{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,25]],"date-time":"2026-02-25T19:59:00Z","timestamp":1772049540315,"version":"3.50.1"},"reference-count":52,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000181","name":"Air Force Office of Scientific Research","doi-asserted-by":"publisher","award":["FA8655-22-1-7026"],"award-info":[{"award-number":["FA8655-22-1-7026"]}],"id":[{"id":"10.13039\/100000181","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000181","name":"Air Force Office of Scientific Research","doi-asserted-by":"publisher","award":["FA9550-19-1-7018"],"award-info":[{"award-number":["FA9550-19-1-7018"]}],"id":[{"id":"10.13039\/100000181","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Computation"],"abstract":"<jats:p>This paper concerns the application of a long short-term memory model (LSTM) for high-resolution reconstruction of turbulent pressure fluctuation signals from sparse (reduced) data. The model\u2019s training was performed using data from high-resolution computational fluid dynamics (CFD) simulations of high-speed turbulent boundary layers over a flat panel. During the preprocessing stage, we employed cubic spline functions to increase the fidelity of the sparse signals and subsequently fed them to the LSTM model for a precise reconstruction. We evaluated our reconstruction method with the root mean squared error (RMSE) metric and via inspection of power spectrum plots. Our study reveals that the model achieved a precise high-resolution reconstruction of the training signal and could be transferred to new unseen signals of a similar nature with extremely high success. The numerical simulations show promising results for complex turbulent signals, which may be experimentally or computationally produced.<\/jats:p>","DOI":"10.3390\/computation12010004","type":"journal-article","created":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T13:02:58Z","timestamp":1704114178000},"page":"4","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["LSTM Reconstruction of Turbulent Pressure Fluctuation Signals"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0103-5857","authenticated-orcid":false,"given":"Konstantinos","family":"Poulinakis","sequence":"first","affiliation":[{"name":"Institute for Advanced Modelling and Simulation, University of Nicosia, Nicosia CY-2417, Cyprus"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3300-7669","authenticated-orcid":false,"given":"Dimitris","family":"Drikakis","sequence":"additional","affiliation":[{"name":"Institute for Advanced Modelling and Simulation, University of Nicosia, Nicosia CY-2417, Cyprus"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9694-3764","authenticated-orcid":false,"given":"Ioannis W.","family":"Kokkinakis","sequence":"additional","affiliation":[{"name":"Institute for Advanced Modelling and Simulation, University of Nicosia, Nicosia CY-2417, Cyprus"}]},{"given":"S. Michael","family":"Spottswood","sequence":"additional","affiliation":[{"name":"Air Force Research Laboratory, Wright Patterson Air Force Base, OH 45433-7402, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9710-4978","authenticated-orcid":false,"given":"Talib","family":"Dbouk","sequence":"additional","affiliation":[{"name":"Complexe de Recherche Interprofessionnel en A\u00e9rothermochimie, University of Rouen, 675, Avenue de l\u2019Universit\u00e9, BP 12, 76801 Saint Etienne du Rouvray Cedex Rouen, France"}]}],"member":"1968","published-online":{"date-parts":[[2024,1,1]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Frank, M., Drikakis, D., and Charissis, V. (2020). Machine-Learning Methods for Computational Science and Engineering. 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