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The reinforcement of concrete with polymer fibers provides resistance to crack formation. The orientation distribution of these fibers has a significant influence on the mechanical behavior of the material. To optimize material performance, micromechanical models that are capable of making accurate predictions of the mechanical behavior of composite materials are needed. These models must be calibrated using experimental results from microstructural characterization. For the fiber orientation distribution analysis in the present study, computed tomography (CT) data were used to evaluate the properties of a fiber-reinforced cement mortar. The results have indicated that the fibers in this material have highly anisotropic orientation characteristics and that there is a clear tendency for the polymer fibers to agglomerate during mixing and casting. The incorporation of this experimental data into micromechanical models will increase the accuracy of those models for material simulation and optimization.
Industrial radiography or Radiographic Testing (RT) is a method of non-destructive testing where many types of manufactured components can be examined to verify the internal structure and integrity of the specimen. The computer program aRTist can generate synthetic radiographs from a virtual RT test set-up. In the field of industrial radiology simulation is used, e.g. to optimize techniques for complex applications, to support the preparation of written procedures, and for education purposes.
The simulator aRTist combines analytical and Monte Carlo methods to efficiently model the radiation transport. The program comes with a graphical user interface written in Tcl/Tk. In combination of Tcl/Tk and the 3D capabilities of the visualization toolkit (VTK) a practical and convenient simulator has been realized. This will be illustrated by discussing application scenarios of classical radiography, X-ray computer tomography, and X-ray backscatter imaging. Additionally, some insight to the software implementation of the simulator will be given.
Damage Analysis in Metal Matrix Composites by means of Synchrotron Radiation Computed Tomography
(2017)
The damage evolution after compression tests of two types of MMC, consisting of eutectic AlSi12CuMgNi alloy and reinforced with 15vol% of Al2O3 fibers and with 7vol% of Al2O3 fibers+15vol% of SiC particles was studied by synchrotron CT. Internal damage at different pre-strain conditions in eutectic Si, intermetallic phases and Al2O3 fibers was observed, as well as debonding of SiC particles.
The combination of tomographic, microstructural data with other experimental techniques and with modeling is paramount, if we want to extract the maximum amount of information on material and component properties. In particular, quantitative image analysis, statistical approaches, direct discretization of tomographic reconstructions represent concrete possibilities to extend the power of the tomographic 3D representation to insights into the material and component performance. This logic thread equally holds for industrial and academic research, and valorizes expensive experiments such as those carried out at synchrotron sources, which cannot be daily repeated.
I will show a few examples of possible use of X-ray tomographic data for quantitative assessment of damage evolution and microstructural properties, as well as for non-destructive testing. Examples of micro-structured inhomogeneous materials will be given, such as Composites, Ceramics, Concrete, and Additively manufactured parts. I will also show how X-ray refraction computed tomography (CT) can be highly complementary to classic absorption CT, being sensitive to internal interfaces.
Additionally, I will present a new technique in our portfolio, Neutron Diffraction, which is extremely well suited to the study of internal stresses, both residual and under external load.
A special 3D tomographic algorithm was developed for mobile inspection of large objects. The method is based on a coplanar movement of an X-ray tube parallel to the surface of a digital detector array (DDA). Two different designs were developed and applied for 3D testing of welded pipes in nuclear power plants and large aircraft components made from carbon fiber reinforced polymers (CFRP). The reconstructed tomo-graphic images permit the detection, characterization and measurement of the dimensions of flaws with en-hanced sensitivity compared to conventional radiography and UT.
The evolution of the microstructure of multiphase metal matrix composite AlSi12CuNiMg with 7% vol. Al2O3 + 15% vol. SiC (short fibers and whiskers, respectively) was studied by synchrotron computed tomography. It comprehended as cast and after heat treatment conditions, as well as damage evaluation after ex-situ compression tests at room temperature. The volume fraction of different phases, their distribution, their orientation, and damage events are studied.
The influence on mechanical properties of the orientation of the planar random short fibres Al2O3 towards loading was investigated. Phase-specific load partition analysis for samples with fiber plane parallel and orthogonal to load, respectively, was performed by means of neutron diffraction (ND) during in-situ compression tests at room temperature. ND results proved that damage occurrence in the fillers strongly depends on the preferential orientation of those, playing a crucial role in the failure of the sample. The computed tomography observations confirm the damage observations from curves of load partition analysis of each phase.
Defect recognition in CFRP components using various NDT methods within a smart manufacturing process
(2017)
The manufacturing process of carbon fiber reinforced polymer (CFRP) components is playing a more and more significant role when looking at the increasing amount of CFRPs used in industries today. The monitoring of the manufacturing process and hence the reliability of the manufactured products, is one of the major challenges we need to face in the near future. Common defects which arise during manufacturing are e.g. porosity and voids which may lead to delaminations during operation and under load. To find those defects in an early stage of the manufacturing process is of huge importance for the safety and reliability of the finished products, as well as of significant impact from an economical point of view. In this study we present various NDT methods which are applied to similar CFRP laminate samples in order to detect and characterize defective volume. Besides ultrasound, thermography and eddy current, different x-ray methods like radiography, laminography and computed tomography are used to investigate the samples. These methods are compared with the intention to evaluate their capability to reliably detect and characterize defective volume. Beyond the detection of flaws, we also investigate possibilities to combine various NDT methods within a smart manufacturing process in which the decision which method to apply is made by the process itself. Is it possible to design an in-line or at-line testing process which can recognize defects reliably and reduce testing time and costs? This study aims to show up opportunities of designing a smart NDT process synchronized to the production based on the ideas of smart production (Industry 4.0). A set of defective CFRP laminate samples and different NDT methods were used to demonstrate how effective defects are recognized and how communication between interconnected NDT sensors and the manufacturing process could be organized.