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11 results for “Stone masonry”
DocumeNDT stone masonry walls geometry: Photogrammetric models dataset
<p>This repository contains detailed geometric data from six stone masonry walls constructed for an experimental campaign carried out at the laboratory of the Institute for Physical and Information Technologies (ITEFI), from the Spanish National Research Council (CSIC).</p> <p>The data set is structured in 2 levels of folders:<br> - At first level, the 6 folders correspond to the 6 tested stone masonry walls (Wall 1-6).<br> - At second level, for each wall, there are two folders. The first folder contains the photogrammetric model of each wall, e.g., "W1", and a photograph showing the wall. The second folders contains individual photogrammetric models of each stone composing the walls and their exact location within the walls, e.g., "Stone 101".</p> <p>The global coordinates of the general photogrammetry of the wall and the individual photogrammetries of the stones are the same. They can be imported in any viewer and will be correctly located.</p> <p>The geometric data is presented in .obj files that can be imported in any 3D modeling software.</p> <p>Please cite the following related publication:</p> <p>Ortega J, Meersman MFL, Aparicio S, Liébana JC, Martin R, Anaya JJ, Gonzalez M. An automated sonic tomography system for the inspection of historical masonry walls (2023)</p>
DocumeNDT stone masonry walls tomographic inspection dataset
<p>This repository contains data from the sonic tomography inspections of six stone masonry walls constructed for an experimental campaign carried out at the laboratory of the Institute for Physical and Information Technologies (ITEFI), from the Spanish National Research Council (CSIC).</p> <p>The data set is structured in 2 levels of folders:<br> - At first level, the 6 folders correspond to the 6 tested stone masonry walls (Wall 1-6).<br> - At second level, for each wall, there are three folders:<br> - The folder 'Coordinates' contains: (1) the coordinates of the emission and reception points; (2) diagrams of the emission and reception locations in elevation; and (3) readme file with specific details about the inspection, e.g., number of emission and reception points<br> - The folder 'Emission raw signal' contains the recorded emission signal for each emission location<br> - The folder 'Reception raw signal' contains the recorded reception signal for each emission location</p> <p>Sonic data are presented in .csv files, structured in columns. Each column correspond to a reception location. The values correspond to the voltage recorded. </p> <p>The frequency of acquisition is 256000 samples/s.</p> <p>Please cite the following related publication:</p> <p>Ortega J, Meersman MFL, Aparicio S, Liébana JC, Martin R, Anaya JJ, Gonzalez M. An automated sonic tomography system for the inspection of historical masonry walls (2023)</p>
CRACK-CH: A Crack detection and classification dataset on complex stone masonry surfaces
<p><strong>Description</strong></p> <p>This dataset includes various images with cracks from the test sites of HYPERION H2020 project (Grant Agreement No. 821054). Specifically, square image patches of 224x224 pixels from the test sites of Naillac and St. Nikolaos Fort are included.</p> <p>The Saint Nikolaos Fort is an important part of the great fortifications of the Medieval City of Rhodes located at the entrance of the Mantraki port. At this location, there was just a chapel dedicated to Saint Nikolaos until 1464, when it was turned to a fortification. Since then it has undergone reinforcements and expansions in order to defend the city. The outer walls were built in 1480 AD and in 1863 AD it was finally transformed to a lighthouse. The second study area is the Naillac at Saint Paul’s rampart where a monumental tower was located as part of the fortification of the Commercial Harbour of Rhodes. It was constructed around 1400 AD on the Hellenistic Pier, but it was destroyed in 1863 after a severe earthquake. In 2017, the Naillac Tower was graphically reconstructed and presented as it stood until 1863, during the Ottoman rule. The Rodini Roman Bridge is one of the few ancient bridges surviving in Greece and part of the Hellenistic fortification of the city, making it a monument of great importance. It was built across the stream of Rhodini, situated outside the Medieval City and has two arched openings. The Roman Bridge is in continuous use until today and its static efficiency has deteriorated, while the scaffoldings which now support the arches are gradually rusting and losing their efficiency. Those images were split into two separate categories, facilitating the later training and evaluation of the model: “Cracks” and “No cracks”.</p> <p>The dataset is used to train and evaluate the CNN models for crack detection on complex stone masonry surfaces.</p> <p><strong>Publication</strong></p> <p>The paper is availbale here: https://arxiv.org/abs/2303.17989</p> <p><strong>If you use this dataset please cite it as CRACK-CH [reference]</strong>.<br> [Reference] Agrafiotis, Panagiotis, Doulamis, Anastasios, and Georgopoulos, Andreas. (2023) "Unsupervised crack detection on complex stone masonry surfaces", <em>arXiv preprint arXiv:2303.17989</em><br> <br> Bibtex entry:</p> <p>@misc{agrafiotis2023unsupervised,<br> title={Unsupervised crack detection on complex stone masonry surfaces}, <br> author={Panagiotis Agrafiotis and Anastastios Doulamis and Andreas Georgopoulos},<br> year={2023},<br> eprint={2303.17989},<br> archivePrefix={arXiv},<br> primaryClass={cs.CV}<br> }</p>
Experimental data on plastered rubble stone masonry walls
<p>This repository contains data from experimental tests on plastered rubble stone masonry walls conducted at École Polytechnique Fédérale de Lausanne (EPFL) in Switzerland. </p> <p><strong>Data visualization in RENKU</strong>: <a href="https://renkulab.io/projects/eesd.epfl/plastered-rubble-stone-masonry-walls">Click here</a></p> <p>Please cite the following related publications:</p> <blockquote> <p><br> [1] Rezaie, A., Godio, M., Beyer, K. (2020). Experimental investigation of strength, stiffness and drift capacity of rubble stone masonry walls. Construction and Building Materials, 251, 118972.</p> <p> </p> <p>[2] Rezaie, A., Achanta, R., Godio, M., Beyer, K. (2020). Comparison of crack segmentation using digital image correlation measurements and deep learning. Construction and Building Materials, 261, 120474.</p> <p> </p> <p>[3] Rezaie, A., Godio, M., & Beyer, K. (2021). Investigating the cracking of plastered stone masonry walls under shear–compression loading. Construction and Building Materials, 306, 124831.</p> <p><br> [4] Rezaie, A., Godio, M., Achanta, R., & Beyer, K. (2022). Machine-learning for damage assessment of rubble stone masonry piers based on crack patterns. <em>Automation in Construction</em>, <em>140</em>, 104313.</p> </blockquote>
Dataset: Quasi-static shear-compression tests on stone masonry walls with plaster: Influence of load history and axial load ratio
<p>This repository contains the results of six quasi-static cyclic shear-compression tests performed on single-leaf stone masonry walls made of limestone blocks and lime-based mortar joints. Of the six walls, four are tested under different axial load ratios, performing a cyclic load history with two cycles per increasing drift demand. Three are tested under the same axial load ratio but are subjected to different load histories, namely, one monotonic loading, one cyclic loading with two cycles per drift level and one cyclic loading with one hundred cycles per drift level.</p> <p>Results and details of the tests are reported in:</p> <blockquote> <p>Godio M, Vanin F, Zhang S, Beyer K (2019). “Quasi-Static Shear-Compression Tests on Stone Masonry Walls with Plaster: Influence of Load History and Axial Load Ratio.” Engineering Structures 192: 264–78. <a href="https://doi.org/10.1016/j.engstruct.2019.04.041">https://doi.org/10.1016/j.engstruct.2019.04.041</a> </p> </blockquote>
Quasi-static cyclic shear-compression tests on plastered rubble stone masonry walls - Experimental data
<p>This dataset contains quasi-static cyclic shear-compression tests on six large-scale rubble stone masonry walls plus two example point clouds created from two specimens.</p> <p> </p>
Estimates for the stiffness, strength and drift capacity of stone masonry walls based on 123 quasi-static cyclic tests reported in the literature
<p>Database of 123 shear and compression tests on stone masonry walls reported in the literature. Test references, geometrical and typological data, loading and boundary conditions, mechanical characterisation data, and synthetic test results are collected. Such test results include failure mode, force and displacement capacities for different limit states and estimates of the elastic and effective stiffness. Hysteretic force-displacement curves, digitalised from the sources, and the derived envelopes are provided, when available, as .csv files.</p>
Dataset for geometrical digital twins of the as-built microstructure of three-leaf stone masonry walls with laser scanning
<p>This repository contains the dataset from the geometrical digital twinning of the as-built microstructure of three-leaf stone masonry walls of 700mm x 700 mm x 400 mm (Height x Length x Width) with laser scanning. It includes raw and processed data and data analysis scripts. A Readme file explains the structure of the dataset and the contents of each folder. The dataset corresponds to the journal paper <strong><em>Geometrical digital twins of the as-built microstructure of three-leaf stone masonry walls with laser scanning</em></strong> published on Scientific data https://doi.org/10.1038/s41597-023-02417-3.</p> <p>Please, cite as:</p> <p>Saloustros, S., Settimi, A., Ascencio, A.C., Gamerro, J, Weinand, Y., Beyer, K. Geometrical digital twins of the as-built microstructure of three-leaf stone masonry walls with laser scanning. <em>Sci Data</em> <strong>10</strong>, 533 (2023). https://doi.org/10.1038/s41597-023-02417-3</p>
Historical stone masonry road structure
These structures seem to be frequently built next to roads Source: Objaverse 1.0 / Sketchfab
Dataset for image-based geometric digital twinning for stone masonry elements
<p>This is the dataset used to assess the performance of the geometrical digital twinning algorithm proposed by Pantoja-Rosero et, al (2023) in the article "Image-based geometric digital twinning for stone masonry elements" (<a href="https://doi.org/10.1016/j.autcon.2022.104632">https://doi.org/10.1016/j.autcon.2022.104632</a>)</p>
Dataset for image-based geometric digital twinning for stone masonry elements - part 2
<p>This is the dataset used to assess the performance of the geometrical digital twinning algorithm proposed by Pantoja-Rosero et, al (2023) in the article "Image-based geometric digital twinning for stone masonry elements" (<a href="https://doi.org/10.1016/j.autcon.2022.104632">https://doi.org/10.1016/j.autcon.2022.104632</a>)</p>
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International Brain Laboratory public data
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OpenNeuro
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