Methodology for Including Base Infrastructure in Conceptual System Analysis

Abstract

The 2018 National Defense Strategy defines a transition to agile basing, where the logistics footprint of new conceptual systems can be distributed across a set of airfields, instead of one main operating base. Currently, there is no capability to assess early concepts using airfield data. This research develops a methodology and a tool that assesses system concepts using world-wide civil and military airfield infrastructure, such as runway parameters, parking, munitions, fuel and warehouse storage, and distance to areas of interest. Specifically, the focus of the thesis is on concepts for the Intelligence, Surveillance, and Reconnaissance (ISR) Strike mission. Four concepts were assessed, a Medium-Altitude Long Endurance (MALE) ISR vehicle similar to a MQ-9 Reaper, a light attack aircraft, a light attack jet, and a low-cost attritable aircraft similar to a BQM-167A aerial drone. The tool incorporates Value Focused Thinking, with the value model conditioned by selected design parameters. The system that values a set of airfields the highest would be advantageous in an adaptive basing environment. The MALE ISR platform resulted in a statistically significant difference (nearly 10 ) in median value determined by the Wilcoxon signed rank test, then the other systems.

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Document Details

Document Type
Technical Report
Publication Date
Mar 21, 2019
Accession Number
AD1077467

Entities

People

  • Patrick J. Kelly

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • C4I
  • Engineered Resilient Systems
  • Space
  • Weapons Technologies

DTIC Thesaurus Topics

  • Air Force
  • Air Force Facilities
  • Aircrafts
  • Airframes
  • Department Of Defense
  • Digital Engineering
  • Information Operations
  • Logistics
  • Military Operations
  • Military Science
  • Model Based Systems Engineering
  • National Security
  • Surveillance
  • Systems Engineering
  • United States
  • United States Government
  • Unmanned Aerial Vehicles

Readers

  • Aerospace logistics and air mobility.
  • Regression Analysis.
  • Unmanned Aerial System (UAS) Autonomous Capabilities and Mission Reconnaissance.

Technology Areas

  • Autonomy
  • Autonomy - UAVs