Properties and Effects of Rinse Water Additives on the Corrosion Rates of Structural Metals Used for Marine Corps Ground Vehicles

Abstract

Corrosion of military equipment remains a serious problem. It affects both operational readiness and life cycle costs. Commercial additives have been proposed for inclusion in fresh water rinses used to inhibit corrosion of military vehicles exposed to marine environments. The performance data available for these products are qualitative and do not permit reliable assessment of their utility or the anticipated level of protection. Investigation of the problem is complicated by the fact that during operations, military vehicles usually experience a wide range of environments that influence corrosion behavior. This work investigates the properties of commercial rinse additives and their influence on the corrosion rates of aluminum and steel samples. The properties examined were the ability of additives to affect seawater-induced corrosion processes, the level of inhibition observed as a function of salinity of seawater, and adherence of additive to the metal surface. An attempt was made to establish a basis for predicting and ranking the value added by wash additives during practical application.

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Document Details

Document Type
Technical Report
Publication Date
May 30, 2003
Accession Number
ADA416044

Entities

People

  • Khershed P. Cooper
  • Nick E. Train
  • Patricia P. Trzaskoma-paulette
  • Samuel G. Lambrakos

Organizations

  • United States Naval Research Laboratory

Tags

Communities of Interest

  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Adhesion
  • Chemistry
  • Environment
  • Free Electrons
  • Fresh Water
  • Ground Vehicles
  • Inhibition
  • Life Cycle Costs
  • Life Cycles
  • Materials
  • Military Operations
  • Military Science
  • Military Vehicles
  • Operational Readiness
  • Surface Plasmon Resonance
  • Surface Plasmons
  • Surface Properties

Readers

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