Role and Importance of Resilience and Engineering Asset Management at Times of Major, Large-Scale Instabilities and Disruptions

• Speaker: Dr. Dragan Komljenovic, Senior Research Scientist, Institut de recherche d’Hydro-Québec (IREQ)
• Time & Date: 14:10-15:30 EST, Friday, February 24, 2023,
• Location: Online
• Zoom Link: Please registration for the Zoom link. If you want to be included in the subscription list, please write to Dr. Arnold Yuan.

Abstract

Contemporary organizations function in a complex business and operational environment composed of closely interdependent systems. They are also complex by their internal structure, management and deployed modern technologies. This complexity is not always well understood and cannot be efficiently controlled. As the complexity and interdependencies increase, man-made systems become more unstable creating conditions for cascading, system-level failures causing serious threats to both themselves and society in general.

Such breakdowns may consist of a) serious physical damages and destruction of their physical assets (caused by natural disasters, extreme weather phenomena and climate change, malicious human actions, etc.), b) large functional disruptions with no physical damages of assets (caused by major organization’s internal disturbances, market crashes, pandemics, wars, disruptions of supply chains, etc.) or c) both. Those sources of risks are basically external to organizations. They are unable to control them but are deeply affected by those risks.
Recent examples of such functional disruptions include Covid-19 epidemic and the Russia-Ukraine war. It is affecting both all sectors of life and businesses worldwide. It convincingly shows that we need to think, plan and act globally in order to deal with such situations that will also take place in the future. Thus, organizations must find ways of coping with this reality to remain economically viable. We are of opinion that the concepts of structured Asset Management (AM) and resilience put together may provide an efficient framework in this regard.

Two case studies in a major North American electrical utility (Hydro-Quebec) demonstrate the applicability of this approach: i) during an exceptional ice storm with significant damages of its physical assets, and ii) coping with challenges of COVID-19 with no destruction of its physical assets.

About the Speaker

Dragan Komljenovic received his BSc at the University of Tuzla, his MSc at the University of Belgrade, his 1^st Ph.D. at Laval University (Quebec-City, Canada) in 2002 and 2^nd Ph.D. at the University of Quebec in Trois-Rivieres (UQTR), Canada in Industrial Engineering in the field of Engineering Asset Management in 2018. He works as a Senior Research Scientist at the Hydro- Quebec’s Research Institute (IREQ) in the field of reliability, asset management, risk analysis and maintenance optimization. Dragan worked almost 12 years as a Reliability and Nuclear Safety Engineer at the Gentilly- 2 Nuclear Power Plant, Hydro-Quebec. He collaborates with several universities in Canada and abroad. Dragan has published more than 90 refereed journal and conference papers. He is a Fellow of the International Society of Engineering Asset Management (ISEAM), and Vice- President of the Montreal Chapter of Society of Reliability Engineers (SRE). Dragan has the status of professional engineer in the province of Quebec, Canada.

Scopus Author Identifier:6505846970

ORICID ID:https://orcid.org/0000-0002-1542-4426

Sustainable infrastructure is a two-way street: balancing environmental and condition performance goals

• Speaker: Dr. Omar Swei, Assistant Professor, Department of Civil Engineering, University of British Columbia
• Time & Date: 14:10-15:30 EST, Friday, January 27, 2023,
• Location: Online
• Zoom Link: Please register here for the zoom link.

Abstract

Governmental agencies are under increasing pressure to mitigate the global warming impact of our infrastructure systems. This objective, however, must be carefully balanced with other performance metrics of interest (e.g., pavement condition) for agencies. This presentation will highlight recent work aimed at understanding these tradeoffs for managing infrastructure systems at both the facility- and network-level. Through a series of case studies, this presentation will highlight key takeaways and opportunities for future research.

About the Speaker

Omar Swei joined the Department of Civil Engineering at The University of British Columbia (UBC) as an Assistant Professor in 2018. He presently oversees the department’s graduate program in project and construction management. His research emphasizes the use of operations research methods to improve the design, delivery, and maintenance of infrastructure systems.

Efficient Scenario Analysis for Optimal Adaptation of Bridge Networks under Deep Uncertainties through Knowledge Transfer

• Speaker: Dr. Minghui Cheng, Postdoctoral Associate, Systems Engineering, Cornell University
• Time & Date: 14:10-15:30, Friday, October 28, 2022
• Location: Online
• Zoom Link: https://ryerson.zoom.us/j/4612874120

Abstract

Due to deep uncertainties associated with climate change and socioeconomic growth, managing bridge networks faces the challenge to perform optimization for different scenarios. There exist a large number of scenarios when various sources of uncertainties, such as population growth and the increasing magnitude and frequency of natural hazards due to climate change, are compounded. Traditionally, scenarios are analyzed sequentially. However, when optimization for one single scenario is time-consuming, only a limited number of scenarios can be considered. To accelerate scenario analysis, this presentation introduces a novel scheme through knowledge transfer between scenarios. Specifically, after finishing the optimization of a certain number of scenarios, the analyses of any new scenarios are accelerated by utilizing the knowledge obtained from optimization of previous scenarios. The scheme builds on meta-learning-based surrogate modelling (MLSM), previously developed by Dr. Cheng and his colleagues, to realize the concept of knowledge transfer. The presentation first introduces MLSM and shows several applications. A proper definition of similar scenarios for adaptation of bridge networks under deep uncertainties is then given to stipulate the situation when knowledge transfer can occur. A bridge network in Camden County, New Jersey, is used as an illustrative example to demonstrate the computational efficiency of the proposed novel scheme. The full paper covered by the presentation can be found here.

About the Speaker

Dr. Minghui Cheng  (Google Scholar Profile) is currently a postdoctoral associate at Systems Engineering, Cornell University. He obtained his Ph.D. in Structural Engineering at Lehigh University, USA, in 2021 under the supervision of Prof. Dan Frangopol. Prior to that, he earned his B.E. in Civil Engineering at Hunan University, China, in 2016. His research is primarily focused on (1) establishing digital twins for bridge networks, (2) optimal life-cycle management of structures and infrastructure systems, (3) realizing knowledge transfer in engineering analysis, and (4) calibrating decision-making models for civil engineering stakeholders. He is the recipient of multiple awards including University Fellowship and P.C. Rossin Doctoral Fellowship at Lehigh Univerisy and National Scholarship (twice) and Chinese Government Scholarship during his time at Hunan University. He has multiple publications in prestigious journals, such as Structural Safety, Reliability Engineering & System Safety, Computers & Structures, Journal of Bridge Engineering, among others. Two of them are selected into the ASCE Bridge Asset Management Collection.

Probability, risk, uncertainty and decisions all are abstract concepts. In CV8311 (Risk and Reliability for Engineers), our study will have to emphasize on engineering applications. However, if you are interested in risk and decision in general, I give below a list of books that you may find useful and helpful to maintain social distancing during this difficult year. The list are given in my order of likeness.

1. Bernstein P L (1996). Against the gods: the remarkable story of risk. Wiley.  Ah, how mighty and inspiring is the book title, and yet we human sapiens still have to collaborate with the Gods. I read this book from beginning to end each time I taught CV8311 or equivalent.
2. Khaneman D (2011). Thinking, fast and slow. Doubleday Canada. Written by a Nobel prize winner, this book tells a lot about the other side of probability, uncertainty, risk and decisions.
3. Savage S L (2009). The flaw of averages. Wiley. As I mentioned in Lecture 1 of CV8311, the whole course can be summarized by the Jessen’s inequality, a mathematical way of explaining the flaw of averages.
4. Taleb N N (2018). Skin in the game. Random House. Taleb is a well-known writer in risk and uncertainty. His incerto (greek for ‘uncertainty’) collection deserves serious reading (and ‘slow thinking’!). This book is one of the collection. Another famous one in the collection is of course Black Swan. Taleb recently published a new book titled Statistical consequences of fat tail, which I just ordered from Amazon.

Enjoy reading!

The RILCIE group keep recruiting self-motivated post-doctoral researchers and PhD students from time to time. The recruitment focus for year 2020 is on infrastructure asset management, progressive collapse, and probabilistic structural integrity. If you have a strong background in one of the following combined expertise AND a solid command on MATLAB, Python or R, please feel free to contact me:

• Engineering risk and reliability, and optimization
• Structural reliability, and nonlinear structural analysis (concrete structures only)
• Probability and statistics, and infrastructure asset management (if you have good knowledge of materials, design and lifecycle activities of any ONE of the following asset types it would suffice: pavement, bridges, municipal pipes, oil and gas pipelines)

When you send your first inquiry email, please (1) indicate which research area you would like to work on, (2) identify at least three major active researchers (not your references) in the world, and (3) explain why you choose Ryerson and me for further study. General inquiries that do not include those elements will NOT be responded to. I give my apology in advance as too many such emails flood in every week.

This book was published in 2011, and I purchased in 2013 for the preparation of CVL609, Civil Engineering Systems. I just read it second time, and I believe it deserves more reading.

https://www.amazon.ca/Engineering-Systems-Meeting-Complex-Technological/dp/0262529947

This books is revolutionary. Most of our teaching is still focusing on, at most, the epoch of complex systems. However, the authors warned us: The epoch of great inventions and artifacts has gone, and even the epoch of complex systems is phasing out. To equip our students with 21-century skills and techniques, we need to embrace the epoch of Engineering Systems, which I believe the words should be converted to a proper noun to highlight its major difference from traditional systems engineering.

In Chapter 2, the authors highlight five major characteristic of Engineering Systems:

• Existence in the real world (i.e., physical systems)
• Artificial (man-made vs. natural environment)
• Dynamic properties (i.e., partially evolved and partially designed)
• Hybrid state (mix of continuous and discrete states)
• Some human control

The partially evolved and partially designed feature of Engineering Systems is a sharp observation that we rarely learn from other texts. A difficulty in dealing with urban infrastructure issues may be attributed to this dynamic property of urban infrastructure systems.

What really separates Engineering Systems from conventional large complex system is the interaction of the existing system and human activities. Highway transportation system is a typical example. Because of this, the subject of Engineering Systems calls for the study and application of not only mathematics and natural sciences, but also social sciences, economics, and management. With the advancement of Big Data, deep learning, and artificial intelligence, civil infrastructure systems are evolving to a complex artifact that is deeply interwoven with cyber, social, and technology complexities. Very soon, our civil engineering students will be asked to learn, beyond optimization and decision theory that we are currently learning at CVL609, more general systems methodologies such as graph and network theory, system dynamics, general economic equilibrium, among others that are currently mainly in researchers’ minds.