Abstract: Modelling and simulation of multiscale systems constitutes a grand challenge in computational science, and is widely applied in fields ranging from the physical sciences and engineering to the life sciences and the socio-economic domain. To adequately simulate numerous intertwined processes characterized by different spatial and temporal scales (often spanning many orders of magnitude), sophisticated models and advanced computational techniques are required. Additionally, these multiscale models frequently need large scale computing capabilities as well as dedicated software and services that enable the exploitation of existing and evolving computational ecosystems. The aim of the annual Workshop on Multiscale Modelling and Simulation is to facilitate the progress in this multidisciplinary research field http://www.computationalscience.nl/MMS/. In this paper, we reflect on the 12 years of workshop history and glimpse at the latest developments presented in 2015 in Iceland, the Land of Fire and Ice. In Section 6, we invite new workshop co-organizers.

Abstract: This paper presents a systematic survey of open source multiphysics frameworks in the engineering domains. These domains share many commonalities despite the diverse application areas. A thorough search for the available frameworks with both academic and industrial origins has revealed numerous candidates. Considering key characteristics such as project size, maturity and visibility, we selected Elmer, OpenFOAM and Salome for a detailed analysis. All the public documentation for these tools has been manually collected and inspected. Based on the analysis, we built a feature model for multiphysics in engineering, which captures the commonalities and variability in the domain. We in turn validated the resulting model via two other tools; Kratos by manual inspection, and OOFEM by means of expert validation by domain experts.

Abstract: Extensive research efforts have been invested in reducing model errors to improve the predictive ability of biogeochemical earth and environmental system simulators, with applications ranging from contaminant transport and remediation to impacts of biogeochemical elemental cycling (e.g., carbon and nitrogen) on local ecosystems and regional to global climate. While the bulk of this research has focused on improving model parameterizations in the face of observational limitations, the more challenging type of model error/uncertainty to identify and quantify is model structural error which arises from incorrect mathematical representations of (or failure to consider) important physical, chemical, or biological processes, properties, or system states in model formulations. While improved process understanding can be achieved through scientific study, such understanding is usually developed at small scales. Process-based numerical models are typically designed for a particular characteristic length and time scale. For application-relevant scales, it is generally necessary to introduce approximations and empirical parameterizations to describe complex systems or processes. This single-scale approach has been the best available to date because of limited understanding of process coupling combined with practical limitations on system characterization and computation. While computational power is increasing significantly and our understanding of biological and environmental processes at fundamental scales is accelerating, using this information to advance our knowledge of the larger system behavior requires the development of multiscale simulators. Accordingly there has been much recent interest in novel multiscale methods in which microscale and macroscale models are explicitly coupled in a single hybrid multiscale simulation. A limited number of hybrid multiscale simulations have been developed for biogeochemical earth systems, but they mostly utilize application-specific and sometimes ad-hoc approaches for model coupling. We are developing a generalized approach to hierarchical model coupling designed for high-performance computational systems, based on the Swift computing workflow framework. In this presentation we will describe the generalized approach and provide two use cases: 1) simulation of a mixing-controlled biogeochemical reaction coupling pore- and continuum-scale models, and 2) simulation of biogeochemical impacts of groundwater – river water interactions coupling fine- and coarse-grid model representations. This generalized framework can be customized for use with any pair of linked models (microscale and macroscale) with minimal intrusiveness to the at-scale simulators. It combines a set of python scripts with the Swift workflow environment to execute a complex multiscale simulation utilizing an approach similar to the well-known Heterogeneous Multiscale Method. User customization is facilitated through user-provided input and output file templates and processing function scripts, and execution within a high-performance computing environment is handled by Swift, such that minimal to no user modification of at-scale codes is required.

Abstract: Nano- and microscale flow phenomena turn out to be highly non-trivial for simulation and require the use of heterogeneous modeling approaches. While the continuum Navier-Stokes equations and related boundary conditions quickly break down at those scales, various direct simulation methods and hybrid models have been applied, such as Molecular Dynamics and Dissipative Particle Dynamics. Nonetheless, a continuum model for nanoscale flow is still an unsolved problem. We present a model taking into account nonlocal momentum transfer. Instead of a bulk viscosity an improved system of parameters of liquid properties, represented by a spatial scalar function for momentum transfer rate between neighboring volumes, is used. Our model does not require boundary conditions on the channel walls. Common nanoflow models relying on a bulk viscosity in combination with a slip boundary condition can be obtained from the model. The required model parameters can be calculated from momentum density fluctuations obtained by Molecular Dynamics simulations. Thus, our model is multiscale, however, the continuum model is applied in the whole region of the simulation. We demonstrate good agreed with nanoflow in a tube as obtained by complete Molecular Dynamics.

Abstract: Cerebrovascular diseases such as brain aneurysms are a primary cause of adult disability. The flow dynamics in brain arteries, both during periods of rest and increased activity, are known to be a major factor in the risk of aneurysm formation and rupture, although the precise relation is still an open field of investigation. We present an automated ensemble simulation method for modelling cerebrovascular blood flow under a range of flow regimes. By automatically constructing and performing an ensemble of multiscale simulations, where we unidirectionally couple a 1D solver with a 3D lattice-Boltzmann code, we are able to model the blood flow in a patient artery over a range of flow regimes. We apply the method to a model of a middle cerebral artery, and find that this approach helps us to fine-tune our modelling techniques, and opens up new ways to investigate cerebrovascular flow properties.

Abstract: We developed a mathematical model of monochorionic twin pregnancies to simulate both the normal gestation and the Twin-Twin Transfusion Syndrome (TTTS), a disease in which the interplacental anastomose create a flow imbalance, causing one of the twin to receive too much blood and liquids, becoming hypertensive and polyhydramnios (the Recipient) and the other to become hypotensive and oligohydramnios (the Donor). This syndrome, if untreated, leads almost certainly to death one or both twins. We propose a compartment model to simulate the flows between the placenta and the fetuses and the accumulation of the amniotic fluid in the sacs. The aim of our work is to provide a simple but realistic model of the twins-mother system and to stress it by simulating the pathological cases and the related treatments, i.e. aminioreduction (elimination of the excess liquid in the recipient sac), laser therapy (removal of all the anastomoses) and other possible innovative therapies impacting on pressure and flow parameters.