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high order semi-implicit weighted compact nonlinear scheme for the all-Mach isentropic Euler system

Advances in Aerodynamics 2020年第1期2卷 555-578页

作者： Yanqun Jiang Xun Chen Xu Zhang Tao Xiong Shuguang Zhou Department of Mathematics Southwest University of Science and Technology621010 MianyangChina School of Mathematical Sciences Fujian Provincial Key Laboratory of Mathematical Modeling and High-Performance Scientific ComputingXiamen University361005 XiamenChina Computational Aerodynamics Institute China Aerodynamics Research and Development Center621000 MianyangChina

The computation of compressible flows at all Mach numbers is a very challenging *** efficient numerical method for solving this problem needs to have shock-capturing capability in the high Mach number regime,while it can deal with stiffness and accuracy in the low Mach number *** paper designs a high order semi-implicit weighted compact nonlinear scheme(WCNS)for the all-Mach isentropic Euler system of compressible gas *** avoid severe Courant-Friedrichs-Levy(CFL)restrictions for low Mach flows,the nonlinear fluxes in the Euler equations are split into stiff and non-stiff components.A third-order implicit-explicit(IMEX)method is used for the time discretization of the split components and a fifth-order WCNS is used for the spatial discretization of flux *** high order IMEX method is asymptotic preserving and asymptotically accurate in the zero Mach number ***-and two-dimensional numerical examples in both compressible and incompressible regimes are given to demonstrate the advantages of the designed IMEX WCNS.

关键词： high order scheme IMEX time discretization WCNS Asymptotic-preserving property Low Mach number Isentropic Euler equations

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Wireless Sensor Networks for Intensive Irrigated Agriculture

Wireless Sensor Networks for Intensive Irrigated Agriculture

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Consumer Communications and Networking Conference, CCNC IEEE

作者： Yang Wang Liusheng Huang Junmin Wu Hongli Xu Department of Computer Science and Technology Anhui Province-Most Co-Key Laboratory of High Performance Computing and Its Application University of Science and Technology Hefei Anhui China

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Behind the quantum and size effects: Broken-bond-induced local strain and skin-depth densified quantum trapping of charge and energy

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Key Engineering Materials 2010年 444卷 17-45页

作者： Pan, Likun Gu, Mingxia Ouyang, Gang Sun, Chang Q. Engineering Research Center for Nanophotonics and Advanced Instrument Department of Physics East China Normal University Shanghai 200062 China Institute of High Performance Computing ASTAR 1 Fusionopolis Way Singapore 138632 Singapore School of Electrical and Electronic Engineering Nanyang Technological University Singapore 639798 Singapore Key Laborastory of Low-dimensional Materials and Application Technolgies Institute of Quantum Enginering and Moicro-Nano Energy Technology Xiangtan University Changsha 411105 China

ISBN: (纸本)9780878492657

Shrinking the size of a solid down to nanometer scale is indeed fascinating, which makes all the otherwise constant physical quantities to be tunable such as the Young's modulus, dielectric constant, melting point, etc. The variation of size also generates novel properties that can hardly be seen in the bulk such as the conductor-insulator and nonmagnetic-magnetic transition of noble metals at the nanoscale. Although the physics of materials at the nanoscale has been extensively investigated, the laws governing the energetic and dynamic behavior of electrons at such a scale and their consequences on the tunable physical properties of nanostructures have not been well understood [C. Q. Sun, Prog Solid State Chem 35, 1-159 (2007);Prog Mater Sci 54, 179-307 (2009)]. The objective of the contribution is to update the recent progress in dealing with the coordination-resolved energetic and dynamic behavior of bonds in the low-dimensional systems with consideration of the joint effect of temperature and pressure. It is shown that the broken-bond-induced local strain and the associated charge and energy quantum trapping at the defect sites perturbs the atomic cohesive energy, electroaffinity, the Hamiltonian and the associated properties of entities ranging from point defects, surfaces, nanocavities and nanostructures. application of the theories to observations has led to consistent understanding of the behavior of nanometer-sized materials and the interdependence of these entities as well as the means of determining the bond energy through the temperature-dependent measurements. © (2010) Trans Tech Publications.

关键词： Hamiltonians

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Discovery of Motif Pairs from Protein-Protein Interaction Networks

Discovery of Motif Pairs from Protein-Protein Interaction Ne...

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International Joint Conference on Bioinformatics, Systems Biology and Intelligent computing, IJCBS

作者： Hong Zhang Yun Xu Yuzhong Zhao Department of Computer Science Anhui Province-MOST Co-Key Laboratory of High Performance Computing and Its Application University of Science and Technology Hefei Anhui China

Motif pairs can provide insight on how protein-protein interactions are encoded. Their discovery requires laborious and expensive biological experiments. Recently, Tan et al. proposed a computational approach to find motif pairs in the sequences of interacting proteins. However, their approach suffers from two drawbacks. The heuristic used in their approach is not accurate and may lead to a result including some false positive motif instances. Their approach is also not scalable. It may take days to process a set of 5000 protein sequences with about 20,000 interactions. We present in this work a new algorithm DMPCP, which finds motifs from a subset of proteins and then pairs them up according to Chi-squared scoring functions. Experiments on real biological datasets and simulated datasets show that our approach is efficient and can find actual motif pairs. We also evaluated our approach on simulated datasets with planted motif pairs. The results show that our approach can achieve high success rates when interaction data is insufficient.

关键词： Protein engineering Sequences Biology computing Computer networks high performance computing Biological information theory Biological system modeling Bioinformatics Systems biology Intelligent systems

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Visualization for Anomaly Detection and Data Management by Leveraging Network, Sensor and GIS Techniques

Visualization for Anomaly Detection and Data Management by L...

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International Conference on Parallel and Distributed Systems (ICPADS)

作者： Zhaoxia Wang Chee Seng Chong Rick Siow Mong Goh Wanqing Zhou Dan Peng Hoong Chor Chin Department of Computing Science Institute of High Performance Computing Singapore Institute of High Performance Computing Singapore SG Tianjin Hanker Science & Technology Development Co. Ltd Tianjin P.R. China Department of Civil & Environmental Engineering National University of Singapore Singapore

This paper studies the importance of visualization for discerning and interpreting patterns of data and its application for solving real problems, such as anomaly detection and data management. There are various ways to realize visualization to cater to the needs of numerous real life applications. Depending on needs, a combination of some of these ways may be required for presenting an effective visualization. The authors present visualization schemes for anomaly detection/condition monitoring and data management by leveraging network techniques and combining them with modern techniques such as sensor, database, mobile communication, GPS and GIS techniques. Two case studies are presented and analyzed. By stepping through the design and implementation processes of these projects, this paper aims to serve as a guide for other designers or researchers to create visual analysis tools or implement projects requiring such visualization.

关键词： Data visualization Servers Real-time systems Mobile communication Global Positioning System Databases Visualization

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EMC design with embedded metamaterial technology

EMC design with embedded metamaterial technology

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IEEE International Symposium on Electromagnetic Compatibility

作者： Richard Xian-Ke Gao Si-Ping Gao Hui Min Lee Wanlan Yang Electronics and Photonics Department Institute of High Performance Computing A~*STAR Singapore 138632 Engineering Product Development Singapore University of Technology and Design Singapore 487372

ISBN: (纸本)9781509039555

Due to the special negative electromagnetic properties, metamaterial has gained wide attention and also been increasingly applied in electromagnetic compatibility (EMC). In the paper, the metamaterial associated EMC design has been addressed through two case studies, one is defected ground structure for common-mode noise inhibition and another is frequency selective surface for the sake of shielding effectiveness for high speed electronics. The results manifest that metamaterial can provide effective solutions to tackle electromagnetic interference issues where conventional EMC approaches are difficult to be deployed or even lose efficacy.

关键词： defected ground structure electromagnetic bandgap electromagnetic compatibility frequency selective surface metamaterial

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Temporal and spectral compression using two-stage nonlinear integrated systems on ultra-silicon-rich nitride

Temporal and spectral compression using two-stage nonlinear ...

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Nonlinear Optics, NLO 2019

作者： Choi, Ju Won Sahin, Ezgi Sohn, Byoung-Uk Chen, George F.R. Ng, Doris K. T. Tan, Dawn T. H. Photonics Devices and System Group Engineering Product Development Singapore University of Technology and Design Singapore487372 Singapore Electronics and Photonics Department Institute of High Performance Computing Agency for Science Technology and Research 1 Fusionopolis Way Singapore138632 Singapore Institute of Microelectronics Agency for Science Technology and Research 2 Fusionopolis Way #08-02 Innovis Tower Singapore138634 Singapore

We demonstrate pulse compression using ultra-silicon-rich nitride grating devices. Frequency chirp from a waveguide is temporally synchronized by a dispersive grating to achieve temporal compression by a factor of 4.3... 详细信息

ISBN: (纸本)9781943580620

关键词： Silicon nitride

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Efficient reconstruction of CASCI-type wave functions for a DMRG state using quantum information theory and genetic algorithm

arXiv

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arXiv 2017年

作者： Luo, Z. Ma, Y. Liu, C. Ma1, H. Key Laboratory of Mesoscopic Chemistry of MOE School of Chemistry and Chemical Engineering Nanjing University Nanjing210023 China Department of High Performance Computing Technology and Application Development Computer Network Information Center Chinese Academy of Sciences Beijing100190 China

We improve the methodology to construct a complete active space-configuration interaction (CAS-CI) expansion for density-matrix renormalization group (DMRG) wave function using matrix-product state representation, nspired by the sampling-reconstructed CAS [SR-CAS, Boguslawski et al, J. Chem. Phys. 2011, 134, 224101] algorithm. In our scheme, a genetic algorithm, n which the "crossover" and "mutation" process can be optimized based on quantum information theory, s employed when reconstructing the CASCI-type wave function in the Hilbert space. Test analysis results for the ground and excited state wave functions of conjugated molecules and transition metal compounds illustrate that our scheme is very efficient for searching the most important CI expansions in large active spaces. Copyright © 2017, The Authors. All rights reserved.

关键词： Wave functions

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Multi-reference Epstein-Nesbet perturbation theory with density matrix renormalization group reference wavefunction

arXiv

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arXiv 2019年

作者： Song, Yinxuan Cheng, Yifan Ma, Yingjin Ma, Haibo School of Chemistry and Chemical Engineering Nanjing University Nanjing210023 China Department of High Performance Computing Technology and Application Development Computer Network Information Center Chinese Academy of Sciences Beijing100190 China Center of Scientific Computing Applications & Research Chinese Academy of Sciences Beijing100190 China

The accurate electronic structure calculation for strongly correlated chemical systems requires an adequate description for both static and dynamic electron correlation, and is a persistent challenge for quantum chemistry. In order to account for static and dynamic electron correlations accurately and efficiently, in this work we propose a new method by integrating the density matrix renormalization group (DMRG) method and multi-reference second-order Epstein-Nesbet perturbation theory (ENPT2) with a selected configuration interaction (SCI) approximation. Compared to previous DMRG-based dynamic correlation methods, the DMRG-ENPT2 method extends the range of applicability, allowing us to efficiently calculate systems with very large active spaces beyond 30 orbitals. We demonstrate this by performing calculations on H2S with an active space of (16e, 15o), hexacene with an active space of (26e, 26o) and trinuclear Manganese cluster with an active space of (47e, 43o). Copyright © 2019, The Authors. All rights reserved.

关键词： Quantum chemistry

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A Smart Forecasting System of Computational Cost of DFT calculations using Machine Learning and Cheminformatics

A Smart Forecasting System of Computational Cost of DFT calc...

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2019中国化学会第十五届全国计算（机）化学学术会议

作者：马硕 Yingjin Ma Baohua Zhang Yingqi Tian Zhong Jin 中科院计算机网络信息中心 Department of High Performance Computing Technology and Application Development Computer Network Information Center Chinese Academy of Sciences Center of Scientific Computing Applications & Research Chinese Academy of Sciences School of Computer Science and Technology University of Chinese Academy of Sciences

The Density-functional theory(DFT) should be the most popular approach that used in computational physics or computational chemistry community. Normally, the computational time is unknown until the calculation is done. And as such, researchers can hardly arrange their schedules rationally. Additionally, for calculations that are carried out with computing clusters, unreasonable schedules would greatly increase the time and energy cost. Herein, we introduced a smart forecasting system based on three machine learning models, which are RF with FNNs(random forest with feedforward neural networks), Bi-LSTM with attention mechanism[1,2,3] and MPNN[4](message passing neural networks). The three models can accept the molecular information, calculating scheme(the combination of basis set and functional etc.) and machine configuration information as inputs, and then can predict the proposed computational cost. Comparing to the actual computational time, the average relative error is generally less than 20%, and it follows the normal distribution[5].

关键词： density-functional theory machine learning neural networks cheminformatics

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