of the problem,we introduce appropriate affine matrix and construct an affine scaling ARC subproblem with linearized constraints.Composite step methods and reduced Hessian methods are applied to tackle the linearized constraints.As a result,a standard unconstrained ARC subproblem is deduced and its solution can supply sufficient decrease.The fraction to the boundary rule maintains the strict feasibility(for nonnegative constraints on variables)of every iteration point.Reflection techniques are employed to prevent the iterations from approaching zero too early.Under mild assumptions,global convergence of the algorithm is analysed.Preliminary numerical results are reported.
文摘Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.
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%.
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financially supported by Guangdong Province Basic and Applied Basic Research Fund Project(Grant No.2022B1515250009)Liaoning Provincial Natural Science Foundation-Doctoral Research Start-up Fund Project(Grant No.2024-BSBA-05)+1 种基金Major Science and Technology Innovation Project in Shandong Province(Grant No.2024CXGC010803)the National Natural Science Foundation of China(Grant Nos.52271269 and 12302147).
文摘The umbilical,a key component in offshore energy extraction,plays a vital role in ensuring the stable operation of the entire production system.The extensive variety of cross-sectional components creates highly complex layout combinations.Furthermore,due to constraints in component quantity and geometry within the cross-sectional layout,filler bodies must be incorporated to maintain cross-section performance.Conventional design approaches based on manual experience suffer from inefficiency,high variability,and difficulties in quantification.This paper presents a multi-level automatic filling optimization design method for umbilical cross-sectional layouts to address these limitations.Initially,the research establishes a multi-objective optimization model that considers compactness,balance,and wear resistance of the cross-section,employing an enhanced genetic algorithm to achieve a near-optimal layout.Subsequently,the study implements an image processing-based vacancy detection technique to accurately identify cross-sectional gaps.To manage the variability and diversity of these vacant regions,the research introduces a multi-level filling method that strategically selects and places filler bodies of varying dimensions,overcoming the constraints of uniform-size fillers.Additionally,the method incorporates a hierarchical strategy that subdivides the complex cross-section into multiple layers,enabling layer-by-layer optimization and filling.This approach reduces manufac-turing equipment requirements while ensuring practical production process feasibility.The methodology is validated through a specific umbilical case study.The results demonstrate improvements in compactness,balance,and wear resistance compared with the initial cross-section,offering novel insights and valuable references for filler design in umbilical cross-sections.
文摘Purpose–The study aims to build a high-precision longitudinal dynamics model for heavy-haul trains and validate it with line test data,present an optimization method for multi-stage cyclic brakes based on the model and conduct a multi-objective detailed evaluation of the driver’s manipulation during cyclic braking.Design/methodology/approach–The high-precision longitudinal train dynamics model was established and verified by the cyclic braking test data of the 20,000 t heavy-haul combination train on the long and steep downgrade.Then the genetic algorithm is employed for optimization subsequent to decoupling multiple cyclic braking procedures,with due consideration of driver operation rules.For evaluation,key manipulation assessments in the scenario are prioritized,supplemented by multi-objective evaluation requirements,and the computational model is employed for detailed evaluation analysis.Findings–Based on the model,experimental data reveal that the probability of longitudinal force error being less than 64.6 kN is approximately 68%,95%for less than 129.2 kN and 99.7%for less than 193.8 kN.Upon optimizing manipulations during the cyclic braking,the maximum reduction in coupler force spans from 21%∼23.9%.Andtheevaluation scoresimply that a proper elevationof the releasingspeed favorssafety.A high electric braking force,although beneficial to some extent for energy-saving,is detrimental to reducing coupler force.Originality/value–The results will provide a theoretical basis and practical guidance for further ensuring the safety and energy-efficient operation of heavy haul trains on long downhill sections and improving the operational quality of heavy-haul trains.
文摘Modern aircraft tend to use fuel thermal management systems to cool onboard heat sources.However,the design of heat transfer architectures for fuel thermal management systems relies on the experience of the engineers and lacks theoretical guidance.This paper proposes a concise graph representation method based on graph theory for fuel thermal management systems,which can represent all possible connections between subsystems.A generalized optimization algorithm is proposed for fuel thermal management system architecture to minimize the heat sink.This algorithm can autonomously arrange subsystems with heat production differences and efficiently utilize the architecture of the fuel heat sink.At the same time,two evaluation indices are proposed from the perspective of subsystems.These indices intuitively and clearly show that the reason for the high efficiency of heat sink utilization is the balanced and moderate cooling of each subsystem and verify the rationality of the architecture optimization method.A set of simulations are also conducted,which demonstrate that the fuel tank temperature has no effect on the performance of the architecture.This paper provides a reference for the architectural design of aircraft fuel thermal management systems.The metrics used in this paper can also be utilized to evaluate the existing architecture.
基金funded by National Nature Science Foundation of China(92266203)National Nature Science Foundation of China(52205278)+1 种基金Key Projects of Shijiazhuang Basic Research Program(241791077A)Central Guide Local Science and Technology Development Fund Project of Hebei Province(246Z1022G).
文摘In this paper,a topology optimization method for coordinated stiffness and strength design is proposed under mass constraints,utilizing the Solid Isotropic Material with Penalization approach.Element densities are regulated through sensitivity filtering tomitigate numerical instabilities associatedwith stress concentrations.Ap-norm aggregation function is employed to globalize local stress constraints,and a normalization technique linearly weights strain energy and stress,transforming the multi-objective problem into a single-objective formulation.The sensitivity of the objective function with respect to design variables is rigorously derived.Three numerical examples are presented,comparing the optimized structures in terms of strain energy,mass,and stress across five different mathematical models with varying combinations of optimization objectives.The results validate the effectiveness and feasibility of the proposed method for achieving a balanced design between structural stiffness and strength.This approach offers a new perspective for future research on stiffness-strength coordinated structural optimization.
基金supported by the National Natural Science Foundation of China(Grant No.52172356)the Hunan Provincial Natural Science Foundation of China(Grant No.2022JJ10012).
文摘The application of multi-material topology optimization affords greater design flexibility compared to traditional single-material methods.However,density-based topology optimization methods encounter three unique challenges when inertial loads become dominant:non-monotonous behavior of the objective function,possible unconstrained characterization of the optimal solution,and parasitic effects.Herein,an improved Guide-Weight approach is introduced,which effectively addresses the structural topology optimization problem when subjected to inertial loads.Smooth and fast convergence of the compliance is achieved by the approach,while also maintaining the effectiveness of the volume constraints.The rational approximation of material properties model and smooth design are utilized to guarantee clear boundaries of the final structure,facilitating its seamless integration into manufacturing processes.The framework provided by the alternating active-phase algorithm is employed to decompose the multi-material topological problem under inertial loading into a set of sub-problems.The optimization of multi-material under inertial loads is accomplished through the effective resolution of these sub-problems using the improved Guide-Weight method.The effectiveness of the proposed approach is demonstrated through numerical examples involving two-phase and multi-phase materials.
基金Natural Science Foundation of Heilongjiang Province of China(Grant No.YQ2022F012)the Fundamental Research Funds for the Central Universities(Grant No.HIT.OCEF.2023010)to provide fund for conducting experiments.
文摘Aiming at the missile avoidance problem of the unmanned aerial vehicle(UAV)in complex obstacle environments,this work proposes a collision-avoidance method based on receding horizon optimization.The proposed method generated a specific trajectory for the UAV to effectively induce the proportional navigation missile to successfully intercept the obstacle,thereby accomplishing the evasive maneuver.The evasive maneuver was divided into two distinct stages,namely the collision-inducing phase and the fast departure phase.The obstacle potential field-based target selection algorithm was employed to identify the most appropriate target obstacle,while the induced trajectory was determined through a combination of receding horizon optimization and the hp-adaptive pseudo-spectral method.Simulation experiments were carried out under three different types of obstacle environments and one multiobstacle environment,and the simulation results show that the method proposed in this paper greatly improves the success rate of UAV evasive maneuvers,proving the effectiveness of this method.
基金supported by the National Natural Science Foundation of China(Grant Nos.12372200 and 12072242).
文摘Parameterized level-set method(PLSM)has been proposed and developed for many years,and is renowned for its efficacy in ad-dressing topology optimization challenges associated with intricate boundaries and nucleation of new holes.However,most pertinent investigations in the field rely predominantly on fixed background mesh,which is never remeshed.Consequently,the mesh element partitioned by material interface during the optimization process necessitates approximation by using artificial interpolation models to obtain its element stiffness or other properties.This paper introduces a novel approach to topology op-timization by integrating the PLSM with body-fitted adaptive mesh and Helmholtz-type filter.Primarily,combining the PLSM with body-fitted adaptive mesh enables the regeneration of mesh based on the zero level-set interface.This not only precludes the direct traversal of the material interface through the mesh element during the topology optimization process,but also improves the accuracy of calculation.Additionally,the incorporation of a Helmholtz-type partial differential equation filter,relying solely on mesh information essential for finite element discretization,serves to regulate the topological complexity and the minimum feature size of the optimized structure.Leveraging these advantages,the topology optimization program demonstrates its versa-tility by successfully addressing various design problems,encompassing the minimum mean compliance problem and minimum energy dissipation problem.Ultimately,the result of numerical example indicates that the optimized structure exhibits a dis-tinct and smooth boundary,affirming the effective control over both topological complexity and the minimum feature size of the optimized structure.
基金supported by the National Natural Science Foundation of China(Grant 12472113).
文摘The traditional topology optimization method of continuum structure generally uses quadrilateral elements as the basic mesh.This approach often leads to jagged boundary issues,which are traditionally addressed through post-processing,potentially altering the mechanical properties of the optimized structure.A topology optimization method of Movable Morphable Smooth Boundary(MMSB)is proposed based on the idea of mesh adaptation to solve the problem of jagged boundaries and the influence of post-processing.Based on the ICM method,the rational fraction function is introduced as the filtering function,and a topology optimization model with the minimum weight as the objective and the displacement as the constraint is established.A triangular mesh is utilized as the base mesh in this method.The mesh is re-divided in the optimization process based on the contour line,and a smooth boundary parallel to the contour line is obtained.Numerical examples demonstrate that the MMSB method effectively resolves the jagged boundary issues,leading to enhanced structural performance.
基金supported by Fundamental Research Funds for the Central Universities(No.lzujbky-2024-05)Innovation Foundation of Provincial Education Department of Gansu(2024B-005)+2 种基金Scientific Department of Gansu(24CXGA083,24CXGA024,JK2024-28,JK2024-32 and 23CXJA0007)Industrial Support Plan Project of Provincial Education Department of Gansu(2025CYZC-003 and CYZC-2024-10)the Hunan Natural Science Foundation Science and Education Joint Fund Project(2022JJ60109).
文摘Transportation structures such as composite pavements and railway foundations typically consist of multi-layered media designed to withstand high bearing capacity.A theoretical understanding of load transfer mechanisms in these multi-layer composites is essential,as it offers intuitive insights into parametric influences and facilitates enhanced structural performance.This paper employs an improved transfer matrix method to address the limitations of existing theoretical approaches for analyzing multi-layer composite structures.By establishing a twodimensional composite pavement model,it investigates load transfer characteristics and validates the accuracy through finite element simulation.The proposed method offers a straightforward analytical approach for examining internal interactions between structural layers.Case studies indicate that the concrete surface layer is the main load-bearing layer for most vertical normal and shear stresses.The soil base layer reduces the overall mechanical response of the substructure,while horizontal actions increase the risk of interfacial slip and cracking.Structural optimization analysis demonstrates that increasing the thickness of the concrete surface layer,enhancing the thickness and stiffness of the soil base layer,or incorporating gradient layers can significantly mitigate these risks of interfacial slip and cracking.The findings of this study can guide the optimization design,parameter analysis,and damage prevention of multi-layer composite structures.
基金Supported in part by Natural Science Foundation of Guangxi(2023GXNSFAA026246)in part by the Central Government's Guide to Local Science and Technology Development Fund(GuikeZY23055044)in part by the National Natural Science Foundation of China(62363003)。
文摘In this paper,we consider the maximal positive definite solution of the nonlinear matrix equation.By using the idea of Algorithm 2.1 in ZHANG(2013),a new inversion-free method with a stepsize parameter is proposed to obtain the maximal positive definite solution of nonlinear matrix equation X+A^(*)X|^(-α)A=Q with the case 0<α≤1.Based on this method,a new iterative algorithm is developed,and its convergence proof is given.Finally,two numerical examples are provided to show the effectiveness of the proposed method.
基金funded by the Hanoi University of Mining and Geology(Grant No.T23-44)The research is also funded by the German Research Foundation(DFG e Project number 518862444)in collaboration with the Vietnam National Foundation for Science and Technology Development(NAFOSTED)under grant number DFG.105e2022.03The third author was funded by the Postdoctoral Scholarship Program of the Vingroup Innovation Foundation(VINIF)(VINIF.2023.STS.15).
文摘The quasi-rectangular tunnel represents a novel cross-section design,intended to supersede the traditional circular and rectangular tunnel formats.Due to the limited capacity of the tunnel vault to withstand vertical loads,an interior column is often installed at the center to enhance its load-bearing capacity.This study aims to develop a hyperstatic reaction method(HRM)for the analysis of deformation and structural integrity in this specific tunnel type.The computational model is validated through comparison with the corresponding finite element method(FEM)analysis.Following comprehensive validation,an ensemble machine learning(ML)model is proposed,using numerical benchmark data,to facilitate real-time design and optimization.Subsequently,three widely used ensemble models,i.e.random forest(RF),gradient boosting decision tree(GBDT),and extreme gradient boosting(XGBoost)are compared to identify the most efficient ML model for replacing the HRM model in the design optimization process.The performance metrics,such as the coefficient of determination R2 of about 0.999 and the mean absolute percentage error(MAPE)of about 1%,indicate that XGBoost outperforms the others,exhibiting excellent agreement with the HRM analysis.Additionally,the model demonstrates high computational efficiency,with prediction times measured in seconds.Finally,the HRM-XGBoost model is integrated with the well-known particle swarm optimization(PSO)for the real-time design optimization of quasi-rectangular tunnels,both with and without the interior column.A feature importance assessment is conducted to evaluate the sensitivity of design input features,enabling the selection of the most critical features for the optimization task.
基金supported by the Graduate Student Scientific Research Innovation Project through Research Innovation Fund for Graduate Students in Shanxi Province(Project No.2024KY648).
文摘In this paper,we develop an advanced computational framework for the topology optimization of orthotropic materials using meshless methods.The approximation function is established based on the improved moving least squares(IMLS)method,which enhances the efficiency and stability of the numerical solution.The numerical solution formulas are derived using the improved element-free Galerkin(IEFG)method.We introduce the solid isotropic microstructures with penalization(SIMP)model to formulate a mathematical model for topology opti-mization,which effectively penalizes intermediate densities.The optimization problem is defined with the numerical solution formula and volume fraction as constraints.The objective function,which is the minimum value of flexibility,is optimized iteratively using the optimization criterion method to update the design variables efficiently and converge to an optimal solution.Sensitivity analysis is performed using the adjoint method,which provides accurate and efficient gradient information for the optimization algorithm.We validate the proposed framework through a series of numerical examples,including clamped beam,cantilever beam,and simply supported beam made of orthotropic materials.The convergence of the objective function is demonstrated by increasing the number of iterations.Additionally,the stability of the iterative process is analyzed by examining the fluctuation law of the volume fraction.By adjusting the parameters to an appropriate range,we achieve the final optimization results of the IEFG method without the checkerboard phenomenon.Comparative studies between the Element-Free Galerkin(EFG)and IEFG methods reveal that both methods yield consistent optimization results under identical parameter settings.However,the IEFG method significantly reduces computational time,highlighting its efficiency and suitability for orthotropic materials.
基金supported by the National Science Foundation for Distinguished Young Scholars of China(No.52425212)National Key Research and Development Program of China(No.2021YFA0717100)National Natural Science Foundation of China(Nos.12072270,U2013206,and 52442214).
文摘To establish the optimal reference trajectory for a near-space vehicle under free terminal time,a time-optimal model predictive static programming method is proposed with adaptive fish swarm optimization.First,the model predictive static programming method is developed by incorporating neighboring terms and trust region,enabling rapid generation of precise optimal solutions.Next,an adaptive fish swarm optimization technique is employed to identify a sub-optimal solution,while a momentum gradient descent method with learning rate decay ensures the convergence to the global optimal solution.To validate the feasibility and accuracy of the proposed method,a near-space vehicle example is analyzed and simulated during its glide phase.The simulation results demonstrate that the proposed method aligns with theoretical derivations and outperforms existing methods in terms of convergence speed and accuracy.Therefore,the proposed method offers significant practical value for solving the fast trajectory optimization problem in near-space vehicle applications.
文摘The process of including renewable energy sources in power networks is moving quickly,so the need for innovative configuration solutions for grid-side ESS has grown.Among the new methods presented in this paper is GA-OCESE,which stands for Genetic Algorithm-based Optimization Configuration for Energy Storage in Electric Networks.This is one of the methods suggested in this study,which aims to enhance the sizing,positioning,and operational characteristics of structured ESS under dynamic grid conditions.Particularly,the aim is to maximize efficiency.A multiobjective genetic algorithm,the GA-OCESE framework,considers all these factors simultaneously.Besides considering cost-efficiency,response time,and energy use,the system also considers all these elements simultaneously.This enables it to effectively react to load uncertainty and variations in inputs connected to renewable sources.Results of an experimental assessment conducted on a standardized grid simulation platform indicate that by increasing energy use efficiency by 17.6%and reducing peak-load effects by 22.3%,GA-OCESE outperforms previous heuristic-based methods.This was found by contrasting the outcomes of the assessment with those of the evaluation.The results of the assessment helped to reveal this.The proposed approach will provide utility operators and energy planners with a decision-making tool that is both scalable and adaptable.This technology is particularly well-suited for smart grids,microgrid systems,and power infrastructures that heavily rely on renewable energy.Every technical component has been carefully recorded to ensure accuracy,reproducibility,and relevance across all power systems engineering software uses.This was done to ensure the program’s relevance.
基金Project(52175445)supported by the National Natural Science Foundation of ChinaProject(2022JJ30743)supported by the Natural Science Foundation of Hunan Province,China+1 种基金Project(2023GK2024)supported by the Key Research and Development Program of Hunan Province,ChinaProject(2023ZZTS0391)supported by the Fundamental Research Funds for the Central Universities of China。
文摘Red-green-blue(RGB)beam combiners are widely used in scenarios such as augmented reality/virtual reality(AR/VR),laser projection,biochemical detection,and other fields.Optical waveguide combiners have attracted extensive attention due to their advantages of small size,high multiplexing efficiency,convenient mass production,and low cost.An RGB beam combiner based on directional couplers is designed,with a core-cladding relative refractive index difference of 0.75%.The RGB beam combiner is optimized from the perspective of parameter optimization.Using the beam propagation method(BPM),the relationship between the performance of the RGB beam combiner and individual parameters is studied,achieving preliminary optimization of the device’s performance.The key parameters of the RGB beam combiner are optimized using the entropy weight-technique for order preference by similarity to an ideal solution TOPSIS method,establishing the optimal parameter scheme and further improving the device’s performance indicators.The results show that after optimization,the multiplexing efficiencies for red,green,and blue lights,as well as the average multiplexing efficiency,reached 99.17%,99.76%,96.63%and 98.52%,respectively.The size of the RGB beam combiner is 4.768 mm×0.062 mm.
基金supported in part by the General Program of the National Natural Science Foundation of China(No.52175467)the National Key R&D Program of China(No.2022YFB3402600).
文摘Obtaining residual stress is crucial for controlling the machining deformation in annular parts,and can directly influence the performance and stability of key components in advanced equipment.Since existing research has achieved global residual stress field inference for components by using the deformation force-based method where the deformation force is monitored during the machining process,reliable acquisition of deformation force stll remains a significant challenge under complex machining conditions.This paper proposes a hierarchical optimization method for the layout of deformation force monitoring of annular parts.The proposed method establishes two optimization objectives by analyzing the relationship between the deformation force and the residual stress in annular parts,i.e.,equivalence and ilconditioning of solving process.Specifically,the equivalence of the monitored deformation force and residual stress in terms of effect on caused machining deformation is evaluated by local deformation,and the illconditioning is also optimized to enhance the stability of residual stress inference.Verification is implemented in both simulation and actual machining experiments,demonstrating effectiveness of the proposed layout optimization method in inferring residual stress field of annular parts with deformation force.
