Article
Energy & Fuels
Shuwei Wang, Pieter-Jan Hoes, Jan L. M. Hensen, Olaf C. G. Adan, Pim A. J. Donkers
Summary: With the increasing share of renewable energy in total energy consumption, the temporal mismatch between energy supply and demand in buildings is becoming a challenge. Thermochemical heat storage, with its considerable energy density, acceptable cost, and negligible heat loss, is a promising alternative to common heat storage solutions in building applications. This study proposes a method that combines modeling and simulation to assess the potential impact and benefit of a thermochemical heat storage system integrated into a building, using a data-driven surrogate model and a building performance simulation engine. The results from a case study show that the heat battery can effectively reduce electricity consumption for heating a detached house without sacrificing thermal comfort, and that a small-scale heat battery exhibits efficient usage of the designed storage capacity.
JOURNAL OF ENERGY STORAGE
(2023)
Article
Computer Science, Hardware & Architecture
Linbo Hui, Mowei Wang, Liang Zhang, Lu Lu, Yong Cui
Summary: The digital twin network (DTN) is a technology that can alleviate network burdens by virtually enabling users to understand how performance changes with modifications. This study compares several data-driven methods and explores their trends in data, models, and applications. The survey finds that performance models have been widely applied, but there are still challenges in handling diversified inputs and limited data.
Article
Computer Science, Artificial Intelligence
Patrick Haynes, Sheng Yang
Summary: Digital twins are digital replicas of physical entities that capture historical and real-time data. They are expected to be essential tools in industry 4.0 as they collect massive amounts of real-world data for various purposes. This paper proposes three types of digital twins - similar-product DT, mock-up prototype DT, and Supersystem DT - and presents a systematic framework that integrates Supersystem DT with the Theory of Inventive Problem Solving for early design activities.
ADVANCED ENGINEERING INFORMATICS
(2023)
Article
Engineering, Electrical & Electronic
Md. Mhamud Hussen Sifat, Sajal K. Das, Safwat Mukarrama Choudhury
Summary: This paper proposes a conceptual framework based on systems engineering approaches to address the issue of constructing and deploying digital twin systems in power systems. By establishing a well-defined and comprehensive development framework, the adoption of digital twin technologies in the power grid can be accelerated, leading to enhanced stability, efficiency, and sustainability.
ELECTRIC POWER SYSTEMS RESEARCH
(2024)
Article
Computer Science, Artificial Intelligence
Yinping Gao, Daofang Chang, Chun-Hsien Chen, Zhenyu Xu
Summary: This paper proposes a digital twin-enabled automated storage yard scheduling framework that utilizes the Internet of Things (IoT), virtual reality, and digital thread technologies. The framework monitors disturbed scenarios during practical operation and visualizes real-time data in the virtual space to adapt to the changing environment. The optimization of storage area, automated stacking cranes (ASCs), and automated guided vehicles (AGVs) is the main focus of this framework. A case study is conducted to demonstrate the effectiveness of the proposed framework in handling uncertainties and making optimization decisions in the port.
ADVANCED ENGINEERING INFORMATICS
(2022)
Article
Computer Science, Interdisciplinary Applications
Jinjiang Wang, Xiaotong Niu, Robert X. Gao, Zuguang Huang, Ruijuan Xue
Summary: This paper proposes a digital twin-driven virtual commissioning method to simulate machining processes in a virtual environment and obtain better commissioning results.
ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING
(2023)
Article
Computer Science, Artificial Intelligence
Jinfeng Liu, Xuwu Cao, Honggen Zhou, Lei Li, Xiaojun Liu, Peng Zhao, Jianwei Dong
Summary: This paper proposes a digital twin-driven approach towards traceability and dynamic control for processing quality. It introduces a Bayesian network model to analyze factors affecting processing quality, establishes a multi-level scalable information model and association mechanism to integrate multi-source data, and discusses the construction method of an IoT system for dynamic control of processing quality.
ADVANCED ENGINEERING INFORMATICS
(2021)
Article
Engineering, Industrial
Lin Zhang, Longfei Zhou, Berthold K. P. Horn
Summary: The concept of digital twin is gaining more attention, but there is no consensus on the definition of a right digital twin. This paper introduces some basic principles and metrics for a right digital twin, and proposes an evolutionary concurrent modeling method to guide the modeling process.
JOURNAL OF MANUFACTURING SYSTEMS
(2021)
Article
Construction & Building Technology
Yunzhu Ji, Wei Wang, Yingdong He, Lu Li, Hui Zhang, Tong Zhang
Summary: This study proposes an innovative framework for performance-based design optimization, which combines generative design with performance optimization techniques to enhance various environmental aspects of buildings. The framework can generate optimized design solutions efficiently, achieving significant improvements in thermal comfort and daylighting compared to user-defined designs.
ENERGY AND BUILDINGS
(2023)
Article
Energy & Fuels
Yuan Gao, Yuki Matsunami, Shohei Miyata, Yasunori Akashi
Summary: This study focuses on the off-grid operation and battery safety optimization of a renewable building energy system using reinforcement learning algorithms. Through training and validation with real measured data, the proposed reinforcement learning design achieves the optimization goals of off-grid operation and battery safety.
Article
Engineering, Mechanical
Shuo Wang, Xiaonan Lai, Xiwang He, Yiming Qiu, Xueguan Song
Summary: This article presents a universal framework to build accurate and trustworthy digital twins by integrating numerical simulations, sensor data, multifidelity surrogate models, and visualization techniques. The proposed framework combines simulation results and sensor data to fulfill the requirements of high accuracy and instantaneousness. It has been validated by a truss test case and shows potential as an effective tool for building digital twins.
JOURNAL OF MECHANICAL DESIGN
(2022)
Article
Computer Science, Artificial Intelligence
Jyrki Savolainen, Michele Urbani
Summary: This study focuses on optimizing time-based maintenance policy in the mining industry by utilizing digital twin systems and discrete event simulation technology to create a high-fidelity simulation environment, ultimately minimizing operational and maintenance costs.
JOURNAL OF INTELLIGENT MANUFACTURING
(2021)
Article
Computer Science, Interdisciplinary Applications
Concetta Semeraro, Mario Lezoche, Herve Panetto, Michele Dassisti
Summary: The Digital Twin (DT) is a virtual copy of a physical system that predicts failures and opportunities for change, prescribes actions in real-time, and optimizes unexpected events. However, modeling the virtual copy is complex and requires accurate models. This paper proposes a new approach that uses modeling patterns and their invariance property to design a DT. The potential of invariance modeling patterns is demonstrated through a real industrial application.
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION
(2023)
Article
Computer Science, Information Systems
Stephan Ruhe, Kevin Schaefer, Stefan Branz, Steffen Nicolai, Peter Bretschneider, Dirk Westermann
Summary: This paper introduces a hierarchical Digital Twin architecture and implementation that utilizes real-time simulation to mimic the physical grid and support grid planning and operation. With the increasing demand for detailed grid information in automated grid operations and the ongoing shift in energy systems, Digital Twins can expand data acquisition by establishing reliable real-time simulations. The system employs observer algorithms to process model information concerning the voltage dependencies of grid nodes, providing insights into the dynamic behavior of the grid. The architecture involves multiple layers of data monitoring, processing, and simulation to create node-specific Digital Twins integrated into a real-time Hardware-in-the-Loop setup. The paper includes a simulation study that validates the accuracy of the Digital Twin regarding steady-state conditions, dynamic behavior, and processing time requirements. The results demonstrate that the proposed architecture can accurately replicate the physical grid and its corresponding dynamic behavior.
Article
Automation & Control Systems
Ruijuan Xue, Xiang Zhou, Zuguang Huang, Fengli Zhang, Fei Tao, Jinjiang Wang
Summary: This paper proposes a comprehensive framework for assessing the performance of a spindle driven by digital twin, using multi-domain modeling and index system construction. The method combines subjective and objective weights to comprehensively assess the spindle performance level, and has been verified to be effective and feasible for on-site application.
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
(2022)
Article
Green & Sustainable Science & Technology
Xiaolei Yuan, Mingya Zhu, Yumin Liang, Mehdi Shahrestani, Risto Kosonen
Summary: This study compares the energy-related carbon emissions and performance of two heating, ventilation, and air-conditioning technologies (GSHP and cogeneration) in short and long-term periods under the UK decarbonization plans. It shows that the GSHP system outperforms the cogeneration system in terms of carbon reduction in both periods, despite the cogeneration system performing better in a scenario without future electricity decarbonization plans.
Article
Construction & Building Technology
Weixin Zhao, Sami Lestinen, Simo Kilpelainen, Xiaolei Yuan, Juha Jokisalo, Risto Kosonen, Miao Guo
Summary: This paper studied the potential of two micro-environment ventilation systems in mitigating airborne transmission risk indoors and compared their performance with a typical mixing ventilation system. The results showed that the micro-environment systems could reduce the infection risk for the exposed person in a short period of time.
BUILDING AND ENVIRONMENT
(2023)
Review
Multidisciplinary Sciences
Yumin Liang, Changqi Li, Zhichao Liu, Xi Wang, Fei Zeng, Xiaolei Yuan, Yiqun Pan
Summary: Accounting for one third of global energy-related carbon emissions, the construction and operation of buildings are crucial for mitigating climate change. This paper collects the latest cases to offer a comprehensive understanding of building life cycle carbon emissions (LCCEs) and explores effective approaches for their assessment and reduction. The operational process accounts for the largest share of building LCCEs, followed by the production and construction phase. Process-based assessment combining activity level and emission factors is commonly used. Advanced technologies like building information modelling and simulation are employed for effective assessment. Different approaches are proposed for decarbonization at each stage of the building life cycle, including optimizing structure, improving material performance, and using bio-based materials. Energy conservation, renewable energy integration, and smart energy management can effectively reduce operational carbon emissions. Recycling waste materials also has great environmental benefits.
Article
Construction & Building Technology
Xiaolei Yuan, Behrang Vand, Kristian Martin, Juha Jokisalo, Yumin Liang, Risto Kosonen, Yiqun Pan
Summary: This study compared three approaches to reduce heating costs in an educational office building while maintaining thermal comfort. The decentralized control method achieved the highest cost savings (5%) by adjusting the heating set point, while both centralized control and peak demand limiting also showed potential for savings. Depending on the district heating provider, implementing peak demand limiting can achieve significant cost savings (up to 16.9%) with a slight sacrifice in thermal comfort. Overall, decentralized control and district heating-based demand limiting are effective strategies for reducing heating costs.
Article
Construction & Building Technology
Haizhou Fang, Hongwei Tan, Risto Kosonen, Xiaolei Yuan, Kai Jiang, Renrong Ding
Summary: This study proposes a data augmentation based on occupancy behavior (DAOB) method to enhance the robustness and reliability of building energy consumption predictive modeling by expanding the building's three occupancy behavior data.
Article
Thermodynamics
Yifan Mao, Yongcun Li, Xiaolei Yuan, Risto Kosonen
Summary: This paper studies the maximum entropy change characteristics under different working condition parameters and validates the model. The results show that the change in sludge entropy during the drying process is mainly affected by irreversible moisture diffusion, heat transfer, and pressure. The inlet temperature, air volume, and sludge radius have significant effects on the entropy change peak and drying time, while the initial sludge temperature has little impact.
THERMAL SCIENCE AND ENGINEERING PROGRESS
(2024)
Review
Green & Sustainable Science & Technology
Xiaolei Yuan, Yumin Liang, Xinyi Hu, Yizhe Xu, Yongbao Chen, Risto Kosonen
Summary: Data centers are influential energy consumers and carbon emitters. Waste heat recovery technology is a promising approach to improve energy efficiency and mitigate environmental impacts.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2023)
Article
Construction & Building Technology
Yan Lyu, Yiqun Pan, Zhizhong Huang
Summary: This paper presents a fast load prediction method for district energy systems based on a presimulated forward modelling database and KNN algorithm, and develops it into a practical tool. The performance of the new method is compared with the traditional simulation methods, showing high prediction accuracy.
Article
Construction & Building Technology
Xiaolei Yuan, Xuetao Zhou, Yumin Liang, Yiqun Pan, Risto Kosonen, Zhongping Lin
Summary: This paper proposes a decentralized cooling system combined with heat pipe exchangers to optimize the thermal environment in a data center. The best cooling efficiency is achieved when the heat pipe exchangers are installed below each server.
Article
Construction & Building Technology
Yongbao Chen, Zhe Chen, Xiaolei Yuan, Lin Su, Kang Li
Summary: This paper proposes an innovative demand response (DR) control approach that considers the energy flexibility of buildings. Two DR control strategies, rule-based and prediction-based, are designed to shift part of the load from peak load time to valley load time, effectively improving the net load demand curve of the grid and enhancing the grid's ability to adopt renewable energies.
Article
Construction & Building Technology
Yikun Yang, Yiqun Pan, Fei Zeng, Ziran Lin, Chenyu Li
Summary: The BIM-BEM interoperability issues hinder the efficiency and automation of building energy simulation in sustainable design. This project successfully developed a workflow that addresses these issues and enables seamless geometry exchange between BIM and BEM.
