Multi-Objective Optimization of VBHF in Deep Drawing Based on the Improved QO-Jaya Algorithm

Blank holder force(BHF)is a crucial parameter in deep drawing,having close relation with the forming quality of sheet metal.However,there are different BHFs maintaining the best forming effect in different stages of deep drawing.The variable blank holder force(VBHF)varying with the drawing stage can overcome this problem at an extent.The optimization of VBHF is to determine the optimal BHF in every deep drawing stage.In this paper,a new heuristic optimization algorithm named Jaya is introduced to solve the optimization efficiently.An improved“Quasi-oppositional”strategy is added to Jaya algorithm for improving population diversity.Meanwhile,an innovated stop criterion is added for better convergence.Firstly,the quality evaluation criteria for wrinkling and tearing are built.Secondly,the Kriging models are developed to approximate and quantify the relation between VBHF and forming defects under random sampling.Finally,the optimization models are established and solved by the improved QO-Jaya algorithm.A VBHF optimization example of component with complicated shape and thin wall is studied to prove the effectiveness of the improved Jaya algorithm.The optimization results are compared with that obtained by other algorithms based on the TOPSIS method.

基于TLBO算法的不确定性条件下复杂产品协同设计的可靠性拓扑优化

复杂产品的拓扑优化设计可以显著节省材料和节能,有效地降低惯性力和机械振动。本研究以一种大吨位液压机作为典型的复杂产品,用于阐述该优化方法。本文提出了一种基于可靠性与优化解耦模型和基于教学学习的优化(TLBO)算法的可靠性拓扑优化方法。将由板结构形成的支撑物作为拓扑优化对象,重量轻、稳定性好。将不确定性下的可靠性优化和结构拓扑优化协同处理。首先,利用有限差分法将优化问题中的不确定性参数修正为确定性参数。然后,将不确定性可靠性分析和拓扑优化的复杂嵌套解耦。最后,利用TLBO算法求解解耦模型,该算法参数少,求解速度快。TLBO算法采用了自适应教学因子,在初始阶段实现了更快的收敛速度,并在后期进行了更精细的搜索。本文给出了一个液压机基板结构的数值实例,说明了该方法的有效性。

Construction of Human Digital Twin Model Based on Multimodal Data and Its Application in Locomotion Mode Identifcation

With the increasing attention to the state and role of people in intelligent manufacturing, there is a strong demand for human-cyber-physical systems (HCPS) that focus on human-robot interaction. The existing intelligent manufacturing system cannot satisfy efcient human-robot collaborative work. However, unlike machines equipped with sensors, human characteristic information is difcult to be perceived and digitized instantly. In view of the high complexity and uncertainty of the human body, this paper proposes a framework for building a human digital twin (HDT) model based on multimodal data and expounds on the key technologies. Data acquisition system is built to dynamically acquire and update the body state data and physiological data of the human body and realize the digital expression of multi-source heterogeneous human body information. A bidirectional long short-term memory and convolutional neural network (BiLSTM-CNN) based network is devised to fuse multimodal human data and extract the spatiotemporal features, and the human locomotion mode identifcation is taken as an application case. A series of optimization experiments are carried out to improve the performance of the proposed BiLSTM-CNN-based network model. The proposed model is compared with traditional locomotion mode identifcation models. The experimental results proved the superiority of the HDT framework for human locomotion mode identifcation.

Complicated deformation simulating on temperature-driven 4D printed bilayer structures based on reduced bilayer plate model

The four-dimensional(4D) printing technology, as a combination of additive manufacturing and smart materials, has attracted increasing research interest in recent years. The bilayer structures printed with smart materials using this technology can realize complicated deformation under some special stimuli due to the material properties.The deformation prediction of bilayer structures can make the design process more rapid and thus is of great importance. However, the previous works on deformation prediction of bilayer structures rarely study the complicated deformations or the influence of the printing process on deformation. Thus, this paper proposes a new method to predict the complicated deformations of temperature-sensitive 4D printed bilayer structures,in particular to the bilayer structures based on temperature-driven shape-memory polymers(SMPs) and fabricated using the fused deposition modeling(FDM) technology. The programming process to the material during printing is revealed and considered in the simulation model. Simulation results are compared with experiments to verify the validity of the method. The advantages of this method are stable convergence and high efficiency,as the three-dimensional(3D) problem is converted to a two-dimensional(2D) problem.The simulation parameters in the model can be further associated with the printing parameters, which shows good application prospect in 4D printed bilayer structure design.

Layout design and application of 4D-printing bio-inspired structures with programmable actuators

Four-dimensional(4D)printing is an advanced form of three-dimensional(3D)printing with controllable and programmable shape transformation over time.Actuators are used as a controlling factor with multi-stage shape recovery,with emerging opportunities to customize the mechanical properties of bio-inspired structures.The print pattern of shape memory polymer(SMP)fbers strongly afects the achievable resolution,and consequently infuences several other physical and mechanical properties of fabricated actuators.However,the deformations of bio-inspired structures due to actuator layout are more complex because of the presence of the coupling of multi-directional strain.In this study,the initial structure was designed from closed-shell behavior and divided into a general unit and actuator unit,the latter responsible for driving the transformation.Mutual stress confrontation between the actuator and the general unit was considered in the layout thermodynamic model,in order to eliminate the transformation produced by the uncontrolled shape memory behavior of the general unit.Three critical and efective strategies for the layout design of actuators were proposed and then applied to achieve the desired accurate deformation of 3D-printed bilayer structures.Finally,the proposed approach was validated and adopted for fabricating a complex shell-like gripper structure.

Simulation model of self-organizing pedestrian movement considering following behavior

在本文中一种新的力学模型被引入到社会力模型中,用来仿真相向行人流中的跟随行为。这种跟随行为指的是行人通过接近同向行人以避免与反向行人冲突的行为。新的力学模型类似于一种引力模型,在建模过程中考虑了行人的视野范围、自身的运动状态、被跟随行人的运动状态等因素。我们利用新的力学模型对相向行人流进行了仿真,研究了跟随行为对渠化现象、行人间冲突以及双向通道通行效率的影响。仿真结果表明:跟随行为能促进渠化现象形成,并能起到缓解相向行人流拥堵的作用;跟随行为具有降低相向行人流冲突次数的作用,这种作用在入口流量较低时并不明显,但随着行人流量的升高而增强。跟随行为能够提高双向通道的通行效率,并且跟随行为的强度参数越大通道的通行效率越高。

Prediction of medium-to-coal ratio effect in a dense medium cyclone by using both traditional and coarse-grained CFD-DEM models

Dense medium cyclone(DMC)is the working horse in coal industry.In practice,it is usually operated under constant pressure and the operational conditions(mainly medium-to-coal(M:C)ratio and oper-ational pressure)need to be adjusted according to coal washability data(mainly coal particle size and density distributions).Nonetheless,until now it is still not well understood how the M:C ratio would affect the performance of DMCs especially under the practical conditions.In this work,the effect of M:C ratio is for the first time numerically studied under conditions similar to plant operation by using both tra-ditional and coarse-grained(CG)combined approach of computational fluid dynamics(CFD)and discrete element method(DEM),called as traditional CFD-DEM and CG CFD-DEM,in which the flow of coal par-ticles is modelled by DEM or CG DEM which applies Newton's laws of motion to individual particles and that of medium flow by the conventional CFD which solves the local-averaged Navier-Stokes equations,allowing consideration of particle-fluid mutual interaction and particle-particle collisions.Moreover,impulse and momentum connection law is used to achieve energy conservation between traditional CFD-DEM and CG CFD-DEM.It is found that under constant pressure,the M:C ratio affects DMC perfor-mance significantly.The specific effect depends on coal washability or coal type.Under extremely low M:C ratio,the phenomenon that high-quality coal product is misplaced to reject is successfully repro-duced,which has been observed in plants in Australian coal industry and called as"low-density tail".Moreover,strategies are proposed to mitigate the"low-density tail"phenomenon based on the model.