25 papers · ranked by Valyu relevance
Jógvan Magnus Haugaard Olsen, Viacheslav Bolnykh, Simone Meloni, Emiliano Ippoliti + 3 more
We present a flexible and efficient framework for multiscale modeling in computational chemistry (MiMiC). It is based on a multiple-program multiple-data (MPMD) model with loosely coupled programs. Fast data exchange between programs is achieved through the use of MPI intercommunicators. This allows exploiting the…
Alfons G. Hoekstra, Bastien Chopard, David Coster, Simon Portegies Zwart + 1 more
'Simon Portegies Zwart' 'Peter V. Coveney'] In this position paper, we discuss two relevant topics: (i) generic multiscale computing on emerging exascale high-performing computing environments, and (ii) the scaling of such applications towards the exascale. We will introduce the different phases when developing a…
Mengke Ren, Junfeng Gu, Zheng Li, Shilun Ruan + 2 more
'Ming-Shyan Huang'] In this article, a multiscale simulation method of polymer melt injection molding filling flow is established by combining an improved smoothed particle hydrodynamics method and clustered fixed slip-link model. The proposed method is first applied to the simulation of HDPE melt in a classic…
Derek Groen, Stefan J. Zasada, Peter V. Coveney
—Multiscale and multiphysics applications are now commonplace, and many researchers focus on combining existing models to construct combined multiscale models. Here we present a concise review of multiscale applications and their source communities. We investigate the prevalence of multiscale projects in the EU and the…
Saad Alowayyed, Derek Groen, Peter V. Coveney, Alfons G. Hoekstra
- 1 Computational Science Lab, Institute for Informatics, University of Amsterdam, The Netherlands - 2 King Abdulaziz City for Science and Technology (KACST), Riyadh, Saudi Arabia - 3 Department of Computer Science, Brunel University London, United Kingdom - 4 Centre for Computational Science, University College…
Huandong Wang, Huan Yan, Can Rong, Yuan Yuan + 5 more
'Zhenyu Han' 'Hongjie Sui' 'Depeng Jin' 'Yong Li'] Complex system simulation has been playing an irreplaceable role in understanding, predicting, and controlling diverse complex systems. In the past few decades, the multi-scale simulation technique has drawn increasing attention for its remarkable ability to overcome…
Derek Groen, Joris Borgdorff, Carles Bona-Casas, James Hetherington + 8 more
'Rupert W. Nash' 'Stefan J. Zasada' 'I. Saverchenko' 'Mariusz Mamoński' 'Krzysztof Kurowski' 'Miguel O. Bernabéu' 'Alfons G. Hoekstra' 'P. V. Coveney'] Multiscale simulations are essential in the biomedical domain to accurately model human physiology. We present a modular approach for designing, constructing and…
Derek Groen, Jaroslaw Knap, Philipp Neumann, Diana Suleimenova + 2 more
In the last few decades, multiscale modelling has emerged as one of the dominant modelling paradigms in many areas of science and engineering. Its rise to dominance is primarily driven by advancements in computing power and the need to model systems of increasing complexity. The multiscale modelling paradigm is now…
David Stephenson, James R. Kermode, Duncan A. Lockerby
We present a scheme for accelerating hybrid continuum-atomistic models in multiscale fluidic systems by using Gaussian process regression as a surrogate model for computationally expensive molecular dynamics simulations. Using Gaussian process regression, we are able to accurately predict atomic-scale information…
Martin O. Steinhauser, Stefan Hiermaier
This review discusses several computational methods used on different length and time scales for the simulation of material behavior. First, the importance of physical modeling and its relation to computer simulation on multiscales is discussed. Then, computational methods used on different scales are shortly reviewed…
Viacheslav Bolnykh, Jógvan Magnus Haugaard Olsen, Simone Meloni, Martin P. Bircher + 3 more
We present a highly scalable DFT-based QM/MM implementation developed within MiMiC, a recently introduced multiscale modeling framework that uses a loose-coupling strategy in conjunction with a multiple-program multiple-data (MPMD) approach. The computation of electrostatic QM/MM interactions is parallelized exploiting…
Pariksheet Nanda, Maral Budak, Christian T. Michael, Kathryn Krupinsky + 1 more
Although infectious disease dynamics are often analyzed at the macro-scale, increasing numbers of drug-resistant infections highlight the importance of within-host modeling that simultaneously solves across multiple scales to effectively respond to epidemics. We review multiscale modeling approaches for complex…
Adam Noel, Karen C. Cheung, Robert Schober
—Recently, hybrid models have emerged that combine microscopic and mesoscopic regimes in a single stochastic reaction-diffusion simulation. Microscopic simulations track every individual molecule and are generally more accurate. Mesoscopic simulations partition the environment into subvolumes, track when molecules move…
Giulia Palermo, Alexandre M. J. J. Bonvin, Matteo Dal Peraro, Rommie E. Amaro + 1 more
Indeed, elements from system biology must be included when the level of simulation scales toward that of the cell. Widely used approaches in this case are those of Kinetic Master Equations (KME) connecting a set of cell elements. KME is used for instance in the representation of the whole complement cascade of the…
Anupam Ojha, Lane Votapka, Gary Huber, Shang Gao + 1 more
SEEKR2 (Simulation enabled estimation of kinetic rates v. 2) is a powerful and versatile software tool designed to computationally estimate the kinetics and thermodynamics of complex molecular processes, particularly emphasizing the process of receptor-ligand binding and unbinding. We present a suite of tutorials for…
T.J. Sego, James P. Sluka, Herbert M. Sauro, James A. Glazier
Tissue Forge is an open-source interactive environment for particle-based physics, chemistry and biology modeling and simulation. Tissue Forge allows users to create, simulate and explore models and virtual experiments based on soft condensed matter physics at multiple scales, from the molecular to the multicellular…
Benjamin S. Hanson, Daniel J. Read
Many biophysical systems and proteins undergo mesoscopic conformational changes in order to perform their biological function. However, these conformational changes often result from a cascade of atomistic interactions within a much larger overall object. For simulations of such systems, the computational cost of…
Authors not listed
We present the next generation of AMP, a neural network potential (NNP) with anisotropic message passing designed to study large biomolecular systems at DFT accuracy in the condensed phase using a multiscale approach similar to quantum-mechanics/molecular-mechanics (QM/MM) with electrostatic embedding. We trained AMPv3…
Sonata Kvedaravičiūtė, Andrej Antalík, Olivier Adjoua, Thomas Plé + 4 more
In this work, we present the development of a fully-polarizable KS-DFT/AMOEBA embedding scheme for delocalized basis sets such as plane-waves and real-space grids. The augmented problem of electron spill-out inherent to a polarizable QM/MM implementation with plane-wave basis sets is addressed and the periodicity for…
Andrea Tangherloni, Marco S. Nobile, Paolo Cazzaniga, Giulia Capitoli + 4 more
Mathematical models of biochemical networks can largely facilitate the comprehension of the mechanisms at the basis of cellular processes, as well as the formulation of hypotheses that can then be tested with targeted laboratory experiments. However, two issues might hamper the achievement of fruitful outcomes. On the…
Andrew J. Loza, Marc S. Sherman
Biological systems frequently contain biochemical species present as small numbers of slowly diffusing molecules, leading to fluctuations that invalidate deterministic analyses of system dynamics. The development of mathematical tools that account for the spatial distribution and discrete number of reacting molecules…
Gavin Fullstone, Cristiano Guttà, Amatus Beyer, Markus Rehm
Agent-based modelling is particularly adept at modelling complex features of cell signalling pathways, where heterogeneity, stochastic and spatial effects are important, thus increasing our understanding of decision processes in biology in such scenarios. However, agent-based modelling often is computationally…
Martin Kutscherauer, Scott Anderson, Sebastian Böcklein, Gerhard Mestl + 2 more
Modeling catalytic fixed bed reactors with a small tube-to-particle diameter ratio requires a detailed description of the interactions between fluid flow, intra-particle transport, and the chemical reaction(s) within the catalyst. Particle-resolved computational fluid dynamics (PRCFD) simulations are the most promising…
Aaron Finney, Matteo Salvalaglio
Nucleation is the initial step towards the formation of crystalline materials from solutions. Various factors, such as environmental conditions, composition, and external fields, can influence its outcomes and rates. Indeed, controlling this rate-determining step towards phase separation can affect the resulting…
Matthew J. Simpson, Ruth E. Baker, Pascal R. Buenzli, Ruanui Nicholson + 1 more
Stochastic individual-based mathematical models are attractive for modelling biological phenomena because they naturally capture the stochasticity and variability that is often evident in biological data. Such models also allow us to track the motion of individuals within the population of interest. Unfortunately…