多机器人体间动态碰撞检测方法仿真研究

当前多结合包围求碰撞检测法、Average-Case法、K-DOPs法等实现多机器人体间动态碰撞的检测,均存在寻优性能较差、检测效率较低的问题。为此提出一种基于动态粒子群的多机器人体间动态碰撞检测方法。采用OBB层次包围盒方法,缩小多机器人之间需要动态碰撞检测的区域,同时把动态碰撞检测问题转换为物体特征对间距离机制的非线性优化问题,进而构建层次拓扑框架进行局部碰撞检测,将机器人体引入到粒子群算法中建立混合进化算法,找到动态碰撞检测的最优解,实现多机器人体间动态碰撞检测。仿真结果证明,所提方法的检测效率高达96%,且具有较高的寻优性能。     

Performance analysis of large-scale MIMO system for wireless backhaul network

In this paper, we present a performance analysis of large-scale multi-input multi-output (MIMO) systems for wireless backhaul networks. We focus on fully connected N nodes in a wireless meshed and multi-hop network topology. We also consider a large number of antennas at both the receiver and transmitter. We investigate the transmission schemes to support fully connected N nodes for half-duplex and full-duplex transmission, analyze the achievable ergodic sum rate among N nodes, and propose a closed-form expression of the achievable ergodic sum rate for each scheme. Furthermore, we present numerical evaluation results and compare the resuts with closed-form expressions.     

Void region restriction for additive manufacturing via a diffusion physics approach

A longstanding challenge in additive manufacturing (AM), the presence of void regions in additively manufactured components, causes two main issues: the enclosing of build material powder in powder bed fusion techniques and limiting tool access in critical post-processing operations to remove sacrificial support structures. As topology optimization has embraced and overcome many of the obstacles of incorporating AM constraints into the underlying numerical optimization statement, there exist few solutions that directly address this fundamental void region issue. By developing computationally efficient and effective solutions to this problem, the integration of these two advanced technologies can be fully realized. Drawing on inspiration from the principles of diffusion physics, a particle diffusion void restriction (PDVR) method is presented in this work that is capable of encouraging the optimization scheme to generate final designs that are fully accessible. Additionally, this method empowers the user to choose the type of post-processing method to clear support material (eg, three-axis or five-axis milling operations, number and orientation of part set-ups) and, therefore, quantify the level of costs associated with the post-processing operation. The PDVR optimization framework is demonstrated on multiple two- and three-dimensional test problems, with physically manufactured examples depicting the real-world benefits this method admits.     

A novel minimum weight formulation of topology optimization implemented with reanalysis approach

In this paper, we develop an efficient diagonal quadratic optimization formulation for minimum weight design problem subject to multiple constraints. A high-efficiency computational approach of topology optimization is implemented within the framework of approximate reanalysis. The key point of the formulation is the introduction of the reciprocal-type variables. The topology optimization seeking for minimum weight can be transformed as a sequence of quadratic program with separable and strictly positive definite Hessian matrix, thus can be solved by a sequential quadratic programming approach. A modified sensitivity filtering scheme is suggested to remove undesirable checkerboard patterns and mesh dependence. Several typical examples are provided to validate the presented approach. It is observed that the optimized structure can achieve lighter weight than those from the established method by the demonstrative numerical test. Considerable computational savings can be achieved without loss of accuracy of the final design for 3D structure. Moreover, the effects of multiple constraints and upper bound of the allowable compliance upon the optimized designs are investigated by numerical examples.     

An engineering method for complex structural optimization involving both size and topology design variables

This work presents an engineering method for optimizing structures made of bars, beams, plates, or a combination of those components. Corresponding problems involve both continuous (size) and discrete (topology) variables. Using a branched multipoint approximate function, which involves such mixed variables, a series of sequential approximate problems are constructed to make the primal problem explicit. To solve the approximate problems, genetic algorithm (GA) is utilized to optimize discrete variables, and when calculating individual fitness values in GA, a second-level approximate problem only involving retained continuous variables is built to optimize continuous variables. The solution to the second-level approximate problem can be easily obtained with dual methods. Structural analyses are only needed before improving the branched approximate functions in the iteration cycles. The method aims at optimal design of discrete structures consisting of bars, beams, plates, or other components. Numerical examples are given to illustrate its effectiveness, including frame topology optimization, layout optimization of stiffeners modeled with beams or shells, concurrent layout optimization of beam and shell components, and an application in a microsatellite structure. Optimization results show that the number of structural analyses is dramatically decreased when compared with pure GA while even comparable to pure sizing optimization.     

Impact of defects on the decomposition of chemical warfare agent simulants in Zr-based metal organic frameworks

Metal organic frameworks (MOFs) containing zirconium secondary building units (SBUs) in UiO-67 and related MOFs, are highly active for neutralizing both the chemical warfare agents and simulants, such as dimethyl methylphosphonate (DMMP). However, two recent publications gave conflicting reports of DMMP reaction with UiO-67 under ultra high vacuum (UHV) conditions, with one reporting chemisorption and reaction (Wang et al., J Phys Chem C, 2017, 121, 11261–11272) and the other reporting only physisorption and reversible desorption (Ruffley et al., J Phys Chem C, 2019, 123, 19748–19758) from very similar temperature programmed desorption experiments. We show that the discrepancy between these experiments may be explained by different levels of missing linker defects in the UiO-67 samples. We present density functional theory calculations showing that SBU sites having two-adjacent missing linkers exhibit reaction barriers that are about 30 kJ/mol lower than SBU sites having a single missing linker. We also show that topology of the undercoordinated sites plays an important role in the reaction barrier under UHV conditions.     

Information system business affecting impact evaluation method

To effectively analyze the impact of continuous business interruption on the information system,an information system business affecting impact evaluation method (IBAIE) is proposed.First,we identify the main businesses of the system and quantify their vulnerability.Then,we take the businesses as the nodes of network topology and weight nodes based on the business significance.The orderly association between businesses is taken as the edges which are weighted based on the association between asset and business,and the directed weighted business network topology is obtained.Finally,the method of directed weighted network structure entropy is used to evaluate the change of system business network structure during the period from business interruption to recovery.Experiments show that this method has obvious advantages in evaluating accuracy compared to other methods,and can be applied in ensuring information system security.     

Design and analysis adaptivity in multiresolution topology optimization

Multiresolution topology optimization (MTO) methods involve decoupling of the design and analysis discretizations, such that a high-resolution design can be obtained at relatively low analysis costs. Recent studies have shown that the MTO method can be approximately 3 and 30 times faster than the traditional topology optimization method for two-dimensional (2D) and three-dimensional (3D) problems, respectively. To further exploit the potential of decoupling analysis and design, we propose a dp-adaptive MTO method, which involves locally increasing/decreasing the polynomial degree of the shape functions (p) and the design resolution (d). The adaptive refinement/coarsening is performed using a composite refinement indicator that includes criteria based on analysis error, presence of intermediate densities, as well as the occurrence of design artifacts referred to as QR-patterns. While standard MTO must rely on filtering to suppress QR-patterns, the proposed adaptive method ensures efficiently that these artifacts are suppressed in the final design, without sacrificing the design resolution. The applicability of the dp-adaptive MTO method is demonstrated on several 2D mechanical design problems. For all the cases, significant speedups in computational time are obtained. In particular for design problems involving low material volume fractions, speedups of up to a factor of 10 can be obtained over the conventional MTO method.     

IC基板传输机器人末端执行器结构拓扑优化设计

在半导体封装基板检测的传输过程中,末端执行器对其快速稳定高效率的传输起着关键作用。在满足设计强度、刚度的条件下,以末端执行器轻量化为目标,建立了末端执行器的三维模型,利用有限元分析软件ANSYS对基板传输机器人末端执行器进行静力学和模态分析,得到末端执行器在最大载荷情况下的应力、应变特性和对应的振型,并对其进行拓扑优化设计,根据拓扑优化结果建立新的末端执行器结构,对新的结构进行强度校核,验证设计方案的有效性。研究结果表明,优化后末端执行器的前四阶固有频率都大于伺服电动机的回转频率(50Hz),质量减少了26.7%,较好地实现了轻量化的目标,同时为后续的相关产品研制提供了一种新的技术方案。     

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.