United States Marine Corps Assault Amphibian Vehicle Egress Study

Abstract

Due to the cancellation of the Expeditionary Fighting Vehicle (EFV) program, the Marine Corps have begun developing the Amphibious Combat Vehicle (ACV) to replace the 42-year-old Assault Amphibian Vehicle (AAV). Because the ACV will not be fielded until 2022, the AAV is being modified to improve its survivability. Upgrades to the AAV will make it heavier and, therefore, will make it sink faster. This thesis explores the factors that give Marines the best chance for surviving a sinking AAV. A 2 (17 vs. 21 embarked infantry) x 2 (daylight vs. restricted lighting) x 3 (combinations of armor and floatation devices) x 6 (combinations of egress or evacuation and number of hatches) full factorial experiment was conducted at Camp Pendleton, CA, in August 2012. An analysis of variance (ANOVA) identified specific factor combinations that yielded the lowest egress times. Specifically, subjects who left their weapons and body armor and exited through the two rear cargo hatches had the best chance of survival. This thesis provides baseline results for future emergency egress studies on the AAV and the new ACV.

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Document Details

Document Type
Technical Report
Publication Date
Jun 01, 2014
Accession Number
ADA607499

Entities

People

  • Jason T. Ford

Organizations

  • Naval Postgraduate School

Tags

Communities of Interest

  • Ground and Sea Platforms
  • Human Systems
  • Materials and Manufacturing Processes
  • Weapons Technologies

DTIC Thesaurus Topics

  • Aircraft Equipment
  • Aircraft Industry
  • Airframes
  • Amphibious Operations
  • Amphibious Vehicles
  • Analysis Of Variance
  • Armored Personnel Carriers
  • Body Armor
  • Databases
  • Experimental Design
  • Fighter Aircraft
  • Human Factors Engineering
  • Human Systems Integration
  • Human-Computer Interaction
  • Information Science
  • National Security
  • Test And Evaluation

Readers

  • Maritime Combat Support and Expeditionary Logistics.
  • Materials Science
  • Regression Analysis.