Proceedings in Applied Mathematics and Mechanics, 4 May 2017

Modeling and evaluation of cyber-physical systems in civil engineering

Dmitrii Legatiuk1,∗, Kosmas Dragos2,3, and Kay Smarsly3

1 Chair of Applied Mathematics, Bauhaus University Weimar, Germany2 DFG Research Training Group 1462, Bauhaus University Weimar, Germany3 Chair of Computing in Civil Engineering, Bauhaus University Weimar, Germany

A cyber-physical system (CPS) is a coupled system integrating computing, networking, and physical processes. Throughactuation, cyber-physical systems control the physical processes, usually with feedback loops, where the physical processesaffect computing and networking processes, and vice versa. In civil engineering, the most common fields of CPS applicationsare structural health monitoring (SHM) and structural control. A typical CPS task is the assessment of a structure based on (i)collected measurement data and (ii) a corresponding model. However, for an accurate and precise assessment of a structure,the CPS itself must be modeled and evaluated. In this paper, a conceptual modeling and evaluation approach is proposed,in which each part of a CPS is evaluated individually. In this study, the conceptual approach is presented for modeling andevaluation of CPS in civil engineering. The evaluation is based on an abstract approach allowing a discussion of a principle(i.e. general) model structure of a CPS, identifying critical issues to be studied in more detail in future research.

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1 Cyber-physical systems in civil engineering

Engineering applications are associated with physical processes, while computational models are usually developed to de-scribe the physical processes. Specifically in dynamic (time-variant) physical processes, the application requirements maydictate user intervention during the physical processes. To enable such user intervention, information needs to be exchangedbetween the physical processes and the computational models. Moreover, in several engineering applications user interven-tion is automated through physical components employed to control the physical processes through feedback loops, essentiallyextending the computational models to computational and networking processes that describe and interact with physical pro-cesses. In this context, utilizing the dual nature of cyber-physical systems (CPS), which integrate physical and computationalprocesses [1], has received considerable research attention in the fields of civil and structural engineering (structural test-ing) [2].

In civil and structural engineering, the trend towards cyber-physical systems predominantly concerns the field of structuralhealth monitoring (SHM) and structural control [3]. Cyber-physical systems in civil and structural engineering do not fall intothe category of conventional systems used for monitoring structures (e.g. centralized cable-based SHM systems). Rather, theadvent of wireless technologies and the gradually increasing adoption of wireless sensor networks for structural health moni-toring marks a transition phase from conventional SHM practice to cyber-physical approaches for SHM [4,5]. The distributednature of wireless SHM systems and the ability of wireless sensor nodes to perform monitoring tasks in a decentralized mannerhave enabled partially or fully automated decision making in wireless SHM systems. Moreover, in CPS approaches in civiland structural engineering, SHM systems are typically coupled with structural subsystems (actuators) aiming to control thebehavior of the monitored structure [6]. Examples of actuators in civil engineering systems are devices that modify structuralresponses, such as active (or semi-active) tuned mass dampers and magnetorheological dampers, or software components en-suring the robustness of the SHM system, such as fault diagnosis embedded algorithms [7]. Structural health monitoring andcontrol devices are usually applied in “irregular” structures that exhibit unconventional dynamic behavior under time-variantloads, such as skyscrapers and tensegrity structures [8].

2 Types of coupling in cyber-physical systems

The behavior of the components of cyber-physical systems in civil engineering, i.e. of the structural health monitoring andcontrol systems and of the monitored structure, is characterized by strong interactions and, therefore, by a high degree ofcoupling. As has already been highlighted, the adoption of cyber-physical systems in civil engineering is associated withunconventional structural systems (usually employed in structures of high significance, such as large financial centers); thus,ensuring the highest possible level of performance of such cyber-physical systems is of utmost importance to the structure’sstakeholders. In this direction, a methodology for assessing the quality of cyber-physical systems is necessary, accounting forthe quality of the individual components of cyber-physical systems as well as of the complex coupling conditions between thecomponents.

Fig. 1 indicates two principle types of coupling appearing in cyber-physical system modeling:

∗ Corresponding author: dmitrii.legatiuk@uni-weimar.de

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Fig. 1: Coupling in cyber-physical systems

• Coupling between cyber-physical subsystems (“inter-subsystem coupling”)

• Coupling among the components of each cyber-physical subsystems (“intra-subsystem coupling”)

For an overall quality assessment of cyber-physical systems, the coupling between cyber-physical subsystems must be as-sessed. However, existing modeling methodologies for cyber-physical system modeling do not address the issue of inter andintra-subsystem coupling clearly, and particularly, do not assess these couplings [9]. Thus, practical assessment of cyber-physical systems entails developing of a conceptual modeling methodology with sufficient expressive power to describe suchcouplings. The abstract modeling methodology based on category theory, introduced in [10], provides a sufficient level ofabstraction to describe the coupling between cyber-physical subsystems. However, this modeling methodology has been de-veloped for mathematical models (physics-based models), and its application to cyber-physical system modeling requires afurther generalization, which is the objective of future research.

Acknowledgements This research is partially supported by the German Research Foundation (DFG) through grant SM 281/7-1 and theResearch Training Group “Evaluation of Coupled Numerical Partial Models in Structural Engineering (GRK 1462)”. The support offeredby DFG is gratefully acknowledged. Any opinions, findings, conclusions, or recommendations expressed in this paper are solely those ofthe authors and do not necessarily reflect the views of DFG or any other organizations and collaborators.

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