Problem 1
At the start, two midpoints using successive predictions, and the endpoint.
Faculty use
Classical Fourth-Order Runge–Kutta
Reward correct mathematics, explicit units, conditions, and hypotheses, interpretation, and verification. Equivalent valid reasoning should receive credit.
Problem 2
O(h⁴).
Problem 3
Definitions should identify the equation type, dependent and independent variables, parameters, conditions, units or domain, and the hypotheses behind combining four slope samples to obtain fourth-order accuracy. Use the formulas k₁=f(t_n,y_n); y_{n+1}=y_n+h(k₁+2k₂+2k₃+k₄)/6.
Problem 4
A strong error analysis identifies the first step that violates classification, algebra, theorem hypotheses, units, initial/boundary data, or numerical assumptions; then repairs that step and re-verifies the final result.
Problem 5
Application responses vary. Require defined variables, a compatible differential-equation model connected to simulation, control, orbital motion, chemical kinetics, heat transfer, and computational engineering, a complete computation, interpretation, and limitations.
Problem 6
Accept two independent checks appropriate to the task: differentiation/substitution, initial or boundary conditions, dimensional analysis, phase-line or stability evidence, residuals, step refinement, conservation/energy checks, data comparison, or a second method.
Scoring guidance
Six problems × 10 points: 5 mathematical accuracy, 2 structure/justification, 2 verification/interpretation, 1 notation and communication.