Date of Award
Spring 2024
Document Type
Dissertation
Degree Name
Doctor of Philosophy (PhD)
Department
Mechanical & Aerospace Engineering
Program/Concentration
Aerospace Engineering
Committee Director
Gene Hou
Committee Member
Brett Newman
Committee Member
Drew Landman
Committee Member
Hong Yang
Abstract
Characterizing the behavior of dynamic systems requires the inclusion of initial conditions to propagate behavior forward in time. More realistic representations of system behavior quantify uncertainty about the initial conditions to assess sensitivity, reliability, and other stochastic response parameters. In many engineering applications, the uncertain initial conditions may be unknown given a desired response. This research applies the Fokker-Planck equation to reversible dynamic systems of select multi-dimensional nonlinear differential equations as a means for predicting the uncertainty about initial conditions. An alternating directions implicit numerical scheme is used to numerically solve the Fokker-Planck equation for both forward and reversed equations of motion. Initial conditions are predicted for a linear oscillating system, nonlinear trim solution, and atmospheric reentry equations. A use case is presented where the initial atmospheric entry conditions are predicted for a Mars reentry vehicle given a landing zone and parachute deployment response conditions. Monte Carlo simulations are also implemented to verify the outputs of the numerical scheme. Additional verification is conducted by comparing forward and reverse transient results of each problem set. It is shown that the initial conditions can be adequately predicted using the presented methodology. Computational resources quickly become a limitation as additional dimensions of variability are added to the problem.
Rights
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DOI
10.25777/8m4n-0771
ISBN
9798382770406
Recommended Citation
Newhart, Troy S..
"Application of the Fokker-Planck Equation for Quantifying Initial Condition Uncertainty of Reversible Dynamic Systems"
(2024). Doctor of Philosophy (PhD), Dissertation, Mechanical & Aerospace Engineering, Old Dominion University, DOI: 10.25777/8m4n-0771
https://digitalcommons.odu.edu/mae_etds/377
ORCID
0000-0001-7535-280X
Included in
Aerospace Engineering Commons, Mechanical Engineering Commons, Statistical, Nonlinear, and Soft Matter Physics Commons