Dynamic Optimization Design Research Articles

Reducing undesirable effects of revolute joint clearances on the dynamic performance of spatial parallel mechanism

To mitigate the adverse effects of joint clearances on the dynamic performance of mechanisms, it is essential to investigate the dynamic optimization design of spatial parallel mechanisms with clearances. Currently, there are many studies on the dynamic characteristics of mechanisms with clearances, but there are few studies on dynamic optimization design of mechanisms with clearances, especially on the optimization design of parallel mechanisms with clearances. Therefore, the dynamic optimization design of 3-RRPaR (R stands for revolute joint, Pa stands for quadrilateral structure) parallel mechanism with dry friction clearance of revolute joints is studied. The dynamic model of the parallel mechanism with revolute joint clearance is derived. On these grounds, the dynamic response of the end actuator, the contact collision force at the clearance joint, and their weighted combination are defined as objective functions, respectively. The mass and moment of inertia of the end actuator are taken as optimization variables. A mathematical model for the dynamic optimization design of the parallel mechanism considering dry friction clearances is developed, and the optimal mass and moment of inertia of the end actuator are obtained by G-MSRS method. This study comparatively analyzes the dynamic characteristics of parallel mechanisms with clearances before and after optimization. The results indicate that dynamic optimization significantly enhances the dynamic characteristics of the mechanism. This study lays a theoretical foundation for dynamic optimization design of parallel mechanisms with clearances.

Dynamic response and optimal design of aluminum foam sandwich circular tubes with V-shaped constraint under lateral blast loading

Dynamic response and optimal design of aluminum foam sandwich circular tubes with V-shaped constraint under lateral blast loading

Cyclic chromatography processes as hybrid systems: Dynamic simulation and optimal design for 5-HMF/water separation

Cyclic chromatography processes as hybrid systems: Dynamic simulation and optimal design for 5-HMF/water separation

Damped nonlinear normal modes of bistable nonlinear energy sink for steady-state dynamic analysis and optimal design

Damped nonlinear normal modes of bistable nonlinear energy sink for steady-state dynamic analysis and optimal design

Dynamic characteristics analysis and optimization design of medical grinding machine

In order to improve the stability and reliability of medicinal grinding machine, reduce vibration and noise, and enhance the strength of load-bearing, a scheme for optimizing dynamic response characteristics without increasing mass was proposed based on multi-objective optimization methods. Using the finite element method, the modal analysis was conducted on the entire model of the grinding machine to determine its natural frequencies and vibration modes. The structural optimization design was carried out with the optimization goal of having a sixth-order natural frequency below 30 Hz and a seventh-order natural frequency above 100 Hz. The stress distribution was obtained by conducting the strength analysis on the connecting rod structure. The optimization design of the structure was carried out with the minimum value of the stress peak and the maximum value of the fatigue safety factor as the optimization objectives. The results show that the multi-objective optimization method can make the equipment avoid the resonance zone and reduce the peak stress, which is of great significance for improving the performance of the medical grinding machine.

Dynamic write-voltage design and read-voltage optimization for MLC NAND flash memory

Dynamic write-voltage design and read-voltage optimization for MLC NAND flash memory

Dynamic optimization design of thin plate structure based on surrogate model

Abstract To enhance dynamic optimization efficiency in traditional thin plate structures, surrogate models are integrated for structural dynamic size optimization, reducing dependence on high-precision finite element simulations. This paper focuses on optimizing the aluminum alloy sheet as the subject of research. The parameters of the specimen are optimized through sensitivity analysis, based on the comparison between the free mode Finite Element Analysis (FEA) and Experimental Modal Analysis (EMA) results. The modified specimen undergoes validation under a four-edge clamped boundary condition. Subsequently, random vibration analysis is conducted to determine the root mean square (RMS) value of the acceleration response. Employing surrogate model technology, four models are constructed using parametric modeling and experimental design methods. These models are then compared for their fitting effectiveness. The results indicate that the RBF model exhibits the highest accuracy in fitting each response, effectively replacing dynamic simulation. Finally, the RBF combined with the NSGA-II method, optimizes the specimen’s structural size, resulting in a 21.6% reduction in mass and an 18.60% decrease in acceleration response. These outcomes demonstrate satisfactory optimization results, ensuring accuracy while enhancing the dynamic characteristics of the specimen structure. This research offers valuable insights for related engineering applications.

Reliable simulation analysis for high-temperature inrush water hazard based on the digital twin model of tunnel geological environment

In complex mountainous terrains, tunnel construction faces unique challenges from high-temperature water inrush hazards, a systemic risk arising from the interplay of stress, seepage, and temperature fields. Traditional simulation methods, focusing on isolated disaster scenarios, fall short in addressing the multifaceted nature of these risks due to geological ambiguity and data incompleteness. Digital twin technology presents an effective solution to these challenges; however, its core challenge lies in how to utilize digital twin technology for data-model-co-driven simulation analysis of coupled multi-physical fields in situations of incomplete data. This paper introduces a digital twin paradigm for the simulation analysis of water inrush, which significantly enhances efficiency and accuracy through the integration of advanced machine learning and finite element analysis techniques. Specifically, this is achieved by combining a high-precision geological modeling method based on Gaussian Processes (GP) with a parameter calibration method through Gaussian Process-Differential Evolution (GP-DE) back-analysis. Firstly, a voxel structure is utilized to integrate the multi-field attribute features of the tunnel environment. Secondly, through the integration of multi-source advanced geological prediction data, we construct a dynamic digital twin model of the tunnel environment leveraging machine learning techniques. To overcome the issue of low modeling accuracy, the GP is employed, enhancing the exploitation of latent information within multi-source geophysical data. Lastly, we utilize the GP-DE back-analysis method to calibrate the parameters of the tunnel environment, thereby enhancing the precision and reliability of water inrush simulations. The method has been validated through application to a section of an ultra-high-temperature water inrush tunnel in China, featuring a burial depth of 230 meters. The accuracy of the method is corroborated by the monitoring data from the tunnel, supporting dynamic optimization design and safety prevention measures during construction.

Dynamic simulation and optimal design of a combined cold and power system with 10 MW compressed air energy storage and integrated refrigeration

A combined cold and power system with 10 MW compressed air energy storage and integrated refrigeration (CCR) is proposed. In traditional 10 MW compressed air energy storage (CAES) system, outlet pressure of air tank is throttled to a low pressure by throttling device. In CCR system, the throttling device is replaced by a piston turbine to achieve control of pressure and mass flow. Meanwhile, pressure potential energy of compressed air is converted to mechanical work, which is used to drive refrigeration subsystem. The dynamic mathematic model of proposed CCR system is built up. According to energy and exergy analysis of the whole dynamic process, it is confirmed that the proposed model obeys the first and second laws of thermodynamics. The optimal solution for T23 and γAC are calculated to be 259.6896 K and 1.2335, respectively. The Pareto frontier of multi-objective optimization of energy and exergy efficiencies are conducted. Energy efficiency of proposed CCR system is higher than that of CAES system by at least 32.8 %. The electrical efficiency of proposed CCR system is also higher than that of CAES system. It suggests that the pressure potential energy wasted in the throttle process is well utilized by the piston turbine in CCR system.

Dynamic optimization design of open-pit mine full-boundary slope considering uncertainty of rock mass strength

Rock and soil strength profoundly influences the stability of open-pit mine slopes. Traditional slope design, based on limited drilling data, often disregards inherent uncertainties. Effectively utilizing new sample information from mining operations poses a challenge, hindering dynamic and differentiated design for the entire perimeter slope. To address this, we propose a dynamic optimization method considering rock mass strength uncertainty for the entire perimeter slope. Our approach involves designing slope angles separately in different zones, while thoroughly considering decision-makers' preferences. Furthermore, we delegate the final adjustment authority of slope angles within the safety permissible range to on-site decision-makers. Compared to traditional methods, our dynamic design method incorporates rock mass strength uncertainty into slope evaluation while also accounting for decision-makers' safety and economic preferences. Through a case study of a specific open-pit mine, our proposed dynamic design method increases the overall slope angle by approximately 2.5°, fully accommodating the influence of on-site decision-making preferences on slope design. This article introduces a new method of dynamic optimization of open-pit mine slope based on simplified observation method, which improves the flexibility of decision-making and realizes the differential design of the whole surrounding slope.

Generalized model for eigenfrequency analysis of bolted variable-stiffness flanged-cylindrical shells

A general semi-analytical modeling method for the bolted variable stiffness composite cylindrical shell, incorporating precise modeling of the boundary and connecting flanges, is proposed in this paper. The coupling between shells and flanges is achieved through a spring-based penalty function method. A novel bolted joint model for flange connections is introduced, enabling the simulation of non-uniform pressure distributions at the joint interface. The joint model features a stiffness characterization technique that effectively improves adjustability and computational efficiency. The correctness and accuracy of the proposed modeling method are systematically validated through finite element analysis based on the ANSYS commercial software and experimental testing approaches. The series of parameter influence analyses on the bolted variable stiffness composite cylindrical shell with flanges, conducted using the proposed modeling method, accurately demonstrate the influence of geometric dimensions, fiber layup parameters, and bolt parameters on the free vibration behavior of such structures. Furthermore, these analyses aid in a deeper understanding of the dynamic characteristics of such structures, partially highlighting key design considerations and offering valuable guidance for their dynamic optimization design.

Dynamic power matching for wheel loader based on power reflux hydrodynamic transmission system

The power reflux hydrodynamic transmission system (PRHTS) has the advantages of flexible transmission, low-speed torque multiplication, adaptive adjustment of speed ratio to external load, and improved torque converter (TC) transmission efficiency. Therefore, it is highly suitable for wheel loaders. Wheel loaders usually work in harsh environments with complex and changing working conditions, and static power matching makes it challenging to fully utilize wheel loaders’ performance. In response to the above issues, this paper proposes a dynamic power matching optimization design method for PRHTS with capacity adjustment gear (CAG) based on wheel loader. The optimization design method obtains data through V-shaped working condition experiments of the wheel loader, and conducts clustering analysis on the data to obtain high-frequency kinematic segments and their characteristic parameters. On this basis, combined with the analysis of the working principle of PRHTS, the system structural parameters are optimized and designed. Compared with static power matching, the dynamic power matching optimization design method increases the average traction force by 4.9 kN, improves the transmission efficiency by 2.6%, reduces the average fuel consumption rate by 3.66 g (kW·h)−1, and reduces the fuel consumption per V-cycle by 27.7 ml in V-shaped working conditions.

Cellular gradient algorithm for solving complex mechanical optimization design problems

In mechanical optimization design problems, there are often some non-continuous or non-differentiable objective functions. For these non-continuous and non-differentiable optimization objectives, it is often difficult for existing optimal design algorithms to find the desired optimal solutions. In this paper, we incorporate the idea of gradient descent into cellular automata and propose a Cellular Gradient (CG) method. First, we have given the basic rules and algorithmic framework of CG and designed three kinds of growth and extinction rules respectively. Then, the three evolutionary rules for cellular within a single cycle are analyzed separately for form and ordering. The best expressions for the cellular jealous neighbor rule and the solitary regeneration rule are given, and the most appropriate order in which the rules are run is selected. Finally, the solution results of the cellular gradient algorithm and other classical optimization design algorithms are compared with a multi-objective multi-parameter mechanical optimization design problem as an example. The computational results show that the cellular gradient algorithm has an advantage over other algorithms in solving global and dynamic mechanical optimal design problems. The novelty of CG is to provide a new way of thinking for solving optimization problems with global discontinuities.

An XYZ parallel nanopositioning stage with hybrid damping

It is well known that lightly damping linear dynamics of a piezo-hysteresis-compensated flexure-based stage severely limits its motion control bandwidth. To address it, a novel damped XYZ parallel flexure-based nanopositioning stage (3⊥(P⊥K∥K), P for prismatic, K for Cardan or Universal) with hybrid passive damping, which is composed of shearing–squeezing hinge damping and in-band damping by graded local resonators (GLRs), is presented. The dynamic modeling and optimization design are implemented based on the maximization of motion amplification ratio, first-order natural frequency, and inverse in-band H2 norm of frequency response function (FRF). The optimized GLR module has distributed dynamic characteristics. The approximate motion decoupling is verified by Jacobin matrix analysis and experiments. The static/scanning-frequency dynamic experiments and step/triangular trajectory tracking control with the low-order controllers for all-hinge damping and hybrid damping stages are implemented. The experimental results indicate the small crosstalks due to hybrid passive damping, as the static crosstalks in X-to-Z and Y-to-Z are 0.293% and 0.276%, respectively, and the dynamic crosstalks in X-to-Z and Y-to-Z are 0.922% and 0.910%, respectively. The capability of improving positioning precision and expanding control bandwidth by hybrid damping only with a low-order controller is also validated experimentally.

Multi-level dynamic zoning design to improve the restorative capability of resilience: An emergence response in water contamination flushing

ABSTRACT The conventional district metered areas (DMAs) bounded by closed valves reduce space of emergency response actions to cope with system failure or emergency events for resilience improvement. In order to improve the restorative capability of a zoning water distribution system (WDS), a novel dynamic DMA optimization design method and a coupled emergency response strategy are proposed. A multi-level zoning method is applied to determine optimization of water source areas (WSAs), pressure management areas (PMAs), and dynamic DMAs. A coupled emergency response strategy of WDS zoning, valve closure, hydrant flushing, and dynamic DMA adjustment is proposed and validated in a real large-scale water distribution network. The results show that the coupled emergency response strategy based on dynamic DMA can enhance capacity for dynamic emergency response and improve resilience during contamination flushing.

An investigation into the effects of profile shifts on helical gear mesh stiffness

Time-varying meshing stiffness (TVMS) is a significant nonlinear periodic excitation in helical gears, it poses significant impacts on gear system’s dynamic characteristics and fatigue life. However, the specific impact of profile shift on it remains unclear. This article establishes an analytical model for the TVMS of helical gears by utilizing the slicing method to address this gap based on the potential energy method, and quantitatively analyze the TVMS with different modification coefficients. The research found that the helical gear’s TVMS decreases with the increase of modification coefficient for individual profile shifts. For the equal compound profile shifts, it rises with the increase of modification coefficient of pinion. For the unequal compound profile shifts, the positive drive increases the TVMS, but the negative drive to the contrary. The research achievements provide valuable guidelines for dynamic design and structure optimization for helical gears.

TD3-BC-PPO: Twin delayed DDPG-based and behavior cloning-enhanced proximal policy optimization for dynamic optimization affine formation

This article addresses the dynamic optimal design problem of the affine formation for adversarial multi-agent systems in real-time confrontation environments. To maximize the win rate and maximize the battle damage ratio, a novel deep reinforcement learning (DRL) algorithm named TD3-BC-PPO is designed to adaptively control the shape transformation of affine formation, including translation, rotation, and scaling. Specifically, Twin Delayed Deep Deterministic Policy Gradient (TD3) is introduced to enhance the exploratory aspect of the strategy and efficiently leverage the crucial sparse win–loss rewards. Behavior cloning (BC) is used for strategy replication and model migration. Proximal policy optimization (PPO) is utilized for stabilizing policy updates, conducting a secondary optimization of the strategy through dense damage-related rewards. To validate the effectiveness and robustness of the proposed algorithm, extensive simulation experiments are conducted. Comparative analyses are performed against several baselines, encompassing a diverse range of formation confrontation situations. These situations involve various initial formation structures, differing attack angles, unequal combat quantity and expanded confrontation space dimensions. Simulation results show that the proposed TD3-BC-PPO algorithm can engender an impressive surge of at least 5.4% in the win rate and an incremental ascent of at least 0.274 in the battle damage ratio of the affine formation for adversarial multi-agent systems in complex real-time confrontation scenarios.

A hybrid numerical model for horizontal ground heat exchanger

The horizontal ground heat exchanger (HGHE) possesses a complicated heat transfer mechanism as its extensive spatial scale, long operational duration, and vulnerability to meteorological conditions. Consequently, the long-period simulations of HGHE usually involve significant computational costs, posing challenges for its dynamic optimization implementation. Therefore, this study initially established and validated a conventional numerical (full-order) model for HGHE as the reference model. Subsequently, a hybrid model was developed using the proposed adaptive proper orthogonal decomposition (POD) method. By analyzing the influential characteristics, the study identified the solution strategy and the key parameter values for adaptive POD, followed by the generality tests. The hybrid model proved to successfully mitigate the issue of error accumulation commonly associated with native POD extrapolation. Finally, employing a long-running engineering case study, the accuracy and the solution efficiency of the hybrid model were compared against those of the conventional (full-order) model. The results demonstrated that the hybrid model maintained computational accuracy at a comparable level while exhibiting a computational efficiency 326 % higher than that of the conventional (full-order) model, without requiring additional computational resources. This study can provide efficient modeling support for the dynamic optimization design of HGHE.

Dynamic responses of cylindrical lithium-ion battery under localized impact loading

Engineering problems, such as fire and explosion caused by mechanical damage, have restricted the further development of lithium-ion batteries (LIBs). The paper aims to present an effective method for studying the impact responses of cylindrical LIBs under localized impact loadings. An impact model in which the cell is simplified to a beam is developed considering the interaction between bending and stretching. The membrane factor (fn ) of the beam with a circular cross-section is introduced, and then the motion control equations for the cell with large deformation are derived. The accuracy of the theoretical method is verified based on the results from the mass block impact experiment and finite element simulation. A method for cell failure detection is established based on the force-displacement-voltage response from the impact experiment. It is shown that higher impact velocities and smaller punch widths increase cell deformation. Moreover, a larger punch mass results in greater displacement when the impact energy remains unchanged, and the strengthening tendency increases with the punch width. The research will provide theoretical guidance for the safety assessment and dynamic optimization design of LIBs.

Dynamic analysis of drag-based vibratory swimmers using higher-order averaging

This paper discusses the mathematical modeling, dynamic analysis, and design optimization of a class of drag-based vibratory swimmers using averaging. A typical swimmer of this class consists of a surface or subsurface main body, an oscillatory mass inside the body, and a rigid fin attached to the main body using torsional springs and immersed in water. This paper takes advantage of third-order averaging techniques for dynamic analysis and design optimization of the swimmer for high frequencies. The averaged dynamics are used for determining the optimum stiffness of the springs for maximizing the average speed of the swimmer for high-frequency motion of the oscillatory mass. Experimental results confirm the general response of the mathematical model.