Model-based engineering of Digital Twins for early verification and validation of Industrial Systems (MATISSE), Proposal number: 101140216-2, Call: HORIZON-KDT-JU-2023-2-RIA, 2024 – 2027.
Thanks to the advances in information technology, modern industrial systems are becoming increasingly intelligent and autonomous; thus their requirements for, e.g., correctness, availability, traceability and reliability, are also increasing. Monitoring, analysis and diagnosis of such industrial systems became pivotal and fueled the development of virtualization and simulation solutions such as digital twins.
In a nutshell, digital twins are virtual representations of actual systems or processes that serve as real-time digital counterparts for, e.g., prediction, analysis, testing, and simulation. Developing digital twins is a complex process. On the one hand, it includes developing digital twins at different levels of abstraction of the system to allow one to focus on different relevant aspects (e.g, behavioural, logical, physical). On the other hand, it must ensure the correctness of digital twins with respect to the system specifications and the respective level of abstraction, and the federation enabling the communication between digital twins conceived as exchange and resume of models.
This project aims to develop a model-based framework addressing the above-mentioned challenges by i) automating the creation of digital twins for the simulation, monitoring and testing of functional and non-functional properties ii) continuous validating digital twins to meet the required properties and iii) developing a multidomain and automated digital twin toolchain for the verification and validation of complex industrial systems based on digital twins. We foresee that this project will positively impact the efficiency of such systems by reducing their time to value and by increasing their final quality.
Advanced Technologies Platform for Sustainable Cities, Proposal Number: 22AG040, Call:1004- Mükemmeliyet Merkezi Destek Programı, 19 December 2022 – 19 December 2025
Developing software quality assurance, verification and validation tools for Fleet Management System components and endpoints is critical for sustainable city technology. In this context, verification and validation workflows, methods and tools will be developed for the artificial intelligence algorithms to be developed within the scope of the project together with mutation-based tests or model-based formal verification approaches, and demonstrations will be carried out by performing tests and applications on the system.
https://1004.tubitak.gov.tr/tr/node/95
OPtimize Electric Vehicle Autonomy (OPEVA), Proposal number: 101097267, Call: HORIZON-KDT-JU-2021-2-RIA, 1 January 2023 – 31 December 2025.
The OPEVA project will study all actors that will create a modern "mobility experience", taking into account sustainability and resource optimisation in the transition to fossil fuel-free vehicles. It targets outputs in six critical technology areas in the ecosystem and four areas for socio-economic compatibility in order to accelerate the deployment of electric vehicles (EVs).
The first technology area (TD1) in the OPEVA project targets innovation in collecting information not only from the battery, but also from other on-board sensors, driver behaviour and the vehicle itself, in order to create a performance and consumption model tailored to the individual vehicle and its driver. The second technology area (TD2) aims to optimise the individual driving segment using off-vehicle data such as road condition, weather, charging station location and occupancy, etc. collected from back-end systems. The third technology area (TD3) will also address the challenges related to the communication between the vehicle and the infrastructure to collect data from back-end systems. It also targets innovation in the use of charging stations and related applications (TD4). It also aims to better understand what the battery and its constituent cells actually do during real-world use for an improved battery management system (TD5). Finally, TD6 also covers driver-oriented human factors to optimise the use of electric vehicles. On the other hand, the OPEVA methods will consider economic factors (NTD1), legal and ethical aspects (N-TD2), human development related to EVs (N-TD3) and societal and environmental factors (NTD4). Studies will be carried out within the scope of the project in order to increase the acceptance and awareness of these developments in the society.
https://opeva.eu
Verification and Validation of Automated Systems' Safety and Security (Valu3s), Proposal number: 876852-2, Call: H2020-ECSEL-2019-2-RIA, 1 May 2020 – 1 May 2023.
Manufacturers of automated systems and their components have been allocating an enormous amount of time and effort in R&D activities. This effort translates into an overhead on the V&V (verification and validation) process making it time-consuming and costly. The ECSEL JU project VALU3S aims to evaluate the state-of-the-art V&V methods and tools, and design a multi-domain framework to create a clear structure around the components and elements needed to conduct the V&V process. The main expected benefit of the framework is to reduce time and cost needed to verify and validate automated systems with respect to safety, cyber-security, and privacy requirements. This is done through identification and classification of evaluation methods, tools, environments and concepts for V&V of automated systems with respect to the mentioned requirements. To this end, VALU3S brings together a consortium with partners from 10 different countries, amounting to a mix of 25 industrial partners, 6 leading research institutes, and 10 universities to reach the project goal.
Prognostics and Health Management Tool for ROS, funded by EU ROSin Project, 2018-2020
PHM tool is model-based user interface which the user creates his system using various mechanical and electrical equipment’s, but can also calculates the reliability, failure rate and probability of task completion (POTC) of the created system. In addition, the PHM Tool offers the user the ability to formulate his own components and add them to the system. PHM Tool can also work with a real robot. Data from the sensors on the real robot are published via ROS topics. By subscribing to these topics in the PHM Tool, the system’s failure rate, reliability and POTC values are calculated together with the data which is obtained from the sensors.
https://github.com/ESOGU-SRLAB/phm_tools-release
https://github.com/ESOGU-SRLAB/phm_tools
https://www.rosin-project.eu/ftp/prognostics-and-health-management-tool-for-ros