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Dimensional scaling of flame propagation in discrete particulate clouds

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arXiv 2019年

作者： Lam, Fredric Y.K. Mi, XiaoCheng Higgins, Andrew J. Institute for Computational and Mathematical Engineering Stanford University StanfordCA94305 United States Laboratory for Scientific Computing Cavendish Laboratory Department of Physics University of Cambridge CambridgeCB3 0HE United Kingdom Department of Mechanical Engineering McGill University MontrealQCH3A 0C3 Canada

The critical dimension necessary for a flame to propagate in suspensions of fuel particles in oxidizer is studied analytically and numerically. Two types of models are considered: First, a continuum model, wherein the individual particulate sources are not resolved and the heat release is assumed spatially uniform, is solved via conventional finite difference techniques. Second, a discrete source model, wherein the heat diffusion from individual sources is modeled via superposition of the Green’s function of each source, is employed to examine the influence of the random, discrete nature of the media. Heat transfer to cold, isothermal walls and to a layer of inert gas surrounding the reactive medium are considered as the loss mechanisms. Both cylindrical and rectangular (slab) geometries of the reactive medium are considered, and the flame speed is measured as a function of the diameter and thickness of the domains, respectively. In the continuum model with inert gas confinement, a universal scaling of critical diameter to critical thickness near 2:1 is found. In the discrete source model, as the time scale of heat release of the sources is made small compared to the interparticle diffusion time, the geometric scaling between cylinders and slabs exhibits values greater than 2:1. The ability of the flame in the discrete regime to propagate in thinner slabs than predicted by continuum scaling is attributed to the flame being able to exploit local fluctuations in concentration across the slab to sustain propagation. As the heat release time of the sources is increased, the discrete source model reverts back to results consistent with the continuum model. Implications of these results for experiments are discussed. Copyright © 2019, The Authors. All rights reserved.

关键词： Solvents

π-anisotropy: A nanocarbon route to hard magnetism

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Physical Review B 2020年第6期101卷 060408(R)-060408(R)页

作者： Timothy Moorsom Shoug Alghamdi Sean Stansill Emiliano Poli Gilberto Teobaldi Marijan Beg Hans Fangohr Matt Rogers Zabeada Aslam Mannan Ali B. J. Hickey Oscar Cespedes School of Physics and Astronomy University of Leeds Leeds LS2 9JT United Kingdom Department of Physics Taibah University Medina 42331 Saudi Arabia Scientific Computing Department STFC-UKRI Rutherford Appleton Laboratory OX11 0QX Didcot United Kingdom Beijing Computational Science Research Center 100193 Beijing China Stephenson Institute for Renewable Energy Department of Chemistry University of Liverpool Liverpool L69 3BX United Kingdom School of Chemistry University of Southampton Southampton SO17 1BJ United Kingdom Faculty of Engineering and Physical Sciences University of Southampton Southampton United Kingdom European XFEL GmbH Holzkoppel 4 22869 Schenefeld Germany

High coercivity magnets are an important resource for renewable energy, electric vehicles, and memory technologies. Most hard magnetic materials incorporate rare earths such as neodymium and samarium, but concerns about the environmental impact and supply stability of these materials are prompting research into alternatives. Here, we present a hybrid bilayer of cobalt and the nanocarbon molecule C60 which exhibits significantly enhanced coercivity with minimal reduction in magnetization. We demonstrate how this anisotropy enhancing effect cannot be described by existing models of molecule-metal magnetic interfaces. We outline a form of anisotropy, arising from asymmetric magnetoelectric coupling in the metal-molecule interface. Because this phenomenon arises from π−d hybrid orbitals, we propose calling this effect π-anisotropy. While the critical temperature of this effect is currently limited by the rotational degree of freedom of the chosen molecule, C60, we describe how surface functionalization would allow for the design of room-temperature, carbon-based hard magnetic films.

关键词： Anisotropic magnetoresistance Exchange bias Magnetic anisotropy Magnetism Bilayer films Fullerenes Interfaces Density functional calculations Magnetization measurements Micromagnetic modeling

Energy stable second order linear schemes for the allen-cahn phase-field equation

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arXiv 2018年

作者： Wang, Lin Yu, Haijun LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing100049 China NCMIS and LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Beijing100190 China

Phase-field model is a powerful mathematical tool to study the dynamics of interface and morphol- ogy changes in fluid mechanics and material sciences. However, numerically solving a phase field model for a real problem is a challenge task due to the non-convexity of the bulk energy and the small interface thickness parameter in the equation. In this paper, we propose two stabilized second order semi-implicit linear schemes for the Allen-Cahn phase-field equation based on backward differentiation formula and Crank-Nicolson method, respectively. In both schemes, the nonlinear bulk force is treated explicitly with two second-order stabilization terms, which make the schemes unconditional energy stable and numerically efficient. By using a known result of the spectrum estimate of the linearized Allen-Cahn operator and some regularity estimates of the exact solution, we obtain an optimal second order con- vergence in time with a prefactor depending on the inverse of the characteristic interface thickness only in some lower polynomial order. Both 2-dimensional and 3-dimensional numerical results are presented to verify the accuracy and efficiency of proposed *** Codes 65M12, 65M15, 65P40 Copyright © 2018, The Authors. All rights reserved.

关键词： Fluid mechanics

A CASCADIC MULTIGRID METHOD FOR EIGENVALUE PROBLEM

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Journal of computational mathematics 2017年第1期35卷 74-90页

作者： Xiaole Han Hehu Xie Fei Xu IAPCM Institute of Applied Physics and Computational Mathematics Beijing 100093 China LSEC NCMIS Institute of Computational Mathematics Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China Beijing Institute for Scientific and Engineering Computing Beijing University of Technology Beijing 100124 China

A cascadic multigrid method is proposed for eigenvalue problems based on the multilevel correction scheme. With this new scheme, an eigenvalue problem on the finest space can be solved by linear smoothing steps on a series of multilevel finite element spaces and nonlinear correcting steps on special coarsest spaces. Once the sequence of finite element spaces and the number of smoothing steps are appropriately chosen, the optimal convergence rate with the optimal computational work can be obtained. Some numerical experiments are presented to validate our theoretical analysis.

关键词： Eigenvalue problem Cascadic multigrid Multilevel correction scheme Finiteelement method.

Scalability of high-performance PDE solvers

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arXiv 2020年

作者： Fischer, Paul Min, Misun Rathnayake, Thilina Dutta, Som Kolev, Tzanio Dobrev, Veselin Camier, Jean-Sylvain Kronbichler, Martin Warburton, Tim Swirydowicz, Kasia Brown, Jed Mathematics and Computer Science Argonne National Laboratory LemontIL60439 Department of Computer Science University of Illinois at Urbana-Champaign UrbanaIL61801 Department of Mechanical Science and Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 Center for Applied Scientific Computing Lawrence Livermore National Laboratory LivermoreCA94550 Institute for Computational Mechanics Technical University of Munich Garching b. Muenchen85748 Germany Department of Computer Science University of Colorado BoulderCO80309 National Renewable Energy Laboratory LakewoodCO80401 Department of Mathematics Virginia Tech BlacksburgVA24061 Mechanical & Aerospace Engineering Utah State University UT84322

Performance tests and analyses are critical to effective HPC software development and are central components in the design and implementation of computational algorithms for achieving faster simulations on existing and future computing architectures for large-scale application problems. In this paper, we explore performance and space-time trade-offs for important compute-intensive kernels of large-scale numerical solvers for PDEs that govern a wide range of physical applications. We consider a sequence of PDE-motivated bake-off problems designed to establish best practices for efficient high-order simulations across a variety of codes and platforms. We measure peak performance (degrees of freedom per second) on a fixed number of nodes and identify effective code optimization strategies for each architecture. In addition to peak performance, we identify the minimum time to solution at 80% parallel efficiency. The performance analysis is based on spectral and p-type finite elements but is equally applicable to a broad spectrum of numerical PDE discretizations, including finite difference, finite volume, and h-type finite *** Codes 35-04 Copyright © 2020, The Authors. All rights reserved.

关键词： Computer architecture

Incentivizing wi-fi network crowdsourcing: A contract theoretic approach

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arXiv 2018年

作者： Ma, Qian Gao, Lin Liu, Ya-Feng Huang, Jianwei Department of Information Engineering Chinese University of Hong Kong Hong Kong School of Electronic and Information Engineering Harbin Institute of Technology Shenzhen China 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 China

Crowdsourced wireless community network enables individual users to share their private Wi-Fi access points (APs) with each other, hence can achieve a large Wi-Fi coverage with a small deployment cost via crowdsourcing. This paper presents a novel contract-based incentive framework to incentivize such a Wi-Fi network crowdsourcing under incomplete information (where each user has certain private information such as mobility pattern and Wi-Fi access quality). In the proposed framework, the network operator designs and offers a set of contract items to users, each consisting of a Wi-Fi access price (that a user can charge others for accessing his AP) and a subscription fee (that a user needs to pay the operator for joining the community). Different from the existing contracts in the literature, in our contract model each user's best choice depends not only on his private information but also on other users' choices. This greatly complicates the contract design, as the operator needs to analyze the equilibrium choices of all users, rather than the best choice of each single user. We first derive the feasible contract that guarantees the users' truthful information disclosure based on the equilibrium analysis of user choice, and then derive the optimal (and feasible) contract that yields the maximal profit for the operator. Our analysis shows that a user who provides a higher Wi-Fi access quality is more likely to choose a higher Wi-Fi access price and subscription fee, regardless of the user mobility pattern. Simulation results further show that when increasing the average Wi-Fi access quality of users, the operator can gain more profit, but (counter-intuitively) offer lower Wi-Fi access prices and subscription fees for users. Copyright © 2018, The Authors. All rights reserved.

关键词： Crowdsourcing

FAIR for AI: An interdisciplinary and international community building perspective

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arXiv 2022年

作者： Huerta, E.A. Blaiszik, Ben Brinson, L. Catherine Bouchard, Kristofer E. Diaz, Daniel Doglioni, Caterina Duarte, Javier M. Emani, Murali Foster, Ian Fox, Geoffrey Harris, Philip Heinrich, Lukas Jha, Shantenu Katz, Daniel S. Kindratenko, Volodymyr Kirkpatrick, Christine R. Lassila-Perini, Kati Madduri, Ravi K. Neubauer, Mark S. Psomopoulos, Fotis E. Roy, Avik Rübel, Oliver Zhao, Zhizhen Zhu, Ruike Data Science and Learning Division Argonne National Laboratory LemontIL60439 United States Department of Computer Science University of Chicago ChicagoIL60637 United States Globus University of Chicago ChicagoIL60637 United States Department of Mechanical Engineering and Materials Science Duke University DurhamNC27708 United States Scientific Data Division Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Biological Systems & Engineering Lawrence Berkeley National Laboratory BerkeleyCA94720 United States Helen Wills Neuroscience Institute University of California Berkeley BerkeleyCA94720 United States Department of Physics University of California La Jolla San DiegoCA92093 United States Lund University Department of Physics Box 118 Lund221 00 Sweden School of Physics & Astronomy The University of Manchester ManchesterM13 9PL United Kingdom Leadership Computing Facility Argonne National Laboratory LemontIL60439 United States Biocomplexity Institute Department of Computer Science University of Virginia CharlottesvilleVA22904 United States Department of Physics Massachusetts Institute of Technology CambridgeMA02139 United States Technical University Munich Arcisstraße 21 München80333 Germany Computational Science Initiative Brookhaven National Laboratory UptonNY11973 United States Electrical and Computer Engineering Rutgers The State University of New Jersey PiscatawayNJ08854 United States National Center for Supercomputing Applications University of Illinois Urbana-Champaign UrbanaIL61801 United States Department of Computer Science University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Electrical & Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States School of Information Sciences University of Illinois at Urbana-Champaign UrbanaIL61801 United States San Diego Supercomputer Center University of California La Jolla San DiegoCA

A foundational set of findable, accessible, interoperable, and reusable (FAIR) principles were proposed in 2016 as prerequisites for proper data management and stewardship, with the goal of enabling the reusability of scholarly data. The principles were also meant to apply to other digital assets, at a high level, and over time, the FAIR guiding principles have been reinterpreted or extended to include the software, tools, algorithms, and workflows that produce data. FAIR principles are now being adapted in the context of AI models and datasets. Here, we present the perspectives, vision, and experiences of researchers from different countries, disciplines, and backgrounds who are leading the definition and adoption of FAIR principles in their communities of practice, and discuss outcomes that may result from pursuing and incentivizing FAIR AI research. The material for this report builds on the FAIR for AI Workshop held at Argonne National Laboratory on June 7, 2022. Copyright © 2022, The Authors. All rights reserved.

关键词： Information management

Application of bounded total variation denoising in urban traffic analysis

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arXiv 2018年

作者： Tang, Shanshan Yu, Haijun School of Mathematical Sciences University of Chinese Academy of Sciences LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Beijing100190 China NCMIS LSEC Institute of Computational Mathematics and Scientific/Engineering Computing Academy of Mathematics and Systems Science Beijing100190 China School of Mathematical Sciences University of Chinese Academy of Sciences

While it is believed that denoising is not always necessary in many big data applications, we show in this paper that denoising is helpful in urban traffic analysis by applying the method of bounded total variation denoising to the urban road traffic prediction and clustering problem. We propose two easy-to-implement methods to estimate the parameter noise strength in the denoising algorithm, and apply the denoising algorithm to GPS-based traffic data from Beijing taxi system. For the traffic prediction problem, numerical experiments show that the predicting accuracy is improved by applying the proposed bounded total variation denoising algorithm. For the clustering problem, we apply a recently developed parameter-free clustering analysis method for more than one hundred urban road segments in Beijing based on their velocity profiles. Much better clustering results are obtained after denoising. Copyright © 2018, The Authors. All rights reserved.

关键词： Cluster analysis

Anisotropic spectral manifold wavelet descriptor for deformable shape analysis and matching 26

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Anisotropic spectral manifold wavelet descriptor for deforma...

26th Pacific Conference on Computer Graphics and Applications, Pacific Graphics 2018

作者： Li, Qinsong Liu, Shengjun Hu, Ling Liu, Xinru Institute of Engineering Modeling and Scientific Computing Central South University Hunan Changsha410083 China School of Mathematics and Computational Science Hunan First Normal University Hunan Changsha410205 China State Key Laboratory of High Performance Manufacturing Complex Central South University Hunan Changsha410083 China

ISBN: (纸本)9783038680734

In this paper, we present a novel framework termed Anisotropic Spectral Manifold Wavelet Transform (ASMWT) for shape analysis. ASMWT comprehensively analyzes the signals from multiple directions on local manifold regions of the shape with a series of low-pass and band-pass frequency filters in each direction. Using the ASMWT coefficients of a very simple function, we efficiently construct a localizable and discriminative multiscale point descriptor, named as the Anisotropic Spectral Manifold Wavelet Descriptor (ASMWD). Since the filters used in our descriptor are direction-sensitive and able to robustly reconstruct the signals with a finite number of scales, it makes our descriptor be intrinsic-symmetry unambiguous, compact as well as efficient. The extensive experimental results demonstrate that our method achieves significant performance than several state-of-the-art methods when applied in vertex-wise shape matching. © 2018 The Author(s).

关键词： Wavelet transforms