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.
  • 2023-09-09

    On September 9, I was invited to Laoshan Laboratory to attend a meeting on Marine environmental monitoring, and made a report on the work and achievements of the research group in related aspects. In addition, Li Sunwei, a core member of the research team, and Liu Yi, a doctoral student, also participated in the meeting.

    Laoshan Laboratory is a breakthrough, leading and platform integrated new scientific research institution in the Marine field approved by the State. It is jointly built by the State ministries, Shandong Province and Qingdao, aiming to focus on the innovation-driven development strategy and the overall requirements of building a maritime power, adhere to the "four aspects", carry out scientific and technological innovation and institutional innovation, and strive to build a national Marine strategic scientific and technological force.

  • 2023-08-30

    Approaches Improving Cesium Rendering Performance for Displaying Massive 3D Models has been published in the Journal of Information Technology in Civil Engineering and Architecture.

    Rendering performance optimization is needed to display dense 3D models in Cesium requires improving the. However, the native approaches are unstable and will cause bad rendering results. To avoid this problem as much as possible, a mechanism is proposed in this paper to enable high-performance rendering when the camera state changes in which the camera states change pauses primitives loading, and applies parameter settings and algorithms that can improve rendering performance but may cause bad rendering results. Besides, this paper proposes a heap-based 3D tile draws command limitation approach, which can directly limit the number of draw commands and reduce the amount of GPU computation. The results prove that the mechanism of high-performance rendering when camera state changes are feasible. The mechanism outperforms the max screen space error (MSSE) increasing and the draw commands limiting, which excels reducing the resolution scale (RS) in improving rendering performance. Limiting the draw commands can ensure the stability of rendering performance compared with increasing MSSE.

    Note: The first author of this paper is Wang Hengwei, a postdoctoral fellow, and I am the corresponding author. The research results have been funded by the National Key Research and Development Program of China and the National Natural Science Foundation of China.

  • 2023-08-28

    The 19th China CAE Engineering Analysis Technology Conference and the 5th China Digital Simulation Forum were successfully held in Xiamen, Fujian Province, from August 18th to 20th. The theme of this year's conference was "Simulation Leading Intelligent Manufacturing, Digital Driving Twinning."

    Among them, the 18th was the keynote report of the conference, I attended the conference, and made a special invited report on the topic of "The fundamental way to achieve China's 'double carbon' goal", introducing the current situation of China's "carbon neutrality". On the evening of the 18th, the award ceremony of the "Yundao Cup" China Digital Simulation Competition was held. The team of the research group won the second prize of the university group of the Digital simulation Innovation Competition, and the paper submitted by the research group "The Application research of digital twin in the installation of offshore wind power" won the excellent paper award. On the 20th, members of the research group participated in the offshore engineering and petroleum equipment simulation application Forum, and reported on the submitted papers, demonstrating the application feasibility of digital twins in offshore wind power installation.

    The China CAE Engineering Analysis Technology Annual Conference is currently the largest and most influential professional exchange event in our country, with the highest level of technology. The conference was attended by more than 800 offline and more than 8,000 online representatives from scientific research institutes, enterprises, universities and major media across the country, providing a valuable platform for strengthening research, sharing and cooperation in the field of CAE.

  • 2023-08-25

    "Prediction of Magnitude and Epicentral Distance Based on Neural Network" has been published in the journal of Municipal Technology.

    In order to predict rapidly the magnitude and epicentral distance, various machine learning techniques including convolutional neural network, fully connected neural network, GELU activation function, dropout and multi-task learning were applied to establish an efficient model for predicting the magnitude and epicentral distance. The model was trained, validated, and tested by the Stanford Earthquake Dataset (STEAD). The predicted values demonstrated a better positive correlation with the actual ones, with determination coefficients of 0.938 and 0.881 for magnitude and epicentral distance respectively. These results provides new ideas and methods for the development of earthquake warning systems.

  • 2023-08-03

    "Architecture and Key Technologies of Big Data Platform for Highway Engineering Safety" has been first published in "Highway" on CNKI.

    A large number of safety-related data will be generated during the execution of highway project, which is difficult to be systematically managed and fully utilized. Firstly, the classification, content and collection method of safety data in the process of highway construction are explained, and the characteristics and processing requirements of safety data are analyzed. Secondly, the architecture of big data platform for highway engineering safety is constructed, and the main levels of the platform are briefly explained. Finally, four key technologies of data pre-processing, data fusion and storage, data asset management, data analysis and mining for highway construction safety are analyzed in detail. The results show that:(1) The data of highway project implementation can be divided into seven categories, such as basic data, structure, machinery and equipment, etc., and data processing should meet the requirements, such as data extraction from heterogeneous data sources, etc.(2) The architecture of big data platform for highway project safety can be divided into six layers: data source layer, data access and pre-processinglayer, etc.(3) The key technologies of platform include data pre-processing, data fusion and storage, etc.

    Note: Highway is a core journal of science and technology in the category of comprehensive technology.