22.17 Recall that the velocity of the freefalling parachutist with linear drag can be computed analytically as gm v(t) = (1-e(c/m)r) C where v(t) = velocity (m/s), t = time (s), g = 9.81 m/s², m = mass (kg), c = linear drag coefficient (kg/s). Use Romberg integration to compute how far the jumper travels during the first 8 seconds of free fall given m = 80 kg and c = 10 kg/s. Compute the answer to ε₁ = 1%. Problem 22.17. Start with trapezoid multform= 1, 2, and 4. Use Romberg Integration to improve the approximation first from O(h²) to O(h²), then from O(h²) to O(hº).

22.17 Recall that the velocity of the freefalling parachutist with linear drag can be computed analytically as gm v(t) = (1-e(c/m)r) C where v(t) = velocity (m/s), t = time (s), g = 9.81 m/s², m = mass (kg), c = linear drag coefficient (kg/s). Use Romberg integration to compute how far the jumper travels during the first 8 seconds of free fall given m = 80 kg and c = 10 kg/s. Compute the answer to ε₁ = 1%. Problem 22.17. Start with trapezoid multform= 1, 2, and 4. Use Romberg Integration to improve the approximation first from O(h²) to O(h²), then from O(h²) to O(hº).

Elements Of Electromagnetics

7th Edition

ISBN:9780190698614

Author:Sadiku, Matthew N. O.

Publisher:Sadiku, Matthew N. O.

ChapterMA: Math Assessment

Section: Chapter Questions

Problem 1.1MA

See similar textbooks

Similar questions

The 2nd order ODE given below models the vertical fall of on Object under the influence of gravity and air friction md²y acceleration -mg + (1/2 Co A Pair) (dy) ² Forcing due logranty Forcing due to air friction
Use bisection to determine the drag coefficient needed so that an 80-kg parachutist has a velocity of 36 m/s after 4 s of free fall. Note: The acceleration of gravity is 9.81 m/s2 . Start with initial guesses of xl = 0.1 and xu = 0.2 and iterate until the approximate relative error falls below 2%.
This for Matlab Please modify the script bisect.m to report/create the iteration table.
For all the following problems, 5. a) b) You need to show at least 3 iterations calculated manually with all steps. You do not need to include the M.files for the bisection method (bisect.m) and for false position (falspos.m). You must, however, show the command lines for the given functions with their variables and other parameters. Fanning friction factor For fluid flow in pipes, friction is described by a dimensionless number, the Fanning friction factor f. The Fanning friction factor is dependent on a number of parameters related to the size of the pipe and the fluid, which can all be represented by another dimensionless quantity, the Reynolds number Re. A formula that predicts ƒ given Re is the von Karman equation: 4log₁0 (Re√) - 0.4 = Typical values for the Reynolds number for turbulent flow are 10,000 to 500,000 and for the Fanning friction factor are 0.001 to 0.01. (a) Develop a function that uses bisection to solve for fgiven a user-supplied value of Re between 500 and…
mathforadmi..2dff1dd723 PTU Kadoorie sygini 1930 Technical Department of Applied Mathematics Second Semester 2020/2021 Math for Administration Assignment 2 Question 1 For the function: y = 0.01x- 0.001x² Find the zeros, the vertex and the optimum value (max. or min.) Question 2 Suppose a company has fixed costs of $300 and variable 3 costs of x + 1460 dollars per unit, 4 where x is the total number of units produced. Suppose further that the selling price of its product is 1500 X- ♡ lar Fine break-even points. init. II جامعة Palestine ||
I am trying to compute the probability of collision with the monte carlo method in MATLAB. But I get an error in teh following code. The error is the matrix P_01 must be semi definete and P_02 must be symmetric. How should I fix this problem? % Initial Mean and Covariance mu_01 = [153446.180; 41874155.872; 0; 3066.875; -11.374; 0] / 1000; P_01 = [6494.080 -376.139 0 0.0160 -0.494 0; -376.139 22.560 0 -9.883e-4 0.0286 0; 0 0 1.205 0 0 -6.071e-5; 0.0160 -9.883e-4 0 4.437e-8 -1.212e-6 0; -0.494 0.0286 0 -1.212e-6 3.762e-5 0; 0 0 -6.071e-5 0 0 3.390e-9] * 1e-6; mu_02 = [153446.679; 41874156.372; 5.000; 3066.865; -11.374; -1.358e-6] / 1000; P_02 = [6494.224 -376.156 -4.492e-5 0.0160 -0.494 -5.902e-8; -376.156 22.561 2.550e-6 -9.885e-3 0.0286 3.419e-9; -4.492e-5 2.550e-6 1.205 -1.180e-10 3.419e-9 -6.072e-5; 0.0160 -9.883e-3 -1.180e-10 4.438e-8 -1.212e-6 -1.448e-13; -0.494 0.0286 3.419e-9 -1.212e-6 3.762e-5 4.492e-12; -5.902e-8 3.419e-9 -6.072e-5 -1.448e-13 4.492e-12 3.392e-9] * 1e-6;…
look at the graph wich presents F vs x graph ... Q : Determine the compression of the spring from the change in position of the cart+block in Graph ? please tell me the steps how can I find compression of the spring from the change in position of the cart+block
An object is shot upward from the ground with an initial velocity of 640 ft/sec, and experiencés a constant deceleration of 32 ft/sec² due to gravity as well as a deceleration of (v(t) / 10) ft/sec due to air resistance, where v(t) is the object's velocity in ft/sec. (a) Set up and solve an initial-value problem to determine the object's velocity v(t) at time t. (b) At what time does the object reach its highest point?
a) b) c) Use composite Simpson's rule to estimate xe*dx with n=4. Subsequently, find the absolute error. dy dx Given 3y + 2x, where y(0) = 1 and h = 0.2. Approximate the solution for the differential equation for one iteration only by using Runge Kutta method of order two. Set up the Gauss-Siedel iterative equations the following linear system: 6x₁-3x₂ = 2 -x₁ + 3x₂ + x3 =1 x₂ + 4x₂ = 3 (Do not solve)
The figure shows a plot of potential energy U versus position x of a 0.270 kg particle that can travel only along an x axis under the Influence of a conservative force. The graph has these values: UA9.00 ). Uc 20.0 J and Ug 24.0J. The particle is released at the point where Uforms a "potential hill" of "height" Ua 12.0J. with kinetic energy 7.50 J.What is the speed of the particle at la) -3.50m and (b)x - 6.50 m? What is the position of the turning paint on (c) the right side and (d) the left side?
Q1: The number of bacterial cells (P) in a given reactor is related to time in days (t) as described by the following mathematical model: dp dt 0.0000007 P², If at initial time (P = 106). Determine the number of cells when (t 2days) using the fourth order Runge-Kutta method and at time increment of (1 day). = = 0.3 P 1
I am computing the probablility of collision with the Monte Carlo method in MATLAB. The following is my code for it. The results don't seem to be accurate. Is there something wrong with my code? Also, it takes more than 5 min to run this code. Can you tell me why? %Initial Mean and Covariance mu_01 = [153446.180; 41874155.872;0;3066.875;-11.374;0]/1000; P_01 = [6494.080 -376.139 0 0.0160 -0.494 0; -376.139 22.560 0 -9.883e-4 0.0286 0; 0 0 1.205 0 0 -6.071e-5; 0.0160 -9.883e-4 0 4.437e-8 -1.212e-6 0; -0.494 0.0286 0 -1.212e-6 3.762e-5 0; 0 0 -6.071e-5 0 0 3.390e-9]*1e-6; mu_02 = [153446.679; 41874156.372;5.000;3066.865;-11.374;-1.358e-6]/1000; P_02 = [6494.224 -376.156 -4.492e-5 0.0160 -0.494 -5.902e-8; -376.156 22.561 2.550e-6 -9.885e-3 0.0286 3.419e-9; -4.492e-5 2.550e-6 1.205 -1.180e-10 3.419e-9 -6.072e-5; 0.0160 -9.883e-3 -1.180e-10 4.438e-8 -1.212e-6 -1.448e-13; -0.494 0.0286 3.419e-9 -1.212e-6 3.762e-5 4.492e-12; -5.902e-8 3.419e-9 -6.072e-5 -1.448e-13 4.492e-12 3.392e-9]*1e-6;…