Toward an Accurate and Fast Hybrid Multi-Simulation with the FMI-CS Standard

International audienceMulti-simulation in the context of future smart electrical grids consists in associating components modeling different physical domains, but also their local or global control. Our DACCOSIM multi-simulation environment is based on the version 2.0 of the FMI-CS (Functional Mock-up Interface for Co-Simulation) standard maintained by the Modelica Association. It has been specifically designed to run large-scale and complex systems on a single PC or a cluster of multicore nodes. But it is quite challenging to accurately simulate FMUs-composed systems involving predictable and unpredictable events while preserving the system overall performance. This paper presents some additions to the FMI-CS standard aiming to improve the accuracy and the performance of distributed multi-simulations involving a mix of both time steps and various kinds of events. The proposed FMI-CS primitives are explained, as well as the Master Algorithm strategies to exploit them efficiently

CoSim20: An Integrated Development Environment for Accurate and Efficient Distributed Co-Simulations

International audienceThe development of Cyber-Physical Systems involves several disciplines and stakeholders, which use heterogeneous models and formalisms to specify the system and make early validation and verification. In order to understand the behaviour emerging from the heterogeneous models, a collaborative simulation (co-simulation) can be used. To make it happen, the system engineer must define a correct coordination of the different executable models, which can be distributed over different enterprises. This is an important but difficult (and error prone) task that can not be done without information about the behavioral semantics of each model. In this paper, we introduce an integrated development environment which allows 1) to import different executable models (named simulation units), 2) to graphically connect them with rich connectors and 3) to generate a dedicated, accurate and efficient distributed co-simulation. The framework is based on Eclipse EMF for the modeling part and on ∅MQ for the deployment. It is named CoSim20

Modelling and Co-simulation of Multi-Energy Systems: Distributed Software Methods and Platforms

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An approach to design smart grids and their IT system by cosimulation

International audienceSmart grids are the oncoming generation of power grids, which rely on information and communication technologies to tackle decentralized and intermittent energy sources such as wind farms and photovoltaic plants. They integrate electronics, software information processing and telecommunications technical domains. Therefore the design of smart grids is complex because of the various technical domains and modeling tools at stake. In this article, we present an approach to their design, which relies on model driven engineering, executable models and FMI based cosimulation. This approach is illustrated on the use case of an insular power grid and allows to study the impact of power production decision

A Semantic-Aware, Accurate and Efficient API for (Co-)Simulation of CPS

International audienceTo understand the behavior emerging from the coordination of heterogeneous simulation units, co-simulation usually relies on either a time-triggered or an event-triggered Application Programming Interface (API). It creates bias in the resulting behavior since time or event triggered API may not be appropriate to the behavioral semantics of the model inside the simulation unit. This paper presents a new semanticaware API to execute models. This API is a simple and straightforward extension of the Functional Mock-up Interface (FMI) API. It can be used to execute models in isolation, to debug them, and to co-simulate them. The new API is semantic aware in the sense that it goes beyond time/event triggered API to allow communication based on the behavioral semantics of internal models. This API is illustrated on a simple co-simulation use case with both Cyber and Physical models

WIP on a Coordination Language to Automate the Generation of Co-Simulations

International audienc

A systems biology approach to multi-scale modelling and analysis of planar cell polarity in drosophila melanogaster wing

This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Systems biology aims to describe and understand biology at a global scale where biological systems function as a result of complex mechanisms that happen at several scales. Modelling and simulation are computational tools that are invaluable for description, understanding and prediction these mechanisms in a quantitative and integrative way. Thus multi-scale methods that couple the design, simulation and analysis of models spanning several spatial and temporal scales is becoming a new emerging focus of systems biology. This thesis uses an exemplar – Planar cell polarity (PCP) signalling – to illustrate a generic approach to model biological systems at different spatial scales, using the new concept of Hierarchically Coloured Petri Nets (HCPN). PCP signalling refers to the coordinated polarisation of cells within the plane of various epithelial tissues to generate sub-cellular asymmetry along an axis orthogonal to their apical-basal axes. This polarisation is required for many developmental events in both vertebrates and non-vertebrates. Defects in PCP in vertebrates are responsible for developmental abnormalities in multiple tissues including the neural tube, the kidney and the inner ear. In Drosophila wing, PCP is seen in the parallel orientation of hairs that protrude from each of the approximately 30,000 epithelial cells to robustly point toward the wing tip. This work applies HCPN to model a tissue comprising multiple cells hexagonally packed in a honeycomb formation in order to describe the phenomenon of Planar Cell Polarity (PCP) in Drosophila wing. HCPN facilitate the construction of mathematically tractable, compact and parameterised large-scale models. Different levels of abstraction that can be used in order to simplify such a complex system are first illustrated. The PCP system is first represented at an abstract level without modelling details of the cell. Each cell is then sub-divided into seven virtual compartments with adjacent cells being coupled via the formation of intercellular complexes. A more detailed model is later developed, describing the intra- and inter-cellular signalling mechanisms involved in PCP signalling. The initial model is for a wild-type organism, and then a family of related models, permitting different hypotheses to be explored regarding the mechanisms underlying PCP, are constructed. Among them, the largest model consists of 800 cells which when unfolded yields 164,000 places (each of which is described by an ordinary differential equation). This thesis illustrates the power and validity of the approach by showing how the models can be easily adapted to describe well-documented genetic mutations in the Drosophila wing using the proposed approach including clustering and model checking over time series of primary and secondary data, which can be employed to analyse and check such multi-scale models similar to the case of PCP. The HCPN models support the interpretation of biological observations reported in literature and are able to make sensible predictions. As HCPN model multi-scale systems in a compact, parameterised and scalable way, this modelling approach can be applied to other large-scale or multi-scale systems.This study was funded by Brunel University

Automated Validation of State-Based Client-Centric Isolation with TLA ⁺

Clear consistency guarantees on data are paramount for the design and implementation of distributed systems. When implementing distributed applications, developers require approaches to verify the data consistency guarantees of an implementation choice. Crooks et al. define a state-based and client-centric model of database isolation. This paper formalizes this state-based model in, reproduces their examples and shows how to model check runtime traces and algorithms with this formalization. The formalized model in enables semi-automatic model checking for different implementation alternatives for transactional operations and allows checking of conformance to isolation levels. We reproduce examples of the original paper and confirm the isolation guarantees of the combination of the well-known 2-phase locking and 2-phase commit algorithms. Using model checking this formalization can also help finding bugs in incorrect specifications. This improves feasibility of automated checking of isolation guarantees in synthesized synchronization implementations and it provides an environment for experimenting with new designs.</p

What scans we will read: imaging instrumentation trends in clinical oncology

Oncological diseases account for a significant portion of the burden on public healthcare systems with associated costs driven primarily by complex and long-lasting therapies. Through the visualization of patient-specific morphology and functional-molecular pathways, cancerous tissue can be detected and characterized non- invasively, so as to provide referring oncologists with essential information to support therapy management decisions. Following the onset of stand-alone anatomical and functional imaging, we witness a push towards integrating molecular image information through various methods, including anato-metabolic imaging (e.g., PET/ CT), advanced MRI, optical or ultrasound imaging. This perspective paper highlights a number of key technological and methodological advances in imaging instrumentation related to anatomical, functional, molecular medicine and hybrid imaging, that is understood as the hardware-based combination of complementary anatomical and molecular imaging. These include novel detector technologies for ionizing radiation used in CT and nuclear medicine imaging, and novel system developments in MRI and optical as well as opto-acoustic imaging. We will also highlight new data processing methods for improved non-invasive tissue characterization. Following a general introduction to the role of imaging in oncology patient management we introduce imaging methods with well-defined clinical applications and potential for clinical translation. For each modality, we report first on the status quo and point to perceived technological and methodological advances in a subsequent status go section. Considering the breadth and dynamics of these developments, this perspective ends with a critical reflection on where the authors, with the majority of them being imaging experts with a background in physics and engineering, believe imaging methods will be in a few years from now. Overall, methodological and technological medical imaging advances are geared towards increased image contrast, the derivation of reproducible quantitative parameters, an increase in volume sensitivity and a reduction in overall examination time. To ensure full translation to the clinic, this progress in technologies and instrumentation is complemented by progress in relevant acquisition and image-processing protocols and improved data analysis. To this end, we should accept diagnostic images as “data”, and – through the wider adoption of advanced analysis, including machine learning approaches and a “big data” concept – move to the next stage of non-invasive tumor phenotyping. The scans we will be reading in 10 years from now will likely be composed of highly diverse multi- dimensional data from multiple sources, which mandate the use of advanced and interactive visualization and analysis platforms powered by Artificial Intelligence (AI) for real-time data handling by cross-specialty clinical experts with a domain knowledge that will need to go beyond that of plain imaging