High-performance simulations of wave propagation for structure analysis of concrete

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It is experimentally demonstrated that ultrasonic waves are sensitive to different loadings of Reinforced Concrete (RC). A tool for the corresponding analysis is the Coda wave Interferometry (CWI). However, concrete is a strongly heterogeneous and densely packed composite material. Due to the high density of scattering constituents and inclusions, ultrasonic wave propagation in this material consists of a complex mixture of multiple scattering, mode conversion and diffusive energy transport. For a better understanding of the effect of aggregates, porosity, and of crack distribution on elastic wave propagation in concrete and to optimize inverse techniques it is useful to simulate the wave propagation and scattering process explicitly in the time domain. For this purpose, we use the Rotated Staggered Grid (RSG) finite-difference technique for solving the wave equations for elastic, anisotropic, and/or viscoelastic media.The subproject BU of the research unit is subdivided into five Work Packages (WP). The first one concentrates on ultrasound simulations as a service for collaborating partners (especially with RUB1, BAM and TUM2). With this task we continue the close collaboration on this issue during the first phase of the research unit. In the second work package we will further develop digital twins by X-Ray Computed Tomographic (XRCT) images. With this tool we estimate the influence of different loads (moisture, temperature, and mechanical load) to the microstructure of concrete. Image segmentation based on material knowledge is a crucial step in this procedure. By the transformation of several Digital Rock Physics approaches from geophysics to concrete we can estimate the corresponding influence on effective properties of concrete. In work package four we use the results of WP 3 to estimate the corresponding influence on the Coda signal. With the help of an international partner, we also will apply further machine learning techniques to interpret the coda signal in synthetic as well as in real structures. The fourth work package aims to extend the Time Reverse Imaging (TRI) technique for localization and characterization of Acoustic Events to an Active-TRI which will use the Coda signals to localize and characterize damage zones. The goal of WP 5 is to apply the machine learning techniques to identify the different loads (WP 3) and the Active-TRI technique to locate damage zones (WP4) to the test sides suggested in the main proposal of the research unit (Gänstorbrücke and station Scheidplatz).In summary we will optimize CWI with the help of high-performance computer simulations and the application of geophysical inversion techniques. Qualitative and quantitative long-term assessment of RC will be further developed.