(Photos: by Liu Yang)
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19.01.2018 | Behnaz Hosseinnia Xiaopeng Li | Title: New Ph.D. Candidate Self-introduction Speaker: Behnaz Hosseinnia Self intorduction_Behnaz.pdf Abstract: Introduce herself and talk about her previous research project at Safety and Security Science group at TU Delft, the Netherlands. She will also give a brief introductionofherPhD research topic at RAMS group. About Speaker: NewPhD student within RAMS group. She received her master degree in chemical engineering (minor: HSE) and did her undergraduate studies in Safety and Technical Protection Engineering in Petroleum University of Technology (Iran) with the first rank honor. In her M.Sc.thesis she has studied the application of fire and explosion modeling, failure probability analysis and quantitative risk-based decision making in petroleum pipelines emergency response planning. Besides the academic experience, two internships with National Iranian Oil Company (NIOC) and four-year work with engineering consultancies have enabled her to combine the technical knowledge with hands-on experience in risk analysis, process safety and accidents consequence modeling. From 2016, she worked as a researcher at the Safety and Security Science group in TU Delft, the Netherlands. Her research project was funded by LDE (Leiden. Delft. Erasmus) Centre for Safety and Security and focused on developing an effective decision-making tool for multi-plant emergency response planning against terrorist attacks in the chemical industrial areas. Speaker: Xiaopeng Li ( Exchange Ph.D. candidate) Self-introduction_Xiaopeng Li.pdf About Speaker: He is from College of Management and Economics, Tianjin University, China. He will introduce himself and his previous research works on warranty management in Tianjin University and his research plan in NTNU. |
| 26.01.2018 | Wenyan Song | Title: Data-driven fuzzy modeling method and its application Data driven_Wenyan.pdf Abstract: Fuzzy modeling method is an effective computation intelligence technology that can handle data information and human knowledge. Now it has been widely applied in system modeling, decision system design and data analysis. In this talk, we will introduce some basic concepts about fuzzy set theory and a few examples of fuzzy modeling method combined with other machine learning algorithms. Besides, we also introduce some application cases about fuzzy modeling. Speaker: Dr. Wenyan Song is an associated professor in School of Economic, Dongbei University of Finance and Economics University in China. She has research interests in machine-learning, and she works more in applying the technique to industrial process and financial market. |
02.02.2018 | HyungJu Kim | Title: Systems-Theoretic Process Analysis (STPA) for subsea systemsSTPA to Subsea_HyungJun Kim.pdf Abstract: Systems-Theoretic Process Analysis (STPA) is a recently developed hazard identification technique that is based on control and systems theory. Previous studies on STPA emphasizes two major strengths of the method: (1) STPA provides a systematic top-down approach that enables early identification of system flaws, and (2) STPA covers a wider scope of hazards compared to traditional methods. Despite these advantages, there are only a limited number of studies that have applied the method to subsea systems. It is therefore of interest to investigate how STPA can be used to formulate new or verify existing requirements for safety-critical systems for subsea facilities. The contents of the presentation are 1) Introduction to STPA; 2) Ongoing STPA studies in RAMS group; 3) STPA to subsea gas compression system - ESREL 2018 conference; 4) STPA toisolationof subsea STPAtoisolationofsubsea wells - OTC 2018 conference About speaker: Hyungju Kim is a postdoctoral fellow at RAMS group, MTP, NTNU. His research topic is new control and safety philosophies of subsea systems, which is a part of SFISUBPRO project. He completed his Ph.D. in RAMS at NTNU and earned his Master's and Bachelor's degree in Naval Architecture and Ocean Engineering at Seoul National University. Before he started his Ph.D. at NTNU, he worked for Samsung Heavy Industries for seven years, as a naval architect. |
16.02.2018
| Harald Rødseth | Title: Risk-based maintenance backlog Maintenance backlog _Harald.pdf Abstract: TBAA relevant issue in manufacturing and production seems to be “silo”- organizations and “silo”- planning with lack of coordination between departments. Integrated Planning (IPL) is a concept that aims to cope with this “silo”-problem. With the ground-breaking potentials from Industry 4.0, it should be expected that the advancement of IPL will speed up in development and implementation in companies. To manage IPL sound key performance indicators (KPIs) must be implemented and established by the company. A promising indicator for IPL is maintenance backlog (MB). A strength of this indicator is the capability to be modeled with Risk OMT (Risk modeling – Integration of Organisational, human and Technical factors). It remains to investigate how MB can be modeled to a Quantitative Risk Analysis (QRA). The main objective of this article is to develop a model of MB in QRA. In particular, the article demonstrates a case study of a production system where both fault tree analysis (FTA), and event tree analysis (ETA) is modeled. The article discusses About speaker: Harald Rødseth, Postdoctoral fellow, MTP, NTNU. Opponents: Prof. Jørn Vatn & Ph.D. candidate Yun Zhang |
02.03.2017 | Professor Anne Barros | Title: On the Use of Piecewise Deterministic Markov Processes in Reliability and Maintenance PDMP_Anne Barros.pdf Abstract: Piecewise deterministic Markov processes (PDMP) are widely used in dynamic reliability to model phenomena which are considered as deterministic most of the time (e.g. evolution of the fluid level in a tank) and which are influenced from time to time by stochastic events (e.g. failures in the control loop for the fluid level). Usually, a PDMP is made of a set of differential equations (deterministic part) whose solutions can experience random “jumps” (effect of stochastic events). We present here a very specific type of PDMP: the deterministic part is reduced to a set of trivial differential equations whose solutions will be used to measure the time elapsed since the last stochastic events. Hence, the deterministic part is not related to any physical phenomena but is an artifact to model stochastic behaviors that require a combination of discrete random “jumps” and continuous variables to count time. We will discuss how such PDMP can be used to study maintained systems with several units. Stochastic jumps will model failure, repair, detection times while the continuous variables will model deterministic repair durations or delays, timebetween the time between inspections, time spent in different states of interest (especially in case of Weibull lifetime or repair time). We will try to explore how such a formalism can help for the modeling work, and when an explicit numerical scheme can be easily developed to calculate the quantities of interest (MDT, Availability, Reliability, Mean number of repairs…). About speaker: Anne Barros is a professor at NTNU in the Department of Mechanical and Industrial Engineering. Her research activity is focused on the use of stochastic processes in Reliability and Maintenance. Career: Master's degree in Systems Control from the University of Technology of Compiegne UTC (France), 2000, Master of Engineering in Industrial System from the University of Technology of Troyes UTT (France), 2000 and PhD2000andPhD(dr.philos) in Optimisation and System Safety from UTT, 2003. Associate Professor of Reliability and Maintenance engineering at UTT (2003-2011). Professor of Reliability and Maintenance engineering at UTT (2011-2014). Professor of Subsea Reliability at Norwegian University of Sciences and Technology NTNU (professorship founded byDNVby DNV-GL, 2014-). |
| 16.03.2018 | Professor Antoine Rauzy | Title: Reliability Analysis of Looped Systems Abstract: It is well widely assumed (and true) that reliability block diagrams are equivalent to fault trees, although this equivalence is formally established in no textbook. A reliability block diagram can be seen as an oriented graph: blocks are represented by nodes and connections between blocks by edges of the graph. This graph is oriented, contains no loop (is acyclic), has a unique source node s and a unique target node t. The system described by the reliability block diagram works if and only if there is a working s-t path in the graph, an i.e. s-t path along which all nodes are working (only nodes can fail, edges are assumed to be perfectly reliable). An interesting question is: what does happen if we accept loops, i.e. if we consider reliability networks rather than reliability block diagrams? Assessing the reliability of networks is indeed of practical importance as most infrastructures can be seen as networks. Nevertheless, reliability networks are only seldom used as a modeling tool. In this seminar, the main mathematical results explaining why it is so and present several algorithms to solve the problem will be recalled. About speaker: Antoine B. Rauzy has currently a full professor position at Norwegian University of Science and Technology (NTNU, Trondheim, Norway). He is also the head of the chair Blériot-Fabre, sponsored by the group SAFRAN, at CentraleSupélec (Paris, France). During his career, he moved back and forth from academia to industry, being notably senior researcher at French National Center for Scientific Research (CNRS), associate professor at Universities of Bordeaux and Marseille, professor at Ecole Polytechnique and Ecole Centrale Paris, CEO of the start-up company ARBoost Technologies he founded, and director of the R&D department on Systems Engineering at Dassault Systemes (largest French software editor). He got his PhD in 1989 gothisPhDin1989 and his tenure (habilitation àdirigerdes Recherches) in 1996, both in computer science. He works in the reliability engineering field for more than 20 years. He extended his research topics to systems engineering more recently. He published over 150 articles in international conferences and journals. He is on the advisory boards of several international conferences and journals and is regularly invited to deliver keynote talks at international conferences. He renewed mathematical foundations and designed state-of-the-art algorithms of probabilistic safety/risk assessment. Alone or with his students and collaborators, he developed safety/risk assessment software that is daily used in industry (Aralia, XFTA, MarkXPR). He is also the main designer of the AltaRica modeling language and the scientific advisor of the Open-AltaRica project (IRT SystemX). He managed numerous collaborations between academia and industry, in Europe, in the USA and in JapantheUSAandinJapan, and has been the adviser of fifteen PhD thesesfifteenPhDtheses. |
| 06.04.2018 | Shenae Lee
| Title: Application of Bayesian Belief Networks (BBNS) for process plant Abstract: TBA About speaker: Shenae Lee, Ph.D.student of RAMS group, MTP, NTNU. This study is about risk analysis of process plants where main accidents continue to occur. Conventional risk analysis method has the limitation of having a static structure, while another challenge is difficult to aggregate operational data from different sources. To focus on these limitations, the paper suggests an approach based on Bayesian networks (BNs), and it is illustrated by a case study of a pressure relief valve in an Ammonia plant. The approach seems to be suitable for updating frequency of accident scenarios when new risk information is collected during the operational phase. About speaker: Shenae Lee is a Ph.D. student in RAMS group. The topic for herPhDis a dynamic risk analysis of major accident hazards in process facility operations to support safety-critical decisions. She is under the main supervision of Prof. Nicola Paltrinieri in RAMS group. She has a Master’s from the international RAMS program, NTNU. Opponents: Pierluigi Salvo Rossi, Kongsberg Digital AS, Norway; Juntao Zhang, RAMS group |
| 20.04.20.04.2018 | Associate Professor Astrid S. de Wijn | Title: Traffic jams Abstract: TBA About speaker: Associate Professor, MTP, NTNU. |
| 04.05.2018 | Juntao Zhang | Title: Adapting Systematic Theoretic Process Analysis for Reliability Analysis Abstract: TBA About speaker: Juntao Zhang, Ph.D.student of RAMS group, MTP, NTNU. |
| 25.05.2018 | Yun Zhang | Title: Modelling methodology and patterns for the monitored system using formal modeling language AltaRica 3.0: a study case Abstract: TBA About speaker: Yun Zhang, Ph.D.student of RAMS group, MTP, NTNU. |
| 01.06.2018 | Himanshu Srivastav, Lin Xie, Aibo Zhang | Title: Presentation for ESREL
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| 08.06.2018 | Associate Professor Cecilia Haskins | Title: Systems Engineering in 45 minutes Abstract: TBA About speaker: TBA |
15.06.2018 | Closing social event |
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| When | Who | What |
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- | - | No more meetings until January due to the holiday season |
15.12.2017
| Liu Yang
Closing social event | Title: An Algebraic foundation of combinatorial reliability models (Finite Degradation Structures - Liu Yang.pdf) Abstract: The combinatorial models, including fault trees and reliability block diagrams, are basic models in reliability analysis, in which components are traditionally assumed to be either working or failed (i.e. Boolean cases), and then to be composed using the logic connectives (and, or, …) to represent the failure mechanism of the system. In our work, the mathematical foundation of these models is extended from the Boolean algebra to a more generalized algebraic structure, which we call the “Finite Degradation Structure” that allows a component to have more than two states (working, degraded, failed1, failed2, …) but still be combinatorial. This presentation will start with a formal introduction of the Combinatorial Degradation Structure, including some basic concepts and the extended minimal cut sets and importance measurements. Then, a couple of examples will be given to show how it works for reliability analysis. About speaker: Liu Yang, Ph.D.student of RAMS group, MTP, NTNU.
Pizza or cake
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07.12.2017
| ROSS Gemini Seminar | ROSS Gemini Seminar(RAMS) Abstract:
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01.12.2017 | Pierluigi Salvo Rossi (Principal Engineer, Kongsberg Digital AS) | Title: Machine Learning & Industry 4.0 (Kongsberg Digital presentatio_DDL.pdf) Abstract: Artificial intelligence, big data, internet of things, machine learning, sensor networks are popular terms which currently pervade almost every human activity. A crucial field which contributes significantly to their success is the industrial setting, where the marriage between information technology and process technology is denoted Industry 4.0. This talk will start with introducing the driving elements which contributed to the large popularity of machine learning in the industrial setting and then focus on the significant role that such knowledge plays within the Kongsberg Group. Activities, where Kongsberg Digital is developing machine-learning tools, are presented and special emphasis is given to the projects in collaboration with NTNU. About speaker: Pierluigi Salvo Rossiwas born in Naples, Italy, 1977. He received the Dr.Eng. degree in telecommunications engineering (summa cum laude) and the Ph.D. degree in computer engineering, in 2002 and 2005, respectively, both from the University of Naples “Federico II”, Naples, Italy. From 2005 to 2008, he worked as a postdoc at the Dept. Computer Science & Systems, University of Naples “Federico II”, Naples, Italy, at the Dept. Information Engineering, Second University of Naples, Aversa (CE), Italy, and at the Dept. Electronics & Telecommunications, Norwegian University of Science and Technology (NTNU), Trondheim, Norway. From 2008 to 2014, he was an Assistant Professor (tenured in 2011) in telecommunications at the Dept. Industrial & Information Engineering, Second University of Naples, Aversa (CE), Italy. From 2014 to 2016, he was an Associate Professor in signal processing with the Dept. Electronics & Telecommunications, NTNU, Trondheim, Norway. From 2016 to 2017 he was a Full Professor in signal processing with the Dept. Electronic Systems, NTNU, Trondheim, Norway. Since 2017 he is a Principal Engineer with the Advanced Analytics and Machine Learning Team, Kongsberg Digital AS, Norway. He held visiting appointments at the Dept. Electrical & Computer Engineering, Drexel University, Philadelphia, PA, US, at the Dept. Electrical & Information Technology, Lund University, Lund, Sweden, at the Dept. Electronics & Telecommunications, NTNU, Trondheim, Norway, and at the Excellence Center for Wireless Sensor Networks (WISENET), Uppsala University, Uppsala, Sweden. He is an IEEE Senior Member and serves as Senior Editor for the IEEE Communications Letters (since 2016) and Associate Editor for the IEEE Transactions on Wireless Communications (since 2015). He was Associate Editor for the IEEE Communications Letters (from 2012 to 2016). His research interests fall within the areas of communications and signal processing. |
| 17.11.2017 | Prof. Baruch Barzel (Bar-Ilan University) | Title: Dynamic Resilience of Complex Networks (PresentationBarzel.pdf) Abstract: Resilience, a system’s ability to retain functionality under errors, failures and environmental perturbation, is a defining property of many complex systems. Yet, despite its widespread consequences for human health, the economy and the environment, events leading to loss of resilience - from cascading failures in technological systems to mass extinctions in ecological networks - are rarely predictable and are often irreversible. This lacuna is rooted in a deep theoretical gap: the current analytical framework of resilience is designed to treat low-dimensional models with a few interacting components, overlooking the complex multi-dimensional nature of most real social, biological and technological systems. How then do we predict and influence the resilience of a complex networked system? To achieve this we will expose the natural control parameters of network resilience, providing us with a universal framework to understand, predict and ultimately influence the resilience of complex networks. Along the way, we will also learn why your friends have more friends than you do... For more details see ''Universal resilience patterns in complex networks'', Nature 530, 307–312 (2016). About speaker: Baruch Barzel is an Israeli physicist and applied mathematician at Bar-Ilan University. His main research areas are statistical physics, complex systems, nonlinear dynamics and network science. Barzel completed his Ph.D. in physics at the Hebrew University of Jerusalem, Israel as a Hoffman Fellow. He then pursued his postdoctoral training at the Center for Complex Network Research at Northeastern University and at the Channing Division of Network Medicine, Harvard Medical School. Dr. Barzel's research focuses on the dynamic behavior of complex networks, uncovering universal principles that govern the dynamics of diverse systems, such as disease spreading, gene regulatory networks, protein interactions or population dynamics(Ref. https://en.wikipedia.org/wiki/Baruch_Barzel). You can find more information at http://u.cs.biu.ac.il/~barzelb/index.html. |
| 03.11.2017 | Lin Xie Aibo Zhang | Title: New Ph.D. candidate self-introduction |
| 19.10.2017 | ROSS Gemini Seminar | ROSS Gemini Seminar(SHE) This first seminar is held by Safety, Health and Environment (SHE) section, at meeting room F5(("Gamlefysikk, 2.etasje"), kl14.00-16.00. The seminar will include short presentations on topics from ongoing activities in the group, and may this time include arctic safety, safety in fish farm industry, maritime management and accident in building and construction sector. |
06.10.2017 | Renny Arismendi Himanshu Srivastav | Title: New Ph.D. candidate self-introduction |
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