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.     

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.     

Nodal ant colony optimization for solving profit based unit commitment problem for GENCOs

This paper proposes a nodal ant colony optimization (NACO) technique to solve profit based unit commitment problem (PBUCP). Generation companies (GENCOs) in a competitive restructured power market, schedule their generators with an objective to maximize their own profit without any regard for system social benefit. Power and reserve prices become important factors in decision process. Ant colony optimization that mimics the behavior of ants foraging activities is suitably implemented to search the UCP search space. Here a search space consisting of optimal combination of binary nodes for unit ON/OFF status is represented for the movement of the ants to maintain good exploration and exploitation search capabilities. The proposed model help GENCOs to make decisions on the quantity of power and reserve that must be put up for sale in the markets and also to schedule generators in order to receive the maximum profit. The effectiveness of the proposed technique for PBUCP is validated on 10 and 36 generating unit systems available in the literature. NACO yields an increase of profit, greater than 1.5%, in comparison with the basic ACO, Muller method and hybrid LR-GA.     

基于滤波的SAR影像去噪方法分析

根据SAR(Synthetic Aperture Radar)影像相干噪声的特点,对现在广泛应用的各种抑制噪声的滤波方法如均值滤波、Frost滤波、增强型Lee滤波、Lee滤波、中值滤波等进行分析,并提出适合本研究区影像的基于小波变换的分量滤波处理去噪方法,利用均值、标准差、平滑指数、PM值、信息熵和平均梯度等评价指标对各种滤波去噪后的影像质量进行评价,并对去噪效果进行对比分析,证明本文所采用的滤波方法对SAR影像噪声有很好的抑制作用,并且较好的保存了图像纹理信息。     

选择性集成算法分类与比较

选择性集成是当前机器学习领域的研究热点之一。由于选择性集成属于NP"难"问题,人们多利用启发式方法将选择性集成转化为其他问题来求得近似最优解,因为各种算法的出发点和描述角度各不相同,现有的大量选择性集成算法显得繁杂而没有规律。为便于研究人员迅速了解和应用本领域的最新进展,本文根据选择过程中核心策略的特征将选择性集成算法分为四类,即迭代优化法、排名法、分簇法、模式挖掘法;然后利用UCI数据库的20个常用数据集,从预测性能、选择时间、结果集成分类器大小三个方面对这些典型算法进行了实验比较;最后总结了各类方法的优缺点,并展望了选择性集成的未来研究重点。     

粉末冶金TiAl合金排气门的研制

利用元素粉末冶金方法制备了TiAl合金排气阀。为提高排气门杆部的致密度、均匀度 ,设计了特有的径向热压工艺 ,并从理论上分析了与该工艺相关的压坯密度、致密化和应力变化规律。制备出高径比为 10 .7,密度为 3.79g/cm3 的粉末冶金TiAl合金汽车发动机排气门     

Site occupations and ordering behaviour of O phase in Ti2AlNb—based intermetallics

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基于可拓学的新型职业农民培育模式创新研究

“产业兴旺”是乡村振兴的重点, 是乡村振兴的经济基础, 是解决农村一切问题的前提。为了破解乡村产业兴旺中高素质农民短缺所造成的人才制约问题, 本研究梳理了现有新型职业农民培育文献, 对负责新型职业农民培育的政府部门工作人员进行深度访谈, 以此为基础形成新型职业农民培育供需现状调查问卷, 基于分析结果厘清了新型职业农民培育规模和培育内容两个供需矛盾问题。基于可拓学原理, 建立了矛盾问题的可拓模型, 并通过可拓变换来解决矛盾问题, 最终形成了新的新型职业农民培育模式。此研究对有效提升新型职业农民培育效能, 促进乡村产业兴旺的有效实施具有重要意义。     

自交联型水性聚丙烯酸酯分散体的制备及其性能

以甲基丙烯酸甲酯（MMA）为硬单体、丙烯酸丁酯（BA）为软单体、丙烯酸（AA）为功能单体、甲基丙烯酸乙酰乙酰氧基乙酯（AAEM）为交联单体、过氧化苯甲酸叔丁酯为引发剂、乙二醇丁醚为溶剂,通过自由基溶液聚合经转相方式制备了自交联型丙烯酸酯分散体,该分散体在烘烤条件下不需要外加交联剂即可发生自交联反应。研究了丙烯酸、甲基丙烯酸乙酰乙酰氧基乙酯和固化时间等因素对树脂分散体和涂膜性能的影响。结果表明,优化的配方为：AA质量占单体总质量的3.5%、AAEM质量占单体总质量的5.0%、固化温度为180 ℃、固化时间为1.0 h。红外光谱和凝胶渗透色谱分析表明,AAEM成功接到了丙烯酸树脂分子链上;扫描电镜和粒度分析仪分析表明,乳胶粒呈球形且分布均匀;差示扫描量热分析表明,合成后的树脂分散体在高温下烘烤一段时间后,涂膜的玻璃化转变温度明显提高。     

两种Ni-Cr-Co基高温合金的凝固偏析及其对Rayleigh数的影响

利用SEM和EDAX研究了2种Ni-Cr-Co基高温合金GH742和GH738凝固过程中组织、液相成分变化,用图像分析软件测定了各温度下的液相分数,并计算了2种合金凝固过程中液相密度差和相对Rayleigh数变化。结果表明,GH742凝固过程中主要是Cr、Co和Nb的偏析,GH738合金凝固过程中主要是Cr、Co和Ti的偏析;GH742和GH738合金凝固过程中都存在着液相密度反转,后者密度差的绝对值较大;GH738合金相对Rayleigh数绝对值的最大值是GH742的3.5倍,凝固时更易形成黑斑。