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Many engineering structures are made of composite materials or metal foam. To simulate the deformational behaviour of these structures often requires a high number of discretisation elements. This in turn yields a very large system of linear equations that are extremely time and memory consuming or practically impossible to solve. It is therefore desirable to find an approach to overcome this obstacle.
One major ambition in Structural Health Monitoring (SHM) is to develop the ability to detect, identify and localize damage as well as to predict the lifespan of civil structures (Worden et al. 2007). This would allow well-informed decision on whether to repair or to demolish these structures. The word monitoring in SHM brings up several frequently ignored questions: What type of sensors and accuracies are needed to monitor a given structure? Where are the optimal sensor placements? How many sensors are necessary? How to analyse spatially distributed hybrid measurements? Or, in short: What is the sensor configuration best suited for structural health monitoring? If these questions are not explicitly addressed, the usefulness of the measurement data for an evaluation is left to coincidence.
Die Verwendung offener Standards bietet eine Vielzahl von Möglichkeiten, gerade im Bereich des Datenaustausches, Datenlagerung, aber auch der Interoperabilität. GML und CityGML sind hervorragende Beispiele für die Beschreibung von Realweltobjekten mittels eines offenen Standards wohingegen SensorML dazu dient, Messungen, Sensoren und Messplattformen zu beschreiben. Die Verwendung solcher Standards eröffnet dem Nutzer nicht nur die Möglichkeiten der Verwendung einer gemeinsamen standardisierten Sprache, sondern auch die Nutzung von offenen Servicestandards, wie Web Feature Service (WFS), Web Map Service (WMS) oder von Sensor Observation Services (SOS).
Die Kombination von Geodaten- und Sensorstandards in einer Dienste- und Servicearchitektur geht über bisherige am Markt existierende Lösungen hinaus und schafft eine neuartige Plattform für die Bauwerksüberwachung, die weit mehr als ein simples Datenhaltungsmodell darstellt. Die in diesem Beitrag vorgestellte Plattform ermöglicht eine direkte Integration von Sensordaten sowie deren Bereitstellung durch eine offene Standardsprache. Dabei sind alle Zwischenschritte jederzeit über eine offene Diensteschnittstelle adressierbar und können so verschiedenen Akteuren zur Verfügung gestellt werden. Das große Potential und der Mehrwert eines derartigen Informationssystems liegt vor allem in der permanenten Verfüg-barkeit von Mess- und Objektdaten und einer damit verbundenen integrierten Analyse der Sensormessdaten in Kombination mit einem Finite-Elemente-Modell (FEM), basierend auf den Objektdaten. Die automatische Ableitung eines FE-Modells aus dem 3D-Bauwerks-modell, die Visualisierung der FEM-Simulationsergebnisse anhand des Bauwerksmodells, die Bereitstellung von Messrohdaten und Sensorinformationen zu jedem Messzeitpunkt machen die Plattform zu einem universell einsetzbaren Werkzeug im Bereich der Bauwerksüberwachung. In diesem Beitrag werden die einzelnen Bausteine, die verwendeten Standards und die Interaktion der einzelnen Komponenten zu einem Gesamtsystem vorgestellt.
The integration of finite element method (FEM) into the least-squares adjustment presented in [1] is further extended for a joint evaluation of an elastostatic model and displacement field measurement. For linear solids which obey the HOOKE's law, the material parameters determination from measurements is being examined. In many literature, see for example [2], parameters are iteratively tuned until the computed FEM results are in accordance with the measurements. In contrast to these debatable approaches, we follow a rigorous and direct method. The “classical” FEM procedure starts with known material constants and ends up with computed fields such as dis-placement or temperature field. We present a method to invert the FEM procedure using the most general least-squares adjustment – the GAUSS-HELMERT Model (GHM). From given fields, the material parameters are directly calculated.
The integration of finite element method (FEM) into the least-squares adjustment presented in is further extended for a joint evaluation of an elastostatic model and displacement field measurement. For linear solids which obey the Hooke's law, the material parameters determination from measurements is being examined.
The present work is intended to make a contribution to the monitoring of civil engineering structures. The detection of damage to structures is based on the evaluation of spatially and temporally distributed hybrid measurements. The acquired data can be evaluated purely geometrically or physically. It is preferable to do the latter, since the cause of damage can be determined by means of geometrical-physical laws in order to be able to intervene in time and ensure the further use of the structures. For this reason, the continuum mechanical field equations in conjunction with the finite element method and hybrid measurements are combined into a single evaluation method by the adjustment calculation. This results in two challenges.
The first task deals with the relationship between the finite element method and the method of least squares. The finite element method solves certain problem classes, which are described by a system of elliptical partial differential equations. Whereas the method of least squares solves another class of problems, which is formulated as an overdetermined system of equations. The striking similarity between both methods is known since many decades. However, it remains unresolved why this resemblance exists. The contribution is to clarify this by examining the variational calculus, especially with regard to its methodological procedure. Although the well-known Gauss-Markov model within the method of least squares and the finite element method solve inherently different problem classes, it is shown that both methods can be derived by following the same methodological steps of the variational calculus. From a methodical viewpoint, this implies that both methods are not only similar, but actually the same. In addition, it is pointed out where a possible cross-connection to other methods exists.
The second task introduces a Measurement- and Model-based Structural Analysis (MeMoS) by integrating the finite element method into the adjustment calculation. It is shown in numerical examinations how this integrated analysis can be used for parameter identification of simple as well as arbitrarily shaped structural components. Based on this, it is examined with which observation types, with which precision and at which location of the structure these measurements must be carried out in order to determine the material parameters as precisely as possible. This serves to determine an optimal and economic measurement set-up. With this integrated analysis, a substitute model of a geometrically complex structure can also be determined. The issue of the detection and localisation of damage within a structure is studied by means of this structural analysis. The Measurement and Model-based Structural Analysis is validated using two different test setups, an aluminum model bridge and a bending beam.