Alan Barhorst

Alan Barhorst
  • Faculty
  • Department Head
  • Professor

Education

Ph.D., Mechanical Engineering, 1991 
Texas A&M University

M.S., Mechanical Engineering, 1989
Texas A&M University

B.S., Mechanical Engineering, 1984
Texas A&M University

Student Research/Collaboration

Dr. Barhorst's research interests are in:

  • Aerospace
  • Bio-Mechanics
  • Control System Design
  • Dynamics
  • Design
  • Fluid-Structure Interaction
  • Manufacturing
  • Mechanics
  • Mechatronics
  • Micro-Electro-Mechanical Systems
  • Multi-body Elasto-dynamics
  • Non-Destructive Evaluation–Acoustic Emissions
  • Robotics
  • System Dynamics
  • Vibrations
  • Wavelet Based Signal Processing

Publications

  • Nalaka Amarasiri, Alan A. Barhorst, and Raju Gottumukkala (2022). Robust Dynamic Modeling and Trajectory Tracking Controller of A Universal Omni-Wheeled Mobile Robot. ASME Letters in Dynamic Systems and Control. Accepted for Publication, https://doi.org/10.1115/1.4055690.
  • Christopher Umstead, Alan Barhorst, Thivakorn Kasemsri, and Kelly Mitchell (2020), Hypertension as a factor in Retinal Hemorrhaging from Abusive Head Trauma. Journal of Healthcare Engineering. Volume 2020, Article ID 4714927, 10 pages https://doi.org/10.1155/2020/4714927
  • Alan A. Barhorst (2019). Generalized Momenta in Constrained Non-Holonomic System– Another Perspective on the Canonical Equations of Motion, International Journal of Non-Linear Mechanics. https://doi.org/10.1016/j.ijnonlinmec.2019.03.006.
  • Ross Wilson, and Alan Barhorst (2018). Intercondylar Notch Impingement of the Anterior Cruciate Ligament: A Cadaveric In Vitro Study Using Robots. Journal of Healthcare Engineering, vol. 2018, Article ID 8698167, 27 pages, 2018. https://doi.org/10.1155/2018/8698167
  • Reimus, N., Barhorst, A. & Baker, M. (2018), Uncovering Neural Commands from Noisy Dermal Signals–an Experimental Verification of a Minimalistic Robotic Exoskeletal Hand Design for Medical Rehabilitation. Data-Enabled Discov. Appl. 2: 1. DOI:10.1007/s41688-017-0013-y.
  • Alan A. Barhorst (2017). Uncovering a troll in the machine–69´«Ã½ing time series data mining techniques to uncovering the mechanism causing persistent damaging oscilla- tion in a campus wide steam generator. Data Enabled Discovery and Applications, DOI:10.1007/s41688-017-0005-y
  • Alan A. Barhorst and Gang Qi (2017). Editorial. Data Enabled Discovery and Applica- tions, 1: 1. DOI:10.1007/s41688-017-0002-1.

Awards & Recognition

  • Awarded J.T. Oden Faculty Fellowship, Institute for Computational Engineering and Sciences, UT Austin, Fall 2016.
  • Elected Fellow of the American Society of Mechanical Engineers, December, 2013.