{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,26]],"date-time":"2026-06-26T20:57:27Z","timestamp":1782507447894,"version":"3.54.5"},"reference-count":77,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2024,7,31]],"date-time":"2024-07-31T00:00:00Z","timestamp":1722384000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>This study investigates the methods for controlling porosity in thermal pipes manufactured using selective laser melting (SLM) technology. Experiments conducted include water permeability tests and surface roughness measurements, which are complemented by SEM image ML-based analysis for pore recognition. The results elucidate the impact of SLM printing parameters on water permeability. Specifically, an increase in hatch and point distances leads to a linear rise in permeability, while higher laser power diminishes permeability. Using machine learning (ML) techniques, precise pore identification on SEM images depicting surface microstructures of the samples is achieved. The average percentage of the surface area containing detected pores for microstructure samples printed with laser parameters (laser power (W) _ hatch distance (\u00b5m) _ point distance (\u00b5m)) 175_ 80_80 was found to be 5.2%, while for 225_120_120, it was 4.2%, and for 275_160_160, it was 3.8%. Pore recognition was conducted using the Haar feature-based method, and the optimal patch size was determined to be 36 pixels on monochrome images of microstructures with a magnification of 33\u00d7, which were acquired using a Leica S9 D microscope.<\/jats:p>","DOI":"10.3390\/s24154959","type":"journal-article","created":{"date-parts":[[2024,7,31]],"date-time":"2024-07-31T10:34:43Z","timestamp":1722422083000},"page":"4959","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Controlled Porosity of Selective Laser Melting-Produced Thermal Pipes: Experimental Analysis and Machine Learning Approach for Pore Recognition on Pipes Surfaces"],"prefix":"10.3390","volume":"24","author":[{"ORCID":"https:\/\/orcid.org\/0009-0008-8986-402X","authenticated-orcid":false,"given":"Ivan","family":"Malashin","sequence":"first","affiliation":[{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-1563-4036","authenticated-orcid":false,"given":"Dmitry","family":"Martysyuk","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3959-2969","authenticated-orcid":false,"given":"Vadim","family":"Tynchenko","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4263-2367","authenticated-orcid":false,"given":"Vladimir","family":"Nelyub","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia"},{"name":"Scientific Department, Far Eastern Federal University, 690922 Vladivostok, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9648-2395","authenticated-orcid":false,"given":"Aleksei","family":"Borodulin","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrei","family":"Gantimurov","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Anton","family":"Nisan","sequence":"additional","affiliation":[{"name":"Engineering Center \u201cForta\u201d, 117036 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nikolay","family":"Novozhilov","sequence":"additional","affiliation":[{"name":"Engineering Center \u201cForta\u201d, 117036 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Viatcheslav","family":"Zelentsov","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aleksey","family":"Filimonov","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Andrey","family":"Galinovsky","sequence":"additional","affiliation":[{"name":"Artificial Intelligence Technology Scientific and Education Center, Bauman Moscow State Technical University, 105005 Moscow, Russia"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"311","DOI":"10.1016\/j.actamat.2016.07.012","article-title":"Microstructure and strength of selectively laser melted AlSi10Mg","volume":"117","author":"Wu","year":"2016","journal-title":"Acta Mater."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"319","DOI":"10.1016\/j.matdes.2018.01.022","article-title":"Microstructure prediction of selective laser melting AlSi10Mg using finite element analysis","volume":"142","author":"Liu","year":"2018","journal-title":"Mater. 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