Nachrichten - Rheinland-Pfälzische Technische Universität Kaiserslautern-Landau

Gulliver – A new kind of industrial CT

Thu, 06 Mar 2025 08:42:32 +0100

We are pleased to present our new paper on the Gulliver large scale CT system at ��ֱ�� in Kaiserslautern. In this publication we present some of the measurement results obtained during the current completion of the system. The CT measurements are intended to provide new insights into concrete structures up to 6 m long and rectangular in cross-section with a width and height of 0.3 m at the point of load application. It also outlines future measurement campaigns planned with the system and explains how to access the innovative testing system for your own research activities.

Numerical model validation with computed tomography

Tue, 17 Sep 2024 14:17:29 +0200

In order to make accurate predictions of the structural behaviour of non-metallic reinforced concrete elements, one of the key problems in the development of this type of new material system is the capacity of modelling the load transfer mechanisms between the concrete matrix and the reinforcement elements. To predict the load-deflection response up to ultimate limit state conditions, a wide range of numerical simulation approaches, with capability of modelling the bond behaviour between the different materials has been proposed over the years and compared to experimental results. This research work presents new possibilities for comparing numerical finite elements models with laboratory data generated by computed tomography, namely in the context of three-point bending tests performed on carbon-reinforced concrete specimens. The aim is to present the potential of in situ computed tomography for validation of numerical simulations. Examples of computed tomography generated quantitative results and data visualisation are shown, which focus on generated displacement fields and crack patterns.

Damage analysis in structural engineering

Tue, 17 Sep 2024 14:02:53 +0200

The renovation of existing buildings and infrastructures is becoming in the last years increasingly important. This results in an increasingly greater need to understand the real condition of building components and to objectively measure their level of damage with both qualitative and quantitative indicators. There are many known methods in the field of structural health monitoring and damage control. Among them, non-destructive testing (NDT) methods assume particular importance as they enable the evaluation of structural integrity without compromising functionality. This article explores the potential of non-destructive testing using computed tomography (CT) in the context of damage analysis for concrete structures.

Application of the Computed Tomography in Structural Engineering

Fri, 09 Jun 2023 07:46:00 +0200

Imaging techniques such as computed tomography (CT) enable interior screening of the object - not only for medical diagnosis in humans but also for x-ray materials. Currently, there are many applications in the field of structural engineering, which can be very informative for research and possibly even represent a milestone in basic research in material science. Special attention is given to CT recordings of damage in concrete specimens. Here it is necessary to mention damages such as cracks or discontinuities like pores. However, the maximum sample size is limited, and the CT can only examine relatively small samples, there is planned a test procedure with the larger specimens. To be able to examine reinforced concrete samples non-destructively, a worldwide unique CT system is being built on the campus of the Technical University of Kaiserslautern. This system will enable the CT scan of specimens the size of six meters. In addition, the components can be stressed and even destroyed at the same time during the X-ray exposure. The three-dimensional recordings during the static or dynamic loads provide information about damage processes inside the specimen and the formation of cracks and structural changes that occur in the process. This article illustrates the application possibilities of computed tomographic image recordings in structural engineering on different materials. The experimental investigations are discussed with different possible research questions. Finally, the numerous examples are supplemented with their own experimental results.

3d imaging and analysis of cracks in loaded concrete samples

Thu, 02 Mar 2023 07:44:00 +0100

Concrete plays a central role as the standard building material in civil engineering. Experimental characterization of the concrete microstructure and a description of failure mechanisms are important to understand the concrete’s mechanical properties. Computed tomography is a powerful source of information as it yields 3d images of concrete specimens. However, complete visual inspection is often infeasible due to very large image sizes. Hence, automatic methods for crack detection and segmentation are needed. A region-growing algorithm and a 3d U-Net showed promising results in a previous study. Cracks in normal concrete and high-performance concrete that were initiated via tensile tests were investigated. Here, the methods are validated on a more diverse set of concrete types and crack characteristics. Adequate adaptions of the methods are necessary to deal with the complex crack structures. The segmentation results are assessed qualitatively and compared to those of a template matching algorithm which is well-established in industry.

Towards automatic crack segmentation in 3d concrete images

Fri, 11 Feb 2022 13:03:00 +0100

Concrete is one of the most commonly used construction materials. A deeper insight into its mechanical properties, in particular cracking behaviour, can be gained from stress tests. Computed tomography captures the microstructure of building materials, including crack initiation and propagation in a fully three-dimensional manner. However, the complex microstructure of concrete renders crack segmentation a very challenging task. Both, the validation of segmentation methods and the training of machine learning approaches, are hindered by the lack of reliable ground truth segmentations for real data sets. To overcome this problem, a novel procedure for generating pairs of semi-synthetic images and ground truth was introduced by the authors in a previous study. Using this semi-synthetic data, Hessian-based percolation and 3d U-net were identified as the most promising of eight approaches for crack segmentation. Here, we discuss adaptions of the methods that allow for a handling of additional features observed in real computed tomography data of concrete, in particular local variations in crack thickness.