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04-BS-5 · May 2018

Question 5 of 7: Romberg Integration of Tabulated Data

Nivaar worked solution (AI-drafted; not reviewed by a licensed engineer)

Notes on this paper

National Examinations, May 2018 — 04-BS-5 Advanced Mathematics, 3 hours, closed book (approved Casio/Sharp calculator and one double-sided aid sheet permitted). Any five of the seven questions constitute a complete paper and all questions are of equal value; all seven are answered below as a full study resource.

Reference texts: Kreyszig, Advanced Engineering Mathematics, 10th ed. (Wiley) — Ch. 5 (Series Solutions of ODEs about an ordinary point), Ch. 11 (Fourier Series, Fourier Integrals and Transforms), Ch. 19 (Numerics in General: interpolation, numerical differentiation, Romberg integration, iterative equation solving), Ch. 20 (Numeric Linear Algebra: Cholesky/LU factorization). Supporting: Chapra & Canale, Numerical Methods for Engineers, 7th ed. — Ch. 5–6 (bracketing and open root-finding methods), Ch. 18 (interpolation), Ch. 22 (Romberg integration); Strang, Introduction to Linear Algebra, 6th ed. — Ch. 2 (Cholesky/LU factorization).

Question 5: Romberg Integration of Tabulated Data (20 marks)

Question text not reproduced: the examination questions are © Engineers and Geoscientists BC. Open the official past paper (linked at the top of this page) to read the question, then follow the worked solution below.

Given. Nine tabulated points spanning $x=-2$ to $x=2$ at uniform step $h=0.5$.

Find. The Romberg estimate $R(4,4)$ of $\displaystyle\int_{-2}^{2}y\,dx$.

Approach. Build trapezoidal estimates $R(k,1)$ for step sizes $H=4,2,1,0.5$ by sub-sampling the table (using every 8th, 4th, 2nd, and every point respectively), then Richardson-extrapolate the triangular array using the recursion.

  1. Base trapezoidal estimates. $R(1,1)$ uses only the two endpoints ($H_1=4$); $R(2,1)$ adds the midpoint ($H_2=2$, nodes $-2,0,2$); $R(3,1)$ uses every second table point ($H_3=1$, nodes $-2,-1,0,1,2$); $R(4,1)$ uses the full table ($H_4=0.5$): $$R(1,1)=\dfrac{4}{2}[10.0+90.0]=\boxed{200}$$ $$R(2,1)=\dfrac{2}{2}[10.0+2(80.0)+90.0]=\boxed{260}$$ $$R(3,1)=\dfrac{1}{2}[10.0+2(70.0+80.0+60.0)+90.0]=\boxed{260}$$ $$R(4,1)=\dfrac{0.5}{2}[10.0+2(63.75+70.0+86.25+80.0+68.75+60.0+61.25)+90.0]=\boxed{270}$$
  2. Richardson-extrapolate column 2 ($j=2$, kills the $O(H^2)$ error). $R(k,2)=R(k,1)+\dfrac{R(k,1)-R(k-1,1)}{3}$: $$R(2,2)=260+\dfrac{260-200}{3}=\boxed{280},\quad R(3,2)=260+\dfrac{260-260}{3}=260,\quad R(4,2)=270+\dfrac{270-260}{3}=273.\overline3$$
  3. Extrapolate column 3 ($j=3$). $R(k,3)=R(k,2)+\dfrac{R(k,2)-R(k-1,2)}{15}$: $$R(3,3)=260+\dfrac{260-280}{15}=258.\overline6,\qquad R(4,3)=273.\overline3+\dfrac{273.\overline3-260}{15}=274.2\overline2$$
  4. Extrapolate column 4 ($j=4$, the final answer). $R(4,4)=R(4,3)+\dfrac{R(4,3)-R(3,3)}{63}=274.2\overline2+\dfrac{274.2\overline2-258.\overline6}{63}$ $$\boxed{R(4,4)=274.4691\ (=22232/81)}$$
$k\backslash j$1234
1200.0000
2260.0000280.0000
3260.0000260.0000258.6667
4270.0000273.3333274.2222274.4691