Open AccessBook
Numerical Solution of Time-Dependent Advection-Diffusion-Reaction Equations
Willem Hundsdorfer,Jan Verwer +1 more
TLDR
This paper presents a meta-modelling procedure called “Stabilized Explicit Runge-Kutta Methods”, which automates the very labor-intensive and therefore time-heavy and therefore expensive process of integrating discrete-time components into a coherent system.Abstract:
I Basic Concepts and Discretizations.- II Time Integration Methods.- III Advection-Diffusion Discretizations.- IV Splitting Methods.- V Stabilized Explicit Runge-Kutta Methods.read more
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A Comprehensive Survey of Recent Advancements in Molecular Communication
TL;DR: A comprehensive survey of molecular communication (MC) through a communication engineering lens is provided in this paper, which includes different components of the MC transmitter and receiver, as well as the propagation and transport mechanisms.
Journal ArticleDOI
On splitting methods for Schrödinger-Poisson and cubic nonlinear Schrödinger equations
TL;DR: An error analysis of Strang-type splitting integrators for nonlinear Schrodinger equations using Lie-commutator bounds for estimating the local error and H m -conditional stability for error propagation is given.
Journal ArticleDOI
Spatio-temporal dynamics of a planktonic system and chlorophyll distribution in a 2D spatial domain: matching model and data
Davide Valenti,G. Denaro,Rosalia Ferreri,Simona Genovese,Salvatore Aronica,Salvatore Mazzola,Angelo Bonanno,Gualtiero Basilone,Bernardo Spagnolo,Bernardo Spagnolo +9 more
TL;DR: The advection-diffusion-reaction model used to analyze how both the velocity field of marine currents and the two components of turbulent diffusivity affect the spatial distributions of phytoplankton abundances in the Modified Atlantic Water, the upper layer of the water column of the Mediterranean Sea can be extended to predict the spatio-temporal behaviour of the primary production, and to prevent the consequent decline of some fish species in the Mediterranean sea.
Book
An Introduction to Computational Stochastic PDEs
TL;DR: This book offers graduate students and researchers powerful tools for understanding uncertainty quantification for risk analysis and theory is developed in tandem with state-of-the art computational methods through worked examples, exercises, theorems and proofs.