Key Issues in Modeling Indoor Air Quality for Building Design.

Abstract

Because of its impact on the health and productivity of building occupants, indoor air quality (IAQ) should be an important consideration in the design of any building to be used by U.S. Army military personnel or civilian employees. Frequently, however, IAQ does not receive adequate attention during design because the interrelationships between IAQ and design are often too complex or subtle to be fully understood by the architect or engineer. An effective IAQ model could help the designer take into account the major elements that contribute to poor IAQ and understand the implications his or her design decisions may have on IAQ. This report discusses key issues to be addressed in the development of an effective computer-based IAQ modeling system. The major indicators of an IAQ problem are outlined, and the contaminants that most commonly create such problems are identified. The state of modeling technology is surveyed, and gaps in modeling methodology are identified. The general requirements for a useful IAQ modeling and diagnostic tool are discussed, followed by a detailed outline of the specific research and development components required for the creation of such a tool.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Sep 01, 1992
Accession Number
ADA256783

Entities

People

  • Don Kermath
  • Eileen T. O'connor
  • Glen A. Chamberlin
  • Michael R. Kemme

Organizations

  • Construction Engineering Research Laboratory

Tags

Communities of Interest

  • Biomedical
  • Ground and Sea Platforms

DTIC Thesaurus Topics

  • Air Conditioning
  • Air Pollution
  • Carbon Monoxide
  • Chemistry
  • Computational Fluid Dynamics
  • Computational Science
  • Computer Programs
  • Computer-Aided Design
  • Computers
  • Control Systems
  • Databases
  • Dielectric Gases
  • Environment
  • Environmental Protection
  • Indoor Air Pollution
  • Steady State
  • Volatile Organic Compounds

Fields of Study

  • Engineering

Readers

  • Computational Modeling and Simulation
  • Energy Conservation and Renewable Energy Engineering.
  • Instructional Design and Training Evaluation.