Evidence map›Paper›PMID 36196082›Full record

ArticleBuilding simulation2023

Nationwide evaluation of energy and indoor air quality predictive control and impact on infection risk for cooling season.

Xuezheng Wang, Bing Dong, Jianshun Jensen Zhang

Abstract read
In one paragraph

Article in Building simulation, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
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.

Xuezheng WangDepartment of Mechanical and Aerospace Engineering, Syracuse University, Syracuse, NY 13244 USA.
Bing DongDepartment of Mechanical and Aerospace Engineering, Syracuse University, Syracuse, NY 13244 USA.
Jianshun Jensen ZhangDepartment of Mechanical and Aerospace Engineering, Syracuse University, Syracuse, NY 13244 USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Since the coronavirus disease 2019, the extended time indoors makes people more concerned about indoor air quality, while the increased ventilation in seeks of reducing infection probability has increased the energy usage from heating, ventilation, and air-conditioning systems. In this study, to represent the dynamics of indoor temperature and air quality, a coupled grey-box model is developed. The model is identified and validated using a data-driven approach and real-time measured data of a campus office. To manage building energy usage and indoor air quality, a model predictive control strategy is proposed and developed. The simulation study demonstrated 18.92% energy saving while maintaining good indoor air quality at the testing site. Two nationwide simulation studies assessed the overall energy saving potential and the impact on the infection probability of the proposed strategy in different climate zones. The results showed 20%-40% energy saving in general while maintaining a predetermined indoor air quality setpoint. Although the infection risk is increased due to the reduced ventilation rate, it is still less than the suggested threshold (2%) in general. Electronic Supplementary Material ESM: The Appendix is available in the online version of this article at 10.1007/s12273-022-0936-6.

Indexed as

energy-savingindoor air qualityinfection risklarge-scale simulationmodel predictive control

Identifiers

PMID36196082
PMCPMC9523641

What OpenQuestion holds

Textmetadata
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.