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Nondestructive Modular Leak Detection in 3D Printed 316L Stainless Steel Pipes via Laser Powder Bed Fusion

  • Jorge Avila 1,*,   
  • Eric MacDonald 2,   
  • David A. Roberson 1,   
  • Cesar Balderrama Armendáriz 3,   
  • Ana C. Martínez 1,   
  • Alexis Maurel 1,   
  • Sivasai Balivada 4,   
  • Miguel Hoffmann 5,   
  • Thomas Feldhausen 5,   
  • Pedro Cortés 1

Received: 29 Dec 2025 | Revised: 23 Mar 2026 | Accepted: 26 Mar 2026 | Published: 02 Apr 2026

Abstract

This research investigates the leak detection features of 316L Stainless Steel pipe structures manufactured via Laser Powder Bed Fusion (LPBF). This work involves the design of a modular sensor system integrating nondestructive evaluation (NDE) methods, including thermal imaging and ultrasonic frequency detection to detect and characterize leaks in components. This aims to improve leak detection sensitivity within medium-pressure gas systems, during continuous operation without halting flow or introducing safety risks. The system could be adaptable for use on unmanned aerial vehicles (UAVs), enabling remote leak detection in active environments. A custom pneumatic system incorporating temperature and pressure sensors was assembled to detect leaks in LPBF-printed 316L SS tee pipes. Experimental results and simulations confirm the system’s effectiveness in leak detection and material evaluation. This research program also integrated a Python-based image recognition platform based on a metallography and optical microscopy to assess the porosity and complement the leak detection data on the printed structures. This allows a detailed analysis of pore distribution and internal leak paths, which could compromise structural integrity, critical for quality control during manufacturing. Findings suggest that the investigated approach holds potential for enhancing leak detection technologies and adapt them for advanced manufactured parts.

References 

  • 1.

    Bond, A.C.; Pohl, H.O.; Chaffee, N.H.; et al. Design Guide for High Pressure Oxygen Systems. NASA-RP-1113; NASA Lyndon B. Johnson Space Center, 1983. Available online: https://ntrs.nasa.gov/citations/19830024719 (accessed on 6 January 2026).

  • 2.

    Kulor, F.; Markus, E.D.; Kanzumba, K. Design and Control Challenges of Hybrid, Dual Nozzle Gas Turbine Power Generating Plant: A Critical Review. Energy Rep. 2021, 7, 324–335. https://doi.org/10.1016/j.egyr.2020.12.042.

  • 3.

    Oehlschlaeger, M.A. Grand Challenges in Aerospace Propulsion. Front. Aerosp. Eng. 2022, 1, 1027943. https://doi.org/10.3389/fpace.2022.1027943.

  • 4.

    Cirrone, D.M.C. Hazards from Catastrophic Failure of High-Pressure Hydrogen Storage. Bachelor’s Thesis, Ulster University, Belfast, Northern Ireland, 2018. Available online: https://pure.ulster.ac.uk/en/studentTheses/hazards-from-catastrophic-failure-of-high-pressure-hydrogen-stora (accessed on 6 January 2026).

  • 5.

    Clausen, J.; Larsen, A.; Larsen, J.; et al. Disruption Management in the Airline Industry—Concepts, Models and Methods. Comput. Oper. Res. 2010, 37, 809–821. https://doi.org/10.1016/j.cor.2009.03.027.

  • 6.

    Daga, R.; Samal, M.K. Real-Time Monitoring of High Temperature Components. Procedia Eng. 2013, 55, 421–427. https://doi.org/10.1016/j.proeng.2013.03.274.

  • 7.

    Constantin, L.; Kraiem, N.; Wu, Z.; et al. Manufacturing of Complex Diamond-Based Composite Structures via Laser Powder-Bed Fusion. Addit. Manuf. 2021, 40, 101927. https://doi.org/10.1016/j.addma.2021.101927.

  • 8.

    Singh, R.; Gupta, A.; Tripathi, O.; et al. Powder Bed Fusion Process in Additive Manufacturing: An Overview. Mater. Today Proc. 2020, 26, 3058–3070. https://doi.org/10.1016/j.matpr.2020.02.635.

  • 9.

    Eliasu, A. Microstructural and Mechanical Integrity of 3D Printed 316L Stainless Steel. Master’s Thesis, York University, North York, ON, Canada, 2020. Available online: https://yorkspace.library.yorku.ca/items/5b50882d-2fc2-4794-8a6f-e33f64829804 (accessed on 6 January 2026).

  • 10.

    Mahmood, M.A.; Ishfaq, K.; Oane, M.; et al. Porosity Prediction in LPBF of AISI 316L Stainless Steel: Refined Volumetric Energy Density and FEM Simulation Approach. Opt. Laser Technol. 2025, 188, 113015. https://doi.org/10.1016/j.optlastec.2025.113015.

  • 11.

    Honarvar, F.; Varvani-Farahani, A. A Review of Ultrasonic Testing Applications in Additive Manufacturing: Defect Evaluation, Material Characterization, and Process Control. Ultrasonics 2020, 108, 106227. https://doi.org/10.1016/j.ultras.2020.106227.

  • 12.

    Chatillon, S.; Cattiaux, G.; Serre, M.; et al. Ultrasonic Non-Destructive Testing of Pieces of Complex Geometry with a Flexible Phased Array Transducer. Ultrasonics 2000, 38, 131–134. https://doi.org/10.1016/S0041-624X(99)00181-X.

  • 13.

    Attallah, O. Multitask Deep Learning-Based Pipeline for Gas Leakage Detection via E-Nose and Thermal Imaging Multimodal Fusion. Chemosensors 2023, 11, 364. https://doi.org/10.3390/chemosensors11070364.

  • 14.

    Yuan, F.; Zeng, Y.; Khoo, B.C. A New Real-Gas Model to Characterize and Predict Gas Leakage for High-Pressure Gas Pipeline. J. Loss Prev. Process Ind. 2022, 74, 104650. https://doi.org/10.1016/j.jlp.2021.104650.

  • 15.

    Barber, R.; Rodriguez-Conejo, M.A.; Melendez, J.; et al. Design of an Infrared Imaging System for Robotic Inspection of Gas Leaks in Industrial Environments. Int. J. Adv. Robot. Syst. 2015, 12, 23. https://doi.org/10.5772/60058.

  • 16.

    Kumpati, R.; Skarka, W.; Ontipuli, S.K. Current Trends in Integration of Nondestructive Testing Methods for Engineered Materials Testing. Sensors 2021, 21, 6175. https://doi.org/10.3390/s21186175.

  • 17.

    Agarwal, A. An Investigation on Leakage Behaviour of Seals for Aerospace Applications. Master’s Thesis, Delft University of Technology, Delft, The Netherlands, 2014. Available online: https://repository.tudelft.nl/record/uuid:04e3d6f0-a621-4bee-95ef-2c872628ffb2 (accessed on 6 January 2026).

  • 18.

    Zaman, D.; Tiwari, M.K.; Gupta, A.K.; et al. A Review of Leakage Detection Strategies for Pressurised Pipeline in Steady-State. Eng. Fail. Anal. 2020, 109, 104264. https://doi.org/10.1016/j.engfailanal.2019.104264.

  • 19.

    Zhu, P.; Liyanage, J.P.; Panesar, S.S.; et al. Review of Workflows of Emergency Shutdown Systems in the Norwegian Oil and Gas Industry. Saf. Sci. 2020, 121, 594–602. https://doi.org/10.1016/j.ssci.2019.02.037.

  • 20.

    Santos, A.; Younis, M. A Sensor Network for Non-Intrusive and Efficient Leak Detection in Long Pipelines. In Proceedings of the 2011 IFIP Wireless Days (WD), Niagara Falls, ON, Canada, 10–12 October 2011; pp. 1–6. https://doi.org/10.1109/WD.2011.6098178.

  • 21.

    Sonkar, S.K.; Kumar, P.; George, R.C.; et al. Detection and Estimation of Natural Gas Leakage Using UAV by Machine Learning Algorithms. IEEE Sens. J. 2022, 22, 8041–8049. https://doi.org/10.1109/JSEN.2022.3157872.

  • 22.

    Lu, H.; Huang, K.; Azimi, M.; et al. Blockchain Technology in the Oil and Gas Industry: A Review of Applications, Opportunities, Challenges, and Risks. IEEE Access 2019, 7, 41426–41444. https://doi.org/10.1109/ACCESS.2019.2907695.

  • 23.

    Papa, I.; Manco, E.; Epasto, G.; et al. Impact Behaviour and Non-Destructive Evaluation of 3D Printed Reinforced Composites. Compos. Struct. 2022, 281, 115112. https://doi.org/10.1016/j.compstruct.2021.115112.

  • 24.

    Bayaniahangar, R.; Okoh, I.; Nawaz, K.; et al. Toward Extreme High-Temperature Supercritical CO2 Power Cycles: Leakage Characterization of Ceramic 3D-Printed Heat Exchangers. Addit. Manuf. 2022, 54, 102783. https://doi.org/10.1016/j.addma.2022.102783.

  • 25.

    Asadzadeh, S.; de Oliveira, W.J.; de Souza Filho, C.R. UAV-Based Remote Sensing for the Petroleum Industry and Environmental Monitoring: State-of-the-Art and Perspectives. J. Pet. Sci. Eng. 2022, 208, 109633. https://doi.org/10.1016/j.petrol.2021.109633.

  • 26.

    Ho, M.; El-Borgi, S.; Patil, D.; et al. Inspection and Monitoring Systems for Subsea Pipelines: A Review Paper. Struct. Health Monit. 2019, 19, 606–645. https://doi.org/10.1177/1475921719837718.

  • 27.

    Seifi, M.; Salem, A.; Beuth, J.; et al. Overview of Materials Qualification Needs for Metal Additive Manufacturing. JOM 2016, 68, 747–764. https://doi.org/10.1007/s11837-015-1810-0.

  • 28.

    Najmon, J.C.; Raeisi, S.; Tovar, A. Review of Additive Manufacturing Technologies and Applications in the Aerospace Industry. In Additive Manufacturing for the Aerospace Industry; Froes, F., Boyer, R., Eds.; Elsevier: Amsterdam, The Netherlands, 2019; pp. 7–31. https://doi.org/10.1016/B978-0-12-814062-8.00002-9.

  • 29.

    Dwivedi, S.K.; Vishwakarma, M.; Soni, A. Advances and Researches on Non-Destructive Testing: A Review. Mater. Today Proc. 2018, 5, 3690–3698. https://doi.org/10.1016/j.matpr.2017.11.620.

  • 30.

    NASA. Standard for Stainless Steel Piping Systems AA, ACK1, ACK4, ACK6, B, BCK1, BCK3, BCK4, BCK6, BCK10, C, EE, G, H, JJ, K3, L1, L2, NCK1, NCK2, NCK3, NCK10, NCK11, NCK12, P, R, T, and Z. Available online: https://standards.nasa.gov/standard/SSC/SSTD-8070-0047-PIPE (accessed on 6 January 2026).

  • 31.

    Sun, C.-N.; Aw, B.L.; Gu, H.; et al. Porosity Distribution of 316L Stainless Steel in Laser Powder Bed Fusion Additive Manufacturing Due to Spatial Variation. J. Manuf. Process. 2025, 139, 81–89. https://doi.org/10.1016/j.jmapro.2025.02.031.

  • 32.

    Ronneberg, T.; Davies, C.M.; Hooper, P.A. Revealing Relationships between Porosity, Microstructure, and Mechanical Properties of Laser Powder Bed Fusion 316L Stainless Steel through Heat Treatment. Mater. Des. 2020, 189, 108481. https://doi.org/10.1016/j.matdes.2020.108481.

  • 33.

    Snell, R.; Tammas-Williams, S.; Chechik, L.; et al. Methods for Rapid Pore Classification in Metal Additive Manufacturing. JOM 2020, 72, 101–109. https://doi.org/10.1007/s11837-019-03761-9.

  • 34.

    Kim, F.H.; Moylan, S.P.; Garboczi, E.J.; et al. Investigation of Pore Structure in Cobalt Chrome Additively Manufactured Parts Using X-ray Computed Tomography and Three-Dimensional Image Analysis. Addit. Manuf. 2017, 17, 23–38. https://doi.org/10.1016/j.addma.2017.06.011.

  • 35.

    Huang, X.; Yang, D.; Kang, Z. Impact of Pore Distribution Characteristics on Percolation Threshold Based on Site Percolation Theory. Physica A 2021, 570, 125800. https://doi.org/10.1016/j.physa.2021.125800.

  • 36.

    Zurcher, T.; Fridrici, V.; Charkaluk, E. Surface Microstructure of an IN718 3D Coating Manufactured by Laser Metal Deposition. Mater. Charact. 2023, 203, 113054. https://doi.org/10.1016/j.matchar.2023.113054.

  • 37.

    Pant, P.; Salvemini, F.; Proper, S.; et al. A Study of the Influence of Novel Scan Strategies on Residual Stress and Microstructure of L-Shaped LPBF IN718 Samples. Mater. Des. 2022, 214, 110386. https://doi.org/10.1016/j.matdes.2022.110386.

  • 38.

    Yildiz, R.A.; Popa, A.-A.; Malekan, M. On the Effect of Small Laser Spot Size on the Mechanical Behaviour of 316L Stainless Steel Fabricated by L-PBF Additive Manufacturing. Mater. Today Commun. 2024, 38, 108168. https://doi.org/10.1016/j.mtcomm.2024.108168.

  • 39.

    Smagowska, B.; Pawlaczyk-Łuszczyńska, M. Effects of Ultrasonic Noise on the Human Body—A Bibliographic Review. Int. J. Occup. Saf. Ergon. 2013, 19, 195–202. https://doi.org/10.1080/10803548.2013.11076978.

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Avila, J.; MacDonald, E.; Roberson, D. A.; Armendáriz, C. B.; Martínez, A. C.; Maurel, A.; Balivada, S.; Hoffmann, M.; Feldhausen, T.; Cortés, P. Nondestructive Modular Leak Detection in 3D Printed 316L Stainless Steel Pipes via Laser Powder Bed Fusion. Journal of Innovations in Materials and Manufacturing Engineering 2026, 1 (1), 5.
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