7.2 Ingenieurbau
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- Damage localization (3)
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- Structural health monitoring (3)
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Organisationseinheit der BAM
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- 8.1 Sensorik, mess- und prüftechnische Verfahren (1)
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At the Bundesanstalt für Materialforschung und -prüfung (BAM) full scale specimens for nuclear transport and storage containers (casks) are tested for their structural integrity in a series of drop tests on the Test Site Technical Safety in Horstwalde, 50 km south of Berlin. These drop tests cause a major stress not only on the casks, but also on the steel tower structure of the test facility, itself. The load pattern makes the structure very interesting for detailed investigation. The focus of the monitoring lies on the bolted joints of the flange connections that are a typical connection for cylindrical elements if welding is technical or economical unfavorable. The definition of the monitoring takes was done by investigating the existing documents and inspection results accompanied by building an initial digital representation of the structure, consisting of two finite element (FE) models and a geometrical 3D point cloud representation. As a first step the structures behavior during static and dynamic loading was analyzed using measurement data and an updated numerical FE Model. The idea behind is to use models for a digital planning and operation/evaluation of the structural health monitoring. A static FE simulation and a dynamic FE simulation are generated, to investigate how the structure behaves under the load conditions.
Fault detection for linear parameter varying systems under changes in the process noise covariance
(2020)
Detecting changes in the eigenstructure of linear systems is a comprehensively investigated subject. In particular, change detection methods based on hypothesis testing using Gaussian residuals have been developed previously. In such residuals, a reference model is confronted to data from the current system. In this paper, linear output-only systems depending on a varying external physical parameter are considered. These systems are driven by process noise, whose covariance may also vary between measurements. To deal with the varying parameter, an interpolation approach is pursued, where a limited number of reference models -- each estimated from data measured in a reference state -- are interpolated to approximate an adequate reference model for the current parameter. The problem becomes more complex when the different points of interpolation correspond to different noise conditions. Then conflicts may arise between the detection of changes in the eigenstructure due to a fault and the detection of changes due to different noise conditions. For this case, a new change detection approach is developed based on the interpolation of the eigenstructure at the reference points. The resulting approach is capable of change detection when both the external physical parameter and the process noise conditions are varying. This approach is validated on a numerical simulation of a mechanical system.
Reinforced concrete (RC) is used as structural material in most diverse civil engineering applications. For the variability of its physical properties it is still an engineering challenge to meet all necessary requirements for the prediction of dynamic effects under impact loading. In this paper, investigations are shown within the scope of quantifying and evaluating the damage caused by an impact. The experimental investigations are performed in the field of low- and medium-velocity impact. The chosen flat nose shape results in small penetrations on the top side and scabbing on the bottom side. The plate is scanned with an adapted planar tomographic examination after the impact, and the damage is analysed, afterwards. Cracks and spalling are made visible with a reconstruction. The numerical model validated on the tomographic results justifies the application for further predictions of the damage description.
At present, to produce renewable energy offshore wind farms play an important role. The available space combined with the more valuable wind conditions make offshore locations very attractive for wind powered energy production. In Europe a significant number of offshore wind farms already exist, especially in the North and Baltic Sea. In future this trend will continue, and further offshore wind farms will be built. The majority of offshore wind turbines are mounted on steel foundation structures. Due to the high-cyclic loading by wind and waves fatigue stress plays a substantial role regarding structural safety.
Besides the consideration of fatigue within the design process, to monitor existing steel structures for potential fatigue cracks during their life time is a major topic and a challenge.
For the structures of the offshore wind turbines are large and partially under water effective reliable methods for the detection of fatigue cracks are required.
This contribution presents investigations on different crack detection methods applied at high-cycle fatigue tests on small-scale welded steel samples as well as on large-scale welded steel components. The tests were conducted at the BAM laboratories. For crack detection mainly three different methods were used and compared. The first method regards to the measurement of strain by conventionally strain gauges. Secondly, the crack luminescence was used as a new and effective optical method for surface monitoring. And finally, crack detection by pressure differentials of the inner and outer section of tubular steel elements was investigated. A comparison study will emphasize the advantages and disadvantages of the different methods and show which of the described methods is potentially more suitable for an application on real offshore wind structures.
The subject of damage localization is an important issue for Structural Health Monitoring (SHM) particularly in mechanical or civil structures under ambient excitation. In this paper, the statistical subspacebased damage localization method has been applied on a benchmark application, namely a 1/200 scale model of the Saint-Nazaire Bridge, which is a cable-stayed bridge located on the Loire River near the river’s mouth. The employed damage localization method combines data-driven features with physical parameter information from a finite element model in statistical tests, avoiding typical ill-conditioning problems of FE model updating. Damage is introduced in the mockup for cable failures on some of the 72 cables. The purpose of the experiment is to assess the capability of damage assessment methods to find a cable failure.
The Stochastic Dynamic Damage Locating Vector (SDDLV) approach is a vibration-based damage localization method based on both a finite element model of a structure and modal parameters estimated from output-only measurements in the damage and reference states. A statistical version of the Approach takes into account the inherent uncertainty due to noisy measurement data. In this paper, the effect of temperature fluctuations on the performance of the method is analyzed in a model-based approach using a finite element model with temperature dependent parameters. Robust damage localization is carried out by rejecting the temperature influence on the identified modal parameters in the damaged state. The algorithm is illustrated on a simulated structure.
The subject of damage localization is an important issue for Structural Health Monitoring (SHM) particularly in mechanical or civil structures under ambient excitation. In this paper, the statistical subspacebased damage localization method has been applied on a benchmark application, namely a 1/200 scale model of the Saint-Nazaire Bridge, which is a cable-stayed bridge located on the Loire River near the river’s mouth. The employed damage localization method combines data-driven features with physical parameter information from a finite element model in statistical tests, avoiding typical ill-conditioning problems of FE model updating. Damage is introduced in the mockup for cable failures on some of the 72 cables. The purpose of the experiment is to assess the capability of damage assessment methods to find a cable failure.
The Stochastic Dynamic Damage Locating Vector (SDDLV) approach is a vibration-based damage localization method based on both a finite element model of a structure and modal parameters estimated
from output-only measurements in the damage and reference states. A statistical version of the Approach takes into account the inherent uncertainty due to noisy measurement data. In this paper, the effect of temperature fluctuations on the performance of the method is analyzed in a model-based approach using a finite element model with temperature dependent parameters. Robust damage localization is carried out by rejecting the temperature influence on the identified modal parameters in the damaged state. The algorithm is illustrated on a simulated structure.
Within the presented research project, experimental and numerical investigations were performed to develop a thin-shelled, modular, mobile element system made of a micro-reinforced ultra-high-performance ductile concrete (DUCON®). Material parameters were experimentally determined to adapt the material model within the numerical analysis applying the Drucker-Prager relationship. Afterwards, for validation of the numerical models, quasi-static and high-velocity impact tests were performed on plate-like structures. Finally, a suitable geometry of transportable barrier elements will be designed, which provides a maximum of resistance against impact by a minimum of weight and a maximum of mobility.