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Isochromatic-Art: A Computational Dataset for Digital Photoelasticity Studies

Author

Listed:
  • Juan-Carlos Briñez-De-Leon

    (Grupo GIIAM, Facultad de Ingeniería, Institución Universitaria Pascual Bravo, Calle 73 No. 73A-226, Medellín 050034, Colombia)

  • Mateo Rico-Garcia

    (Grupo GIIAM, Facultad de Ingeniería, Institución Universitaria Pascual Bravo, Calle 73 No. 73A-226, Medellín 050034, Colombia)

  • Alejandro Restrepo-Martínez

    (Grupo GPIMA, Departamento de Ingeniería Mecánica, Facultad de Minas, Universidad Nacional de Colombia, Sede Medellín, Núcleo el Río, Bloque 04, Carrera 64C No. 63-120, Medellín 050034, Colombia)

Abstract

The importance of evaluating the stress field of loaded structures lies in the need for identifying the forces which make them fail, redesigning their geometry to increase the mechanical resistance, or characterizing unstressed regions to remove material. In such work line, digital photoelasticity highlights with the possibility of revealing the stress information through isochromatic color fringes, and quantifying it through inverse problem strategies. However, the absence of public data with a high variety of spatial fringe distribution has limited developing new proposals which generalize the stress evaluation in a wider variety of industrial applications. This dataset shares a variated collection of stress maps and their respective representation in color fringe patterns. In this case, the data were generated following a computational strategy that emulates the circular polariscope in dark field, but assuming stress surfaces and patches derived from analytical stress models, 3D reconstructions, saliency maps, and superpositions of Gaussian surfaces. In total, two sets of ‘101430’ raw images were separately generated for stress maps and isochromatic color fringes, respectively. This dataset can be valuable for researchers interested in characterizing the mechanical response in loaded models, engineers in computer science interested in modeling inverse problems, and scientists who work in physical phenomena such as 3D reconstruction in visible light, bubble analysis, oil surfaces, and film thickness.

Suggested Citation

  • Juan-Carlos Briñez-De-Leon & Mateo Rico-Garcia & Alejandro Restrepo-Martínez, 2022. "Isochromatic-Art: A Computational Dataset for Digital Photoelasticity Studies," Data, MDPI, vol. 7(11), pages 1-11, November.
  • Handle: RePEc:gam:jdataj:v:7:y:2022:i:11:p:151-:d:959592
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