Isochromatic-Art: A Computational Dataset for Digital Photoelasticity Studies

Juan-Carlos Briñez- De-Leon (), Mateo Rico-Garcia and Alejandro Restrepo-Martínez
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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

Data, 2022, vol. 7, issue 11, 1-11

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.

Keywords: digital photoelasticity; isochromatic images; fringe patterns; stress field; birefringence; phase maps (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2022
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