Interdicting Tradeflow on the U.S. Rail Network LTC Brian Axelsen MAJ Steve Jones

U.S. Rail Network Vital to moving large amounts of goods between large population centers. a network of more than 140,000 miles 43 percent of intercity freight volume Shippers would pay $69-95 billion more per year if all freight moved by rail were shifted to truck On average, railroads are four times more fuel efficient than trucks. Source: - Association of American Railroadshttp://

US Rail Network Class 1 Rail Network

Model Scenario Determine the impact of a “dirty bomb” attack on the tradeflow between the two largest U.S. cities and the rest of the country. Multi-commodity (NYC and Los Angeles) – “New York” and “LA” commodities – Two of the most populous cities and busiest ports – Demand from each node is the tradeflow between that node and NYC and LA – Supply is sum of all demand for each commodity

Gravity Model Basic theoretical model for trade Used to evaluate NAFTA and WTO

Model Scenario Nodes: 50 largest Metropolitan Statistical Areas (MSA) and 20 key rail intersections. Edges: Represent multiple rail lines between two nodes. – Cost = $1 per tradeflow unit per mile – Very large capacity

US Rail Network

US Rail and Abstract Networks

Abstract Network

Measure of Effectiveness Total economic cost of the supply and demand model for tradeflow. – Shipping costs along usable edges – Cost of unsatisfied demand – Both NYC and LA commodities

Operator’s/Attacker’s Problem Operator wants to satisfy all demand for each commodity at the minimum cost Attacker uses dirty bombs to maximize the cost of tradeflow between the two largest population centers and the rest of the country. Attacking an edge represents the incapacitation of the rail network between two MSA’s. Additional Constraint to Attacker: Edges originating from a supply node cannot be attacked.

Operator Resilience Curve Detroit Isolated D.C Isolated Pittsburg Shipping Restricted Seattle Isolated Boston Isolated

1 Attack No City Isolated; increased cost to meet demand.

2 Attacks Detroit Isolated

3 Attacks Washington D.C Isolated

4 Attacks Washington D.C and Virginia Beach Isolated; there is now “excess” supply in NY.

5 Attacks No City Isolated; significantly increased cost; ¼ of supply cannot leave NY.

6 Attacks No City Isolated; significantly increased cost; ¼ of supply cannot leave NY.

7 Attacks Seattle Isolated; significantly increased cost; 1/4 of supply cannot leave NY.

8 Attacks Boston Isolated; significantly increased cost; 1/3 of supply cannot leave NY.

Model Extension Removed constraint that arcs coming from supply nodes cannot be attacked. – New York isolated first: consistent with Gravity Model – Solutions are not nested – Costs increase by orders of magnitude upon isolation of a supply node – Consistent with securing supply nodes

Open Ended Analysis Total Economic activity: All nodes have supply to and demand from all other nodes. All Port Economic activity: All nodes with a port have supply to and demand from all other nodes. Split nodes in two to model attacking a city’s population as well as the network (Multi- objective model for the attacker) Adjust capacity based on number of nodes between two cities.

Summary and Conclusions Overall Resiliency of Rail Network – High physical capacity, especially east of Mississippi – No single point of failure – No point of extreme vulnerability: Solutions not nested. Greatest increase in cost incurred by isolating a transportation hub, not a city.