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360 results for “steel”
Database of measurements for damage detection of steel beam splice connection by Coaxial Correlation Method in 6-D space
<p>This database includes series of measurements of the structure's response taken in six-dimensional space using two 6D sensors, coaxially positioned on either side of the investigated splice connection between two steel beams. The data set consists of two parts. The first part of the data set is measurements for six different specimens with wave type impact – short sweep signal with duration 0.05 s. The second part is the measurements during splice connection degradation of one of the specimens with short impulse. The degradation of a connection is presented by four different states of joints. In the "<strong>Read_me_first.pdf</strong>" is described the experiment, the format of .csv files names and files' structure.</p><p>Used materials, methods and results for the second part of the data set is described in Buka-Vaivade, K.; Kurtenoks, V.; Serdjuks, D. Non-Destructive Damage Detection of Structural Joint by Coaxial Correlation Method in 6D Space. <i>Buildings</i> <strong>2023</strong>, <i>13</i>, 1151. https://doi.org/10.3390/buildings13051151</p>
Database of measurements for damage detection of steel beam splice connections by Coaxial Correlation Method in 6-D space
<p>This database includes series of measurements of the structure's response taken in six-dimensional space using two 6D sensors, coaxially positioned on either side of the investigated splice connection between two steel beams. The data set consists of measurements for six different specimens with two types of impact – sweep signal with duration 0.5 s and short impulse, during degradation of the splice connections realised by unbolting the bolts in the connections. In the "<strong>Read_me_first.pdf</strong>" is described the experiment, the format of .csv files names and files' structure.</p><p>This database is a continuation of the database Kurtenoks, V., Buka-Vaivade, K., Serdjuks, D., Lapkovskis, V., Mironovs, V., & Podkoritovs, A. (2023). Database of measurements for damage detection of steel beam splice connection by Coaxial Correlation Method in 6-D space (1.0.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.10077332<br>Suggested by authors data post-processing is described in Buka-Vaivade, K.; Kurtenoks, V.; Serdjuks, D. Non-Destructive Damage Detection of Structural Joint by Coaxial Correlation Method in 6D Space. <i>Buildings</i> <strong>2023</strong>, <i>13</i>, 1151. https://doi.org/10.3390/buildings13051151</p>
Digital image correlation measurement of linear elastic steel specimen
<p>The dataset comprises the axial and lateral displacements on the surface of a plate with a hole subjected to tensile load. The displacement data are measured by digital image correlation and the material is assumed to behave linear elastic. The material under investigation is a common low-carbon steel alloy of type S235. The displacement data are used for calibration of a linear elastic constitutive model using parametric physics-informed neural networks and finite elements. For that purpose, the dataset comprises both the raw experimental displacement data and displacement data interpolated onto a regular grid using linear interpolation, where the interpolation routine is provided as well.</p>
Pseudodynamic testing of a substandard infilled steel structure
<p>Data from the pseudodynamic testing of a substandard, infilled steel building, is provided. The structure and related testing activities are described in:</p> <div> <div> <div> <p><em>"Assessment of existing steel frames: Numerical study, pseudo-dynamic testing and influence of masonry infills" (2021) Luigi Di Sarno, Fabio Freddi, Mario D’Aniello, Oh-Sung Kwon, Jing-Ren Wu, Fernando Guti ́errez-Urzúa, Raffaele Landolfo, Jamin Park, Xenofon Palios, Elias Strepelias,Journal of Constructional Steel Research, 185, https://doi.org/10.1016/j.jcsr.2021.106873</em></p> <p> </p> </div> </div> </div>
Construction Industry Steel Ordering Lists (CISOL) Dataset
<p>The Construction Industry Steel Ordering Lists (CISOL) dataset comprises table-centric, real-world documents from the construction industry, annotated to facilitate the testing and training of deep learning models for table detection (TD) and table structure recognition (TSR). </p> <p>CISOL Key Features:</p> <ul> <li>Steel ordering lists from 24 construction projects carried out between 2015-2023, contributed by 10 distinct German structural engineering firms.</li> <li>Anonymized images to ensure the unrecognizability of specific project or creator information.</li> <li>A total of 3280 images, with 844 annotated following the CISOL annotation guidelines.</li> </ul> <p>CISOL is structured into two tracks:</p> <ul> <li><strong>Track A: TD-TSR </strong>version for end-to-end table detection and table structure recognition tasks.</li> <li><strong>Track B: TSR-</strong>only version for table structure recognition tasks, featuring images cropped to the actual table areas with accordingly adjusted annotations.</li> </ul> <p>The dataset is developed in accordance with the FAIR Principles, ensuring that it is Findable, Accessible, Interoperable, and Reusable. The CISOL dataset permits expansion following the established annotation guideline.</p> <p>Access to the CISOL Leaderboard will be provided at <a href="https://eval.ai/web/challenges/challenge-page/2257" target="_blank" rel="noopener">EvalAI.</a></p> <p> </p>
Dataset on the experimental investigation of the seismic response of moment-resisting steel frames using shaking table tests
<h2>Description:</h2> <p>This dataset contains data from experimental shake table tests conducted on a two-storey steel-frame structure, involving linear sweep, white noise, impulse, and seismic excitations (see 'Load_Protocols_v1.0.0.pdf'). The experiments were carried out using the uniaxial shaking table at the <a href="https://www.lbb.rwth-aachen.de/cms/lbb/der-lehrstuhl/~bjlfvq/geraetezentzrum/?lidx=1">RWTHDynLab</a> of the <a href="https://www.lbb.rwth-aachen.de/go/id/eaxh/">Chair of Structural Analysis and Dynamics (LBB) - RWTH Aachen University</a>, in cooperation with the <a href="https://www.stb.rwth-aachen.de/cms/~iozv/STB/">Institute of Structural Steel (STB) - RWTH Aachen</a> and the <a href="https://www.cwe.rwth-aachen.de/home-2/">Center for Wind and Earthquake Engineering (CWE) – RWTH Aachen</a>.</p> <p>The experimental campaign was developed to gain a better understanding of the interaction between the main structure and non-structural components, to investigate the reliability and accuracy of analytical methods to predict response floor spectra and non-structural component acceleration described in various guidelines and seismic codes. Regarding applications of Structural Health Monitoring the necessity for additional sensors on non-structural components was studied. Three single-degree-of-freedom oscillators (SDOFs) were connected to the upper floor representing non-structural components. The test structure was subjected to a total of twelve earthquake excitations with different spectral properties. The main objectives of the test campaign were:</p> <ul> <li>Identification of the modal properties of the test structure.</li> <li>Measurement of the floor response in terms of acceleration and displacement.</li> <li>Determination of the real floor response spectra based on the measurements of the acceleration sensors installed on the first and second floors.</li> <li>Comparison of the expected peak accelerations from the floor response spectra with the peak accelerations measured by the accelerometers attached to the three SDOFs.</li> </ul> <h3>Test structure:</h3> <p>The test structure consisted of a two-storey steel structure which was stabilised in the direction of excitation by moment resisting frames (MRFs). In the transverse direction the global stability was ensured by concentrically braced frames (braces QRo 50x5). The structure was designed in accordance with provisions of prEN-1998-1 for energy dissipation and ductile seismic behaviour. As ductile members were considered the frame beams so that the columns and connections remain undamaged. An illustration of the test structure is depicted in 'Test_Structure_Sketch_v1.0.0.pdf'. The dimensions of the test structure are: 2.40 m in length, 2.40 m in width and 3.78 m in total height (1st storey: 2.02 m; 2nd storey: 1.76 m). Four large steel I-sections, each with a dead weight of 1700 kg, were attached to the main structure as masses and secured by U-Profiles. A tank with a dead load of approx. 100 kg and a volume of 400 litres was mounted onto the first floor. The tank remained empty during this test series. HEA200 profiles (S355-J2) were selected as column profiles, whereas IPE160 profiles (S235-JR) as frame beams. All main and secondary beams were realised by HEA140 profiles (S235-JR). Four L60x6 bars were arranged in a rhombus shape in the floor plane to ensure a diaphragm action. In the area of the MRF connections, the columns were reinforced with an additional double web plate (t = 10 mm) and with three ribs (t = 10 mm) at the level of the beam top flange, the beam bottom flange and the haunch flange. The beam-to-column connections were classified as full strength and semi-rigid in terms of capacity and stiffness. The critical welds connecting the frame transom to the top plate (t = 15 mm) were designed as full penetration groove welds in accordance with the specifications of Annex E of prEN1998-1 for seismically standardised connections. Twelve M16-10.9 bolts were used to ensure the force transfer between the beam and column. All connections of the secondary beams to the main beams were realised as end plate connections to prevent premature failure due to combined loading by normal and shear forces. The arrangement of the secondary beams and the corresponding force transmission was conceptualized in such a way that the frame beams could be replaced after a series of tests without having to remove the masses and the tank. The columns were hinged to the shaking table (see 'Column_Base_Anchorage_v1.0.0.pdf'). Slots in the anchor plates allow the rotation of the support base around the strong axis of the columns. The anchoring to the shaking table was realised using four M24-8.8 threaded rods. To simulate non-structural components, three SDOFs were attached to the centre of the secondary beams that run across the frame transom on the second floor (see 'Test_Structure_v1.0.0.pdf'). The SDOFs consisted of a flat steel and a mass. Depending on the thickness of the flat steel and the position of the mass, the three SDOFs were calibrated so that the natural frequency of the first SDOF matches the natural frequency of the second modal shape of the test structure in the frame direction, and the natural frequency of the third SDOF corresponds the first natural frequency of the structure. The natural frequency of the second SDOF was set so that it lies between those of the other SDOFs, creating a staggered range of dynamic responses.</p> <h3>Test setup:</h3> <p>The shaking table specifications are:</p> <ul> <li>Table size: 3.0x3.0 m</li> <li>Max. specimen mass: 10 t</li> <li>Max. overturning moment: 30 m t</li> <li>Max. actuator stroke: +/- 250 mm</li> <li>Max. table velocity: +/- 1 m/s at rated load</li> <li>Max. table acceleration: +/- 1g at rated load</li> <li>Test frequency: 0 to 50 Hz</li> </ul> <p>The instrumentation scheme of the test setup consisted of accelerometers and displacement tranducers, measuring the excitation provided by the shaking table and the response of the structure. Regarding the global response of the test structure, the recordings of the accelerometers and displacement tranducers indicated in the uploaded file 'Instrumentation_Scheme_v1.0.0.pdf' are provided. </p> <p>The properties of the accelerometers are:</p> <ul> <li>Type: M3701-series</li> <li>Manufacturer: PCB Piezotronics, Inc.</li> <li>Measurement range: +/- 3g</li> <li>Frequency range: 0-500 Hz</li> <li>Sensitivity: 900 mV/g</li> <li>Resolution: 2.2e-5g</li> <li>Noise: 1 µg/Hz<sup>-0.5</sup></li> </ul> <p>The properties of the displacement tranducers are:</p> <ul> <li>Type: LZW-M-500</li> <li>Manufacturer: WayCon Positionsmesstechnik GmbH</li> <li>Measurement range: +/- 250 mm</li> <li>Linearity: +/- 0.05%</li> <li>Repeatability: 0.01 mm</li> <li>Displacement force: ≤15 N</li> <li>Displacement speed: ≤5 m/s</li> </ul> <h2>Files:</h2> <ul> <li>Column_Base_Anchorage_v1.0.0.pdf <ul> <li>Photo of the column-base anchorage.</li> </ul> </li> <li>Data_v1.0.0.zip <ul> <li>Contains all data files according to the load protocols.</li> <li>The experimental data is provided as .csv files for each load protocol. </li> </ul> </li> <li>Instrumentation_Scheme_v1.0.0.pdf <ul> <li>.pdf file illustrating the sensor placements on the test structure.</li> </ul> </li> <li>Load_Protocols_v1.0.0.pdf <ul> <li>.pdf file listing all load protocols applied to the structure.</li> </ul> </li> <li>References_v1.0.0.bib <ul> <li>Contains a bibtex reference with the associated publications.</li> </ul> </li> <li>Shake_Table.jpg <ul> <li>Photo of the shaking table without any specimen.</li> </ul> </li> <li>Test_Structure_v1.0.0.pdf <ul> <li>Photo of the shaking table including the test structure.</li> </ul> </li> <li>Test_Structure_Sketch_v1.0.0.pdf <ul> <li>.pdf file illustrating the test structure.</li> </ul> </li> <li>Time_Histories_v1.0.0.pdf <ul> <li>.pdf file including plots of the measurement data.</li> </ul> </li> </ul> <h2>File format of the datasets:</h2> <p>The data is stored in .csv files, where each file contains the following columns (see also 'Instrumentation_Scheme_v1.0.0.pdf'):</p> <ul> <li>Time (s): Time in seconds since the start of the test (time step equals 0.0025 s).</li> <li>Acc_0 (m/s2): Acceleration signal measured in m/s<sup>2</sup> on the shaking table in the direction of excitation (Axis A-A).</li> <li>Acc_1 (m/s2): Acceleration response of the structure measured in m/s<sup>2</sup> on the first floor in the direction of excitation (Axis A-A).</li> <li>Acc_2 (m/s2): Acceleration response of the structure measured in m/s<sup>2</sup> on the second floor in the direction of excitation (Axis A-A).</li> <li>Acc_L (m/s2): Acceleration response of SDOF I measured in m/s<sup>2</sup> in the direction of excitation.</li> <li>Acc_F (m/s2): Acceleration response of SDOF II measured in m/s<sup>2</sup> in the direction of excitation.</li> <li>Acc_H (m/s2): Acceleration response of SDOF III measured in m/s<sup>2</sup> in the direction of excitation.</li> <li>Acc_G (m/s2): Acceleration response of the structure measured in m/s<sup>2</sup> on the second floor in the direction of excitation (Axis B-B).</li> <li>Acc_J (m/s2): Acceleration response of the structure measured in m/s<sup>2</sup> on the second floor in the transverse direction of excitation (Axis B-B).</li> <li>Dis_0 (mm): Displacement signal measured mm on the shaking table in the direction of excitation (Axis A-A).</li> <li>Dis_1 (mm): Displacement response of the structure measured in mm on the first floor in the direction of excitation (Axis A-A).</li> <li>Dis_2 (mm): Displacement response of the structure measured in mm on the second floor in the direction of excitation (Axis A-A).</li> </ul> <p>These data files can easily be uploaded using the pandas library in Python. For example by:</p> <pre><code>import pandas as pd df = pd.read_csv('1_IM_4mm.csv') time = df["Time (s)"] acc_0 = df["Acc_0 (m/s2)"] dis_0 = df["Dis_0 (mm)"]</code></pre> <h2>Contact:</h2> <p>Please send your enquiries regarding the shaking table to <a href="dynamics@lbb.rwth-aachen.de">dynamics@lbb.rwth-aachen.de</a>. Further information can be found on our <a href="https://www.lbb.rwth-aachen.de/cms/lbb/der-lehrstuhl/~bjlfvq/geraetezentzrum/?lidx=1">website</a>.</p> <h2>Usage/License:</h2> <ul> <li>The data is licensed under CC BY-SA 4.0.</li> <li>If you have used our data and are publishing your work, we ask you to please reference both <ul> <li>this database by its DOI, and</li> <li>any publication that is associated with the experiments. See the "References_v1.0.0.bib" for the associated publication references.</li> </ul> </li> </ul> <h2>Fundings:</h2> <ul> <li>Deutsche Forschungsgemeinschaft - <em>Grant number: INST 222/1161-1 FUGG</em>. Einaxialer Schwingtisch für dynamische Modell- und Bauteilversuche.</li> <li>Bundesministerium für Bildung und Forschung - <em>Grant number: 03G0892A</em>. ROBUST – Nutzerorientiertes Erdbebenfrühwarnsystem mit intelligenten Sensorsystemen und digitalen Bauwerksmodellen – Entwicklung Installation und Anwendung von sensorbasierten Monitoringsystemen mit BIM-Integration zur Echtzeit-Schadenerkennung in kritischen Infrastrukturen.</li> </ul>
Decarbonizing primary steel production : Techno-economic assessment of green steel production in Norway
<p>Python codes for the modelling of a grid connected Hydrogen direct reduced plant combined with an electrical arc furnace for steel production. </p>
Stiffness of randomly sampled stainless steel frames under gravity and gravity plus wind load scenarios
<p>Data was generated using the general purpose finite element software ABAQUS and performing advanced nonlinear analyses. The database is comprised of vertical and lateral system stiffness values corresponding to different random samples of six different nominal stainless steel frames under gravity and gravity plus wind load combinations. The values of the random variable assignments are given for each case. </p> <p>The full details of the finite element model can be found in: Arrayago, I.; Rasmussen, K.J.R. Reliability of stainless steel frames designed using the Direct Design Method in serviceability limit states. Journal of Constructional Steel Research 196, 107425, 2022. DOI: https://doi.org/10.1016/j.jcsr.2022.107425</p> <p>The data included in the dataset corresponds to the vertical & lateral stiffness of each frame under different load conditions.</p> <p>Although the data has been generated using the finite element software ABAQUS, no special software is required to read or interpret the data.</p>
TCM: Benchmark Datasets for Predictive Maintenance in Steel Manufacturing
<h1>Anomaly-TCM</h1> <p>Predictive Maintenance (PdM) is a strategy that uses advanced data analytics to predict equipment failures and maintain industrial machinery in good condition. Its goals are to minimize downtime, reduce operational costs, and ensure product quality. PdM methods are applicable across various industries, including steel manufacturing.</p> <p>In steel production, cold rolling is a critical process that reduces the thickness of hot-rolled steel. Developing PdM methods for tandem cold mills (TCM) can significantly improve production efficiency. However, researchers often rely on real manufacturing data, which is typically unavailable, unlabeled, and noisy, making it difficult to validate and compare methods.</p> <p>To overcome this, we created synthetic datasets for the cold rolling process to identify anomalies based on physical principles. These datasets were generated using a mathematical model of a 5-stand TCM, calculating key process parameters like rolling force, torque, speed, tension, gap, thickness reduction, and motor power. We introduced anomalies related to specific failures in the process.</p> <p>We produced six diverse datasets, each with varying complexity, to enable benchmarking of machine learning-based PdM methods for the cold rolling process. Four different types of anomalies were introduced, which are related to a physics-based deviations in the process:</p> <ol> <li>Anomaly in reduction scheme</li> <li>Anomaly in work roll (increased work roll friction)</li> <li>Anomaly in bearing (increased motor torque)</li> <li>Anomaly in electric motor (decrease efficiency)</li> </ol> <p> The details of the datasets are provided below.</p> <table> <tbody> <tr> <td><strong>Dataset</strong></td> <td><strong>Observations</strong></td> <td><strong>Anomalies</strong></td> <td><strong>Share of Anomalies</strong></td> <td><strong>Features</strong></td> <td><strong>Anomaly Types</strong></td> <td><strong>Products</strong></td> <td><strong>Data Drift</strong></td> </tr> <tr> <td>tcm5_dataset_1</td> <td>20009</td> <td>1045</td> <td>5.2%</td> <td>51</td> <td>1</td> <td>4</td> <td>FALSE</td> </tr> <tr> <td>tcm5_dataset_2</td> <td>20001</td> <td>1035</td> <td>5.2%</td> <td>51</td> <td>1</td> <td>20</td> <td>FALSE</td> </tr> <tr> <td>tcm5_dataset_3</td> <td>20003</td> <td>981</td> <td>4.9%</td> <td>51</td> <td>4 (16)</td> <td>4</td> <td>FALSE</td> </tr> <tr> <td>tcm5_dataset_4</td> <td>20001</td> <td>925</td> <td>4.6%</td> <td>51</td> <td>4 (16)</td> <td>20</td> <td>FALSE</td> </tr> <tr> <td>tcm5_dataset_5</td> <td>20005</td> <td>1031</td> <td>5.2%</td> <td>51</td> <td>4 (16)</td> <td>5</td> <td>TRUE</td> </tr> <tr> <td>tcm5_dataset_6</td> <td>20008</td> <td>954</td> <td>4.8%</td> <td>51</td> <td>4 (16)</td> <td>25</td> <td>TRUE</td> </tr> </tbody> </table> <p> </p> <p>Each dataset is generated as a data stream, meaning the observations follow a chronological order, represented by increasing work roll mileage (which is reset after a predefined threshold). The table below provides details about the features and labels present in the datasets. Several features are recorded for each rolling stand, totaling 51 features. Apart from the anomaly related to reduction, the other anomalies are specific to individual stands, resulting in 16 anomaly labels in total.</p> <table> <tbody> <tr> <td><strong>Feature</strong></td> <td><strong>Suffixes</strong></td> <td><strong>Unit</strong></td> <td><strong>Description</strong></td> </tr> <tr> <td>thickness_entry</td> <td>-</td> <td>mm</td> <td>steel entry thickness</td> </tr> <tr> <td>thickness_exit</td> <td>-</td> <td>mm</td> <td>steel exit thickness</td> </tr> <tr> <td>width</td> <td>-</td> <td>mm</td> <td>steel width</td> </tr> <tr> <td>ys_entry</td> <td>-</td> <td>MPa</td> <td>steel entry yield strength</td> </tr> <tr> <td>ys_exit</td> <td>-</td> <td>MPa</td> <td>steel exit yield strength</td> </tr> <tr> <td>work_roll_diam</td> <td>1 to 5</td> <td>mm</td> <td>work roll diamaeter (stands 1 to 5)</td> </tr> <tr> <td>work_roll_mileage</td> <td>1 to 5</td> <td>km</td> <td>work roll mileage (stands 1 to 5)</td> </tr> <tr> <td>reduction</td> <td>1 to 5</td> <td>-</td> <td>thickness reduction (stands 1 to 5)</td> </tr> <tr> <td>tension</td> <td>0 to 5</td> <td>N</td> <td>interstand tension (0 is tension before stand 1, 1-5 refer to tension after stands 1-5)</td> </tr> <tr> <td>roll_speed</td> <td>1 to 5</td> <td>NaN</td> <td>linear work roll speed (stands 1 to 5)</td> </tr> <tr> <td>force</td> <td>1 to 5</td> <td>N</td> <td>rolling force (stands 1 to 5)</td> </tr> <tr> <td>torque</td> <td>1 to 5</td> <td>Nm</td> <td>rolling torque (stands 1 to 5)</td> </tr> <tr> <td>gap</td> <td>1 to 5</td> <td>mm</td> <td>stand gap (stands 1 to 5)</td> </tr> <tr> <td>motor_power</td> <td>1 to 5</td> <td>kW</td> <td>electric motor power (stands 1 to 5)</td> </tr> <tr> <td>Anomaly_Reduction</td> <td>-</td> <td>-</td> <td>(label) anomaly in reduction scheme</td> </tr> <tr> <td>Anomaly_Electric</td> <td>1 to 5</td> <td>-</td> <td>(label) anomaly in electric motor (stands 1 to 5)</td> </tr> <tr> <td>Anomaly_Bearing</td> <td>1 to 5</td> <td>-</td> <td>(label) anomaly in stand bearing (stands 1 to 5)</td> </tr> <tr> <td>Anomaly_WorkRoll</td> <td>1 to 5</td> <td>-</td> <td>(label) anomaly in work roll friction (stands 1 to 5)</td> </tr> </tbody> </table>
FIB-SEM tomograms of the steel-concrete interface of mortar and concrete specimens
<p>This datasets contains tomograms showing the steel-concrete interface of mortar (files starting with NCI) and concrete (files starting with CI) specimens. They were acquired by a FIB-SEM (focused ion beam-scanning electron microscope).</p> <p>There are five datasets:</p> <ol> <li>NCI-1, with a voxel size of 30 nm</li> <li>NCI-2, with a voxel size of 50 nm</li> <li>NCI-3, with a voxel size of 50 nm, consisting of four microscopy sessions (A, B, C, D)</li> <li>NCI-4, with a voxel size of 30 nm, consisting of four microscopy sessions (A, B, C, D)</li> <li>CI, with a voxel size of 30 nm, consisting of six microscopy sessions (A, B, C, D, E, F)</li> </ol> <p>More information can be found here: (TBD)</p> <p> </p> <p> </p>
Database of Residual Stress Measurements on Hot-rolled Wide Flange Steel Cross Sections
<p><a href="https://zenodo.org/deposit/7677600#:~:text=Delete-,Data_info.csv,-md5%3A98a0f787ce2ea1b81d42ac898f6bb110">Data_info.csv</a>: Database of 'Residual Stress Measurements on Hot-rolled Wide Flange Steel Cross Sections' including cross-sectional and material characteristics as well as information relevant to ploting the residual stress distributions.</p> <p><a href="https://zenodo.org/deposit/7677600#:~:text=7%20kB-,Distributions.zip,-md5%3Af7f66a9ad607f27edde3dc7438b82ad2">Distributions.zip</a>: Residual stress distributions for the web and the flanges. To be unziped and positioned at the same location with the 'Data_info.csv', 'Processor.m' and 'QP_Coefficients' folder.</p> <p><a href="https://zenodo.org/deposit/7677600#:~:text=197%20kB-,Processor.m,-md5%3A29935e24d40cbd4398d260124ec71fa8">Processor.m</a>: MATLAB code that plots the residual stress distributions of a selected research work.</p> <p><a href="https://zenodo.org/deposit/7677600#:~:text=16%20kB-,QP_Coefficients.zip,-md5%3Aafd1a8771cf39c9c6584331d10030d96">QP_Coefficients.zip</a>: Coefficients of a proposed optimization method to fit the measured residual stresses in the web and the flanges. To be unziped and positioned at the same location with the 'Data_info.csv', 'Processor.m' and 'Distributions' folder.</p>
Scanning electron diffraction tilt series data of an aluminium-steel interface region
<p>This dataset contains scanning electron diffraction (SED) data used in the publication entitled "<strong>Microstructural and mechanical characterisation of a second generation hybrid metal extrusion & bonding aluminium-steel butt joint</strong>". The data denoted “SED_HYB_...” were recorded from an aluminium-steel interface region that includes aluminium and steel grains, an interfacial Al-Fe-Si layer, and dispersoids and some oxide particles located within the aluminium region. The nanoscale interfacial intermetallic phase layer is polycrystalline, and to increase the probability of recording data from intermetallic phase crystals oriented close to zone axes, the data were recorded in a tilt series covering 30 degrees, in steps of 1 degree. The file names give the goniometer x-tilt values in degrees, e.g. " SED_HYB_TX-150.hdf5" denotes an x-tilt of -15.0 degrees. SED data recorded from an Au cross-grating specimen, named "SED_AuX.hdf5", and from a MoO3 specimen, named "SED_MoO3.hdf5", are also included for calibration purposes.</p>
Estimating TOF from ultrasound signal over bare steel sample of 5 mm thickness
<p>These data have been obtained using the CEIT ultrasound testbed exciting a PZT piezoelectric sensor with a +/-15 volts pulse located over a 5 mm bare steel sample. The testbed receives the ultrasound response and estimates the TOF measuring the distance between two consecutive echoes. The aim is to develop an embedded system to measure the loss of thickness produced by corrosion.</p>
Global physical input-output tables for iron and steel (2008-2017).
<p><strong>Dataset:</strong> Global physical input-output tables for iron and steel</p> <p><strong>Years:</strong> 2008-2017</p> <p><strong>Base classification:</strong> 32 regions, 39 processes and 30 flows</p> <p><strong>Associated journal article: </strong>The PIOLab - Building global physical input-output tables in a virtual laboratory (forthcoming, Journal for Industrial Ecology)</p> <p><strong>Associated GitHub repository</strong>: www.github.com/fineprint-global/PIOLab</p> <p><strong>Contact:</strong> hanspeter.wieland@wu.ac.at</p> <p>The folder <em>RawData</em> contains the unprocessed results of the reconciliation run in the PIOLab. These tables (in the Tvy format) form the basis for the R scripts that are available from the GitHub repository mentioned above. Please note the instructions on GitHub for further information and how i.e. where the content of <em>RawData</em> needs to be stored in your local repository.</p> <p>The folder <em>gPSUT</em> contains the processed physical supply-use tables, including final use matrices and boundary input and output blocks. The variable names are described in detail in the method section of the journal article.</p> <p>The folder <em>gPIOT</em> contains the process-by-process IO model, which was used for the calculation of the footprint indicators in the Journal article. Please read the information on the footprint calculus in the journal article.</p> <p>The folder<em> Diagnostics </em>contains, for all years of the time series, results from the analyses of the constraint realization. The journal article presents only the diagnostic test for the year 2008.</p>
DHM Tensile Loading of 316L Stainless Steel
<p>Video <em><strong>3D.avi</strong></em> shows the in-situ observation and height measurement of the tensile deformation of 316L stainless steel by DHM</p> <p>Video <em><strong>Plot of aligned stack.avi</strong></em> shows the measured height profile of the segment indicated in image <em><strong>ROI.jpg</strong></em></p> <p>Inoue Laboratory - Materials Infomatics in Physical Metallurgy Lab, Institute of Industrial Science, The University of Tokyo</p>
Experimental load-displacement response of a stainless steel specimen under cyclic loading
<p>Experimental load-displacement data was obtained by testing a autenitic stainless steel RHS member under cyclic bending around its major axis following a cantilever loading scheme. The database is comprised of the horizontal displacement measured by a string potentiometer attached at the free end of the specimen and the horizontal force introduced by the actuator. </p> <p>The data corresponds to the specimen named S1-L1, which was an austenitic stainless steel RHS specimen, with a cross-section S1 (120 × 80 × 6 mm) and an effective length of L1 = 1650 mm. </p> <p>The full details of the experimental test can be found in: González-de-León I., Nastri E., Arrayago I., Montuori R., Piluso V., Real E. Experimental study on stainless steel tubular members under cyclic loading. Thin-Walled Structures 181, 109969, 2022. DOI: https://doi.org/10.1016/j.tws.2022.109969.</p>
Database of Uniaxial Shaking Table Tests for a Two-Storey Steel-Frame Structure
<h2>Description:</h2> <p>This data set contains data from experiments conducted on a two-storey steel-frame structure, involving sine-sweep, white noise, impulse, and earthquake loading. The experiments were carried out using a uniaxial shaking table of the <a href="https://www.lbb.rwth-aachen.de/go/id/eaxh/">Institute of Structural Analysis and Dynamics (LBB) - RWTH Aachen University</a>, in cooperation with the <a href="https://www.stb.rwth-aachen.de/cms/~iozv/STB/">Institute of Structural Steel (STB) - RWTH Aachen</a> and the <a href="https://www.cwe.rwth-aachen.de/home-2/">Center for Wind and Earthquake Engineering (CWE) – RWTH Aachen</a>.</p> <h3>Test structure:</h3> <p>The test structure was a two-storey, single-bay moment resisting frame (MRF) in the direction of excitation. In the perpendicular direction, a concentrically braced system provided lateral stability. The dimensions of the test structure were: 2.40 m length, 2.40 m width, and 3.78 m total height. Each floor had a distinct height: 2.02 m for the first floor and 1.76 m for the second. The moment resisting connections were realized as bolted extended unstiffened endplate joints. The column web panel was strengthened by two supplementary web plates (SWP) and continuity plates (CP). The base plate was meticulously modified to allow for rotation movement in order to approximate a pinned boundary condition. In addition, diaphragm action was ensured using diagonally arranged L-profiles in the plane of each floor. For additional mass, four steel I-profiles, each weighting 1650 kg were attached to the main structure (2 on each floor) and were secured by using steel U-profiles. An industrial pressure vessel with a self-weight of 100 kg, which remained empty for the first phase of the experimental campaign, was additionally mounted on the first floor. </p> <p>The properties of the frame structure are:</p> <ul> <li>Columns: HEA200 S355-J2 + 2 SWP + 6 CP</li> <li>Beams: HEA160 S235-JR</li> <li>Bolts: 8x M16, 10.9 HV</li> <li>Joints: Partial strength, semi-rigid</li> <li>End-plate: 272x190x8 mm</li> <li>Welds: Full penetration groove welds</li> </ul> <h3>Test setup:</h3> <p>The shaking table specifications are:</p> <ul> <li>Table size: 3.0x3.0 m</li> <li>Max. specimen mass: 10 t</li> <li>Max. overturning moment: 30 m t</li> <li>Max. actuator stroke: +/- 250 mm</li> <li>Max. table velocity: +/- 1 m/s at rated load</li> <li>Max. table acceleration: +/- 1g at rated load</li> <li>Test frequency: 0 to 50 Hz</li> </ul> <p>The instrumentation scheme of the test setup consisted mainly of accelerometers, displacement tranducers and strain gauges, measuring the excitation provided by the shaking table and the response of the structure. Regarding the global response of the test structure, the recordings of the accelerometers and displacement tranducers indicated in the uploaded file 'Instrumentation_Scheme_v1.0.0.pdf' are provided. </p> <p>The properties of the accelerometers are:</p> <ul> <li>Type: M3701-series</li> <li>Manufacturer: PCB Piezotronics, Inc.</li> <li>Measurement range: +/- 3g</li> <li>Frequency range: 0-500 Hz</li> <li>Sensitivity: 900 mV/g</li> <li>Resolution: 2.2e-5g</li> <li>Noise: 1 µg/Hz<sup>-0.5</sup></li> </ul> <p>The properties of the displacement tranducers are:</p> <ul> <li>Type: LZW-M-500</li> <li>Manufacturer: WayCon Positionsmesstechnik GmbH</li> <li>Measurement range: +/- 250 mm</li> <li>Linearity: +/- 0.05%</li> <li>Repeatability: 0.01 mm</li> <li>Displacement force: ≤15 N</li> <li>Displacement speed: ≤5 m/s</li> </ul> <h2>Files:</h2> <ul> <li>Load_Protocols_v1.0.0.pdf <ul> <li>.pdf file listing all load protocols applied to the structure.</li> </ul> </li> <li>Time_Histories_v1.0.0.pdf <ul> <li>.pdf file displaying the acceleration and displacement time histories according to the load protocols.</li> </ul> </li> <li>Data_v1.0.0.zip <ul> <li>Contains all data files according to the load protocols.</li> <li>The experimental data is provided as .csv files for each load protocol. The experiments are named by the load protocol. A .pdf file contains the corresponding data plots.</li> </ul> </li> <li>References_v1.0.0.bib <ul> <li>Contains a bibtex reference with the associated publications.</li> </ul> </li> <li>Shake_Table.jpg <ul> <li>Photo of the shaking table without any specimen.</li> </ul> </li> <li>Test_Structure_v1.0.0.jpg <ul> <li>Photo of the shaking table including the test structure.</li> </ul> </li> <li>Test_Structure_Sketch_v1.0.0.pdf <ul> <li>.pdf file illustrating the test structure.</li> </ul> </li> <li>Instrumentation_Scheme_v1.0.0.pdf <ul> <li>.pdf file illustrating the sensor placements on the test structure.</li> </ul> </li> </ul> <h2>File format of the data sets:</h2> <p>The data is stored in .csv files, where each file contains the following columns:</p> <ul> <li>Time: Time in seconds since the start of the test (time step equals 0.003 s).</li> <li>Acc_0: Acceleration signal measured in m/s<sup>2</sup> on the shaking table.</li> <li>Acc_1: Acceleration response of the structure measured in m/s<sup>2</sup> on the first floor.</li> <li>Acc_2: Acceleration response of the structure measured in m/s<sup>2</sup> on the second floor.</li> <li>Disp_0: Displacement signal measured mm on the shaking table.</li> <li>Disp_1: Displacement response of the structure measured in mm on the first floor.</li> <li>Disp_2: Displacement response of the structure measured in mm on the second floor.</li> </ul> <p>These data files can easily be uploaded using the pandas library in Python. For example by:</p> <pre><code>import pandas as pd df = pd.read_csv('LP01_Sweep_001.csv') time = df["Time"] acc_0 = df["Acc_0"] disp_0 = df["Disp_0"]</code></pre> <h2>Contact:</h2> <p>Please send your enquiries regarding the shaking table to <a href="dynamics@lbb.rwth-aachen.de">dynamics@lbb.rwth-aachen.de</a>. Further information can be found on our <a href="https://www.lbb.rwth-aachen.de/go/id/eaxh/">website</a>.</p> <h2>Usage/License:</h2> <ul> <li>The data is licensed under CC BY-SA 4.0.</li> <li>If you have used our data and are publishing your work, we ask you to please reference both <ul> <li>this database by its DOI, and</li> <li>any publication that is associated with the experiments. See the "References_v1.0.0.bib" for the associated publication references.</li> </ul> </li> </ul> <h2>Fundings:</h2> <ul> <li>Deutsche Forschungsgemeinschaft - <em>Grant number: INST 222/1161-1 FUGG</em>. Einaxialer Schwingtisch für dynamische Modell- und Bauteilversuche.</li> <li>Bundesministerium für Bildung und Forschung - <em>Grant number: 03G0892A</em>. ROBUST – Nutzerorientiertes Erdbebenfrühwarnsystem mit intelligenten Sensorsystemen und digitalen Bauwerksmodellen – Entwicklung Installation und Anwendung von sensorbasierten Monitoringsystemen mit BIM-Integration zur Echtzeit-Schadenerkennung in kritischen Infrastrukturen.</li> </ul> <p> </p>
Strain path change characterization of dual-phase steel (DP780) using non-linear strain path experiments: true strain-stress and equivalent strain-stress data
<p>Strain path change characterization of dual-phase steel (DP780) using non-linear strain path experiments: true strain-stress and equivalent strain-stress data.</p>
Nonlinear macro-model for OpenSEES simulation of composite steel beams
<p>The dataset consist of the following:</p> <p>1- Source_Code.zip</p> <p>This folder includes the subroutines that can be used to implement the macro-model for simulating the hysteretic behavior of composite steel beams. The README.txt file provides a description of each subroutine </p> <p>2- Nonlinear_Models.zip</p> <p>This folder includes the nonlinear building models. The README.txt file explains the procedure to run nonlinear static or dynamic analysis.</p> <p>3- Incremental_Dynamic_Analysis_Results.zip</p> <p>This folder includes the IDA results for each building at three different sites. The README.txt file provides a description of the data.</p> <p>4- Ground_Motion_Sets.zip</p> <p>This folder includes the ground motion records for four different sites at two different return periods: 475 and 2475 years. The site hazard curves are also included. A description of the hazard analysis, disaggregation and record selection is provided in PSHA_Report.doc</p>
[Dataset] In situ laser-ultrasonic monitoring of Poisson's ratio and bulk sound velocities of steel plates during thermal processes
<p>Data generated and analyzed in the work titled "In situ laser-ultrasonic monitoring of Poisson’s ratio and bulk sound velocities of steel plates during thermal processes". See the associated publication for more context.</p> <p>All files are stored in Matlab's binary MAT-file format.</p> <ul> <li>cutOffs_ZGVs_nu_S1S2_A2A3_S3S6_A4A7.mat <ul> <li>Dispersion relation data of plates obtained from numerical calculation with a range of Poisson's ratios and otherwise arbitrary but fixed material properties.</li> <li>S1S2-, A2A3-, S3S6- and A4A7-ZGV resonance frequencies and k-values</li> <li>L1 and T1 thickness resonance frequencies</li> </ul> </li> <li>lusResults_jmat_dilatometry_data.mat <ul> <li>LUS measurement data and resulting material properties (raw displacement data recorded on the oscilloscope is stored separately to keep the file size reasonable.)</li> <li>Dilatometer measurements</li> <li>JMatPro simulation</li> </ul> </li> <li>lusOscilloscope_data.mat <ul> <li>Normal surface displacement measurement data obtained in situ with LUS and recorded with an oscilloscope</li> </ul> </li> </ul>
ScienceDex guides
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