Jean-Luc Falcone

A Complex Automata approach for in-stent restenosis: two-dimensional multiscale modelling and simulations

In-stent restenosis, the maladaptive response of a blood vessel to injury caused by the deployment of a stent, is a multiscale system involving a large number of biological and physical processes. We describe a Complex Automata model for in-stent restenosis, coupling bulk flow, drug diffusion, and smooth muscle cell models, all operating on different time scales. Details of the single scale models and of the coupling interfaces are described, together with first simulation results, obtained with a dedicated software environment for Complex Automata simulations. Preliminary results show that the model can reproduce growth trends observed in experimental studies and facilitate testing of hypotheses concerning the interaction of key factors.

Foundations of distributed multiscale computing: Formalization, specification, and analysis

Inherently complex problems from many scientific disciplines require a multiscale modeling approach. Yet its practical contents remain unclear and inconsistent. Moreover, multiscale models can be very computationally expensive, and may have potential to be executed on distributed infrastructure. In this paper we propose firm foundations for multiscale modeling and distributed multiscale computing. Useful interaction patterns of multiscale models are made predictable with a submodel execution loop (SEL), four coupling templates, and coupling topology properties. We enhance a high-level and well-defined Multiscale Modeling Language (MML) that describes and specifies multiscale models and their computational architecture in a modular way. The architecture is analyzed using directed acyclic task graphs, facilitating validity checking, scheduling distributed computing resources, estimating computational costs, and predicting deadlocks. Distributed execution using the multiscale coupling library and environment (MUSCLE) is outlined. The methodology is applied to two selected applications in nanotechnology and biophysics, showing its capabilities.

Multi-scale Modeling with Cellular Automata: The Complex Automata Approach

Cellular Automata are commonly used to describe complex natural phenomena. In many cases it is required to capture the multi-scale nature of these phenomena. A single Cellular Automata model may not be able to efficiently simulate a wide range of spatial and temporal scales. It is our goal to establish a Cellular Automata modeling paradigm for multi-scale processes. Here we will demonstrate that Complex Automata, a paradigm that we recently introduced, are capable to facilitate such modeling.

Towards a Complex Automata Framework for Multi-scale Modeling: Formalism and the Scale Separation Map

Complex Automata were recently proposed as a paradigm to model multi-scale complex systems. The concept is formalized and the scale separation map is further investigated in relation with its capability to specify the components of Complex Automata. Five classes of scale separation are identified, each potentially giving rise to a specific multi-scale modeling paradigm. A number of canonical examples are briefly discussed.

MML: towards a Multiscale Modeling Language

Recent multiscale applications require more and more often the coupling of many sub-models, usually originating form different fields of science. Therefore, it is increasingly important to propose an effective description language that can help scientists with different background to co-develop a multiscale application. We propose a Multiscale Modeling Language (MML) i.e. a description language aiming at specifying the architecture of a multiscale simulation program. We will illustrate this approach by proposing a MML description of a computer model for restenosis in a stented vessel.

Complex Automata: Multi-scale Modeling with Coupled Cellular Automata

Cellular Automata (CA) are generally acknowledged to be a powerful way to describe and model natural phenomena [1–3]. There are even tempting claims that nature itself is one big (quantum) information processing system, e.g. [4], and that CA may actually be nature’s way to do this processing [5–7]. We will not embark on this philosophical road, but ask ourselves a more mundane question. Can we use CA to model the inherently multi-scale processes in nature and use these models for efficient simulations on digital computers?

Optimization of Strut Placement in Flow Diverter Stents for Four Different Aneurysm Configurations

A modern technique for the treatment of cerebral aneurysms involves insertion of a flow diverter stent. Flow stagnation, produced by the fine mesh structure of the diverter, is thought to promote blood clotting in an aneurysm. However, apart from its effect on flow reduction, the insertion of the metal device poses the risk of occlusion of a parent artery. One strategy for avoiding the risk of arterial occlusion is the use of a device with a higher porosity. To aid the development of optimal stents in the view point of flow reduction maintaining a high porosity, we used lattice Boltzmann flow simulations and simulated annealing optimization to investigate the optimal placement of stent struts. We constructed four idealized aneurysm geometries that resulted in four different inflow characteristics and employed a stent model with 36 unconnected struts corresponding to the porosity of 80%. Assuming intracranial flow, steady flow simulation with Reynolds number of 200 was applied for each aneurysm. Optimization of strut position was performed to minimize the average velocity in an aneurysm while maintaining the porosity. As the results of optimization, we obtained nonuniformed structure as optimized stent for each aneurysm geometry. And all optimized stents were characterized by denser struts in the inflow area. The variety of inflow patterns that resulted from differing aneurysm geometries led to unique strut placements for each aneurysm type.

A Principled Approach to Distributed Multiscale Computing, from Formalization to Execution

In several disciplines, a multiscale approach is being used to model complex natural processes yet a principled background to multiscale modeling is not clear. Additionally, some multiscale models requiring distributed resources to be computed in an acceptable timeframe, while no standard framework for distributed multiscale computing is place. In this paper a principled approach to distributed multiscale computing is taken, formalizing multiscale modeling based on natural processes. Based on these foundations, the Multiscale Modeling Language (MML) is extended as a clear, general, formal, and high-level means to specify scales and interactions in, and as a guide to a uniform approach to crystalize, communicate, develop and execute a multiscale model. With an MML specification, a multiscale model can be analyzed for scheduling or deadlock detection using a task graph. The potential of this method is shown by applying it to two selected applications in nano materials and biophysics.

Towards a Complex Automata Multiscale Model of In-Stent Restenosis

In-stent restenosis, the maladaptive response of a blood vessel to injury caused by the deployment of a stent, is a multiscale problem involving a large number of processes. We describe a Complex Automata Model for in-stent restenosis, coupling a bulk flow, drug diffusion, and smooth muscle cell model, all operating on different time scales. Details of the single scale models and of the coupling interfaces are described, together with first simulation results, obtained with a dedicated software environment for Complex Automata simulations. The results show that the model can reproduce growth trends observed in experimental studies.

A numerical model of ballistic transport with collisions in a volcanic setting

Fragments associated with explosive volcanic eruptions range from microns to meters in diameter, with the largest ones following ballistic trajectories from the eruptive vent. Recent field observations suggest that bombs ejected during Strombolian eruptions may collide while airborne. We developed a Discrete Event Simulator to study numerically the impact of such collisions on hazard assessment. We show that the area where bombs can land might be significantly increased when collisions occur. As a consequence, if collisions are dominant, the deposition distance cannot be used to estimate important eruption parameters, such as exit speed.