scholarly journals Computational Multiscale Solvers for Continuum Approaches

Materials ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 691 ◽  
Author(s):  
Francisco Montero-Chacón ◽  
José Sanz-Herrera ◽  
Manuel Doblaré

Computational multiscale analyses are currently ubiquitous in science and technology. Different problems of interest—e.g., mechanical, fluid, thermal, or electromagnetic—involving a domain with two or more clearly distinguished spatial or temporal scales, are candidates to be solved by using this technique. Moreover, the predictable capability and potential of multiscale analysis may result in an interesting tool for the development of new concept materials, with desired macroscopic or apparent properties through the design of their microstructure, which is now even more possible with the combination of nanotechnology and additive manufacturing. Indeed, the information in terms of field variables at a finer scale is available by solving its associated localization problem. In this work, a review on the algorithmic treatment of multiscale analyses of several problems with a technological interest is presented. The paper collects both classical and modern techniques of multiscale simulation such as those based on the proper generalized decomposition (PGD) approach. Moreover, an overview of available software for the implementation of such numerical schemes is also carried out. The availability and usefulness of this technique in the design of complex microstructural systems are highlighted along the text. In this review, the fine, and hence the coarse scale, are associated with continuum variables so atomistic approaches and coarse-graining transfer techniques are out of the scope of this paper.

2021 ◽  
Vol 48 ◽  
pp. 102353
Author(s):  
Patrick I. O’Toole ◽  
Milan J. Patel ◽  
Chao Tang ◽  
Dayalan Gunasegaram ◽  
Anthony B. Murphy ◽  
...  

2013 ◽  
Vol 9 (11) ◽  
pp. 5168-5175 ◽  
Author(s):  
Anu Nagarajan ◽  
Christoph Junghans ◽  
Silvina Matysiak

2016 ◽  
Vol 879 ◽  
pp. 1207-1212 ◽  
Author(s):  
Piotr Macioł ◽  
Danuta Szeliga ◽  
Łukasz Sztangret

A typical multiscale simulation consists of numerous fine scale models, usually one for each computational point of a coarse scale model. One of possible ways of limiting computing power requirements is replacing fine scale models with some simplified and speeded up ersatz ones. In this paper, the authors attempt to develop a metamodel, replacing direct thermodynamic computations of precipitation kinetic with an advanced approximating model. MatCalc simulator has been used for thermodynamic modelling of precipitation kinetic. Typical heat treatment of P91 steel grade was examined. Selected variables were chosen to be modelled with approximating models. Several attempts with various approximation variants (interpolation algorithms and Artificial Neural Networks) have been investigated and its comparison is included in the paper.


2014 ◽  
Vol 5 (12) ◽  
pp. 3076-3082 ◽  
Author(s):  
R. G. M. van der Sman ◽  
J. Broeze

We investigate the effect of salt on the expansion of starchy snacks during frying by means of a multiscale simulation model.


MRS Bulletin ◽  
2007 ◽  
Vol 32 (11) ◽  
pp. 929-934 ◽  
Author(s):  
Gary S. Ayton ◽  
Will G. Noid ◽  
Gregory A. Voth

AbstractCoarse-grained modeling is a key component in the field of multiscale simulation. Many biomolecular and otherwise complex systems require the characterization of phenomena over multiple length and time scales in order to fully resolve and understand their behavior. These different scales range from atomic to near macroscopic dimensions, and they are generally not independent of one another, but instead coupled. That is, phenomena occurring at atomic length scales have an effect at macroscopic dimensions and vice versa. Systematic transfer of information between these different scales represents a core challenge in the field of multiscale simulation. Coarse-grained modeling works at an intermediate resolution that can bridge the very high resolution (atomic) scale to the very low resolution (macroscopic) scale. As such, a significant challenge is the development of a systematic methodology whereby coarse-grained models can be derived from their high-resolution atomistic-scale counterpart. Here, a systematic theoretical and computational methodology will be described for developing coarse-grained representations of biomolecular and other soft-matter systems. At the heart of the methodology is a variational statistical mechanical algorithm that uses forcematching of atomistic molecular dynamics data to a coarse-grained representation. A theoretical analysis of the coarse-graining methodology will be presented, along with illustrative applications to membranes, peptides, and carbohydrates.


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