Coupling in situ experiments and modeling – Opportunities for data fusion,machine learning,and discovery of emergent behavior

This paper reviews recent studies, that not only includes both experiments and modeling components, but celebrates a close coupling between these techniques, in order to provide insights into the plasticity and failure of polycrystalline metals. Examples are provided of studies across multiple-scales, including, but not limited to, density functional theory combined with atom probe tomography, molecular dynamics combined with in situ transmission electron miscopy, discrete dislocation dynamics combined with nanopillars experiments, crystal plasticity combined with digital image correlation, and crystal plasticity combined with in situ high energy X-ray diffraction. The close synergy between in situ experiments and modeling provides new opportunities for model calibration, verification, and validation, by providing direct means of comparison, thus removing aspects of epistemic uncertainty in the approach. Further, data fusion between in situ experimental and model-based data, along with data driven approaches, provides a paradigm shift for determining the emergent behavior of deformation and failure, which is the foundation that underpins the mechanical behavior of polycrystalline materials.     

有水气藏开发早期可采储量的评价方法

有水气藏是天然气藏中的一个基本气藏类型，其采收率受多种因素的影响，如地面集输压力、井筒混合气水流动的液柱压力和储层物性等，目前普遍采用经验取值、物质平衡和气藏数值模拟等方法进行研究，但由于受开发评价阶段试采资料偏少和气藏数值模拟无法模拟井筒流动等因素的影响，早期采收率计算往往偏差较大，针对这些问题，从气田开发一体化的特点出发，提出了一种全面考虑地层→井筒→地面流动条件下，有水气藏（含凝析有水气藏）发废弃压力的计算方法，发展了利用物质平衡早期预测有水气藏采收率的理论，方法可靠、适用性强，能够推广应用。     

微机控制托辊管筒加工机床的设计

介绍了一种生产效率高、加工质量稳定、利用单片机控制液压传动系列带式输送机托辊管筒自动加工机床的设计过程。     

The summary of researches on ADS in China

The conceptual study on the accelerator driven system (ADS) that lasted for about five years ended in 1999 in China. As one project of the National Basic Research Program of China (973 Program) in the energy domain, which is sponsored by the China Ministry of Science and Technology (MOST), a five-year-program of fundamental research of ADS physics and related technology was launched in 2000 and passed national review at the end of 2005. The China Institute of Atomic Energy (CIAE), the Institute of High Energy Physics (IHEP), the Institute of Heavy Ion Physics in Peking University (PKU-IHIP) and other institutions jointly carried out the research. The research activities were focused on HPPA physics and technology, reactor physics of external source driven sub-critical assembly, nuclear data base and material study. For HPPA, a high current injector consisting of an ECR ion source, LEBT and an RFQ accelerating structure of 3.5 MeV was built. In reactor physics study, a series of neutron multiplication experimental study has been carried out and still being done. The VENUS facility has been constructed as the basic experimental platform for neutronics study in ADS blanket. It’s a zero power sub-critical neutron multiplying assembly driven by external neutron produced by a pulsed neutron generator. The theoretical, experimental and simulation study on nuclear data, material properties and nuclear fuel circulation related to ADS is carrying on to provide the database for ADS system analysis. The main results on ADS related researches will be reported.     

基于PI3000平台的分布式任务调度研究与实现

在PI3000平台中任务调度是应用系统中很重要的部分,应用环境的复杂程度导致各式各样调度的框架和算法.文中提出一个新的分布式负载均衡的任务调度框架,以解决在并行任务中特定的应用环境下的任务调度问题.这个框架是动态的、可重用的,通过提供给各种不同的资源环境对应的接口,来进行跨服务的调度.整个框架关注于实际应用环境下任务、资源的动态不稳定性和任务计算的快速响应.     

基于进化计算的兴趣建模

为实现对个体的兴趣建模,提出基于进化计算的建模(Evolutionary Computation Based Modeling,ECBM)方法。该方法采用定性和定量相结合的方式对个体的兴趣系统进行建模,首先通过定性分析构建个体的兴趣模型框架,然后通过进化计算(Evolutionary Computation)方法对模型参数自动进化。实验结果表明,ECBM能够通过数据驱动模式优化模型参数,并利用更新信息进化模型,使其不断逼近真实系统。     

用例驱动技术在需求获取过程中的应用

需求获取是软件开发过程中非常重要的环节,它贯穿于整个软件生命周期。针对系统客户和开发人员由于认识问题角度和知识的差异而存在的需求获取障碍,提出了一种基于用例的需求获取方法。该方法以用户和任务为中心,设计了一个用户需求描述模板,引导用户填写需求描述信息,开发人员利用用例驱动技术对需求描述信息进行分析和验证,最终获取全面和准确的参与者和用例信息。该构建过程不仅为构造用例图和类图奠定了基础,而且也使软件工程活动更加规范。     

模型驱动下的Web应用系统自动生成

为了提高Web应用系统开发效率,提出了模型驱动下的Web应用系统自动生成方法。这种生成方法是以Me—taEdit＋作为元建模工具,首先创建Web应用系统元模型、定制DSL,进而建立Web应用系统领域模型,然后通过MetaEdit＋提供的生成器定义语言MERL,软件开发人员可以很方便地设计出Web应用系统所需的JSP生成器、Servlet生成器、Jayabeans生成器和数据库生成器,从Web应用系统图形模型直接生成整个Web应用系统。最后通过一个WebShopping实例详细介绍了模型驱动下的Web应用系统生成方法及生成过程。经测试,所生成的Web应用系统可以在Windows操作系统中的Web应用服务器上正确运行。     

Response correction techniques for surrogate‐based design optimization of microwave structures

Simulation‐based optimization has become an important design tool in microwave engineering. However, using electromagnetic (EM) solvers in the design process is a challenging task, primarily due to a high‐computational cost of an accurate EM simulation. In this article, we present a review of EM‐based design optimization techniques exploiting response‐corrected physically based low‐fidelity models. The surrogate models created through such a correction can be used to yield a reasonable approximation of the optimal design of the computationally expensive structure under consideration (high‐fidelity model). Several approaches using this idea are reviewed including output space mapping, manifold mapping, adaptive response correction, and shape‐preserving response prediction. A common feature of these methods is that they are easy to implement and computationally efficient. Application examples are provided. © 2011 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2012.     

An Intelligent Robust Tracking Control for a Class of Electrically Driven Mobile Robots

This paper addresses the problem of designing robust tracking control for a class of uncertain wheeled mobile robots actuated by brushed direct current motors. This class of electrically‐driven mechanical systems consists of the robot kinematics, the robot dynamics, and the wheel actuator dynamics. Via the backstepping technique, an intelligent robust tracking control scheme that integrates a kinematic controller and an adaptive neural network‐based (or fuzzy‐based) controller is developed such that all of the states and signals of the closed‐loop system are bounded and the tracking error can be made as small as possible. Two adaptive approximation systems are constructed to learn the behaviors of unknown mechanical and electrical dynamics. The effects of both the approximation errors and the unmodeled time‐varying perturbations in the input and virtual‐input weighting matrices are counteracted by suitably tuning the control gains. Consequently, the robust control scheme developed here can be employed to handle a broader class of electrically‐driven wheeled mobile robots in the presence of high‐degree time‐varying uncertainties. Finally, a simulation example is given to demonstrate the effectiveness of the developed control scheme.