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This paper addresses the quantification of the value of structural health monitoring (SHM) before its implementation for structural systems on the basis of its Value of Information (VoI). The value of SHM is calculated utilizing the Bayesian pre-posterior decision analysis modelling the structural life cycle performance, the integrity management and the structural risks. The relevance and precision of SHM information for the reduction of the structural system risks and the expected cost of the structural integrity management throughout the life cycle constitutes the value of SHM and is quantified with this framework. The approach is focused on fatigue deteriorating structural steel systems for which a continuous resistance deterioration formulation is introduced. In a case study, the value of SHM for load monitoring is calculated for a Daniels system subjected to fatigue deterioration. The influence of and the value of SHM in regard to the structural system risks and the integrity management is explicated and explained. The results are pointing to the importance of the consideration of the structural system risks for the quantification of the value of SHM.
For the vast majority of ellipsometric measurements, the application of planar substrates is mandatory and requires a proper sample alignment prior to the measurement. Here, the authors present a generalized approach of how to extract the isotropic ellipsometric sample parameters from an imaging Mueller-matrix measurement even if the sample is significantly misaligned. They validate the method by layer-thickness calculations based on imaging Mueller-matrix measurements of flat crystalline silicon samples that were misaligned on purpose. Furthermore, they also exploit this method’s capabilities to perform spatially resolved layer-thickness measurements of a single-layer indium-tin-oxide coating on a fused-silica microlens without the need of realignment or repositioning of the sample during the measurement.
The authors describe and interpret curvature-related changes to the ellipsometric readout. As model system for a concave curvature, a set of three spherical microscopic indents in silicon (100) of different sizes was prepared by instrumented indentation testing using a spherical indenter. For reference, these samples were characterized by AFM to reveal the topography of each structure. The concavelike indents were analyzed by Mueller-Matrix imaging ellipsometry to extract lateral intensity images of 12 elements of the Mueller-Matrix. As a result of the detailed analysis of the image elements m22, m23, and m14, it was possible to correlate intensity changes and symmetry properties to depolarization and cross polarization induced by the edge threshold and the curved surface of the indent.
Reliability analysis of deteriorating structural systems requires the solution of time-variant reliability problems.
In the general case, both the capacity of and the loads on the structure vary with time. This analysis can be approached by approximation through a series of time-invariant reliability problems, which is a potentially effective strategy for cases where direct solutions of the time-variant reliability problem are challenging, e.g. for structural systems with many elements or arbitrary load processes. In this contribution, we thoroughly Review the formulation of the equivalent time-invariant reliability problems and extend this approximation to structures for which inspection and monitoring data is available. Thereafter, we present methods for efficiently evaluating the reliability over time. In particular, we propose the combination of sampling-based methods with a FORM (first-order reliability method) approximation of the series system reliability problem that arises in the computation of the lifetime reliability. The framework and algorithms are demonstrated on a set of numerical examples, which include the computation of the reliability conditional on inspection data.