Initial Identification and Investigation of Parameters for Choosing the Most Appropriate Rapidly Assembled or Deployable Structure

Abstract

It is well known that a young engineer in the professional arena is commonly faced with problems that are unlike what he has learned to solve through the rigors of his academic education. In particular, the amount of known information is small compared to what is uncertain; it may be difficult to see the real problem because it is hard to place the situation in the proper context. Unlike in formal engineering education, the problem may not have a correct answer. Instead a matrix of options may need to be generated and the decision may need to be based on financial analysis and political correctness along with technical merit. A complete factual analysis that will lead to more than one option may help in such decision-making. The necessity to base decisions on more than the issues typically addressed in engineering design classes may indicate that a decision among technically acceptable alternatives is driven by specific financial, personal, or other needs of the user. From trouble shooting computer chip circuits to performing structural analysis on concrete beams to designing a new house, an interdisciplinary approach involving a plethora of issues must be used in our dynamic culture.

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Document Details

Document Type
Technical Report
Publication Date
Aug 01, 2001
Accession Number
ADA393183

Entities

People

  • Stephen J. Donley

Organizations

  • University of Texas at Austin

Tags

Communities of Interest

  • Biomedical
  • C4I
  • Energy and Power Technologies
  • Ground and Sea Platforms
  • Human Systems

DTIC Thesaurus Topics

  • Case Studies
  • Construction
  • Department Of Defense
  • Engineering
  • Engineers
  • Environment
  • Fire Extinguishers
  • Fire Protection
  • Health Services
  • Maintenance
  • Medical Personnel
  • Natural Disasters
  • Physical Properties
  • Safety
  • Safety Equipment
  • Structural Components
  • Transportation

Readers

  • Computational Modeling and Simulation
  • Instructional Design and Training Evaluation.
  • Systems Analysis and Design