One primary objective of drone simulation is to evaluate diverse drone configurations and contexts aligned with specific user objectives. The initial challenge for simulator designers involves managing the heterogeneity of drone components, encompassing both software and hardware systems, as well as the drone’s behavior. To facilitate the integration of these diverse models, the Functional Mock-Up Interface (FMI) for co-simulation proposes a generic data-oriented interface. However, an additional challenge lies in simplifying the configuration of co-simulation, necessitating an approach to guide the modeling of parametric features and operational conditions such as failures or environment changes. The article addresses this challenge by introducing CARES, a model-driven engineering and component-based approach for designing drone simulators, integrating the FMI for co-simulation. The proposed models incorporate concepts from component-based software engineering and FMI. The NAVIDRO architectural style is presented for designing and configuring drone co-simulation. CARES utilizes a code generator to produce structural glue code (Java or C++), facilitating the integration of FMI-based domain-specific code. The approach is evaluated through the development of a simulator for navigation functions in an autonomous underwater vehicle, demonstrating its effectiveness in assessing various autonomous underwater vehicle configurations and contexts.

One key objective of Cyber-Physical System (CPS) simulation is to evaluate different CPS configurations regarding a certain user objective. First, simulation of CPS necessitates frameworks to handle heterogeneity of CPS components (the software and hardware system control, the behavior of the CPS itself and its physical environment). Then, to build simulators, designers use paradigms like FMI (Functional Mock-Up Interface) that proposes a data-driven generic interface facilitating the integration of heterogeneous models. However, in order to facilitate simulation configuration, an approach is required to drive modeling of parametric features and operational conditions. In this paper, we present CARES, a component-based and model-driven approach to facilitate CPS simulation. CARES is applied to evaluate an Autonomous Underwater Vehicle (AUV) navigation function by simulation. The proposed models integrate both the principles of a generic simulation (integration of Component Based Software Engineering CBSE concepts and FMI paradigm) and domain specific aspects through a component-based architecture style. From a design model, a code generator builds the structural (Java or C++) code of the simulator. The generated code relies on a given run-time library for its execution and its structure facilitates integration of domain-specific code. The experiments show the effectiveness of the approach to build simulators for evaluation of different AUV configurations.

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MOTIVATION: Intrinsically disordered proteins (IDPs) represent a significant fraction of the human proteome. The classical structure function paradigm that has successfully underpinned our understanding of molecular biology breaks down when considering proteins that have no stable tertiary structure in their functional form. One convenient approach is to describe the protein in terms of an equilibrium of rapidly inter-converting conformers. Currently, tools to generate such ensemble descriptions are extremely rare, and poorly adapted to the prediction of experimental data. RESULTS: We present flexible-meccano-a highly efficient algorithm that generates ensembles of molecules, on the basis of amino acid-specific conformational potentials and volume exclusion. Conformational sampling depends uniquely on the primary sequence, with the possibility of introducing additional local or long-range conformational propensities at an amino acid-specific resolution. The algorithm can also be used to calculate expected values of experimental parameters measured at atomic or molecular resolution, such as nuclear magnetic resonance (NMR) and small angle scattering, respectively. We envisage that flexible-meccano will be useful for researchers who wish to compare experimental data with those expected from a fully disordered protein, researchers who see experimental evidence of deviation from 'random coil' behaviour in their protein, or researchers who are interested in working with a broad ensemble of conformers representing the flexibility of the IDP of interest. AVAILABILITY: A fully documented multi-platform executable is provided, with examples, at http://www.ibs.fr/science-213/scientific-output/software/flexible-meccano/ CONTACT: [email protected].