Article
Chemistry, Multidisciplinary
Yousef Alipouri, Lexuan Zhong
Summary: The study proposes a new multi-model approach to identify and regulate HVAC systems, which simultaneously conducts clustering and regression steps, optimizes cost functions, and develops a global model using a gap metric-based approach.
APPLIED SCIENCES-BASEL
(2021)
Article
Engineering, Electrical & Electronic
Izhar, Xiaoyi Wang, Wei Xu, Hadi Tavakkoli, Zhikun Yuen, Xiaofang Shan, Yi-Kuen Lee
Summary: This article presents a HTCS system based on MEMS sensors with improved accuracy compared to traditional systems, utilizing novel technology and algorithms. Experimental results show promising potential for integration into smart HVAC systems in the era of the Internet of Things.
IEEE SENSORS JOURNAL
(2021)
Article
Energy & Fuels
C. Blad, S. Bogh, C. Kallesoe, Paul Raftery
Summary: This paper presents a laboratory study on Offline-trained Reinforcement Learning (RL) control of a Heating Ventilation and Air-Conditioning (HVAC) system. The experiments were conducted on a radiant floor heating system with real-world weather in Denmark. The results show that the RL policy exhibited predictive control-like behavior and reduced system oscillations by at least 40%. Additionally, the RL policy was found to be at least 14% more cost-effective than the traditional control policy used in the benchmarking test.
Article
Construction & Building Technology
W. T. Ho, F. W. Yu
Summary: This study explores the predictor variables for time series models of chiller systems and finds that the part load ratio is a key factor influencing system performance and predictability. Proper chiller sequencing can increase system efficiency.
JOURNAL OF BUILDING ENGINEERING
(2021)
Article
Multidisciplinary Sciences
Qi He, Chongshi Gu, Silvio Valente, Erfeng Zhao, Xing Liu, Dongyang Yuan
Summary: In this study, the safety of the Foziling multi-arch dam was evaluated by analyzing measured displacements and simulating concrete stresses. The dam is currently in an elastic state, with temperature being the main factor contributing to displacements. The stresses generally meet code requirements. The methods and results of this study can provide references for the safety evaluation of other concrete dams.
SCIENTIFIC REPORTS
(2022)
Article
Thermodynamics
Jose Eduardo Pachano, Maria Fernandez-Vigil Iglesias, Juan Carlos Saiz, Carlos Fernandez Bandera
Summary: Buildings account for 40% of Europe's total energy consumption, and heating, ventilation, and air conditioning systems consume 50-60% of the energy spent inside buildings. This study validates an optimization-based calibration methodology for building thermal simulation and energy models. It optimizes the parameters of cooling system components and evaluates the energy consumption and interior temperature of a commercial building.
APPLIED THERMAL ENGINEERING
(2023)
Article
Automation & Control Systems
Huan Xu, Feng Ding, Erfu Yang
Summary: This paper explores data filtering-based identification algorithms for an exponential autoregressive time-series model with moving average noise. By using the hierarchical identification principle, the model is transformed into three sub-identification models and a new extended stochastic gradient algorithm is derived. Through simulation results, it is shown that the proposed algorithm can effectively improve parameter estimation accuracy.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Automation & Control Systems
Shunjian Ma, Yuanyuan Zou, Shaoyuan Li
Summary: This paper proposes a coordinated strategy of distributed model predictive control (DMPC) to regulate Variable Air Volume (VAV) boxes and Air Handling Unit (AHU) in a multi-zone HVAC system. By implementing equivalent local cooling cost and total-air-mass-rate penalty term, the operational cost of the HVAC system can be reduced with coordination from both DMPC and the upper layer.
JOURNAL OF PROCESS CONTROL
(2021)
Article
Construction & Building Technology
R. M. Schierloh, S. N. Bragagnolo, J. R. Vega, J. C. Vaschetti
Summary: This study proposes an optimal real-time management scheme for multi-units HVAC systems based on predictive control. It aims to improve energy efficiency and reduce electrical cost, applicable to multi-zone buildings with low-cost implementations. The scheme formulates an optimization problem to be solved using simple variable prediction models and is applied to a radiotherapy and medical imaging center HVAC system in Argentina. The performance is evaluated using different prediction models and compared against an improved on-off control, showing significant improvements in thermal comfort and electrical cost reduction.
ENERGY AND BUILDINGS
(2023)
Article
Energy & Fuels
David Blum, Zhe Wang, Chris Weyandt, Donghun Kim, Michael Wetter, Tianzhen Hong, Mary Ann Piette
Summary: Model Predictive Control (MPC) is a promising technique for HVAC systems, but has not been widely adopted due to factors such as high implementation expertise requirements, lack of high quality data, and industry risk aversion. This study demonstrates the implementation of MPC using a developed tool-chain in a real office building, discussing challenges and estimating implementation effort to inform future workflow development.
Article
Physics, Fluids & Plasmas
Lucas Fuentes Valenzuela, Lindell Williams, Michael Chertkov
Summary: We study the collective phenomena and constraints associated with the aggregation of individual cooling units in buildings. A realistic model is built to analyze the relaxation dynamics of individual unit temperatures. We observe the emergence of bimodal probability distribution and a trade-off between occupant comfort and energy consumption.
Article
Biochemical Research Methods
Gang Wen, Limin Li
Summary: In this work, a novel multi-omics deep survival prediction approach named FGCNSurv is proposed, which utilizes a dually fused graph convolutional network (GCN). The FGCNSurv method demonstrates superior performance in extracting complementary information from multi-omics data, and outperforms existing survival prediction methods on real-world datasets.
Article
Environmental Sciences
Joel Hernandez-Bedolla, Abel Solera, Javier Paredes-Arquiola, Sonia Tatiana Sanchez-Quispe, Constantino Dominguez-Sanchez
Summary: This study developed a novel stochastic model to analyze the impact of temperature and precipitation on river basins, and conducted a case study on the Jucar River Basin in Spain. We used a Markov model to determine daily rainfall occurrences and developed a multisite multivariate autoregressive model to represent the short-term memory of temperature. The reduction of parameters and normalization of temperature were important factors in this approach.
Article
Economics
Luc Bauwens, Guillaume Chevillon, Sebastien Laurent
Summary: Two recent studies have found conditions for large dimensional networks or systems to generate long memory. Building on these findings, we propose a multivariate methodology for modeling and forecasting series with long range dependence. By incorporating long memory properties in a vector autoregressive system of order 1, and applying Bayesian estimation or ridge regression, we outperform univariate time series long memory models in forecasting daily volatility for 250 U.S. company stocks over twelve years. This empirical validation supports the theoretical results that long memory can be sourced from marginalization within a large dimensional system.
JOURNAL OF ECONOMETRICS
(2023)
Review
Energy & Fuels
Manoj Bhandari, Nelson Fumo
Summary: This paper presents a comprehensive review of research in the field of ductless mini split heat pump systems. By categorizing and summarizing papers based on their topics, the study provides insights into the performance, thermal comfort, energy savings, and market potential of such systems.
Article
Construction & Building Technology
Parth Bansal, Steven Jige Quan
Summary: This study investigates the relationship between urban form and canopy layer urban heat island (CUHI) using a relatively large sample of microclimate sensors in Seoul, Korea. The study compares different statistical models and finds that the spatially explicit gradient boosting decision tree (GBDT) model has the highest accuracy. The study also shows that the effect of urban form on CUHI varies at different time instances during the day. These findings provide valuable insights for planners to understand the complexity of urban climate and reduce CUHI magnitude.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Miaomiao Liu, Salah Almazmumi, Pinlu Cao, Carlos Jimenez-bescos, John Kaiser Calautit
Summary: Windcatchers provide effective low-energy ventilation and summer passive cooling in temperate climates. However, their use in winter is limited due to significant ventilation heat loss and potential discomfort. This study evaluates the applicability of windcatchers in low-temperature conditions, highlighting the need for control strategies to reduce over-ventilation and the integration of heat recovery or thermal storage to enhance winter thermal conditions.
BUILDING AND ENVIRONMENT
(2024)
Review
Construction & Building Technology
Behrouz Nourozi, Aneta Wierzbicka, Runming Yao, Sasan Sadrizadeh
Summary: This article presents a systematic review of ventilation solutions in hospital wards, aiming to enhance pathogen removal performance while maintaining patient and healthcare staff comfort using air-cleaning techniques. The study reveals the importance of proper ventilation systems in reducing infection risk and adverse effects of cross-contamination.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Zhen Yang, Weirong Zhang, Hongkai Liu, Weijia Zhang, Mingyuan Qin
Summary: The study examines the influence of personalized local heating on the thermal comfort of occupants in old residential buildings. The findings reveal that personalized local heating can increase the overall thermal sensation of occupants, but only a few methods are effective in enhancing thermal comfort. The chosen heating methods and background temperature affect the participants' selection of heating parts.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Hong Cheng, Dan Norback, Huilin Zhang, Liu Yang, Baizhan Li, Yinping Zhang, Zhuohui Zhao, Qihong Deng, Chen Huang, Xu Yang, Chan Lu, Hua Qian, Tingting Wang, Ling Zhang, Wei Yu, Juan Wang, Xin Zhang
Summary: The home environment and sick building syndrome (SBS) symptoms in five southern Chinese cities have been studied over time. The study found a decrease in asthma prevalence and an increase in allergic rhinitis. Cockroaches, rats, mice, mosquitoes or flies were identified as consistent biological risk factors for SBS symptoms, while redecoration, buying new furniture, and traffic air pollution were identified as other risk factors.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Chaojie Xing, Zhengtao Ai, Zhiwei Liu, Cheuk Ming Mak, Hai Ming Wong
Summary: This study experimentally investigated the emission characteristics of droplets around the mouth during dental treatments. The results showed that the peak mass fraction of droplets occurs within the size range of 20 μm to 100 μm, and droplets with a diameter less than 200 μm account for over 80% of the mass fraction. The dominant emission direction of droplets is towards the dummy's head and chest, forming an approximately cone shape.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Zhijian Liu, Zhe Han, Lina Hu, Chenxing Hu, Rui Rong
Summary: This study compared the effects of different respiratory behaviors on the distribution of aerosols in a ward and the risk of infection for healthcare workers using numerical simulation. It was found that talking in the ward significantly increased aerosol concentrations, particularly short periods of talking. Wards designed with side-supply ventilation had lower overall infection risk. Talking alternately between healthcare workers and patients slightly extended the impact time of aerosols.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Yan Yan, Mengyuan Kang, Haodong Zhang, Zhiwei Lian, Xiaojun Fan, Chandra Sekhar, Pawel Wargocki, Li Lan
Summary: In a high-density city, opening windows for sleep may lead to increased indoor temperature, higher PM2.5 concentration, and noise disturbance, which can negatively impact sleep quality.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Yan Bai, Liang Liu, Kai Liu, Shuai Yu, Yifan Shen, Di Sun
Summary: This study developed a non-intrusive personal thermal comfort model using machine learning techniques combined with infrared facial recognition. The results showed that the ensemble learning models perform better than traditional models, and the broad learning model has a higher prediction precision with lower computational complexity and faster training speed compared to deep neural networks. The findings provide a reference for optimizing building thermal environments.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Yue Lei, Zeynep Duygu Tekler, Sicheng Zhan, Clayton Miller, Adrian Chong
Summary: Mixed-mode ventilation is a promising solution for achieving energy-efficient and comfortable indoor environments. This study found that occupants can thermally adapt when switching between natural ventilation (NV) and air-conditioning (AC) modes within the same day, with the adaptation process stabilizing between 35 to 45 minutes after the mode switch. These findings are important for optimizing thermal comfort in mixed-mode controls, considering the dynamic nature of thermal adaptation.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Nan Mo, Jie Han, Yingde Yin, Yelin Zhang
Summary: This study develops a method based on the LCZ framework for a comprehensive evaluation of urban-scale heat island effects, considering the impact of geographic factors on LST. The results show that Guilin's geomorphological conditions lead to abnormal heat island effects during winter, and the cooling effects of mountains and water bodies vary seasonally in different built areas, with LCZ 2 exhibiting the strongest cooling effect.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Tunga Salthammer
Summary: Monitoring the potential formaldehyde emission of wood-based materials through test chamber investigations has significantly contributed to reducing indoor formaldehyde concentrations. However, the different methodologies used in these procedures prevent direct result comparison. Empirical models for converting formaldehyde steady-state concentrations based on temperature, humidity, air change rate, and loading were developed in the 1970s and have been modified to accommodate the development of lower-emitting materials. Formaldehyde emissions from wood-based materials are complex and require nonlinear regression tools for mathematical analysis.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Katarina Stebelova, Katarina Kovacova, Zuzana Dzirbikova, Peter Hanuliak, Tomas Bacigal, Peter Hartman, Andrea Vargova, Jozef Hraska
Summary: This study investigated the impact of reduced short-wavelength light on the hormone melatonin metabolite 6-sulfatoxymelatonin (u-sMEL) and examined the association between previous day's light exposure and u-sMEL. It was found that reducing short-wavelength light during the day did not change the concentration of u-sMEL. Personal photopic illuminance was positively correlated with u-sMEL in the reference week. The illuminance had a significant impact on u-sMEL, as shown by the evaluation of the mean of all three urine samples. However, this correlation was not found in the experimental week.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Ruoxin Xiong, Ying Shi, Haoming Jing, Wei Liang, Yorie Nakahira, Pingbo Tang
Summary: This study proposes a data-model integration method to identify and calibrate uncertainties in machine learning models, leading to improved thermal perception predictions. The method utilizes the Multidimensional Association Rule Mining algorithm to identify biased human responses and enhances prediction accuracy and reliability. The study also evaluates different calibration techniques and discovers their potential in enhancing prediction reliability.
BUILDING AND ENVIRONMENT
(2024)
Article
Construction & Building Technology
Beichao Hu, Zeda Yin, Abderrachid Hamrani, Arturo Leon, Dwayne McDaniel
Summary: This paper introduces an innovative super-resolution approach to model the air flow and temperature field in the cold aisle of a data center. The proposed method reconstructs a high-fidelity flow field by using a low-fidelity flow field, significantly reducing the computational time and enabling real-time prediction.
BUILDING AND ENVIRONMENT
(2024)