scholarly journals Hierarchical phenomena in multicomponent liquids: simulation methods, analysis, chemistry

2020 ◽  
Vol 22 (18) ◽  
pp. 9850-9874 ◽  
Author(s):  
Michael J. Servis ◽  
Ernesto Martinez-Baez ◽  
Aurora E. Clark
Keyword(s):  
Simulation Methods ◽  
Solution Speciation

Complex, multicomponent, liquids benefit from a hierarchical understanding of solution speciation, collective organization and dynamics.

SIMULATION METHODS FOR FLOOD DAMAGE AND SCOUR DAMAGE ON LAND BY HUGE TSUNAMI

2018 ◽  
Vol 74 (2) ◽  
pp. I_193-I_198
Author(s):  
Yoshimichi YAMAMOTO ◽  
Maiki HAYAKAWA ◽  
S Masihullah AHMADI
Keyword(s):  
Flood Damage ◽  
Simulation Methods

Computer Simulations of Dislocations

2006 ◽  
Author(s):  
Vasily Bulatov ◽  
Wei Cai
Keyword(s):  
Case Studies ◽  
Time Scales ◽  
Computer Simulations ◽  
Common Ground ◽  
Practical Knowledge ◽  
Simulation Methods ◽  
Computational Approaches ◽  
Learn By Doing ◽  
Data Files ◽  
Computational Materials

This book presents a broad collection of models and computational methods - from atomistic to continuum - applied to crystal dislocations. Its purpose is to help students and researchers in computational materials sciences to acquire practical knowledge of relevant simulation methods. Because their behavior spans multiple length and time scales, crystal dislocations present a common ground for an in-depth discussion of a variety of computational approaches, including their relative strengths, weaknesses and inter-connections. The details of the covered methods are presented in the form of "numerical recipes" and illustrated by case studies. A suite of simulation codes and data files is made available on the book's website to help the reader "to learn-by-doing" through solving the exercise problems offered in the book.

Qualitative simulation and related approaches for the analysis of dynamic systems

2004 ◽  
Vol 19 (2) ◽  
pp. 93-132 ◽  
Author(s):  
HIDDE DE JONG
Keyword(s):  
Qualitative Analysis ◽  
Dynamic Systems ◽  
Quantitative Information ◽  
Simulation Methods ◽  
Science And Engineering ◽  
Computational Framework ◽  
Combinatorial Explosion ◽  
Qualitative Simulation ◽  
Qualitative Phase ◽  
Made In

Methods for qualitative simulation allow predictions on the dynamics of a system to be made in the absence of quantitative information, by inferring the range of possible qualitative behaviors compatible with the structure of the system. This article reviews QSIM and other qualitative simulation methods. It discusses two problems that have seriously compromised the application of these methods to realistic problems in science and engineering: the occurrence of spurious behavior predictions and the combinatorial explosion of the number of behavior predictions. In response to these problems, related approaches for the qualitative analysis of dynamic systems have emerged: qualitative phase-space analysis and semi-quantitative simulation. The article argues for a synthesis of these approaches in order to obtain a computational framework for the qualitative analysis of dynamic systems. This should provide a solid basis for further upscaling and for the development of model-based reasoning applications of a wider scope.

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