2025-01-17

"A dynamic cable dynamic response monitoring method, computer readable storage medium and program product based on deep learning" has obtained the invention patent certificate (patent number: ZL202411609188.X).

The invention discloses a dynamic cable dynamic response monitoring method based on deep learning, which collects the 6-DOF motion time history data of floating platform and the 3-DOF motion time history data of float section through the monitoring system, and combines the dynamic response data of each monitoring node along the cable length to form a training data set for different fatigue hot spots. Next, a multi-task integrated model is constructed with multiple parallel regression modules, each focused on predicting the tension or bending moment of a specific monitoring node. Each regression module is trained separately using training data sets for different fatigue hotspots and integrated to form a complete multi-task integration model. Finally, the real-time motion history data is input into the model to predict the tension and bending moment of each monitoring node, and realize the dynamic response monitoring of the dynamic cable. The invention realizes the health monitoring of the dynamic response in the dynamic cable operation and maintenance stage, reduces the monitoring cost, and improves the economic benefit of the floating wind farm.

Note: The inventors of this patent also include Associate Professor Li Binbin and master student Liu Jin.

2025-01-15

Recently, China National Knowledge Infrastructure (CNKI) released the list of highly cited scholars for 2024, and I was selected as one of the "Top 1% Highly Cited Scholars of CNKI in 2024".

The "2024 CNKI Highly Cited Researchers Top 1%" is the first quantitative assessment of scholars' academic influence conducted by the China Science Literature Metrology and Evaluation Research Center of CNKI based on the domestic academic papers and conference papers included in CNKI in 2024. It selected the list of "2024 CNKI Highly Cited Researchers" to promote the domestic first publication of outstanding academic achievements. This selection activity aims to objectively and scientifically measure and honor the group of scholars with rich research achievements and outstanding academic influence in China over the past decade.

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

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

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.