Multiscale multiagent architecture validation by virtual instruments in molecular dynamics experiments

Combes, Manuel; Buin, Benjamin; Parenthoën, Marc; Tisseau, Jacques

doi:10.1016/j.procs.2010.04.082

Cited by 5 publications

(5 citation statements)

References 15 publications

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“…More generally, combining multiscale modelling with the use of virtual reality could provide significant progress on providing virtual experimentation of LIBs. 286 Finally, to get progress on the development of multiscale models, it is crucial to develop multidisciplinarity between application domains. For example, computational scientists working in cosmology, geology and climate science could bring interesting methodological concepts for the widespread use of multiscale modelling in electrochemistry.…”

Section: Conclusion and Challengesmentioning

confidence: 99%

Multiscale modelling and numerical simulation of rechargeable lithium ion batteries: concepts, methods and challenges

2013

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This review focuses on the role of physical theory and computational electrochemistry for fundamental understanding, diagnostics and design of new electrochemical materials and operation conditions for energy storage through rechargeable Li ion batteries (LIBs). More particularly, deep insight based on multiscale physical modelling techniques, spanning scales from few atoms to the device level, can advise about the materials behaviour and aging and how components with optimal specifications could be made and how they can be integrated into operating devices. Concepts and different existing multiscale modelling methodologies are presented and some of the ongoing efforts within the community to understand from physical multiscale modelling and numerical simulation electrochemical mechanisms and degradation processes in LIBs are discussed. Finally, major challenges and perspectives in multiscale modelling for battery applications are highlighted.

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Section: Conclusion and Challengesmentioning

confidence: 99%

Multiscale modelling and numerical simulation of rechargeable lithium ion batteries: concepts, methods and challenges

2013

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“…These laws are prescribed in a physical (or economic, biological, etc.) model that may be improved and complexified at will, through individual properties and interactions (perception, communication) between them [e.g., Müller et al , 2003; Combes et al , 2010]. An intuitive vision of MAS considers that each agent is a cyclic engine operating in three steps: (1) Perception: it perceives its environment through specialized sensors, (2) Decision: it decides on its behavior following its sensors and internal state, (3) Action: it behaves by modifying its internal state and direct environment.…”

Section: Introductionmentioning

confidence: 99%

“…An intuitive vision of MAS considers that each agent is a cyclic engine operating in three steps: (1) Perception: it perceives its environment through specialized sensors, (2) Decision: it decides on its behavior following its sensors and internal state, (3) Action: it behaves by modifying its internal state and direct environment. Multiagent systems are commonly used for biology and medicine [e.g., Kerdelo et al , 2002; Vicari et al , 2003; Corradini and Merelli , 2005; Boruchov et al , 2007], molecular dynamics [e.g., Gordon‐Spears and Spears , 2002; Coulon et al , 2008; Combes et al , 2010] and fluid dynamics [ Müller et al , 2003; Parenthoën et al , 2004]. Few geophysical studies have used multiagent systems until recently [e.g., Marcenac and Giroux , 1998], although cellular automata have been used successfully to describe dune dynamics [ Narteau , 2007; Narteau et al , 2009; Zhang et al , 2010].…”

Section: Introductionmentioning

confidence: 99%

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Multiagent simulation of evolutive plate tectonics applied to the thermal evolution of the Earth

Combes¹,

Grigné²,

Husson³

et al. 2012

Geochem Geophys Geosyst

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[1] The feedback between plate tectonics and mantle convection controls the Earth's thermal evolution via the seafloor age distribution. We therefore designed the MACMA model to simulate time-dependent plate tectonics in a 2D cylindrical geometry with evolutive plate boundaries, based on multiagent systems that express thermal and mechanical interactions. We compute plate velocities using a local force balance and use explicit parameterizations to treat tectonic processes such as trench migration, subduction initiation, continental breakup and plate suturing. These implementations allow the model to update its geometry and thermal state at all times. Our approach has two goals: (1) to test how empirically-and analyticallydetermined rules for surface processes affect mantle and plate dynamics, and (2) to investigate how plate tectonics impact the thermal regime. Our predictions for driving forces, plate velocities and heat flux are in agreement with independent observations. Two time scales arise for the evolution of the heat flux: a linear long-term decrease and high-amplitude short-term fluctuations due to surface tectonics. We also obtain a plausible thermal history, with mantle temperature decreasing by less than 200 K over the last 3 Gyr. In addition, we show that on the long term, mantle viscosity is less thermally influential than tectonic processes such as continental breakup or subduction initiation, because Earth's cooling rate depends mainly on its ability to replace old insulating seafloor by young thin oceanic lithosphere. We infer that simple Copyright 2012 by the American Geophysical Union 1 of 24 convective considerations alone cannot account for the nature of mantle heat loss and that tectonic processes dictate the thermal evolution of the Earth.

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“…We find individualbased simulation appropriate when addressing problems in which limit conditions change according to unpredictable influences such as the user's actions. As for example, it facilitates the interactive adjustment of an ethological model producing patterns [1], it makes the injection of a substance possible if a peculiar situation is observed during a medical experiment simulation [2] or it enables the study of the measurement process impact in a molecular dynamic simulation [3]. Moreover, the interactive aspect is decisive when using virtual reality for learning or training.…”

Section: Introductionmentioning

confidence: 99%

Designing a Multicore and Multiprocessor Individual-Based Simulation Engine

Harrouet¹

2012

IEEE Micro

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Multiscale multiagent architecture validation by virtual instruments in molecular dynamics experiments

Cited by 5 publications

References 15 publications

Multiscale modelling and numerical simulation of rechargeable lithium ion batteries: concepts, methods and challenges

Multiscale modelling and numerical simulation of rechargeable lithium ion batteries: concepts, methods and challenges

Multiagent simulation of evolutive plate tectonics applied to the thermal evolution of the Earth

Designing a Multicore and Multiprocessor Individual-Based Simulation Engine

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