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This document is a result of the COOCK project "Smart Port 2025: improving and accelerating the operational efficiency of a harbour eco-system through the application of intelligent technologies". The project is mainly aimed at SMEs, but also at large corporations. Together, they form the value-chain of the harbour. The digital maturity of these actors will be increased by model and data-driven digitization. The project brings together both technology users and providers/integrators. In this report, the broad spectrum of model and data-based digitization approaches is structured, under the unifying umbrella of "Digital Twins". During the (currently quite ad-hoc) digitization process and in particular, the creations of Digital Twins, a variety of choices have an impact on the ultimately realised system. This document identifies three stages during which this "variability" appears: the Problem Space Goal Construction Stage, the (Conceptual) Architecture Design Stage and the Deployment Stage. To illustrate the workflow, two simple use-cases are used: one of a ship moving in 1 dimension and, at a different scale and level of detail, a macroscopic model of the Port of Antwerp.

This document is a result of the COOCK project "Smart Port 2025: improving and accelerating the operational efficiency of a harbour eco-system through the application of intelligent technologies". It reports on the needs of companies for modelling and simulation and AI-based techniques, with twinning systems in particular. This document categorizes the purposes and Properties of Interest for the use of Digital Twins. It further illustrates some of the twinning usages, and touches on some of the potential architectural compositions for twins. This last topic will be further elaborated in a followup report.

The pace of reporting on Digital Twin (DT) projects continues to accelerate both in industry and academia. However, these experience reports often leave out essential characteristics of the DT, such as the scope of the system-under-study, the insights and actions enabled, and the time-scale of processing. A lack of these details could therefore hamper both understanding of these DTs and development of DT tools and techniques. Our previous work developed a DT description framework with fourteen characteristics as a checklist for experience report authors to better describe the capabilities of their DT projects. This report provides an extended example of reporting to highlight the utility of this description framework, focusing on the DT of an industrial drilling machine. Furthermore, we provide a mapping from our description framework to the Asset Administration Shell (AAS) which is an emerging standard for Industry 4.0 system integration. This mapping aids practitioners in understanding how our description framework relates to AAS, potentially aiding in description or implementation activities.

In this paper, we analyse the impact of delayed event detection on the stability of a 2-mode planar hybrid automata. We consider hybrid automata with a unique equilibrium point for all the modes, and we find the maximum delay that preserves stability of that equilibrium point. We also show for the class of hybrid automata treated that the instability of the equilibrium point for the equivalent hybrid automaton with delay in the transitions is equivalent to the existence of a closed orbit in the hybrid state space, a result that is inspired by the Joint Spectral Radius theorem. This leads to an algorithm for computing the maximum stable delay exactly. Other potential applications of our technique include co-simulation, networked control systems and delayed controlled switching with a state feedback control., Comment: This is the extended version of the corresponding paper at the CDC Conference: Legat, Beno\^it, Cl\'audio Gomes, Paschalis Karalis, Rapha\"el M. Jungers, Eva M. Navarro-L\'opez, and Hans Vangheluwe. "Stability of Planar Switched Systems under Delayed Event Detection." In 2020 IEEE 59th Conference on Decision and Control. Virtual event: IEEE Comput. Soc. Press, 2020

Co-simulation consists of the theory and techniques to enable global simulation of a coupled system via the composition of simulators. Despite the large number of applications and growing interest in the challenges, the field remains fragmented into multiple application domains, with limited sharing of knowledge. This tutorial aims at introducing co-simulation of continuous systems, targeted at researchers new to the field.

We propose an algorithm to restrict the switching signals of a constrained switched system in order to guarantee its stability, while at the same time attempting to keep the largest possible set of allowed switching signals. Our work is motivated by applications to (co-)simulation, where numerical stability is a hard constraint, but should be attained by restricting as little as possible the allowed behaviours of the simulators. We apply our results to certify the stability of an adaptive co-simulation orchestration algorithm, which selects the optimal switching signal at run-time, as a function of (varying) performance and accuracy requirements., Comment: Technical report complementing the following conference publication: Gomes, Cl\'audio, Beno\^it Legat, Rapha\"el Jungers, and Hans Vangheluwe. "Minimally Constrained Stable Switched Systems and Application to Co-Simulation." In IEEE Conference on Decision and Control. Miami Beach, FL, USA, 2018

DEVS is a popular formalism to model system behaviour using a discrete-event abstraction. The main advantages of DEVS are its rigourous and precise specification, as well as its support for modular, hierarchical construction of models. DEVS frequently serves as a simulation "assembly language" to which models in other formalisms are translated, either giving meaning to new (domain-specific) languages, or reproducing semantics of existing languages. Despite this rigourous definition of its syntax and semantics, initialization of DEVS models is left unspecified in both the Classic and Parallel DEVS formalism definition. In this paper, we extend the DEVS formalism by including an initial total state. Extensions to syntax as well as denotational (closure under coupling) and operational semantics (abstract simulator) are presented. The extension is applicable to both main variants of the DEVS formalism. Our extension is such that it adds to, but does not alter the original specification. All changes are illustrated by means of a traffic light example.

For a wide variety of problems, creating detailed continuous models of (continuous) physical systems is, at the very least, impractical. Hybrid models can abstract away short transient behaviour (thus introducing discontinuities) in order to simplify the study of such systems. For example, when modelling a bouncing ball, the bounce can be abstracted as a discontinuous change of the velocity, instead of resorting to the physics of the ball (de-)compression to keep the velocity signal continuous. Impulsive differential equations can be used to model and simulate hybrid systems such as the bouncing ball. In this approach, the force acted on the ball by the floor is abstracted as an infinitely large function in an infinitely small interval of time, that is, an impulse. Current simulators cannot handle such approximations well due to the limitations of machine precision. In this paper, we explore the simulation of impulsive differential equations, where impulses are first class citizens. We present two approaches for the simulation of impulses: symbolic and numerical. Our contribution is a theoretically founded description of the implementation of both approaches in a Causal Block Diagram modelling and simulation tool. Furthermore, we investigate the conditions for which one approach is better than the other.

It is essential to find new ways of enabling experts in different disciplines to collaborate more efficient in the development of ever more complex systems, under increasing market pressures. One possible solution for this challenge is to use a heterogeneous model-based approach where different teams can produce their conventional models and carry out their usual mono-disciplinary analysis, but in addition, the different models can be coupled for simulation (co-simulation), allowing the study of the global behavior of the system. Due to its potential, co-simulation is being studied in many different disciplines but with limited sharing of findings. Our aim with this work is to summarize, bridge, and enhance future research in this multidisciplinary area. We provide an overview of co-simulation approaches, research challenges, and research opportunities, together with a detailed taxonomy with different aspects of the state of the art of co-simulation and classification for the past five years. The main research needs identified are: finding generic approaches for modular, stable and accurate coupling of simulation units; and expressing the adaptations required to ensure that the coupling is correct., Comment: 157 pages, about 30 figures

DEVS is a popular formalism for modelling complex dynamic systems using a discrete-event abstraction. At this abstraction level, a timed sequence ofpertinent "events" input to a system (or internal, in the case of timeouts) cause instantaneous changes to the state of the system. Between events, the state does not change, resulting in a a piecewise constant state trajectory. Main advantages of DEVS are its rigorous formal definition, and its support for modular composition. This chapter introduces the Classic DEVS formalism in a bottom-up fashion, using a simple traffic light example. The syntax and operational semantics of Atomic (i.e., non-hierarchical) models are intruced first. The semantics of Coupled (hierarchical) models is then given by translation into Atomic DEVS models. As this formal "flattening" is not efficient, a modular abstract simulator which operates directly on the coupled model is also presented. This is the common basis for subsequent efficient implementations. We continue to actual applications of DEVS modelling and simulation, as seen in performance analysis for queueing systems. Finally, we present some of the shortcomings in the Classic DEVS formalism, and show solutions to them in the form of variants of the original formalism.

This chapter discusses the current state of the art, and emerging research challenges, for metamodelling. In the state-of-the-art review on metamodelling, we review approaches, abstractions, and tools for metamodelling, evaluate them with respect to their expressivity, investigate what role(s) metamodels may play at run-time and how semantics can be assigned to metamodels and the domain specific modeling languages they could define. In the emerging challenges section on metamodelling we highlight research issues regarding the management of complexity, consistency, and evolution of metamodels, and how the semantics of metamodels impacts each of these., Comment: 20 pages, 3 figures