Mixed semi-Lagrangian/finite difference methods for plasma simulations

In this paper, we present an efficient algorithm for the long time behavior of plasma simulations. We will focus on 4D drift-kinetic model, where the plasma's motion occurs in the plane perpendicular to the magnetic field and can be governed by the 2D guiding-center model. Hermite WENO reconstructions, already proposed in \cite{YF15}, are applied for solving the Vlasov equation. Here we consider an arbitrary computational domain with an appropriate numerical method for the treatment of boundary conditions. Then we apply this algorithm for plasma turbulence simulations. We first solve the 2D guiding-center model in a D-shape domain and investigate the numerical stability of the steady state. Then, the 4D drift-kinetic model is studied with a mixed method, i.e. the semi-Lagrangian method in linear phase and finite difference method during the nonlinear phase. Numerical results show that the mixed method is efficient and accurate in linear phase and it is much stable during the nonlinear phase. Moreover, in practice it has better conservation properties.Comment: arXiv admin note: text overlap with arXiv:1312.448

Conservative and non-conservative methods based on hermite weighted essentially-non-oscillatory reconstruction for Vlasov equations

We introduce a WENO reconstruction based on Hermite interpolation both for semi-Lagrangian and finite difference methods. This WENO reconstruction technique allows to control spurious oscillations. We develop third and fifth order methods and apply them to non-conservative semi-Lagrangian schemes and conservative finite difference methods. Our numerical results will be compared to the usual semi-Lagrangian method with cubic spline reconstruction and the classical fifth order WENO finite difference scheme. These reconstructions are observed to be less dissipative than the usual weighted essentially non- oscillatory procedure. We apply these methods to transport equations in the context of plasma physics and the numerical simulation of turbulence phenomena

Numerical study of a nonlinear heat equation for plasma physics

This paper is devoted to the numerical approximation of a nonlinear temperature balance equation, which describes the heat evolution of a magnetically confined plasma in the edge region of a tokamak. The nonlinearity implies some numerical difficulties, in particular long time behavior, when solved with standard methods. An efficient numerical scheme is presented in this paper, based on a combination of a directional splitting scheme and the IMEX scheme introduced in [Filbet and Jin

An inverse Lax-Wendroff method for boundary conditions applied to Boltzmann type models

International audienceIn this paper we present a new algorithm based on Cartesian meshes for the numerical approximation of kinetic models set in an arbitrary geometry. Due to the high dimensional property of kinetic models, numerical algorithms based on unstructured meshes are not really appropriate since most of numerical methods (semi-Lagrangian, spectral methods) are particularly efficient on structured grids. Here we propose to adapt the inverse Lax-Wendroff procedure, which has been recently introduced for conservation laws [21], for kinetic equations. Numerical simulations in 1D x 3D and 2D x 3D based on this approach are proposed for Boltzmann type operators (BGK, ES-BGK models)

Shielding from Space Radiations

This Final Progress Report for NCC-1-178 presents the details of the engineering development of an analytical/computational solution to the heavy ion transport equation in terms of a multi-layer Green's function formalism as applied to the Small Spacecraft Technology Initiative (SSTI) program. The mathematical developments are recasted into a series of efficient computer codes for space applications. The efficiency of applied algorithms is accomplished by a nonperturbative technique of extending the Green's function over the solution domain. The codes may also be applied to the accelerator boundary conditions to allow code validation in laboratory experiments. Correlations with experiments for the isotopic version of the code with 59 and 80 isotopes present for a two layers target material in water has been verified

PVW: Designing Virtual World Server Infrastructure

This paper presents a high level overview of PVW (Partitioned Virtual Worlds), a distributed system architecture for the management of virtual worlds. PVW is designed to support arbitrarily large and complex virtual worlds while accommodating dynamic and highly variable user population and content distribution density. The PVW approach enables the task of simulating and managing the virtual world to be distributed over many servers by spatially partitioning the environment into a hierarchical structure. This structure is useful both for balancing the simulation load across many nodes, as well as features such as geometric simplification and distribution of dynamic content

Appreciating the Performance of Neuroscience Mining in NeuroIS research: A Case Study on Consumer's Product Perceptions in the Two UI Modes—Dark UI vs. Light UI

The goal of the current study was to provide information on the potential of neuroscience mining (NSM) for comprehending NeuroIS paradigms. NSM is an interdisciplinary field that combines neuroscience and business mining, which is the application of big data analytics, computational social science, and other fields to business problems. Therefore, NSM makes it possible to apply predictive models to NeuroIS datasets, such as machine learning and deep learning, to find intricate patterns that are hidden by conventional regression-based analysis. We predicted 28 individual EEG power spectra separated brainwave data using a Random Forest (RF) model. Next, we used NSM to precisely predict how consumers would perceive a product online, depending on whether a light or dark user interface (UI) mode was being used. The model was then used to extract more precise results that could not be obtained using more conventional linear-based analytical models using sensitivity analysis. The benefits of using NSM in NeuroIS research are as follows: (1) it can relieve the burden of the three-horned dilemma described by Runkel and McGrath; (2) it can enable more temporal data to be directly analyzed on the target variables; and (3) sensitivity analysis can be performed on a condition/individual basis, strengthening the rigor of findings by reducing sample bias that can be lost in grand averaging of data when analyzed with methods like GLM

Kinetic phenomena in mechanochemical depolymerization of poly(styrene

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Digital Dark Nudge: An Exploration of When Digital Nudges Unethically Depart

Digital nudging in information systems has become widely prevalent to guide consumers during online decision-making. However, while nudging is about improving the decisions and behaviors in various domains, limited research has explored when digital nudges unethically depart from their intended purpose, whereby opt-in favors profit motives over the user’s best interests. In e-commerce, we defined this as a digital dark nudge (DDN) and explored its use in multiple scenarios against a typical shopping experience. Using an online experiment, we study the economic intentions and emotional perceptions of DDNs, while also accounting for impulsiveness as a moderating personality trait. This study first attempts to use priming and status quo bias as a theoretical lens, and empirical results show increasing evidence of the perverse effects of using DDNs in online e-commerce whereby consumers revert to their status quo, less likelihood of purchase. Our results provide further warning to practitioners about their use of ethical practices such as digital nudging