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16 MULTIPLE INTEGRALS

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MULTIPLE INTEGRALS In this chapter, we extend the idea of a definite integral to double and triple integrals of functions of two or three variables.

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MULTIPLE INTEGRALS These ideas are then used to compute volumes, masses, and centroids of more general regions than we were able to consider in Chapters 6 and 8.

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MULTIPLE INTEGRALS We also use double integrals to calculate probabilities when two random variables are involved.

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MULTIPLE INTEGRALS We will see that polar coordinates are useful in computing double integrals over some types of regions.

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MULTIPLE INTEGRALS Similarly, we will introduce two coordinate systems in three-dimensional space that greatly simplify computing of triple integrals over certain commonly occurring solid regions. Cylindrical coordinates Spherical coordinates

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**Double Integrals over Rectangles**

MULTIPLE INTEGRALS 16.1 Double Integrals over Rectangles In this section, we will learn about: Double integrals and using them to find volumes and average values.

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**DOUBLE INTEGRALS OVER RECTANGLES**

Just as our attempt to solve the area problem led to the definition of a definite integral, we now seek to find the volume of a solid. In the process, we arrive at the definition of a double integral.

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**DEFINITE INTEGRAL—REVIEW**

First, let’s recall the basic facts concerning definite integrals of functions of a single variable.

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**DEFINITE INTEGRAL—REVIEW**

If f(x) is defined for a ≤ x ≤ b, we start by dividing the interval [a, b] into n subintervals [xi–1, xi] of equal width ∆x = (b – a)/n. We choose sample points xi* in these subintervals.

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**DEFINITE INTEGRAL—REVIEW**

Equation 1 Then, we form the Riemann sum

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**DEFINITE INTEGRAL—REVIEW**

Equation 2 Then, we take the limit of such sums as n → ∞ to obtain the definite integral of f from a to b:

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**DEFINITE INTEGRAL—REVIEW**

In the special case where f(x) ≥ 0, the Riemann sum can be interpreted as the sum of the areas of the approximating rectangles. Fig , p. 987

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**DEFINITE INTEGRAL—REVIEW**

Then, represents the area under the curve y = f(x) from a to b. Fig , p. 987

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**and we first suppose that f(x, y) ≥ 0.**

VOLUMES In a similar manner, we consider a function f of two variables defined on a closed rectangle R = [a, b] x [c, d] = {(x, y) € R2 | a ≤ x ≤ b, c ≤ y ≤ d and we first suppose that f(x, y) ≥ 0. The graph of f is a surface with equation z = f(x, y).

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**S = {(x, y, z) R3 | 0 ≤ z ≤ f(x, y), (x, y) R}**

VOLUMES Let S be the solid that lies above R and under the graph of f, that is, S = {(x, y, z) R3 | 0 ≤ z ≤ f(x, y), (x, y) R} Our goal is to find the volume of S. Fig , p. 987

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**The first step is to divide the rectangle R into subrectangles.**

VOLUMES The first step is to divide the rectangle R into subrectangles. We divide the interval [a, b] into m subintervals [xi–1, xi] of equal width ∆x = (b – a)/m. Then, we divide [c, d] into n subintervals [yj–1, yj] of equal width ∆y = (d – c)/n.

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VOLUMES Next, we draw lines parallel to the coordinate axes through the endpoints of these subintervals. Fig , p. 988

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VOLUMES Thus, we form the subrectangles Rij = [xi–1, xi] x [yj–1, yj] = {(x, y) | xi–1 ≤ x ≤ xi, yj–1 ≤ y ≤ yj} each with area ∆A = ∆x ∆y Fig , p. 988

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**Let’s choose a sample point (xij*, yij*) in each Rij.**

VOLUMES Let’s choose a sample point (xij*, yij*) in each Rij. Fig , p. 988

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VOLUMES Then, we can approximate the part of S that lies above each Rij by a thin rectangular box (or “column”) with: Base Rij Height f (xij*, yij*) Fig , p. 988

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**Compare the figure with the earlier one.**

VOLUMES Compare the figure with the earlier one. Fig , p. 987 Fig , p. 988

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VOLUMES The volume of this box is the height of the box times the area of the base rectangle: f(xij *, yij *) ∆A Fig , p. 988

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VOLUMES We follow this procedure for all the rectangles and add the volumes of the corresponding boxes.

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**Thus, we get an approximation to the total volume of S:**

VOLUMES Equation 3 Thus, we get an approximation to the total volume of S: Fig , p. 988

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**This double sum means that:**

VOLUMES This double sum means that: For each subrectangle, we evaluate f at the chosen point and multiply by the area of the subrectangle. Then, we add the results.

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**So, we would expect that:**

VOLUMES Equation 4 Our intuition tells us that the approximation given in Equation 3 becomes better as m and n become larger. So, we would expect that:

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VOLUMES We use the expression in Equation 4 to define the volume of the solid S that lies under the graph of f and above the rectangle R. It can be shown that this definition is consistent with our formula for volume in Section 6.2

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VOLUMES Limits of the type that appear in Equation 4 occur frequently—not just in finding volumes but in a variety of other situations as well—even when f is not a positive function. So, we make the following definition.

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**The double integral of f over the rectangle R is:**

Definition 5 The double integral of f over the rectangle R is: if this limit exists.

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DOUBLE INTEGRAL The precise meaning of the limit in Definition 5 is that, for every number ε > 0, there is an integer N such that for: All integers m and n greater than N Any choice of sample points (xij*, yij*) in Rij*

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**A function f is called integrable if the limit in Definition 5 exists.**

INTEGRABLE FUNCTION A function f is called integrable if the limit in Definition 5 exists. It is shown in courses on advanced calculus that all continuous functions are integrable. In fact, the double integral of f exists provided that f is “not too discontinuous.”

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INTEGRABLE FUNCTION In particular, if f is bounded [that is, there is a constant M such that |f(x, y)| ≤ for all (x, y) in R], and f is continuous there, except on a finite number of smooth curves, then f is integrable over R.

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DOUBLE INTEGRAL The sample point (xij*, yij*) can be chosen to be any point in the subrectangle Rij*.

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DOUBLE INTEGRAL However, suppose we choose it to be the upper right-hand corner of Rij [namely (xi, yj)]. Fig , p. 988

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**Then, the expression for the double integral looks simpler:**

Equation 6 Then, the expression for the double integral looks simpler:

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DOUBLE INTEGRAL By comparing Definitions 4 and 5, we see that a volume can be written as a double integral, as follows.

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DOUBLE INTEGRAL If f(x, y) ≥ 0, then the volume V of the solid that lies above the rectangle R and below the surface z = f(x, y) is:

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**is called a double Riemann sum.**

DOUBLE REIMANN SUM The sum in Definition 5 is called a double Riemann sum. It is used as an approximation to the value of the double integral. Notice how similar it is to the Riemann sum in Equation 1 for a function of a single variable.

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**If f happens to be a positive function, the double Riemann sum:**

DOUBLE REIMANN SUM If f happens to be a positive function, the double Riemann sum: Represents the sum of volumes of columns, as shown. Is an approximation to the volume under the graph of f and above the rectangle R. Fig , p. 988

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DOUBLE INTEGRALS Example 1 Estimate the volume of the solid that lies above the square R = [0, 2] x [0, 2] and below the elliptic paraboloid z = 16 – x2 – 2y2. Divide R into four equal squares and choose the sample point to be the upper right corner of each square Rij. Sketch the solid and the approximating rectangular boxes.

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**The squares are shown here.**

DOUBLE INTEGRALS Example 1 The squares are shown here. The paraboloid is the graph of f(x, y) = 16 – x2 – 2y2 The area of each square is 1. Fig , p. 990

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**Approximating the volume by the Riemann sum with m = n = 2, we have:**

DOUBLE INTEGRALS Example 1 Approximating the volume by the Riemann sum with m = n = 2, we have:

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**That is the volume of the approximating rectangular boxes shown here.**

DOUBLE INTEGRALS Example 1 That is the volume of the approximating rectangular boxes shown here. Fig , p. 990

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DOUBLE INTEGRALS We get better approximations to the volume in Example 1 if we increase the number of squares.

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**The figure shows how, when we use 16, 64, and 256 squares,**

DOUBLE INTEGRALS The figure shows how, when we use 16, 64, and 256 squares, The columns start to look more like the actual solid. The corresponding approximations get more accurate. Fig , p. 990

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**In Section 16.2, we will be able to show that the exact volume is 48.**

DOUBLE INTEGRALS In Section 16.2, we will be able to show that the exact volume is 48. Fig , p. 990

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**If R = {(x, y)| –1 ≤ x ≤ 1, –2 ≤ y ≤ 2}, evaluate the integral**

DOUBLE INTEGRALS Example 2 If R = {(x, y)| –1 ≤ x ≤ 1, –2 ≤ y ≤ 2}, evaluate the integral It would be very difficult to evaluate this integral directly from Definition 5. However, since , we can compute it by interpreting it as a volume.

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DOUBLE INTEGRALS Example 2 If then x2 + z2 = z ≥ 0

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DOUBLE INTEGRALS Example 2 So, the given double integral represents the volume of the solid S that lies: Below the circular cylinder x2 + z2 = 1 Above the rectangle R Fig , p. 991

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DOUBLE INTEGRALS Example 2 The volume of S is the area of a semicircle with radius 1 times the length of the cylinder. Fig , p. 991

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**Here, we consider only the Midpoint Rule for double integrals.**

The methods that we used for approximating single integrals (Midpoint Rule, Trapezoidal Rule, Simpson’s Rule) all have counterparts for double integrals. Here, we consider only the Midpoint Rule for double integrals.

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THE MIDPOINT RULE This means that we use a double Riemann sum to approximate the double integral, where the sample point (xij*, yij*) in Rij is chosen to be the center of Rij. That is, is the midpoint of [xi–1, xi] and is the midpoint of [yj–1, yj] .

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**MIDPOINT RULE FOR DOUBLE INTEGRALS**

where: is the midpoint of [xi–1, xi] is the midpoint of [yj–1, yj].

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MIDPOINT RULE Example 3 Use the Midpoint Rule with m = n = 2 to estimate the value of the integral where R = {(x, y) | 0 ≤ x ≤ 2, 1 ≤ y ≤ 2}

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MIDPOINT RULE Example 3 In using the Midpoint Rule with m = n = 2, we evaluate f(x, y) = x – 3y2 at the centers of the four subrectangles shown here. Fig , p. 991

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MIDPOINT RULE Example 3 Thus, The area of each subrectangle is ∆A = ½.

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MIDPOINT RULE Example 3 Thus,

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MIDPOINT RULE Example 3

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NOTE In Section 15.2, we will develop an efficient method for computing double integrals. Then, we will see that the exact value of the double integral in Example 3 is –12.

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NOTE Remember that the interpretation of a double integral as a volume is valid only when the integrand f is a positive function. The integrand in Example 3 is not a positive function. So, its integral is not a volume.

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NOTE In Examples 2 and 3 in Section 15.2, we will discuss how to interpret integrals of functions that are not always positive in terms of volumes.

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NOTE Suppose we keep dividing each of these subrectangles into four smaller ones with similar shape. Fig , p. 991

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**Then, we get these Midpoint Rule approximations.**

NOTE Then, we get these Midpoint Rule approximations. Notice how these approximations approach the exact value of the double integral, –12. p. 992

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AVERAGE VALUE Recall from Section 6.5 that the average value of a function f of one variable defined on an interval [a, b] is:

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**where A(R) is the area of R.**

AVERAGE VALUE Similarly, we define the average value of a function f of two variables defined on a rectangle R to be: where A(R) is the area of R.

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**If f(x, y) ≥ 0, the equation says that:**

AVERAGE VALUE If f(x, y) ≥ 0, the equation says that: The box with base R and height fave has the same volume as the solid that lies under the graph of f.

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AVERAGE VALUE Suppose z = f(x, y) describes a mountainous region and you chop off the tops of the mountains at height fave . Then, you can use them to fill in the valleys so that the region becomes completely flat. Fig , p. 992

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AVERAGE VALUE Example 4 The contour map shows the snowfall, in inches, that fell on the state of Colorado on December 20 and 21, Fig , p. 992

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AVERAGE VALUE Example 4 The state is in the shape of a rectangle that measures 388 mi west to east and 276 mi south to north. Fig , p. 992

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AVERAGE VALUE Example 4 Use the map to estimate the average snowfall for the entire state on those days. Fig , p. 992

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**Let’s place the origin at the southwest corner of the state.**

AVERAGE VALUE Example 4 Let’s place the origin at the southwest corner of the state. Fig , p. 992

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AVERAGE VALUE Example 4 Then, 0 ≤ x ≤ 388, 0 ≤ y ≤ 276, and f(x, y) is the snowfall, in inches, at a location x miles to the east and y miles to the north of the origin.

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AVERAGE VALUE Example 4 If R is the rectangle that represents Colorado, the average snowfall for the state on December 20–21 was: where A(R) = 388 · 276

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AVERAGE VALUE Example 4 To estimate the value of this double integral, let’s use the Midpoint Rule with m = n = 4.

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**That is, we divide R into 16 subrectangles of equal size.**

AVERAGE VALUE That is, we divide R into 16 subrectangles of equal size. Fig , p. 993

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**The area of each subrectangle is: ∆A = (1/16) (388)(276) = 6693 mi2**

AVERAGE VALUE The area of each subrectangle is: ∆A = (1/16) (388)(276) = 6693 mi2

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AVERAGE VALUE Using the contour map to estimate the value of f at the center of each subrectangle, we get:

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AVERAGE VALUE Therefore, On December 20–21, 2006, Colorado received an average of approximately 13 inches of snow.

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**PROPERTIES OF DOUBLE INTEGRALS**

We now list three properties of double integrals that can be proved in the same manner as in Section 5.2 We assume that all the integrals exist.

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**These properties are referred to as the linearity of the integral.**

where c is a constant

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**If f(x, y) ≥ g(x, y) for all (x, y) in R, then**

PROPERTY 9 If f(x, y) ≥ g(x, y) for all (x, y) in R, then

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