TY - CONF A1 - Niederleithinger, Ernst T1 - Ultrasound: From Imaging to Monitoring N2 - Review of ultrasonic echo imaging and ultrasonic monitoring techniques applied to concrete structures, especially bridges. Includes newest research results from BAM. T2 - Transport Research Board Annual Meeting, Workshop 1647 CY - Washington, DC, USA DA - 6.1.2018 KW - Ultrasound KW - Imaging KW - Monitoring KW - Concrete KW - Bridges PY - 2018 AN - OPUS4-44587 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Procop, Mathias A1 - Hodoroaba, Vasile-Dan T1 - Uncertainties in secondary fluorescence correction in EPMA N2 - Secondary fluorescence is an inevitable effect that has to be taken into account in any algorithm for quantitative electron probe microanalysis (EPMA) as an additional correction. Moreover, secondary fluorescence worsens spatial resolution of EPMA. Secondary fluorescence is excited both by characteristic radiation and by the X-ray continuum. In most cases the correction is small. There are, however, cases, e.g. the determination of low heavy metal concentration in a light matrix, where the contribution of secondary fluorescence exceeds 10% of the measured X-ray line intensity. For secondary fluorescence correction the measured X-ray line intensity has to be divided by the correction factor (1+I_flchar/I_p +I_flcont/I_p )≈(1+I_flchar/I_p )(1+I_flcont/I_p ) in order to get those intensity I_p, which is excited only by the primary electrons. I_flchar and I_flcont mean the calculated characteristic and continuums fluorescence intensities. In order to get the intensity of fluorescence radiation, the absorption of the exciting radiation in the specimen, the photoionization probability and the self-absorption of the emitted line must be calculated. The critical quantity is the X-ray yield of the exciting atoms in case of fluorescence by characteristic radiation and the bremsstrahlung yield of the specimen in case of continuum fluorescence. In the former case it is reasonable to apply the same physical model to calculate I_flchar and I_p. KW - EPMA KW - Secondary fluorescence correction KW - Uncertainties KW - Microanalysis PY - 2019 UR - https://www.cambridge.org/core/journals/microscopy-and-microanalysis/article/uncertainties-in-secondary-fluorescence-correction-in-epma/AA92E973D350A74C574067AAFB2D9044 DO - https://doi.org/10.1017/S1431927619012534 SN - 1431-9276 SN - 1435-8115 VL - 25 IS - Suppl. 2 SP - 2360 EP - 2361 PB - Cambridge University Press AN - OPUS4-48863 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Hodoroaba, Vasile-Dan A1 - Procop, Mathias T1 - Uncertainties in Secondary Fluorescence Correction in EPMA N2 - Secondary fluorescence is an inevitable effect that has to be taken into account in any algorithm for quantitative electron probe microanalysis (EPMA) as an additional correction. Moreover, secondary fluorescence worsens spatial resolution of EPMA, as discussed once more in two recent papers. Secondary fluorescence is excited both by characteristic radiation and by the X-ray continuum. In most cases the correction is small. There are, however, cases, e.g. the determination of low heavy metal concentration in a light matrix, where the contribution of secondary fluorescence exceeds 10% of the measured X-ray line intensity. For secondary fluorescence correction the measured X-ray line intensity has to be divided by the correction factor (1+I_flchar/I_p +I_flcont/I_p )≈(1+I_flchar/I_p )(1+I_flcont/I_p ) in order to get those intensity I_p, which is excited only by the primary electrons and enables the determination of specimen composition. I_flchar and I_flcont mean the calculated characteristic and continuums fluorescence intensities. In order to get the intensity of fluorescence radiation, the absorption of the exciting radiation in the specimen, the photoionization probability and the self-absorption of the emitted line must be calculated. This can be performed in a straightforward way. The critical quantity is the X-ray yield of the exciting atoms in case of fluorescence by characteristic radiation and the bremsstrahlung yield of the specimen in case of continuum fluorescence. In the former case it is reasonable to apply the same physical model to calculate I_flchar and I_p. T2 - Microscopy & Microanalysis 2019 CY - Portland, OR, USA DA - 03.08.2019 KW - EPMA KW - Secondary fluorescence KW - Uncertainties KW - X-ray spectrometry KW - Fluorescence correction PY - 2019 AN - OPUS4-48673 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Beck, Uwe A1 - Griepentrog, Michael A1 - Hertwig, Andreas A1 - Hielscher-Hofinger, S. A1 - Lange, Thorid A1 - Weise, Matthias T1 - Uncertainty budgets in surface techno-logy: step height, layer thickness, indentation hardness, adehesive strength N2 - The object (sample) and the measurement/testing procedure may always have unknown degrees of freedom, i.e. instead of 𝐯 ≥ n – 1 in many cases 𝐯 ≫ n - 1 may apply, in particular in the micro- and nano-world! T2 - 10. VDI-Fachtagung, Messunsicherheit und Prüfprozesse CY - Erfurt, Germany DA - 10.11.2021 KW - Methodology in metrology KW - Methodology in testing KW - Spectroscopic Ellipsometry KW - Instrumented Indentation (IIT) KW - Centrifugal Adhesion Testing (CAT) PY - 2021 AN - OPUS4-53739 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Beck, Uwe A1 - Griepentrog, Michael A1 - Hertwig, Andreas A1 - Hielscher-Hofinger, Stefan A1 - Lange, Thorid A1 - Weise, Matthias T1 - Uncertainty budgets in surface technology: stepheigt, layerthickness, indentation hardness, adehesive strength N2 - The object (sample) and the measurement/testing procedure may always have unknown degrees of freedom, i.e. instead of 𝐯 ≥ n – 1 in many cases 𝐯 ≫ n - 1 may apply, in particular in the micro- and nano-world! T2 - 10. VDI-Fachtagung, Messunsicherheit und Prüfprozesse CY - Erfurt, Germany DA - 10.11.2021 KW - Methodology in metrology KW - Methodology in testing KW - Spectroscopic Ellipsometry KW - Instrumented Indentation Testing (IIT) KW - Centrifugal Adhesion Testing (CAT) PY - 2021 AN - OPUS4-53986 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Ullner, Christian A1 - Subaric-Leitis, Andreas A1 - Bartholmai, Matthias T1 - Uncertainty of Elastoplastic Material Parameters Calculated from the Spherical Indentation in the Macro Range N2 - The applicability of three methods developed by finite element analysis (FEM) and proposed in the literature are studied on steel S355. Instrumented indentation tests using spherical indenters of radius 200 and 500 μ m are performed in the macro range at depths of more than 6 μ m. The results of the selected methods are compared with the tensile test. To evaluate the partially strongly varying results, the uncertainties of the calculated strain hardening exponent, n, and yield stress, Y, are estimated. Recommendations for an appropriated procedure of the indentation test are given. The machine compliance and the determination of the zero point of Depth play an essential role. If the certain conditions are considered, the instrumented indentation Tests can be used, in particular for investigations of specimens with inhomogeneous elastoplasticity. KW - Indentation KW - Elastoplastic material parameters KW - Uncertainty PY - 2021 DO - https://doi.org/10.1520/JTE20200683 SN - 0090-3973 VL - 49 IS - 6 SP - 4576 EP - 4592 PB - ASTM International AN - OPUS4-52416 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Völker, Christoph A1 - Kruschwitz, Sabine A1 - Benner, Philipp T1 - Uncertainty quantification for a sparse machine learning (ML) data set in non-destructive testing in civil engineering (NDT-CE) N2 - ML has been successfully applied to solve many NDT-CE tasks. This is usually demonstrated with performance metrics that evaluate the model as a whole based on a given set of data. However, since in most cases the creation of reference data is extremely expensive, the data used is generally much sparser than in other areas, such as e-commerce. As a result, performance indicators often do not reflect the practical applicability of the ML model. Estimates that quantify transferability from one case to another are necessary to meet this challenge and pave the way for real world applications. In this contribution we invetigate the uncertainty of ML in new NDT-CE scenarios. For this purpose, we have extended an existing training data set for the classification of corrosion damage by a new case study. Our data set includes half-cell potential mapping and ground-penetrating radar measurements. The measurements were performed on large-area concrete samples with built-in chloride-induced corrosion of reinforcement. The experiment simulated the entire life cycle of chloride induced exposed concrete components in the laboratory. The unique ability to monitor deterioration and initiate targeted corrosion initiation allowed the data to be labelled - which is crucial to ML. To investigate transferability, we extend our data by including new design features of the test specimen and environmental conditions. This allows to express the change of these features in new scenarios as uncertainties using statistical methods. We compare different sampling and statistical distribution-based approaches and show how these methods can be used to close knowledge gaps of ML models in NDT. T2 - EGU General Assembly 2021 CY - Online meeting DA - 19.04.2021 KW - Data fusion KW - Non-destructive testing PY - 2021 DO - https://doi.org/10.5194/egusphere-egu21-8798 AN - OPUS4-54125 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Yablokov, A. A1 - Lugovtsova, Yevgeniya A1 - Serdyukov, A. T1 - Uncertainty quantification of multimodal surface wave inversion using artificial neural networks N2 - An inversion of surface waves dispersion curves is a non-unique and ill-conditioned problem. The inversion result has a probabilistic nature, which becomes apparent when simultaneously restoring the shear wave (S-wave) velocity and layer thickness. Therefore, the problem of uncertainty quantification is relevant. Existing methods through deterministic or global optimization approaches of uncertainty quantification via posterior probability density (PPD) of the model parameters are not computationally efficient since they demand multiple solutions of the inverse problem. We present an alternative method based on a multi-layer fully connected artificial neural network (ANN). We improve the current uni-modal approach, which is known from publications, to multi-modal inversion. The learned ANN maps the phase velocity dispersion curves to values of the S-wave velocity and layers thickness. To estimate the uncertainties, we adapt the Monte-Carlo simulation strategy and project onto the resulting velocity model both frequency-dependent data noise and inverse operator errors, which are evaluated by the prediction of the training data set. The proposed combination of surface waves data processing methods, configured with each other, provides a novel surface waves multi-modal dispersion data inversion and uncertainty quantification approach. We first test our approach on synthetic experiments for various velocity models: a positive velocity gradient, a low-velocity layer and a high-velocity layer. This is done considering uni-modal inversion at first and then compared to the multi-modal inversion. Afterwards, we apply our approach to field data and compare resulting models with the body S-wave processing by the generalized reciprocal method (GRM). The experiments show high-potential results – using ANN yields the possibility to accurately estimate PPD of restored model parameters without a significant computational effort. The PPD-based comparison demonstrates advantages of a multi-modal inversion over uni-modal inversion. The trained ANN provides reasonable model parameters predictions and related uncertainties in real-time. KW - Multi-layers KW - Multichannel analysis of surface waves (MASW) KW - Characterisation of soil sites KW - Monte Carlo simulation KW - Field data PY - 2023 DO - https://doi.org/10.1190/geo2022-0261.1 SN - 0016-8033 VL - 88 IS - 2 SP - 1 EP - 43 PB - Society of Exploration Geophysicists CY - Tulsa, Okla. AN - OPUS4-56624 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Sebald, M. A1 - Gebauer, J. A1 - Koch, Matthias T1 - Under Investigation: Novel Approach towards the Synthesis of Deuterium-labelled Alternariol- and Alternariol monomethylether-Standards for the HPLC-MS/MS-Analysis in Food & Feed N2 - Alternariol (AOH) and Alternariol monomethylether (AME) are two secondary metabolites of Alternaria fungi which can be found in various foodstuffs like tomatoes, nuts and grains. Due to their toxicity and potential mutagenic activity the need for the development of high-throughput methods for the supervision of AOH- and AME-levels is of increasing interest. As the availability of both native and labelled AOH and AME analytical standards is very limited we herein wish to present a novel concise approach towards their synthesis employing a ruthenium-catalyzed ortho-arylation4 as the key step. T2 - 13th International Symposium on the Synthesis and Applications of Isotopes and Isotopically Labelled Compounds CY - Prague, Czech Republic DA - 03.06.2018 KW - Mycotoxins KW - Mass Spectrometry PY - 2018 AN - OPUS4-45268 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - CONF A1 - Völker, Christoph A1 - Moreno Torres, Benjami A1 - Kruschwitz, Sabine T1 - Understanding distributed data – a semantic web approach for data based analysis of NDT data in civil engineering N2 - In the field of non-destructive testing (NDT) in civil engineering, a large number of measurement data are collected. Although they serve as a basis for scientific analyses, there is still no uniform representation of the data. An analysis of various distributed data sets across different test objects is therefore only possible with high manual effort. We present a system architecture for an integrated data management of distributed data sets based on Semantic Web technologies. The approach is essentially based on a mathematical model - the so-called ontology - which represents the knowledge of our domain NDT. The ontology developed by us is linked to data sources and thus describes the semantic meaning of the data. Furthermore, the ontology acts as a central concept for database access. Non-domain data sources can be easily integrated by linking them to the NDT construction ontology and are directly available for generic use in the sense of digitization. Based on an extensive literature research, we outline the possibilities that this offers for NDT in civil engineering, such as computer-aided sorting, analysis, recognition and explanation of relationships (explainable AI) for several million measurement data. The expected benefits of this approach of knowledge representation and data access for the NDT community are an expansion of knowledge through data exchange in research (interoperability), the scientific exploitation of large existing data sources with data-based methods (such as image recognition, measurement uncertainty calculations, factor analysis, material characterization) and finally a simplified exchange of NDT data with engineering models and thus with the construction industry. Ontologies are already the core of numerous intelligent systems such as building information modeling or research databases. This contribution gives an overview of the range of tools we are currently creating to communicate with them. T2 - EGU General Assembly 2020 CY - Online meeting DA - 04.05.2020 KW - Ontology KW - NDT KW - Concrete KW - Onotology KW - Semantic Data Management KW - Reproducible Science PY - 2020 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-518076 DO - https://doi.org/10.5194/egusphere-egu2020-19332 AN - OPUS4-51807 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -