Chemie und Prozesstechnik
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This article presents deep unfolding neural networks to handle inverse problems in photothermal radiometry enabling super-resolution (SR) imaging. The photothermal SR approach is a well-known technique to overcome the spatial resolution limitation in photothermal imaging by extracting high-frequency spatial components based on the deconvolution with the thermal point spread function (PSF). However, stable deconvolution can only be achieved by using the sparse structure of defect patterns, which often requires tedious, handcrafted tuning of hyperparameters and results in computationally intensive algorithms. On this account, this article proposes Photothermal-SR-Net, which performs deconvolution by deep unfolding considering the underlying physics. Since defects appear sparsely in materials, our approach includes trained block-sparsity thresholding in each convolutional layer. This enables to super-resolve 2-D thermal images for nondestructive testing (NDT) with a substantially improved convergence rate compared to classic approaches. The performance of the proposed approach is evaluated on various deep unfolding and thresholding approaches. Furthermore, we explored how to increase the reconstruction quality and the computational performance. Thereby, it was found that the computing time for creating high-resolution images could be significantly reduced without decreasing the reconstruction quality by using pixel binning as a preprocessing step.
A systematic study has been carried out to investigate the neutron transmission signal as a function of sample temperature. In particular, the experimentally determined wavelength-dependent neutron attenuation spectra for a martensitic steel at temperatures ranging from 21 to 700°C are compared with simulated data. A theoretical description that includes the Debye–Waller factor in order to describe the temperature influence on the neutron cross sections was implemented in the nxsPlotter software and used for the simulations. The analysis of the attenuation coefficients at varying temperatures shows that the missing contributions due to elastic and inelastic scattering can be clearly distinguished: while the elastically scattered intensities decrease with higher temperatures, the inelastically scattered intensities increase, and the two can be separated from each other by analysing unique sharp features in the form of Bragg edges. This study presents the first systematic approach to quantify this effect and can serve as a basis , for example, to correct measurements taken during in situ heat treatments, in many cases being a prerequisite for obtaining quantifiable results.
This contribution summarizes actual developments and draft fundamental teaching topics in the field of nondestructive testing in civil engineering (NDT-CE). It is based on the first memorandum on teaching and research in the field of NDT-CE at German speaking universities and provides an overview of the academic education and highlights possible focuses, especially in teaching but also takes into account noteworthy developments and topics in research in the field of NDT-CE.
Suggestions are given for the development and advancement of the teaching curricula in regards to a comprehensive and sound professional education of students in civil engineering and adjacent disciplines.
Nach einer kurzen Einführung in die Schallemissionsprüfung und -Analyse wird ein Versuchsstand vorgestellt, der im Rahmen des Themenfeldprojektes Seal Waste Safe installiert wurde. Schwerpunkt des Vortrages sind die Schallemissionsmessungen an einem 150 l Demonstrator aus Salzbeton und einem weiteren aus alkali-aktiviertem Material. Neben der konventionellen Schallemissionsanaylse mit Aktivitäts- und Intensitätsparametern der Zeitsignale, werden auch frequenzbasierte Parameter zur Analyse andiskutiert.
The amount of data generated worldwide is constantly increasing. These data come from a wide variety of sources and systems, are processed differently, have a multitude of formats, and are stored in an untraceable and unstructured manner, predominantly in natural language in data silos. This problem can be equally applied to the heterogeneous research data from materials science and engineering. In this domain, ways and solutions are increasingly being generated to smartly link material data together with their contextual information in a uniform and well-structured manner on platforms, thus making them discoverable, retrievable, and reusable for research and industry. Ontologies play a key role in this context. They enable the sustainable representation of expert knowledge and the semantically structured filling of databases with computer-processable data triples.
In this perspective article, we present the project initiative Materials-open-Laboratory (Mat-o-Lab) that aims to provide a collaborative environment for domain experts to digitize their research results and processes and make them fit for data-driven materials research and development. The overarching challenge is to generate connection points to further link data from other domains to harness the promised potential of big materials data and harvest new knowledge.
Whereas human factors (HF) in the non-destructive testing (NDT) of metallic components are a poorly investigated topic (in comparison to other industrial fields such as aviation), HF in the inspection of concrete components are even less known. Studies have shown that there is always some variability between individuals in their inspection results and that HF affect the reliability of NDT inspections. The aim of the ongoing WIPANO project is to draft a standard for a holistic reliability assessment, with concrete inspection as one case study. This includes also the HF. A human-oriented Failure Modes and Effects Analysis (FMEA) was carried out to do the following: a) identify possible human-related risks in tunnel inspection processes using a laser scan method (including data collection,evaluation, and assessment of tunnel damage) and b) evaluate these human-related risks as regards their possible causes, consequences and probability of occurrence – in addition with respect to existing and possible preventive measures. The results show that the causes for possible failures can lie within people, the physical environment, technology, organisation, and extra-organisational environment. Whereas current preventive measures rely mostly on the individual and quality management practices, there is potential for even larger improvement at the organisational and extra-organisational level. The FMEA results were also used to develop a quantification method to further understand the HF in tunnel inspection, which could possibly be included in the information into the overall reliability assessment. The usage of qualitative and quantitative data collected through the human-FMEA within the proposed quantification method shows promise that HF can be quantified and could offer broader understanding of HF influences on inspection in various industries.
Whereas human factors (HF) in the non-destructive testing (NDT) of metallic components are a poorly investigated topic (in comparison to other industrial fields such as aviation), HF in the inspection of concrete components are even less known. Studies have shown that there is always some variability between individuals in their inspection results and that HF affect the reliability of NDT inspections. The aim of the ongoing WIPANO project is to draft a standard for a holistic reliability assessment, with concrete inspection as one case study. This includes also the HF. A human-oriented Failure Modes and Effects Analysis (FMEA) was carried out to do the following: a) identify possible human-related risks in tunnel inspection processes using a laser scan method (including data collection,evaluation, and assessment of tunnel damage) and b) evaluate these human-related risks as regards their possible causes, consequences and probability of occurrence – in addition with respect to existing and possible preventive measures. The results show that the causes for possible failures can lie within people, the physical environment, technology, organisation, and extra-organisational environment. Whereas current preventive measures rely mostly on the individual and quality management practices, there is potential for even larger improvement at the organisational and extra-organisational level. The FMEA results were also used to develop a quantification method to further understand the HF in tunnel inspection, which could possibly be included in the information into the overall reliability assessment. The usage of qualitative and quantitative data collected through the human-FMEA within the proposed quantification method shows promise that HF can be quantified and could offer broader understanding of HF influences on inspection in various industries
Menschliche Faktoren sind ein häufig genanntes Thema, wenn wir über
die Zuverlässigkeit der zerstörungsfreien Prüfung (ZfP) sprechen. Die Probability of Detection (POD), das üblicherweise verwendete Maß für die Zuverlässigkeit der ZfP, betrachtet jedoch nur die technische Fähigkeit eines ZfP-Systems, einen Fehler zu entdecken. Nach mehreren Jahrzehnten der Erforschung des Einflusses der menschlichen Faktoren auf die Zuverlässigkeit der ZfP gibt es immer noch keinen allgemein akzeptierten Ansatz, um menschliche Faktoren in der Zuverlässigkeitsbewertung sichtbar zu machen. Dieser Beitrag gibt einen Überblick über verschiedene verfügbare Methoden zur Einbeziehung menschlicher Faktoren in die Zuverlässigkeitsbewertung. Das Thema ist ein essenzieller Bestandteil des laufenden WIPANO-Projekts "normPOD", das sich als Ziel gesetzt hat, die Standardisierung der Zuverlässigkeitsbewertung in Deutschland voranzutreiben und im Vergleich zu den schon bekannten internationalen Normen einen Fokus auf den Umgang mit den menschlichen Faktoren zu legen.
Methodologies for model parameterization of virtual CTs for measurement uncertainty estimation
(2022)
X-ray computed tomography (XCT) is a fast-growing technology for dimensional measurements in industrial applications. However, traceable and efficient methods to determine measurement uncertainties are not available. Guidelines like the VDI/VDE 2630 Part 2.1 suggest at least 20 repetitions of a specific measurement task, which is not feasible for industrial standards. Simulation-based approaches to determine task specific measurement uncertainties are promising, but require closely adjusted model parameters and an integration of error sources like geometrical deviations during a measurement. Unfortunately, the development of an automated process to parameterize and integrate geometrical deviations into XCT models is still an open issue. In this work, the whole processing chain of dimensional XCT measurements is taken into account with focus on the issues and requirements to determine suitable parameters of geometrical deviations. Starting off with baseline simulations of different XCT systems, two approaches are investigated to determine and integrate geometrical deviations of reference measurements. The first approach tries to iteratively estimate geometric deviation parameter values to match the characteristics of the missing error sources. The second approach estimates those values based on radiographs of a known calibrated reference object. In contrast to prior work both approaches only use a condensed set of parameters to map geometric deviations. In case of the iterative approach, some major issues regarding unhandled directional dependencies have been identified and discussed. Whereas the radiographic method resulted in task specific expanded measurements uncertainties below one micrometre even for bi-directional features, which is a step closer towards a true digital twin for uncertainty estimations in dimensional XCT.