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.
Inheritance and Innovation in Building Structure Design
Tongji Architectural Design (Group) Co., LTD, Shanghai, China
The innovation of building structure design should satisfy the aspects of architectural form, function using and interior space design. The process of structural innovation is the fusion of structure and architecture. Firstly, structural system should relate to the architectural design of the building. Secondly, the structural layout should correspond to the building space using. Finally, digital design is a critical technology during the innovation of structural design. Therefore, this essay is going to express how the structural innovation can be achieved during the design of structure from eight cases in details.
Time-dependent Reliability of Concrete Structures Considering Influences of Environmental Actions
Key Laboratory of Performance Evolution and Control for Engineering Structures of Ministry of Education, Tongji University, Shanghai, China
College of Civil Engineering, Tongji University, Shanghai, China
Under influences of environmental actions, the performance of a RC structure may degrade, which would impair the serviceability and safety of the structure and even bring a severe social impact. With the development of degradation, the failure mode of a reinforced concrete structural member under loads or other external actions may change. For example, the bending failure mode of a corroded reinforced concrete beam may change from ductile to brittle failure; besides, if the corrosion rate of stirrups is faster than that of longitudinal steel bars in a loaded reinforced concrete beam, the failure mode of the beam would change from the bending failure to the shearing failure with the development of the corrosion. So, it is of great importance to develop a comprehensive reliability analysis framework for RC structures considering the influences of environmental actions.
In this study, the degradation processes, e.g., chloride ion transport, concrete carbonation, micro- and macro-corrosion of steel bars, are deeply analyzed and well modeled. Based on the existing results, a novel probability density function (PDF) -informed reliability analysis framework is proposed to evaluate the time-dependent reliability of a reinforced concrete structural member considering the influences of common atmospheric and marine environment actions. Within the proposed framework, the analysis steps, including the transport of environmental media, reinforcement corrosion and reliability analysis, are involved, in which different deterioration scenarios and failure modes can be considered. Moreover, some illustrative cases are made to present the analyzing processes of the developed framework. Also, the accuracy and efficiency of the reliability calculation are testified by the traditional methods, e.g., Monte Carlo simulation (MCS) and Importance Sampling, etc. In the future, a time-dependent reliability based design method for reinforced concrete structures will be developed and modified.
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.
Lifetime Assessment of Structural Concrete: Multi-scale and Multi-Chemo-Mechanistic Approach
Department of Urban Innovation, Yokohama National University, Yokohama, Japan
Proposed is the long-term behavioral simulation with inspection data at site for lifetime assessment of structural concrete in service. The concrete cracking and steel corrosion at site are converted to the part of existing structures, and the future performance is assessed for infrastructure management. Concrete bridge decks are especially focused on and the hazard map of crack patterns is inversely derived for periodical inspection and planning of repair and strengthening.
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.
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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