Evidence map›Paper›PMID 35448318›Full record

ArticleMembranes2022

Combined Membrane Dehumidification with Heat Exchangers Optimized Using CFD for High Efficiency HVAC Systems.

Ajay Sekar Chandrasekaran, Andrew J Fix, David M Warsinger

Open access · goldAbstract read
In one paragraph

Article in Membranes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
0.5field-weighted citation impact, top 40% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed, 7 citations in OpenAlex.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Ajay Sekar ChandrasekaranBirck Nanotechnology Center, School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA.ORCID 0000-0003-3122-9193
Andrew J FixBirck Nanotechnology Center, School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA.ORCID 0000-0001-5688-7411
David M WarsingerBirck Nanotechnology Center, School of Mechanical Engineering, Purdue University, West Lafayette, IN 47907, USA.ORCID 0000-0003-3446-1473
Purdue University West Lafayette · US

Funding

Purdue Center for High Performance Buildings CHPB-50-2020
6 · The paper itself

Abstract

Traditional air conditioning systems use a significant amount of energy on dehumidification by condensing water vapor out from the air. Membrane-based air conditioning systems help overcome this problem by avoiding condensation and treating the sensible and latent loads separately, using membranes that allow water vapor transport, but not air (nitrogen and oxygen). In this work, a computational fluid dynamics (CFD) model has been developed to predict the heat and mass transfer and concentration polarization performance of a novel active membrane-based energy exchanger (AMX). The novel design is the first of its kind to integrate both vapor removal via membranes and air cooling into one device. The heat transfer results from the CFD simulations are compared with common empirical correlations for similar geometries. The performance of the AMX is studied over a broad range of operating conditions using the compared CFD model. The results show that strong tradeoffs result in optimal values for the channel length (0.6-0.8 m) and the ratio of coil diameter to channel height (~0.5). Water vapor transport is best if the flow is just past the turbulence transition around 3000-5000 Reynolds number. These trends hold over a range of conditions and dimensions.

Indexed as

dehumidificationenergy efficiencyenergy exchangermembrane

Identifiers

PMID35448318
PMCPMC9029657
OpenAlexW4224319278

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.