Chapter 1: Q19E (page 1)
In Problem 19, solve the given initial value problem
Short Answer
The solution is C
Chapter 1: Q19E (page 1)
In Problem 19, solve the given initial value problem
The solution is C
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Get started for freeOscillations and Nonlinear Equations. For the initial value problem using the vectorized Runge–Kutta algorithm with h = 0.02 to illustrate that as t increases from 0 to 20, the solution x exhibits damped oscillations when , whereas exhibits expanding oscillations when .
The motion of a set of particles moving along the x‑axis is governed by the differential equation where denotes the position at time t of the particle.
⦁ If a particle is located at when , what is its velocity at this time?
⦁ Show that the acceleration of a particle is given by
⦁ If a particle is located at when , can it reach the location at any later time?
[Hint: ]
Determine which values of m the functionis a solution to the given equation.
(a)
(b)
Mixing.Suppose a brine containing 0.2 kg of salt per liter runs into a tank initially filled with 500 L of water containing 5 kg of salt. The brine enters the tank at a rate of 5 L/min. The mixture, kept uniform by stirring, is flowing out at the rate of 5 L/min (see Figure 2.6).
(a)Find the concentration, in kilograms per liter, of salt in the tank after 10 min. [Hint:LetAdenote the number of kilograms of salt in the tank attminutes after the process begins and use the fact that
rate of increase inA=rate of input- rate of exit.
A further discussion of mixing problems is given in Section 3.2.]
(b)After 10 min, a leak develops in the tank and an additional liter per minute of mixture flows out of the tank (see Figure 2.7). What will be the concentration, in kilograms per liter, of salt in the tank 20 min after the leak develops? [Hint:Use the method discussed in Problems 31 and 32.]
In Problems 14–24, you will need a computer and a programmed version of the vectorized classical fourth-order Runge–Kutta algorithm. (At the instructor’s discretion, other algorithms may be used.)†
Using the vectorized Runge–Kutta algorithm, approximate the solution to the initial value problem at . Starting with , continue halving the step size until two successive approximations of both anddiffer by at most 0.1.
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