LabCompass

Taejoon Park

Engineering · The Ohio State University

Established · publishing since 1993

Publications

108

Citations

1,224

Est. group size

~2

Recurring co-author estimate

Active years

34

Publishing since 1993

Research summary
AI-generated

Taejoon Park's work focuses on understanding and predicting how metals and composites deform and fail, using computational modeling techniques such as crystal plasticity (simulating how the internal crystal structure of metals responds to stress) and finite element methods. Much of the research applies these models to materials made by additive manufacturing (3D printing) processes like wire-arc deposition, as well as to hydrogen effects on metal microstructure and fiber-reinforced composites. The work combines physics-based simulation with some machine learning approaches to predict material behavior for engineering design applications.

Crystal plasticity modeling of metalsAdditive manufacturing (wire-arc deposition) of metal alloysHydrogen-microstructure interaction and phase transformationMechanical behavior of composites and advanced steelsMachine learning surrogate models for material property prediction

Publication output grew from 2017 through a peak around 2021, then has gradually declined toward 2024-2026, though preprint activity via SSRN continues alongside journal output.

Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026

Publication cadence
Publications per year over the last 10 years — averaging 5.6/year recently
2017: 3 publications172018: 7 publications182019: 8 publications192020: 10 publications202021: 14 publications14212022: 8 publications222023: 7 publications232024: 8 publications242025: 4 publications252026: 1 publication26
Recent publications
Publishes in
  • Journal of Physics Conference Series×5
  • ˜The œminerals, metals & materials series×4
  • SSRN Electronic Journal×4
  • International Journal of Plasticity×3
  • Materials Science and Engineering A×3
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This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.

Last updated Jul 19, 2026.

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