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Model Inventory
- 2. © Copyright 2015 Dr. Jeffrey Strickland
Discrete Event Simulation
National Aeronautics and Space Administration (NASA)
- 3. NASA Ares I
Ares I was the crew launch vehicle that was being
developed by NASA as part of the Constellation
Program.
Ares I was originally known as the "Crew Launch
Vehicle" (CLV).
NASA planned to use Ares I to launch Orion, the
spacecraft intended for NASA human spaceflight
missions after the Space Shuttle was retired in 2011.
Ares I was to complement the larger, unmanned Ares V,
which was the cargo launch vehicle for Constellation.
NASA selected the Ares designs for their anticipated
overall safety, reliability and cost-effectiveness.
However, the Constellation program, including Ares I
was canceled in October 2010 by the passage of the
2010 NASA authorization bill.
Dr. Strickland and a team of engineers designed the
Reliability and Launch Availability of the Ares I using
ExtendSim.
© Copyright 2015 Dr. Jeffrey Strickland
- 4. © Copyright 2015 Dr. Jeffrey Strickland
Discrete Event Simulation
Ballistic Missile Defense System (BMDS)
- 5. The Ballistic Missile Defense System
Missile defense technology being developed, tested and
deployed by the United States is designed to counter
ballistic missiles of all ranges—short, medium,
intermediate and long.
Since ballistic missiles have different ranges, speeds,
size and performance characteristics, the Ballistic Missile
Defense System is an integrated, "layered" architecture
that provides multiple opportunities to destroy missiles
and their warheads before they can reach their targets.
© Copyright 2015 Dr. Jeffrey Strickland
The system's architecture includes:
networked sensors (including space-based) and ground- and sea-based radars for target detection and tracking;
ground- and sea-based interceptor missiles for destroying a ballistic missile using either the force of a direct collision,
called "hit-to-kill" technology, or an explosive blast fragmentation warhead;
and a command, control, battle management, and communications network providing the operational commanders
with the needed links between the sensors and interceptor missiles.
Dr. Strickland modeled the end-to-end system using ExtendSim and performed threat modeling with MATLAB
- 6. © Copyright 2015 Dr. Jeffrey Strickland
Discrete Event Simulation
Warrior Extended Range Multi-Purpose
(ERMP) Unmanned Aerial Vehicle (UAV)
- 7. Extended Range Multi-Purpose (ERMP)
Unmanned Aerial Vehicle (UAV)
The General Atomics MQ-1C Gray Eagle (previously the Warrior; also called Sky
Warrior and ERMP or Extended-Range Multi-Purpose) is a medium-altitude, long-
endurance (MALE) unmanned aircraft system (UAS).
It was developed by General Atomics Aeronautical Systems for the United States
Army as an upgrade of the General Atomics MQ-1 Predator.
The Army's 1st Infantry Division's combat aviation brigade deployed to Iraq with
developmental Gray Eagles in June 2010.
On 2 June 2012, the Gray Eagle reached a record 10,000 successful automatic
launch and recoveries with the Automatic Takeoff and Landing System.
By 25 July 2012, the Army’s Gray Eagle aircraft has accumulated more than 35,000
flight hours since it was first deployed in 2008.
On 25 June 2012, General Atomics announced that the Gray Eagle had been
deployed in its first full company of 12 aircraft.
Initial Operational Test and Evaluation was completed in August 2012.
There were 50 aircraft in service with a greater than 80 percent system operational
availability rate.
The Reliability, Availability and Maintainability (RAM) of the Sky Warrior ERMP UAV
was engineered by Dr. Strickland using ExtendSim.
© Copyright 2015 Dr. Jeffrey Strickland
- 8. © Copyright 2015 Dr. Jeffrey Strickland
Discrete Event Simulation
Hunter Unmanned Aerial Vehicle (UAV)
- 9. RQ-5 Hunter Unmanned Aerial Vehicle (UAV)
The IAI RQ-5 Hunter unmanned aerial vehicle (UAV) was
originally intended to serve as the United States Army's Short
Range UAV system for division and corps commanders.
It took off and landed (using arresting gear) on runways. It used
a gimbaled EO/IR sensor to relay its video in real time via a
second airborne Hunter over a C-band line-of-sight data link.
The RQ-5 is based on the Hunter UAV that was developed by
Israel Aircraft Industries.
The Reliability, Availability and Maintainability (RAM) of the RQ-
5 Hunter UAV was engineered by Dr. Strickland using
ExtendSim.
In 2004, the United States Department of Homeland Security,
Bureau of Customs and Border Protection, Office of Air and
Marine utilized the Hunter under a trial program for border patrol
duties.
During this program, the Hunter flew 329 flight hours, resulting in
556 detections.
© Copyright 2015 Dr. Jeffrey Strickland
- 10. © Copyright 2015 Dr. Jeffrey Strickland
Discrete Event Simulation
Transportation and Transshipment
- 11. © Copyright 2015 Dr. Jeffrey Strickland
Transportation Systems
Transportation systems involve the movement of people or items from one location to another.
Most manufacturing models involve transportation of parts and finished good into, within, and from a
manufacturing facility.
This transportation can be performed by forklifts, cranes, conveyors, trucks, and other means.
There are many transportation systems that we deal with:
Airport systems from a passenger’s perspective, the airline’s perspective, or the plane’s
perspective.
Mass transit systems, including rails and buses.
Highways, bridges, and toll roads
Trucking networks, including terminals
Rail and maritime freight-shipping systems
Maritime and rail terminals.
School bussing systems (Lakewood, CO)
• modeled by Dr. Strickland
Package delivery systems
- 13. Genetic Algorithms
Groundwater depletion is one of the most important problems threaten oil exploration.
The optimal distribution of well locations and pumping rates mitigate this problem.
Exploration carried out via delineating the optimal well locations and optimal pumping rates.
The methodology of combination between simulation and optimization techniques was applied.
A linked simulation-optimization model for obtaining the optimum management of groundwater flow is
used in this research.
This model uses an integrated Discrete Event Simulation with a Genetic Algorithm (GA) technique (a
heuristic optimization model .
Cases Studies
Fixed well location with maximum pumping rate
Flexible well location with the moving well option
Prediction of the future changes in both head and flow
• were made in steady and transient states, modeled by Dr. Strickland
© Copyright 2015 Dr. Jeffrey Strickland