Lianshan Lin Research Staff Contact 865.241.4531 | linl@ornl.gov All Publications Dataset of Mechanically Induced Thermal Runaway Measurement and Severity Level on Li-ion Batteries Crack Propagation Modeling of a High-Speed Outer Rotor Motor Rotordynamic Analysis and Comparative Study of High-Speed Outer Rotor Permanent Magnet Motor Designs A new perspective on density and strength loss profiles at the surface of thermally oxidized nuclear graphite... Effect of Sample Thickness on the Tensile Strength of Small Graphite Discs... Mechanical and Vibration Analysis of a High-Speed Outer Rotor Electric Motor Finite Element Modeling of the Phase Change in Thermally-Grown SiO2 in SiC Systems for Gas Turbines Calibration of the 2-Phase Bubble Tracking Model for Liquid Mercury Target Simulation with Machine Learning Surrogate Models... Mechanical behavior analysis using small-size graphite disc compression testing with digital image correlation methods Mechanical Analysis of Carbon Fiber Retaining Sleeve for A High-speed Outer Rotor SPM Electric Motor Design An integrated traction drive with a high speed surface permanent magnet external rotor motor for electric vehicles... Initial Assessment of Erosion/Abrasion Issues Related to Gas-Cooled Reactors Contact pressure analysis to allow improved design for the clearing plate in a biomass comminution system... Investigation of Biomass Fouling on Screw Feeder in Preconversion of Pyrolysis... Mechanically induced thermal runaway severity analysis for Li-ion batteries Benchmarking and Exploring Parameter Space of the 2-Phase Bubble Tracking Model for Liquid Mercury Target Simulation Model calibration of the liquid mercury spallation target using evolutionary neural networks and sparse polynomial expansions Bayesian inverse uncertainty quantification of the physical model parameters for the spallation neutron source first target station Investigation of Cutter–Woodchip Contact Pressure in a New Biomass Comminution System Sensitivity Analysis of Tunable Equation of State Material Model In Pulsed Mercury Target Simulation Application of Machine Learning to Predict the Response of the Liquid Mercury Target at the Spallation Neutron Source... Incorporating bubble growth volume feedback to improve simulation of the response of a structure containing liquid and gas to sudden energy input New direction of nuclear code development: artificial intelligence On the nonlinear temperature dependence of residual stresses in solid oxide fuel cells Technical Gap Assessment for Materials and Component Integrity Issues for Molten Salt Reactors Pagination Current page 1 Page 2 Next page ›› Last page Last » Key Links Google Scholar ORCID LinkedIn Organizations Physical Sciences Directorate Materials Science and Technology Division Materials in Extremes Section Mechanical Properties and Mechanics Group
