Fazlur R. Khan Lecture
China's Important Influence on World-Wide Life-Cycle Engineering
Mark P. Sarkisian
Skidmore, Owings & Merrill LLP, San Francisco, USA
By 2030 the World Green Building Council has put forth a challenge that all buildings shall be designed for net zero operational carbon and by 2050 net zero embodied carbon. The construction of the Jin Mao Tower 20 years ago was unique for several reasons and ideas have resulted in progress toward those goals. At the time, it was the tallest building in China, one that resulted in re-writing the Chinese code for wind and seismic engineering but perhaps most importantly inspired the design of other buildings that would incorporate resilient systems. These systems have been designed based on a platform of thinking related to life-cycle engineering and minimal impact on the environment.
Clearly conceived efficient tall building structural systems based on mega-columns interconnected with cores, friction-fused seismic systems, the application of optimization theories, and the considerations of carbon in construction were all influenced by the design of the Jin Mao Tower. The paper and presentation will focus from research to build work that incorporate these ideas with visions of future opportunities. Project examples from around the world will be highlighted including the Jin Mao Tower – Shanghai, the Tianjin World Financial Headquarters, the Huawei Headquarters, the Poly Beijing Headquarters, the 111 South Main Tower in Salt Lake City, and the Los Angeles Federal Courthouse Building among others. Techniques of calculating carbon will be discussed and ideas for the future contemplated.
Data Driven Life Cycle Management
Rijkswaterstaat, Utrecht, the Netherlands
Life Cycle Management deals with the management of performance, risks and cost over the life cycle in a dynamic environment. Life Cycle Management always involves time-related expectations. Future predictions may be based on analytical models, but become much more powerful when supported by data. Sometimes, data even help us to reveal aspects and relations that were not discovered by models. New data-driven approaches quickly gain importance. Along with this new challenges arise.
This keynote deals with the concept of Life Cycle Management, and how data driven approaches are now used in practice. A wide variety of aspects will be discussed, varying from data interoperability, machine learning, pattern recognition, the use of massive point clouds, drones, avatars, digital twins, Linked Data and BIM. Practical experience with predictive maintenance for mechanical and electronic devices will be discussed, and related to the management of risks and performance over the life cycle. Finally a vision will be presented on the way ahead for the effective use of data, raising the question if structures need to be smart, or decisions should be smart.
Understanding and Modeling the Resilience Life Cycle of Communities: a Multi-Disciplinary Endeavour
John W. van de Lindt
Department of Civil and Environmental Engineering, Colorado State University, Fort Collins, USA
Resilience is the ability to prepare for and adapt to changing conditions and withstand and recover rapidly from disruptions. Resilience includes the ability to withstand and recover from deliberate attacks, accidents, or naturally occurring threats or incidents. Thus, comprehensive community resilience assessment and planning includes (1) a planning stage prior to an event to reduce the immediate adverse affects of a hazard strike on a community, (2) the response stage following a hazard event, and (3) the recovery stages. Engineering has long focused on stage 1 by strengthening, stiffening, raising, and coating infrastructure; Planners and managers have focused on stages 1 and 2; and life cycle assessment has included stage 3 often monetizing with tradeoffs in time. In this presentation I will introduce community resilience planning as a stage-wise multi-disciplinary approach to enable analysts the ability to inform communities of near-optimal policies based on an array of community resilience metrics at key points in time during the recovery process. The process of recovery for a community can take years and the objective of understanding and modeling a community through its life before and after an event is to reduce this recovery time while minimizing costs and impacts. These community resilience metrics span engineering, social science/urban planning, and economics. I will also introduce a free open source computational platform available for research and community planning of this type.
The Quest for Multi-Hazard Resilient and Sustainable Infrastructure
Jamie E. Padgett
Rice University, Houston, USA
Our structures and infrastructure systems are exposed to an array of threats throughout their life-time, including both chronic and acute stressors that pose a risk of damage and cascading consequences to social, environmental and economic systems. These stressor include aging and deterioration, increased demand by a growing population, and natural hazards that may become more frequent with climate change. Even a given natural hazard event, such as a hurricane event, brings complex multi-hazard storm conditions that challenge the performance of built infrastructure along with modern risk assessment tools. This lecture will examine two pervasive themes in life-cycle civil engineering, namely resilience and sustainability, and explore their intersection and quantification. The role of life-cycle civil engineering in supporting broader interdisciplinary sustainability and resilience quantification is highlighted, along with recent progress and future opportunities. The talk is organized around select questions that underpin the quest for multi-hazard resilient and sustainable infrastructure. For example: What are the relative risks posed by various threats to infrastructure performance and how do they interact? How have the risks to infrastructure co-evolved with policies and socio-demographic shifts? What technological or computational tools enable the advancement of future resilient and sustainable infrastructure? Case studies using bridge and transportation infrastructure as well as energy and industrial infrastructure illustrate risk-based frameworks for quantifying indicators of infrastructure resilience and sustainability while probing alternative design and management strategies in support of “The Quest”.
The Challenges and Opportunities of Flexible Infrastructure Systems
Universidad de Los Andes, Bogotá, Colombia
Life-Cycle Cost Analysis (LCCA) requires making assumptions about aspects that vary in nature such as the project’s mechanical performance, the financial parameters and market variations, and the contribution to greenhouse emissions. The low dependability of predictions about these aspects, questions the results of many models as actual tools for decision-making. In particular, because traditional approaches to infrastructure operation define, at the outset, management strategies under the assumption that all future scenarios are known – at least in probability. Besides, most traditional models do not capture stakeholder’s decisions that result from non-technical aspects such as exploiting business opportunities. Thus, current infrastructure design and management strategies have little room to accommodate significant deviations from expected design criteria and unplanned events. The success of real projects combines short and long-term predictions of the system’s performance with an understanding of the stakeholder’s interests and decisions, which unravel as the project evolves with time. In practice, successful projects are those that better accommodate change; i.e., those that are flexible enough to adapt to new circumstances as they materialize. For example, variations in demand – associated with uncertainty in the revenue, deterioration and loss of capacity, or currency market oscillations. Within this context, this lecture examines the value of incorporating flexibility in the design and management of large infrastructure. It discusses the nature of flexibility, the complexities of integrating it within a project; and the gains of adopting this approach for both stakeholders and users.
The New Culture of Thunderstorm Outflows for the Safety, Durability, Sustainability and Resilience of Structures in an Evolving Climate
Department of Civil, Chemical and Environmental Engineering, Polytechnic School, University of Genova, Genova, Italy
Various models have been developed over the years, to ensure the safety, durability, sustainability and resilience of the built environment with regard to the wind. These models, born in the 1960s and gradually more and more advanced, assume that the wind is a synoptic cyclone. However, the evolution of knowledge in wind engineering, the development of increasingly efficient monitoring networks and possibly the climate changes underway have shown that the design wind speed and the wind-induced damage at the mid-latitudes usually occur during mesoscale thunderstorms. Considering that cyclones and thunderstorms are fully different events, hence the conviction that current wind models are inconsistent with the physical reality, or at least require a substantial rethinking. THUNDERR is an ERC project, carried out under author’s responsibility, that pursues three objectives: 1) to formulate an interdisciplinary model of the thunderstorm outflows; 2) to assess a novel wind loading format that encapsulates the classic cyclone models and the new thunderstorm ones; 3) to spread this new culture to international community. This paper provides the framework of the THUNDERR project, the results obtained, the perspectives of the studies undertaken, and their potential impact on building safety, durability, sustainability and resilience.
Risk-Informed Decision-Support for Complex Infrastructure Systems Using Matrix-Based Bayesian Network (MBN)
Seoul National University, Seoul, Republic of Korea
Infrastructure systems serve a pivotal role in urban communities, which highlights the importance of making proper decisions on their operation and maintenance. Their life-cycle performance depends on multiple factors with inherent uncertainties, e.g. earthquakes, floods, and deterioration, calling for a probabilistic approach. While it is not straightforward to formulate the high-dimensional probability distribution that covers all these uncertain factors, Bayesian network (BN), by graphically representing their causal relationships, can facilitate a probabilistic modeling and inference. However, the conventional strategy of BN quantification often makes its applications to large-scale systems computationally intractable. This is because the number of the probability values of all basic mutually exclusive and collectively exhaustive (MECE) events, which BN needs to evaluate and store, exponentially increases with the number of components. This talk will show how this issue can be addressed by the Matrix-based BN (MBN; Byun et al. 2019), whose matrix-based quantification eliminates the restrictions of (1) storing instances in the unit of basic MECE events, and (2) incorporating all existing events to the BN model. Once the MBN is quantified, one can analyze various types of complex infrastructure systems, e.g. transportation networks, power systems, and oil distribution networks, and perform probabilistic inference to compute system reliability, component importance measure, etc., and optimization for risk-informed life-cycle decision support, as demonstrated in the talk.
Conference Secretariat IALCCE 2020
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