Article
Thermodynamics
Saeid Mohammadzadeh Bina, Hikari Fujii, Shunsuke Tsuya, Hiroyuki Kosukegawa
Summary: The hybrid GSHP system utilizes supplemental energy sources to balance the load on the ground heat exchanger, improving system performance, especially in regions with imbalanced heating and cooling loads.
ENERGY CONVERSION AND MANAGEMENT
(2022)
Article
Thermodynamics
Taha Arghand, Saqib Javed, Jan-Olof Dalenback
Summary: This article investigates the coupling of direct ground cooling (DGC) with ground-source heat pumps (GSHPs) and district heating (DH). The results show that using DGC-DH significantly reduces purchased electricity, while the total energy cost is lower with DGC-GSHP. In most cases, the investment and lifecycle costs are lower for DGC-DH.
Article
Multidisciplinary Sciences
Mi Aye Su, Jack Ngarambe, Mat Santamouris, Geun Young Yun
Summary: Urban overheating is primarily caused by the urban heat island effect due to increased urbanization, which has substantial impacts on building energy consumption. Existing research relies heavily on numerical simulations, lacking empirical data support.
Article
Thermodynamics
Vittoria Battaglia, Laura Vanoli, Clara Verde, Perumal Nithiarasu, Justin R. Searle
Summary: Heat pumps are a promising solution for climate change mitigation in the European Union. Ground Source Heat Pump (GSHP) systems have high efficiency and low environmental impact, making them suitable for decarbonization of the building sector. This study evaluates strategies for heat pump systems to achieve optimal performance.
Article
Green & Sustainable Science & Technology
Jianwu Xiong, Linlin Chen, Yin Zhang
Summary: Reducing the temperature difference between indoor and outdoor environments is a confirmed energy-saving approach for space cooling and heating in buildings. This study investigates and compares the energy-saving effects of decreasing temperature difference for cooling and heating, revealing the importance of behavioral factors in cooling and heating energy savings.
Article
Construction & Building Technology
Xiaoli Liu, Kazuaki Yazawa, Ming Qu, Orkan Kurtulus, Brian Norton, Niall Holmes, Ruchita Jani, Jorge Kohanoff, Lorenzo Stella, Conrad Johnston, Hongxi Yin
Summary: The thermoelectric building envelope (TBE) integrates thermoelectric materials with the building envelope for active space heating and cooling. This study experimentally evaluates the heating and cooling performance of a TBE prototype under various operating conditions and provides critical guidance for TBE applications.
ENERGY AND BUILDINGS
(2022)
Article
Green & Sustainable Science & Technology
Chuyin Tian, Guohe Huang, Joseph M. Piwowar, Shin-Cheng Yeh, Chen Lu, Ruixin Duan, Jiayan Ren
Summary: This study develops a stochastic RCM-driven residential energy demand analysis to assess the heating and cooling energy demand of residential buildings in British Columbia, Canada. The results suggest a significant increase in energy use for cooling and a slight decrease for heating over the next 80 years. The projected energy use difference between optimistic and pessimistic levels could result in significant greenhouse gas emissions.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2022)
Article
Construction & Building Technology
Barbora Junasova, Michal Krajcik, Ondrej Sikula, Muslum Arici, Martin Simko
Summary: The application of radiant heating and cooling systems in building retrofit can make use of renewable energy sources in existing buildings. This research focused on adapting the design of ceiling and wall systems with pipes for improved heat transfer. The results showed that the spacing of the pipes and the type of insulation used have a significant impact on the system's efficiency and response time.
ENERGY AND BUILDINGS
(2022)
Article
Biology
Igor B. Mekjavic, Daniel Yogev, Ursa Ciuha
Summary: The study found that the rate and direction of temperature change during skin heating and cooling affects thermal perception and comfort. The boundaries of the Thermal Comfort Zone were identified to be higher during cooling and lower during heating. There was a strong correlation between the perception of thermal comfort and the behavioral regulation of comfort.
Article
Construction & Building Technology
Li Zhu, Jiqiang Zhang, Yuzhe Gao, Wei Tian, Zhexing Yan, Xueshun Ye, Yong Sun, Cuigu Wu
Summary: The study focuses on investigating the uncertainty and sensitivity of building loads with a new Monte Carlo method and global sensitivity analysis methods, combining building performance simulation for load forecasting and key variables analysis. The results from an office building case study demonstrate that the proposed method can rapidly and accurately simulate building loads.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Thermodynamics
Theofanis Benakopoulos, William Vergo, Michele Tunzi, Robbe Salenbien, Jakub Kolarik, Svend Svendsen
Summary: This study investigates the impact of changing the control of the heating system in a typical office building from continuous high-temperature operation to high-temperature intermittent heating or continuous low-temperature operation on energy and cost savings. The results show that continuous low-temperature operation can achieve significant energy and cost reductions.
Article
Construction & Building Technology
Huai Li, Shicong Zhang, Zhen Yu, Jianlin Wu, Bojia Li
Summary: The study explores the performance of a multienergy system in Beijing, finding that solar-assisted air conditioning saves about 47% more energy than ground source heat pump. It also shows that GSHP complements SAAC well and operates effectively in the summer season.
ENERGY AND BUILDINGS
(2021)
Article
Construction & Building Technology
Yu Cui, Zishang Zhu, Xudong Zhao, Zhaomeng Li, Peng Qin
Summary: This paper introduces the application of Bayesian calibration (BC) method in building energy models, and presents a calibrated prediction model for office buildings in Guangdong, China. The model's accuracy meets the requirement of ASHRAE Guideline 14 and has significant implications for improving the quality and integrity of existing building energy databases.
Article
Chemistry, Analytical
Rajasekhar Chaganti, Furqan Rustam, Talal Daghriri, Isabel de la Torre Diez, Juan Luis Vidal Mazon, Carmen Lili Rodriguez, Imran Ashraf
Summary: This study focuses on building energy consumption prediction using a data-driven approach. An ensemble model is proposed to achieve better prediction for cooling and heating load. The study finds that relative compactness, surface area, and wall area play a significant role in determining the appropriate cooling and heating load for a building. The proposed model outperforms existing state-of-the-art models in terms of prediction accuracy and can contribute to the design of energy-efficient buildings in future smart homes.
Article
Construction & Building Technology
Xinyi Li, Runming Yao
Summary: The building sector is a significant contributor to global energy consumption and carbon emissions. By combining physical modeling and data-driven methods, accurate predictions of heating and cooling energy consumption can be made to support building retrofit policies.
ENERGY AND BUILDINGS
(2021)
Article
Engineering, Geological
Pierre Guy Atangana Njock, Ning Zhang, Annan Zhou, Shui-Long Shen
Summary: This study proposes an improved random forest (IRF) model to evaluate ground displacement caused by jet grouting. By integrating a hybrid particle swarm optimization-simulated annealing algorithm (PSO-SA) into random forest, the IRF model shows better searching and convergence abilities compared to its counterparts. The results demonstrate that the IRF model outperforms benchmark models in predicting ground displacement. Additionally, the analysis of variable importance shows that ground lateral displacement can be controlled through two operating parameters.
GEOTECHNICAL AND GEOLOGICAL ENGINEERING
(2023)
Article
Environmental Sciences
Khalid Elbaz, Ibrahim Hoteit, Wafaa Mohamed Shaban, Shui-Long Shen
Summary: A novel deep-learning method was proposed to extract spatiotemporal features for air pollution concentration prediction, and a health risk assessment was conducted in NEOM City. The results showed that the proposed method significantly improved the accuracy of air quality forecasting compared to existing models.
Article
Environmental Sciences
Tao Yan, Annan Zhou, Shui-Long Shen
Summary: A new framework for predicting long-term water quality is proposed using Bayesian-optimized machine learning methods and key pollution indicators. The SG-op model achieves the best performance with high accuracy and Kappa coefficient. The framework can efficiently predict future water quality and provide technical support for emergency pollution control.
ENVIRONMENTAL POLLUTION
(2023)
Article
Green & Sustainable Science & Technology
Pierre Guy Atangana Njock, Annan Zhou, Zhenyu Yin, Shui-Long Shen
Summary: This study proposes a flexible methodology for quantifying the risk status of coastal subbasins, which integrates the characteristics of multi-criteria analysis and fuzzy set theory. The methodology includes constructing a risk index to reveal the extent of cumulative nutrients discharges. The application of the proposed model in the Baltic Sea shows an increasing trend of risk index over the years and aligns well with field observations and HELCOM predictions.
JOURNAL OF CLEANER PRODUCTION
(2023)
Article
Engineering, Chemical
Xin Liu, Annan Zhou, Kai Sun, Shui-Long Shen
Summary: In this study, the influence of suction on the macro/micro-mechanical behaviour of unsaturated soil was investigated through a series of three-dimensional simulations using the discrete element method. The results were compared with laboratory test results to understand the relationship between macroscopic behavior and micro-mechanical variables.
Article
Construction & Building Technology
Shui-Long Shen, Tao Yan, Annan Zhou
Summary: This paper presents an approach for estimating the locations of the soil-rock interfaces during shield tunnelling based on vibration data. The vibration data were collected using accelerometers on the back of the soil chamber wall. The continuous wavelet transform was used to analyze the time-frequency spectrum of the acceleration and identify vibration peaks. The approach was validated on the Guangzhou-Foshan intercity railway project.
AUTOMATION IN CONSTRUCTION
(2023)
Article
Engineering, Geological
Song-Shun Lin, Annan Zhou, Shui-Long Shen
Summary: Risk events in karst geological environments during excavation construction can be reduced by implementing a suitable risk-control scheme. This study proposes a decision-making approach based on the fuzzy VIKOR method to identify the optimal risk-control scheme. The approach uses a triangular fuzzy set for expressing expert judgements and constructs a decision hierarchy based on four criteria and 12 sub-criteria. The identified scheme, involving pressure grouting with a two-phase liquid system, was validated through core recovery and modified number of blows using a standard penetration test. A flowchart for optimal scheme identification in geotechnical engineering practice is also provided.
CANADIAN GEOTECHNICAL JOURNAL
(2023)
Article
Environmental Sciences
Yu -Lin Chen, Lin-Shuang Zhao, Annan Zhou, Shui-Long Shen
Summary: This paper presents a case study on the hazards of red tides in the Pearl River Estuary. Data on red tide hazards, meteorology, and seawater monitoring were collected from 1996 to 2020 in different locations around the estuary to investigate the factors influencing red tide occurrences. The ASSETS method was used to evaluate the effects of meteorological factors and seawater eutrophication on the risk level of red tides. The study established a framework for red tide risk assessment and identified external and internal factors contributing to red tide formation.
MARINE ENVIRONMENTAL RESEARCH
(2023)
Article
Engineering, Geological
Ning Zhang, Annan Zhou, Yin-Fu Jin, Zhen-Yu Yin, Shui-Long Shen
Summary: The study proposes an enhanced deep learning method to address the accuracy issue in neural network-based methods for soil stress-strain response. The enhanced method significantly improves accuracy, extrapolation capacity, and robustness. A rationality investigation is conducted into the weight gradient variation in neural networks. The effectiveness is verified through three stress-strain responses of soil, demonstrating improved predictive accuracy and robustness against errors.
Article
Construction & Building Technology
Song-Shun Lin, Annan Zhou, Shui-Long Shen
Summary: This study develops an intelligent multi-criteria decision-making (MCDM) model to select the optimal construction method for complex and fuzzy construction environments in underground infrastructure construction (UIC) in China. The model consists of three stages: decision hierarchy establishment and data collection, data processing, and MCDM modelling. It also introduces the coefficient of variation for spherical fuzzy set to evaluate the degree of consensus on judgments of experts towards evaluated objects, and outlines a decision hierarchy for the optimal construction method for UIC. The developed model provides an alternative approach to address complex decision-making issues in the UIC field.
AUTOMATION IN CONSTRUCTION
(2023)
Article
Engineering, Geological
Wei Cao, Annan Zhou, Shui-Long Shen
Summary: This paper proposes a coupled method for characterizing the stratigraphic uncertainty and rotated anisotropy of soil properties, and investigates the unsaturated soil slope stability considering the two uncertainties. The results show that the proposed method can well characterize the two uncertainties at the same time, and the rotational anisotropy of soil properties has a substantial impact on the slope stability and groundwater table.
INTERNATIONAL JOURNAL FOR NUMERICAL AND ANALYTICAL METHODS IN GEOMECHANICS
(2023)
Article
Engineering, Civil
Yi Zeng, Pierre Guy Atangana Njock, Wang Xiong, Xiao-Long Zhang, Shui-Long Shen
Summary: This paper presents a case study on the identification and management of geological and environmental risks during the construction of the largest slurry shield tunnel in China. The ground conditions and settlement control were challenging due to mixed ground conditions, fault zones, and tunneling under residential areas and Metro Lines. Novel monitoring systems, ground treatment, and safety management technologies were successfully implemented. A technical framework was proposed as a risk management guidance for similar tunneling operations.
Article
Energy & Fuels
Shui-Long Shen, Pierre Guy Atangana Njock, Annan Zhou
Summary: This paper investigates the effect of nozzle structure on efficiency of jet flow and determines the optimal nozzles for jet grouting operations through a combination of field experiment, numerical simulation, and multicriteria decision analysis. The results show that 4 out of the 10 structures investigated achieved the steadiest jetting pressure attenuation along different standoff distances, while satisfying the required driving pressure and flow rate. The study identified the converging section as critical for the conversion of viscous force within the nozzle and determined the optimal nozzle structure based on parameters such as L2 and theta.
GEOENERGY SCIENCE AND ENGINEERING
(2023)
Article
Environmental Sciences
Khalid Elbaz, Wafaa Mohamed Shaban, Annan Zhou, Shui-Long Shen
Summary: This study proposes an image-based deep learning method that improves air quality recognition and produces accurate multiple horizon forecasts. The proposed model combines a 3D-CNN, a GRU, and an attention mechanism to extract hidden features, recognize environmental variables, extract temporal features, and adjust the influence of features to avoid fluctuations in air pollutant values. Experimental results show that the proposed method outperforms other state-of-the-art methods in terms of forecasting accuracy.
Article
Construction & Building Technology
Samiran Khorat, Debashish Das, Rupali Khatun, Sk Mohammad Aziz, Prashant Anand, Ansar Khan, Mattheos Santamouris, Dev Niyogi
Summary: Cool roofs can effectively mitigate heatwave-induced excess heat and enhance thermal comfort in urban areas. Implementing cool roofs can significantly improve urban meteorology and thermal comfort, reducing energy flux and heat stress.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Qi Li, Jiayu Chen, Xiaowei Luo
Summary: This study focuses on the vertical wind conditions as a main external factor that limits the energy assessment of high-rise buildings in urban areas. Traditional tools for energy assessment of buildings use a universal vertical wind profile estimation, without taking into account the unique wind speed in each direction induced by the various shapes and configurations of buildings in cities. To address this limitation, the study developed an omnidirectional urban vertical wind speed estimation method using direction-dependent building morphologies and machine learning algorithms.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Xiaojun Luo, Lamine Mahdjoubi
Summary: This paper presents an integrated blockchain and machine learning-based energy management framework for multiple forms of energy allocation and transmission among multiple domestic buildings. Machine learning is used to predict energy generation and consumption patterns, and the proposed framework establishes optimal and automated energy allocation through peer-to-peer energy transactions. The approach contributes to the reduction of greenhouse gas emissions and enhances environmental sustainability.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Ying Yu, Yuanwei Xiao, Jinshuai Chou, Xingyu Wang, Liu Yang
Summary: This study proposes a dual-layer optimization design method to maximize the energy sharing potential, enhance collaborative benefits, and reduce the storage capacity of building clusters. Case studies show that the proposed design significantly improves the performance of building clusters, reduces energy storage capacity, and shortens the payback period.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Felix Langner, Weimin Wang, Moritz Frahm, Veit Hagenmeyer
Summary: This paper compares two main approaches to consider uncertainties in model predictive control (MPC) for buildings: robust and stochastic MPC. The results show that compared to a deterministic MPC, the robust MPC increases the electricity cost while providing complete temperature constraint satisfaction, while the stochastic MPC slightly increases the electricity cost but fulfills the thermal comfort requirements.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Somil Yadav, Caroline Hachem-Vermette
Summary: This study proposes a mathematical model to evaluate the performance of a Double Skin Facade (DSF) system and its impact on indoor conditions. The model considers various design parameters and analyzes their effects on the system's electrical output and room temperature.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Ruijun Chen, Holly Samuelson, Yukai Zou, Xianghan Zheng, Yifan Cao
Summary: This research introduces an innovative resilient design framework that optimizes building performance by considering a holistic life cycle perspective and accounting for climate projection uncertainties. The study finds that future climate scenarios significantly impact building life cycle performance, with wall U-value, windows U-value, and wall density being major factors. By using ensemble learning and optimization algorithms, predictions for carbon emissions, cost, and indoor discomfort hours can be made, and the best resilient design scheme can be selected. Applying this framework leads to significant improvements in building life cycle performance.
ENERGY AND BUILDINGS
(2024)
