Junting Li | Structural health monitoring | Best Researcher Award

Published on by Global Academic Awards

Dr. Junting Li | Structural health monitoring | Best Researcher Award

lecturer at Shaanxi University of Technology, China

Dr. Junting Li is a lecturer with expertise in civil engineering, focusing on reliability-based life-cycle assessment for bridges, finite element analysis, and structural health monitoring. He holds a Ph.D. from Xi’an University of Architecture & Technology and has worked extensively on magnetic memory techniques for evaluating bridge damage. His research projects are supported by the National Natural Science Foundation of China. Dr. Li’s technical skills include ANSYS, ABAQUS, MATLAB, and Python. 📚🔧 His publications explore fatigue crack growth, corrosion defects, and structural evaluations using innovative non-destructive methods. 📊🛠️

Publication Profile

Scopus

Research Interests 🔍🏗️

Dr. Junting Li’s research focuses on the reliability-based life-cycle assessment of bridges, utilizing finite element analysis (FEA) to predict and evaluate structural integrity. His work in structural health monitoring aims to enhance the longevity and safety of infrastructure, incorporating advanced techniques like Metal Magnetic Memory (MMM) for non-destructive testing of hidden damages. Additionally, Dr. Li investigates crack propagation analysis, contributing to the development of more accurate assessment methods for bridge steel. His innovative approach combines modern computational methods with practical applications to improve the assessment and maintenance of critical civil structures. 🛠️📊

Education 🎓📚

Dr. Junting Li is currently pursuing a Ph.D. in Civil Engineering at Xi’an University of Architecture & Technology, China, with a focus on evaluating fatigue damage and life of bridge steel using Metal Magnetic Memory. His research is supervised by Prof. Sanqing Su. Previously, he completed a Master’s in Civil Engineering at Shenzhen University, where his thesis explored factors influencing shrinkage and cracking of high-strength concrete, under Prof. Weilun Wang. Dr. Li began his academic journey with a Bachelor’s in Civil Engineering from Chang’an University, Xi’an, China, solidifying his expertise in structural engineering. 🏗️🎓

Professional Experience 🛠️🏢

Since September 2024, Dr. Junting Li has been serving as a lecturer at the School of Civil Engineering and Architecture at Shaanxi University of Technology, Hanzhong, China. In this role, he is involved in teaching and conducting research in civil engineering, with a focus on the reliability-based life-cycle assessment of bridges and structural health monitoring. Dr. Li’s expertise in Metal Magnetic Memory and finite element analysis further enhances his contributions to the academic environment. His position allows him to apply his knowledge to bridge the gap between research and practical engineering solutions. 🏫🔧

Research Focus 🧠🔬

Dr. Junting Li’s research primarily centers on bridge health monitoring and structural integrity assessment using innovative techniques like Metal Magnetic Memory (MMM). His work involves evaluating fatigue damage, crack propagation, and life-cycle analysis of materials, especially steel bridges. He employs methods such as finite element analysis, stress ratio impact studies, and residual load-bearing capacity assessments to enhance the durability of civil engineering structures. Dr. Li also focuses on defect detection in ferromagnetic materials and corrosion analysis through advanced MMM techniques, aiming to improve the safety and longevity of infrastructure. 🏗️🔧💡

Publication Top Notes

  • Junting Li, Sanqing Su, Wei Wang, Xinwei Liu, Fuliang Zuo. “Fast reconstruction method for defect profiles of ferromagnetic materials based on metal magnetic memory technique,” Measurement, 2023, 215: 112885. (Cited by: 10+ 📈)

  • Sanqing Su, Junting Li, Wei Wang, Xinwei Liu, Fuliang Zuo, Ruize Deng. “Quantitative study of the defects of ferromagnetic materials using the magnetic charge model and particle swarm optimization algorithm,” Journal of Magnetism and Magnetic Materials, 2022, 564: 170076. (Cited by: 15+ 📈)

  • Sanqing Su, Junting Li, Wei Wang, Xinwei Liu, Fuliang Zuo, Ruize Deng. “Study of fatigue crack growth behavior and reliability update analysis of steel bridges,” China Civil Engineering Journal, 2024, 57(7). (Cited by: 5+ 📈)

  • Sanqing Su, Junting Li, Wei Wang, Xinwei Liu, Fuliang Zuo, Ruize Deng. “Metal magnetic memory characterization of fatigue crack propagation of Q345qD bridge steel under the influence of stress ratio,” Journal of Magnetism and Magnetic Materials, 2024: 171888. (Cited by: 8+ 📈)

  • Weilun Wang, Junting Li, Wenjun Peng. “Effects of water-to-cement ratio, curing method and fiber on the autogenous shrinkage of early-age concrete,” Journal of Ceramic Processing Research, 2019, 20: 77-85. (Cited by: 20+ 📈)

  • Zixuan Li, Zhen Chen, Junting Li, Zhiwen Xu, Weilun Wang. “Research on the Early-Age Cracking of Concrete Added with Magnesium Oxide under a Temperature Stress Test Machine,” Materials, 2023, 17(1): 194. (Cited by: 5+ 📈)

  • Xinwei Liu, Sanqing Su, Wei Wang, Junting Li, Fuling Zuo. “Evaluation of residual load-bearing capacity for corroded steel strands via MMM technique,” Journal of Constructional Steel Research, 2024, 219: 108777. (Cited by: 3+ 📈)

  • Xinwei Liu, Sanqing Su, Wei Wang, Junting Li, Fuliang Zuo, Ruize Deng. “Quantitative method for evaluating corrosion defects and residual bearing capacity of bridge structural steel via MMM technique,” Journal of Magnetism and Magnetic Materials, 2024, 590: 171639. (Cited by: 4+ 📈)

  • Xinwei Liu, Sanqing Su, Wei Wang, Junting Li, Fuliang Zuo. “Quantitative Evaluation of Corrosion Defects on Structural Steel Plates via Metal Magnetic Memory Method,” Research in Nondestructive Evaluation, 2023, 34(5-6): 169-185. (Cited by: 6+ 📈)

  • Sanqing Su, Fuliang Zuo, Wei Wang, Xinwei Liu, Junting Li, Ruize Deng. “Invisible damage identification and danger warning for steel box girders using the metal magnetic memory method,” Structures, 2023, 54: 704-715. (Cited by: 7+ 📈)