The Experts below are selected from a list of 29571 Experts worldwide ranked by ideXlab platform
Alfons G Hoekstra - One of the best experts on this subject based on the ideXlab platform.
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semi intrusive Multiscale metamodelling uncertainty quantification with application to a model of in stent restenosis
Philosophical Transactions of the Royal Society A, 2019Co-Authors: Anna Nikishova, Lourens Veen, Pavel Zun, Alfons G HoekstraAbstract:We explore the efficiency of a semi-intrusive uncertainty quantification (UQ) method for Multiscale Models as proposed by us in an earlier publication. We applied the Multiscale metamodelling UQ me...
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foundations of distributed Multiscale computing formalization specification and analysis
Journal of Parallel and Distributed Computing, 2013Co-Authors: Joris Borgdorff, Jeanluc Falcone, Eric Lorenz, Carles Bonacasas, Bastien Chopard, Alfons G HoekstraAbstract: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.
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Multiscale computing with the Multiscale modeling library and runtime environment
International Conference on Conceptual Structures, 2013Co-Authors: Joris Borgdorff, Mariusz Mamonski, Bartosz Bosak, Derek Groen, Mohamed Ben Belgacem, Krzysztof Kurowski, Alfons G HoekstraAbstract:We introduce a software tool to simulate Multiscale Models: the Multiscale Coupling Library and Environment 2 (MUSCLE 2). MUSCLE 2 is a component-based modeling tool inspired by the Multiscale modeling and simulation framework, with an easy-to-use API which supports Java, C++, C, and Fortran. We present MUSCLE 2's runtime features, such as its distributed computing capabilities, and its benefits to Multiscale modelers. We also describe two Multiscale Models that use MUSCLE 2 to do distributed Multiscale computing: an in-stent restenosis and a canal system model. We conclude that MUSCLE 2 is a notable improvement over the previous version of MUSCLE, and that it allows users to more flexibly deploy simulations of Multiscale Models, while improving their performance.
Joris Borgdorff - One of the best experts on this subject based on the ideXlab platform.
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foundations of distributed Multiscale computing formalization specification and analysis
Journal of Parallel and Distributed Computing, 2013Co-Authors: Joris Borgdorff, Jeanluc Falcone, Eric Lorenz, Carles Bonacasas, Bastien Chopard, Alfons G HoekstraAbstract: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.
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Multiscale computing with the Multiscale modeling library and runtime environment
International Conference on Conceptual Structures, 2013Co-Authors: Joris Borgdorff, Mariusz Mamonski, Bartosz Bosak, Derek Groen, Mohamed Ben Belgacem, Krzysztof Kurowski, Alfons G HoekstraAbstract:We introduce a software tool to simulate Multiscale Models: the Multiscale Coupling Library and Environment 2 (MUSCLE 2). MUSCLE 2 is a component-based modeling tool inspired by the Multiscale modeling and simulation framework, with an easy-to-use API which supports Java, C++, C, and Fortran. We present MUSCLE 2's runtime features, such as its distributed computing capabilities, and its benefits to Multiscale modelers. We also describe two Multiscale Models that use MUSCLE 2 to do distributed Multiscale computing: an in-stent restenosis and a canal system model. We conclude that MUSCLE 2 is a notable improvement over the previous version of MUSCLE, and that it allows users to more flexibly deploy simulations of Multiscale Models, while improving their performance.
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a distributed Multiscale computation of a tightly coupled model using the Multiscale modeling language
International Conference on Conceptual Structures, 2012Co-Authors: Joris Borgdorff, Mariusz Mamonski, Bartosz Bosak, Krzysztof Kurowski, Carles Bonacasas, Tomasz Piontek, Katarzyna Rycerz, Eryk Ciepiela, Tomasz Gubala, Daniel HarezlakAbstract:Abstract Nature is observed at all scales; with Multiscale modeling, scientists bring together several scales for a holistic analysis of a phenomenon. The Models on these different scales may require significant but also heterogeneous computational resources, creating the need for distributed Multiscale computing. A particularly demanding type of Multiscale Models, tightly coupled, brings with it a number of theoretical and practical issues. In this contribution, a tightly coupled model of in-stent restenosis is first theoretically examined for its Multiscale merits using the Multiscale Modeling Language (MML); this is aided by a toolchain consisting of MAPPER Memory (MaMe), the Multiscale Application Designer (MAD), and Gridspace Experiment Workbench. It is implemented and executed with the general Multiscale Coupling Library and Environment (MUSCLE). Finally, it is scheduled amongst heterogeneous infrastructures using the QCG-Broker. This marks the first occasion that a tightly coupled application uses distributed Multiscale computing in such a general way.
Jaan-willem Simon - One of the best experts on this subject based on the ideXlab platform.
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Method of cells-based Multiscale modeling of elastic properties of filament wound C/C-SiC including free Si and matrix porosity
Journal of Materials Science & Technology, 2019Co-Authors: Evan J. Pineda, Marek Fassin, Stefanie Reese, Jaan-willem SimonAbstract:Abstract Three different Multiscale Models, based on the method of cells (generalized and high fidelity) micromechanics Models were developed and used to predict the elastic properties of C/C-SiC composites. In particular, the following Multiscale modeling strategies were employed: Concurrent modeling of all phases using the generalized method of cells, synergistic (two-way coupling in space) Multiscale modeling with the generalized method of cells, and hierarchical (one-way coupling in space) Multiscale modeling with the high fidelity generalized method of cells. The three Models are validated against data from a hierarchical Multiscale finite element model in the literature for a repeating unit cell of C/C-SiC. Furthermore, the Multiscale Models are used in conjunction with classical lamination theory to predict the stiffness of C/C-SiC plates manufactured via a wet filament winding and liquid silicon infiltration process recently developed by the German Aerospace Institute. Finally, un-reacted Si (or free Si) and porosity in the C matrix are included in the Multiscale model, and the effect of these new phases on the stiffness and local stresses are considered.
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Comparison of Multiscale Method of Cells-Based Models for Predicting Elastic Properties of Filament Wound C/C-SiC
American Society for Composites 2017, 2017Co-Authors: Evan J. Pineda, Marek Fassin, Stefanie Reese, Brett A Bednarcyk, Jaan-willem SimonAbstract:Three different Multiscale Models, based on the method of cells (generalized and high fidelity) micromechanics Models were developed and used to predict the elastic properties of C/C-SiC composites. In particular, the following Multiscale modeling strategies were employed: Concurrent Multiscale modeling of all phases using the generalized method of cells, synergistic (two-way coupling in space) Multiscale modeling with the generalized method of cells, and hierarchical (one-way coupling in space) Multiscale modeling with the high fidelity generalized method of cells. The three Models are validated against data from a hierarchical Multiscale finite element model in the literature for a repeating unit cell of C/C-SiC. Furthermore, the Multiscale Models are used in conjunction with classical lamination theory to predict the stiffness of C/C-SiC plates manufactured via a wet filament winding and liquid silicon infiltration process recently developed by the German Aerospace Institute
Daniel Harezlak - One of the best experts on this subject based on the ideXlab platform.
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a distributed Multiscale computation of a tightly coupled model using the Multiscale modeling language
International Conference on Conceptual Structures, 2012Co-Authors: Joris Borgdorff, Mariusz Mamonski, Bartosz Bosak, Krzysztof Kurowski, Carles Bonacasas, Tomasz Piontek, Katarzyna Rycerz, Eryk Ciepiela, Tomasz Gubala, Daniel HarezlakAbstract:Abstract Nature is observed at all scales; with Multiscale modeling, scientists bring together several scales for a holistic analysis of a phenomenon. The Models on these different scales may require significant but also heterogeneous computational resources, creating the need for distributed Multiscale computing. A particularly demanding type of Multiscale Models, tightly coupled, brings with it a number of theoretical and practical issues. In this contribution, a tightly coupled model of in-stent restenosis is first theoretically examined for its Multiscale merits using the Multiscale Modeling Language (MML); this is aided by a toolchain consisting of MAPPER Memory (MaMe), the Multiscale Application Designer (MAD), and Gridspace Experiment Workbench. It is implemented and executed with the general Multiscale Coupling Library and Environment (MUSCLE). Finally, it is scheduled amongst heterogeneous infrastructures using the QCG-Broker. This marks the first occasion that a tightly coupled application uses distributed Multiscale computing in such a general way.
Bartosz Bosak - One of the best experts on this subject based on the ideXlab platform.
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Multiscale computing with the Multiscale modeling library and runtime environment
International Conference on Conceptual Structures, 2013Co-Authors: Joris Borgdorff, Mariusz Mamonski, Bartosz Bosak, Derek Groen, Mohamed Ben Belgacem, Krzysztof Kurowski, Alfons G HoekstraAbstract:We introduce a software tool to simulate Multiscale Models: the Multiscale Coupling Library and Environment 2 (MUSCLE 2). MUSCLE 2 is a component-based modeling tool inspired by the Multiscale modeling and simulation framework, with an easy-to-use API which supports Java, C++, C, and Fortran. We present MUSCLE 2's runtime features, such as its distributed computing capabilities, and its benefits to Multiscale modelers. We also describe two Multiscale Models that use MUSCLE 2 to do distributed Multiscale computing: an in-stent restenosis and a canal system model. We conclude that MUSCLE 2 is a notable improvement over the previous version of MUSCLE, and that it allows users to more flexibly deploy simulations of Multiscale Models, while improving their performance.
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a distributed Multiscale computation of a tightly coupled model using the Multiscale modeling language
International Conference on Conceptual Structures, 2012Co-Authors: Joris Borgdorff, Mariusz Mamonski, Bartosz Bosak, Krzysztof Kurowski, Carles Bonacasas, Tomasz Piontek, Katarzyna Rycerz, Eryk Ciepiela, Tomasz Gubala, Daniel HarezlakAbstract:Abstract Nature is observed at all scales; with Multiscale modeling, scientists bring together several scales for a holistic analysis of a phenomenon. The Models on these different scales may require significant but also heterogeneous computational resources, creating the need for distributed Multiscale computing. A particularly demanding type of Multiscale Models, tightly coupled, brings with it a number of theoretical and practical issues. In this contribution, a tightly coupled model of in-stent restenosis is first theoretically examined for its Multiscale merits using the Multiscale Modeling Language (MML); this is aided by a toolchain consisting of MAPPER Memory (MaMe), the Multiscale Application Designer (MAD), and Gridspace Experiment Workbench. It is implemented and executed with the general Multiscale Coupling Library and Environment (MUSCLE). Finally, it is scheduled amongst heterogeneous infrastructures using the QCG-Broker. This marks the first occasion that a tightly coupled application uses distributed Multiscale computing in such a general way.
