Monthly Archives: September 2017

Probabilistic Prediction of Post-disaster Functionality

Probabilistic Prediction of Post-disaster Functionality Loss of Community Building Portfolios Considering Utility Disruptions

Journal of Structural Engineering

I am proud to announce that the latest collaborative work from the CORE lab has been accepted for publication in the ASCE’s Journal of Structural Engineering.  The new paper title is a mouthful, “Probabilistic Prediction of Post-disaster Functionality Loss of Community Building Portfolios Considering Utility Disruptions”, but the researchers (Weili Zhang, Peihui Lin, Naiyu Wang, Charles Nicholson, and Xianwu Xue) have been just calling the effort the “PPPD” project.

The study proposes a framework for the probabilistic prediction of building portfolio functionality loss in a community following an earthquake hazard. Building functionality is jointly affected by both the structural integrity of the building itself and the availability of critical utilities.

Post-disaster functionality loss relates to direct damage and critical utilities

To this end, the framework incorporates three analyses for a given earthquake scenario:

  1. evaluation of the spatial distribution of physical damages to both buildings and utility infrastructure
  2. computation of utility disruptions deriving from the cascading failures occurring in the interdependent utility networks; the cascading failures are simulated by use of new mixed-integer, multicommodity network flow optimization model
  3. by integrating (1) and (2), a probabilistic prediction of the post-event functionality loss of building portfolios at the community scale.
Framework for Post-disaster Functionality Loss Prediction

Overview of the PPPD Framework

The framework couples functionality analyses of physical systems of distinct topologies and hazard response characteristics in a consistent spatial scale, providing a rich array of information for community hazard mitigation and resilience planning.

Case Study

An implementation of the framework is illustrated using the residential building portfolio in Shelby County, TN, subjected to an earthquake hazard.  A single realization of an earthquake scenario in Shelby Country, TN is depicted below.

Single realization of post-disaster functionality

Single disruptive event simulation realization

Since the building damage, the flow model, the data collection/aggregation can all be complted efficiently, it is easy to extend the single simulation realization to many realizations.  This allows for a spatial probabilistic analysis of the vulnerabilities in the affected area. The figure below depicts the expected impact to the region based on 1,000 simulations of the scenario earthquake.

Multiple realizations of post-disaster functionality

Expected impact based on multiple earthquake simulation realizations

The intricacies that relate how the electric power network (EPN) support the potable water network (PWN), along with the particular individual component vulnerabilities of the EPN and PWN, produce probabilistic failure patterns in building functionality (see sub-figure d. above), that are not obvious!


Additionally, the framework allows us to compare a more traditional building portfolio analysis to with that of the practical implications of disruptive events.  That is, even if your place of employment is not damaged, if the building does not have power or water, then it will be closed for business anyway!

The green line in the figure to the right denotes the probability of exceedance for the ratio of buildings which cannot be occupied (RUO) due to physical damage.  The dotted line relates to the ratio of functional loss of buildings (RFL) which is due to any combination of direct damage and utility loss.   Clearly, the RUO is a conservative estimate compared to RFL.  For example, there is only a 40% chance that 40+% of the buildings will be directly damaged to the extent of restricted occupancy. However, that number jumps to 80% when the utilities are considered!


This work represents a wonderful collaborative effort within the CORE lab.  Weili Zhang developed the interdependency model and worked closely with Peihui Lin, who provided the building analyses.  And both worked closely with Xianwu Xue, the GIS expert.  And of course, I am always pleased to work with my colleague Naiyu Wang in Civil Engineering.   We have much, much collaborative work already in-progress and planned for the future!

Southwest Airlines Operations Tour

NOC at Southwest Airlines

Southwest Airlines Network Operations Control


Southwest Airlines Visit

(back row, left-to-right) Kyle Beatty, Warren Qualley, Kelvin Droegemeier, Hank Jenkins-Smith, Ed Cokely (front row, left-to-right) Carol Silva, Amy McGovern, Radhika Santhanam, Le Gruenwald, Sridhar Radhakrishnan, Charles Nicholson

I was happy to represent the Analytics Lab recently as a part of a larger team from OU who were invited down to Dallas, TX near Love Field to meet with Southwest Airlines (SWA) to learn more about the airline business and operations.   The attendees from OU included the Vice President of Research; directors from the School of Computer Science in the Gallogly College of Engineering and Management Information Systems in the Price College of Business; senior researchers and specialists from political science, psychology, computer science, and of course, data science.

We were privileged to take a tour of the famous Southwest Airlines Network Operations Control, a.k.a., the NOC.  This facility and the employees who work here are at the very core of the SWA network operations.   From dispatchers to air traffic control specialists to flight operations to maintenance to crew schedulers to weather analysts — this is where the major operational decisions are made.  

The unique look of the NOC, bathed in blue as it is, was designed scientifically to help with mood and to reduce eye strain.  And, well, it simply looks cool.

While we were at the NOC, it so happens that Southwest Airlines was actively engaged in planning for the expected impacts from the impending Hurricane Harvey.  Obviously, weather, and especially major weather events like hurricanes, play a huge role in flight delays and cancellations for all airlines. Such disruptive events can have impacts across across an entire transportation network. Analyzing and optimizing under this larger “system-wide” view is what ISE’s are famous for. These are hard problems, but they are worth solving!

Planning for Harvey at Southwest Airlines NOC

Southwest NOC in action planning for Hurricane Harvey