HVAC pipe/duct sizing using artificial neural networks

Shaw Jee D Yeh, Kaufui Wong

Research output: Contribution to journalArticle

2 Citations (Scopus)

Abstract

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
Pages (from-to)282-286
Number of pages5
JournalInternational Journal of Modelling and Simulation
Volume19
Issue number3
StatePublished - Dec 1 1999

Fingerprint

Conditioning
Air conditioning
Ducts
Artificial Neural Network
Heating
Pipe
Neural networks
Air
Pressure Drop
Personal Computer
Design Process
System Design
Friction
Simplify
Personal computers
Pressure drop
Neural Networks
Fluid
Systems analysis
Output

ASJC Scopus subject areas

  • Hardware and Architecture
  • Modeling and Simulation
  • Software
  • Safety, Risk, Reliability and Quality
  • Chemical Health and Safety

Cite this

HVAC pipe/duct sizing using artificial neural networks. / Yeh, Shaw Jee D; Wong, Kaufui.

In: International Journal of Modelling and Simulation, Vol. 19, No. 3, 01.12.1999, p. 282-286.

Research output: Contribution to journalArticle

Yeh, Shaw Jee D ; Wong, Kaufui. / HVAC pipe/duct sizing using artificial neural networks. In: International Journal of Modelling and Simulation. 1999 ; Vol. 19, No. 3. pp. 282-286.
@article{544fd01ac666437188383fb40d6dd658,
title = "HVAC pipe/duct sizing using artificial neural networks",
abstract = "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.",
author = "Yeh, {Shaw Jee D} and Kaufui Wong",
year = "1999",
month = "12",
day = "1",
language = "English",
volume = "19",
pages = "282--286",
journal = "International Journal of Modelling and Simulation",
issn = "0228-6203",
publisher = "ACTA Press",
number = "3",

}

TY - JOUR

T1 - HVAC pipe/duct sizing using artificial neural networks

AU - Yeh, Shaw Jee D

AU - Wong, Kaufui

PY - 1999/12/1

Y1 - 1999/12/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=0033357297&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033357297&partnerID=8YFLogxK

M3 - Article

AN - SCOPUS:0033357297

VL - 19

SP - 282

EP - 286

JO - International Journal of Modelling and Simulation

JF - International Journal of Modelling and Simulation

SN - 0228-6203

IS - 3

ER -