Microstructure-based knowledge systems for capturing process-structure evolution linkages

This paper reviews and advances a data science framework for capturing and communicating critical information regarding the evolution of material structure in spatiotemporal multiscale simulations. This approach is called the MKS (Materials Knowledge Systems) framework, and was previously applied successfully for capturing mainly the microstructure-property linkages in spatial multiscale simulations. This paper generalizes this framework by allowing the introduction of different basis functions, and explores their potential benefits in establishing the desired process-structure-property (PSP) linkages. These new developments are demonstrated using a Cahn-Hilliard simulation as an example case study, where structure evolution was predicted three orders of magnitude faster than an optimized numerical integration algorithm. This study suggests that the MKS localization framework provides an alternate method to learn the underlying embedded physics in a numerical model expressed through Green’s function based influence kernels rather than differential equations, and potentially offers significant computational advantages in problems where numerical integration schemes are challenging to optimize. With this extension, we have now established a comprehensive framework for capturing PSP linkages for multiscale materials modeling and simulations in both space and time.     

Comparing rutting of airfield pavements to simulations using Pavement Analysis Using Nonlinear Damage Approach (PANDA)

This study presents the rutting performance results of full-scale pavement test sections subjected to F-15E and C-17 aircraft wheels at two different temperatures. Pavement structures for the tests were constructed under shelter in the U.S. Army Engineer Research and Development Center's (ERDC) pavement test facility. The full-scale test results are used to validate viscoelastic, viscoplastic and hardening-relaxation constitutive relationships implemented in the Pavement Analysis Using Nonlinear Damage Approach (PANDA) model. PANDA is a mechanistic-based model which incorporates nonlinear viscoelastic, viscoplastic, hardening-relaxation, viscodamage, moisture-induced damage and ageing constitutive relationships. Results of dynamic modulus and different repeated creep-recovery laboratory tests are analysed to extract the parameters associated with viscoelastic, viscoplastic and hardening-relaxation constitutive relationships implemented in PANDA. Once calibrated, PANDA is used to predict the rutting performance observed in full-scale pavement test sections. The simulation results illustrate that PANDA is capable of predicting the rutting of airfield pavements subjected to heavy aircraft wheel loads at intermediate and high temperatures. It is shown that PANDA successfully predicts the effect of shear flow and upheaval at the edges of the wheel. The data from simulation suggested that PANDA, once calibrated, can provide insight into the critical locations of tensile and compressive stresses within the pavement structure. PANDA simulations not only provide a tool for evaluating existing structures, but also can be used in designing more sustainable pavement structures and materials.     

Design and qualification of the AMS-02 flight cryocoolers

Four commercial Sunpower M87N Stirling-cycle cryocoolers will be used to extend the lifetime of the Alpha Magnetic Spectrometer-02 (AMS-02) experiment. The cryocoolers will be mounted to the AMS-02 vacuum case using a structure that will thermally and mechanically decouple the cryocooler from the vacuum case. This paper discusses modifications of the Sunpower M87N cryocooler to make it acceptable for space flight applications and suitable for use on AMS-02. Details of the flight model qualification test program are presented.AMS-02 is a state-of-the-art particle physics detector containing a large superfluid helium-cooled superconducting magnet. Highly sensitive detector plates inside the magnet measure a particle’s speed, mass, charge, and direction. The AMS-02 experiment, which will be flown as an attached payload on the International Space Station, will study the properties and origin of cosmic particles and nuclei including antimatter and dark matter.Two engineering model cryocoolers have been under test at NASA Goddard since November 2001. Qualification testing of the engineering model cryocooler bracket assembly including random vibration and thermal vacuum testing was completed at the end of April 2005. The flight cryocoolers were received in December 2003. Acceptance testing of the flight cryocooler bracket assemblies began in May 2005.     

Characterisation of the PSI whole body counter by radiographic imaging

A joint project between the Paul Scherrer Institut (PSI) and the Institute of Radiation Physics was initiated to characterise the PSI whole body counter in detail through measurements and Monte Carlo simulation. Accurate knowledge of the detector geometry is essential for reliable simulations of human body phantoms filled with known activity concentrations. Unfortunately, the technical drawings provided by the manufacturer are often not detailed enough and sometimes the specifications do not agree with the actual set-up. Therefore, the exact detector geometry and the position of the detector crystal inside the housing were determined through radiographic images. X-rays were used to analyse the structure of the detector, and (60)Co radiography was employed to measure the core of the germanium crystal. Moreover, the precise axial alignment of the detector within its housing was determined through a series of radiographic images with different incident angles. The hence obtained information enables us to optimise the Monte Carlo geometry model and to perform much more accurate and reliable simulations.     

Kennfeldanalyse einer Schraubenvakuumpumpe

Operating Performance of Screw Vacuum Pumps This paper presents detailed analyses of the operating performance of a dry‐running screw vacuum pump. The characteristic parameters, suction speed and final attainable pressure ‐ which primarily define the operating performance of screw vacuum pumps ‐ are explored in experimental and theoretical investigations. Experiment and simulation in combination are used to show the correlation between the main physical and technical characteristics and the operating performance of screw vacuum pumps. This basic knowledge is essential for understanding the specific machine physics of positive displacement vacuum pumps, especially for screw vacuum pumps, and is useful in view of further design and optimization processes. The experiment covers measurements of the operating performance of the investigated isochoric screw vacuum pump working against ambient pressure. As operating parameters intake pressure (1000mbar to 10^‐3mbar) and rotor speed are varied over a wide range. The theoretical analysis of the operating performance contains simplifying models as well as simulations of the thermodynamic processing. The impact of external leakages, clearance vacuum flows and further losses on operating performance are described in detail.     

工程计算可视化的几个热点问题

随着工程数值模拟的规模和复杂度的提高,可视化研究面临着发展机遇和挑战,结合国内外的技术发展情况,对于工程计算应用中的表达方式、算法优化、集成解决框架等几个热点问题展开讨论,指出可视化技术发展与应用学科结合的重要性.     

A Dendrite Net based decoupled framework for the reliability-based control co-design problem

To improve the reliability of the dynamic system including physical and control design, the reliability-based control co-design (RB-CCD) problem has been studied to account for the uncertainty stemming from the random physical design. However, when encountering RB-CCD in the sophisticated system in which the dynamic model simulation is time-consuming or the state equation is expressed implicitly, the available RB-CCD methods will consume significant computational effort to perform numerous system simulations for the reliability analysis and deterministic optimization. Therefore, this work proposes a Dendrite Net-based decoupled framework for RB-CCD to alleviate the computational burden. Specifically, the Dendrite (DD) model constructed by the suggested training scheme integrated with an adaptive sampling strategy is used to approximate the state equation in the dynamic system. After that, the sequential optimization and reliability assessment method decouples RB-CCD into the control co-design (CCD) problem and time-dependent reliability assessment problem, which are solved sequentially based on the cheap estimations of DD model, rather than the expensive simulations of the original system. Furthermore, two numerical examples and an engineering example of 3-DOF robot system are applied to demonstrate the feasibility and efficiency of the proposed framework.     

基于DSP的动态电压恢复器实现

对动态电压恢复器的主要结构、应用场合、控制策略与补偿策略等进行比较分析和优化选择．详细介绍了基于TM$320F2812芯片的动态电压恢复器（DVR）的设计,采用串联补偿方式、同相位补偿策略及LC滤波,实现三相电压的实时动态补偿功能．在MATLAB下建立DVR的详细仿真模型,并用实验验证了动态电压恢复器的动态性能和电压跌落补偿效果．     

雷达高功率铰链装配工艺规划系统的开发

面向并行工程的需求,提出并设计了雷达高功率铰链三维装配工艺规划系统（HPH-CAAP）。系统利用微软的Microsoft Visual C＋＋6.0作为开发语言,UG/OPEN API作为开发工具,用来验证和改进产品可装配性的仿真系统。阐述了HPH-CAAP的体系结构以及虚拟装配模型的定义、交互式装配工艺规划、装配仿真、干涉检验和模型的参数化重构关键技术模块。研究了HPH-CAAP各模块的实现全流程。最后给出了系统的应用实例。     

Hybrid systems for planning and optimization of virtual assembly

Virtual assembly is the simulation of parts assembly processes by computer, analysing, evaluating and optimizing the feasibilities and procedures of assembly. It can thus avoid the potential problems and risks from designing to assembling. In this way, we can achieve the global optimization of the products and timely respond to the needs of the market. This paper presents a modelling framework for virtual assembly paths design and optimization of two objects on the basis of a class of hybrid system, which is applicable in many manufacturing environments. We propose an elementary hybrid machine containing time-driven and event-driven dynamics. We describe in detail a method of assembly paths design. The objective of optimization is evaluated in terms of time in the transition dynamics so as to make the problem more tractable. An explicit algorithm for deriving optimal assembly policies is developed. The optimal results indicate the feasibility and efficacy of the model and control algorithms.     

Monte Carlo Simulation of Massive Absorbers for Cryogenic Calorimeters

There is a growing interest in cryogenic calorimeters with macroscopic absorbers for applications such as dark matter direct detection and rare event search experiments. The physics of energy transport in calorimeters with absorber masses exceeding several grams is made complex by the anisotropic nature of the absorber crystals as well as the changing mean free paths as phonons decay to progressively lower energies. We present a Monte Carlo model capable of simulating anisotropic phonon transport in cryogenic crystals. We have initiated the validation process and discuss the level of agreement between our simulation and experimental results reported in the literature, focusing on heat pulse propagation in germanium. The simulation framework is implemented using Geant4, a toolkit originally developed for high-energy physics Monte Carlo simulations. Geant4 has also been used for nuclear and accelerator physics, and applications in medical and space sciences. We believe that our current work may open up new avenues for applications in material science and condensed matter physics.     

A calibration framework for discrete element model parameters using genetic algorithms

In this research, a universal framework for automated calibration of microscopic properties of modeled granular materials is proposed. The proposed framework aims at industrial scale applications, where optimization of the computational time step is important. It can be generally applied to all types of DEM simulation setups. It consists of three phases: data base generation, parameter optimization, and verification. In the first phase, DEM simulations are carried out on a multi-dimensional grid of sampled input parameter values to generate a database of macroscopic material responses. The database and experimental data are then used to interpolate the objective functions with respect to an arbitrary set of parameters. In the second phase, the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to solve the calibration multi-objective optimization problem. In the third phase, the DEM simulations using the results of the calibrated input parameters are carried out to calculate the macroscopic responses that are then compared with experimental measurements for verification and validation.The proposed calibration framework has been successfully demonstrated by a case study with two-objective optimization for the model accuracy and the simulation time. Based on the concept of Pareto dominance, the trade-off between these two conflicting objectives becomes apparent. Through verification and validation steps, the approach has proven to be successful for accurate calibration of material parameters with the optimal simulation time.     

KDON-18000/30000型空分设备工艺特点及投运

简介KDON-18000/30000型空分设备的流程,详细介绍了设备配置的特点;分析了设备投运中遇到的问题及解决方法。