Professor Ying Zhou, Tongji University, Shanghai, China

December 2024 Webinar: Intelligent earthquake response prediction and resilience assessment for building clusters

Building clusters are the major carriers of populations, resources, and wealth. Compared to those of infrastructure systems, research of seismic resilience assessment of building clusters is limited. This may be attributed to several factors: 1) seismic response prediction of building clusters is time-consuming and computationally expensive; 2) the diversity of building types and their interactions with infrastructure systems make it challenging to define unified functionality measures for building clusters, which are essential for resilience assessment. To address these challenges, this webinar will introduce a physics-informed deep learning-based real-time structural response prediction algorithm, denoted as Phy-SeisFormer, to achieve high-precision and efficient building response prediction. Based on the algorithm, a foundation model, denoted as SeisGPT, for building cluster earthquake response prediction is developed. The key advancement of SeisGPT compared to Phy-SeisFormer is its use of large model and transfer learning to predict the response of buildings that may not necessarily be within the trained database. Additionally, the webinar will present a novel resilience assessment framework of building clusters. The new framework considers the role of infrastructure systems as supports for building functionality, thereby capturing the complex interplay between building clusters and infrastructure. Two key functionality measure, Economic Productivity and Service Capacity, are proposed to unify the functionalities of various building types. A semi-flexible, dynamic optimization method is employed to simulate post-disaster recovery, allowing for the plotting of recovery curves and calculation of building cluster resilience indexes such as Total Economic Loss and Cumulative Service Capacity Loss. Finally, an application example using the building cluster on Tongji University campus will be presented. The proposed intelligent earthquake response prediction and resilience assessment method serves as a powerful tool for evaluating the seismic resilience of building clusters and providing policymakers with actionable insights for informed mitigation strategies.

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Professor Anastasios Sextos, University of Bristol, Bristol, United Kingdom

October 2024 Webinar: Cost- And Resilience-Based Prioritization of Bridges for Pre-Earthquake Strengthening

Pre-quake retrofit is key to enhance the seismic resilience of road network bridge portfolios and the community as a whole. Given that the resources that are made available for this purpose are typically limited, it is important to develop a rational, efficient, yet rigorous procedure for prioritizing the bridge(s) that should be strengthened first. Current stakeholder practice tends to be mainly focusing on simply identifying the most vulnerable structures within a network, based on the data that are gathered by means of regular maintenance schemes, sometimes further convoluting the regional or site-specific hazard and the associated bridge-dependent seismic risk. In this paper, a resilience-based decision-making framework is presented, for further considering the direct and indirect losses in prioritizing those bridges for which a potential failure may have a disproportional impact at a road network level. A large-scale computational framework is introduced and employed in three consecutive steps. First, seismic hazard, vulnerability, exposure and consequence of failure in the form of diverted traffic flow are duly quantified and accounted for probabilistically, in order to estimate the direct and indirect cost of earthquake scenarios for the network “as-built” (i.e., without any pre-earthquake retrofit). Next, alternative scenarios of bridge strengthening are explored, and the above loss quantities are updated. Finally, a set of resilience-based indicators are introduced to calculate the cost-benefit of each individual strengthening scheme, thus identifying the bridges whose structural upgrade has the highest relative (cost-benefit) impact on the resilience on the network. The applicability of the framework is presented for the case of a realistic road network in a highly seismic region. The results highlight that conventional risk-based bridge retrofit prioritization may well disregard, highly efficient, low-cost retrofit options that can significantly enhance the resilience of the entire network.

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Prof. Michael Beer, Institute for Risk and Reliability, Leibniz Universität Hannover, Germany

June 2024 Webinar - Towards Resilience of Complex Infrastructure Systems

Infrastructure systems are critical for the functionality of our economic and societal life, they are the technical backbone of our society. A key requirement is, thus, to ensure their reliable performance. Reliability and performance analysis, however, become increasingly complicated due to uncertainties and complexity. In our developed societies, infrastructure systems are characterized by a rapid growth in scale and complexity. The amount of information needed to model these systems with their complexity is, thus, growing as well. In contrast to this increasing need for information the available information remains almost at the same level. Hence, with increasing scale and complexity the gap between required and available information is growing quickly, so that uncertainties and risks are involved in our models and analyses to a greater extent than ever before. This lecture will highlight a numerically efficient access to address this challenge. Concepts for dealing with epistemic and hybrid uncertainties are discussed in association with the survival signature as a powerful systems model and a decision-making technology for most effective and economic implementation of resilience in infrastructure systems. Engineering examples are presented to demonstrate the capabilities of the approaches and concepts.

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Professor Bilal M. Ayyub, Director of the University of Maryland Center for Technology and Systems Management, a Co-Director, International Joint Research Center for Resilient Infrastructure, Tongji University, China, and senior economist at the National Institute of Standards and Technology of the Department of Commerce

May 2024 Webinar - Network Analytics for Sustainable Resilient Cities

Natural and human-caused hazardous events may cause damage, functionality loss and failure of components, systems and networks representing city infrastructure including buildings and other structures with potential environmental, economic and social impacts. Such a complexity can be modeled and analyzed as a network of networks or hypernetworks in order to identify any hidden structures and gain insights for informing policies and decisions for developing and maintaining a state of a resilient sustainability of a city. Analytics for quantitatively measuring network performance, and the associated likelihood, in addition to consequences, are necessary for quantifying risks, requiring appropriate measures of several attributes of interest including reliability, risk, resilience and sustainability. This presentation offers quantitative performance-based time-dependent attributes by taking into account the effects of performance deterioration and nonstationary external loads as needed. For example, the resilience measure for a planning horizon, which is a function of the duration of considered service period, is developed and used for illustration purposes. Additional examples are provided covering metro transit systems, railroad networks, and nature-based solutions using networks analytics and associated economics and socioeconomics. The concepts introduced are illustrated with examples and offer a foundation for managing different hazard types at the system and network levels for cities.

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Professor Dan M. Frangopol, The Fazlur Rahman Khan Endowed Chair of Structural Engineering and Architecture, Department of Civil and Environmental Engineering,ATLSS Center, Lehigh University, Bethlehem, USA

April 2024 Webinar - Moving Toward Risk, Resilience, and Sustainability of Civil Infrastructure in a Life-Cycle Optimization Context

Decisions regarding design, assessment and maintenance of civil infrastructure systems should be supported by an integrated risk-, resilience- and sustainability-based life-cycle optimization framework by considering, among other factors, the likelihood of successful performance and the total expected cost accrued over their entire life. The primary objective of this webinar is to present a life-cycle multi-objective optimization framework for risk-, resilience- and sustainability-informed decision making for structures and infrastructure systems under lifetime hazards. Several important performance indicators such as risk, resilience and sustainability necessary to be implemented in the design, assessment and maintenance of civil infrastructure systems under single and multiple hazards are introduced. Bridges and bridge transportation networks are used to illustrate the application of the proposed approach.

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Professor Božidar Stojadinović, Chair of Structural Dynamics and Earthquake Engineering Department of Civil, Environmental and Geomatic Engineering ETH Zürich

March 2024 Webinar - From performance-based design of buildings to resilience-based design of cities

Performance-based design (PBD) in general, and specifically that concerning the earthquake hazard, has advanced significantly in the past four decades. This design approach is intended to facilitate a risk-informed tradeoff between the engineering characteristics of the structure, the damage states it may undergo during an earthquake, and its life-cycle costs from construction to repairs after earthquakes. PBD saves lives in catastrophes: however, events in the past decade showed the increasing relative importance of the functional recovery of structures after earthquakes. Functional recovery of a building in a city after a disaster does not happen in a vacuum. First, there are many simultaneously recovering buildings in the affected region sharing the recovery resources. Second, the infrastructure systems that support the functions of a structure need to recover their own functions after a disaster, too. These interdependencies make the transition from designing single structures to be safe and functional to designing communities and cities to be more resilient to earthquakes difficult, but offer an opportunity to extend the notion of performance-based seismic design to the level of cities. Modeling, analyzing and quantifying the disaster resilience of cities is the basis for resilience-based design (RBD). It builds on PBD of city elements, buildings and infrastructure systems components, but looks at a city as a system-of-interdependent-systems. These systems are the infrastructures systems, the portfolios of buildings that provide housing for the population as well as spaces for learning, working and societal interaction, and the recovery resources fielded in the recovery effort. In this seminar, I will present my view of the transition from seismic PBD of buildings to seismic RBD of cities, and address aspects of this transition pertaining to quantifying resilience, analyzing the recovery of buildings and modeling system-to-system interdependencies.

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Professor John W. van de Lindt, Harold H. Short Endowed Chair Professor, Colorado State University, USA. Co-Director, Center for Risk-Based Community Resilience Planning

December 2023 Webinar - Measuring the Resilience of a Community Based on Four Areas of Community Stability: An Interdisciplinary Approach to Measurement Science

Resilience is the ability to prepare for, adapt to, and recover rapidly from hazards such as earthquakes, hurricanes, tornadoes, or floods. The ability to model a community necessitates combining models from different disciplines including the interfaces, propagation of uncertainty, and ultimately the measurement of resilience metrics across physical systems, households, social institutions, and the economy. This presentation will begin with a brief overview of a recent Resilient Cities and Structures Special Issue entitled “Integrated Modeling of Cities to Improve Natural Hazards Resilience” guest co-edited by John W. van de Lindt, Andre R. Barbosa, and You Dong. This will be followed by a brief summary of the state of the research in interdisciplinary resilience modeling of communities and cities developed by the U.S. National Institute of Standards and Technology-funded Center for Risk-Based Community Resilience Planning. The computational environment IN-CORE enables researchers to set up complex interdependent models of an entire city consisting of buildings, transportation networks, water and electric power networks, and to include social science data-driven household and business models as well as a computable general equilibrium (CGE) models to predict the level and distributional economic effects of a natural hazard on the economy. The focus of this presentation will be on explaining the use of four community stability areas which each contain multiple community resilience metrics. These areas are physical services stability, social services stability, economic stability, and population stability. An illustrative example for an entire community will be provided to demonstrate how to measure the resilience of an entire city.

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