A Model Identity Card to Support Simulation Model Development Process in a Collaborative Multidisciplinary Design Environment

Sirin, Göknur; Paredis, Christiaan J. J.; Yannou, Bernard; Coatanéa, Éric; Landel, Eric

doi:10.1109/jsyst.2014.2371541

Cited by 35 publications

(24 citation statements)

References 22 publications

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“…The flexibility F(o i ) is defined by equation (6). F(o i ) expresses the length of an execution interval within which operation o i can be executed without increasing the total execution time of the graph:…”

Section: Dependence Graph Attributesmentioning

confidence: 99%

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A method for parallel scheduling of multi-rate co-simulation on multi-core platforms

Saidi

Pernet

Sorel

2019

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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The design of cyber-physical systems is a complex process and relies on the simulation of the system behavior before its deployment. Such is the case, for instance, of joint simulation of the different subsystems that constitute a hybrid automotive powertrain. Co-simulation allows system designers to simulate a whole system composed of a number of interconnected subsystem simulators. Traditionally, these subsystems are modeled by experts of different fields using different tools, and then integrated into one tool to perform simulation at the system-level. This results in complex and compute-intensive co-simulations and requires the parallelization of these co-simulations in order to accelerate their execution. The simulators composing a co-simulation are characterized by the rates of data exchange between the simulators, defined by the engineers who set the communication steps. The RCOSIM approach allows the parallelization on multi-core processors of co-simulations using the FMI standard. This approach is based on the exploitation of the co-simulation parallelism where dependent functions perform different computation tasks. In this paper, we extend RCOSIM to handle additional co-simulation requirements. First, we extend the co-simulation to multi-rate, i.e. where simulators are assigned different communication steps. We present graph transformation rules and an algorithm that allow the execution of each simulator at its respective rate while ensuring correct and efficient data exchange between simulators. Second, we present an approach based on acyclic orientation of mixed graphs for handling mutual exclusion constraints between functions that belong to the same simulator due to the non-thread-safe implementation of FMI. We propose an exact algorithm and a heuristic for performing the acyclic orientation. The final stage of the proposed approach consists in scheduling the co-simulation on a multi-core architecture. We propose an algorithm and a heuristic for computing a schedule which minimizes the total execution time of the co-simulation. We evaluate the performance of our proposed approach in terms of the obtained execution speed. By applying our approach on an industrial use case, we obtained a maximum speedup of 2.91 on four cores.

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Section: Dependence Graph Attributesmentioning

confidence: 99%

“…Co-simulation requires domain-specific information for each involved FMU. Such information, which is beyond the scope of FMI, can be provided by domain experts, for example by using an approach like the one proposed by Sirin et al [6]. The communication steps of FMUs can be shared as part of this information.…”

Section: Introductionmentioning

confidence: 99%

A method for parallel scheduling of multi-rate co-simulation on multi-core platforms

Saidi

Pernet

Sorel

2019

Oil Gas Sci. Technol. – Rev. IFP Energies nouvelles

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“…The specification framework is based on a set of DSMs and DMMs populated by numbers; these matrices form a "fingerprint" of the design problem and its conceptual solution. This "identity card" 19 can be used to specify problem requirements in a compact manner and validate the produced solution. The DACM framework can also be used to specify the development of reusable modeling primitives and create new models to address alternative problems.…”

Section: Input Extrapolationmentioning

confidence: 99%

A Conceptual Modeling and Simulation Framework for System Design

et al. 2016

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The dimensional analysis conceptual modeling (DACM) framework is a conceptual modeling mechanism for lifecycle systems engineering. Originally developed for military projects, the DACM framework is now available for other applications, too. This powerful approach handles the specifying, discovering, validating, and reusing of building blocks as well as system behavior analysis in early development stages.

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“…Recently, a model identity card was proposed as a standard description of model requests [34]. The MIC permits to describe some of the desired characteristics of the model in order to guide its development.…”

Section: Formalize Model Requests To Model Suppliersmentioning

confidence: 99%