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Solving Nonlinear First-order Ordinary Differential Equations (ODEs) using
Backward Differentiation Formulae (BDF).
Noramira Binti Mohd Ezi
Supervisor: Dr. Loy Kak Choon
Bachelor of Science (Computational Mathematics)
School of Informatics and Applied Mathematics
Backward Differentiation Formulae (BDF) methods are categorised as linear multistep
methods. BDF methods are fully implicit, thereby increasing the overall stability of the
schemes. Higher-order BDF methods are popular used to solve stiff nonlinear first-order
ODEs without relying on a very small step size. While gaining better accuracy by using
test problems, for fisrt, second and third order BDF methods are reproduce the order of
convergence using Octave programming language. BDF methods with higher-order of
accuracy are exceptionally accurate but are less efficient than explicit and semi-implicit
methods since they require Newton’s method to be computed at each step size. The
significance of output from this research project is a proper understanding of BDF
methods and to know how to compute first-order nonlinear ODEs especially involving stiff
nonlinear ODEs problems.
968 | UMT UNDERGRADUATE RESEARCH DAY 2018