面向对象有限元并行计算框架PANDA的多物理场耦合服务

针对结构分析软件面向多物理场的应用,分析讨论面向对象有限元并行计算框架PANDA的多物理场耦合服务设计,即多物理场分析类型的扩充能力、不同物理场间的数据传递和多物理场耦合分析的求解策略.在PANDA提供的多物理场耦合服务的基础上,开展热-力耦合分析功能的程序开发,实现热弹性分析功能.热弹性分析算例计算结果与ANSYS的...     

基于PANDA框架的并行有限元模态分析程序开发和应用

为提高大型结构振动分析的规模、精度和效率,基于面向对象有限元并行计算框架PANDA和高性能矩阵特征问题并行求解算法,开发出适用于大规模结构振动问题计算的并行有限元模态分析程序;在超级计算机银河YH和曙光5000A上,通过不同算例验证该程序的正确性和可靠性.以某靶室结构为研究对象演示该程序的应用,指出实际应用时需注意加速...     

Introducing realistic tire–pavement contact stresses into Pavement Analysis using Nonlinear Damage Approach (PANDA)

Realistic tire–pavement interface contact areas and stresses were incorporated into the Pavement Analysis using Nonlinear Damage Approach (PANDA) user interface (PUI). PANDA is a software library developed to simulate the complex thermo-viscoelastic–viscoplastic–viscodamage responses of the pavement to mechanical and environmental loads. The PUI is an interface generating a finite element representation of the pavement within PANDA. The application of realistic tire loading is necessary to calculate accurate pavement responses. The PUI incorporates a database of tire contact areas and stresses obtained from tire finite element simulations. The database includes tire interface characteristics with pavements for various applied loads, tire inflation pressures, vehicle speeds and scenarios of different rolling simulations. A parametric study was conducted to investigate the effect of simulations of tire contact stresses that match field measurements on viscoelastic and viscoplastic pavement responses. Pavement responses are greatly affected using realistic tire loading contact stresses and contact geometry as compared to simplified contact models. The impact on rutting and damage predictions cannot be ignored if reliable projections of pavement performance are to be made. This study confirms the importance of considering realistic three-dimensional contact stresses to design and analyse pavements.     

The pairwise attribute noise detection algorithm

Analyzing the quality of data prior to constructing data mining models is emerging as an important issue. Algorithms for identifying noise in a given data set can provide a good measure of data quality. Considerable attention has been devoted to detecting class noise or labeling errors. In contrast, limited research work has been devoted to detecting instances with attribute noise, in part due to the difficulty of the problem. We present a novel approach for detecting instances with attribute noise and demonstrate its usefulness with case studies using two different real-world software measurement data sets. Our approach, called Pairwise Attribute Noise Detection Algorithm (PANDA), is compared with a nearest neighbor, distance-based outlier detection technique (denoted DM) investigated in related literature. Since what constitutes noise is domain specific, our case studies uses a software engineering expert to inspect the instances identified by the two approaches to determine whether they actually contain noise. It is shown that PANDA provides better noise detection performance than the DM algorithm. Jason Van Hulse is a Ph.D. candidate in the Department of Computer Science and Engineering at Florida Atlantic University. His research interests include data mining and knowledge discovery, machine learning, computational intelligence and statistics. He is a student member of the IEEE and IEEE Computer Society. He received the M.A. degree in mathematics from Stony Brook University in 2000, and is currently Director, Decision Science at First Data Corporation. Taghi M. Khoshgoftaar is a professor at the Department of Computer Science and Engineering, Florida Atlantic University, and the director of the Empirical Software Engineering and Data Mining and Machine Learning Laboratories. His research interests are in software engineering, software metrics, software reliability and quality engineering, computational intelligence, computer performance evaluation, data mining, machine learning, and statistical modeling. He has published more than 300 refereed papers in these subjects. He has been a principal investigator and project leader in a number of projects with industry, government, and other research-sponsoring agencies. He is a member of the IEEE, the IEEE Computer Society, and IEEE Reliability Society. He served as the program chair and general chair of the IEEE International Conference on Tools with Artificial Intelligence in 2004 and 2005, respectively. Also, he has served on technical program committees of various international conferences, symposia, and workshops. He has served as North American editor of the Software Quality Journal, and is on the editorial boards of the journals Empirical Software Engineering, Software Quality, and Fuzzy Systems. Haiying Huang received the M.S. degree in computer engineeringfrom Florida Atlantic University, Boca Raton, Florida, USA, in 2002. She is currently a Ph.D. candidate in the Department of Computer Science and Engineering at Florida Atlantic University. Her research interests include software engineering, computational intelligence, data mining, software measurement, software reliability, and quality engineering.     

面向对象有限元并行计算框架PANDA

为提高我国工程数值模拟软件的开发能力,面向武器工程大规模并行计算需求,基于层次化、模块化及面向对象的现代软件设计技术,分析探讨有限元并行计算框架的设计方法,形成初步的基础开发框架PANDA 0.1版;详细描述PANDA框架的层次结构设计,并探讨该基础开发框架设计中的底层网格数据结构设计、有限元共性管理模块及并行策略等部分关键技术;简要介绍PANDA框架的扩展应用方法.研究表明：采用框架技术进行结构力学有限元程序开发,具有高效、快速和便捷等优点.     

Long Non-Coding RNAs and p53 Regulation

The advent of novel and high-throughput sequencing (next generation) technologies allowed for the sequencing of the genome at an unprecedented depth. The majority of transcribed RNAs have been classified as non-coding RNAs. Among them, long non-coding RNAs (lncRNAs) are emerging as important regulators in many biological processes. Here, we discuss the role of those lncRNAs which are under the control of p53 or that are able to regulate its activity, due to the central role of p53 pathway in many conditions. We also briefly discussed the emerging need of having novel strategies and computational tools to completely unravel the multifaceted roles of lncRNAs and to pave the way to the development of novel diagnostic and therapeutic applications based on these peculiar molecules.     

Analysis of different containment models for IRIS small break LOCA, using GOTHIC and RELAP5 codes

Advanced nuclear water reactors rely on containment behaviour in realization of some of their passive safety functions. Steam condensation on containment walls, where non-condensable gas effects are significant, is an important feature of the new passive containment concepts, like the AP600/1000 ones.In this work the international reactor innovative and secure (IRIS) was taken as reference, and the relevant condensation phenomena involved within its containment were investigated with different computational tools. In particular, IRIS containment response to a small break LOCA (SBLOCA) was calculated with GOTHIC and RELAP5 codes. A simplified model of IRIS containment drywell was implemented with RELAP5 according to a sliced approach, based on the two-pipe-with-junction concept, while it was addressed with GOTHIC using several modelling options, regarding both heat transfer correlations and volume and thermal structure nodalization. The influence on containment behaviour prediction was investigated in terms of drywell temperature and pressure response, heat transfer coefficient (HTC) and steam volume fraction distribution, and internal recirculating mass flow rate. The objective of the paper is to preliminarily compare the capability of the two codes in modelling of the same postulated accident, thus to check the results obtained with RELAP5, when applied in a situation not covered by its validation matrix (comprising SBLOCA and to some extent LBLOCA transients, but not explicitly the modelling of large dry containment volumes).The option to include or not droplets in fluid mass flow discharged to the containment was the most influencing parameter for GOTHIC simulations. Despite some drawbacks, due, e.g. to a marked overestimation of internal natural recirculation, RELAP5 confirmed its capability to satisfactorily model the basic processes in IRIS containment following SBLOCA.     

面向对象有限元并行计算框架PANDA的并行机制

为实现面向对象有限元并行计算框架PANDA对高性能计算的支持,分别从并行计算流程、区域分解、分区信息和通信封装等部分设计PANDA框架在并行计算方面的数据结构.在计算流程中建立区域分解和并行求解器的配合协作方式,进而描述进行区域分割的3种网格剖分方法;对分区边界单元和节点信息的组织以及对并行通信操作的封装使复杂的并行通...     

基于Jaumin的等参单元算法框架设计

针对等参有限元的计算特点和有限元软件多种单元的开发需求,基于高性能计算程序开发框架Jaumin,使用面向对象语言,采用抽象和多态技术以及工厂模式,为有限元软件PANDA设计等参单元算法框架.该框架具有良好的可复用性及可扩展性,开发过程清晰,有利于提高开发效率.给出等参单元算法框架中各个模块所对应的类以及类的接口.实例表明用PANDA中已实现的等参单元计算结果与ANSYS的计算结果一致.     

基于背向衍射图像特征的熊猫光纤定轴方法

对激光束与熊猫光纤相互作用形成的背向衍射图像进行了研究,结果表明,衍射图像中,多级明条纹的长度曲线和其中心位置曲线都与熊猫光纤偏振轴的方位角有关,而且用明条纹的长度曲线作为定轴特征量比用其中心位置曲线作为定轴特征量更灵敏.基于这两个特量提出了一种熊猫光纤的定轴新方法,实现了1°的定轴分辨率,并用图像互相关的方法对这种基于特征量的定轴方法进行了验证,所得的实验结果两者一致.