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    BIM-based information modeling for semantic description of intelligent structural health monitoring systems
    Intelligent structural health monitoring systems, which play a crucial role in digitalization processes within the construction industry, are composed of sensor nodes possessing so called "on-chip intelligence". Structural health monitoring (SHM) based on sensor nodes with on-chip intelligence, referred to as "intelligent SHM", advances automated, pro-active real-time analyses of measured data directly on board the sensor nodes. Although intelligent SHM is continuously gaining importance, there are no standards available to regulate design and implementation of intelligent SHM systems. Furthermore, there is a lack of well-defined formalisms supporting digital representations of life-cycle information about the inherent logics of intelligent sensor nodes, about the SHM strategies implemented, about the overall SHM system and about the system dynamics ("monitoring-related information"). The proposed research project aims at developing a semantic model to digitally represent monitoring-related information based on a consistent formalism. In order to ensure correct semantics on a sound mathematical basis, the semantic model builds upon an ontology-driven conceptual approach. A major research question addresses the representation of system dynamics, which is to be solved through ontology temporalization using temporal logics as well as temporal-logical model structures based on modal logics. It is proposed to integrate the semantic model into the methods of building information modeling (BIM). Therefore, a "parametric" BIM concept (as opposed to "parameterized" BIM concepts) for intelligent SHM systems will be proposed. For validation, the concept will be materialized in a logical schema that builds upon open BIM standards. A main benefit of this project is a novel methodology for coherent integration of monitoring-related information (even in the planning phase of a building) into standardized building information models widely used in civil engineering. All monitoring-related information will be digitally available and can be updated throughout the life time of buildings. Finally, holistic analyses of structural, environmental, and operational data will be possible in a new context, which may serve as a reliable basis for decision making with respect to operation, maintenance and repair, facilitating infrastructure sustainability and resilience.
      484
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    Metaization concept for structural health monitoring
    With the advances in information and communication technologies and the pervasive informatization in civil engineering (Industry 4.0, Internet of Things, Digital Engineering), structural health monitoring based on decentralized sensor networks is increasingly drawing research attention. For automated structural health monitoring, interacting (wireless or tethered) sensor nodes, equipped with embedded intelligence, are spatially distributed in civil infrastructure systems. Referred to as "smart structures" or "intelligent infrastructure", the sensor nodes are capable of autonomously collecting sensor data and, using embedded algorithms, of processing and analyzing sensor data on board in real time. Recent research projects have demonstrated that not only algorithms can be embedded into the sensor nodes; using appropriate decomposition strategies, also models can be embedded into the sensor nodes, such as hybrid, multi-coupled numerical models, which digitally represent the monitored structure in a fully decentralized manner. Thus, it can be expected that next-generation assessment of civil infrastructure is no longer either monitoring-based or model-based. Instead, a new multi-paradigm approach evolves, merging monitoring-based and model-based structural assessment. To precisely evaluate the quality of the structural assessment, which is not sufficiently possible using current state-of-the-art methods, the proposed research project aims at developing a metaization concept, resulting in a holistic metamodel architecture. The technological nucleus of the metamodel architecture - the metamodel - is a metalinguistic instrument to be used for holistic modeling and digital representation of structural health monitoring (SHM) systems, including all system components and relationships (also: "couplings", "relations" or, in a mathematical sense, "transfer functions") between the system components. As a result, it is expected that the well-defined formalism provided by the metamodel architecture enables a lifecycle-oriented documentation and a continuous updating of all monitoring-related information. In consequence, the monitoring quality, and thus the quality of structural assessment, can substantially be enhanced. The central question related to the principle of parsimony within SHM, commonly known as "Ockham's razors", is to be is to be answered: How complex and resource-consuming must the models be and how simple and resource-efficient can the models be in order to meet the requirements imposed on the quality of structural assessment? To validate the proposed metaization concept, different model classes relevant to typical SHM problems will be considered in a multi-stage validation strategy, using both laboratory tests as well as sensor data taken from civil infrastructure systems in operation.
      75
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    Resilient infrastructure based on cognitive buildings
    Climate change is evident. There is an urgent need to ensure resilience of civil infrastructure against impacts of a changing climate. Making civil infrastructure resilient requires precise insights into the infrastructure condition, taking into account structural and environmental information and, increasingly, socio-economic phenomena. Modern civil infrastructure is able to both analyze its condition and to adapt to the environment, e.g. through (semi-)active dampers or sensor-based actuators. However, although frequently termed "smart", current infrastructure is unable to learn or to anticipate from structural and environmental factors, or to utilize the Internet of Things (IoT) for integrating socio-economic phenomena. This project aims to take advantage of the emerging paradigm of "cognitive buildings" to develop a novel scientific basis towards resilient infrastructure. Cognitive buildings are able to sense environmental conditions, to learn from external (or user-related) factors, and to integrate IoT devices to optimize performance. However, cognitive buildings, typically focusing on reducing energy consumption and carbon footprint, lack the ability of seamlessly integrating structural information relevant to resilience. The proposed project therefore aims to extend the cognitive buildings paradigm towards infrastructure resilience. As a point of departure, structural health monitoring and structural control (SHM/SC) strategies, relevant to resilient infrastructure, will be considered. For several years, SHM/SC practice has been mainly relying on data-driven modeling for extracting information on the structural condition. However informative, data-driven modeling lacks physical background and fails to provide the information necessary for SHM/SC to produce reliable predictions on future structural behavior. As a consequence, the proposed extension to the cognitive buildings paradigm will involve integrating decentralized, physics-based modeling into wireless SHM/SC. This research is proposed out of a DFG-funded German-Greek joint research project conducted to initiate an international collaboration. The expected outcome of the proposed research is a methodology for efficiently embedding decentralized physics-based models into wireless SHM/SC systems to advance infrastructure resilience. It is further expected that this project will contribute to enhancing the performance of wireless SHM/SC systems and to integrating infrastructure systems into the concepts of "Industry 4.0", "Smart City", and the "Internet of Everything". This research project marks a shift towards an entirely new paradigm in embedded computing for wireless SHM/SC in accordance with ongoing developments facilitating resilient infrastructure in the light of climate change.
      86
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    Semi-probabilistic, sensor-based design concepts for intelligent structural systems
    Engineering structures are increasingly equipped with structural health monitoring systems. From the sensor data obtained, valuable sensor-based information is available during the whole life-cycle of a structure. Continuously updated in real time, sensor-based information can be communicated online and coupled with information from further sources to derive knowledge about the structure (Industry 4.0, Semantic Web, Internet of Things, "Intelligent Bridge"). Both, that is engineering structure and intelligent structural health monitoring system, are considered as one unit, referred to as "intelligent structural system". However, current design standards have not kept pace with the rapid developments in intelligent sensing technologies: Sensor-based information provided by structural health monitoring systems is not considered in current structural design concepts. For example, Eurocodes and corresponding partial safety factor concepts are adapted from the assumption that no sensor-based information is available throughout the whole life-cycle of a structure; rather, a hypothetical, unknown structural state is taken as a basis for the design. This state has to reflect different influences and associated uncertainties the structure is exposed to during its life time. This assumption may result in oversizing and additional costs as well as in rehabilitation and repair works that cannot be planned optimally. The goal of this research project is twofold: First, the implications of integrating sensor-based information into structural design concepts are to be investigated and design concepts particularly for intelligent structural systems are to be proposed. Second, based on the first goal, a general development strategy for structural health monitoring systems for intelligent structural systems is to be developed. To achieve these goals, the proposed research addresses the following key issues. Upon analyzing current design concepts, a semi-probabilistic safety concept will be developed for intelligent structural systems, taking into account the availability of additional sensor-based information on the structural state. A major part of this work is devoted to investigating to which extent loads and resistances (as well as their correlation) can be captured by sensors and how they should formally be represented. Clearly, when incorporating additional sensor-based information into structural design concepts, uncertainties with respect to the actual state of a structure can significantly be reduced. However, new uncertainties arise, which are caused by the hardware and software components of the structural health monitoring system installed on the intelligent structural systems (e.g. sensor failures, miscalibrations, and interrupted data lines). These additional uncertainties will be addressed and integrated into the safety concept to be proposed as an outcome of this research project.
      279