Geir Grasmo

• Ibrahim, Mohammad; Du, Qiang; Hovig, Even Wilberg; Grasmo, Geir; Hulme, Christopher & Aune, Ragnhild Elizabeth (2023). Gas-Atomized Nickel Silicide Powders Alloyed with Molybdenum, Cobalt, Titanium, Boron, and Vanadium for Additive Manufacturing. Metals. ISSN 2075-4701. 13(9). doi: 10.3390/met13091591. Full text in Research Archive Show summary

  Nickel silicides (NiSi) are renowned for their ability to withstand high temperatures and resist oxidation and corrosion in challenging environments. As a result, these alloys have garnered interest for potential applications in turbine blades and underwater settings. However, their high brittleness is a constant obstacle that hinders their use in producing larger parts. A literature review has revealed that incorporating trace amounts of transition metals can enhance the ductility of silicides. Consequently, the present study aims to create NiSi-based powders with the addition of titanium (Ti), boron (B), cobalt (Co), molybdenum (Mo), and vanadium (V) for Additive Manufacturing (AM) through the process of gas atomization. The study comprehensively assesses the microstructure, phase composition, thermal properties, and surface morphology of the produced powder particles, specifically NiSi11.9Co3.4, NiSi10.15V4.85, NiSi11.2Mo1.8, and Ni-Si10.78Ti1.84B0.1. Commonly used analytical techniques (SEM, EDS, XRD, DSC, and laser diffraction) are used to identify the alloy configuration that offers optimal characteristics for AM applications. The results show spherical particles within the size range of 20–63 μm, and only isolated satellites were observed to exist in the produced powders, securing their smooth flow during AM processing.

• Tareq, Foysal Kabir; Hovig, Even Wilberg; Aune, Ragnhild Elizabeth & Grasmo, Geir (2023). Microstructure and Mechanical Properties of Arc-Melted NiSi11Cx Alloys, TMS 2023 152nd Annual Meeting & Exhibition Supplemental Proceedings. Springer. ISSN 978-3-031-22523-9. p. 216–225. doi: 10.1007/978-3-031-22524-6_21. Show summary

  Functional materials such as nickel silicides (Ni3Si) are considered promising materials for building complex and strong structures. They have proven to have a high melting point, low electronic resistivity, excellent corrosion resistance, and thermally stability, however, their overall performances are still challenging due to their brittleness. Therefore, it is essential to prepare high-strength nickel silicide-based materials to improve their toughness. In the present study, arc melting has been utilized to synthesize nickel silicide (NiSi11, wt%) and carbon (C) alloyed nickel silicide (NiSi11Cx, x = 0.2, 1 wt%) with varying amounts of C aiming to improve the microstructure and mechanical properties of the alloy. The NiSi11 and NiSi11Cx alloys were characterized by Scanning Electron Microscope (SEM), Energy Dispersive Spectroscopy (EDS), and microhardness tests. Results show that the NiSi11 alloy comprises lamellar-like eutectic Ni3Si and Ni solid solution phases. After alloying with C, the microstructure of the Ni-rich solid solution and Ni3Si phase is changed to a relatively fine-scale morphology, and C is mainly dissolved in the Ni-rich solid solution phase. The microhardness of the alloys is increased with the addition of C, which is mainly attributed to the microstructure refinement and solid solution strengthening obtained through C addition.

• Ibrahim, Mohammad; Sætre, Tor Oskar; Grasmo, Geir & Aune, Ragnhild (2022). Characterisation of Nickel Silicide Deposited on Steel and Nickel Substrates, World PM2022 Proceedings. European Powder Metallurgy Association. ISSN 978-1-899072-55-2.
• Tareq, Foysal Kabir; Aune, Ragnhild Elizabeth; Grasmo, Geir; Akhtar, Naureen & Sætre, Tor Oskar (2022). Preparation and Characterization of Spherical Nickel Silicide Powder by Inductively Coupled Plasma Spheroidization for Additive Manufacturing, TMS 2022 151st Annual Meeting & Exhibition Supplemental Proceedings. Springer. ISSN 978-3-030-92381-5. p. 1488–1496. doi: 10.1007/978-3-030-92381-5_141. Full text in Research Archive Show summary

  Metal alloy powder with spherical-shaped morphology, high flowability, and packing density is the main requirements for metal-based additive manufacturing (AM). Among metal alloys, nickel silicide is considered as a potential candidate due to its unique properties such as high melting point, good electrical conductivity, as well as high corrosion and wear resistance. However, the fabrication of spherical nickel silicide powder has proven to be a challenging task. In the present work, spherical NiSi16 alloy powders were synthesized by inductively coupled plasma spheroidization (ICPS). The influence of the feed rate on the properties of the as-prepared powder was investigated using different analytical techniques to evaluate the particle morphology, particle size distribution, oxygen content, bulk density, fluidity, and spheroidization rate. The results showed some unique advantages of the ICPS technology in the preparation of spherical nickel silicide powder that is believed to be well suited for AM.

• Falconer, Shaun; Krause, Peter; Bäck, Thomas; Nordgård-Hansen, Ellen Marie & Grasmo, Geir (2022). Condition Classification of Fibre Ropes during Cyclic Bend over Sheave testing Using Machine Learning. International Journal of Prognostics and Health Management. ISSN 2153-2648. 13(1). doi: 10.36001/IJPHM.2022.v13i1.3105. Full text in Research Archive Show summary

  Fibre ropes have been shown to be a viable alternative to steel wire rope for offshore lifting operations. Visual inspection remains a common method of fibre rope condition monitoring and has the potential to be further automated by machine learning. This would provide a valuable aid to current inspection frameworks to make more accurate decisions on recertification or retirement of fibre ropes in operational use. Three different machine learning algorithms: decision tree, random forest and support vector machine are compared to classical statistical approaches such as logistic regression, k-nearest neighbours and Naïve-Bayes for condition classification for fibre ropes under cyclic-bend-over-sheave (CBOS) testing. By measuring the rope global elongation throughout the CBOS tests, a binary classification system has been used to label recorded samples as healthy or close to rupture. Predictions are made on one rope through leave-one-out cross validation. The models are then assessed through calculating the accuracy, probability of detection, probability of false alarm and Matthew’s Correlation Coefficient, and ranked based on the results. The results show that both machine learning and classical statistical methods are effective options for condition classification of fibre ropes under CBOS regimes. Typical values for Matthews Correlation Coefficient (MCC) were shown to exceed 0.8 for the best performing methods.

• Falconer, Shaun; Nordgård-Hansen, Ellen Marie & Grasmo, Geir (2021). Remaining useful life estimation of HMPE rope during CBOS testing through machine learning. Ocean Engineering. ISSN 0029-8018. 238. doi: 10.1016/j.oceaneng.2021.109617. Full text in Research Archive Show summary

  Fibre rope used in cranes for offshore deployment and recovery has significant potential to perform lifts with smaller cranes and vessels to reach depths limited by weight of steel wire rope. Current condition monitoring methods based on manual inspection and time-based and reactive maintenance have significant potential for improvement coupled with more accurate remaining useful life (RUL) prediction. Machine learning has found use as a condition monitoring approach, coupled with vast improvements in data acquisition methods. This paper details data-driven RUL prediction methods based on machine learning algorithms applied on cyclic-bend-over-sheave (CBOS) tests performed on two fibre rope types until failure. Data extracted through computer vision and thermal monitoring is used to predict RUL through neural networks, support vector machines and random forest. Random forest and neural networks methods are shown to be particularly adept at predicting RUL compared to support vector machines . Additionally, improved RUL predictions can be achieved by combining data from distinct rope types subject to different test conditions.

• Falconer, Shaun; Nordgård-Hansen, Ellen Marie & Grasmo, Geir (2020). Computer vision and thermal monitoring of HMPE fibre rope condition during CBOS testing. Applied Ocean Research. ISSN 0141-1187. 102. doi: 10.1016/j.apor.2020.102248. Full text in Research Archive Show summary

  Fibre rope usage in deep sea lifting operations is gaining more prominence in recent times. With rope minimum break loads (MBL) comparable to that of their steel wire counterparts, the use of high modulus polyethylene (HMPE) ropes is seen as a viable option for use in subsea construction cranes. The ropes are worn out during use and visual inspection remains one of the main methods of determining whether a fibre rope is to be retired from use, therefore a natural extension is condition monitoring through computer vision. Creep and temperature are constraining with HMPE ropes and should be monitored continuously, particularly when the rope is cyclically bent over sheaves. Additionally, interpreting the thermal history of the rope during use could give insight into deterioration. In this paper, a condition monitoring system based on combined computer vision and thermal monitoring is used during cyclic bend over sheave tests performed on 560 kN break load of 12 strand braided HMPE ropes. New monitoring features such as local length and width through computer vision algorithms combined with surface thermal monitoring and global elongation are presented and their effectiveness as condition monitoring features is assessed.

• Falconer, Shaun; Nordgård-Hansen, Ellen Marie & Grasmo, Geir (2020). Temperature Measurements as a Method for Monitoring Ropes. In Liyanage, Jayantha Prasanna; Amadi-Echendu, Joe E. & Mathew, Joseph (Ed.), Engineering assets and public infrastructures in the age of digitalization : Proceedings of the 13th world congress on engineering asset management. Springer. ISSN 9783030480202. p. 772–779. doi: 10.1007/978-3-030-48021-9_85.
• Stave, Daniel Årrestad; Schlanbusch, Rune; Vysochinskiy, Dmitry & Grasmo, Geir (2019). Condition Monitoring of Steel Wire Ropes. In Dohm, M. A. R. (Eds.), Exploring Opportunities - Synthetic/Steel - Proceedings of the OIPEEC Conference 2019. OIPEEC. ISSN 978-1-7336004-0-8.
• Falconer, Shaun; Grasmo, Geir & Nordgård-Hansen, Ellen Marie (2019). Condition monitoring of HMPE fibre rope using computer vision during CBOS testing. In Dohm, M. A. R. (Eds.), Exploring Opportunities - Synthetic/Steel - Proceedings of the OIPEEC Conference 2019. OIPEEC. ISSN 978-1-7336004-0-8. p. 129–147. Show summary

  The paper details the results of recent cyclic-bend-over-sheave (CBOS) experiments performed at the Mechatronics Innovation Lab (MIL) located at the University of Agder, Norway. A method for measuring diameter and elongation of discrete sections of fibre rope using computer vision is detailed. Estimations of the change in roundness of the rope are also explored based on the diameter measurements. These measurements are then assessed for their suitability as condition indicators.

• Falconer, Shaun; Gromsrud, Andreas; Oland, Espen & Grasmo, Geir (2017). Preliminary Results on Condition Monitoring of Fiber Ropes using Automatic Width and Discrete Length Measurements, PHM 2017 Proceedings of the Annual Conference of the Prognostics and Health Management Society 2017. PHM Society. ISSN 978-1-936263-26-4.

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• Knudsen, Atle; Giulianotti, Mark; Håverstad, Thor Arne; Tande, John Olav Giæver; Klausen, Rune & Nesse, Arvid [Show all 7 contributors for this article] (2024). Vi trenger en sektorplan for havvind. Europower.
• Falconer, Shaun; Grasmo, Geir & Nordgård-Hansen, Ellen Marie (2019). Condition monitoring of HMPE fibre rope using computer vision during CBOS testing.
• Falconer, Shaun; Nordgård-Hansen, Ellen Marie & Grasmo, Geir (2018). Temperature measurements as a method for monitoring ropes.
• Falconer, Shaun; Gromsrud, Andreas; Oland, Espen & Grasmo, Geir (2017). Preliminary Results on Condition Monitoring of Fiber Ropes using Automatic Width and Discrete Length Measurements.

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