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Numerous case histories show evidence that geophysical methods are valuable tools for levee inspection and monitoring. National and international standards and recommendations recommend the use of geophysics for a variety of tasks. However, in some cases reported have been flaws missed or false indications given. Due to the larger variety in type, size and construction of levees and the even larger variety of potential tasks and targets the success of geophysical surveys still pretty much depends on the available budget and the experience and capabilities of the clients and contractors involved. It is strongly recommended that all relevant parties agree on the detailed objectives of the survey, required accuracy and reliability of the results and any follow up measures. For the most common tasks more research and practical work using techniques as POD (probability of detection), which are well established in other fields of non-destructive testing, would be of benefit.
A novel method for risk-based optimization of inspection and repair strategies for deteriorating structural systems has recently been proposed. The method defines heuristics at the system level to reduce the number of possible strategies. For each defined strategy, it computes the updated system failure probability conditional on simulated inspection and repair histories, and evaluates the associated costs and risk. The expected total service life costs and risk for a strategy are finally determined using Monte Carlo simulation. The optimal strategy minimizes the expected total service life costs and risk. We intend to adopt this approach to optimize inspection, monitoring and repair activities for offshore wind park support structures. As a first step, we simulate – in analogy to an offshore wind park – the service life performance of an inspected group of jacket-type frames. The performance is quantified in terms of the group’s system failure probability conditional on simulated inspection and repair histories. The underlying system model accounts for the structural redundancy of the frames and the interdependence among their failure events due to similar loading conditions. The model also captures stochastic dependence among the deterioration states of the frames. As part of the simulation process the a-priori unknown outcome of any planned inspection is generated conditional on the outcome of all previous inspections.
Practical applications of recent BAM-research results of NDT and monitoring in civil engineering
(2018)
Nondestructive testing and monitoring was of mayor interest in BAM-research related to the survey of civil engineering structures during the last two decades. Three case studies about research projects carried out at BAM were presented. All three projects focussed on the survey of parameters and safety related tasks in bridge engineering and inspection. First, the monitoring of the Berlin main station was presented with focus on the sensors developed specifically for this project. The second case study presented and application of guided ultrasonic waves to CFRP-strengthened bridges. The method was sucsessully applied to two of four different strengthening measures carried out min. 10 years ago. The last project presented the feasibility study of a network consisting of simple Bluetooth modules to survey changes in the moisture content in sand and massive concrete.
The presentation starts with some key figures about BAM. Then it introduces BAM's competence centre H2Safety@BAM and shows aspects of special competence of the centre. It closes with information about the engagement of BAM in European research projects on hydrogen and a reference to our bilingual paper about our hydrogen strategy.
In this presentation, a framework for integrating vibration-based structural health monitoring data into the optimization of inspection and maintenance of deteriorating structural systems is presented. The framework is demonstrated in an illustrative example considering a steel frame subject to fatigue.
The reliability of deteriorating structures at time t is quantified by the probability that failure occurs within the period leading up to time t. This probability is often referred to as cumulative failure probability and is equal to the cumulative distribution function of the time to failure. In structural reliability, an estimate of the cumulative failure probability is obtained based on probabilistic engineering models of the deterioration processes and structural performance. Information on the condition and the loading contained in inspection and monitoring data can be included in the probability estimate through Bayesian updating. Conditioning the probability of failure on the inspection or monitoring outcomes available at time t (e.g. detections or no detection of damages) can lead to a reduction in that probability.
Such a drop in the cumulative failure probability might seem counterintuitive since the cumulative failure probability is a non-decreasing function of time. In this paper, we illustrate—with the help of a numerical example—that such a drop is possible because the cumulative probability before and after the updating is not based on the same information, hence not on the same probabilistic model.
Thermographic super-resolution techniques allow the resolution of defects/inhomogeneities beyond the classical limit, which is governed by the diffusion properties of thermal wave propagation. Photothermal super-resolution is based on a combination of an experimental scanning strategy and a numerical optimization which has been proven to be superior to standard thermographic methods in the case of 1D linear defects. In this contribution, we report on the extension of this approach towards a full frame 2D photothermal super-resolution technique. The experimental approach is based on a repeated spatially structured heating using high power lasers. In a second post-processing step, several measurements are coherently combined using mathematical optimization and taking advantage of the (joint) sparsity of the defects in the sample. In our work we extend the possibilities of the method to efficiently detect and resolve defect cross sections with a fully 2D-structured blind illumination.