TY - GEN A1 - Aßmann, Norman A1 - Bühling, Benjamin T1 - Impact-echo dataset "Radarplatte" T2 - Harvard Dataverse Repository N2 - This dataset contains raw data resulting from Impact-Echo measurements at the reference conrete block "Radarplatte", located at BAM (German Federal Institute for Materials Research and Testing). This specimen has been described in detail by Niederleithinger et al. (2021), who applied muon tomography, ultrasonic echo measurements, radar and X-ray laminography to visualize its internal structure. The Impact-Echo method is based on the excitation of the zero-group-velocity frequency of the first symmetric Lamb mode of a plate-like structure, in order to assess its thickness. Numerous publication elaborate on Impact-Echo theory, examples are (Gibson and Popovics 2005, Schubert and Köhler 2008 , Abraham and Popovics 2010). The measurements have been conducted using a setup that contains only commercially available components. The setup consists of an Olson CTG-2 concrete thickness gauge (Olsen Instruments, USA) for actuation and sensing and an 8-bit NI USB-5132 digital storage oscilloscope (National Instruments, USA) combined with the Echolyst software (Schweizerischer Verein für technische Inspektionen (SVTI), Switzerland) for data acquisition. Measurements were conducted using a grid of 23x23 points with a spacing of 50 mm. At each point 8192 samples were recorded at a sampling rate of 1 MS/s. The dataset contains the (X,Y) location in mm of the individual measurement points as well as the raw measurement data at those points. The data is provided in the formats *.mir/*.mhdr (Echolyst), *.npy (Python) and *.mat (Matlab) and *.csv to ease the import in various post-processing tools. KW - Nondestructive testing KW - Impact-echo KW - S1-ZGV mode KW - Concrete PY - 2021 DO - https://doi.org/10.7910/DVN/UNOH2U PB - Harvard College CY - Cambridge, MA, USA AN - OPUS4-53886 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Bühling, Benjamin T1 - Acoustic and flow data of an ultrasonic fluidic switch and an ultrasonic piezoelectric transducer T2 - Harvard Dataverse Repository N2 - This dataset contains acoustic and flow data of an ultrasonic fluidic switch, which have been acquired using a microphone, a hot-wire anemometer and a pitot tube. Furthermore, acoustic data of a commercial piezoelectric transducer is provided. KW - Fluidics KW - Air-coupled ultrasound KW - Ultrasound KW - Non-destructive testing KW - Acoustic-flow interaction KW - Piezoelectric transducer PY - 2020 DO - https://doi.org/10.7910/DVN/OQYPC9 PB - Harvard College CY - Cambridge, MA, USA AN - OPUS4-52392 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Gebauer, D. A1 - Beltrán Gutierrez, R. A1 - Marx, S. A1 - Maack, Stefan A1 - Küttenbaum, Stefan A1 - Pirskawetz, Stephan A1 - Breit, W. A1 - Mechtcherine, V. A1 - Grahl, K. A1 - Thiel, T. A1 - Schickert, M. A1 - Krüger, M. T1 - Interrelated Data Set from Nondestructive and Destructive Material Testing of Concrete Compressive Strength Specimens T2 - Harvard Dataverse Repository N2 - "This data set contains three different data types obtained from concrete specimens. For each specimen, the rebound numbers, ultrasonic data (ultrasonic velocity, time of flight), and destructive concrete strength are given. Two kind of specimen geometries were tested: cubes and drilled cores. The files are labeled according to the specimen geometry as "cube" or "core" and the type of measurement data as "compressive_strength", "rn_R" and "rn_Q" for rebound numbers as well as "us" for ultrasonic data. The ultrasonic data were generated by six independent laboratories, the rebound numbers by five independent laboratories and the destructive tests by one laboratory. The designation of each specimen establishes the relationship between the different data types." KW - Compressive Concrete Strength KW - Rebound Hammer KW - Ultrasonic Pulse Velocity PY - 2023 DO - https://doi.org/10.7910/DVN/AFCITK PB - Harvard College CY - Cambridge, MA, USA AN - OPUS4-57223 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Gebauer, D. A1 - Gutierrez, B. A1 - Marx, S. A1 - Maack, Stefan A1 - Küttenbaum, Stefan A1 - Pirskawetz, Stephan A1 - Breit, W. A1 - Mechtcherine, V. A1 - Grahl, K. A1 - Thiel, T. A1 - Schickert, M. A1 - Krüger, M. T1 - Interrelated data set from nondestructive and destructive material testing of concrete compressive strength specimens T2 - Harvard Dataverse Repository N2 - This data set contains three different data types obtained from concrete specimens. For each specimen, the rebound numbers, ultrasonic data (ultrasonic velocity, time of flight), and destructive concrete strength are given. Two kind of specimen geometries were tested: cubes and drilled cores. The files are labeled according to the specimen geometry as "cube" or "core" and the type of measurement data as "compressive_strength", "rn_R" and "rn_Q" for rebound numbers as well as "us" for ultrasonic data. The ultrasonic data were generated by six independent laboratories, the rebound numbers by five independent laboratories and the destructive tests by one laboratory. The designation of each specimen establishes the relationship between the different data types. KW - Non-destructive testing KW - Rebound number KW - Ultrasonic pulse velocity KW - Compressive concrete strength KW - Interlaboratory comparison PY - 2023 DO - https://doi.org/10.7910/DVN/AFCITK PB - Harvard College CY - Cambridge, MA, USA AN - OPUS4-57499 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Grotelüschen, Bjarne A1 - Bühling, Benjamin T1 - Impact-Echo Dataset "IE Platte" T2 - Harvard Dataverse Repository N2 - This dataset contains raw data resulting from Impact-Echo measurements at the reference concrete block "IE Platte", located at BAM (German Federal Institute for Materials Research and Testing). The specimen contains three polystyrene slabs and one polyethylene foil to act as reflectors. The specimen was produced in a three-step process. First, the base plate was cast. Second, the reflectors were taped to the base plate. Finally, the upper layer was cast on top of base plate and reflectors. A drawing is contained in the dataset. The Impact-Echo method is based on the excitation of the zero-group-velocity frequency of the first symmetric Lamb mode of a plate-like structure, in order to assess its thickness. Numerous publications elaborate on Impact-Echo theory, examples are (Gibson and Popovics 2005, Schubert and Köhler 2008 , Abraham and Popovics 2010). The measurements have been conducted using a setup that contains only commercially available components. The setup consists of an Olson CTG-2 concrete thickness gauge (Olsen Instruments, USA) for actuation and sensing and an 8-bit NI USB-5132 digital storage oscilloscope (National Instruments, USA) combined with the Echolyst software (Schweizerischer Verein für technische Inspektionen (SVTI), Switzerland) for data acquisition. Measurements were conducted using a grid of 29x29 points with a spacing of 50 mm. At each point 8192 samples were recorded at a sampling rate of 1 MS/s. The dataset contains the (X,Y) location in mm of the individual measurement points as well as the raw measurement data at those points. The data is provided in the formats *.mir/*.mhdr (Echolyst), *.npy (Python) and *.mat (Matlab) and *.csv to ease the import in various post-processing tools. KW - Concrete KW - Impact-Echo KW - Nondestructive testing PY - 2022 DO - https://doi.org/10.7910/DVN/EH4E9G PB - Harvard College CY - Cambridge, MA, USA AN - OPUS4-55279 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Kern, Simon A1 - Liehr, Sascha A1 - Wander, Lukas A1 - Bornemann-Pfeiffer, Martin A1 - Müller, S. A1 - Maiwald, Michael A1 - Kowarik, Stefan T1 - Training data of quantitative online NMR spectroscopy for artificial neural networks N2 - Data set of low-field NMR spectra of continuous synthesis of nitro-4’-methyldiphenylamine (MNDPA). 1H spectra (43 MHz) were recorded as single scans. Two different approaches for the generation of artificial neural networks training data for the prediction of reactant concentrations were used: (i) Training data based on combinations of measured pure component spectra and (ii) Training data based on a spectral model. Synthetic low-field NMR spectra First 4 columns in MAT-files represent component areas of each reactant within the synthetic mixture spectrum. Xi (“pure component spectra dataset”) Xii (“spectral model dataset”) Experimental low-field NMR spectra from MNDPA-Synthesis This data set represents low-field NMR-spectra recorded during continuous synthesis of nitro-4’-methyldiphenylamine (MNDPA). Reference values from high-field NMR results are included. KW - NMR spectroscopy KW - Real-time process monitoring KW - Artificial neural networks KW - Online NMR spectroscopy KW - Automation KW - Process industry PY - 2020 DO - https://doi.org/10.5281/zenodo.3677139 PB - Zenodo CY - Geneva AN - OPUS4-50456 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Klewe, Tim A1 - Strangfeld, Christoph A1 - Ritzer, Tobias A1 - Kruschwitz, Sabine T1 - GPR Dataset of Moisture Measurements on Building Floors in Laboratory and On-Site N2 - Related work Laboratory Study: Combining Signal Features of Ground-Penetrating Radar to Classify Moisture Damage in Layered Building Floors https://doi.org/10.3390/app11198820 On-Site Study: TBA Doctoral Thesis: Non-destructive classification of moisture deterioration in layered building floors using ground penetrating radar https://doi.org/10.14279/depositonce-19306 Measurement Parameters The GPR measurements were carried out with the SIR 20 from GSSI and a 2 GHz antenna pair (bandwidth 1 GHz to 3 GHz) in common-offset configuration. Each B-Scan consists of N A-Scans, each including 512 samples of a 11 ns time window. Survey lines were recorded with 250 A-Scans/ meter, which equals a 4 mm spacing between each A-Scan No Gains were applied. Folder Description: Lab_dry, Lab_insulDamage, Lab_screedDamage - each contain 168 Measurements (B-Scans) in .csv on 84 dry floors, floors with insulation damage and screed damage. - each floor setup was measured twice on two orthogonal survey lines, indicated by _Line1_ and _Line2_ in the file name. - the file names encode the building floor setup e.g. CT50XP100 describes a 50 mm cement screed with 100 mm extruded polystyrene below - the material codes are CT: cement screed, CA: anhydrite screed, EP: expanded polystyrene, XP: extruded polystyrene, GW: glass wool, PS: perlites further information can be found in the publication https://doi.org/10.3390/app11198820 OnSite_ - 5 folders containing B-Scans on 5 different practical moisture damages - the building floor setup is encoded according to the lab with an additional measurement point numbering at the start and a damage case annotation at the end of the file name with _dry, _insulationDamage and_screedDamage File Description: B-Scans, Measurement files - no header - dimension: 512 x N data point with N beeing the number of A-Scans including 512 samples of a 11 ns time window. - survey lines were recorded with 250 A-Scans/ meter, which equals a 4 mm spacing between each A-Scan Moisture References - Moist_Reference of On-Site Locations include the columns MeasPoint: Measurement point, wt%Screed: moisture content of screed layer in mass percent; wt%Insul: moisture content of insulation layer in mass percent. References were obtained by drilling cores with 68 mm diameter in the center of each survey line. - Moist_Reference_Screed of Lab data include the columns Screed: Screed material and thickness in mm, wt%Screed moisture content of screed layer in mass percent - Moist Reference_Insul of Lab data include the columns Insulation: Insulation material and thickness in mm, water addition in l: water added to the insulation layer in liters, V%Insulation: water added to the insulation layer in volume percent, RH%: resulting relative humidy in the insulation layer during measurement. These References are only avaible for Lab measurements on insulation damages. KW - GPR KW - Material Moisture KW - Building Floors KW - Laboratory KW - On-Site PY - 2024 DO - https://doi.org/10.5281/zenodo.10776684 PB - Zenodo CY - Geneva AN - OPUS4-59609 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Kowarik, Stefan A1 - Pithan, L. T1 - kowarik-labs/AI-reflectivity: v0.1 N2 - AI-reflectivity is a code based on artificial neural networks trained with simulated reflectivity data that quickly predicts film parameters from experimental X-ray reflectivity curves. This project has a common root with (ML-reflectivity)[https://github.com/schreiber-lab/ML-reflectivity] and evolved in parallel. Both are linked to the following publication: Fast Fitting of Reflectivity Data of Growing Thin Films Using Neural Networks A. Greco, V. Starostin, C. Karapanagiotis, A. Hinderhofer, A. Gerlach, L. Pithan, S. Liehr, F. Schreiber, S. Kowarik (2019). J. Appl. Cryst. For an online live demonstration using a pre-trained network have a look at github. KW - Artificial neural networks KW - X-ray reflectivity PY - 2019 DO - https://doi.org/10.5281/zenodo.3477583 PB - Zenodo CY - Geneva AN - OPUS4-51888 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Kudela, P. A1 - Radzienski, M. A1 - Moix-Bonet, M. A1 - Willberg, C. A1 - Lugovtsova, Yevgeniya A1 - Bulling, Jannis A1 - Tschöke, K. A1 - Moll, J. T1 - Dataset on full ultrasonic guided wavefield measurements of a CFRP plate with fully bonded and partially debonded omega stringer N2 - The fourth dataset dedicated to the Open Guided Waves platform presented in this work aims at a carbon fiber composite plate with an additional omega stringer at constant temperature conditions. The dataset provides full ultrasonic guided wavefields. A chirp signal in the frequency range 20-500 kHz and Hann windowed tone-burst signal with 5 cycles and carrier frequencies of 16.5 kHz, 50 kHz, 100 kHz, 200 kHz and 300kHz are used to excite the wave. The piezoceramic actuator used for this purpose is attached to the center of the stringer side surface of the core plate. Three scenarios are provided with this setup: (1) wavefield measurements without damage, (2) wavefield measurements with a local stringer debond and (3) wavefield measurements with a large stringer debond. The defects were caused by impacts performed from the backside of the plate. As result, the stringer feet debonds locally which was verified with conventional ultrasound measurements. The dataset can be used for benchmarking purposes of various signal processing methods for damage imaging. The detailed description of the dataset is published in Data in Brief Journal. KW - Open data KW - Ultrasonic guided waves KW - Experimental data PY - 2021 DO - https://doi.org/10.5281/zenodo.5105861 PB - Zenodo CY - Geneva AN - OPUS4-54504 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - GEN A1 - Liehr, Sascha T1 - ANNforPAT - Artificial Neural Networks for Process Analytical Technology N2 - This code accompanies the paper "Artificial neural networks for quantitative online NMR spectroscopy" published in Analytical and Bioanalytical Chemistry (2020). KW - Artificial neural networks KW - Automation KW - Online NMR spectroscopy KW - Process industry KW - Real-time process monitoring PY - 2020 UR - https://github.com/BAMresearch/ANNforPAT PB - GitHub CY - San Francisco AN - OPUS4-54481 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -