CORE
🇺🇦
make metadata, not war
Services
Services overview
Explore all CORE services
Access to raw data
API
Dataset
FastSync
Content discovery
Recommender
Discovery
OAI identifiers
OAI Resolver
Managing content
Dashboard
Bespoke contracts
Consultancy services
Support us
Support us
Membership
Sponsorship
Community governance
Advisory Board
Board of supporters
Research network
About
About us
Our mission
Team
Blog
FAQs
Contact us
research
Experimental investigation on performance of fabrics for indirect evaporative cooling applications
Authors
Kevin S. Fancey
Xiaoli Ma
Peng Xu
Xudong Zhao
Publication date
11 October 2016
Publisher
'Elsevier BV'
Doi
Cite
Abstract
© 2016 Indirect evaporative cooling, by using water evaporation to absorb heat to lower the air temperature without adding moisture, is an extremely low energy and environmentally friendly cooling principle. The properties of the wet channel surface in an indirect evaporating cooler, i.e. its moisture wicking ability, diffusivity and evaporation ability, can greatly affect cooling efficiency and performance. Irregular fibres help to divert moisture and enlarge the wetted area, thus promoting evaporation. A range of fabrics (textiles) weaved from various fibres were experimentally tested and compared to Kraft paper, which has been conventionally used as a wet surface medium in evaporative coolers. It was found that most of the textile fabrics have superior properties in moisture wicking ability, diffusivity and evaporation ability. Compared with Kraft paper, the wicking ability of some fabrics was found to be 171%–182% higher, the diffusion ability 298%–396% higher and evaporation ability 77%–93% higher. A general assessment concerning both the moisture transfer and mechanical properties found that two of the fabrics were most suitable for indirective evaporative cooling applications
Similar works
Full text
Open in the Core reader
Download PDF
Available Versions
Supporting member
Repository@Hull - CRIS
See this paper in CORE
Go to the repository landing page
Download from data provider
oai:hull-repository.worktribe....
Last time updated on 27/02/2018