Parameterization of Some Surfaces of Revolution Through Curvature-Varying Curves: a Computational Analysis
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Parametric Surfaces and 16.6 Their Areas Parametric Surfaces
Parametric Surfaces and 16.6 Their Areas Parametric Surfaces 2 Parametric Surfaces Similarly to describing a space curve by a vector function r(t) of a single parameter t, a surface can be expressed by a vector function r(u, v) of two parameters u and v. Suppose r(u, v) = x(u, v)i + y(u, v)j + z(u, v)k is a vector-valued function defined on a region D in the uv-plane. So x, y, and, z, the component functions of r, are functions of the two variables u and v with domain D. The set of all points (x, y, z) in R3 s.t. x = x(u, v), y = y(u, v), z = z(u, v) and (u, v) varies throughout D, is called a parametric surface S. Typical surfaces: Cylinders, spheres, quadric surfaces, etc. 3 Example 3 – Important From Book The vector equation of a plane through (x0, y0, z0) and containing vectors is rather 4 Example – Point on Surface? Does the point (2, 3, 3) lie on the given surface? How about (1, 2, 1)? 5 Example – Identify the Surface Identify the surface with the given vector equation. 6 Example – Identify the Surface Identify the surface with the given vector equation. 7 Example – Find a Parametric Equation The part of the hyperboloid –x2 – y2 + z = 1 that lies below the rectangle [–1, 1] X [–3, 3]. 8 Example – Find a Parametric Equation The part of the cylinder x2 + z2 = 1 that lies between the planes y = 1 and y = 3. 9 Example – Find a Parametric Equation Part of the plane z = 5 that lies inside the cylinder x2 + y2 = 16. -
Multivariable and Vector Calculus
Multivariable and Vector Calculus Lecture Notes for MATH 0200 (Spring 2015) Frederick Tsz-Ho Fong Department of Mathematics Brown University Contents 1 Three-Dimensional Space ....................................5 1.1 Rectangular Coordinates in R3 5 1.2 Dot Product7 1.3 Cross Product9 1.4 Lines and Planes 11 1.5 Parametric Curves 13 2 Partial Differentiations ....................................... 19 2.1 Functions of Several Variables 19 2.2 Partial Derivatives 22 2.3 Chain Rule 26 2.4 Directional Derivatives 30 2.5 Tangent Planes 34 2.6 Local Extrema 36 2.7 Lagrange’s Multiplier 41 2.8 Optimizations 46 3 Multiple Integrations ........................................ 49 3.1 Double Integrals in Rectangular Coordinates 49 3.2 Fubini’s Theorem for General Regions 53 3.3 Double Integrals in Polar Coordinates 57 3.4 Triple Integrals in Rectangular Coordinates 62 3.5 Triple Integrals in Cylindrical Coordinates 67 3.6 Triple Integrals in Spherical Coordinates 70 4 Vector Calculus ............................................ 75 4.1 Vector Fields on R2 and R3 75 4.2 Line Integrals of Vector Fields 83 4.3 Conservative Vector Fields 88 4.4 Green’s Theorem 98 4.5 Parametric Surfaces 105 4.6 Stokes’ Theorem 120 4.7 Divergence Theorem 127 5 Topics in Physics and Engineering .......................... 133 5.1 Coulomb’s Law 133 5.2 Introduction to Maxwell’s Equations 137 5.3 Heat Diffusion 141 5.4 Dirac Delta Functions 144 1 — Three-Dimensional Space 1.1 Rectangular Coordinates in R3 Throughout the course, we will use an ordered triple (x, y, z) to represent a point in the three dimensional space. -
Math 1300 Section 4.8: Parametric Equations A
MATH 1300 SECTION 4.8: PARAMETRIC EQUATIONS A parametric equation is a collection of equations x = x(t) y = y(t) that gives the variables x and y as functions of a parameter t. Any real number t then corresponds to a point in the xy-plane given by the coordi- nates (x(t); y(t)). If we think about the parameter t as time, then we can interpret t = 0 as the point where we start, and as t increases, the parametric equation traces out a curve in the plane, which we will call a parametric curve. (x(t); y(t)) • The result is that we can \draw" curves just like an Etch-a-sketch! animated parametric circle from wolfram Date: 11/06. 1 4.8 2 Let's consider an example. Suppose we have the following parametric equation: x = cos(t) y = sin(t) We know from the pythagorean theorem that this parametric equation satisfies the relation x2 + y2 = 1 , so we see that as t varies over the real numbers we will trace out the unit circle! Lets look at the curve that is drawn for 0 ≤ t ≤ π. Just picking a few values we can observe that this parametric equation parametrizes the upper semi-circle in a counter clockwise direction. (0; 1) • t x(t) y(t) 0 1 0 p p π 2 2 •(1; 0) 4 2 2 π 2 0 1 π -1 0 Looking at the curve traced out over any interval of time longer that 2π will indeed trace out the entire circle. -
Parametric Curves You Should Know
Parametric Curves You Should Know Straight Lines Let a and c be constants which are not both zero. Then the parametric equations determining the straight line passing through (b; d) with slope c=a (i.e., the line y − d = c=a(x − b)) are: x(t) = at + b ; −∞ < t < 1: y(t) = ct + d Note that when c = 0, the line is horizontal of the form y = d, and when a = 0, the line is vertical of the form x = b. 15 10 x(t)= 2t+ 3, y(t)=t+4 5 x(t)=3-2t, y(t)= 2t+1 �������� x(t)=t+ 2, y(t)=3- 3t x(t)= 3, y(t)=2+ 3t -10 -5 5 10 15 x(t)=2+3t, y(t)=3 -5 -10 Figure 1 A collection of lines whose parametric equations are given as above. Circles Let r > 0 and let x0 and y0 be real numbers. Then the parametric equations determining the circle of radius r centered at (x0; y0) are: x(t) = r cos t + x 0 ; 0 < t < 2π: (1) y(t) = r sin t + y0 To get a circular arc instead of the full circle, restrict the t-values in (1) to t1 < t < t2. 1 1 1 2 3 4 5 2 3 4 5 (3,-1) -1 -1 (3,-1) -2 -2 -3 -3 (a) 0 ≤ t ≤ 2π (b) π=4 ≤ t ≤ 7π=6 Figure 2 The circle x(t) = 2 cos t + 3, y(t) = 2 sin t − 1 and a circular arc thereof. Note that the center is at (3; 1). -
Surface Integrals
VECTOR CALCULUS 16.7 Surface Integrals In this section, we will learn about: Integration of different types of surfaces. PARAMETRIC SURFACES Suppose a surface S has a vector equation r(u, v) = x(u, v) i + y(u, v) j + z(u, v) k (u, v) D PARAMETRIC SURFACES •We first assume that the parameter domain D is a rectangle and we divide it into subrectangles Rij with dimensions ∆u and ∆v. •Then, the surface S is divided into corresponding patches Sij. •We evaluate f at a point Pij* in each patch, multiply by the area ∆Sij of the patch, and form the Riemann sum mn * f() Pij S ij ij11 SURFACE INTEGRAL Equation 1 Then, we take the limit as the number of patches increases and define the surface integral of f over the surface S as: mn * f( x , y , z ) dS lim f ( Pij ) S ij mn, S ij11 . Analogues to: The definition of a line integral (Definition 2 in Section 16.2);The definition of a double integral (Definition 5 in Section 15.1) . To evaluate the surface integral in Equation 1, we approximate the patch area ∆Sij by the area of an approximating parallelogram in the tangent plane. SURFACE INTEGRALS In our discussion of surface area in Section 16.6, we made the approximation ∆Sij ≈ |ru x rv| ∆u ∆v where: x y z x y z ruv i j k r i j k u u u v v v are the tangent vectors at a corner of Sij. SURFACE INTEGRALS Formula 2 If the components are continuous and ru and rv are nonzero and nonparallel in the interior of D, it can be shown from Definition 1—even when D is not a rectangle—that: fxyzdS(,,) f ((,))|r uv r r | dA uv SD SURFACE INTEGRALS This should be compared with the formula for a line integral: b fxyzds(,,) f (())|'()|rr t tdt Ca Observe also that: 1dS |rr | dA A ( S ) uv SD SURFACE INTEGRALS Example 1 Compute the surface integral x2 dS , where S is the unit sphere S x2 + y2 + z2 = 1. -
Calculus Terminology
AP Calculus BC Calculus Terminology Absolute Convergence Asymptote Continued Sum Absolute Maximum Average Rate of Change Continuous Function Absolute Minimum Average Value of a Function Continuously Differentiable Function Absolutely Convergent Axis of Rotation Converge Acceleration Boundary Value Problem Converge Absolutely Alternating Series Bounded Function Converge Conditionally Alternating Series Remainder Bounded Sequence Convergence Tests Alternating Series Test Bounds of Integration Convergent Sequence Analytic Methods Calculus Convergent Series Annulus Cartesian Form Critical Number Antiderivative of a Function Cavalieri’s Principle Critical Point Approximation by Differentials Center of Mass Formula Critical Value Arc Length of a Curve Centroid Curly d Area below a Curve Chain Rule Curve Area between Curves Comparison Test Curve Sketching Area of an Ellipse Concave Cusp Area of a Parabolic Segment Concave Down Cylindrical Shell Method Area under a Curve Concave Up Decreasing Function Area Using Parametric Equations Conditional Convergence Definite Integral Area Using Polar Coordinates Constant Term Definite Integral Rules Degenerate Divergent Series Function Operations Del Operator e Fundamental Theorem of Calculus Deleted Neighborhood Ellipsoid GLB Derivative End Behavior Global Maximum Derivative of a Power Series Essential Discontinuity Global Minimum Derivative Rules Explicit Differentiation Golden Spiral Difference Quotient Explicit Function Graphic Methods Differentiable Exponential Decay Greatest Lower Bound Differential -
16.6 Parametric Surfaces and Their Areas
CHAPTER 16. VECTOR CALCULUS 239 16.6 Parametric Surfaces and Their Areas Comments. On the next page we summarize some ways of looking at graphs in Calc I, Calc II, and Calc III, and pose a question about what comes next. 2 3 2 Definition. Let r : R ! R and let D ⊆ R . A parametric surface S is the set of all points hx; y; zi such that hx; y; zi = r(u; v) for some hu; vi 2 D. In other words, it's the set of points you get using x = some function of u; v y = some function of u; v z = some function of u; v Example 1. (a) Describe the surface z = −x2 − y2 + 2 over the region D : −1 ≤ x ≤ 1; −1 ≤ y ≤ 1 as a parametric surface. Graph it in MATLAB. (b) Describe the surface z = −x2 − y2 + 2 over the region D : x2 + y2 ≤ 1 as a parametric surface. Graph it in MATLAB. Solution: (a) In this case we \cheat": we already have z as a function of x and y, so anything we do to get rid of x and y will work x = u y = v z = −u2 − v2 + 2 −1 ≤ u ≤ 1; −1 ≤ v ≤ 1 [u,v]=meshgrid(linspace(-1,1,35)); x=u; y=v; z=2-u.^2-v.^2; surf(x,y,z) CHAPTER 16. VECTOR CALCULUS 240 How graphs look in different contexts: Pre-Calc, and Calc I graphs: Calc II parametric graphs: y = f(x) x = f(t), y = g(t) • 1 number gets plugged in (usually x) • 1 number gets plugged in (usually t) • 1 number comes out (usually y) • 2 numbers come out (x and y) • Graph is essentially one dimensional (if you zoom in enough it looks like a line, plus you only need • graph is essentially one dimensional (but we one number, x, to specify any location on the don't picture t at all) graph) • We need to picture the graph in two dimensional • We need to picture the graph in a two dimen- world. -
Polynomial Curves and Surfaces
Polynomial Curves and Surfaces Chandrajit Bajaj and Andrew Gillette September 8, 2010 Contents 1 What is an Algebraic Curve or Surface? 2 1.1 Algebraic Curves . .3 1.2 Algebraic Surfaces . .3 2 Singularities and Extreme Points 4 2.1 Singularities and Genus . .4 2.2 Parameterizing with a Pencil of Lines . .6 2.3 Parameterizing with a Pencil of Curves . .7 2.4 Algebraic Space Curves . .8 2.5 Faithful Parameterizations . .9 3 Triangulation and Display 10 4 Polynomial and Power Basis 10 5 Power Series and Puiseux Expansions 11 5.1 Weierstrass Factorization . 11 5.2 Hensel Lifting . 11 6 Derivatives, Tangents, Curvatures 12 6.1 Curvature Computations . 12 6.1.1 Curvature Formulas . 12 6.1.2 Derivation . 13 7 Converting Between Implicit and Parametric Forms 20 7.1 Parameterization of Curves . 21 7.1.1 Parameterizing with lines . 24 7.1.2 Parameterizing with Higher Degree Curves . 26 7.1.3 Parameterization of conic, cubic plane curves . 30 7.2 Parameterization of Algebraic Space Curves . 30 7.3 Automatic Parametrization of Degree 2 Curves and Surfaces . 33 7.3.1 Conics . 34 7.3.2 Rational Fields . 36 7.4 Automatic Parametrization of Degree 3 Curves and Surfaces . 37 7.4.1 Cubics . 38 7.4.2 Cubicoids . 40 7.5 Parameterizations of Real Cubic Surfaces . 42 7.5.1 Real and Rational Points on Cubic Surfaces . 44 7.5.2 Algebraic Reduction . 45 1 7.5.3 Parameterizations without Real Skew Lines . 49 7.5.4 Classification and Straight Lines from Parametric Equations . 52 7.5.5 Parameterization of general algebraic plane curves by A-splines . -
Lecture 1: Explicit, Implicit and Parametric Equations
4.0 3.5 f(x+h) 3.0 Q 2.5 2.0 Lecture 1: 1.5 Explicit, Implicit and 1.0 Parametric Equations 0.5 f(x) P -3.5 -3.0 -2.5 -2.0 -1.5 -1.0 -0.5 0.5 1.0 1.5 2.0 2.5 3.0 3.5 x x+h -0.5 -1.0 Chapter 1 – Functions and Equations Chapter 1: Functions and Equations LECTURE TOPIC 0 GEOMETRY EXPRESSIONS™ WARM-UP 1 EXPLICIT, IMPLICIT AND PARAMETRIC EQUATIONS 2 A SHORT ATLAS OF CURVES 3 SYSTEMS OF EQUATIONS 4 INVERTIBILITY, UNIQUENESS AND CLOSURE Lecture 1 – Explicit, Implicit and Parametric Equations 2 Learning Calculus with Geometry Expressions™ Calculus Inspiration Louis Eric Wasserman used a novel approach for attacking the Clay Math Prize of P vs. NP. He examined problem complexity. Louis calculated the least number of gates needed to compute explicit functions using only AND and OR, the basic atoms of computation. He produced a characterization of P, a class of problems that can be solved in by computer in polynomial time. He also likes ultimate Frisbee™. 3 Chapter 1 – Functions and Equations EXPLICIT FUNCTIONS Mathematicians like Louis use the term “explicit function” to express the idea that we have one dependent variable on the left-hand side of an equation, and all the independent variables and constants on the right-hand side of the equation. For example, the equation of a line is: Where m is the slope and b is the y-intercept. Explicit functions GENERATE y values from x values. -
Plotting Circles and Ellipses Parametrically Example 1: the Unit Circle
Lesson 1 Plotting Circles and Ellipses Parametrically Example 1: The Unit Circle Let's compare traditional and parametric equations for the unit circle : Traditional : Parametric : x22 y 1 x(t) cos(t) y(t) sin(t) P(t) cos(t),sin(t) t is called a parameter 0 t 2 You can see that the parametric equation satisfies the traditional equation by substituting one into the other: x22 y 1 (cos(t))22 (sin(t)) 1 11 Created by Christopher Grattoni. All rights reserved. Example 2: Circle of Radius r Let's compare traditional and parametric equations for a circle of radius r centeredTraditional at the : origin : Parametric : 2 2 2 x y r x(t) r cos(t) y(t) r sin(t) P(t) r cos(t),sin(t) 0 t 2 Orientation: Counterclockwise Think of this as dilating the unit circle by a factor of r. Created by Christopher Grattoni. All rights reserved. Example 3: Recentering the Circle Let's compare traditional and parametric equations for a circle of radius r centeredTraditional at (h,k) : : Parametric : 2 2 2 (x h) (y k) r x(t) r cos(t) h y(t) r sin(t) k P(t) r cos(t),sin(t) (h,k) 0 t 2 Think of this as dilating the unit circle by a factor of r and translating by the point (h,k). Let's add the orientation: Created by Christopher Grattoni. All rights reserved. Example 4: Ellipses Let's compare traditional and parametric equations for an ellipse centeredTraditional at (h,k) : : Parametric : 2 2 xh yk x(t) acos(t) h 1 ab y(t) bsin(t) k P(t) acos(t),bsin(t) (h,k) 0 t 2 Think of this as dilating the unit circle by a factor of "a" in the x-direction, a factor of "b" in the y-direction, and translated by the Created by Christopherpoint Grattoni. -
Surface Normals and Tangent Planes
Surface Normals and Tangent Planes Normal and Tangent Planes to Level Surfaces Because the equation of a plane requires a point and a normal vector to the plane, …nding the equation of a tangent plane to a surface at a given point requires the calculation of a surface normal vector. In this section, we explore the concept of a normal vector to a surface and its use in …nding equations of tangent planes. To begin with, a level surface U (x; y; z) = k is said to be smooth if the gradient U = Ux;Uy;Uz is continuous and non-zero at any point on the surface. Equivalently,r h we ofteni write U = Uxex + Uyey + Uzez r where ex = 1; 0; 0 ; ey = 0; 1; 0 ; and ez = 0; 0; 1 : Supposeh now thati r (t) =h x (ti) ; y (t) ; z (t) hlies oni a smooth surface U (x; y; z) = k: Applying the derivative withh respect to t toi both sides of the equation of the level surface yields dU d = k dt dt Since k is a constant, the chain rule implies that U v = 0 r where v = x0 (t) ; y0 (t) ; z0 (t) . However, v is tangent to the surface because it is tangenth to a curve on thei surface, which implies that U is orthogonal to each tangent vector v at a given point on the surface. r That is, U (p; q; r) at a given point (p; q; r) is normal to the tangent plane to r 1 the surface U(x; y; z) = k at the point (p; q; r). -
Surface Area of a Sphere in This Example We Will Complete the Calculation of the Area of a Surface of Rotation
Surface Area of a Sphere In this example we will complete the calculation of the area of a surface of rotation. If we’re going to go to the effort to complete the integral, the answer should be a nice one; one we can remember. It turns out that calculating the surface area of a sphere gives us just such an answer. We’ll think of our sphere as a surface of revolution formed by revolving a half circle of radius a about the x-axis. We’ll be integrating with respect to x, and we’ll let the bounds on our integral be x1 and x2 with −a ≤ x1 ≤ x2 ≤ a as sketched in Figure 1. x1 x2 Figure 1: Part of the surface of a sphere. Remember that in an earlier example we computed the length of an infinites imal segment of a circular arc of radius 1: r 1 ds = dx 1 − x2 In this example we let the radius equal a so that we can see how the surface area depends on the radius. Hence: p y = a2 − x2 −x y0 = p a2 − x2 r x2 ds = 1 + dx a2 − x2 r a2 − x2 + x2 = dx a2 − x2 r a2 = dx: 2 2 a − x The formula for the surface area indicated in Figure 1 is: Z x2 Area = 2πy ds x1 1 ds y z }| { x r Z 2 z }| { a2 p 2 2 = 2π a − x dx 2 2 x1 a − x Z x2 a p 2 2 = 2π a − x p dx 2 2 x1 a − x Z x2 = 2πa dx x1 = 2πa(x2 − x1): Special Cases When possible, we should test our results by plugging in values to see if our answer is reasonable.