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D-Index & Metrics

Mechanical and Aerospace Engineering

D-Index
49
Citations
7545
World Ranking
1243
National Ranking
505

Overview

Yongming Liu is affiliated with Arizona State University in the United States and has contributed extensively to the field of engineering. Their research covers a wide range of engineering disciplines, focusing primarily on aerospace engineering, civil and structural engineering, mechanical engineering, mechanics of materials, and artificial intelligence.

The main topics addressed in Yongming Liu's work include:

  • Air Traffic Management and Optimization
  • Structural Health Monitoring Techniques
  • Fatigue and fracture mechanics
  • Probabilistic and Robust Engineering Design
  • Non-Destructive Testing Techniques
  • Autonomous Vehicle Technology and Safety
  • Aerospace and Aviation Technology

Liu has published numerous papers with some notable recent works as follows:

  • Removal of Copper Ions from Wastewater: A Review, 2023, International Journal of Environmental Research and Public Health
  • Fatigue modeling using neural networks: A comprehensive review, 2022, Fatigue & Fracture of Engineering Materials & Structures
  • Data-driven trajectory prediction with weather uncertainties: A Bayesian deep learning approach, 2021, Transportation Research Part C Emerging Technologies
  • Probabilistic physics-guided machine learning for fatigue data analysis, 2020, Expert Systems with Applications
  • Structural dynamics simulation using a novel physics-guided machine learning method, 2020, Engineering Applications of Artificial Intelligence

Frequent collaborators in Liu's research include:

  • Yutian Pang
  • Jueming Hu
  • Changyu Meng
  • Yi Gao
  • Hao Yan

Liu's work has appeared regularly in several scholarly venues, demonstrating a pattern of publication in:

  • arXiv (Cornell University)
  • SSRN Electronic Journal
  • AIAA Scitech 2020 Forum
  • International Journal of Fatigue
  • Reliability Engineering & System Safety

Additionally, Yongming Liu has contributed to book publications, including a title published by Springer Science+Business Media:

  • Problem Solving Methods and Strategies in High School Mathematical Competitions, 2023

Best Publications

  • Probabilistic fatigue life prediction using an equivalent initial flaw size distribution

    Yongming Liu;Sankaran Mahadevan

  • Multiaxial high-cycle fatigue criterion and life prediction for metals

    Yongming Liu;Sankaran Mahadevan

  • Microstructure Representation and Reconstruction of Heterogeneous Materials Via Deep Belief Network for Computational Material Design

    Ruijin Cang;Yaopengxiao Xu;Shaohua Chen;Yongming Liu

  • Fatigue crack initiation life prediction of railroad wheels

    Yongming Liu;Brant Stratman;Sankaran Mahadevan

  • Probabilistic physics-guided machine learning for fatigue data analysis

    Unknown

  • Probabilistic prediction with Bayesian updating for strength degradation of RC bridge beams

    Yafei Ma;Jianren Zhang;Lei Wang;Yongming Liu

  • Stochastic fatigue damage modeling under variable amplitude loading

    Yongming Liu;Sankaran Mahadevan

  • Structural health monitoring of railroad wheels using wheel impact load detectors

    Brant Stratman;Yongming Liu;Sankaran Mahadevan

  • Structural response reconstruction based on empirical mode decomposition in time domain

    Jingjing He;Xuefei Guan;Yongming Liu

  • In-situ fatigue life prognosis for composite laminates based on stiffness degradation

    Tishun Peng;Yongming Liu;Abhinav Saxena;Kai Goebel

  • A probabilistic crack size quantification method using in-situ Lamb wave test and Bayesian updating

    Jinsong Yang;Jingjing He;Xuefei Guan;Dengjiang Wang

  • Analysis of subsurface crack propagation under rolling contact loading in railroad wheels using FEM

    Yongming Liu;Liming Liu;Sankaran Mahadevan

  • A unified multiaxial fatigue damage model for isotropic and anisotropic materials

    Yongming Liu;Sankaran Mahadevan

  • Fatigue life prediction for aging RC beams considering corrosive environments

    Yafei Ma;Yibing Xiang;Lei Wang;Jianren Zhang

  • Threshold stress intensity factor and crack growth rate prediction under mixed-mode loading

    Yongming Liu;Sankaran Mahadevan

  • Crack growth-based fatigue life prediction using an equivalent initial flaw model. Part I: Uniaxial loading

    Yibing Xiang;Zizi Lu;Yongming Liu

  • A generalized 2D non-local lattice spring model for fracture simulation

    Hailong Chen;Enqiang Lin;Yang Jiao;Yongming Liu

  • Model selection, updating, and averaging for probabilistic fatigue damage prognosis

    Xuefei Guan;Ratneshwar Jha;Yongming Liu

  • A multi-feature integration method for fatigue crack detection and crack length estimation in riveted lap joints using Lamb waves

    Jingjing He;Xuefei Guan;Tishun Peng;Yongming Liu

  • Structural dynamics simulation using a novel physics-guided machine learning method

    Yang Yu;Houpu Yao;Yongming Liu

  • Investigation of incremental fatigue crack growth mechanisms using in situ SEM testing

    Wei Zhang;Yongming Liu

  • Small time scale fatigue crack growth analysis

    Zizi Lu;Yongming Liu

Frequent Co-Authors

Sankaran Mahadevan
Sankaran Mahadevan Vanderbilt University
Kai Goebel
Kai Goebel Palo Alto Research Center
Abhinav Saxena
Abhinav Saxena General Electric (United States)
Lei Ying
Lei Ying University of Michigan–Ann Arbor
Steve C.S. Cai
Steve C.S. Cai Southeast University
Alexander A. Green
Alexander A. Green Boston University
Nima Shamsaei
Nima Shamsaei Auburn University
Nancy J. Cooke
Nancy J. Cooke Arizona State University
R. Srikant
R. Srikant University of Illinois at Urbana-Champaign
Jingrui He
Jingrui He University of Illinois at Urbana-Champaign

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