Features of Integrated Model-Based Co-modelling and Co-simulation Technology

Larsen, Peter Gorm; Fitzgerald, JS; Woodcock, Jim; Gamble, Carl; Payne, Richard J.; Pierce, Ken

doi:10.1007/978-3-319-74781-1_26

Cited by 21 publications

(15 citation statements)

References 41 publications

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“…In Engineering of Cyber-Physical Systems in the automotive context: case study of a range prediction assistant [12] (in this issue), the authors present a case study addressing the development of an assistant for estimating the range of an electric vehicle. The approach is based on the methodology and tools from the EU Horizon 2020 INTO-CPS project [13]. The paper promises an outlook on the development of similar tool chains for automotive planning.…”

Section: Abstract: Formal Methods Verification Modelling Discretementioning

confidence: 99%

Cyber-Physical Systems Engineering: An Introduction

Gibson

Larsen

Pantel

et al. 2018

Leveraging Applications of Formal Methods, Verification and Validation. Distributed Systems

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Section: Abstract: Formal Methods Verification Modelling Discretementioning

confidence: 99%

Cyber-Physical Systems Engineering: An Introduction

Gibson

Larsen

Pantel

et al. 2018

Leveraging Applications of Formal Methods, Verification and Validation. Distributed Systems

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“…To that end, the multi-model needed to represent infrastructure, including power supply; to describe realistic rolling stock performance, including Fig. 1 Co-simulation in the INTO-CPS tool chain [41] power characteristics and regenerative braking; to describe driver behaviour, including more defensive, energy-efficient driving; and to support movement authority (i.e. a signalling system) to represent the communication to drivers when they have permission to proceed.…”

Section: Conceptual Multi-model Architecturementioning

confidence: 99%

“…The INTO-CPS technologies are a collection of tools based around multi-models [41]. These tools form a tool chain that can be used to analyse multi-models, for example, through co-simulation.…”

Section: Introductionmentioning

confidence: 99%

Multi-modelling for Decarbonisation in Urban Rail Systems

et al. 2019

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This paper demonstrates a methodology for flexible, dynamic systems modelling relevant to urban rail decarbonisation. Decarbonisation of urban rail is a vital component of policy and strategy to minimize anthropogenic emissions. Decarbonisation is a systems problem, however, that needs to reflect the interaction between components and processes. Dynamic computer modelling of systems for decarbonisation involves interfacing multiple models together and running them in parallel in order to observe and predict systems-level effects. This is challenging due to the diverse nature of models, achieving parallel model integration and concerns around intellectual property (IP). One solution is the multi-modelling paradigm, which supports integrated, diverse, secure interfacing of models. This paper demonstrates the application of the multi-modelling approach, using the INTO-CPS tool chain. A multi-model was developed comprising key components required for urban rail decarbonisation problems. This multi-model was tested for power consumption in four different scenarios with an example drawn from the Tyne and Wear Metro in Newcastle-upon-Tyne in the United Kingdom. These scenarios compared combinations of decarbonisation intervention (baseline rolling stock versus lightweight, regenerative braking rolling stock and baseline driving style versus energy-efficient defensive driving style), generating different power consumption profiles for each. As such, this serves as a proof of the application of the multi-modelling approach and demonstrates a number of benefits for flexible and rapid systems modelling. This paper fills a knowledge gap by demonstrating a potentially valuable tool for future systems-level decarbonisation challenges in urban rail.

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“…If the item is rejected (the test fails to confirm the requested characteristics of the stick), then the process is automatically re-started, and a new request is made to the warehouse unit. In addition, to capture the value adding processes in Industry 4.0 [14,18,20], the case study includes distinct units to reflect the users who place orders for assembling the USB sticks, and the required infrastructure that make possible for the others CPSs to exist. These are: Layout of the production line as depicted in the 3D rendering of the simulation: 1) the warehouse stacks; 2) the assembly box at the base of the warehouse stacks; 3) the memory boxes of the warehouse unit; 4) the robotic arm for moving parts around the warehouse; 5) wagons on different locations of the track; 6) the loading station; 7) the test station; 8) the circular track for the wagons The HMI unit handles the user interface; it communicates only with the Part Tracker.…”

Section: Case Study: Manufacturing Usb Sticksmentioning

confidence: 99%

Multi-Paradigm Discrete-Event Modelling and Co-simulation of Cyber-Physical Systems

Neghina¹,

Zamfirescu²,

Larsen³

et al. 2018

STUD INFORM CONTROL

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Abstract:In the modelling of Cyber-Physical Systems (CPSs), there are different possible routes that can be followed to gradually achieve a collection of constituent models that can be co-simulated with a high level of accuracy. This paper demonstrates a methodology which initially develops all constituent models at a high level of abstraction with discreteevent models expressed using the Vienna Development Method (VDM). Subsequently, a number of these are refined (without changing the interfaces) by more detailed models expressed in different formalisms, and using tools that can export Functional Mock-up Units (FMUs) for co-simulation through the Functional Mock-up Interface (FMI) standard. The development team of each of these more detailed models can then experiment with the interactions with all the other constituent models, using the high-level discrete-event versions until higher-fidelity alternatives are ready. The results reported in this paper were obtained in an innovation experiment within the EU CPSE Labs research project, part of Smart Anything Everywhere initiative.

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Features of Integrated Model-Based Co-modelling and Co-simulation Technology

Cited by 21 publications

References 41 publications

Cyber-Physical Systems Engineering: An Introduction

Cyber-Physical Systems Engineering: An Introduction

Multi-modelling for Decarbonisation in Urban Rail Systems

Multi-Paradigm Discrete-Event Modelling and Co-simulation of Cyber-Physical Systems

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