Digital twin-enabled building operations and control
摘要截稿:
全文截稿: 2024-09-01
影响因子: 4.867
期刊难度:
CCF分类: 无
中科院JCR分区:
• 大类 : 工程技术 - 2区
• 小类 : 结构与建筑技术 - 2区
• 小类 : 能源与燃料 - 3区
• 小类 : 工程:土木 - 2区
Overview
Energy efficiency is increasingly emphasized in the building sector, especially in the operational stages, under global carbon neutrality scenarios. In the International Energy Agency (IEA), buildings are described as “a source of enormous untapped efficiency potential” and digitalization is regarded as “a way to make energy systems smarter, more connected, efficient, and resilient.” The synergy between building areas and digitalization technologies is crucial for achieving energy-efficient and intelligent building operations. In this context, the concept of digital twins has recently been discussed in the field of building operations. Digital twins emphasize the importance of data, information, and behavioral models specifically during the building operation phase. When developing the digital twin environments and enabling digital twin-based operational applications in buildings, it is essential to consider the inherent characteristics of buildings, which are massive, designed based on specific requirements, constructed in the field, equipped with heterogeneous systems and equipment, and operated over long periods.
This special issue is intended to cover a broad range of research topics related to in-situ digital twinning and the implementation of digital twin-enabled intelligent applications, especially for the building operations. This special issue aims to present recent research that addresses key questions, academic and industrial challenges, and comprehensive solutions, ultimately enabling digital twin-based building operations.
All research topics primarily focus on the scopes of digital twin-enabled applications in the phase of building operations (but not limited to):
Building operations
Digital twins
Smart buildings and intelligent operations
Living lab
Building automation and sensing
Guest editors:
Dr. Sungmin YoonAffiliation: Sungkyunkwan University, Jongno-gu, Korea, South(Building systems, Building informatics, Building automation and sensing, Digital twins, Fault detection and diagnosis (FDD))
Dr. Clayton MillerAffiliation: National University of Singapore, Singapore, Singapore(Building energy, Human-building interaction, Personalized buildings)
Prof. Gregor HenzeAffiliation: University of Colorado Boulder, Boulder, Colorado, United States of America(Model-based predictive optimal control, Building-to-grid integration, building operational performance, Whole-building fault detection and diagnosis)