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Smart HVAC systems — Adjustable airflow direction

  • Virginia Polytechnic Institute and State University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

10 Scopus citations

Abstract

Enhancing the thermal comfort level of the occupants has been the subject of several research efforts focused on controlling the Heating, Ventilation and Air-Conditioning (HVAC) systems with the objective of higher occupant-thermal-comfort. It has been demonstrated that improving occupants’ thermal comfort often leads to savings in energy consumption. Also there are numerous studies that have directly aimed to optimize the energy consumption of the HVAC system while keeping the occupants’ thermal comfort within an acceptable range. In majority of the cases the level of control over the actions of the HVAC system is restricted to controlling the temperature set-point for the thermal zone. This study aims to explore the benefits of creating a more flexible HVAC system, which can lead to improvements in occupant thermal comfort and energy consumption of the HVAC system. The envisioned HVAC system will be capable of adjusting the direction of the airflow at each diffusor thereby producing a wider range of actions. In this study, a Computational Fluid Dynamic (CFD) simulation of a room was used as a proxy for the real-world environment, and the results of the CFD model were generalized through a Gaussian Process Regression (GPR) model to provide higher resolution data. The benefits of enabling the HVAC system to control the direction of airflow at the point of diffusion have been evaluated in terms of occupant’s thermal comfort and reduction in energy consumption.

Original languageEnglish
Title of host publicationAdvanced Computing Strategies for Engineering - 25th EG-ICE International Workshop 2018, Proceedings
EditorsIan F. Smith, Bernd Domer
PublisherSpringer Verlag
Pages193-209
Number of pages17
ISBN (Print)9783319916378
DOIs
StatePublished - 2018
Event25th Workshop of the European Group for Intelligent Computing in Engineering, EG-ICE 2018 - Lausanne, Switzerland
Duration: Jun 10 2018Jun 13 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10864 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference25th Workshop of the European Group for Intelligent Computing in Engineering, EG-ICE 2018
Country/TerritorySwitzerland
CityLausanne
Period06/10/1806/13/18

Keywords

  • Airflow direction
  • Computational fluid dynamics
  • HVAC
  • Statistical learning
  • Thermal comfort

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