Article
Construction & Building Technology
Gang Jing, Chenguang Ning, Jingwen Qin, Xudong Ding, Peiyong Duan, Haitao Liu, Huiyun Sang
Summary: This study proposes a physics-guided framework of neural networks to fast predict the full-field temperature in indoor environments. The framework integrates numerical simulation, physical laws, and sparse measured data. It includes a surrogate model, a discrepancy model, and a recovery model. The proposed approach bridges the gap between numerical simulation and real-world applications, providing better full-field temperature prediction with limited measured data.
JOURNAL OF BUILDING ENGINEERING
(2023)
Article
Construction & Building Technology
Yongqiang Luo, Yixiao Song, Zhiyong Tian, Jianhua Fan, Ling Zhang
Summary: The thermal environment in a built indoor space is often non-uniform and needs to be simulated and analyzed for a healthy, energy-efficient, and comfortable space. This study proposes a new model, based on the POD and RBF methods, with the help of the Taguchi method for data preparation. The results show that the POD-RBF model is fast, accurate, robust, and flexible in applications, with a construction time of less than 3 s and computation time of less than 1 s per case. The average model error in predicting temperature and velocity field is about 0.3% and 8% across different tests.
BUILDING AND ENVIRONMENT
(2023)
Article
Thermodynamics
Hao-Cheng Zhu, Chen Ren, Shi-Jie Cao
Summary: This research presents optimal control strategies for HVAC systems, utilizing fast prediction methods and low-dimensional linear models, combined with artificial neural network and contribution ratio models, to rapidly predict indoor CO2 concentration, temperature, and humidity, and achieve optimal balance between IEQ and energy consumption.
BUILDING SIMULATION
(2021)
Article
Computer Science, Information Systems
Eslam Eldeeb, Mohammad Shehab, Anders E. Kalor, Petar Popovski, Hirley Alves
Summary: This study presents a novel traffic prediction and fast uplink framework for IoT networks controlled by binary Markovian events, utilizing hidden Markov models and the forward algorithm for resource scheduling. The performance is evaluated in terms of regret metric and Age of Information while minimizing regret and optimizing fairness. An iterative algorithm and online-learning version of the traffic prediction scheme are proposed.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Construction & Building Technology
Sai Sushanth Varma Kalidindi, Hadi Banaee, Hans Karlsson, Amy Loutfi
Summary: This paper presents a novel approach using contextual factors to predict average indoor temperature in residential buildings. Advanced deep learning architectures, including LSTM and Transformers, are utilized to create generalized predictive models. The incorporation of building rise significantly improves the accuracy of the models' predictions.
BUILDING AND ENVIRONMENT
(2023)
Article
Engineering, Civil
Oliver Scheel, Naveen Shankar Nagaraja, Loren Schwarz, Nassir Navab, Federico Tombari
Summary: This study focuses on predicting lane change events in autonomous vehicles, proposing a novel attention mechanism and scenario-based evaluation scheme. Additionally, it details a support layer for planning tasks and emphasizes the importance of leveraging similarities between tasks to improve performance.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2022)
Article
Geography, Physical
Hongdeng Jian, Xiangtao Fan, Zhenzhen Yan, Mingrui Huang
Summary: This study discusses a novel approach for 3D path prediction of moving objects in a video-augmented indoor virtual environment, showing that these methods can efficiently provide solutions for continuous tracking of moving objects.
INTERNATIONAL JOURNAL OF DIGITAL EARTH
(2021)
Article
Construction & Building Technology
Nilufer Kizilkaya Oksuz, Ali Murat Tanyer, Mehmet Koray Pekericli
Summary: Compared to other building objectives, fire safety evaluation is rarely involved in the building design process. However, all buildings should have adequate fire protection regardless of architectural design priorities. This research develops a fire vulnerability assessment model based on the impact of architects on fire protection and effects of building design characteristics on fire safety. The model effectively detects and visualizes escape route vulnerabilities, improving the interoperability of fire safety and architectural design practices.
INDOOR AND BUILT ENVIRONMENT
(2023)
Article
Energy & Fuels
Alessandro Floris, Simone Porcu, Roberto Girau, Luigi Atzori
Summary: Smart buildings utilize IoT sensors to monitor indoor environmental parameters, requiring data analytics and machine learning techniques for extracting useful insights. This paper proposes an IoT-based smart building solution for indoor environment management, including monitoring environmental parameters, detecting occupants, a cloud platform, and a control dashboard.
Article
Chemistry, Analytical
Tae-Hoon Kim, Myung Kyu Choi, Hang Seok Choi
Summary: This study utilized data-based prediction algorithms to model a biomass fast pyrolyzer and predict the yields of major products. Eight data-based prediction models were compared, indicating better agreement with experimental results compared to traditional lumped process models. The study provides new guidelines for modeling fast pyrolysis reactions using data-based prediction methods.
JOURNAL OF ANALYTICAL AND APPLIED PYROLYSIS
(2022)
Article
Engineering, Chemical
Yidan Shang, Jingliang Dong, Lin Tian, Fajiang He, Jiyuan Tu
Summary: Social distance remains a key measure to contain COVID-19 before widespread vaccination. This study conducted simulations to evaluate infection risks in the office environment and found that lower humidity increases the risk. In standard conditions, a social distance of 1.7-1.8m is sufficient to achieve a low probability of infection, but in windy conditions, a larger distance is required.
JOURNAL OF AEROSOL SCIENCE
(2022)
Article
Thermodynamics
Cary A. Faulkner, Dominik S. Jankowski, John E. Castellini, Wangda Zuo, Philipp Epple, Michael D. Sohn, Ali Taleb Zadeh Kasgari, Walid Saad
Summary: The study proposes a CGAN model for predicting indoor airflow distribution and addresses the limitations of current methods, including limited output prediction. A novel feature-driven algorithm is also designed to reduce the amount of expensive training data while maintaining prediction accuracy.
BUILDING SIMULATION
(2023)
Article
Construction & Building Technology
Liling Pan, Hanying Zheng, Tingxun Li
Summary: This study examined the impact of indoor thermal conditions on EEG signals and employed logistic regression to differentiate indoor thermal comfort. Twenty male participants were recruited to record resting EEG signals under different combinations of temperature, humidity, and air velocity. Subjective questionnaires were utilized to gather individuals' perceptions of the environment and used as criteria to develop logistic regression models. The findings demonstrated that theta, beta 1, beta 2, and gamma waves were highly similar at 22°C and 25°C, as well as velocity for all EEG waves at 0.5 and 1 m/s. Additionally, 70% relative humidity was determined as the cut-off point for high humidity in the humidity test for beta 1, beta 2, and gamma waves. Moreover, regression models were developed utilizing frequency bands associated with comfort, with the overall model accurately categorizing 88.6% of the data. This research serves as a foundation for further exploration of the interconnected environment and neuronal mechanisms.
BUILDING AND ENVIRONMENT
(2023)
Review
Computer Science, Interdisciplinary Applications
Divya J. Navamani, Jagabar M. Sathik, A. Lavanya, Dhafer Almakhles, Ziad M. Ali, Shady H. E. Abdel Aleem
Summary: This article reviews three main reliability assessment models, compares their advantages and disadvantages in DC-DC power converters, proposes an optimal assessment tool, and discusses reliability calculation tools and fault identification methods. The importance of reliability study in applications is emphasized, and a comparative analysis of statistical approaches is provided for researchers to choose appropriate methods.
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
(2023)
Article
Environmental Sciences
Chung-Yu Chen, Yu-Hsuan Liu, Chia-Hui Chieh, Wei-Hsiang Chang
Summary: The study developed and validated rapid, green, and cost-effective GC-MS methods for the simultaneous analysis of eleven OPFRs in indoor air, house dust, and skin wipes. The results showed good practices for quality assurance and quality control in the developed methods.
Article
Construction & Building Technology
Chang Xi, Junwei Ding, Chen Ren, Junqi Wang, Zhuangbo Feng, Shi-Jie Cao
Summary: In regions with hot summers and cold winters, there is a high demand for thermal comfort. However, active solutions used to improve comfort level may increase energy consumption, hindering sustainable development. The proposed passive solution of green glass space can achieve a favorable balance between comfort and energy efficiency. Through a case study, the impacts of design parameters on thermal comfort and energy efficiency are investigated, providing important design strategies for the sustainable development of green buildings and cities.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Construction & Building Technology
Jiacheng Fu, Yupeng Wang, Dian Zhou, Shi-Jie Cao
Summary: This research is based on Xingqing Palace Park in Xi'an and focuses on the impact of urban park design on urban microclimate. The study found that green coverage rate is a key factor affecting urban microclimate, while building density and mean building height have significant effects on microclimate changes during nights.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Construction & Building Technology
Chen Ren, Shi-Jie Cao, Fariborz Haghighat
Summary: During the COVID-19 pandemic, the airborne transmission of viruses has raised concerns. This study focuses on developing mitigation strategies for infection disease transmission in classrooms through optimal window design and the use of window-integrated fans. Numerical simulations show that redesigning window openings and incorporating fans can significantly improve airflow distribution and reduce infection risk.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Construction & Building Technology
Chen Ren, Haofu Chen, Junqi Wang, Zhuangbo Feng, Shi-Jie Cao
Summary: This study aims to optimize the design of subway carriage ventilation systems. Through questionnaire surveys and simulation predictions, it was found that increasing the ventilation rate is beneficial for reducing infection risk, but it can lead to worsened environmental quality and increased energy consumption. By optimizing the supply air parameters and ventilation modes, a more comfortable and healthier carriage environment can be achieved, along with better comprehensive benefits.
BUILDING AND ENVIRONMENT
(2022)
Article
Construction & Building Technology
Cunkuan Zhang, Chang Xi, Zhuangbo Feng, Junqi Wang, Shi-Jie Cao
Summary: In recent years, more and more buildings have been adopting passive technologies to meet the needs of energy saving and sustainable development. The use of green glass space (GGS) has the potential to balance thermal comfort and energy savings. In this study, a GGS-EATS coupled system is proposed to improve thermal comfort and reduce cooling loads. The optimized parameters of the system effectively solve overheating problems and can lead to significant reductions in cooling capacity and investment costs.
ENERGY AND BUILDINGS
(2022)
Article
Construction & Building Technology
Haorui Wang, Junqi Wang, Zhuangbo Feng, Chuck Wah Yu, Shi-Jie Cao
Summary: The study developed an efficient Ventilation Mode with Deflector and Slot air outlets (VMDS) to achieve efficient indoor ventilation performance for large halls. The VMDS utilizes a deflector with slot air outlets to enhance ventilation performance. Numerical simulation and comprehensive evaluation were conducted to compare VMDS with three other side air supply modes. Results show that VMDS effectively reduces indoor air pollutant concentrations and transmission of infectious diseases in large spaces, while meeting energy efficiency and thermal comfort requirements.
INDOOR AND BUILT ENVIRONMENT
(2023)
Article
Construction & Building Technology
Huai-Wen Wu, Prashant Kumar, Shi-Jie Cao
Summary: The elderly population is vulnerable to air pollution and thermal stress, but appropriate green infrastructure can improve their living environment. This review investigates the impacts of green infrastructure on elderly care centres (ECCs) and presents approaches for integrating it into the building environment design. The review highlights the importance of linking air quality with the thermal environment to ECCs and discusses the effects of green infrastructure on the physical health of the elderly.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Construction & Building Technology
Chang Xi, Junwei Ding, Junqi Wang, Zhuangbo Feng, Shi-Jie Cao
Summary: Rapid urbanization has increased the vulnerability of cities to climate change, leading to damage to urban ecosystems. Nature-based solutions can effectively regulate urban ecosystems and promote sustainable development. This study investigates the impact of greenery configurations on microclimate environment and carbon sequestration comprehensive benefits through quantitative design and evaluation.
ENERGY AND BUILDINGS
(2022)
Editorial Material
Construction & Building Technology
Junqi Wang, Chuck Wah Yu, Shi-Jie Cao
INDOOR AND BUILT ENVIRONMENT
(2023)
Editorial Material
Construction & Building Technology
Miao Yang, Haorui Wang, Chuck Wah Yu, Shi-Jie Cao
INDOOR AND BUILT ENVIRONMENT
(2023)
Article
Construction & Building Technology
Miao Yang, Chang Xi, Junqi Wang, Zhuangbo Feng, Shi-jie Cao
Summary: This paper proposes an interactive design framework for outdoor environmental paving (O-EP) and indoor ventilated atrium skylight orientation (I-VA), and investigates their impact on building carbon abatement and comfort. The results show that different combinations have significant differences, with the combination of water bodies of O-EP and 135 degrees of I-VA achieving higher carbon abatement rate and comfort than the worst combination by 17.5% and 15% respectively. Correlation analysis indicates that carbon abatement rate is significantly correlated with O-EP, while comfort is significantly correlated with O-EP in warmer seasons and with I-VA in cooler seasons.
ENERGY AND BUILDINGS
(2023)
Article
Construction & Building Technology
Prashant Kumar, Sarkawt Hama, Rana Alaa Abbass, Thiago Nogueira, Veronika S. Brand, Hui-Wen Wu, Francis Olawale Abulude, Adedeji A. Adelodun, Maria de Fatima Andrade, Araya Asfaw, Kosar Hama Aziz, Shi-Jie Cao, Ahmed El-Gendy, Gopika Indu, Anderson Gwanyebit Kehbila, Fryad Mustafa, Adamson S. Muula, Samiha Nahian, Adelaide Cassia Nardocci, William Nelson, Aiwerasia V. Ngowi, Yris Olaya, Khalid Omer, Philip Osano, Abdus Salam, S. M. Shiva Nagendra
Summary: The study found that kitchen air pollution is mainly influenced by cooking, poor ventilation, and the use of polluting fuels. In 12 global cities studied, CO2 concentrations in kitchens were generally higher.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Construction & Building Technology
Chen Ren, Hao-Cheng Zhu, Junqi Wang, Zhuangbo Feng, Gang Chen, Fariborz Haghighat, Shi-Jie Cao
Summary: This paper aims to develop intelligent operation, maintenance, and control systems in public buildings by coupling intelligent ventilation and air purification systems. The optimal deployment of sensors is determined by Fuzzy C-mean (FCM) and CO2 concentration fields are predicted using artificial neural network (ANN) and self-adaptive low-dimensional linear model (LLM). Negative oxygen ion and particle concentrations are simulated with different numbers of negative ion generators, and the optimal ventilation rates and number of generators are decided. The results showed reduced CO2 concentration, infection risk, and energy consumption, as well as high removal efficiency with a certain number of negative ion generators. The study contributes to the development of intelligent systems for infection prevention and energy sustainability.
SUSTAINABLE CITIES AND SOCIETY
(2023)
Article
Construction & Building Technology
Chang Xi, Shi-Jie Cao
Summary: Excessive carbon emissions are causing global warming and the greenhouse effect, and reducing carbon emissions in the construction industry, which is one of the main sources, is crucial. This paper summarizes the current status of building design and proposes the SCPO path to address the challenges, providing theoretical guidance for low carbon building design.
Article
Construction & Building Technology
Chen Ren, Hao-Cheng Zhu, Shi-Jie Cao
Summary: This study compared several ventilation strategies in offices and found that stratum ventilation showed the best performance in mitigating the spread of infectious diseases.
