Academic Credentials
  • Ph.D., Mechanical Engineering, National University of Ireland Galway (NUIG), Ireland, 2022
  • M.Sc., Materials Science and Engineering, University of Birmingham, UK, 2017
  • B.Eng., Materials Forming Control Engineering, Nanjing Institute of Technology (NJIT) 南京工程学院, 2016

Dr. Tu specializes in solid mechanics, computational finite element analysis (FEA), additive manufacturing, metallurgical characterization, and possesses a profound understanding of novel alloys, structural design, and manufacturing processes.

Dr. Tu's expertise in FEA model development, troubleshooting, and parameter validation benefits a range of industrial applications, including automotive, aerospace, medical devices, digital products, CAE software and material database development. His hands-on experience in manufacturing processes optimization provides valuable insights into factory audits, fabrication digital twinning, and failure root cause analysis for metal fabrication companies, and the energy sector. He utilizes his metallurgical and micromechanics knowledge to investigate strength, fatigue, and creep properties of alloys such as Ti-6Al-4V, CoCr, and stainless steels, and develop advanced surface technology and functional gradient material for metal R&D centers. Dr.Tu is also proficient in product safety reviews and export eligibility checks, and has helped clients in medical devices and electrical appliances to mitigate risks and avoid compliance hurdles.

Dr. Tu is well-versed in cutting-edge manufacturing technologies such as 3D printing (Renishaw SLM, 3D System PBF machines) and laser welding, complemented by post-heat treatment expertise. Dr. Tu's capabilities extend to the development of computational tools, with proficiency in programming languages like Fortran, Python, and MATLAB. He has integrated multi-scale and interdisciplinary approaches to conduct FEA meshing and predict mechanical properties directly from SEM/EBSD microstructural images. He also develops automation and deep learning tools for straightforward and efficient quality control.

Prior to joining Exponent, his research at the National University of Ireland, Galway, included the creation of computational models for additive manufactured alloys, highlighting a dedication to process-structure-property research. These works include the through-process ABAQUS (core modified and constitutive subroutine implemented) models to predict dislocation-based stress and fatigue life, phase-field theories (MOOSE and OpenPhase) to control grain growth during heat treatment, VASP calculation of stacking fault energy on plastic deformation, and a machine learning tool (TensorFlow) with GUI in the industry.