{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,9]],"date-time":"2026-01-09T21:35:01Z","timestamp":1767994501772,"version":"3.49.0"},"reference-count":23,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,3,22]],"date-time":"2022-03-22T00:00:00Z","timestamp":1647907200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100003130","name":"Research Foundation - Flanders","doi-asserted-by":"publisher","award":["1SC0819N"],"award-info":[{"award-number":["1SC0819N"]}],"id":[{"id":"10.13039\/501100003130","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100007660","name":"University of Antwerp","doi-asserted-by":"publisher","award":["Antigoon ID 42339"],"award-info":[{"award-number":["Antigoon ID 42339"]}],"id":[{"id":"10.13039\/501100007660","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Algorithms"],"abstract":"<jats:p>We address the challenge of determining a valid set of parameters for a dynamic line scan thermography setup. Traditionally, this optimization process is labor- and time-intensive work, even for an expert skilled in the art. Nowadays, simulations in software can reduce some of that burden. However, when faced with many parameters to optimize, all of which cover a large range of values, this is still a time-consuming endeavor. A large number of simulations are needed to adequately capture the underlying physical reality. We propose to emulate the simulator by means of a Gaussian process. This statistical model serves as a surrogate for the simulations. To some extent, this can be thought of as a \u201cmodel of the model\u201d. Once trained on a relative low amount of data points, this surrogate model can be queried to answer various engineering design questions. Moreover, the underlying model, a Gaussian process, is stochastic in nature. This allows for uncertainty quantification in the outcomes of the queried model, which plays an important role in decision making or risk assessment. We provide several real-world examples that demonstrate the usefulness of this method.<\/jats:p>","DOI":"10.3390\/a15040102","type":"journal-article","created":{"date-parts":[[2022,3,22]],"date-time":"2022-03-22T14:55:35Z","timestamp":1647960935000},"page":"102","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Dynamic Line Scan Thermography Parameter Design via Gaussian Process Emulation"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-4109-8839","authenticated-orcid":false,"given":"Simon","family":"Verspeek","sequence":"first","affiliation":[{"name":"Faculty of Applied Engineering, Department Electromechanics, Research Group InViLab, University of Antwerp, Groenenborgerlaan 171, B 2020 Antwerp, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3060-262X","authenticated-orcid":false,"given":"Ivan","family":"De Boi","sequence":"additional","affiliation":[{"name":"Faculty of Applied Engineering, Department Electromechanics, Research Group InViLab, University of Antwerp, Groenenborgerlaan 171, B 2020 Antwerp, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8777-2008","authenticated-orcid":false,"given":"Xavier","family":"Maldague","sequence":"additional","affiliation":[{"name":"Computer Vision and Systems Laboratory, Department of Electrical and Computer Engineering, Universit\u00e9 Laval, Quebec City, QC G1V 0A6, Canada"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0921-1950","authenticated-orcid":false,"given":"Rudi","family":"Penne","sequence":"additional","affiliation":[{"name":"Faculty of Applied Engineering, Department Electromechanics, Research Group InViLab, University of Antwerp, Groenenborgerlaan 171, B 2020 Antwerp, Belgium"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9944-520X","authenticated-orcid":false,"given":"Gunther","family":"Steenackers","sequence":"additional","affiliation":[{"name":"Faculty of Applied Engineering, Department Electromechanics, Research Group InViLab, University of Antwerp, Groenenborgerlaan 171, B 2020 Antwerp, Belgium"}]}],"member":"1968","published-online":{"date-parts":[[2022,3,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Maldague, X. (1993). Nondestructive Evaluation of Materials by Infrared Thermography\u2013Xavier P.V. Maldague, Springer.","DOI":"10.1007\/978-1-4471-1995-1"},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Verspeek, S., Gladines, J., Ribbens, B., Maldague, X., and Steenackers, G. (2021). Dynamic Line Scan Thermography Optimisation Using Response Surfaces Implemented on PVC Flat Bottom Hole Plates. Appl. Sci., 11.","DOI":"10.3390\/app11041538"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Ibarra-Castanedo, C., Servais, P., Ziadi, A., Klein, M., and Maldague, X. (2014, January 7\u201311). RITA\u2013Robotized Inspection by Thermography and Advanced Processing for the Inspection of Aeronautical Components. 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Design and Modeling for Computer Experiments, Chapman and Hall\/CRC.","DOI":"10.1201\/9781420034899"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"455","DOI":"10.1023\/A:1008306431147","article-title":"Efficient Global Optimization of Expensive Black-Box Functions","volume":"13","author":"Jones","year":"1998","journal-title":"J. Glob. Optim."},{"key":"ref_18","first-page":"409","article-title":"Design and Analysis of Computer Experiments","volume":"4","author":"Sacks","year":"1989","journal-title":"Stat. Sci."},{"key":"ref_19","unstructured":"Buisson-Fenet, M., Solowjow, F., and Trimpe, S. (2020, January 11\u201312). Actively learning gaussian process dynamics. Proceedings of the 2nd Conference on Learning for Dynamics and Control, Online."},{"key":"ref_20","doi-asserted-by":"crossref","unstructured":"Pasolli, E., and Melgani, F. (2011, January 24\u201329). Gaussian process regression within an active learning scheme. 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