Multiscale simulations model phenomena across natural scales using monolithic or
component-based code, running on local or distributed resources. In this work, we …

We present and discuss a framework for computer-aided multiscale analysis, which enables
models at a fine (microscopic/stochastic) level of description to perform modeling tasks at a …

Many multiscale methods are based on the idea of extracting macroscopic behavior of
solutions by solving an array of microscale models over small domains. A key ingredient in …

Computational Fluid Dynamics (CFD) has numerous applications in the field of energy
research, in modelling the basic physics of combustion, multiphase flow and heat transfer; …

Multiscale modeling has recently been widely used in various fields of science and
engineering. A few research efforts have attempted to generalize existing applications …

Inherently complex problems from many scientific disciplines require a multiscale modeling
approach. Yet its practical contents remain unclear and inconsistent. Moreover, multiscale …

All of the above-mentioned spaces have specific geometrical properties, but they also share
something in common, which has to do with them being continuous spaces rather than …

Abstract Machine learning is increasingly recognized as a promising technology in the
biological, biomedical, and behavioral sciences. There can be no argument that this …

Multiscale simulation is a promising approach for addressing a variety of real-world
engineering problems. Various mathematical approaches have been proposed to link single …

Many mechanical engineering applications call for multiscale computational modeling and
simulation. However, solving for complex multiscale systems remains computationally …