Pregunta

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**(1 point)**
Evaluate the surface integral:
\[
\iint_S (-2yj + zk) \cdot dS
\]

Where \( S \) consists of the paraboloid \( y = x^2 + z^2, \, 0 \leq y \leq 1 \) and the disk \( x^2 + z^2 \leq 1, \, y = 1 \), and has outward orientation.

Consider splitting the surface into its parts \( S = S_1 \cup S_2 \), where \( S_1 \) is the paraboloid and \( S_2 \) is the disk. Then we have:
\[
\iint_S \mathbf{F} \cdot dS = \iint_{S_1} \mathbf{F} \cdot dS_1 + \iint_{S_2} \mathbf{F} \cdot dS_2
\]

- \( S_1 \) can be parametrized by \( \mathbf{r}_1(s, t) = \langle s \cos(t), \, \Sigma, \, \Sigma \rangle \)
- \( S_2 \) can be parametrized by \( \mathbf{r}_2(s, t) = \langle s \cos(t), \, 1, \, \Sigma \rangle \)

\[
\iint_S (-2yj + zk) \cdot dS = \int_{t_1}^{t_2} \int_{s_1}^{s_2} \Sigma \, ds \, dt + \int_{t_1}^{t_2} \int_{s_1}^{s_2} \Sigma \, ds \, dt
\]

(Evaluate \( S_1 \) for the first blank and \( S_2 \) for the second blank)

Where:
- \( t_1 = \Sigma, \, t_2 = \Sigma \)
- \( s_1 = \Sigma, \, s_2 = \Sigma \)

Evaluate:
\[
\iint_S (-2yj + zk) \cdot dS = \Sigma + \Sigma
\]

(Evaluate \( S_1 \) for the first blank and \( S_2 \) for the second blank)

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Solve the question by typing the followings: The solution contains atleast two steps. Write the subject or sub-subject. In step 1: What is given, what do we need to find out, explanation part (Define/concept used, formula used), Step-by-step solution. In other steps: Continue the step-by-step solution by giving heading what now we are going to calculate in this step. (In brief)
Final answer in sentence.

Pensamiento

Investigating the task

The user needs help solving a problem with a specific format: identifying the subject, explaining concepts, using formulas, and providing a step-by-step solution with a final answer in a sentence.

Breaking down the surface integral

I’m splitting SS into S1S_1 (paraboloid) and S2S_2 (disk) to simplify the outward-oriented surface integral.

Parametrizing and integrating

I’m working through parametrizing surfaces S1S_1 and S2S_2, then evaluating the integrals by substituting the missing parts in the given expression.

Formulating the solution

I’m developing the final evaluation by addressing S1 and S2. The task involves breaking down the solution into defined steps, covering concepts, formulas, and calculations, leading to a comprehensive final answer.

Understanding the surface

OK, let me see. We're working with a vector field F=2yj+zk\mathbf{F} = -2y \mathbf{j} + z \mathbf{k}. The surface SS includes a paraboloid S1S_1 and a disk S2S_2 at y=1y = 1, aiming to evaluate the integral SFdS\iint_S \mathbf{F} \cdot d\mathbf{S} by splitting it into integrals over S1S_1 and S2S_2.

Identifying parametrizations

OK, let’s break this down: I need to parametrize S1S_1 and S2S_2 to find dS1d\mathbf{S}_1 and dS2d\mathbf{S}_2, then calculate their dot products and integrals.

Mapping the integration

I’m thinking through the vector field applied to surfaces S1S_1 and S2S_2. First, parametrize and find dSd\mathbf{S} for each surface segment.

Parametrizing the paraboloid

OK, let me see. I’m parametrizing the paraboloid S1S_1 with cylindrical coordinates. The radial coordinate ss and angular coordinate tt are chosen for their symmetry.

Mapping parametrizations for surfaces:

I’m noting the parametrizations for S1S_1 and S2S_2, detailing ss and tt limits for both surfaces. This helps in visualizing the geometric representation.

Mapping out ranges

I'm thinking through the ranges for S1S_1 and S2S_2. For S1S_1, ss spans 00 to 1\sqrt{1}, and for S2S_2, ss ranges from 00 to 11, both with tt from 00 to 2π2\pi.

Determining parameter ranges

I’m adjusting the parameterization of ss and tt for S1S_1 and S2S_2 where ss spans from 0 to 1 and tt spans from 0 to 2π2\pi, considering y=s2y = s^2.

Clarifying parametrizations

I’m mapping out the parametrizations of S1S_1 and S2S_2 with their associated limits of integration.

Calculating surface element

I’m figuring out the infinitesimal surface element dS1d\mathbf{S}_1 for the size in question. This involves the unit normal vector n1\mathbf{n}_1 and the infinitesimal area element dA1dA_1.

Breaking down the surface area

I'm calculating the surface area vector differential by first determining partial derivatives of the parametrized surface, then computing their cross product to find the normal vector, ensuring orientation accuracy.

Confirming orientation

OK, let me see. I’m ensuring the normal vector N\mathbf{N} points outward from the paraboloid surface S1S_1, as the outward orientation seems crucial.

Mapping the surface

OK, let's break this down: I’m calculating the normal vector for S2S_2. After determining r2s\frac{\partial \mathbf{r}_2}{\partial s} and r2t\frac{\partial \mathbf{r}_2}{\partial t}, I cross these to find N\mathbf{N} via the determinant method.

Reversing the normal vector

I’m thinking through the equation for dS2d\mathbf{S}_2 by reversing the direction of the normal vector, which initially points in the negative yy-direction. This adjustment is necessary to ensure the normal vector points outward, aligning with the positive yy-direction.

Adjusting the normal

I’m piecing together the normal vector for S1S_1 to ensure it points outward, given the paraboloid's orientation and the yy-component's negativity. Toy with the dS1d\mathbf{S}_1 direction to make the yy-component positive.

Analyzing surface integrals

I’m working through surface integrals by evaluating dot products and setting up integrals. Coincidentally, both surface elements have a positive yy-component.

Calculating dot product

I’m working through the dot product of the vector field F\mathbf{F} and the surface element dS1d\mathbf{S}_1. The first term is zero, the second term simplifies to 2s3-2s^3 using y=s2y = s^2, and the third term is 2s2sintz-2s^2 \sin t \cdot z.

Handling the dot product

OK, I’m rechecking the dot product for S1S_1 with z=ssintz = s \sin t. The expression looks off, so I’m carefully re-evaluating to ensure accuracy.

Calculating the dot product

I’m figuring out the dot product of F\mathbf{F} and dS1d\mathbf{S}_1. By breaking down each term, I simplify the expression to 2s3(1+sin2t)-2s^3 (1 + \sin^2 t).

Dot product calculation

I’m noting the dot product of the force field F\mathbf{F} and the differential surface element dS2d\mathbf{S}_2 at S2S_2 by focusing on their j\mathbf{j} components. The result is 2s-2s.

Calculating the dot product

I’m working through the dot product FdS2\mathbf{F} \cdot d\mathbf{S}_2, which simplifies to 2s-2s. Next, I’ll integrate this over S2S_2.

Breaking down integrals

I started with separating the integral into two ss-integrals. Evaluating these gave 12-\frac{1}{2}. Combining with tt-integrals, the final expression was derived.

Calculating surface integral

I’m working through the surface integral by evaluating I1I_1 and I2I_2, integrating over their respective domains. Summing these results, I reach the final surface integral value of 7π2-\frac{7\pi}{2}.

Revisiting arithmetic precision

Breaking down the integral

I’m examining S(2yj+zk)dS\iint_S (-2yj + zk) \cdot dS. Splitting into S1S_1 and S2S_2, the final value is 7π2-\frac{7\pi}{2}.

Understanding the problem

I’m mapping out the surface integral SFdS\iint_S \mathbf{F} \cdot d\mathbf{S} by parametrizing the paraboloid y=x2+z2y = x^2 + z^2 and the disk x2+z21x^2 + z^2 \leq 1 at y=1y = 1. Calculating dSd\mathbf{S} for each surface is next.

Noticing the interval

OK, so it looks like tt is set to span from 00 to 2π2\pi, covering a full cycle.

Piecing together surface integrals

First, I calculate S1FdS1\iint_{S_1} \mathbf{F} \cdot d\mathbf{S}_1 to get 3π2-\frac{3\pi}{2}. Then, I find S2FdS2\iint_{S_2} \mathbf{F} \cdot d\mathbf{S}_2 to be 2π-2\pi. Adding these, I arrive at the final integral value of 7π2-\frac{7\pi}{2}.

Respuesta

Subject: Vector Calculus - Surface Integrals

Step 1: Understanding the Problem and Setting Up the Parametrizations

Given:

  • A vector field F=2yj+zk\mathbf{F} = -2y\,\mathbf{j} + z\,\mathbf{k}.
  • Surface SS consists of:
    • S1S_1: The paraboloid y=x2+z2y = x^2 + z^2 for 0y10 \leq y \leq 1.
    • S2S_2: The disk x2+z21x^2 + z^2 \leq 1 at y=1y = 1.
  • The surface has outward orientation.

To Find:

  • Evaluate the surface integral: SFdS=S1FdS1+S2FdS2\iint_S \mathbf{F} \cdot d\mathbf{S} = \iint_{S_1} \mathbf{F} \cdot d\mathbf{S}_1 + \iint_{S_2} \mathbf{F} \cdot d\mathbf{S}_2

Explanation and Concepts Used:

  • Parametrization: We'll parametrize each part of the surface using cylindrical coordinates due to symmetry.
  • Surface Element dSd\mathbf{S}: Calculated using the cross product of partial derivatives.
  • Orientation: Ensure normals point outward for correct orientation.

Parametrizations and Limits:

  • For S1S_1: r1(s,t)=scost,s2,ssint\mathbf{r}_1(s, t) = \langle s\cos t,\, s^2,\, s\sin t \rangle
    • ss ranges from 00 to 11.
    • tt ranges from 00 to 2π2\pi.
  • For S2S_2: r2(s,t)=scost,1,ssint\mathbf{r}_2(s, t) = \langle s\cos t,\, 1,\, s\sin t \rangle
    • ss ranges from 00 to 11.
    • tt ranges from 00 to 2π2\pi.

Step 2: Calculating the Surface Integrals

Computing dS1d\mathbf{S}_1 and Evaluating S1FdS1\iint_{S_1} \mathbf{F} \cdot d\mathbf{S}_1:

  1. Calculate Partial Derivatives: r1s=cost,2s,sint,r1t=ssint,0,scost\frac{\partial \mathbf{r}_1}{\partial s} = \langle \cos t,\, 2s,\, \sin t \rangle,\quad \frac{\partial \mathbf{r}_1}{\partial t} = \langle -s\sin t,\, 0,\, s\cos t \rangle
  2. Compute Cross Product for dS1d\mathbf{S}_1: dS1=(r1s×r1t)dsdt=2s2cost,s,2s2sintdsdtd\mathbf{S}_1 = \left( \frac{\partial \mathbf{r}_1}{\partial s} \times \frac{\partial \mathbf{r}_1}{\partial t} \right) ds\,dt = \langle -2s^2\cos t,\, s,\, -2s^2\sin t \rangle ds\,dt
    • Adjusted for outward orientation.
  3. Compute FdS1\mathbf{F} \cdot d\mathbf{S}_1: FdS1=(2s2)s+(ssint)(2s2sint)=2s32s3sin2t\mathbf{F} \cdot d\mathbf{S}_1 = \left( -2s^2 \right) s + \left( s\sin t \right) \left( -2s^2\sin t \right) = -2s^3 - 2s^3\sin^2 t
  4. Evaluate the Integral: S1FdS1=02π01(2s32s3sin2t)dsdt=3π2\iint_{S_1} \mathbf{F} \cdot d\mathbf{S}_1 = \int_{0}^{2\pi} \int_{0}^{1} \left( -2s^3 - 2s^3\sin^2 t \right) ds\,dt = -\frac{3\pi}{2}

Computing dS2d\mathbf{S}_2 and Evaluating S2FdS2\iint_{S_2} \mathbf{F} \cdot d\mathbf{S}_2:

  1. Calculate Partial Derivatives: r2s=cost,0,sint,r2t=ssint,0,scost\frac{\partial \mathbf{r}_2}{\partial s} = \langle \cos t,\, 0,\, \sin t \rangle,\quad \frac{\partial \mathbf{r}_2}{\partial t} = \langle -s\sin t,\, 0,\, s\cos t \rangle
  2. Compute Cross Product for dS2d\mathbf{S}_2: dS2=(r2s×r2t)dsdt=0,s,0dsdtd\mathbf{S}_2 = \left( \frac{\partial \mathbf{r}_2}{\partial s} \times \frac{\partial \mathbf{r}_2}{\partial t} \right) ds\,dt = \langle 0,\, s,\, 0 \rangle ds\,dt
    • Adjusted for outward orientation.
  3. Compute FdS2\mathbf{F} \cdot d\mathbf{S}_2: FdS2=(2×1)×s=2s\mathbf{F} \cdot d\mathbf{S}_2 = (-2 \times 1) \times s = -2s
  4. Evaluate the Integral: S2FdS2=02π01(2s)dsdt=2π\iint_{S_2} \mathbf{F} \cdot d\mathbf{S}_2 = \int_{0}^{2\pi} \int_{0}^{1} (-2s) ds\,dt = -2\pi

Final Answer:

The surface integral evaluates to:

SFdS=(3π2)+(2π)=7π2\iint_S \mathbf{F} \cdot d\mathbf{S} = \left( -\frac{3\pi}{2} \right) + \left( -2\pi \right) = -\frac{7\pi}{2}

So, S(2yj+zk)dS=3π2+(2π)\iint_S (-2y\,\mathbf{j} + z\,\mathbf{k}) \cdot d\mathbf{S} = -\frac{3\pi}{2} + (-2\pi).

Answer: The surface integral evaluates to 7π2-\dfrac{7\pi}{2}.

Pregunta

Suppose that, near the point \(a = \begin{pmatrix} 2 \\ 1 \end{pmatrix}\), the Celsius temperature is specified by the function \(f(x, y) = 20 + xy^2\).

(a) Suppose that you drive with a constant velocity vector \(\vec{v}_1 = \begin{pmatrix} 1 \\ 3 \end{pmatrix}\), passing through the point \(a = \begin{pmatrix} 2 \\ 1 \end{pmatrix}\) at time \(t = 0\). Express the temperature outside your car as a function \(g(t)\) and use single-variable calculus to calculate \(g'(0)\), the rate at which the reading on your car’s thermometer is changing. You have calculated the directional derivative of \(f\) along the vector \(\vec{v}_1\) by using single-variable calculus.

(b) Do the same for the velocity vector \(\vec{v}_2 = \begin{pmatrix} -1 \\ -1 \end{pmatrix}\).

(c) As it turns out, the given function \(f\) is differentiable, and the directional derivative is therefore a linear function of velocity. Use this fact to determine the directional derivative of \(f\) along the standard basis vector \(\vec{e}_2 = \begin{pmatrix} 0 \\ 1 \end{pmatrix}\) from your earlier answers, and confirm that your answer agrees with the partial derivative \(D_2 f(a)\).

(d) Verify your answers to parts (a) and (b) by recalculating the directional derivatives using the formula \([Df(a)] \vec{v}\).

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Solve the question by typing the followings: The solution contains atleast two steps. Write the subject or sub-subject. In step 1: What is given, what do we need to find out, explanation part (Define/concept used, formula used), Step-by-step solution. In other steps (2 to 4): Continue the step-by-step solution by giving heading what now we are going to calculate in this step. (In brief)
Final answer in sentence.

Pensamiento

Clarifying the approach

The assistant is tasked with breaking down a solution into detailed steps, ensuring clarity and following OpenAI's guidelines.

Ensuring compliance and clear instructions

Analyzing directional derivatives

I’m working through the objective of calculating the directional derivative of the temperature function along specific velocity vectors. This involves expressing the temperature as a function of time and determining how it changes with the vectors.

Evaluating directional derivative

I’m thinking through the directional derivative of ff along e2\vec{e}_2 and comparing it to the partial derivative D2f(a)D_2 f(a). Recalculating with [Df(a)]v[Df(a)] \vec{v} confirms accuracy.

Breaking down the solution

I’m focusing on presenting the next steps in the solution, ensuring clarity and progression. Each step hones in on a specific calculation or concept.

Navigating the problem

I’m analyzing the temperature of a moving car using g(0)g'(0) and integrating the chain rule in calculus to express g(t)g'(t) and subsequently determine g(0)g'(0).

Step 3️⃣: I expanded and simplified the function g(t)=22+13t+24t2+9t3g(t) = 22 + 13t + 24t^2 + 9t^3 to express temperature as a polynomial in tt.

Expressing car's path

I mapped out the car's trajectory as r(t)=(2t1t)\mathbf{r}(t) = \begin{pmatrix} 2 - t \\ 1 - t \end{pmatrix}, leading to x(t)=2tx(t) = 2 - t and y(t)=1ty(t) = 1 - t.

Breaking down temperature dynamics

I expanded and simplified the temperature function h(t)h(t). Then, finding h(t)h'(t) and evaluating it at t=0t = 0 showed a rate of 5C per unit time-5^\circ \text{C per unit time}.

Azimuthal angle derivation

OK, let me break this down: I calculated dϕdρ\frac{d\phi}{d\rho} using partial derivatives and the chain rule, which gives 2ρ\frac{2}{\rho}.

Revisiting my approach

I updated equation (2) and tried combining it with equation (1). It turns out the simplest method is to discard equation (3) and solve using the original two equations.

Breaking down the steps

Firstly, I multiplied equation (2') by 3. Subtracting equation (1) from it, I simplified to find fx(a)=1f_x(a) = 1. Then, through direct computation, I confirmed fy(a)=4f_y(a) = 4.

Recalculating derivatives

I’m recalculating directional derivatives using the gradient vector f(a)\nabla f(a) and verifying them against previous results, ensuring consistency in parts (a) and (b).

Verifying directional derivatives

I’m confirming the directional derivatives calculated using the gradient, ensuring they align with earlier results. This confirms both the linearity and correctness of the findings.

Respuesta

Subject: Multivariable Calculus - Directional Derivatives and Differentiability


Step 1: Problem (a) - Calculating the Rate of Change of Temperature Along v1\vec{v}_1

Given:

  • Temperature function: f(x,y)=20+xy2f(x, y) = 20 + x y^2
  • Point of interest: a=(21)a = \begin{pmatrix} 2 \\ 1 \end{pmatrix}
  • Velocity vector: v1=(13)\vec{v}_1 = \begin{pmatrix} 1 \\ 3 \end{pmatrix}
  • At time: t=0t = 0, the car is at point aa

To Find:

  • Function g(t)g(t): Temperature outside the car as a function of time
  • Derivative g(0)g'(0): Rate at which the temperature is changing at t=0t = 0

Explanation and Concepts Used:

  • Parametric Path: The position of the car over time is given by r(t)=a+v1t\mathbf{r}(t) = a + \vec{v}_1 t.
  • Composition of Functions: The temperature as a function of time is g(t)=f(r(t))g(t) = f(\mathbf{r}(t)).
  • Single-variable Calculus: Use derivative g(t)g'(t) to find the rate of change at t=0t = 0.

Step-by-Step Solution:

  1. Determine the Path of the Car:

    r(t)=(21)+t(13)=(x(t)y(t))=(2+t1+3t)\mathbf{r}(t) = \begin{pmatrix} 2 \\ 1 \end{pmatrix} + t \begin{pmatrix} 1 \\ 3 \end{pmatrix} = \begin{pmatrix} x(t) \\ y(t) \end{pmatrix} = \begin{pmatrix} 2 + t \\ 1 + 3t \end{pmatrix}
  2. Express Temperature as a Function of Time:

    g(t)=f(x(t),y(t))=20+(2+t)(1+3t)2g(t) = f(x(t), y(t)) = 20 + (2 + t)(1 + 3t)^2
  3. Simplify g(t)g(t):

    • Expand (1+3t)2=1+6t+9t2(1 + 3t)^2 = 1 + 6t + 9t^2
    • Multiply: (2+t)(1+6t+9t2)=(2)(1+6t+9t2)+t(1+6t+9t2)(2 + t)(1 + 6t + 9t^2) = (2)(1 + 6t + 9t^2) + t(1 + 6t + 9t^2) =(2+12t+18t2)+(1t+6t2+9t3)=2+13t+24t2+9t3= (2 + 12t + 18t^2) + (1t + 6t^2 + 9t^3) = 2 + 13t + 24t^2 + 9t^3
    • Add the constant 20: g(t)=20+2+13t+24t2+9t3=22+13t+24t2+9t3g(t) = 20 + 2 + 13t + 24t^2 + 9t^3 = 22 + 13t + 24t^2 + 9t^3
  4. Compute g(t)g'(t):

    g(t)=ddt[22+13t+24t2+9t3]=13+48t+27t2g'(t) = \frac{d}{dt}[22 + 13t + 24t^2 + 9t^3] = 13 + 48t + 27t^2
  5. Evaluate g(0)g'(0):

    g(0)=13+48(0)+27(0)2=13g'(0) = 13 + 48(0) + 27(0)^2 = 13

Answer to Part (a): The rate at which the temperature is changing at t=0t = 0 is g(0)=13C per unit timeg'(0) = 13^\circ \text{C per unit time}.


Step 2: Problem (b) - Calculating the Rate of Change of Temperature Along v2\vec{v}_2

Given:

  • Velocity vector: v2=(11)\vec{v}_2 = \begin{pmatrix} -1 \\ -1 \end{pmatrix}

To Find:

  • Function h(t)h(t): Temperature outside the car as a function of time
  • Derivative h(0)h'(0): Rate at which the temperature is changing at t=0t = 0

Step-by-Step Solution:

  1. Determine the Path of the Car:

    r(t)=(21)+t(11)=(x(t)y(t))=(2t1t)\mathbf{r}(t) = \begin{pmatrix} 2 \\ 1 \end{pmatrix} + t \begin{pmatrix} -1 \\ -1 \end{pmatrix} = \begin{pmatrix} x(t) \\ y(t) \end{pmatrix} = \begin{pmatrix} 2 - t \\ 1 - t \end{pmatrix}
  2. Express Temperature as a Function of Time:

    h(t)=f(x(t),y(t))=20+(2t)(1t)2h(t) = f(x(t), y(t)) = 20 + (2 - t)(1 - t)^2
  3. Simplify h(t)h(t):

    • Expand (1t)2=12t+t2(1 - t)^2 = 1 - 2t + t^2
    • Multiply: (2t)(12t+t2)=2(12t+t2)t(12t+t2)(2 - t)(1 - 2t + t^2) = 2(1 - 2t + t^2) - t(1 - 2t + t^2) =(24t+2t2)(t2t2+t3)=25t+4t2t3= (2 - 4t + 2t^2) - (t - 2t^2 + t^3) = 2 - 5t + 4t^2 - t^3
    • Add the constant 20: h(t)=20+25t+4t2t3=225t+4t2t3h(t) = 20 + 2 - 5t + 4t^2 - t^3 = 22 - 5t + 4t^2 - t^3
  4. Compute h(t)h'(t):

    h(t)=ddt[225t+4t2t3]=5+8t3t2h'(t) = \frac{d}{dt}[22 - 5t + 4t^2 - t^3] = -5 + 8t - 3t^2
  5. Evaluate h(0)h'(0):

    h(0)=5+8(0)3(0)2=5h'(0) = -5 + 8(0) - 3(0)^2 = -5

Answer to Part (b): The rate at which the temperature is changing at t=0t = 0 is h(0)=5C per unit timeh'(0) = -5^\circ \text{C per unit time}.


Step 3: Problem (c) - Determining the Directional Derivative Along e2\vec{e}_2

To Find:

  • Directional derivative along e2\vec{e}_2: Use linearity to determine De2f(a)D_{\vec{e}_2} f(a)
  • Confirm: Verify that De2f(a)=D2f(a)D_{\vec{e}_2} f(a) = D_2 f(a)

Explanation and Concepts Used:

  • Linearity of Directional Derivatives: Dvf(a)=fx(a)v1+fy(a)v2D_{\vec{v}} f(a) = f_x(a) v_1 + f_y(a) v_2
  • Partial Derivatives: D1f(a)=fx(a)D_1 f(a) = f_x(a), D2f(a)=fy(a)D_2 f(a) = f_y(a)

Step-by-Step Solution:

  1. Set Up Equations from Previous Results:

    From Part (a):

    Dv1f(a)=13=fx(a)(1)+fy(a)(3)D_{\vec{v}_1} f(a) = 13 = f_x(a)(1) + f_y(a)(3)

    From Part (b):

    Dv2f(a)=5=fx(a)(1)+fy(a)(1)D_{\vec{v}_2} f(a) = -5 = f_x(a)(-1) + f_y(a)(-1)
  2. Solve for Partial Derivatives:

    • Add the equations: 13+(5)=[fx(a)(1)+fy(a)(3)]+[fx(a)(1)+fy(a)(1)]13 + (-5) = [f_x(a)(1) + f_y(a)(3)] + [f_x(a)(-1) + f_y(a)(-1)] 8=fx(a)(11)+fy(a)(31)=fy(a)(2)8 = f_x(a)(1 - 1) + f_y(a)(3 - 1) = f_y(a)(2)
    • Solve for fy(a)f_y(a): fy(a)=82=4f_y(a) = \frac{8}{2} = 4
    • Substitute fy(a)f_y(a) back into one of the equations: 5=fx(a)4-5 = -f_x(a) - 4 5=fx(a)4    fx(a)=1-5 = -f_x(a) - 4 \implies f_x(a) = 1
  3. Determine De2f(a)D_{\vec{e}_2} f(a):

    • Since fy(a)=4f_y(a) = 4, the directional derivative along e2\vec{e}_2 is De2f(a)=4D_{\vec{e}_2} f(a) = 4.
  4. Confirm with Partial Derivative:

    • Compute fy(x,y)=fy=2xyf_y(x, y) = \frac{\partial f}{\partial y} = 2 x y
    • At a=(2,1)a = (2, 1): fy(a)=221=4f_y(a) = 2 \cdot 2 \cdot 1 = 4
    • This confirms D2f(a)=4D_2 f(a) = 4.

Answer to Part (c): The directional derivative along e2\vec{e}_2 is De2f(a)=4D_{\vec{e}_2} f(a) = 4, confirming that D2f(a)=4D_2 f(a) = 4.


Step 4: Problem (d) - Verifying Directional Derivatives Using the Gradient

To Find:

  • Recalculate directional derivatives: Use [Df(a)]v=f(a)v[Df(a)] \vec{v} = \nabla f(a) \cdot \vec{v}
  • Verify: Ensure results match those from Parts (a) and (b)

Explanation and Concepts Used:

  • Gradient Vector: f(a)=(fx(a)fy(a))\nabla f(a) = \begin{pmatrix} f_x(a) \\ f_y(a) \end{pmatrix}
  • Directional Derivative Formula: Dvf(a)=f(a)vD_{\vec{v}} f(a) = \nabla f(a) \cdot \vec{v}

Step-by-Step Solution:

  1. Use Calculated Partial Derivatives:

    • fx(a)=1f_x(a) = 1
    • fy(a)=4f_y(a) = 4
    • f(a)=(14)\nabla f(a) = \begin{pmatrix} 1 \\ 4 \end{pmatrix}
  2. Calculate Dv1f(a)D_{\vec{v}_1} f(a):

    Dv1f(a)=f(a)v1=(1)(1)+(4)(3)=1+12=13D_{\vec{v}_1} f(a) = \nabla f(a) \cdot \vec{v}_1 = (1)(1) + (4)(3) = 1 + 12 = 13
  3. Calculate Dv2f(a)D_{\vec{v}_2} f(a):

    Dv2f(a)=f(a)v2=(1)(1)+(4)(1)=14=5D_{\vec{v}_2} f(a) = \nabla f(a) \cdot \vec{v}_2 = (1)(-1) + (4)(-1) = -1 - 4 = -5
  4. Verify Results:

    • Both directional derivatives match the results from Parts (a) and (b).

Answer to Part (d): The directional derivatives using the gradient are Dv1f(a)=13D_{\vec{v}_1} f(a) = 13 and Dv2f(a)=5D_{\vec{v}_2} f(a) = -5, confirming our earlier calculations.


Final Answer:

By applying single-variable calculus and properties of differentiable functions, we determined:

  • (a) The rate at which the temperature changes along v1\vec{v}_1 is g(0)=13C per unit timeg'(0) = 13^\circ \text{C per unit time}.
  • (b) The rate at which the temperature changes along v2\vec{v}_2 is h(0)=5C per unit timeh'(0) = -5^\circ \text{C per unit time}.
  • (c) The directional derivative along e2\vec{e}_2 is De2f(a)=4D_{\vec{e}_2} f(a) = 4, matching the partial derivative fy(a)f_y(a).
  • (d) The gradient method verifies our previous results, confirming the calculations.

Therefore, we have successfully calculated the rates of temperature change along different paths and verified the linearity of directional derivatives for the given differentiable function.

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