Information Of MATMA 2022
Prof. Bing Wang
Fuzhou University, China
Title:Structural and functional integration of foldable mechanical composite hinges
Abstract:Bistable or multistable composite structures have received increasing interest in aerospace engineering to reduce weight, complexity, and improve aerodynamic efficiency. In particular, we focus on a bistable composite tape-spring structure, which is a thin-walled, open slit composite tube, that is stable in its extended and coiled configurations. This inherent behaviour makes it ideal for the applications to foldable mechanical hinge designs: there are great opportunities in replacing the conventional hinge assemblies.
Experience: Bing Wang, a Postdoctoral researcher from University of Cambridge, with a PhD from University of Hull. He is now working at School of Mechanical Engineering and Automation, Fuzhou University, as a Professor and Doctoral Supervisor. He is also a High-level Oversea Talent in Fujian Province, a Doctoral Thesis Reviewer for the Degree Centre of the Ministry of Education, Committee Member forAdvanced Structural Materials, Life Member of Clare Hall Cambridge, Senior Member of both Chinese Mechanical Engineering Society and Chinese Society for Composite Materials. Bing is a Topic Editor and Guest Editor for Materials, Guest Editor for Advances in Mechanical Engineering, Youth Editor for Journal of Fuzhou University, and recognised peer-reviewer for more than twenty international journals. His main research direction is focused on Smart Materials and Structures, Composite Mechanics, Non-destructive testing & Evaluation, as well as Deployable Structures.
Prof. Eckart Meiburg
University of California Santa Barbara, U.S
Title:Exploring Multiphase Flow Processes via Particle-resolving Simulations
Abstract:We present an overview of particle resolving Navier Stokes simulations for a variety of multiphase flow processes. These simulations are based on an Immersed Boundary approach, which accurately captures the flow around each particle and in each pore space. We will discuss several different applications, among them particle sedimentation, particle turbulence interaction and submerged granular collapse processes. One focus will be on the influence of cohesive forces in such flows, especially the formation and break-up of aggregates consisting of several individual particles.
Experience: Professor Meiburg's research interests lie in the general area of fluid dynamics and transport phenomena. His group primarily employs the tools of computational fluid dynamics (CFD), in particular highly resolved direct numerical simulations, in order to obtain insight into the physical mechanisms that govern the spatio-temporal evolution of a wide variety of geophysical, porous media and multiphase flow fields. Occasionally, his group extends their analyses to address issues of linear stability as well. Frequently, they collaborate closely with corresponding experimental investigations. Some current interests focus on gravity and turbidity currents, Hele-Shaw displacements, double-diffusive phenomena in particle laden flows, and internal bores.
Prof. Shahid Hussain
Jiangsu University, China
Title:Recent Progresses of Atomically Thin 2D Heterostructures in Sensing Industry
Abstract:The emerging two-dimensional (2D) materials have led to the revolution across many felds in optics, electronics, optoelectronics, and sensors. Physical sensors such as photodetector and chemical sensors like gas and biological sensors play important roles in optical communications, imaging, environmental monitoring, remediation, as well as healthcare and medical industries. The implementation of 2D materials can signifcantly enhance the performances of such sensors due to their ultra-thin planar surface, large surfaceto-volume ratio, and unique physiochemical properties.
Experience: Prof. Shahid Hussain is currently working as a professor (Full) at School of Materials Science and Engineering, Jiangsu University, China. He completed his Ph.D. degree at Chongqing University, in 2015, after starting a Post-Doctoral research fellowship from 2015 to 2017. He joined Jiangsu University as Associate Professor in July 2017 and based on his outstanding achievements and experiences, he was promoted to Full Professor in July 2020 and was also approved by the state Govt of China. Dr. Shahid Hussain and the project team has executed a lot of work in the field of metal oxide, sulfides, MXenes and MOF nanomaterials based applications in gas sensors, supercapacitors and LiS Batteries. He has published high-quality research articles, and also has a wealth of experience, which laid a solid foundation for the project related research. Dr. Shahid Hussain has excellent working experience on gas sensors and has been working on sensor device fabrication since 2011. He has published more than 235 journal research articles indexed by SCI with H-Index is 38 in Google Scholar with 4650 citations (Till date Aug 2022) including Nano Energy, Chemical Engineering Journal, Journal of Hazardous Materials, Applied Materials & Interfaces, Journal of Materials Chemistry A, Sensors and Actuators B, Chemosphere, Inorganic Chemistry, Journal of Cleaner Production, Applied Surface Science, Electrochemica Acta, Materials Science and Engineering, etc. He is also working as an Editor for 18 journals indexed by SCI (Elsevier, Springer, Frontiers, Hindawi, American Scientific Publishers, and MDPI).
Prof. Junxi Bi
Inner Mongolia University of Technology, China
Title:Research on the Fault Intelligent Diagnosis and Performance Prediction Algorithm of Wind Turbine Blade under the Background of "Double Carbon"
Abstract:Against the background of the global energy crisis and the promotion of the " Double carbon" goal, clean wind energy, as a renewable energy source, has become an important direction for the development of green and clean energy. Wind turbine blades are the key components for capturing wind energy, and their frequent failures have seriously affected the reliability of wind turbines. Aiming at the problem of wind turbine blade failures, the report is based on acoustic emission signal acquisition, and mainly introduced the wind turbine blade fault signal processing based on wavelet analysis, the wind turbine blade state recognition algorithm based on BP neural network, wind turbine blade fault prediction algorithm based on HMM and hybrid neural network and real-time monitoring method of wind turbine blade health based on resonance response.
Experience:Prof. Junxi Bi was born in 1974. He is a doctor of engineering and a master instructor of mechanical engineering/ transportation of Inner Mongolia University of technology, dissertation review expert of China Academic Degrees & Graduate Education Development Center, meview expert of Scientific Reports Journal, member of Inner Mongolia Autonomous Region Professional Standardization Technical Committee, vice-chairman special committee of Reliability and Quality Management of Electronic Products of Sichuan Institute of Electronics, expert of Science and Technology Expert Database of Inner Mongolia Autonomous Region, senior member of CHINESE MECHANICAL ENGINEERING SOCIETY, expert of Defective Product Recall Expert Database of Inner Mongolia Autonomous Region, member of China Digital Simulation alliance, patent application engineer. He has presided nearly 20 national / provincial and ministerial teaching and scientific research projects such as National Natural Science Foundation, Inner Mongolia natural science foundation, Inner Mongolia Science and technology plan project and Industry-University-Research Collaboration project. He has published more than 50 papers, including 20 SCI/EI articles, obtained 4 authorized invention patents, 22 practical new patents and 1 software copyright. Also he has participated in the formulation of 2 energy industry standards of the national energy administration and a local metrological verification regulation and calibration specification of Inner Mongolia Autonomous Region. He has published 1 National Planning Textbook and participated in writing a monograph. His main directions include reliability design, manufacturing, optimization and control of complex electromechanical equipment; Fault diagnosis and performance prediction of large equipment; Digital machining and intelligent manufacturing technology.