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PhD Defense by Prerna Singh

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Ph.D. Thesis Defense Announcement

Development of Methodologies to Assess Adaptive Resilience in Infrastructure Systems

 

by

Prerna Singh

 

Advisor(s):

Dr. Adjo Amekudzi-Kennedy (CEE)

 

Committee Members:

Dr. Baabak Ashuri (CEE/BC), Dr. Brian Woodall (INTA), Dr. Samuel Labi (CEE, Purdue University), Dr. Thomas A. Wall (Argonne National Laboratory), Dr. Mikhail Chester (SEBE, ASU)

 

Date & Time: July 15, 2021, 2:00 PM EST

Location: In-Person: Room 4222, Price Gilbert Library | Virtual: https://bluejeans.com/987787436/1879

 

With the growing frequency, intensity and consequences of disasters, developing resilience in infrastructure systems is increasingly recognized as critical to maintaining and enhancing system performance. Evolving trends in climate change, population growth, and urbanization make it essential to build adaptive capacity as a critical element of resilience, to enable systems to re-organize, or adapt to changing future conditions. This research focuses on answering two questions: (1) What capabilities of transportation systems foster adaptive resilience, how are they connected to system goals, and how can they be incorporated in planning for more resilient systems? (2) How can we evaluate the benefits of applying adaptive resilience approaches in planning for transportation systems? 
The overall research methodology follows a mixed-methods sequential approach, where qualitative methods are applied to identify, define, and categorize the adaptive resilience capabilities of transportation systems, followed by a quantitative methodology developed to assess the benefits of adaptive resilience initiatives over the life cycle of infrastructure systems. An Adaptive Resilience Capability Maturity Model (AR-CMM) is developed using a quasi-grounded theory approach, involving iterative literature reviews and expert interviews to identify the adaptive resilience capabilities of transportation systems and their connections with system goals. The AR-CMM assesses the maturity level of any transportation agency on 16 identified adaptive resilience (AR) capabilities of transportation systems. The capabilities are categorized into three themes and assessed over a five-level maturity scale. To enable benefits quantification of initiatives that can enhance the maturity levels of the identified AR capabilities, a Modified Resilience Triangles (MRTs) approach is developed, which can be used to evaluate the long-term benefits of adaptive resilience investments in infrastructure systems under future uncertainty. The application of the MRTs approach is demonstrated using three case studies, where investments have focused on different aspects of adaptive resilience enhancement in various infrastructure systems. The results from all three case studies demonstrate the increasing benefits of adaptive resilience strategies over a long time frame due to deep uncertainty, ongoing learning and the evolving nature of resilience strategies. 
This research expands existing infrastructure resilience theory by developing a portfolio of capabilities of transportation systems that enable adaptive resilience in the systems; and by developing the Modified Resilience Triangles approach, thereby extending the theory on resilience assessment to include impacts of adaptive resilience on the long-term resilience of infrastructure systems. The AR-CMM provides a framework for transportation agencies to evaluate and enhance their adaptive resilience maturity levels. Application of the MRTs approach provides practitioners in any infrastructure field with an enhanced approach for assessing the value of resilience investments, thereby offering a tool that can be used to demonstrate the business case for adaptive resilience to uncertain future conditions. The AR-CMM along with the MRTs approach can be used to incorporate adaptive resilience formally in transportation system planning frameworks, enabling more reliable and cost-effective performance. 

Status

  • Workflow Status:Published
  • Created By:Tatianna Richardson
  • Created:06/30/2021
  • Modified By:Tatianna Richardson
  • Modified:06/30/2021

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