HVAC pipe/duct sizing using artificial neural networks

Shaw Jee D. Yeh, Kau Fui V. Wong

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


The objective of this study is to demonstrate that artificial neural networks (ANNs) serve as useful aids to heating, ventilating and air-conditioning (HVAC) system design. The design process for sizing fluid systems in HVAC is simulated by using ANNs. Four ANNs have been constructed in a personal computer, one for air duct sizing and three for pipe sizing. The air duct network was trained to output the friction rate and duct size. The three pipe sizing neural networks product pressure drops and pipe diameters. By using the trained artificial neural networks, we can obtain data instantly with errors less than 3%. Thus, ANNs are shown to simplify traditional methods and procedures in HVAC pipe and air duct sizing.

Original languageEnglish (US)
Pages (from-to)282-286
Number of pages5
JournalUnknown Journal
Issue number3
StatePublished - Jan 1 1999

ASJC Scopus subject areas

  • Modeling and Simulation
  • Mechanics of Materials
  • Hardware and Architecture
  • Industrial and Manufacturing Engineering
  • Electrical and Electronic Engineering


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