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A Navier-Stokes-Korteweg Model for Dynamic Wetting based on the PeTS Equation of State

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A Navier-Stokes-Korteweg Model for Dynamic Wetting based on ...

90th Annual Meeting of the International Association of Applied mathematics and Mechanics, GAMM 2019

作者： Diewald, Felix Heier, Michaela Lautenschläger, Martin Horsch, Martin Kuhn, Charlotte Langenbach, Kai Hasse, Hans Müller, Ralf Institute of Applied Mechanics TU Kaiserslautern Kaiserslautern67653 Germany Laboratory of Engineering Thermodynamics TU Kaiserslautern Kaiserslautern67653 Germany Scientific Computing Department Daresbury Laboratory WarringtonWA4 4AD United Kingdom Computational Mechanics TU Kaiserslautern Kaiserslautern67653 Germany

Dynamic wetting of component surfaces can be investigated by finite element phase field simulations. Often these models use a double-well potential or the van der Waals equation to define the local part of the free energy density at a point of the computational domain. In order to give the present model a stronger physical background the molecular dynamics based perturbed Lennard-Jones truncated and shifted (PeTS) equation of state is used instead. This results in phase field liquid-vapor interfaces that agree with the physical density gradient between the two phases. In order to investigate dynamic scenarios, the phase field description is coupled to the compressible Navier-Stokes equations. This coupling requires a constitutive equation that complies with the surface tension of the liquid-vapor interface resulting from the PeTS equation of state and is comparable to the so-called Korteweg tensor. © 2019 The Authors Proceedings in Applied mathematics & Mechanics published by Wiley-VCH Verlag GmbH & Co. KGaA Weinheim.

关键词： Equations of state

The Studying of Hydrogen Diffusion Non-Stationary Processes Near a Crack in the Field of Heterogeneous Mechanical Tensions for the Encapsulated MEMS Devices

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The Studying of Hydrogen Diffusion Non-Stationary Processes ...

International Conference on Perspective Technologies and Methods in MEMS Design (MEMSTECH)

作者： Winfried Auzinger Roksolyana Stolyarchuk Yaroslav Pelekh Oksana Kozar Serhii Mentynskyi Mykola Ihnatyshyn Institute for Analysis and Scientific Computing Vienna University of Technology (TU Wien) Wien Austria Department of Computational Mathematics and Programming Lviv Polytechnic National University Lviv Ukraine Department of Mechanical Engineering Natural Sciences and Information Technologies Mukachevo State University Mukachevo Ukraine Department of Light Industry and Professional Education Mukachevo State University Mukachevo Ukraine

ISBN: (数字)9781728171807

ISBN: (纸本)9781728171814

In this paper we study an elastic-plastic isotropic body weakened by a rectilinear crack, directed along the abscissa axis, under the action of stresses symmetrical about its plane. An approximate (analytical and numerical) solution of this problem is constructed under the condition that the hydrostatic deformation of the split expansion is approximated by a parabola. The concentration of hydrogen near the top of the crack is calculated. Note that when using the above calculation formulas, at each node we get several approximations to the exact solution. In the proposed methods, only three appeals to the right-hand side of the differential equation are necessary to obtain both the third order accuracy method and the two approximations (upper and lower) of the second order of accuracy.

关键词： mathematical model elastic-plastic isotropic body hydrogen diffusion internal crack continued fractions two-sided approximations nonlinear methods diffusion of hydrogen internal cracks MEMS devices cracks Cocaine Fissure mathematical Model Continued fraction Fields

Strategic priorities for transformative progress in advancing biology with proteomics and artificial intelligence

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arXiv 2025年

作者： Sun, Yingying Jun, A. Liu, Zhiwei Sun, Rui Qian, Liujia Payne, Samuel H. Bittremieux, Wout Ralser, Markus Li, Chen Chen, Yi Dong, Zhen Perez-Riverol, Yasset Khan, Asif Sander, Chris Aebersold, Ruedi Vizcaíno, Juan Antonio Krieger, Jonathan R. Yao, Jianhua Wen, Han Zhang, Linfeng Zhu, Yunping Xuan, Yue Sun, Benjamin Boyang Qiao, Liang Hermjakob, Henning Tang, Haixu Gao, Huanhuan Deng, Yamin Zhong, Qing Chang, Cheng Bandeira, Nuno Li, Ming Weinan, E. Sun, Siqi Yang, Yuedong Omenn, Gilbert S. Zhang, Yue Xu, Ping Fu, Yan Liu, Xiaowen Overall, Christopher M. Wang, Yu Deutsch, Eric W. Chen, Luonan Cox, Jürgen Demichev, Vadim He, Fuchu Huang, Jiaxing Jin, Huilin Liu, Chao Li, Nan Luan, Zhongzhi Song, Jiangning Yu, Kaicheng Wan, Wanggen Wang, Tai Zhang, Kang Zhang, Le Bell, Peter A. Mann, Matthias Zhang, Bing Guo, Tiannan Affiliated Hangzhou First People’s Hospital State Key Laboratory of Medical Proteomics School of Medicine Westlake University Zhejiang Province Hangzhou China Westlake Center for Intelligent Proteomics Westlake Laboratory of Life Sciences and Biomedicine Zhejiang Province Hangzhou China Biology Department Brigham Young University ProvoUT84602 United States Department of Computer Science University of Antwerp Antwerp2020 Belgium Department of Biochemistry CharitéUniversitätsmedizin Berlin Berlin Germany Biomedicine Discovery Institute Department of Biochemistry and Molecular Biology Monash University MelbourneVICVIC 3800 Australia Wellcome Genome Campus Hinxton CambridgeCB10 1SD United Kingdom Harvard Medical School Ludwig Center at Harvard United States Harvard Medical School Broad Institute Ludwig Center at Harvard Dana-Farber Cancer Institute United States Department of Biology Institute of Molecular Systems Biology ETH Zürich Zürich Switzerland Bruker Ltd. MiltonONL9T 6P4 Canada AI for Life Sciences Lab Tencent Shenzhen518057 China State Key Laboratory of Medical Proteomics AI for Science Institute Beijing100080 China Beijing Institute of Lifeomics Beijing102206 China Thermo Fisher Scientific GmbH Hanna-Kunath Str. 11 Bremen28199 Germany Informatics and Predictive Sciences Research Bristol Myers Squibb United States Department of Chemistry Fudan University Songhu Road 2005 Shanghai200438 China Department of Computer Science Luddy School of Informatics Computing and Engineering Indiana University IN47408 United States ProCan® Children’s Medical Research Institute Faculty of Medicine and Health The University of Sydney WestmeadNSW Australia La Jolla CA United States Central China Institute of Artificial Intelligence University of Waterloo Canada AI for Science Institute Center for Machine Learning Research School of Mathematical Sciences Peking University China Research Institute of Intelligent Complex Systems Fudan U

Artificial intelligence (AI) is transforming scientific research, including proteomics. Advances in mass spectrometry (MS)-based proteomics data quality, diversity, and scale, combined with groundbreaking AI techniques, are unlocking new challenges and opportunities in biological discovery. Here, we highlight key areas where AI is driving innovation, from data analysis to new biological insights. These include developing an AI-friendly ecosystem for proteomics data generation, sharing, and analysis;improving peptide and protein identification and quantification;characterizing protein-protein interactions and protein complexes;advancing spatial and perturbation proteomics;integrating multi-omics data;and ultimately enabling AI-empowered virtual cells. © 2025, CC BY.

关键词： Biotic

Uplink-downlink duality between multiple-access and broadcast channels with compressing relays

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arXiv 2020年

作者： Liu, Liang Liu, Ya-Feng Patil, Pratik Yu, Wei the Department of Electronic and Information Engineering The Hong Kong Polytechnic University Hong Kong the State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China The Edward S. Rogers Sr. Department of Electrical and Computer Engineering the University of Toronto the Department of Statistics and Data Science and the Machine Learning Department Carnegie Mellon University PittsburghPA15213 United States The Edward S. Rogers Sr. Department of Electrical and Computer Engineering University of Toronto 10 King’s College Road TorontoONM5S3G4 Canada

—Uplink-downlink duality refers to the fact that under a sum-power constraint, the capacity regions of a Gaussian multiple-access channel and a Gaussian broadcast channel with Hermitian transposed channel matrices are identical. This paper generalizes this result to a cooperative cellular network, in which remote access-points are deployed as relays in serving the users under the coordination of a central processor (CP). In this model, the users and the relays are connected over noisy wireless links, while the relays and the CP are connected over noiseless but rate-limited fronthaul links. Based on a Lagrangian technique, this paper establishes a duality relationship between such a multiple-access relay channel and broadcast relay channel, under the assumption that the relays use compression-based strategies. Specifically, we show that under the same total transmit power constraint and individual fronthaul rate constraints, the achievable rate regions of the Gaussian multiple-access and broadcast relay channels are identical, when either independent compression or Wyner-Ziv and multivariate compression strategies are used. The key observations are that if the beamforming vectors at the relays are fixed, the sum-power minimization problems under the achievable rate and fronthaul constraints in both the uplink and the downlink can be transformed into either a linear programming or a semidefinite programming problem depending on the compression technique, and that the uplink and downlink problems are Lagrangian duals of each other. Moreover, the dual variables corresponding to the downlink rate constraints become the uplink powers;the dual variables corresponding to the downlink fronthaul constraints become the uplink quantization noises. This duality relationship enables an efficient algorithm for optimizing the downlink transmission and relaying strategies based on the uplink. Copyright © 2020, The Authors. All rights reserved.

关键词： Linear programming

Lethe-DEM: An open-source parallel discrete element solver with load balancing

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arXiv 2021年

作者： Golshan, Shahab Munch, Peter Gassmöller, Rene Kronbichler, Martin Blaisa, Bruno Department of Chemical Engineering École Polytechique de Montréal PO Box 6079 Stn Centre-Ville MontréalQCH3C 3A7 Canada Continuum Simulations Institute of Material Systems Modeling Helmholtz-Zentrum Hereon GmbH Germany Max-Planck-Str. 1 Geesthacht21502 Germany Institute for Computational Mechanics Technical University of Munich Boltzmannstr. 15 Garching85748 Germany Department of Geological Sciences University of Florida GainesvilleFL United States Division of Scientific Computing Department of Information Technology Uppsala University Box 337 Uppsala75105 Sweden

Approximately 75% of the raw material and 50% of the products in the chemical industry are granular materials. The Discrete Element Method (DEM) provides detailed insights of phenomena at particle scale and it is therefore often used for modeling granular materials. However, because DEM tracks the motion and contact of individual particles separately, its computational cost increases non-linearly O(np log(np)) - O(n2p) depending on the algorithm) with the number of particles (np). In this article, we introduce a new open-source parallel DEM software with load balancing: Lethe-DEM. Lethe-DEM, a module of Lethe, consists of solvers for two-dimensional and three-dimensional DEM simulations. Load-balancing allows Lethe-DEM to significantly increase the parallel efficiency by ≈ 25 − 70% depending on the granular simulation. We explain the fundamental modules of Lethe-DEM, its software architecture, and the governing equations. Furthermore, we verify Lethe-DEM with several tests including analytical solutions and comparison with other software. Comparisons with experiments in a flat-bottomed silo, wedge-shaped silo, and rotating drum validate Lethe-DEM. We investigate the strong and weak scaling of Lethe-DEM with 1 ≤ nc ≤ 192 and 32 ≤ nc ≤ 320 processes, respectively, with and without load-balancing. The strong-scaling analysis is performed on the wedge-shaped silo and rotating drum simulations, while for the weak-scaling analysis, we use a dam break simulation. The best scalability of Lethe-DEM is obtained in the range of 5000 ≤ np/nc ≤ 15 000. Finally, we demonstrate that large scale simulations can be carried out with Lethe-DEM using the simulation of a three-dimensional cylindrical silo with np = 4.3 × 106 on 320 cores. Copyright © 2021, The Authors. All rights reserved.

关键词： Finite difference method

Energy-preserving exponential integrable numerical method for stochastic cubic wave equation with additive noise

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arXiv 2019年

作者： Cui, Jianbo Hong, Jialin Ji, Lihai Sun, Liying School of Mathematics Georgia Institute of Technology AtlantaGA30332 United States Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China Institute of Applied Physics and Computational Mathematics Beijing100094 China

In this paper, we present an energy-preserving exponentially integrable numerical method for stochastic wave equation with cubic nonlinearity and additive noise. We first apply the spectral Galerkin method to discretizing the original equation and show that this spatial discretization possesses an energy evolution law and certain exponential integrability property. Then the exponential integrability property of the exact solution is deduced by proving the strong convergence of the semi-discretization. To propose a full discrete numerical method which could inherit both the energy evolution law and the exponential integrability, we use the splitting technique and averaged vector field method in the temporal direction. Combining these structure-preserving properties with regularity estimates of the exact and the numerical solutions, we obtain the strong convergence rate of the numerical method. Numerical experiments coincide with these theoretical results. Copyright © 2019, The Authors. All rights reserved.

关键词： Stochastic systems

Considerations for a Distributed GraphBLAS API

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Considerations for a Distributed GraphBLAS API

IEEE International Symposium on Parallel and Distributed Processing Workshops and Phd Forum (IPDPSW)

作者： Benjamin Brock Aydin Buluç Timothy G. Mattson Scott McMillan José E. Moreira Roger Pearce Oguz Selvitopi Trevor Steil EECS Department University of California Berkeley CA Computational Research Department Lawrence Berkeley National Laboratory Berkeley CA Parallel Computing Labs Intel Hillsboro OR Software Engineering Institute Carnegie Mellon University Pittsburgh PA IBM Thomas J. Watson Research Center Yorktown Heights NY Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore CA School of Mathematics University of Minnesota Minneapolis MN

ISBN: (数字)9781728174457

ISBN: (纸本)9781728174570

The GraphBLAS emerged from an international effort to standardize linear-algebraic building blocks for computing on graphs and graph-structured data. The GraphBLAS is expressed as a C API and has paved the way for multiple implementations. The GraphBLAS C API, however, does not define how distributed-memory parallelism should be handled. This paper reviews various approaches for a GraphBLAS API for distributed computing. This work is guided by our experience with existing distributed memory libraries. Our goal for this paper is to highlight the pros and cons of different approaches rather than to advocate for one particular choice.

关键词： Context Parallel processing Libraries Data structures Task analysis Message systems Electronics packaging

On energy stable, maximum-principle preserving, second order BDF scheme with variable steps for the Allen-Cahn equation

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arXiv 2020年

作者： Liao, Hong-Lin Tang, Tao Zhou, Tao Department of Mathematics Nanjing University of Aeronautics and Astronautics Nanjing211106 China SUSTech International Center for Mathematics Shenzhen China Division of Science and Technology BNU-HKBU United International College ZhuhaiGuangdong Province China NCMIS LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China

In this work, we investigate the two-step backward differentiation formula (BDF2) with nonuniform grids for the Allen-Cahn equation. We show that the nonuniform BDF2 scheme is energy stable under the time-step ratio r... 详细信息

关键词： Maximum principle

Joint switch upgrade and controller deployment in hybrid software-defined networks

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arXiv 2019年

作者： Guo, Zehua Chen, Weikun Liu, Ya-Feng Xu, Yang Zhang, Zhi-Li Department of Computer Science and Engineering University of Minnesota Twin Cities MinneapolisMN55455 United States State Key Laboratory of Scientific and Engineering Computing Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing100190 China School Of Computer Science Fudan University Shanghai200433 China

To improve traffic management ability, Internet Service Providers (ISPs) are gradually upgrading legacy network devices to programmable devices that support Software-Defined Networking (SDN). The coexistence of legacy and SDN devices gives rise to a hybrid SDN. Existing hybrid SDNs do not consider the potential performance issues introduced by a centralized SDN controller: flow requests processed by a highly loaded controller may experience long tail processing delay;inappropriate multi-controller deployment could increase the propagation delay of flow requests. In this paper, we propose to jointly consider the deployment of SDN switches and their controllers for hybrid SDNs. We formulate the joint problem as an optimization problem that maximizes the number of flows that can be controlled and managed by the SDN and minimizes the propagation delay of flow requests between SDN controllers and switches under a given upgrade budget constraint. We show this problem is NP-hard. To efficiently solve the problem, we propose some techniques (e.g., strengthening the constraints and adding additional valid inequalities) to accelerate the global optimization solver for solving the problem for small networks and an efficient heuristic algorithm for solving it for large networks. The simulation results from real network topologies illustrate the effectiveness of the proposed techniques and show that our proposed heuristic algorithm uses a small number of controllers to manage a high amount of flows with good performance. Copyright © 2019, The Authors. All rights reserved.

关键词： Software defined networking