Model reduction for nonlinear multiscale parabolic problems using dynamic mode decomposition

In this article, a model reduction technique is presented to solve nonlinear multiscale parabolic problems using dynamic mode decomposition. The multiple scales and nonlinearity bring great challenges for simulating the problems. To overcome this difficulty, we develop a model reduction method for the nonlinear multiscale dynamic problems by integrating constraint energy minimizing generalized multiscale finite element method (CEM-GMsFEM) with dynamic mode decomposition (DMD). CEM-GMsFEM has shown great efficiency to solve linear multiscale problems in a coarse space. However, using CEM-GMsFEM to directly solve multiscale nonlinear parabolic models involves dynamically computing the residual and the Jacobian on a fine grid. This may be very computationally expensive because the evaluation of the nonlinear term is implemented in a high-dimensional fine scale space. As a data-driven method, DMD can use observation data and give an explicit expression to accurately describe the underlying nonlinear dynamic system. To efficiently compute the multiscale nonlinear parabolic problems, we propose a CEM-DMD model reduction by combing CEM-GMsFEM and DMD. The CEM-DMD reduced model is a coarsen linear model, which avoids the nonlinear solver in the fine space. It is crucial to judiciously choose observation in DMD. Only proper observation can render an accurate DMD model. In the context of CEM-DMD, we introduce two different observations: fine scale observation and coarse scale observation. In the construction of DMD model, the coarse scale observation requires much less computation than the fine scale observation. The CEM-DMD model using the coarse scale observation gives a complete coarse model for the nonlinear multiscale dynamic systems and significantly improves the computation efficiency. To show the performance of the CEM-DMD using the different observations, we present a few numerical results for the nonlinear multiscale parabolic problems in heterogeneous porous media.     

Study and evaluation of abrasive water jet turning process performance on AA5083

In this study, the effect of processing parameters on surface roughness and macro surface characteristics was analyzed during the machining of Ø30 mm and 300 mm aluminum alloy AA5083 abrasive water jets. As the processing parameters (up to 10 mm min⁻¹, 15 mm min⁻¹, 20 mm min⁻¹ and 25 mm min⁻¹), abrasive flow rate (50 g min⁻¹, 150 g min⁻¹, 250 g min⁻¹ and 350 g min⁻¹), the lathe chuck rotational speed (25 min⁻¹, 50 min⁻¹, 75 min⁻¹ and 100 min⁻¹) and the nozzle approach distance (2 mm, 5 mm, 8 mm and 11 mm) were used in experiments. In experimental studies, the pump pressure (360 MPa) was used as a constant, in the form of an abrasive Garnet (100 mesh), and the nozzle diameter as 0.76 mm. According to the findings, the best results in terms of surface roughness were obtained as a result of turning speed and abrasive flow rate. When the macro surface characteristics were examined, it was found that the lathe chuck rotational speed increased, the rate of nozzle progression was low, the rate of abrasive flow was high and the nozzle approach distance was lower and the smoother surfaces were obtained.     

Numerical simulation of the effects of elastic anisotropy and grain size upon the machining of AA2024

Turning modeling and simulation of different metallic materials using the commercially available Finite Element (FE) softwares is getting prime importance because of saving of time and money in comparison to the costly experiments. Mostly, the numerical analysis of machining process considers a purely isotropic behavior of metallic materials; however, the literature shows that the elastic crystal anisotropy is present in most of the ‘so-called’ isotropic materials. In the present work, the elastic anisotropy is incorporated in the FE simulations along with the effect of grain size. A modified Johnson-Cook ductile material model based on coupled plasticity and damage evolution has been proposed to model the cutting process. The simulation results were compared with experimental data on the turning process of Aluminum alloy (AA2024). It was found that the elastic anisotropy influences the average cutting force up to 5% as compared to the isotropic models while the effect of grain size was more pronounced up to 20%.     

High-Speed Trains Automatic Operation with Protection Constraints: A Resilient Nonlinear Gain-based Feedback Control Approach

This paper addresses the control design for automatic train operation of high-speed trains with protection constraints. A new resilient nonlinear gain-based feedback control approach is proposed, which is capable of guaranteeing, under some proper non-restrictive initial conditions, the protection constraints control raised by the distance-to-go (moving authority) curve and automatic train protection in practice. A new hyperbolic tangent function-based model is presented to mimic the whole operation process of high-speed trains. The proposed feedback control methods are easily implementable and computationally inexpensive because the presence of only two feedback gains guarantee satisfactory tracking performance and closed-loop stability, no adaptations of unknown parameters, function approximation of unknown nonlinearities, and attenuation of external disturbances in the proposed control strategies. Finally, rigorous proofs and comparative simulation results are given to demonstrate the effectiveness of the proposed approaches.      

Suppression of diamond tool wear in machining of tungsten carbide by combining ultrasonic vibration and electrochemical processing

As an important ceramic material, tungsten carbide (WC) is utilized as the typical mold in precision glass molding, which has replaced conventional grinding and polishing to provide a highly replicative process for mass manufacturing of optical glass components. Ultra-precision grinding, which is time consuming and has low reproducibility, is the only method to machine such WC molds to high profile accuracy. Although diamond turning is the most widely used machining method for fabrication of optical molds made of metals, diamond turning of WC is still considered challenging due to fast abrasive wear of the diamond tool caused by high brittleness and hardness of WC. Ultrasonic vibration cutting has been proven to be helpful in realizing ductile-mode machining of brittle materials, but its tool life is still not long enough to be utilized in practical diamond turning of optical WC molds. In the current study, a hybrid method is proposed to combine electrochemical processing of WC workpiece surface into the diamond turning process. Cutting tests on WC using poly-crystalline diamond tools were conducted to evaluate its effect on improvement of tool wear and surface quality. Validation cutting tests using single crystal diamond tools has proven that the proposed hybrid method is able to significantly reduce the diamond tool wear and improve the surface quality of machined ultra-fine grain WC workpiece compared to ultrasonic vibration cutting without electrochemical processing.     

Novel method of constructing generalized Hoberman sphere mechanisms based on deployment axes

This study proposes a method of constructing type II generalized angulated elements (GAEs II) Hoberman sphere mechanisms on the basis of deployment axes that intersect at one point. First, the constraint conditions for inserting n GAEs II into n deployment axes to form a loop are given. The angle constraint conditions of the deployment axes are obtained through a series of linear equations. Second, the connection conditions of two GAEs II loops that share a common deployable center are discussed. Third, a flowchart of constructing the generalized Hoberman sphere mechanism on the basis of deployment axes is provided. Finally, four generalized Hoberman sphere mechanisms based on a fully enclosed regular hexahedron, arithmetic sequence axes, orthonormal arithmetic sequence axes, and spiral-like axes are constructed in accordance with the given arrangement of deployment axes that satisfy the constraint conditions to verify the feasibility of the proposed method.     

Isogeometric topology optimization based on energy penalization for symmetric structure

We present an energy penalization method for isogeometric topology optimization using moving morphable components (ITO–MMC), propose an ITO–MMC with an additional bilateral or periodic symmetric constraint for symmetric structures, and then extend the proposed energy penalization method to an ITO–MMC with a symmetric constraint. The energy penalization method can solve the problems of numerical instability and convergence for the ITO–MMC and the ITO–MMC subjected to the structural symmetric constraint with asymmetric loads. Topology optimization problems of asymmetric, bilateral symmetric, and periodic symmetric structures are discussed to validate the effectiveness of the proposed energy penalization approach. Compared with the conventional ITO–MMC, the energy penalization method for the ITO–MMC can improve the convergence rate from 18.6% to 44.5% for the optimization of the asymmetric structure. For the ITO–MMC under a bilateral symmetric constraint, the proposed method can reduce the objective value by 5.6% and obtain a final optimized topology that has a clear boundary with decreased iterations. For the ITO–MMC under a periodic symmetric constraint, the proposed energy penalization method can dramatically reduce the number of iterations and obtain a speedup of more than 2.     

Unsupervised regions based segmentation using object discovery

We present a new unsupervised algorithm to discovery and segment out common objects from multiple images. Compared with previous cosegmentation methods, our algorithm performs well even when the appearance variations in the foregrounds are more substantial than those in some areas of the backgrounds. Our algorithm mainly includes two parts: the foreground object discovery scheme and the iterative region allocation algorithm. Two terms, a region-saliency prior and a region-repeatness measure, are introduced in the foreground object discovery scheme to detect the foregrounds without any supervisory information. The iterative region allocation algorithm searches the optimal solution for the final segmentation with the constraints from a maximal spanning tree, and an effective color-based model is utilized during this process. The comparative experimental results show that the proposed algorithm matches or outperforms several previous methods on several standard datasets.     

安塞油田暂堵压裂裂缝转向研究

研究了安塞油田暂堵压裂的增产机理,提出了暂堵压裂应具备的增产前提条件。通过研究储层特性、地应力、初始裂缝形态等关键控制因素,有效地控制新裂缝的起裂和延伸。现场整体应用效果显著,创造了良好的经济和社会效益。     

基于改进粒子群算法的线缆路径规划方法研究

针对复杂机电产品布线路径规划过程中存在的效率较低、可应用性差等问题,提出一种改进粒子群算法,使用栅格法对布线空间进行划分,对障碍物建模并进行方向包围盒处理。为了避免算法在迭代过程中陷入局部最优,引入非线性逐渐递减的惯性权重与异步变化的学习因子,并且将贴壁约束加入到路径规划的过程中,保证线缆在敷设时路径的合理性。最后在仿真试验中,与标准粒子群算法进行对比,验证了改进后算法的合理性与可行性。