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Advances in Energy Efficiency in Buildings

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Energy Science and Technology".

Deadline for manuscript submissions: closed (28 February 2024) | Viewed by 1726

Special Issue Editor


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Guest Editor
School of Architecture, Yeungnam University, Gyeongsan 38541, Republic of Korea
Interests: building commissioning; smart building; building energy simulation; building energy management system
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Paris Agreement was concluded in 2015 in order to restrain problems such as global warming and energy resource depletion. Worldwide, various endeavors are being undertaken with the aim of reducing carbon emissions and becoming carbon neutral. In the building sector, interest in improving energy efficiency and saving energy is on the rise. The development and application of energy-saving methods are crucial in the stages of building design and construction, and the management, automation, and optimization of energy systems are vital in the stage of building operation. Recently, in the field of building energy, research on improving building energy efficiency using advanced technology such as artificial intelligence is being actively conducted. This Special Issue welcomes original research in the area of energy-efficient technology in buildings, smart and intelligent buildings, sustainable and net-zero energy buildings, building optimal control and operation, and building commissioning. Topics of this Special Issue include, but are not limited to, the following specific issues:

  • Building energy conversation and efficiency measure
  • Building energy audit, assessment and commissioning
  • Building energy management System(BEMS)
  • Building energy systems design, modeling and optimization
  • Building optimal control and operation
  • Occupancy comfort and indoor environmental quality
  • Heating, ventilating and air conditioning (HVAC) and renewable energy system
  • Machine and deep learning based control
  • Smart and virtual sensor
  • Fault detection diagnosis and calibration (FDD&C)

Prof. Dr. Young-Hum Cho
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Applied Sciences is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • building energy conversation and efficiency measure
  • building energy audit, assessment and commissioning
  • building energy management system (BEMS)
  • building energy systems design, modeling and optimization
  • building optimal control and operation
  • occupancy comfort and indoor environmental quality
  • heating, ventilating and air conditioning (HVAC) and renewable energy system
  • machine and deep learning based control
  • smart and virtual sensor
  • fault detection diagnosis and calibration (FDD&C)

Published Papers (2 papers)

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Research

37 pages, 18490 KiB  
Article
Numerical Design and Analysis of Advanced Roof Systems in Architecture with Environmentally Friendly Low-Carbon Materials
by Faham Tahmasebinia, Wenxi Zeng, Bernadette Macaraniag and Krzysztof Skrzypkowski
Appl. Sci. 2024, 14(5), 2041; https://doi.org/10.3390/app14052041 - 29 Feb 2024
Viewed by 763
Abstract
This research explores the viability of bamboo as a green replacement for timber in building practices. Bamboo’s advantages lie in its renewability, sustainability, and resilience to disasters, despite possessing mechanical properties similar to timber. The study proposes using Finite Element Analysis (FEA) simulations, [...] Read more.
This research explores the viability of bamboo as a green replacement for timber in building practices. Bamboo’s advantages lie in its renewability, sustainability, and resilience to disasters, despite possessing mechanical properties similar to timber. The study proposes using Finite Element Analysis (FEA) simulations, a potent instrument for designing and analyzing intricate structures under varying loads. The research explicitly employs FEA simulations to examine the application of bamboo in complex rooftop systems, using two commercial 3D CAD software—Rhino7 and Strand7. Rhino7 is responsible for 3D model creation and the member’s division into minuscule elements, whereas Strand7 is used to assign material properties, establish boundary conditions, carry out simulations, and analyze the outcomes. This research includes case studies of bamboo grid-shell structures and implements the suggested methodology. The study’s objective is to augment the scarce engineering data and to analyze bamboo as a material and the impact it can have on construction. The study’s results underscore the potential of eco-friendly, low-carbon materials, such as bamboo, in the construction industry. It also illustrates the effectiveness of FEA simulation in analyzing elaborate structures. Full article
(This article belongs to the Special Issue Advances in Energy Efficiency in Buildings)
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21 pages, 4875 KiB  
Article
Development of Virtual Sensor Based on LSTM-Autoencoder to Detect Faults in Supply Chilled Water Temperature Sensor
by San Jin, Ahmin Jang, Donghoon Lee, Sungjin Kim, Minjae Shin and Sung Lok Do
Appl. Sci. 2024, 14(3), 1113; https://doi.org/10.3390/app14031113 - 29 Jan 2024
Cited by 1 | Viewed by 658
Abstract
Supply chilled water temperature (SCWT) is an important variable for the efficient and stable operation of heating, ventilation, and air conditioning (HVAC) systems. A precisely measured value ensured by the continuous reliability of the temperature sensor is essential for optimal control of an [...] Read more.
Supply chilled water temperature (SCWT) is an important variable for the efficient and stable operation of heating, ventilation, and air conditioning (HVAC) systems. A precisely measured value ensured by the continuous reliability of the temperature sensor is essential for optimal control of an HVAC system because temperature sensor faults can affect the chiller operation and waste energy. Therefore, temperature sensor fault-detection strategies are imperative for maintaining a comfortable indoor thermal environment and ensuring the efficient and stable operation of HVAC systems. This study proposes a fault-detection method for an SCWT sensor using a virtual sensor based on a long short-term memory-autoencoder. The fault-detection performance is evaluated considering a case study under various sensor fault scenarios to evaluate changes in indoor thermal comfort and energy consumption after correcting sensor faults detected by the virtual sensor. The results verify excellent fault-detection performance in various fault scenarios (F-1 scores ranging from 0.9350 to 1.000). After correcting the SCWT fault, indoor thermal comfort is steadily maintained without additional energy consumption (indoor set-point temperature unmet hour reduced by a maximum of 105.7 hours, and energy consumption decreased by up to 1.8%). Full article
(This article belongs to the Special Issue Advances in Energy Efficiency in Buildings)
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