Zhenzhong Hu

    He received both his BE and PhD degree in the Department of Civil Engineering at Tsinghua University, China. He was a visiting researcher in Carnegie Mellon University.
    He is now the associate professor in Shenzhen International Graduate School, Tsinghua University, and also the secretary general of the BIM Specialty Committee of the China Graphics Society.
    His research interests include information technologies in civil and marine engineering, building information modeling (BIM) and digital disaster prevention and mitigation.
  • 2025-01-02

    2025-01-02

    The paper "Geometrized Task Scheduling and Adaptive Resource Allocation for Large-Scale Edge Computing in Smart Cities" has been published in the IEEE Internet of Things Journal. 

    Edge computing is vital in developing smart cities by providing on-site computational resources to support the surging Internet of Things demands. However, the distributed nature of edge nodes and large scale of tasks distributed in expansive urban spaces challenge task scheduling and resource allocation. In this paper, a novel framework is developed to achieve efficient task scheduling (assignment and offloading) and resource allocation for large-scale edge computing in both wired and wireless smart-city applications. To overcome overparameterization in existing optimization-based heuristic algorithms, the geometrized task scheduling problem is addressed by transforming the assignment of clustered tasks into a regional partition problem in a two-dimensional graph and applying a Tetris-like task offloading strategy for edge-cloud cooperation. These approaches avoid combinatorial explosion and NP-hardness, and the regional partition problem is solved by multiplicative weighted Voronoi diagrams with polynomial computational complexity. Furthermore, an adaptive resource allocation algorithm is proposed to overcome the dynamic, uncertain, and highly concurrent task requests. An online learning algorithm is adopted to adjust the sliding window length according to the evolving conditions. Comparison results show that the proposed framework significantly reduces the average task deadline violation rate, i.e., up to 4.72% of (more than 20 times better than) those using the other schemes, especially when handling large-scale workloads.

    Note: The IEEE Internet of Things Journal is a JCR first-tier and Chinese Academy of Sciences first-tier TOP journal with an impact factor of 8.2. The first author of the paper is Chen Yang, a master's student of the 2022 grade. The research results were funded by National Key R&D Program of China.

  • 2024-12-31

    2024-12-31

    Large-amplitude rotation of floating offshore wind turbines: A comprehensive review of causes, consequences, and solutions have been published in Renewable and Sustainable Energy Reviews journals.

    Floating offshore wind turbines (FOWTs) have emerged as a promising option for harnessing offshore wind resources, benefiting from better wind conditions in offshore areas, minimal impact on nearby coastal installations, and the ability to accommodate larger turbine sizes. Field measurements and physical model tests have demonstrated the occurrence of large-amplitude rotation in FOWTs, posing potential threats to structural integrity and causing fluctuations in electricity generation. Some studies have addressed these issues, but targeted and systematic research is noticeably lacking. This review aims to comprehensively identify and analyse the root causes of large-amplitude rotation in FOWTs, categorising them into various aspects such as hydrostatics, hydrodynamics, and aerodynamic loads, etc. The effects of nonlinear wave loads, low-frequency rotation, and negative aerodynamic damping are discussed in detail. Existing solutions proposed to mitigate large-amplitude rotation, including blade pitch control, tuned mass dampers, active ballast, and tuned liquid dampers, are summarised and evaluated. Nevertheless, most solutions to date have been adapted from fixed wind turbines. Accordingly, more specific and efficient measures must be proposed based on a more adequate understanding of the behaviour and causes of large-amplitude rotation.

    Note: Renewable and Sustainable Energy Reviews, which belongs to the Top journal of JCR1 Region and Engineering Technology Region 1 of the Chinese Academy of Sciences, has an impact factor of 16.3. The first author of this paper is Yang Lei, PhD student of Grade 2022, and Associate Professor Li Binbin is the corresponding author. The research results were supported by the General Program of National Natural Science Foundation of China, Guangdong Basic and Applied Basic Research Foundation, Guangdong joint research fund of offshore wind power, the grant of international cooperation of science and technology, department of science and technology of Guangdong province. 

  • 2024-12-24

    2024-12-24

    Recently, I received a notification from the Guangdong Association of Degree and Graduate Education that my "CAE in Civil and Architectural Engineering" teaching case has been awarded the second prize in the 2024 Guangdong Association of Degree and Graduate Education Excellent Teaching Achievement Award after being evaluated by the expert panel, publicly displayed, and reviewed by the award committee. 

    The achievement, themed as "CAE in Civil and Architectural Engineering," has formed a teaching case lineage of "system construction, textbook publication, classroom teaching, and public science popularization" to break down disciplinary barriers, promote interdisciplinary integration, cultivate students' interdisciplinary knowledge and skills, as well as innovation and practical abilities, to train more outstanding talents for the civil and architectural engineering field and provide strong support for infrastructure construction and social and economic development. 

    Firstly, this case is based on real engineering needs and the latest developments in computer information technology, providing a new framework for the knowledge structure of strong cross-disciplinary and composite talent training in the field of civil engineering. It classifies the various sub-categories of CAE technology into seven modules: visualization, modeling, discretization, virtualization, networking, automation, and intelligence. Secondly, in terms of textbook publication, "Civil and Architectural Engineering CAE" has been adopted as a professional course textbook by Tsinghua University and South China University of Technology, providing important resources for undergraduate and graduate students in civil, architectural, ocean, and construction management majors. Furthermore, this teaching case emphasizes the combination of theoretical knowledge and practical application to train students' practical skills. Students can apply their knowledge to solve real-world problems by participating in case analysis, model building, and simulation. Finally, this case extends education to the public, such as popularizing complex and advanced scientific concepts to children through the science book "Where are the Elements?" and emphasizing the importance of environmental awareness and sustainable development. This teaching case has had a wide impact in academia and society, especially its contribution in responding to the Fukushima nuclear polluted water discharge event, demonstrating its scientific basis and important value in digital disaster reduction and relief.

  • 2024-12-23

    2024-12-23

    The paper "BIM-based, data-driven method for intelligent operation and maintenance" was evaluated by the Journal of Tsinghua University (Science and Technology) as an outstanding paper for 2024. 

    The widespread adoption of Building Information Modeling (BIM) has enhanced the efficiency of building operations and maintenance management. However, intelligent operation and maintenance management based on BIM still faces challenges in data acquisition, management, and analysis. This paper combines BIM and data-driven technologies to study methods for intelligent operation and maintenance management, including: expanding and enhancing operation and maintenance BIM information through automatic generation of logical relationships of mechanical and electrical equipment; achieving dynamic operation and maintenance information management based on BIM through the proposed data cube model; and combining clustering, frequent pattern mining, and neural networks, among other machine learning methods, to mine and analyze operation and maintenance data to support intelligent operation and maintenance decision-making. The research results effectively reduce the workload of maintenance personnel, enhance the value of maintenance data, and contribute to improving the level of intelligent operation and maintenance management. 

    Note: The Journal of Tsinghua University (Science and Technology) was founded in 1915 and has a history of over 100 years. It is one of the earliest journals in China to be named after both a university and "journal". I am the first author of the paper, and the other authors are PhD student Leng Shuo and Yuan Shuang. The research was supported by the National Natural Science Foundation of China and the Shenzhen Science and Technology Research and Development Fund.

  • 2024-12-21

    2024-12-21

    On December 21, the second Qingqing Forum, co-hosted by the China Ocean Engineering Research Institute (Qingdao) and the Institute for Ocean Engineering of Tsinghua Shenzhen International Graduate School (referred to as "the Institute for Ocean Engineering"), was held in Qingdao West Coast New Area. Zhang Jianmin Academician, Feng Xiating Academician, and over 200 experts, scholars, representatives of central and state-owned enterprises involved in the sea, and representatives of high-tech enterprises attended the forum. 

    This forum, taking the unveiling of the Ocean Energy Industry Technological Innovation Strategic Alliance and the establishment of the Ocean Intelligent Equipment Innovation Joint Venture as an opportunity, aims to promote the deep integration of government, industry, academia, and research, and support the breakthrough development of ocean intelligent equipment and unmanned technology. During the forum, China Ocean Engineering Research Institute (Qingdao) signed cooperation agreements with 33 high-tech enterprises. In the themed report session, I delivered a report titled "Open Platform Architecture and Ecosystem Construction for Ocean Engineering Software Domestication." 

    The Qingqing Forum not only provides a high-level exchange platform for the field of marine engineering science and technology in China, but also injects new vitality into the innovative development of the marine intelligent equipment industry.