Modeling Alabama Tornado Emergency Relief (MATER)

transcript

Joe Cordell

Spencer Timmons

Michael Fleischmann

Overview

Background Problem Abstract Network Overview (Nodes, Arcs) Mathematical Model Scenarios Results Conclusions Further Work Video Link

Background

State of Alabama Major Cities: Birmingham, Montgomerey, Huntsville,

Mobile, Tuscaloosa Population: 4.7 million

Average 23 Tornados Per Year $13 million in average annual damages

Background

Tornado Outbreak on April 27th 2011 165 tornados across the

United States 248 fatalities Over $16 billion in

damages over 3 days Listed by NOAA as the

fourth deadliest in United States history

April 27th, 2011 – Tornados

62 Tornados in Alabama alone

2219 injuries 192 fatalities Only the second day in

history that there were three or more F5 or EF5 tornadoes.

Background

Cordova Population: 2260 Two tornados Four fatalities

Problem Abstract

Relief supply flow as a Min-Cost Flow Model Goal: To supply damaged cities in the least

amount of time and determine if prepositioning of supplies will affect total travel time

Key modifications to the basic model Randomized delay Interdiction represented by arc delays

Measures of Effectiveness: Total travel time Access to damaged cities

Huntsville

Birmingham

Tuscaloosa

Huntsville

Birmingham

Tuscaloosa

Abstract Network

April 27th, 2011 – Tornados

We Modeled Jasper, AL Area

Mathematical Model

MIN-COST FLOWObjective: Move humanitarian supplies to damaged towns in shortest time where costs are hours of movement required to deliver supplies.

There is a demand for supplies at each damaged town.

MATER looks at worst case scenario by implementation of a “smart” tornado which seeks to damage roads so as to inflict the greatest cost on the operator.

AirPort

Mathematical Model

MIN-COST FLOWObjective: Move humanitarian supplies to damaged towns in shortest time where costs are hours of movement required to deliver supplies.

There is a demand for supplies at each damaged town.

MATER looks at worst case scenario by implementation of a “smart” tornado which seeks to damage roads so as to inflict the greatest cost on the operator.

AirPort

C=24 tC=50

Damaged City City Node Airport Node

Scenario 1aDestroyed Roads-Jasper Only

Scenario 1bDestroyed Roads-Jasper and Blount Springs

Scenario 1cDestroyed Roads-Jasper, Blount Springs and Oneonta

Scenario 1cDestroyed Roads-Jasper and Blount Springs

Scenario 2cDelays Roads-Jasper, Blount Springs and Oneonta

Scenario 2c Delays Roads-Jasper, Blount Springs and Oneonta

Damaged CityPrepositioned Stocks City Node Airport Node

Scenario 3Prepositioned Aid

Scenario 1: Operator Resilience Curve

Scenario 1 Results

With roads completely destroyed, tornado quickly cuts off access to affected area. 5 Roads knocked out cuts off Jasper from relief supplies Must then use Chinook helicopters to deliver supplies to

the city, and vehicle delivery for surrounding areas affected less

Most damaging path with fewer destroyed roads is south of the city, taking out the roads from 2 of the 3 airports Supplies then flow through Huntsville Airport Main storm actually followed this path

Scenario 2 Results

With delayed roads, ramp-up in time is more gradual Spikes when moving across multiple delayed roads

Most damaging tornado path remains the same No longer possible to cut off supplies to ground

shipment

Scenario 3 Results

With supplies pre-positioned instead of flown-in, travel time is decreased, but not significantly Original flown-in supply model does not include flight

time to airport Change in travel time due to proximity of

prepositioned supplies to area

Prepositioned Supplies Comparison

Model Useability

Model is easily customizable to a given scenario Can be used to show movement of supplies to any

affected city/area Scalable for multiple damaged cities via adding

demands to those nodes Can use flown-in supplies or prepositioned supplies

Useful to quickly formulate delivery plan for FEMA/military responders

Conclusions

Depending on the city, tornado damage can quickly cut off area from relief supplies if roads are rendered unusable Helicopter delivery via US Army National Guard would then be

necessary Best option for high network resiliency is to keep road

network in good repair and clear of neighboring trees Prepositioned stocks of relief supplies would not make a

large difference Must still get vehicles and personnel to distribute Not much closer than airports

Potential Future Work

Model entire state or other areas prone to natural disasters

Adjust model to depict hurricane or earthquake damage instead

Analyze changes in results with a more micro-resolution network (more roads, towns)

References

Map images and road distance maps.google.com

Past tornado path and strength data: www.tornadohistoryproject.com

City statistics/demographic info: www.city-data.com

Consolidated list of information and articles: http://en.wikipedia.org/wiki/

April_25%E2%80%9328,_2011_tornado_outbreak

Questions?

Modeling Alabama Tornado Emergency Relief (MATER)

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