{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,14]],"date-time":"2026-02-14T09:00:09Z","timestamp":1771059609292,"version":"3.50.1"},"reference-count":36,"publisher":"MDPI AG","issue":"3","license":[{"start":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T00:00:00Z","timestamp":1740096000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Spanish Ministry of Science and Innovation","award":["PLEC2024-011165"],"award-info":[{"award-number":["PLEC2024-011165"]}]},{"name":"Euroregion Nouvelle-Aquitaine Euskadi Navarra","award":["PLEC2024-011165"],"award-info":[{"award-number":["PLEC2024-011165"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>The accurate prediction of weld bead geometry is crucial for ensuring the quality and consistency of wire and arc additive manufacturing (WAAM), a specific form of directed energy deposition (DED) that utilizes arc welding. Despite advancements in process control, predicting the shape and dimensions of weld beads remains challenging due to the complex interactions between process parameters and material behavior. This paper addresses this challenge by exploring the application of symmetrical neural networks to enhance the accuracy and reliability of geometric predictions in WAAM. By leveraging advanced machine learning techniques and incorporating the inherent symmetry of the welding process, the proposed models aim to precisely forecast weld bead geometry. The use of neuronal networks and experimental validation demonstrate the potential of symmetrical neural networks to improve prediction precision, contributing to more consistent and optimized WAAM outcomes.<\/jats:p>","DOI":"10.3390\/sym17030326","type":"journal-article","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T09:26:32Z","timestamp":1740129992000},"page":"326","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Application of Symmetric Neural Networks for Bead Geometry Determination in Wire and Arc Additive Manufacturing (WAAM)"],"prefix":"10.3390","volume":"17","author":[{"given":"Aitor","family":"Fern\u00e1ndez-Zabalza","sequence":"first","affiliation":[{"name":"Department of Engineering, Public University of Navarre, Los Pinos Building, Campus Arrosad\u00eda, E31006 Pamplona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9311-8635","authenticated-orcid":false,"given":"Fernando","family":"Veiga","sequence":"additional","affiliation":[{"name":"Department of Engineering, Public University of Navarre, Los Pinos Building, Campus Arrosad\u00eda, E31006 Pamplona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5181-1060","authenticated-orcid":false,"given":"Alfredo","family":"Su\u00e1rez","sequence":"additional","affiliation":[{"name":"TECNALIA, Basque Research and Technology Alliance (BRTA), Parque Cient\u00edfico, Parque Cient\u00edfico Tecnol\u00f3gico de Gipuzkoa, E20009 Saint Sebastian, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4120-7038","authenticated-orcid":false,"given":"Virginia","family":"Uralde","sequence":"additional","affiliation":[{"name":"Department of Engineering, Public University of Navarre, Los Pinos Building, Campus Arrosad\u00eda, E31006 Pamplona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5156-4784","authenticated-orcid":false,"given":"Xabier","family":"Sandua","sequence":"additional","affiliation":[{"name":"Department of Engineering, Public University of Navarre, Los Pinos Building, Campus Arrosad\u00eda, E31006 Pamplona, Spain"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4746-1018","authenticated-orcid":false,"given":"Jos\u00e9 Ram\u00f3n","family":"Alfaro","sequence":"additional","affiliation":[{"name":"Department of Engineering, Public University of Navarre, Los Pinos Building, Campus Arrosad\u00eda, E31006 Pamplona, Spain"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,21]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"e2390495","DOI":"10.1080\/17452759.2024.2390495","article-title":"State-of-Art Review on the Process-Structure-Properties-Performance Linkage in Wire Arc Additive Manufacturing","volume":"19","author":"Zhang","year":"2024","journal-title":"Virtual Phys. 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