Digital twin modeling method based on biomimicry for machining aerospace components

High-performance aerospace component manufacturing requires stringent in-process geometrical and performance-based quality control. Real-time observation, understanding and control of machining processes are integral to optimizing the machining strategies of aerospace component manufacturing. Digital Twin can be used to model, monitor and control the machining process by fusing multi-dimensional in-context machining process data, such as changes in geometry, material properties and machining parameters. However, there is a lack of systematic and efficient Digital Twin modeling method that can adaptively develop high-fidelity multi-scale and multi-dimensional Digital Twins of machining processes. Aiming at addressing this challenge, we proposed a Digital Twin modeling method based on biomimicry principles that can adaptively construct a multi-physics digital twin of the machining process. With this approach, we developed multiple Digital Twin sub-models, e.g., geometry model, behavior model and process model. These Digital Twin sub-models can interact with each other and compose an integrated true representation of the physical machining process. To demonstrate the effectiveness of the proposed biomimicry-based Digital Twin modeling method, we tested the method in monitoring and controlling the machining process of an air rudder.     

Mathematical model and discrete artificial Bee Colony algorithm for distributed integrated process planning and scheduling

With the development of the globalization of economy and manufacturing industry, distributed manufacturing mode has become a hot topic in current production research. In the context of distributed manufacturing, one job has different process routes in different workshops because of heterogeneous manufacturing resources and manufacturing environments in each factory. Considering the heterogeneous process planning problems and shop scheduling problems simultaneously can take advantage of the characteristics of distributed factories to finish the processing task well. Thus, a novel network-based mixed-integer linear programming (MILP) model is established for distributed integrated process planning and scheduling problem (DIPPS). The paper designs a new encoding method based on the process network and its OR-nodes, and then proposes a discrete artificial bee colony algorithm (DABC) to solve the DIPPS problem. The proposed DABC can guarantee the feasibility of individuals via specially-designed mapping and switching operations, so that the process precedence constraints contained by the network graph can be satisfied in the entire procedure of the DABC algorithm. Finally, the proposed MILP model is verified and the proposed DABC is tested through some open benchmarks. By comparing with other powerful reported algorithms and obtaining new better solutions, the experiment results prove the effectiveness of the proposed model and DABC algorithm successfully.     

Re-optimization of the binary Sb − Se system aided by ab-initio calculations

Based on the ab-initio calculations the thermodynamics of the Sb₂Se₃ intermediate phase was modeled and used in the calculations of the Sb–Se phase diagram together with the thermodynamic properties of liquid phase elaborated by the association model. The modeled heat capacity of Sb₂Se₃ phase shows excellent agreement with the experiment data available in the literature in the wide temperature range. The calculated equilibrium lines of the Sb–Se phase diagram good correlate with the experimental ones. The determined thermodynamic parameters can be applied in future calculations of the high-ordered systems and for determination of the Sb₂Se₃ thermoelectric properties.     

Customer entrepreneurship on digital platforms: Challenges and solutions for platform business models

Drawing on the mixed methods of qualitative research and agent‐based simulation, this study examines: (a) how end‐users use digital platforms to become customer–entrepreneurs undertaking commercial activities on platforms; and (b) how platform providers can convert this customer entrepreneurship into a revenue stream. Considering that end‐users have traditionally been defined as passive and uncharged actors in platform business models, an in‐depth understanding of their commercial activities and the viable revenue model to monetize this emerging customer practice is warranted. Our qualitative study reveals that customer–entrepreneurs make substantial use of platform offerings to advertise their products; communicate with end‐consumers; and accept payments. These commercial activities are largely exercised for free on platforms, even though they could otherwise serve as a source of revenue. On this point, our simulation results identify two pricing models achieving the generation of nearly identical revenues over time. First, platform providers may charge both advertising and transaction fees, which maximize the survival of professional customer–entrepreneurs. Second, platform businesses may levy advertising fees only, which maximizes the survival of informal customer–entrepreneurs operating on a micro‐scale and part‐time basis. This study offers theoretical, methodological, and managerial implications for platform studies.     

网络信息资源分级体系框架的构建

网络信息分级是保障网络信息内容安全的重要手段。主要构建了网络信息资源分级体系框架六元组模型,分析了相关组成元素的内容,以适应不同行业应用。     

某商品大集人员疏散的仿真模拟研究

目前,在各地均有商贸活动开展,且参与人员众多,如果公安机关事先未做好预案,一旦发生突发性事件,人员疏散不到位,极易造成群死群伤事件。文章以商品大集为例,构建参与人员的流动模型,利用计算机技术实现流量和流动状况的模拟仿真,获得接近实际的流动的时间和动态过程．利于事先对类似活动拥堵情况进行准确评估。     

基于云自适应遗传算法的NoC路径分配研究

路径分配是NoC设计流程中的两个关键步骤之一;路径分配的结果对NoC系统的性能尤其是通讯延时有着很重要的影响;多约束条件下的NoC路径分配问题是NP完全问题,要求出其最优解比较困难,目前常用的方法是利用启发式算法求得其较优解;文中提出一种基于云自适应遗传算法的NoC路径分配解决方案,该算法利用云模型对传统遗传算法加以改进,采取新的方法自动调整遗传算法过程中的交叉概率pc和变异概率pm,将适应度与云模型的3个参数Ex、En、He相互结合,从而达到优化遗传算法的目的;将此算法应用于2D-Mesh拓扑结构的NoC中,以平衡链路负载和联合优化为实验目标,以优化静态通讯分配结果;实验证明,文章所采取的算法在平衡链路负载和联合优化方面均取得了良好的效果。     

Improved results on frequency‐weighted balanced truncation and error bounds

In this paper, we present some new results on frequency‐weighted balanced truncation which is a significant improvement on Lin and Chiu's frequency‐weighted balanced truncation technique. The reduced‐order models, which are guaranteed to be stable in the case of double‐sided weighting, are obtained by direct truncation. Two sets of simple, elegant and easily calculatable a priori error bounds are also derived. Numerical examples and comparison with other well‐known techniques show the effectiveness of the proposed technique. Copyright © 2011 John Wiley & Sons, Ltd.