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This paper presents a new approach to verify accuracy of computational simulations. We develop mathematical theorems which can serve as robust a posteriori error estimation techniques to identify numerical pollution, check the performance…

Numerical Analysis · Computer Science 2016-11-23 M. Shabouei , K. B. Nakshatrala

This paper studies an evolving bulk--surface finite element method for a model of tissue growth, which is a modification of the model of Eyles, King and Styles (2019). The model couples a Poisson equation on the domain with a forced mean…

Numerical Analysis · Mathematics 2024-01-18 Dominik Edelmann , Balázs Kovács , Christian Lubich

We investigate a cellular automaton (CA) model of traffic on a bi-directional two-lane road. Our model is an extension of the one-lane CA model of {Nagel and Schreckenberg 1992}, modified to account for interactions mediated by passing, and…

Statistical Mechanics · Physics 2009-10-31 Patrice Simon , Howard A Gutowitz

At the continuous level, we consider two types of tumor growth models: the cell density model, which is based on the fluid mechanical construction, is more favorable for scientific interpretation and numerical simulations; and the free…

Analysis of PDEs · Mathematics 2019-10-28 Jian-Guo Liu , Min Tang , Li Wang , Zhennan Zhou

Cellular automata have turned out to be important tools for the simulation of traffic flow. They are designed for an efficient impletmentation on the computer, but hard to treat analytically. Here we discuss several approaches for an…

Statistical Mechanics · Physics 2007-05-23 Andreas Schadschneider

Statistical modeling of nuclear data provides a novel approach to nuclear systematics complementary to established theoretical and phenomenological approaches based on quantum theory. Continuing previous studies in which global statistical…

Nuclear Theory · Physics 2009-11-06 N. J. Costiris , E. Mavrommatis , K. A. Gernoth , J. W. Clark

We introduce density dependence of the cell size in cellular-automaton models for traffic flow, which allows a more precise correspondence between real-world phenomena and what observed in simulation. Also, we give an explicit calibration…

Cellular Automata and Lattice Gases · Physics 2015-05-18 Masahiro Kanai

In assumed probability density function (pdf) methods of turbulent combustion, the shape of the scalar pdf is assumed a priori and the pdf is parametrized by its moments for which model equations are solved. In non-premixed flows the beta…

Fluid Dynamics · Physics 2010-11-05 J. Bakosi , J. R. Ristorcelli

In the present investigation we use observational data of $ f \sigma_ {8} $ to determine observational constraints in the plane $(\Omega_{m0},\sigma_{8})$ using two different methods: the growth factor parametrization and the numerical…

Cosmology and Nongalactic Astrophysics · Physics 2021-02-03 A. M. Velásquez-Toribio , Júlio C. Fabris

The large-scale shell-model calculations have been performed for the neutron-rich nuclei in the south region of $^{208}$Pb in the nuclear chart. The $\beta$-decay properties, such as the $\log ft$, average shape factor values, half-lives,…

This paper investigates the beta decay of nuclei within the sd model space, encompassing the $0d_{3/2}$, $0d_{5/2}$, and $1s_{1/2}$ shells. We comprehensively analyze their decay characteristics, including the half-life, $logft$ value, Q…

Nuclear Theory · Physics 2023-07-25 Surender Siwach

Neutrinoless double-beta decay is a unique process that could reveal physics beyond the Standard Model. Essential ingredients in the analysis of neutrinoless double-beta rates are the associated nuclear matrix elements. Most of the…

Nuclear Theory · Physics 2013-12-17 R. A. Sen'kov , M. Horoi

The role of numerical accuracy in training and evaluating neural network-based potential energy surfaces is examined for different experimental observables. For observables that require third- and fourth-order derivatives of the total…

Chemical Physics · Physics 2023-11-30 Silvan Käser , Markus Meuwly

Predictive modeling is the key factor for saving time and resources with respect to manufacturing processes such as fermentation processes arising e.g.\ in food and chemical manufacturing processes. According to Zhang et al. (2002), the…

Analysis of PDEs · Mathematics 2021-04-15 Christina Schenk , Volker H. Schulz

The Stokes-Brinkman equations model flow in heterogeneous porous media by combining the Stokes and Darcy models of flow into a single system of equations. With suitable parameters, the equations can model either flow without detailed…

Numerical Analysis · Mathematics 2019-08-28 Kevin Williamson , Pavel Burda , Bedřich Sousedík

We describe how to consistently incorporate solar model uncertainties, along with experimental errors and correlations, when analyzing solar neutrino data to derive confidence limits on parameter space for proposed solutions of the solar…

High Energy Physics - Phenomenology · Physics 2008-11-26 Evalyn Gates , Lawrence M. Krauss , Martin White

Bayesian nonparametric mixture models are common for modeling complex data. While these models are well-suited for density estimation, recent results proved posterior inconsistency of the number of clusters when the true number of…

Statistics Theory · Mathematics 2024-05-31 Louise Alamichel , Daria Bystrova , Julyan Arbel , Guillaume Kon Kam King

New superheavy nuclei are often identified through their characteristic $\alpha$-decay energies, which requires accurate calculations of $Q_{\alpha}$ values. While many $Q_{\alpha}$ predictions are available, little is known about their…

Nuclear Theory · Physics 2019-01-30 Erik Olsen , Witold Nazarewicz

Modelling interfacial dynamics with soluble surfactants in a multiphase system is a challenging task. Here, we consider the numerical approximation of a phase-field surfactant model with fluid flow. The nonlinearly coupled model consists of…

Computational Physics · Physics 2020-03-02 Guangpu Zhu , Jisheng Kou , Shuyu Sun , Jun Yao , Aifen Li

In complex physical process characterization, such as the measurement of the regression rate for solid hybrid rocket fuels, where both the observation data and the model used have uncertainties originating from multiple sources, combining…

Machine Learning · Computer Science 2023-03-21 Georgios Georgalis , Kolos Retfalvi , Paul E. DesJardin , Abani Patra
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