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

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The prevalence of complexity in flammable ecosystems and the application of complex systems theory to the simulation of fire spread

Les forêts sont une ressource naturelle importante sur le plan écologique, culturel et économique, et sont confrontées à des défis croissants en raison des changements climatiques. Ces défis sont difficiles à prédire en raison de la nature complexe des interactions entre le climat et la végétation, dont une le feu. Compte tenu de l’importance des écosystèmes forestiers, des dangers potentiels des feux de forêt et de la complexité de leurs interactions, il est primordial d'acquérir une compréhension de ces systèmes à travers le prisme de la science des systèmes complexes. La science des systèmes complexes et ses techniques de modélisation associées peuvent fournir des informations sur de tels systèmes que les techniques de modélisation traditionnelles ne peuvent pas. Là où les techniques statistiques et basées sur équations cherchent à contourner la dynamique non-linéaire, auto-organisée et émergente des systèmes complexes, les approches de modélisation telles que les automates cellulaires et les modèles à base d'agents (MBA) embrassent cette complexité en cherchant à reproduire les interactions clés de ces systèmes. Bien qu'il existe de nombreux modèles de comportement du feu qui tiennent compte de la complexité, les MBA offrent un terrain d'entente entre les modèles de simulation empiriques et physiques qui peut fournir de nouvelles informations sur le comportement et la simulation du feu. Cette étude vise à améliorer notre compréhension du feu dans le contexte de la science des systèmes complexes en développant un tel MBA de propagation du feu. Le modèle utilise des données de type de carburant, de terrain et de météo pour créer l'environnement des agents. Le modèle est évalué à l'aide d’une étude de cas d'un incendie naturel qui s'est produit en 2001 dans le sud-ouest de l'Alberta, au Canada. Les résultats de cette étude confirment la valeur de la prise en compte de la complexité lors de la simulation d'incendies de forêt et démontrent l'utilité de la modélisation à base d'agents pour une telle tâche.Forests are an ecologically, culturally, and economically important natural resource that face growing challenges due to climate change. These challenges are difficult to predict due to the complex nature of the interactions between climate and vegetation. Furthermore, fire is intrinsically linked to both climate and vegetation and is, itself, complex. Given the importance of forest ecosystems, the potential dangers of forest fires, and the complexity of their interactions, it is paramount to gain an understanding of these systems through the lens of complex systems science. Complex systems science and its attendant modeling techniques can provide insights on such systems that traditional modelling techniques cannot. Where statistical and equation-based techniques seek to work around the non-linear, self-organized, and emergent dynamics of complex systems, modelling approaches such as Cellular Automata and Agent-Based Models (ABM) embrace this complexity by seeking to reproduce the key interactions of these systems. While there exist numerous models of fire behaviour that account for complexity, ABM offers a middle ground between empirical and physical simulation models that may provide new insights into fire behaviour and simulation. This study seeks to add to our understanding of fire within the context of complex systems science by developing such an ABM of fire spread. The model uses fuel-type, terrain, and weather data to create the agent environment. The model is evaluated with a case study of a natural fire that occurred in 2001 in southwestern Alberta, Canada. Results of this study support the value of considering complexity when simulating forest fires and demonstrate the utility of ABM for such a task

Vision 2040: A Roadmap for Integrated, Multiscale Modeling and Simulation of Materials and Systems

Over the last few decades, advances in high-performance computing, new materials characterization methods, and, more recently, an emphasis on integrated computational materials engineering (ICME) and additive manufacturing have been a catalyst for multiscale modeling and simulation-based design of materials and structures in the aerospace industry. While these advances have driven significant progress in the development of aerospace components and systems, that progress has been limited by persistent technology and infrastructure challenges that must be overcome to realize the full potential of integrated materials and systems design and simulation modeling throughout the supply chain. As a result, NASA's Transformational Tools and Technology (TTT) Project sponsored a study (performed by a diverse team led by Pratt & Whitney) to define the potential 25-year future state required for integrated multiscale modeling of materials and systems (e.g., load-bearing structures) to accelerate the pace and reduce the expense of innovation in future aerospace and aeronautical systems. This report describes the findings of this 2040 Vision study (e.g., the 2040 vision state; the required interdependent core technical work areas, Key Element (KE); identified gaps and actions to close those gaps; and major recommendations) which constitutes a community consensus document as it is a result of over 450 professionals input obtain via: 1) four society workshops (AIAA, NAFEMS, and two TMS), 2) community-wide survey, and 3) the establishment of 9 expert panels (one per KE) consisting on average of 10 non-team members from academia, government and industry to review, update content, and prioritize gaps and actions. The study envisions the development of a cyber-physical-social ecosystem comprised of experimentally verified and validated computational models, tools, and techniques, along with the associated digital tapestry, that impacts the entire supply chain to enable cost-effective, rapid, and revolutionary design of fit-for-purpose materials, components, and systems. Although the vision focused on aeronautics and space applications, it is believed that other engineering communities (e.g., automotive, biomedical, etc.) can benefit as well from the proposed framework with only minor modifications. Finally, it is TTT's hope and desire that this vision provides the strategic guidance to both public and private research and development decision makers to make the proposed 2040 vision state a reality and thereby provide a significant advancement in the United States global competitiveness

Discrete coarse-grained modelling of adsorption and diffusion in host-guest systems

Representing molecular systems above the microscale is a challenging task. The widely-used atomistic methods are very accurate, but at the same time, very limited in terms of efficiency. In this thesis, I report different methodologies to represent adsorption and diffusion occurring in host-guest systems on larger scales, through discrete models. First, I report a data-driven approach for the definition of molecular states based on local atomistic patterns. Second, I propose another method that makes use of the occupancies i.e. local amounts of guest species. Molecular systems are mapped into lattice models equipped with coarse-grained thermodynamics and a local operator, which represents the dynamics. These methods are validated in different ways on several molecular systems, and provide an accurate reproduction of the reference atomistic properties. Moreover, they unveiled interesting physicochemical insights while being strikingly more efficient than their atomistic counterpart

Experimental and numerical study of the effects of the reversal hot rolling conditions on the recrystallization behavior of austenite model alloys

The experimental and numerical study of the effects of the recrystallization behavior of austenite model alloys during hot plate rolling on reverse rolling is the main goal of the paper. The computer models that are currently applied for simulation of reverse rolling are not strain-path-sensitive, thus leading to overestimation of the processing parameters outside the accepted process window (e.g., deformation in the partial austenite recrystallization region). Therefore, in this work, a particular focus is put on the investigation of strain path effects that occur during hot rolling and their influence on the microstructure evolution and mechanical properties of microalloyed austenite. Both experimental and numerical techniques are employed in this study, taking advantage of the integrated computational material engineering concept. The combined isotropic–kinematic hardening model is used for the macroscale predictions to take into account softening effects due to strain reversal. The macroscale model is additionally enriched with the full-field microstructure evolution model within the cellular automata framework. Examples of obtained results, highlighting the role of the strain reversal on the microstructural response, are presented within the paper. The combination of the physical simulation of austenitic model alloys and computer modeling provided new insights into optimization of the processing routes of advanced high-strength steels (AHSS)

Numerical simulation of fluid-fluid and solid-fluid interactions: a lattice Boltzmann strategy

It is crucial to obtain a better understanding of fluid-fluid and solid-fluid interactions with several applications in science and engineering disciplines. Associating fluids such as water, alcohols, asphaltene might exist in many processes. Modeling associating fluids to explore phase equilibrium behaviors is required for proper design, operation, and optimization of various chemical and energy processes. Pseudopotential lattice Boltzmann method (LBM) can be a promising and capable mesoscopic approach to study phase transition and thermodynamic behaviors of complex fluid systems. Results of integrating the cubic equations of state (EOSs) with LBM showed a considerable deviation from experimental data for associating fluids. Cubic-plus-association (CPA) EOS is utilized in the LBM to increase the accuracy of modeling associating fluids. A global optimization approach is applied to determine the optimum association parameters of CPA EOS for water and primary alcohols in the lattice units. Maxwell equal area construction is used to verify the thermodynamic consistency. By increasing the isotropy order of gradient operator, the spurious velocities are decreased, and an extended form of CPA EOS is introduced to find proper initial densities, which increase the stabilities at low reduced temperatures. Simulating fluid flow at high Reynolds number is another aspect of an LBM study that needs further improvement. In fluid flow in porous media, specifically at tight gas reservoirs, a high flow rate might happen at pore throat. Therefore, to increase the stability of the model at high Reynolds number, the central moments collision operator is implemented in the LBM. The advantages of central moments collision operator are shown by comparing with multi relaxation time (MRT) collision operator in the double shear layers test. It is found that using a higher order of isotropy in the gradient operator can lead to a 34% reduction in spurious velocities. From the thermodynamic consistency point of view, it is concluded that collision operators can also have an impact on the consistency of the model. Furthermore, the model validation is performed by observing a straight line in the Laplace law test. Surface wettability is known as an important concept to achieve a better understanding of fluid flow and distribution in both porous and non-porous systems. Improving the solid-fluid interaction can help to have a better understanding of thermodynamics of curved interfaces. The contact angle is an important parameter to study the multiphase fluid flow in various systems such as porous media and membranes. It helps to design better production, separation, treatment, and reaction processes in different applications. In order to increase the accuracy and reliability of the model for simulation of the surface wettability and absorption, a new solid-fluid interaction in the pseudopotential approach is introduced. Usually, the surface wettability is reported by the contact angle, which is measured by fitting a circle on the drop. Because the circle is a constant curvature shape, it is not suitable to consider the disjoining pressure. A new strategy is presented based on the Smoothing Splines to measure the contact angle without considering a constant curvature shape of the interface profile. The new solid-fluid interaction exhibits the capability of simulating extreme non-wetting surfaces without detaching the drop. The probability histogram of the density domain appears to be a reliable tool to measure the phase density in the presence of a surface. The results of the current research have a wide range of applications in energy and environment, such as simulation of fluid flow in porous systems (e.g., shale reservoirs and membranes). Pores and fractures are large in conventional permeable media and pressure-drive convective flow is applicable in the framework of continuum flow. Shale reservoir have fine grains and pores in the range on nanometer where fluid molecular distribution is inhomogeneous and surface adsorption may be significant. Coupling the introduced method with nucleation theory provide a powerful tool to simulate asphaltene precipitation in the porous media. The presence of water component as an associating fluid in some biological processes such as blood coagulation makes the presented model an effective tool to simulate those processes

Relating Representative Elementary Volume of Tortuosity to That of Porosity as Revealed from Computed Tomography Images

Tortuosity and porosity are significant micro-scale parameters that have a major impact on many environmental processes and engineering applications that are usually implemented at a macroscopic scale. Thus, it is essential to quantify the corresponding representative elementary volume of these micro-scale properties to study and improve the understanding of different environmental applications, such as flow and transport of contaminates in porous media systems. 3D x-ray microtomography images of sand systems that have different sizes and geometry were used to compute two important microscopic properties such as porosity and tortuosity. Corresponding representative elementary volumes (REV) of these systems were computed by developing an efficient algorithm using Matlab. Representative elementary volume (REV) of tortuosity was related to that of porosity for each system, to determine whether an REV for porosity is sufficient to define REV for tortuosity. Findings revealed that for regular particles geometry REVmin of porosity was less than REVmin of tortuosity. However, for irregular particles geometry, the REVmin of porosity and REVmin of tortuosity were similar. This indicates that REVmin value of porosity depends on the geometry and the structure of the porous media. Whereas, REVmin value of tortuosity is not affected by the geometry. In addition, the number of particles required to reach REV region was found to be an easier method to be reflected upon.يعد التعرج والمسامية من الخصائص ذات تأثير كبير على العديد من العمليات البيئية والتطبيقات الهندسية. ليتم تطبيق هذه الخصاص على نطاق التطبيقات والعمليات الهندسية، لابد من ايجاد الحجم التمثيلي لهذه الخواص التي تعتبر صغيرة الحجم، وذالك لدراسة وتحسين فهم التطبيقات البيئية المختلفة، مثل نقل تلوث المياه الجوفية في الوسائط المسامية ونشر الغازات في بنية الوسائط المسامية المعقدة. تتمثل الأهداف الرئيسية لهذه الأطروحة في استخدام الصور المجهرية ثلاثية الأبعاد لخمسة عشر نظاما كل نظام يتسم باختلاف شكل الجزيئات واختلاف اقطارها وذالك لحساب خواص مجهرية مهمة مثل المسامية والتعرج على نطاق واسع. من خلال تطوير خوارزمية فعالة باستخدام برنامج وذالك للعثور على الحجم التمثيلي للمسامية والتعرج MatLab تحديد ما إذا كان الحجم التمثيلي للمسامية كافية لتعريف ، وإيجاد علاقة بينهم. بالإضافة إلى ذلك الحجم التمثيلي للتعرج .كشفت النتائج أنه بالنسبة للجزيئات ذات الشكل المنتظمة فأن الحجم التمثيلي للمسامية اقل من الحجم التمثيلي لتعرج. في المقابل بالنسبة للجزيئات غير منتظمة الشكل فأن الحجم التمثيلي للمسامية كان مساويا للحجم التمثيلي لتعرج. بمعنى اخر، تتأثر قيمة الحجم التمثيلي للمسامية بالهندسة وبنية وسائط المسام. بينما، لا تتأثر قيمة الحجم التمثيلي للتعرج تم العثور على عدد الجسيمات المطلوبة للوصول ، بالهندسة وبنية وسائط المسام. بالإضافة إلى ذلك إلى وحدة الحجم التمثيل

Spatiotemporal modeling of interactions between urbanization and flood risk: a multi-level approach

The main goal of this PhD research is to investigate the expected flood damage for future urban patterns at different scales. Four main steps are followed to accomplish this goal. In the first step, a retrospective analysis is performed for the evolution of the urban development in Wallonia (Belgium) as a case study. Afterward, two land use change models, cellular automata-based, and agent-based are proposed and compared. Based on this comparison, the agent-based model is employed to simulate future urbanization scenarios. An important feature of this research is evident in the consideration of the multiple densities of built-up areas, which enables to study both expansion and densification processes. As the model simulates urbanization up to 2100, forecasting land use change over such time frames entails very significant uncertainties. In this regard, uncertainty in land use change models has been considered. In the third step, 24 urbanization scenarios that differed in terms of spatial policies and urbanization rate are generated. The simulated scenarios have then been integrated with a hydrological model. The results suggest that urban development will continue within flood-prone zones in a number of scenarios. Therefore, in the fourth and last step, a procedural urban generation system is developed to analyze the respective influence of various urban layout characteristics on inundation flow, which assists in designing flood-resistant urban layouts within the flood-prone zones.This thesis was funded through the ARC grant for Concerted Research Actions for project number 13/17-01 entitled "Land-use change and future flood risk: influence of micro-scale spatial patterns (FloodLand)" financed by the French Community of Belgium (Wallonia-Brussels Federation)

Patterns for High Performance Multiscale Computing

We describe our Multiscale Computing Patterns software for High Performance Multiscale Computing. Following a short review of Multiscale Computing Patterns, this paper introduces the Multiscale Computing Patterns Software, which consists of description, optimisation and execution components. First, the description component translates the task graph, representing a multiscale simulation, to a particular type of multiscale computing pattern. Second, the optimisation component selects and applies algorithms to find the most suitable mapping between submodels and available HPC resources. Third, the execution component which a middleware layer maps submodels to the number and type of physical resources based on the suggestions emanating from the optimisation part together with infrastructure-specific metrics such as queueing time and resource availability. The main purpose of the Multiscale Computing Patterns software is to leverage the Multiscale Computing Patterns to simplify and automate the execution of complex multiscale simulations on high performance computers, and to provide both application-specific and pattern-specific performance optimisation. We test the performance and the resource usage for three multiscale models, which are expressed in terms of two Multiscale Computing Patterns. In doing so, we demonstrate how the software automates resource selection and load balancing, and delivers performance benefits from both the end-user and the HPC system level perspectives

Simulation of pore-scale flow using finite element-methods

I present a new finite element (FE) simulation method to simulate pore-scale flow. Within the pore-space, I solve a simplified form of the incompressible Navier-Stoke’s equation, yielding the velocity field in a two-step solution approach. First, Poisson’s equation is solved with homogeneous boundary conditions, and then the pore pressure is computed and the velocity field obtained for no slip conditions at the grain boundaries. From the computed velocity field I estimate the effective permeability of porous media samples characterized by thin section micrographs, micro-CT scans and synthetically generated grain packings. This two-step process is much simpler than solving the full Navier Stokes equation and therefore provides the opportunity to study pore geometries with hundreds of thousands of pores in a computationally more cost effective manner than solving the full Navier-Stoke’s equation. My numerical model is verified with an analytical solution and validated on samples whose permeabilities and porosities had been measured in laboratory experiments (Akanji and Matthai, 2010). Comparisons were also made with Stokes solver, published experimental, approximate and exact permeability data. Starting with a numerically constructed synthetic grain packings, I also investigated the extent to which the details of pore micro-structure affect the hydraulic permeability (Garcia et al., 2009). I then estimate the hydraulic anisotropy of unconsolidated granular packings. With the future aim to simulate multiphase flow within the pore-space, I also compute the radii and derive capillary pressure from the Young-Laplace equation (Akanji and Matthai,2010