Article
Green & Sustainable Science & Technology
Hassan Fagehi, Haitham M. Hadidi
Summary: This study discusses the thermal behavior of buildings with PCM in the NEOM city. The results show that using PCM can effectively reduce energy consumption, especially when PCM is installed on the walls to minimize heat exchange.
SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS
(2022)
Article
Computer Science, Information Systems
Young Sun Park, Jae-Cheol Ryou
Summary: This paper discusses the application of digital twin technology in power systems and proposes practical ideas and challenges. It also explores the security of DT technology based on machine learning and provides a comprehensive view for readers.
HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES
(2023)
Article
Urban Studies
Gary White, Anna Zink, Lara Codeca, Siobhan Clarke
Summary: A digital twin is a digital representation of a physical process, place, system or device, originally designed for manufacturing processes but now used for smart city planning. By creating digital twin smart cities, the public can view 3D models of cities online to provide feedback, enhancing transparency and interaction in urban planning.
Article
Computer Science, Information Systems
Zeeshan Pervez, Zaheer Khan, Abdul Ghafoor, Kamran Soomro
Summary: Smart city digital twins can provide valuable insights by utilizing multidisciplinary urban data effectively. However, the authenticity, integrity, traceability, and ownership of data are often overlooked in the digital twin ecosystem. This research introduces a novel framework, SIGNED, which ensures verifiably authentic digital twin data based on principles such as data ownership and verifiability. A proof of concept is conducted to demonstrate the effectiveness of SIGNED in securing the exchange of digital twin data and addressing privacy concerns in a smart city environment.
Article
Construction & Building Technology
Horace Guy, Simon Vittoz, Giulia Caputo, Thimothee Thiery
Summary: This paper analyzes the 2021 energy consumption data of over 20000 commercial buildings in Europe and calibrates a Bayesian multilevel modeling to predict the full distribution of energy use intensity. The modeling takes into account the country, building typology, and climate factors to accurately represent the diversity of the commercial building stock. The originality of the approach lies in its combined use of Bayesian multilevel modeling and a model structure that independently learns specific effects. The modeling shows good predictive power even for combinations of features with limited representative data.
ENERGY AND BUILDINGS
(2023)
Review
Green & Sustainable Science & Technology
Hongxiang Fu, Juan-Carlos Baltazar, David E. Claridge
Summary: Building energy consumption is a significant field of study, with statistical methods being popular due to their simplicity and accuracy in predicting energy consumption. However, there is still limited research on the applications of statistical methods in certain areas such as modeling electric demand and power factor. Further exploration and application of these methods are needed to advance research in building energy analysis.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2021)
Article
Energy & Fuels
Zhanwei He, Javad Khazaei, James D. Freihaut
Summary: The emergence of vehicle-to-building (V2B) technology allows electricity to be exported from electric vehicle (EV) batteries to buildings, aiding in meeting building energy demands. The optimal number of EVs interacting with a building depends on factors such as EV driving patterns, seasonal solar output, building demand profiles, and grid electricity prices. These factors impact the daily electricity bills, V2B capacity, charging loads, and stationary battery energy storage system (BESS) capacity. Simulation results show that the optimal number of EVs varies across seasons and solar irradiance scenarios, suggesting the importance of day-ahead solar energy forecasting for planning EV integration.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2022)
Article
Computer Science, Artificial Intelligence
Hao Wang, Xiaowei Chen, Fu Jia, Xiaojuan Cheng
Summary: A city serves as a carrier of multiple sources of real-time data and information. To effectively manage smart cities, a system is needed to obtain and manage data from different physical objects. The use of digital twin (DT) technology, which involves virtual representations updated in real-time and decision-making support, can address this need. This study reviews 202 papers on DT-supported smart cities, identifies the challenges and solutions, and explores the potential outcomes of applying DT-supported technologies.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Chemistry, Multidisciplinary
Muhyiddine Jradi, Bo Eskerod Madsen, Jakob Hovgaard Kaiser
Summary: The current trend in renovating existing buildings is to perform retrofits on a case-by-case basis without a systematic assessment, resulting in a low rate of energy renovations. This paper presents an innovative digital twin solution, 'DanRETwin', which aims to enhance and expedite energy retrofits in Danish buildings by utilizing building operational data and employing machine learning and artificial intelligence techniques.
APPLIED SCIENCES-BASEL
(2023)
Review
Green & Sustainable Science & Technology
Ehab Shahat, Chang T. Hyun, Chunho Yeom
Summary: The city digital twin is a key focus in current research, with technology advancing rapidly and playing a crucial role in smart city development. Future research directions will focus on improving data processing efficiency, enhancing the inclusivity of socio-economic factors in cities, and developing mutual integration between digital twins.
Review
Construction & Building Technology
Haishan Xia, Zishuo Liu, Maria Efremochkina, Xiaotong Liu, Chunxiang Lin
Summary: This paper provides an insightful literature review on the integration of GIS and BIM technologies. It discusses the different disciplinary classifications of GIS and BIM functional integration, proposes an ontology-based data integration approach, and suggests future research directions.
SUSTAINABLE CITIES AND SOCIETY
(2022)
Article
Construction & Building Technology
Mingyu Zhu, Philip James
Summary: This research develops a daily carbon emission benchmarking system and a digital twin framework to analyze the fluctuation of energy consumption and carbon emissions in a mixed-use building, providing actionable knowledge for asset managers and architects.
Article
Construction & Building Technology
Liang Zhao, Hong Zhang, Qian Wang, Haining Wang
Summary: In the face of increasingly severe global energy environment, effective management and use of renewable energy are needed in the construction industry. The application of BIM technology for evaluating retrofitting schemes of existing buildings is crucial for improving energy efficiency.
ADVANCES IN CIVIL ENGINEERING
(2021)
Article
Green & Sustainable Science & Technology
King Hang Lam, Wai Ming To, Peter K. C. Lee
Summary: Smart buildings save energy and provide a responsive, comfortable, and efficient indoor environment for users and occupants. The smart building management system (SBMS), as a vital component of smart buildings, should offer a wide range of functions and deliver the intended benefits upon successful deployment.
Article
Computer Science, Artificial Intelligence
Wenjie Jia, Wei Wang, Zhenzu Zhang
Summary: The digital twin has gained widespread attention in recent years as a key tool for digitalization and intelligence, but has become increasingly complex due to the expanding needs for multi-scale and multi-scenario simulations in reality. This paper proposes a novel modeling method for complex digital twins based on standardized processing of model division and assembly, enabling the construction of intricate digital twin models with effective elements in specific scales and scenarios through information fusion, multi-scale association, and multi-scenario iterations. This approach also allows for rapid development of digital twins through component and code reuse.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Multidisciplinary Sciences
Yan Wang, Qi Wang, John E. Taylor
Article
Computer Science, Interdisciplinary Applications
Yan Wang, John E. Taylor
JOURNAL OF COMPUTING IN CIVIL ENGINEERING
(2019)
Article
Energy & Fuels
Abigail Francisco, John E. Taylor
Article
Multidisciplinary Sciences
Neda Mohammadi, John E. Taylor
SCIENTIFIC REPORTS
(2019)
Article
Geosciences, Multidisciplinary
Rachel Samuels, John E. Taylor, Neda Mohammadi
Article
Engineering, Industrial
Yan Wang, John E. Taylor, Michael J. Garvin
JOURNAL OF MANAGEMENT IN ENGINEERING
(2020)
Article
Engineering, Industrial
Lei Xu, Abigail Francisco, John E. Taylor, Neda Mohammadi
Summary: As energy consumption in urban areas becomes a global concern, the impact of community behavior on managing energy consumption is critical. Eco-feedback systems utilizing advanced visualization technologies, such as virtual reality, have the potential to effectively encourage sustainable behavior at an urban scale. Participants in a study on a VR-integrated community-scale eco-feedback system showed polarized preferences, indicating the importance of incorporating community preferences in designing energy feedback systems for increased effectiveness.
JOURNAL OF MANAGEMENT IN ENGINEERING
(2021)
Article
Environmental Sciences
Lei Xu, John E. Taylor, Jennifer Kaiser
Summary: The study indicates that short-term exposure to PM2.5 and O3 may increase the risk of COVID-19 infection. There is a significant association between short-term exposure to PM2.5 and COVID-19 confirmed cases, suggesting important implications for policymakers and the public to understand the impact of air pollution on the spread of the pandemic.
ENVIRONMENTAL POLLUTION
(2022)
Article
Engineering, Industrial
John E. Taylor, Gisele Bennett, Neda Mohammadi
JOURNAL OF MANAGEMENT IN ENGINEERING
(2021)
Article
Geosciences, Multidisciplinary
Rachel Samuels, Jiajia Xie, Neda Mohammadi, John E. Taylor
Summary: This paper explores the impact of geographic scale on disaster data analysis by aggregating social media data and hurricane damage data. It studies the correlation between disaster behaviors and damage at different scales and identifies power-law relationships, which can inform more intelligent, equitable, and actionable use of social media in emergency response.
Article
Environmental Sciences
Michael M. Thomas, Neda Mohammadi, John E. Taylor
Summary: This study utilized a national-level ecological approach to measure the association between mass transit adoption and the spread of COVID-19 in US metropolitan areas. The results demonstrated that the adoption of mass transit was correlated with the severity of outbreaks, with areas showing higher levels of transit use experiencing higher incidence of COVID-19 cases. Increases in weekly bus and train transit usage were both associated with higher incidence rates of COVID-19.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Construction & Building Technology
Wei Zhang, Guodong Yuan, Rui Xue, Yilong Han, John E. Taylor
Summary: The importance of reliability in empirical research in construction engineering and management has been emphasized. This study provides a comprehensive overview of common method bias (CMB) issues and proposes effective controls to mitigate its negative impact. The findings show that a majority of articles using survey data in empirical analysis were likely to be affected by CMB.
JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT
(2022)
Article
Environmental Studies
Gregory S. Macfarlane, Nico Boyd, John E. Taylor, Kari Watkins
Summary: Recent research has shown the potential for public green spaces to impact individual and societal health outcomes, with this study applying a comprehensive park accessibility measure to demonstrate a positive relationship between park access and physical activity rates. Additionally, the data suggests a negative relationship between park access and obesity rates, beyond what is expected through physical activity and socioeconomics.
ENVIRONMENT AND PLANNING B-URBAN ANALYTICS AND CITY SCIENCE
(2021)
Article
Engineering, Industrial
Rachel Samuels, John E. Taylor
JOURNAL OF MANAGEMENT IN ENGINEERING
(2020)