Contracts and Behavioral Patterns for SoS: The EU IP DANSE approach

This paper presents some of the results of the first year of DANSE, one of the first EU IP projects dedicated to SoS. Concretely, we offer a tool chain that allows to specify SoS and SoS requirements at high level, and analyse them using powerful toolsets coming from the formal verification area. At the high level, we use UPDM, the system model provided by the british army as well as a new type of contract based on behavioral patterns. At low level, we rely on a powerful simulation toolset combined with recent advances from the area of statistical model checking. The approach has been applied to a case study developed at EADS Innovation Works.Comment: In Proceedings AiSoS 2013, arXiv:1311.319

The Internet of Simulation: Enabling Agile Model Based Systems Engineering for Cyber-Physical Systems

The expansion of the Internet of Things (IoT) has resulted in a complex cyber-physical system of systems that is continually evolving. With ever more complex systems being developed and changed there has been an increasing reliance on simulation as a vital part of the design process. There is also a growing need for simulation integration and co-simulation in order to analyse the complex interactions between system components. To this end we propose that the Internet of Simulation (IoS) as an extension of IoT can be used to meet these needs. The IoS allows for multiple heterogeneous simulations to be integrated together for co-simulation. It's effect on the engineer process is to facilitate agile practices without sacrificing rigour. An Industry 4.0 example case study is provided showing how IoS could be utilized

Artificial intelligence and model checking methods for in silico clinical trials

Model-based approaches to safety and efficacy assessment of pharmacological treatments (In Silico Clinical Trials, ISCT) hold the promise to decrease time and cost for the needed experimentations, reduce the need for animal and human testing, and enable personalised medicine, where treatments tailored for each single patient can be designed before being actually administered. Research in Virtual Physiological Human (VPH) is harvesting such promise by developing quantitative mechanistic models of patient physiology and drugs. Depending on many parameters, such models define physiological differences among different individuals and different reactions to drug administrations. Value assignments to model parameters can be regarded as Virtual Patients (VPs). Thus, as in vivo clinical trials test relevant drugs against suitable candidate patients, ISCT simulate effect of relevant drugs against VPs covering possible behaviours that might occur in vivo. Having a population of VPs representative of the whole spectrum of human patient behaviours is a key enabler of ISCT. However, VPH models of practical relevance are typically too complex to be solved analytically or to be formally analysed. Thus, they are usually solved numerically within simulators. In this setting, Artificial Intelligence and Model Checking methods are typically devised. Indeed, a VP coupled together with a pharmacological treatment represents a closed-loop model where the VP plays the role of a physical subsystem and the treatment strategy plays the role of the control software. Systems with this structure are known as Cyber-Physical Systems (CPSs). Thus, simulation-based methodologies for CPSs can be employed within personalised medicine in order to compute representative VP populations and to conduct ISCT. In this thesis, we advance the state of the art of simulation-based Artificial Intelligence and Model Checking methods for ISCT in the following directions. First, we present a Statistical Model Checking (SMC) methodology based on hypothesis testing that, given a VPH model as input, computes a population of VPs which is representative (i.e., large enough to represent all relevant phenotypes, with a given degree of statistical confidence) and stratified (i.e., organised as a multi-layer hierarchy of homogeneous sub-groups). Stratification allows ISCT to adaptively focus on specific phenotypes, also supporting prioritisation of patient sub-groups in follow-up in vivo clinical trials. Second, resting on a representative VP population, we design an ISCT aiming at optimising a complex treatment for a patient digital twin, that is the virtual counterpart of that patient physiology defined by means of a set of VPs. Our ISCT employs an intelligent search driving a VPH model simulator to seek the lightest but still effective treatment for the input patient digital twin. Third, to enable interoperability among VPH models defined with different modelling and simulation environments and to increase efficiency of our ISCT, we also design an optimised simulator driver to speed-up backtracking-based search algorithms driving simulators. Finally, we evaluate the effectiveness of our presented methodologies on state-of-the-art use cases and validate our results on retrospective clinical data

Measuring Competition between Non-Food and Food Demand on World Grain Markets : Is Biofuel Production Compatible with Pressure for Food Production ?

The flow of agricultural products between countries is conditioned by several factors including domestic and trade policy tools for the main competing exporters countries, and macroeconomic variables (such as real income per capita, rate of population growth,etc). Important structural changes are occurring on world agricultural markets that will have an impact on the long term competitiveness of countries and regions. These changes include developments in biofuels production linked to policy incentives, and the rapid growth in income and population numbers in some developing countries (such as India and China). An important issue is to identify the factors that are going to modify the balance between the supply and demand for agricultural products in the long term. In this paper, we look the example of arable crops. These markets allow an interesting analysis since they are directly concerned with the evolution of biofuels. One important question is to measure the competition between food demand and non food demand. We use a partial equilibrium model that focuses on world arable crop markets, the World Econometric Modeling of Arable Crops. The aim of the model is to produce annual market projections over a medium-term perspective and to simulate the impact of alternative national and international agricultural policy reforms for the main arable crops. The results of the simulations performed show that even if incentives to produce of biofuels have strong impacts on world markets, other factors such as changes in the assumptions of concerning the growth of emerging countries are also of great importance since the world cereal and oilseed markets as much are just bymodeling, econometric, partial equilibrium, land uses, biofuels, Demand and Price Analysis, International Relations/Trade,

A Distributed Multi-Model Platform to Cosimulate Multi-Energy Systems in Smart Buildings

Nowadays, buildings are responsible for large consumption of energy in our cities. Moreover, buildings can be seen as the smallest entity of urban energy systems. On these premises, in this paper, we present a flexible and distributed co-simulation platform that exploits a multi-modelling approach to simulate and evaluate energy performance in smart buildings. The developed platform exploits the Mosaik co-simulation framework and implements the Functional Mock-up Interface (FMI) standard in order to couple and synchronise heterogeneous simulators and models. The platform combines in a shared simulation environment: i) the thermal performance of the building simulated with EnergyPlus; ii) a heat pump integrated with a PID control strategy modelled in Modelica to satisfy the heating demand of the building; iii) an electrical energy storage system modelled in MATLAB Simulink; and iv) different Python models used to simulate household occupancy, electrical loads, photovoltaic production and smart meters, respectively. The platform guarantees a plug-and-play integration of models and simulators, in which one or more models can be easily replaced without affecting the whole simulation engine. Finally, we present a demonstration example to test the functionalities, capability and usability of the developed platform and discuss future developments of our framework

An Empirical Survey on Co-simulation: Promising Standards, Challenges and Research Needs

Co-simulation is a promising approach for the modelling and simulation of complex systems, that makes use of mature simulation tools in the respective domains. It has been applied in wildly different domains, oftentimes without a comprehensive study of the impact to the simulation results. As a consequence, over the recent years, researchers have set out to understand the essential challenges arising from the application of this technique. This paper complements the existing surveys in that the social and empirical aspects were addressed. More than 50 experts participated in a two-stage Delphi study to determine current challenges, research needs and promising standards and tools. Furthermore, an analysis of the strengths, weakness, opportunities and threats of co-simulation utilizing the analytic hierarchy process resulting in a SWOT-AHP analysis is presented. The empirical results of this study show that experts consider the FMI standard to be the most promising standard for continuous time, discrete event and hybrid co-simulation. The results of the SWOT-AHP analysis indicate that factors related to strengths and opportunities predominate

The 14th Overture Workshop: Towards Analytical Tool Chains

This report contains the proceedings from the 14th Overture workshop organized in connection with the Formal Methods 2016 symposium. This includes nine papers describing different technological progress in relation to the Overture/VDM tool support and its connection with other tools such as Crescendo, Symphony, INTO-CPS, TASTE and ViennaTalk