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RAMS Seminars are open to all interested in the RAMS field and target professors, researchers, Ph.D. candidates, master students and postdocs at NTNU. It shall bring together researchers and students to have an academic exchange, share and discuss their research. The seminars take place every two weeks on Thursdays, 10.30-11.30, at Møteroom 216 PUMA, Gløshaugen Verkstedteknisk.
The topics and speakers are shown in the table below. If you want to be on the list to present, please email: sun.tianqi@ntnu.no.
NB: The seminars are also on Teams, feel free to join.
Program 2022 Autumn
Wednesdays, 13:00-14:00, at Møteroom 216 PUMA, Gløshaugen Verkstedteknisk.
The topics and speakers are shown in the table below. If you want to be on the list to present, please email: asmae.bni@ntnu.no.
NB: The seminars are also on Teams, feel free to join.
Program 2023 Autumn
| When | Who | What |
|---|---|---|
| 10.11.2023 | Francesco Piraino | Title Research experiences on hydrogen technologies in Italy Presentation description The brief presentation is an overview of the main scientific activities of Francesco Piraino, along with the main research lines of the "Fuel Cell and Hydrogen Research Team" of the University of Calabria. Among them, particular focus is on fuel cell-based powertrains and hydrogen refueling infrastructures, investigated by numerical and experimental models and developed also in international research centers. In addition, the equipment of the Fuel cell and Hydrogen research labs (at the University of Calabria) is shown. Speaker introduction Francesco Piraino is a Post doc Fellow and Assistant lecturer of "Power systems" at the Department of Mechanical, Energy and Management Engineering of the University of Calabria. He is conducting a visiting period at the Norwegian University of Science and Technology, investigating hydrogen safety topics. His main research interests concern the hydrogen systems, e.g. fuel cells and electrolyzers, and their principal applications, such as fuel cell-based powertrains and hydrogen refueling infrastructures. He obtained the European PhD in 2020, with a thesis on the analysis of hydrogen-based systems for railways by means of numerical and experimental modelling. He carried out a 6-month internship at the California State University of Los Angeles and a 3-month internship at the University of Birmingham. He is the author of 20 papers, with a h-index of 10 (https://orcid.org/0000-0003-1302-2631). |
Niclas Flehmig | New PhD Candidate self- introduction I’m Niclas, the new PhD Candidate in the RAMS group. I am from Germany and received both my degrees (Bachelor and Master) from the Technical University of Munich. During my master’s degree, I specialized on applied machine learning for technical processes. I wrote my master’s thesis here at the MTP department on the topic of Predictive Maintenance for a Salmon Farm. Now, I will work on potential AI usage in CO2 capture within the SUBPRO-Zero project. Next Friday, I would like to give a short presentation on myself, and I’d be happy to get know some of you. | |
| 11.10.2023 | Alessandro Campari | Title: “Evaluation of the tensile properties of X65 pipeline steel in compressed gaseous hydrogen using hollow specimens.” Abstract: Hydrogen has great potential into the decarbonization process of the energy and transport sectors, thus helping to mitigate the urgent issue of global warming. It can be sustainably produced through water electrolysis with potentially zero emissions, and efficiently used in fuel cell systems. Despite its environmental advantages, hydrogen is an extremely flammable substance and its interaction with most metallic materials could result in their mechanical properties degradation to an extent that could make them inherently unsafe. Extensive material testing under realistic operating conditions is required to determine the criteria under which hydrogen-induced damage is to be expected. In-situ slow strain rate tensile (SSRT) test is an option that allow the quantification of the behavior of metals in hydrogenated environments. The standardized procedure for testing in-situ the pressurized gaseous hydrogen effect on metals consists of the utilization of an autoclave as a containment volume. Testing inside an autoclave is difficult, expensive, and time-consuming, and requires specialized equipment and trained personnel. A relatively recent method to circumvent these issues and provide affordable and reliable test results consists in using hollow specimens as the gas containment volume, thus applying the hydrogen pressure inside rather than outside the specimen. This experimental setup allows us to minimize the volume of hydrogen and perform the tests safely and effectively. This study focuses on the evaluation of tensile properties of X65 vintage pipeline steel tested in a high-pressure hydrogen environment using hollow specimens. A constant nominal strain rate of 1ꞏ10-6 s-1 is applied. Tests are performed at several pressure levels (from 6 to 20 MPa) to evaluate the effect on the reduced area at fracture (RA). In this way, this study provides insights on the applicability of novel, reliable, and safer testing method which can be used to assess HE, particularly in relation with hydrogen-induced loss of ductility in metallic material. |
| 27.09.2023 | Sutthipong Yungratog | The meeting is in Gløshaugen Verkstedteknisk 5. etasje Møterom P525 (307_p525). Title: "A Conceptual Framework for Assessing Risks for Data Protection Impact Assessment Process in Maritime Industries". Abstract - Personal data is used to define customer requirements. Organizations should securely collect and process such data, using data protection policies aligned with the applicable regulations. The General Data Protection Regulation (GDPR), an EU data protection law, has include a data protection assessment method called Data Protection Impact Assessment (DPIA) to ensure personal data security. The maritime industry is also concerned about personal data protection. However, there is a still a lack of practical methods to assess data protection risks. This article aims to introduce the conceptual framework for a new method for risk assessment in maritime systems, using DPIA and various systems-theoretic risk approaches as a conceptual basis. The ICT system is a central system in which personal data is utilized in the architecture of maritime systems. In this article, this system will be taken as a basis for illustrating the newly proposed method for personal data security risk assessment in a DPIA context. The conceptual framework will be further concretized and tested in follow-up research. About the speaker: Mr. Yungratog is a PhD candidate in Information Technology Management, Mahidol University, Thailand. His research is in the data protection and risk assessment in maritime area. He is currently member of Norway-ASEAN Consortium in Risk Management for Safer and Sustainable Ocean (322410 - NORGLOBAL2). His research interests include several aspects of Human Computer Interaction, Information Technology, Data Protection, Risk assessment, System Analysis, and Business Analysis. |
| 13.09.2023 | Donghun Lee Reem Nasser Lucas Claussner | Visiting Researcher Self-introduction Donghun Lee: Hello. My name is Donghun Lee. I’m from South Korea. I received my bachelor's degree and master's degree from INHA University in Korea. When I was an undergraduate, my department was naval architecture and ocean engineering. And in my master's course, I conducted research on autonomous ships. My main research field is the design of avoidance system for autonomous ships using collision risk index. Now, I’m in charge of developing a risk model to analyze the human factors of fishing boat accidents. To develop a human reliability analysis method optimized for fishing vessels, I plan to analyze human risk cases that may occur in fishing vessels and improve the existing HRA method. New Ph.D. Candidate Self-introduction Reem Nasser: I'm Reem Nasser, a PhD candidate in RAMS group of NTNU who has just joined in August 2023. I have earned my B.Sc. degree in Petrochemical Engineering from the British University in Egypt. Being passionate about Energy systems, I joined the Masters of Science program for Renewable Energy with a focus on energy conversion and self-cleaning coatings for PV applications. I have also gained experience in the field of education through working as an Assistant Lecturer in the Department of Chemical Engineering for five years. In addition to that, I have participated as an industrial trainer to deliver a course with the title of "Industrial Coatings. The title for my PhD is Risk Management and Production Assurance of Future Energy Infrastructures TO MITIGATE NATECH HAZARD. New Ph.D. Candidate Self-introduction Lucas Claussner: From: Leipzig, Germany Studies: Mechanical Engineering/Industrial Engineering Thesis: Liquid Hydrogen applications in mobility + LH2 Thermodynamics PhD-Topic: Simulation of LH2 thermodynamics in accident scenarios |
| 30.08.2023 | Ph.D. Candidate Wanwan Zhang Tianqi Sun | Title: Statistical analysis of offshore wind turbine failures Abstract: This paper aims to investigate the characteristics of offshore wind turbine failures. Four hypotheses about failure features are proposed and strictly examined by statistical tests. Cox model is chosen to model the failure process. Three forms of covariates are designed to research their influence on failures. Their coefficients are obtained by maximum likelihood estimation, and the Breslow estimator is calculated. Finally, goodness-of-fit tests verify the assumptions of the Cox model. Results from long-term models show that wind significantly favors the growth of the baseline hazard. However, temperature and production mildly reduce it. The effects will gradually become stable if the accumulation time increases. Similar results are observed in models with principal components of covariates. A comparison of models suggests the highest likelihood belongs to models with three accumulated covariates. About Speaker: Wanwan Zhang has a B.E in Safety engineering from China and a M.Sc. in RAMS from NTNU. She started her Ph. D right after her M.Sc in RAMS in September 2021. The title of her Ph.D is Predictive Maintenance and Decision Support for Asset Management, which belongs to NorthWind (Norwegian Research Centre on Wind Energy) co-financed by the Research Council of Norway, industry, and research partners. Title: A phase-type maintenance model considering condition-based inspections and delays before the repairs Abstract: Markov models are widely used in maintenance modelling and system performance analysis due to their computational efficiency and analytical traceability. However, these models are usually restricted by the use of exponential distributions, which are the base of the Markov modelling. Phase-type distributions provide a tool to approximate an adequate distribution, such as Weibull, log-normal and so on, by means of Markov processes. Our earlier work proposes a phase-type maintenance model considering both condition-based inspections and delays before the repairs, where extra matrices are defined in the modelling of repair delays to keep track of the probability masses to repair. The model provides quite good estimations but is complex and requires good knowledge in its implementation. This paper aims to get rid of the extra matrices and investigate the modelling of the repair delays with phase-type distributions. An illustration case of road bridges is presented to demonstrate the modelling process and the results. About Speaker: Tianqi Sun has a B.E. in Safety Engineering from China and a M.Sc. in RAMS from NTNU. After almost three years work as safety engineer in a car manufacture in China, he started his Ph.D. in September 2020. The title for his Ph.D. is Strategies and Criteria for Preventive and Corrective Maintenance, which belongs to a project named SMARTer Maintenance between Statens Vegvesen and NTNU. |
Program 2023 Spring
| When | Who | What |
|---|---|---|
| No more meetings until September due to the holiday season | ||
| 08.06.2023 | Ph.D. Candidate Elena Baboi Asmae Bni | New Ph.D. Candidate Self-introduction About Elena Baboi: Elena Baboi was born in 1989 in Tulcea, Romania. She attended a natural science centred curriculum at a theoretical high school in the same city. In 2012 she obtained her Bachelor in Engineering for Chemical engineering in English diploma upon graduating an organic synthesis/technologies focused curriculum at the Faculty of Engineering in Foreign Languages, Politehnica University of Bucharest, Romania. She also has a Master in Engineering for Chemical Engineering from the Faculty of Applied Chemistry and Material Science, Politehnica University of Bucharest, Romania. During her master she took part in an Erasmus double diploma program. She is currently a PhD candidate at the Department of Mechanical and Industrial Engineering, NTNU where she is taking part in the EU project “HyInHeat”, Hydrogen technologies for decarbonization of industrial heating processes. Her project is titled “Safe Operations in Hydrogen-based Industry” and will cover safety guidelines for the steel and aluminium manufacturing processes as they will be retrofitted to permit the use of hydrogen. Self-introduction Elena Baboi.pdf Title：Cyber-physical attacks detection mechanisms: Case Study Autonomous Systems Abstract: Cyber physical systems have evolved from automated systems to connected and autonomous systems. The threat landscape has since increased requiring integration of various security defense mechanisms into these systems. The Intrusion detection systems are one of these mechanisms and this presentation is a summary of the different attack detection schemes that are used in autonomous systems. About Speaker: Asmae Bni has a bachelor’s degree in computer science and a master’s degree in cryptography and information security. Before joining NTNU, she worked almost 7,5 years in the cyber security field as an engineer. Her work experience is in security testing and secure development. Her PhD topic is about integrating safety and security in autonomous systems design against cyber-physical attacks. |
| 25.05.2023 | Dr. Huixing Meng | Title： Prognostics of Health and Risk for Lithium-ion Batteries Abstract: Lithium-ion batteries has been widely applied in household and industrial domains. As a significant concern for related manufactures and consumers, the health and risk of lithium-ion batteries will be successively discussed in this talk. In the first part of the presentation, based on the long short-term memory network with Bayesian optimization, we will illustrate a battery prognostics method using random segments of charging curves, aiming at improving the flexibility and applicability in practical usage (Ref.: https://doi.org/10.1016/j.ress.2023.109288). In the second part of the presentation, we will introduce a methodology for dynamic risk prediction by integrating fault tree, dynamic Bayesian network and support vector regression (Ref.: https://doi.org/10.1016/j.psep.2023.01.021). The work discussed in this presentation is expected to be an alternative for health and risk management of lithium-ion batteries. About Speaker: Huixing Meng received the B.Sc. degree in Safety Engineering and the M.Sc. degree in Safety Technology and Engineering from the China University of Petroleum (East China), Qingdao, China, in 2011 and 2014, respectively. He obtained the Ph.D. degree in Computer Science from the Ecole Polytechnique, Paris, France, in 2018. He is currently an Assistant Professor in the Department of Safety Engineering, Beijing Institute of Technology, Beijing, China. Previously, he was a postdoctoral research associate in the Department of Industrial Engineering, Tsinghua University, Beijing, China. His major research interests include risk assessment, emergency techniques, and predictive maintenance for energy systems. He has published over 30 academic papers and applied 8 national invention patents. He has also been granted a project from Natural Science Foundation of China (NSFC) and an international exchange project from Ministry of Science and Technology of China (MOST). He serves as the editorial board member of Safety Science and International Journal of Reliability and Safety. |
| 11.05.2023 | Ph.D. Candidate Giulia Collina Farhana Tuhi Intern student: Baptiste Decker Tom Espinosa | The meeting is in Gløshaugen Materialteknisk 3. etasje Holand (308_3-169) New Ph.D. Candidate Self-introduction About Giulia Collina: Giulia Collina was born in Ascoli Piceno, Italy, in 1999. She studied at the scientific high school in the same city and then moved to Bologna to start the University. She got her BSc in Chemical and Biochemical Engineering in July 2020 and her MSc in Chemical and Process Engineering in February 2023. She spent the fall semester of 2022 at NTNU working on her master’s thesis titled “Consequences associated to the Boiling Liquid Expanding Vapour Explosion for liquid hydrogen tanks: assessment and mitigation”. In March 2023, she started her Ph.D. at the Department of Mechanical and Industrial Engineering (MTP). The research project is titled “Loss Prevention and Maintenance Modelling for Hydrogen-based Industry” and it is part of the Horizon Europe project H2GLASS - advancing Hydrogen (H2) technologies and smart production systems TO decarbonise the GLass and Aluminium SectorS. self introduction _ Giulia Collina About Farhana Tuhi： I am Farhana and I am from Bangladesh. I have started my PhD last month after completing my masters in RAMS engineering. My research topic is ' Reliability and resilience of green hydrogen production process'. self introduction _ Farhana Tuhi Self-introduction for new intern students from INSA-Lyon About Baptiste Decker: I'm a french student, I'm 21 years old. I was born in the South of France, in Fréjus. I'm in 4 years of my Engineering Degree in a specialization in Energy and Environment. I want to work in the nuclear field or doing carbon footprint studies of company to help them reduce their CO2 emission. I'm here in Trondheim for 5 months to make a Research Internship. I'm part of the SUSHy project with my tutor Dimitrios. During this internship, I'm going to apprehend the characteristics of hydrogen and then study Hydrogen Refueling Station and analyze accidents to reduce their probability by doing safety measures part of the risk management. Out of the work, i like to hike, listen to music and i love automobile. self introduction _ Baptiste Decker About Tom Espinosa: My name is Tom Espinosa I am 21 years old and I come from Lyon (a beautiful city in France) In France I am studying energy and environmental engineering at INSA Lyon. I am very interested in the automotive sector and transportation in general, and especially in the issues related to this sector in order to have more virtuous means of transportation. I am convinced that hydrogen can help this field to reduce its carbon emissions That is why I am at NTNU for a 5 months research internship to do my master thesis on hydrogen embrittlement due to fatigue in pipeline steel. My purpose is to set up a security protocol which will allow to know if it is safe or note to use and existing pipeline by taking account all parameters which have an effect on Hydrogen embrittlement |
| 27.04.2023 | Ph.D. Candidate Leonardo Giannini | The meeting is in Gløshaugen Verkstedteknisk 5. etasje Møterom P525 (307_p525). Title: Inspection Planning in the Marine Sector: a Case Study of a Hydrogen-Fueled Fishing Vessel Abstract: The climate roadmap of the Norwegian fishing fleet estimates that a low environmental impact technology can contribute to significantly reduce greenhouse gas emissions by 2030, but the implementation of electricity in the marine sector is today almost only appealing for ferries, which in many cases have daily access to recharge stations. In fact, considering the longer working sessions of fishing vessels, the additional weight of batteries, and the considerable occupied volume, it is reasonable to discuss hydrogen-fed fuel cells as a more viable solution. Unfortunately, inspection planning, maintainability and in general safety aspects are yet to be consolidated topics of hydrogen technologies in most of their applications, including the marine sector. Against such background, this paper discusses a case study of a hydrogen-fueled fishing vessel, focusing on risk-based inspection (RBI) and maintenance planning as a way to significantly decrease safety-related uncertainties and optimize the associated operations. The hydrogen-induced degradation mechanisms present in the standard API RBI 581 have been considered to investigate how the existing methodologies might lead to an underestimation of the risks associated with the equipment selected for the fishing vessel. In addition, a discussion regarding the limitations in the applicability of standard RBI planning with respect to hydrogen technologies is carried out as an overall result, along with the limits of the implemented approach. About Speaker: Leonardo Giannini graduated from the faculty of engineering at the University of Bologna. His bachelor’s degree was mainly focused on energy production systems, conversion of energy, and nuclear power plants. And he has a master's degree that focuses more on sustainable energy sources. He also has working experience as a project engineer for a company that produces refrigeration systems. His PhD topic is inspection planning and maintenance for hydrogen technologies. |
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cancelled | |
30.03.2023 13:00-14:00 | Ph.D. Candidate Yixin Zhao | Abstract: Many industrial facilities consisting of multiple components are prone to failure interactions and degradation interactions. In such systems, these interactions are frequently characterized by failure dependences that may accelerate the degradation of components. Due to system layout and functional interactions, not all components have the same failure dependence. In the general context of complex failure dependences in dependent multi-component systems, heterogeneous failure dependences further complicate the maintenance activities during operation. In the present study, a framework to evaluate the heterogeneous failure dependences and develop a maintenance optimization model for multi-component systems by Markov processes is developed. The proposed method is applied to a practical case consisting in a parallel subsea transmission system to illustrate the effects of heterogeneous failure dependences. The results show that the heterogeneous failure dependences framework and maintenance model guides the optimization of maintenance strategies to maximize the system availability and minimize the maintenance cost. About Speaker:Yixin Zhao has a B.E. and M.E. in Safety Engineering and Science from China. She started her Ph.D. in Octorber 2020 at RAMS group, MTP, NTNU, with main supervisor Yiliu Liu and co-supervisor Jørn Vatn. |
| 23.03.2023 | IEEE webinar | 12:00-12:10 Photo session & Introduction 12:10-12:35 Talk 1 Mr. San Giliyana (MDU/MITC): Smart Maintenance Technologies for the Manufacturing Industry 12:35-13:00 Talk 2 Dr. Haizhou Chen (LTU): Physics-based modeling with Simscape/simulink: introduction and applications in PHM project ZOOM MEETING ID: 902 728 5345; PASSWORD: 167528 |
16.03.2023 13:00-14:00 | Ph.D. Candidate Muhammad Gibran Alfarizi | Title: Data-driven design for fault diagnosis and prognosis: Application to technical processes Abstract: In this RAMS seminar, I will present the results of my Ph.D. project. The main objective of my Ph.D. project is to design efficient fault diagnosis and prognosis techniques for technical processes using data-driven methods that consider the operating conditions of the process. Specifically, the goals of this thesis are stated as follows:
In this thesis, one industrial benchmark process and two experiments are utilized to evaluate the effectiveness of the proposed approaches for fault diagnosis and prognosis purpose. About Speaker: Muhammad Gibran Alfarizi has a B.Sc. in Petroleum Engineering from Indonesia and a M.Sc. in Petroleum Engineering from NTNU. His research interest include data driven modeling and machine learning. He started his PhD in August 2020. The project title of his Ph.D. is The Digital Transformation and Data-Driven Methods in the Reliability of Safety Systems. |
02.03.2023 13:00-14:00 | Ph.D. Candidate Andrie Pasca Hendradewa Jie Liu | New Ph.D. Candidate Self-introduction About Andrie Pasca Hendradewa: Andrie come from Yogyakarta, Indonesia for his PhD at MTP NTNU. He is also an Assistant Professor in Dept. of Industrial Engineering Universitas Islam Indonesia, Yogyakarta. He has worked in Indonesia for 9 years with various experience and research journey, namely: information system design (undergraduate thesis), web design (as UI/UX designer), human computer interaction (master degree thesis), optimization, and machine learning. Since four years ago, he has been appointed by Indonesia Ministry of Communication and Informatics as seasonal instructor in Python programming, Big Data & Analytics, and Deep Learning training program in collaboration with Cisco Networking Academy and Huawei ICT Academy. His research project is about implementing Reinforcement Learning to improve maintenance strategy which part of SUBPRO project. It will be focused on how to train an agent to be able to decide the right maintenance strategy in order to reach the optimum condition by minimizing carbon emission. He is very grateful to join RAMS group at NTNU and looking forward for a partnership and collaboration. Self-introduction_Andrie Pasca Hendradewa.pdf Title: A discussion about Qualification of a Digital Twin for maintenance models Abstract: Digital twin (DT) is a new and popular topic for academic researchers and industries. However, whether the new technology could meet end users’ requirements and help improve the current system’s efficiency is still a challenge for the designers. Therefore, evaluating and qualifying the DT during its usage is crucial and needs more studies. We proposed an index for DT's evaluation. Then we used a DT for choke valve degradation prediction as a case study and carried out the qualification process, which follows the proposed index. About Speaker: Jie Liu has a bachelor’s degree in Applied Mathematics in Beijing Institute of Technology from China and a master’s degree in RAMS of NTNU. She started as a PhD candidate at RAMS group, MTP, NTNU in September 2021. Her research topic is Digital Twin Qualification for Maintenance, which is a part of SUBPRO project. |
16.02.2023 13:00-14:00 | Ph.D. Candidate Asmae Bni Federica Tamburini Alice Schiaroli | New Ph.D. Candidate Self-introduction About Asmae Bni: My name is Asmae, I was born and grow up in Morocco. I did my bachelor studies in computer science. Then I started my master studies in cryptography and information security. I was awarded a scholarship and moved to Sweden to pursue a master’s degree in information technology with focus on communication security. I lived in Sweden for about 12 years. Before joining NTNU, I worked almost 7,5 years in the cyber security field as an engineer. My work experience is within security testing and secure development. My PhD topic is about integrating safety and security in autonomous systems design against cyber physical attacks. I am happy to join the RAMS group at NTNU and looking forward to learning and collaborating with you. Self-introduction_Asmae Bni.pdf About Federica Tamburini: Federica Tamburini was born in Lugo, Italy, in 1996. She earned a three-year BSc degree in chemical and biochemical engineering and a two-year MSc degree in chemical and process engineering (with Honours) from the University of Bologna in 2018 and 2021, respectively. In May 2021, she joined the University of Bologna as a research fellow at the Laboratory of Industrial Safety and Sustainability (LISES) in the Department of Civil, Chemical, Environmental and Materials Engineering (DICAM) and, after six months, in November 2021, she started her PhD research in chemical engineering. Her doctoral programme consists in a cotutelle agreement between the University of Bologna and the Norwegian University of Science and Technology (NTNU), where she is enrolled as a PhD candidate at the Department of Mechanical and Industrial Engineering (MTP). In August 2022, Federica was admitted to the Norwegian Research School of Hydrogen and Hydrogen-based Fuels (HySchool) coordinated by the University of Bergen. Federica research project is titled “Advanced methods for the quantitative assessment of the safety of decarbonization technologies”. It looks at the development of innovative models, methodologies, and tools for the risk evaluation of Carbon dioxide Capture and Sequestration (CCS) techniques and blue hydrogen-based systems to assess the effective implementation of these new technologies in future civil and industrial applications. Self-introduction_Federica Tamburini.pdf About Alice Schiaroli: I am Alice and I come from a small town in the Marche region, in central Italy. I started my studies at the scientific high school in Fano and then I moved to Bologna to attend the university for the next five years. I got my Bachelor’s degree in Chemical and Biochemical Engineering in 2020 and I finished my Master’s degree in Chemical and Process Engineering in October 2022. Since November 2022 I am a PhD candidate both at the University of Bologna and at NTNU. This is because my PhD is a cotutelle agreement between the two universities, meaning that I will spend a year of my research work here in Trondheim before coming back to Bologna to finish the research period. My project deals with hydrogen safety, particularly the analysis of the response of hydrogen vessels in external fire conditions. I started working on hydrogen safety during my master’s thesis, which was a risk assessment of hydrogen storage tanks for hydrogen-powered buses. Now I am focused on cryogenic hydrogen tanks and I am using the skills acquired during my academic studies to study these types of equipment when exposed to an external fire. Self-introduction_Alice Schiaroli.pptx Note that the physical meeting will be at Gløshaugen Materialteknisk 3. etasje Holand. |
02.02.2023 10:30-11:30 | Hydrogen safety expert Olav Roald Hansen | Title: Safety in current and future hydrogen applications. Abstract: The business idea of HYEX is to provide expert advice within hydrogen and gas safety. We help projects develop safe and cost efficient solutions using quick engineering models in combination with computational fluid dynamics (CFD). This includes documenting risk for permitting processes with authorities, regulators and classification societies. The company: HYEX (https://hyexsafety.com/) is built by Olav Roald Hansen. The main ambition is to facilitate for a safe transition to a hydrogen society. About Speaker: Olav Roald Hansen is a hydrogen safety expert. He worked for Gexcon and Lloyd Register, and now he founded his own company HYEX safety. During his nearly 30 years’ experience in the field, Olav Roald Hansen, played an instrumental role establishing FLACS as a leading CFD software. Know-how from hundreds of large-scale experiments allowed for the development of techniques making FLACS the most accurate and efficient consequence prediction tool for dispersion and explosion. HYEX is built on this knowledge. |
Program 2022 Autumn
| When | Who | What |
|---|---|---|
15.12.2022 10:00-15:00 | Ph.D. Candidate Tom Ivar Pedersen | There will be no seminar this week. Instead, you are invited to Tom Ivar Pedersen’s defense.
More information can be found here. |
02.12.2022 10:00-15:00 | Ph.D. Candidate Renny Jose Arismendi Torres | There will be no seminar this week. Instead, you are invited to Renny Jose Arismendi Torres’s defense.
More information can be found here. |
| 17.11.2022 | Postdoc Dimitrios Tzioutzios Ph.D. Candidate Leonardo Giannini | About Dimitrios: Hej, I am Dimitris! I am a Spatial Planning and Development Engineer with particular research interest in disaster risk reduction and participatory risk management processes. I recently received my PhD in Human Security Engineering from Kyoto University (Japan). My doctoral research focused on risk communication, information disclosure and citizen engagement issues in the context of chemical accidents caused by natural hazards (Natech). Going beyond academic research, my work also involved the development of a serious game for raising community awareness about Natech risks and fostering stakeholder engagement. Since last month, I joined the Department of Mechanical and Industrial Engineering at NTNU as a postdoc fellow. I am currently involved with the international SUSHy Project: SUStainability and cost-reduction of Hydrogen stations through risk-based, multidisciplinary approaches. I am pleased to meet you and looking forward to collaborating with and learning from your work! Abstract for his presentation: After a short introduction, we will talk about how disclosing information about natural-hazard-triggered technological accidents that involve the release of hazardous materials (Natech) empowers all involved stakeholders to make comprehensive and risk-informed decisions. Our previous study ventured to explore how citizens communicate concerning Natech risk information disclosure and propose an approach to enhance community awareness. We surveyed households in Japan and S. Korea to examine how they perceived and communicated about Natech risk. Moreover, we explored the potential of serious gaming for Natech risk communication by proposing and developing EGNARIA: a novel, educational, role-playing board game considering earthquake and tsunami scenarios potentially causing subsequent chemical accidents. Our survey findings suggested that Natech accident risk is perceived as a concerning issue in both countries, however Japanese were significantly more constrained in resolving it through communication. In comparison, S. Korean respondents seemed to be more communicatively active, and more confident in responding to potential Natech accidents. Regarding the proposed serious game, EGNARIA received overall positive scores from players as an engaging, educational tool useful for introducing communities to and discussing about Natech accident risk. Concluding this presentation, we offer a brief overview of our current research project: SUSHy Project, research on SUStainability and cost-reduction of Hydrogen stations through risk-based, multidisciplinary approaches. Self-introduction_Dimitrios Tzioutzios.pdf About Leonardo: I come from Pesaro, a small city in the east cost of Italy near Bologna. Starting this little recap of my life, I want to mention that I attended a “Scientific Highschool” in Pesaro, focusing on physics, chemistry, mathematics, and biology. There, I discovered my passion for engineering, and so I decided to try to make a living out of it, applying to the faculty of engineering at the University of Bologna. My bachelor’s degree was mainly focused on energy production systems, conversion of energy and nuclear power plants. During my master, I decided to focus more on sustainable energy sources: I attended courses about solar energy, ground-coupled heat pumps, pollutant production and plasma technologies. A fairly solid thermo- and fluid- dynamic background allowed me to realize a study on transport pipes for liquefied natural gas (LNG), to investigate boil-off gas production in relation to pipe insulation. This was my first experience with “unconventional” fuels and a good result allowed me to join the Hydrogen Team here at NTNU to write my master’s thesis last year. From LNG I therefore moved to Hydrogen, and my final thesis focused on the analysis of the overpressure generated by the explosion of a Liquid Hydrogen vessel (). At the start of this year, I came back to Italy where I happily graduated with the maximum of grades and immediately started working as a project engineer for a company that produces refrigeration systems. Despite liking the new work, my main goal was to come back at NTNU, where I felt I had some “unfinished business” and since I was interested in academic research. Hence, I applied for a position about hydrogen safety and here I am, happy to be back here with all of you. Now I moved from consequence analysis to inspection planning and maintenance for hydrogen technologies, so I have to (and I will) learn a lot of new stuff, surely finalizing this PhD and hopefully contributing to a little expansion of our current scientific understanding. |
| 03.11.2022 | Ph.D. Candidate Alessandro Campari | Title: Hydrogen Material Damage in a Safety Assessment Perspective Abstract: Hydrogen as an energy carrier, particularly when combined with renewable sources, can make countries energetically self-sufficient and independent in the long term. Nevertheless, its extreme combustion properties, along with the capability of permeating and embrittling most metallic materials, produce significant safety concerns. The European Hydrogen Incidents and Accidents Database (HIAD 2.0) is a public repository that collects data on hydrogen-related undesired events. An analysis of the database through Business Analytics tools is carried out, mining hidden information from the accident reporting system. In addition, several hydrogen-induced material failures are investigated in-depth to learn about their root causes and consequences. As a result, a deficiency in planning effective inspection and maintenance activities to avoid loss of containment of hydrogen technologies is highlighted as a common cause which determines the accidents with the most severe consequences. A Risk-Based Inspection (RBI) approach is recommended for the inspection and maintenance planning of hydrogen technologies. The newest updates in this perspective are provided. About Speaker: Alessandro Campari has a BSc in Energy and Nuclear Engineering and a MSc in Renewable Energy Engineering, both from the University of Bologna (Italy). He is doing a PhD at the Department of Mechanical and Industrial Engineering at NTNU. His research project is titled “Loss prevention and operational safety of hydrogen technologies” and aims to investigate the hydrogen-induced degradation mechanisms of industrial equipment, their modelling, and monitoring. At present, Alessandro is involved in two research projects on hydrogen safety: the European H2CoopStorage and the Euro-Japanese SUSHy. In addition, he has been actively involved in the organization of the activities of the Norwegian doctoral school HySchool, where he is Student Board Representative for NTNU. Note that the physical meeting will be at Gløshaugen Materialteknisk 3. etasje Holand. |
27.10.2022 15:00-16:00 (Digital Only) | Chi Ji | Title: Autonomy safety and SOTIF (Slides are only for internal use, contact sun.tianqi@ntnu.no if you need it) |
Ph.D. Candidate
Alessandro Campari
20.10.2022
(Digital Only)
Abstract: The presentation will start from the introduction of key technologies in autonomous driving and challenges in autonomy safety. SOTIF (safety and intended functionality) will be then presented, including the approach of SOTIF analysis, acceptance criteria and SOTIF validation targets, followed with examples of calculation methods. About |
Speaker: Mrs. Ji has master’s degrees in both engineering and business administration. She has 12 years of working experience in automobile industry (including airbag, braking and autonomous driving). From 2010 to 2018, Mrs. Ji worked at Autoliv and ZF, she was in charge of the functional safety aspects of airbag and braking systems. After 8 years’ in Tier1, Mrs. Ji joined the SAIC Autonomous Driving Center, her main job was focused on L2+ autonomous driving, as well as system level safety analysis work. Last year she joined UL and become an Autonomy safety consultant. | ||
05.10.2022 | Ph.D. Candidate Michael Pacevicius | There will be no seminar this week. Instead, you are invited to Michael Pacevicius’s defense.
More information can be found here. |
| 22.09.2022 | Ph.D. Candidate Muhammad Gibran Alfarizi | Abstract: Bearings are essential to the reliable operation of rotating machinery in manufacturing processes. There is a rising demand for accurate bearing remaining useful life (RUL) predictions. The data-driven technique for predicting RUL of bearing has demonstrated promising prospects to facilitate intelligent prognostics. This paper proposes a new data-driven prediction framework for bearing RUL utilizing an integration of empirical mode decomposition, random forest, and Bayesian optimization. The proposed framework consists of two main phases: feature extraction and RUL prediction. The first phase of this framework focused on decomposing the empirical input signals using empirical mode decomposition into distinct frequency bands to filter out irrelevant frequencies and determine the fault characteristics of the signals. In the second phase, the RUL prediction is then carried out by an RFs-based model with its hyperparameters tuned by Bayesian optimization. The proposed approach is validated using datasets obtained from an actual run-to-failure experiment of roller bearings. The experiment results significantly improved compared to the standard data-driven and stochastic approaches. (The paper can be found here). Hydrogen can be adopted as a clean alternative to hydrocarbons fuels in the marine sector. Liquid hydrogen (LH2) is an efficient solution to transport and store hydrogen onboard of large ships. LH2 will be implemented in the maritime field in the near future. Additional safety knowledge is required since this is a new application and emerging risk might arise. Recently, a series of LH2 large-scale release tests was carried out in an outdoor facility as well as in a closed room to simulate spills during a bunkering procedure and inside the ship’s tank connection space, respectively. The extremely low boiling point of hydrogen (-253°C) can cause condensation or even solidification of oxygen and nitrogen contained in air, and thus enrich with oxygen the flammable mixture. This can represent a safety concern since it was demonstrated that a burning mixture of LH2 and solid oxygen may transition to detonation. In this study, the experimental data of an LH2 release test series recently carried out were analysed by means of an advanced machine learning approach. The aim of this study was to provide critical insights on the oxygen condensation and solidification during an LH2 accidental release. In particular, a model was developed to predict the possibility and the location of the oxygen phase change depending on the operative conditions during the bunkering operation (e.g. LH2 flowrate). The model demonstrated accurate and reliable predicting capabilities. The outcomes of the model can be exploited to select effective safety barriers such as a water deluge system to prevent the oxygen change phase. About Speaker: Muhammad Gibran Alfarizi has a B.Sc. in Petroleum Engineering from Indonesia and a M.Sc. in Petroleum Engineering from NTNU. His research interest include data driven modeling and machine learning. He started his PhD in August 2020. The project title of his Ph.D. is The Digital Transformation and Data-Driven Methods in the Reliability of Safety Systems. |
| 08.09.2022 | Postdoc Xingheng Liu | Title: Spatial-temporal interpolation for condition monitoring: an application to choke valves Abstract: Critical systems such as subsea choke valves works under a time-varying operating condition (TVOC), which makes it challenging to estimate the system’s health state since the health indicator (HI) may be recorded under different TVOC. State-space models together with Particle Filter are widely used for system identification when the functional forms of the relationship between TVOC and HI are explicitly given. However, assumptions on how the TVOC can influence the observation and the growth of HI are generally hard to validate in practice. In this presentation, we introduce the spatial-temporal interpolation methods for state estimation and prognosis for subsea choke valves. Spatio-temporal interpolation is the task of estimating the unknown values of some property at arbitrary spatial locations and times, using the known values at spatial locations and times where measurements were made. The estimated property varies with both space and time, with the assumption that the values are closer to each other with decreasing spatial and temporal distances. For subsea choke valves, the HI (flow coefficient deviation) is the quantity to be interpolated, the operating condition (percent travel) constitutes the 1-D space dimension and the timestamps at which the observations were made form the time dimension. Two popular methods, namely spatial-temporal Inverse Distance Weighting and Universal Kriging, are fitted to the data, before being compared to some other competing models (ARIMA, Wiener process…) We highlight the difference between the fundamental assumptions in these models and showcase the pros and cons of each model in terms of forecasting. Keywords: condition monitoring, state estimation, spatial-temporal interpolation, Kriging, Forecasting. |
25.08.2022 10:00-11:00 | Ph.D. Candidate Tom Ivar Pedersen | Title: Industry 4.0 and Smart Maintenance Abstract: In this RAMS seminar, I will present the results of my Ph.D. project, which is soon to be completed. My Ph.D. project belongs to the research program BRU21. BRU21 stands for Better Resource Utilization in the 21st century and is NTNU’s research and innovation program in digital and automation solutions for the Norwegian oil and gas industry. The main objectives of my Ph.D. project have been to explore how the introduction of digital solutions and concepts from Industry 4.0 to maintenance can help improve the competitiveness of this industry sector. Opponents: Postdoctoral fellow Xingheng Liu, PhD Candidate Endre Sølvsberg |
Program 2022 Spring
| When | Who | What |
|---|---|---|
| - | - | No more meetings until August due to the holiday season |
09.06.2022 | Guest Ph.D. Candidate Théo Serru | Title: Modeling Cyberattacks Propagation in Cyber-Physical Systems using Discrete Event Simulation Abstract: Cyber-Physical Systems (CPS) are more and more used in our everyday life. Such systems are safety critical as they can have catastrophic effects on their environment and users. To lower the risks of safety critical situation, model-based safety assessments (MBSA) of such systems have been developed and used in industry. However, the very nature of CPS makes them vulnerable not only to accidental failure but also to cyberattacks. Thus, this seminar will present an approach based on discrete event systems to analyze the effects of multi-step cyberattacks on the safety of CPS. We show how to represent systems, their components (either software and/or hardware), links, security measures, and attacks from a malicious intruder. We then show how the formal modeling language AltaRica, primarily dedicated to safety analyses, can be used to assess cyberattacks by representing the system and extracting automatically sequences of attacks leading to a safety critical situation. Finally, as the extraction of sequences is subject to state-space explosion, we will introduce a new notion called footprint. This cutoff allows to consider the dependent nature of cyberattacks to lower the state-space and reduce the number of sequences generated to keep the more likely (without using probabilities). About Speaker: Théo Serru is a PhD candidate in a thesis funded by CY initiative excellence and Apsys-Airbus. The subject of his research is the formal modeling of safety and cybersecurity properties on cyber-physical systems. He is also a dependability engineer graduated from the engineering school Polytech Angers. |
| 19.05.2022 | Ph.D. Candidate Yixin Zhao | Title: An Extended Cascading Failure Model for Loading Dependent Systems with Multi-state Components Abstract: Many production systems consisting of multiple components are vulnerable to the cascading failures, and one example is that the overloading of a component will also affect the other components. Such loading dependence can result in failure propagation and make the systems unavailable and the maintenances more challenging. In this study, we develop a multistate CASCADE model for evaluating the propagation process of cascading failures in loading dependent systems. The multinomial distribution is applied and derived to represent the probability of total number of overloading components and failures. Probability distributions of cascading process stop scenarios are also developed. Numerical examples are investigated with the proposed model for evaluating the factors influencing the probability distributions of total number of failed and overloading components, as well as the occurrences of three stop scenarios. The multi-state CASCADE model and numerical study can provide reference for optimization of some controllable variables in design or maintenance of a general loading dependent system subjected to cascading failures. About Speaker: Yixin Zhao has a B.E. and M.E. in Safety Engineering and Science from China. She started her Ph.D. in Octorber 2020 at RAMS group, MTP, NTNU, with main supervisor Yiliu Liu and co-supervisor Jørn Vatn. |
| 05.05.2022 | Ph.D. Candidate Wanwan Zhang | Title: Condition-based opportunistic maintenance of cascaded hydropower stations Abstract: The purpose of this paper is to build a new condition-based opportunistic maintenance (CBOM) model. It combines short-term hydro scheduling (STHS) and generator maintenance scheduling (GMS) by failure property. One generator in a cascaded hydro system is used as research example. CBOM model schedules 9 maintenance activities in one year for this generator. Sensitivity analysis reveals that this model offers sufficient flexibility to modify scheduling plans based on maintenance requirements. In all the parameters, accident penalty cost and maintenance duration have no effect on maintenance results. Upper and lower limits of failure probability influence the number of maintenance activities. Compared with age-based maintenance (ABM), CBOM strategy obtains more profits and cancels unnecessary maintenance activities by trade-off between operation and maintenance. |
28.04.2022 (12:00-13:00) | Postdoctoral Fellow Federico Ustolin | Title: Modelling of accident scenarios from hydrogen transport and use Abstract: Hydrogen is one of the best candidates in replacing fossil fuels in order to tackle global warming and decarbonise the energy sector. Therefore, hydrogen could be employed in new applications (viz. road transport, maritime, aviation) from which emerging risks might arise. Knowledge gaps for many phenomena still exist for hydrogen. In particular, the behaviour of cryogenic liquid hydrogen during some accident scenarios (e.g. physical explosions) is still unknown. Thus, different research questions emerge: how a cryogenic liquid hydrogen tank performs when exposed to a fire? And what are the consequences of its catastrophic rupture? Are the risk-based inspection methodologies effective for hydrogen technologies? The answers to these questions and an overview on hydrogen safety research carried out at NTNU by the RAMS group will be provided during the seminar. About speaker: Federico Ustolin graduated in Mechanical Engineering at the University of Trieste, Italy. In July 2021, he was awarded a PhD in Mechanical Engineering by NTNU. Since 2018 Federico has been part of the RAMS group at NTNU, he is currently Postdoctoral fellow at MTP, and his research focuses on hydrogen safety. In November 2021, he got the Hydrogen Europe Research Young Scientist Award 2021 for the cross-cutting pillar. |
| 07.04.2022 | Ph.D. Candidate Emefon Dan | Title: Performance assessment of redundant strategies for multi-component system subject to random shocks Abstract: Redundancy is often essential for achieving high system availability. An additional benefit of installing redundant components is that the total system load can be shared among the components. While the system may benefit from having more redundant components, the active components often share a common source of random failure (shocks) which may lead to unexpected system downtime. In this study, we analyse the performance of two redundant strategies: active strategy, where all the components are running from the start and benefit from load sharing but are exposed to a common source of random shocks and a passive redundancy strategy where one of the components is in standby raising the workload of the active components on the one hand, but unaffected by the common source of shocks on the other hand. We compare the performance of both strategies for different frequencies of occurrence of the random shocks and different degrees of load sharing. About Speaker: Emefon Dan has a bachelors in Mechanical Engineering from Nigeria and an MSc in RAMS from NTNU. He started his PhD in October 2021. He is working on Condition-based maintenance decisions for subsea systems with digital twins. |
| 24.03.2022 | Ph.D. Candidate Bahareh Tajiani | Title: Lead Time Modeling for Optimization of an Alarm Threshold Abstract: Lead time is the time from when a spare part is ordered until it arrives, or it is the time from when a maintenance action is ordered until it is carried out. Most recent literatures focused on deterministic lead time in maintenance context to find an optimal maintenance policy, however in real-life applications, lead time is a stochastic variable depending on many factors such as availability of the maintenance team, type of failure, delivery time of an item, etc. In this presentation, we will discuss the deterministic and stochastic lead time modeling for the continuously monitored systems subject to gradual degradation in order to find an optimal alarm threshold. Furthermore, some ideas will be proposed regarding how the model can be improved to consider different failure mechanisms such as external shocks. About Speaker:Bahareh Tajiani has a BSc in Industrial Engineering from Iran and a MSc in RAMS from NTNU. She started her work as a PhD candidate at RAMS group, MTP, NTNU in August 2019. Her PhD working title is mathematical modeling for remaining useful life (RUL) prediction of bearings which is an internal project at NTNU. |
| 10.03.2022 | Ph.D. Candidate Jie Liu | Abstract: The topic of the presentation is about comparison of RUL prediction models which including stochastic approaches and digital twin of Matlab. Data used for prediction is from experiment of RAMS lab. Two stochastic approaches are selected which are Wiener process and Geometric Brownian Motion. The purpose of the study is to compare the models for remaining useful life prediction with standard stochastic approaches and digital twin through real degradation data and try to find the comparison among them. The research could be used as a reference for further remaining useful life prediction research. About Speaker: Jie Liu has a bachelor’s degree in Applied Mathematics in Beijing Institute of Technology from China and a master’s degree in RAMS of NTNU. She started as a PhD candidate at RAMS group, MTP, NTNU in September 2021. Her research topic is Digital Twin Qualification for Maintenance, which is a part of SUBPRO project. |
24.02.2022 15:00 - 18:00 | Ph.D. Candidate Nanda Anugrah Zikrullah | There will be no seminar this week. Instead, you are invited to Nanda Anugrah Zikrullah’s defense.
More information can be found here. |
09.02.2022 10:30-11:30 | Guest Ph.D Candidate Danilo Colombo | Title: Optimizing the testing policy for the Blowout Preventer Abstract: The topic of the presentation is the optimization of the testing policy of a subsea Blowout Preventer (BOP). The subsea BOP is a safety-critical equipment used during the construction or intervention in a well. It is installed at the top of the wellhead, near the seabed, and connects the well with the rig via riser. When a kick occurs, i. e., the formation fluids start to flow into the wellbore, the BOP is activated and acts like a valve, sealing the well and preventing an oil spill from occurring. To ensure its availability and safety, the BOP is periodically tested, which entails the operation to be stopped. The tests are done usually according to the best practices (e.g. regulations, standards). The downtime due to the testing period may have a significant economic impact. The aim of this study is to optimize the test strategy for BOP reducing costs while satisfying the integrity lever required. To do so it will be considered three kinds of tests: (i) functional tests, (ii) partial pressure tests; and (iii) maximum pressure tests. The study will investigate a formulation for the test coverage and costs of each test. The test policy should consider the last overhaul of the BOP (i.e., the age of components) and failures that lead to a loss of redundancy in the system, which affects the probability of having a safety impact. Possible future developments are: (i) to include the degradation caused by the test; (ii) to consider dependent failures. About Speaker: Guest Ph.D Candidate from Brazil, Danilo Colombo. He is a mechatronics engineer and obtained a M.Sc in Production Engineer with the work in Markov chains to model the subsea well integrity. He is a petroleum engineer at Petrobras and he is currently an advisor in reliability and risk analysis at the CENPES Research Center. He is a member of SPE (Society of Petroleum Engineers) and ABRISCO (Brazilian Association of Risk, Reliability and System Safety). |
| 27.01.2022 | Ph.D. Candidate Lin Xie | There will be no seminar this week. Instead, you are invited to Lin Xie’s defense.
Check the program for more information. Lin Xie_english program.pdf |
13.01.2022 (Digital only) | Ph.D. Candidate Lin Xie | Title: Safety barriers in complex systems with dependent failures—Modeling and assessment approaches Abstract: Technical systems are becoming more and more complex with a degree of dependencies. Such dependency issues can significantly reduce system reliability and cause catastrophes without proper prevention. Therefore, a variety of control measures, such as safety barriers, are necessary to be adopted against dependent failures and ensure the safety of technical systems. However, in the current literature, neither the effects of dependent failures within safety barriers nor the impact of safety barriers against dependent failures has been well studied. Therefore, it is desirable to analyze and model the effects of safety barriers in complex systems considering dependency issues, such as dependency between safety barriers and the environment, dependent failures within safety barriers, and safety barriers against dependent failures. The Ph.D. thesis bridges safety barriers and complex systems by considering the dependency issues. The aim is broken into four objectives addressed in five journal articles and three conference articles. |
...
| When | Who | What |
|---|---|---|
- | - | No more meetings until January due to the holiday season |
09.12.2021 (Digital only) | Professor Shen Yin | Title: Robustness and Sensitivity of AI systems - Two Sides of a Coin Abstract: In recent years, artificial intelligence has made remarkable breakthrough, where a large number of AI-enabled systems have been developed and applied in manufacturing industry, medical care, cyber security, and many other fields. An interesting phenomenon lies in the different design targets of AI models – some should be robust to the abnormal changes of data while the others should be another way round. For example, to predict the remaining useful life of batteries, it is favorable to develop robust AI where the model is expected to be least affected by disturbances. By contrast, the sensitivity of the model might be critical in order to diagnosis of cyber-attacks, in which the AI models should be highly sensitive to malfunctions and malicious attack behaviors, keeping effective in case of any insignificant changes. From an engineer point of view, this talk will focus on both robustness and sensitivity of AI systems, which are regarded as two sides of a coin. The formulation of several typical demand-driven examples, the design approaches, and the corresponding performance will be introduced. A balance between sensitivity and robustness of AI is worth to be considered further in the R&D phase to cope with various demands in practice. About Speaker: Shen Yin received the B.E. degree in Automation from the Harbin Institute of Technology, Harbin, China, and the M.Sc. degree in Control and Information Systems and the PhD. (Dr.-Ing.) degree in Electrical Engineering and Information Technology from the University of Duisburg–Essen, Germany. |
| 25.11.2021 | Researcher Shenae Lee | Title: An approach to update the reliability performance of safety barriers based on operating experience (The paper is to be submitted for Loss Prevention 2022) Abstract: Hazardous events in process plants like the leakage of dangerous substances can result in severe damage, and such an event is often defined as the TOP event of a fault tree analysis (FTA) in a quantitative risk analysis. The input data for a FTA are often generic reliability data that are not necessarily catered for a plant specific analysis. Therefore, this paper presents an approach based on Bayesian network (BN) analysis with a focus on Hierarchical Bayesian analysis for handling situations where plant-specific data are sparse. The suggested approach is demonstrated by a case study of a pressure vessel. About Speaker: Shenae Lee is currently a researcher at MTP, NTNU (2020-2022). She finished her Ph.D. at RAMS group, MTP in 2020. She has B.Sc. in Nanotechnology from South Korea and M.Sc. in RAMS, NTNU. |
| 11.11.2021 | Ph.D. Candidate Tom Ivar Pedersen | Title: Data-exploration and possibilities for anomality detection and RUL-prediction Abstract: A dataset of maintenance records and sensor readings from a group of water cooled power cords collected from a plant in the process industry will be presented. Two master students at NTNU used this dataset in their master thesis earlier this year. They explored the possibilities for estimating remaining useful life (RUL) for these component. As part of his Ph.D., he plans to investigate this dataset further. The goal of this presentation is to discuss how this dataset can be used as basis for a paper. He has done some preliminary data exploration and found that there are two types of failures in the dataset. One type is a gradual degradation that can be tracked with a health indicator. A preliminary plan is to use some variant of the Wiener process as basis for RUL-prognosis. |
04.11.2021 (postponed due to time conflict) | Ph.D. Candidate Ewa Maria Laskowska, Emefon Dan | Title: Maintenance Optimization of Emergency Shutdown Valves (ESV) Abstract: The topic of the presentation is the optimization of maintenance and testing policy of Emergency Shutdown Valves (ESVs). ESVs are safety critical equipment used in oil and gas facilities. They are used only in case of a demand and remain passive due to normal operation. To ensure their safety ESVs have to be periodically (full proof tests) tested what often require production shutdown and leads to faster use of these valves. It is also possible to test valves online by so-called partial stroke tests (PST). Although this kind of test doesn’t impede the production process it is less reliable than full proof tests with regard to capacity of revealing failures. The aim of this work is to find the optimal maintenance strategy for ESVs while satisfying ESVs safety requirements. The modelling framework is based on the Markov state degradation model. In such a model, the condition of ESVs is defined by discrete states. The important part of the approach is to consider condition-based inspection policy, when the testing intervals are dependent on the ESV’s condition. Two types of valves tests are considered: partial (online) tests and full proof tests. They differ with regard to the test coverage (reliability) and cost of testing. At each inspection the decision about repair is made, so that valve’s condition can be improved to a better state, or no repair is made but there is a shift in testing frequency. Also repairs have different cost assigned depending on whether they are performed online require production shutdown. Parameters or variables considered in the model: - There are 2 variables (parameters) regarding state of the valve: state and coverage. - There are 2 types of inspections: Full Poof Tests (FPT) and Partial Tests (PT). - There are 2 decision variables with regard to condition of the valve: repair decision and inspection interval. - There are 3 kind of repairs: online repairs, repairs performed during planned shutdown and repairs requiring unplanned shutdown - There are 2 aspects to consider with regard to cost of maintenance. First the cost depends on the revealed condition of the valve. Second, the cost can be accordingly increased or reduced depending on whether it requires unplanned shutdown and is performed withing a planned shutdown - There are two cost figures related to condition monitoring: cost of FPT and cost of PT Speaker: Ph.D. candidate Ewa Maria Laskowska Title: New Ph.D. Candidate Self-introduction Emefon Dan - Self introduction.pdf Speaker: Ph.D. candidate Emefon Dan Note that the physical meeting will be at Gløshaugen Materialteknisk 3. etasje Holand. |
14.10.2021 12:00-13:00 | IEEE Reliability Society, Sweden and Norway Joint Section Chapter | There is no RAMS seminar this week. Instead, you can attend the Kick-off & Webinar of IEEE Reliability Society, Sweden and NorwayJoint Section Chapter. The agenda is as follows:
Speakers: Prof. Min Xie was awarded a scholarship to pursue his undergraduate study in Sweden in 1979. After graduating from KTH, he continued with his PhD study under the supervision of Prof Bo Bergman at Linköping University, and completed his PhD in 1987. He has been involved in IEEE Reliability Society activities since then, and was elected IEEE Fellow in 2005. Prof. Xie moved to National University of Singapore in 1991 and then to City University of Hong Kong in 2011. He has published over 300 journal papers and several books, and guides over 50 PhD students. Dr. and Adjunct Prof. Pierre Dersin studied at MIT, where he obtained first a MS in Operations Research, then a Ph.D. in Electrical Engineering under Prof. Michael Athans. Since 1990, Dr. Dersin has been with Alstom (St-Ouen, France), mainly active in Reliability Engineering and Maintenance of Railway Systems. In particular, he founded there the “RAM Center of Excellence”. He started Alstom’s Predictive Maintenance Program. He is currently Prognostics & Health Management (PHM) Director in Alstom’s Digital & Integrated Systems Division, as well as ‘ RAM Master Expert’. He is the author of many publications in Reliability, Automatic Control, and Power Systems, including four chapters the “Handbook of RAMS in Railways: Theory & Practice” (CRC Press,Taylor & Francis), 2018. Pierre Dersin is a member of the IEEE Reliability Society AdCom and leads the Technical Committee on Systems of Systems. |
30.09.2021 (Digital only) | Yuchen Jiang and Shimeng Wu from Harbin Institute of Technology | Title: Remaining useful life prediction based on machine learning approaches Abstract: Digital transformation and digital twin technologies have facilitate the connection, the interaction, and the in-depth integration of the physical space and the virtual digital space. Colossal amount of process data are available and waiting to be made use of. In light of this, the safety and reliability challenges in industrial systems are likely to usher novel solutions. In this talk, we will share our recent work on system-level RUL prediction based on machine learning approaches. The work is practical problem-driven and therefore the talk will focus on analysis of the practical problem we study, the data-related problems, the feature exploitation tools, and the ideas of how to achieve accurate RUL prediction. Finally, a short discussion will be made about the pros and cons of ML-based and traditional model-based approaches. |
16.09.2021 (Digital only) | PhD candidate Jie Liu, Wanwan Zhang | Title:New Ph.D. Candidate Self-introduction |
02.09.2021 (Digital only) | Postdoc Xingheng Liu | Title: Modeling choke valve erosion with dynamic system Abstract: Choke valve erosion is a major issue encountered in subsea oil production. When the valve is severely eroded, production needs to be slowed down or shut off to reduce the risk of major incidents such as leakage. Visual inspection is hardly possible for subsea equipment and therefore the monitoring of a choke valve installed at an X-mas tree/manifold relies usually on the monitoring of a degradation indicator, Cv (flow coefficient). The Cv indicates a valve's capability to let the fluid flow through a choke. Theoretically, the Cv increases monotonically at a given opening (valve travel/lift) with the erosion. The issue with using Cv as a degradation indicator is that the valve is operated at a non-constant opening. Consequently, plotting Cv against time will lead to a non-monotonic Cv curve. Inappropriate use of the recorded Cv sequences can therefore give misleading results about the degradation level and erosion rate. We propose to use a dynamic system to model the choke valve erosion. The hidden state evolving over time is the effective flow area (EFA) that becomes larger as the valve is eroded. The system model shows how the hidden states evolve each day and is established based on physical models (erosion response model, fluid mechanics equations) and Gamma process (for intrinsic erosion growth randomness). The observation model shows the relationship between observed Cv and the effective flow area, accounting for measurement noise. With some field data (daily allocated flow rate, sand rate, valve opening) and choke valve features (flow characteristics, Cv curve), we can estimate the model parameters and predict the erosion growth and remaining useful life of the valve. About Speaker: Xingheng Liu is a postdoctoral fellow at RAMS group, MTP, NTNU. His research topic is Prediction and optimization of remaining useful lifetime, which is a part of SUBPRO project. He completed his cotutelle Ph.D. in ROSAS (department of Operational Research, Applied Statistics and Simulation) at the University of Technology of Troyes (fr) and in RAMS at NTNU and earned his Master's and Bachelor's degree in Industrial Engineering at UTT. |
19.08.2021 | Ph.D. Candidate Endre Sølvsberg | Abstract: As part of the EU project Qu4lity, the Continental pilot “Autonomous Quality in PCB Production for Future Mobility” involves PCB (Printed Circuit Board) production in an SMD (Surface-Mount Device) line at their site in Sibiu, Romania. The main issue is faulty PCBs passing all in-line testing, and being sent out to customers, resulting in a high number of customer returns. The Pilot team has cooperated with domain expertise on-site in Romania to identify critical variables from the Continental Datalake and employed a PCA approach using the Mahalanobis Distance to identify customer returns as outliers and enabling the quality team at Sibiu to identify faulty PCBs before they are sent out to customers. Using a Docker container, the PCA algorithm has been automated with a Python script. An integrated GUI enables the quality team and other relevant people to see PCBs that are tagged by the algorithm as outliers, in addition to check individual unit ID tags. Through 5 months of PCB production, there have been 171 customer returns, and the quality team at Sibiu has validated that the algorithm was able to identify 169 of these PCBs as outliers, close to 99% of all customer returns in the 5 month period. About Speaker: Endre Sølvsberg has a BA in Economics and an MSc in Sustainable Manufacturing. He has lectured at NTNU in the Masters level course Scientific Methodology. He has worked at SINTEF Manufacturing as a project engineer and researcher, in projects involving I4.0, ZDM and Smart Maintenance. He has served as the technical lead for SINTEF in the Continental Pilot in the EU Quality project. The working title of his PhD project is “Extending lifetime of Norwegian oil installations using predictive maintenance through condition and remaining useful life estimation", and the project is sponsored by OKEA and part of the NTNU program BRU21. Opponents: Harald Rødseth, Ph.D. candidateJon Martin Fordal |
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