Communications in Computational Physics 

About: Communications in Computational Physics is an academic journal published by Cambridge University Press. The journal publishes majorly in the area(s): Discretization & Finite element method. It has an ISSN identifier of 1815-2406. Over the lifetime, 1657 publications have been published receiving 30418 citations.

Heterogeneous multiscale methods: A review

Abstract: This paper gives a systematic introduction to HMM, the heterogeneous multiscale methods, including the fundamental design principles behind the HMM philosophy and the main obstacles that have to be ...

Fast numerical methods for stochastic computations: A review

Abstract: This paper presents a review of the current state-of-the-art of numerical methods for stochastic computations. The focus is on efficient high-order methods suitable for practical applications, with a particular emphasis on those based on generalized polynomial chaos (gPC) methodology. The framework of gPC is reviewed, along with its Galerkin and collocation approaches for solving stochastic equations. Properties of these methods are summarized by using results from literature. This paper also attempts to present the gPC based methods in a unified framework based on an extension of the classical spectral methods into multi-dimensional random spaces. AMS subject classifications: 41A10, 60H35, 65C30, 65C50

Numerical Methods for Fluid-Structure Interaction — A Review

Abstract: The interactions between incompressible fluid flows and immersed struc- tures are nonlinear multi-physics phenomena that have applications to a wide range of scientific and engineering disciplines In this article, we review representative numeri- cal methods based onconforming and non-conforming meshes that arecurrentlyavail- able for computing fluid-structure interaction problems, with an emphasis on some of the recent developments in the field A goal is to categorize the selected methods and assess their accuracy and efficiency We discuss challenges faced by researchers in this field, and we emphasize the importance of interdisciplinary effort for advancing the study in fluid-structure interactions

Efficient collocational approach for parametric uncertainty analysis

Abstract: A numerical algorithm for effective incorporation of parametric uncertainty into mathematical models is presented. The uncertain parameters are modeled as random variables, and the governing equations are treated as stochastic. The solutions, or quantities of interests, are expressed as convergent series of orthogonal polynomial expansions in terms of the input random parameters. A high-order stochastic collocation method is employed to solve the solution statistics, and more importantly, to reconstruct the polynomial expansion. While retaining the high accuracy by polynomial expansion, the resulting “pseudo-spectral” type algorithm is straightforward to implement as it requires only repetitive deterministic simulations. An estimate on error bounded is presented, along with numerical examples for problems with relatively complicated forms of governing equations.

Phase-Field Models for Multi-Component Fluid Flows

Abstract: In this paper, we review the recent development of phase-field models and their numerical methods for multi-component fluid flows with interfacial phenomena. The models consist of a Navier-Stokes system coupled with a multi-component Cahn-Hilliard system through a phase-field dependent surface tension force, variable density and viscosity, and the advection term. The classical infinitely thin boundary of separation between two immiscible fluids is replaced by a transition region of a small but finite width, across which the composition of the mixture changes continuously. A constant level set of the phase-field is used to capture the interface between two immiscible fluids. Phase-field methods are capable of computing topological changes such as splitting and merging, and thus have been applied successfully to multi-component fluid flows involving large interface deformations. Practical applications are provided to illustrate the usefulness of using a phase-field method. Computational results of various experiments show the accuracy and effectiveness of phase-field models.