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1) which are removed in the construction and zero elsewhere. Show that g is Lebesgue integrable and compute its integral. Solution. (1) The total length of the intervals is being reduced by a factor of 1/3 each time. Thus l(Ck) = 3k . Thus the integral of f, which is non­ negative, is actually 2k (6.59) � fk = �...
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which is not an empty set, f (x) = k. (5) The set F, which is the union of the intervals removed is [0, 1) \ E. Taking step functions equal to 1 on each of the intervals removed gives an absolutely summable series, since they are non-negative and the kth one has integral 1/3×(2/3)k−1 for k = 1, . . . . This series...
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has union containing a given rectange then the sum of the areas of the rectangles is at least as large of that of the rectangle contained in the union. (5) Prove the extension of the preceeding result to a countable collection of rectangles with union containing a given rectangle. Solution. (1) For subdivision of...
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. Similarly let C2 be the corresponding set of end-points of the second intervals of the rectangles. Now divide each of the rectangles repeatedly using the finite number of points in C1 and the finite number of points in C2. The total area remains the same and now the rectangles covering [a1, b1) × [A2, b2) are preci...
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D. Each of the resulting rectangles is either contained in D or is disjoint from it. Replace D1 by the (one in fact) subrectangle contained in D. Proceeding by induction we can suppose that the first N −k of the rectangles are disjoint and all contained in D and together all the rectangles cover D. Now look at the ...
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[a1, b1 − δ] × [a2, b1 − δ]. By compactness, a finite number of these open rectangles cover, and hence there semi-closed version, with the same endpoints, covers [a1, b1 − δ) × LECTURE NOTES FOR 18.102, SPRING 2009 39 [a2, b1 − δ). Applying the preceeding finite result we see that (6.66) Sum of areas + 2Cδ ≥ Area...
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fj (x)| < ∞ for all x ∈ [0, 1). (3) Conclude that any continuous function on [0, 1], extended to be 0 outside this interval, is a Lebesgue integrable function on R. Solution. (1) Since the real and imaginary parts of a continuous function are continuous, it suffices to consider a real continous function f and then ...
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(x)| = |Fn+1(x) − Fn(x)| ≤ 2−n ∀ n > 1. |fn| ≤ 2−n and so the series is absolutely summable. Moreover, it Thus actually converges everywhere on [0, 1) and uniformly to f by (6.68). � (3) Hence f is Lebesgue integrable. 40 LECTURE NOTES FOR 18.102, SPRING 2009 (4) For some reason I did not ask you to check that...
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OpencourseWare 2.11 The p diacritic (and the %r tone label) 9 August 2006 Note for this 2006 ToBI tutorial: Prosodic labelling of disfluencies has turned out to be one of the biggest challenges to the ToBI system, and because these events happen often in spontaneous speech, extending the system to label them appro...
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from fluent cases of 2 by the use of the p diacritic. EXAMPLE <display>: Display all the flights from Baltimore to Dallas 1 Timothy Arbisi-Kelm and Sun-Ah Jun (2005) “A comparison of disfluency patterns in normal and stuttered speech” in Proceedings of Disfluency in Spontaneous Speech Workshop, Aix-en Provence, Fran...
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also had an occurrence of 3p. Note the presence of the phrase accent distinguishing this interword juncture from the surrounding cases of 2p. EXAMPLE <amazing>: um But I had I mean the stuff he knows is kind of 0 0 1p 3 1 4 1 1 1 4 1 1 1 amazing 'coz he does a lot of um environmental 3 1p 1 1 X 0 1 4 1 impa...
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keep in mind is that the ‘cutoff’ described for 1p is not equivalent to the loss of phonological material from the end of a word. For example, speakers often apparently delete the final stop from an consonant cluster, as in ‘los’ an’ found’ for ‘lost and found’. In these cases there is clearly no disfluency and 1p s...
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-L% H* 1 1 4 1 !H* L-L% is kind of amazing 'coz he does a lot of um 1 1 1 3 1p 1 1 X 0 1 4 L+H* L- %r H* !H* L-L% environmental impact stuff 1 2p 4 H* H* H-L% EXAMPLE <connections>: What are the plane sizes for these flights and 4 1 4 1 1 1 1 1 H* 1 L* H-H% H* H* H-L% do they ha(ve)- do are th...
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as if there had been no interruption. EXAMPLE <abbreviation>: What is the b- abbreviation n under 0 1 1 1p 3- 3 3p H* H- L+H* L- H* !H- the category d c mean 1 1 1 4 1 H* H* H* L-L% Especially, %r should not be used after a 3p, where the (re)start of a new intonation contour is already implicit in the break ...
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ation where there is a phrase accent in the tone tier. Other disfluency markers: %r: marks the well formed beginning (restart) of an intonational phrase after a disfluent ending of the previous intonational phrase Optional labels: <: late High Tonal peak
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MIT OpenCourseWare http://ocw.mit.edu ESD.70J / 1.145J Engineering Economy Module Fall 2009 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. ESD.70J Engineering Economy Fall 2009 Session One Michel-Alexandre Cardin Prof. Richard de Neufville ESD.70J Engineering Eco...
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exam – one final assignment! ESD.70J Engineering Economy Module - Session 1 5 Course Outline Four (4) recitation-style sessions: 1. NPV, Data Tables, and Sensitivity Analysis – today 2. Monte Carlo simulations 3. Modeling uncertainty using different stochastic models and probability distributions 4. Analyzing the ...
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Lord Kelvin – British Mathematician, Physicist, and President of the British Royal Society, c. 1895 Everything that can be invented has been invented. Charles H. Duell – Commissioner of the U.S. Patent Office, 1899 Reagan doesn’t have the presidential look. United Artists Executive – dismissing Ronald Reagan for the ...
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! ESD.70J Engineering Economy Module - Session 1 14 Session one – Big vs. Small • Objectives: – Good spreadsheet setup habits to facilitate Sensitivity Analysis – Charts – One-way/Two-way Data Tables – Goal Seek ESD.70J Engineering Economy Module - Session 1 15 Proper spreadsheet setup • Programming/modeling (cid:2...
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with capital cost of $300 million • No salvage value for Plan A; $300 million salvage value for Plan B • Discount rate for Plan A is 9%, and 8% for Plan B • The company will sell each computer for $2,000 • Variable cost for Plan A is $1,280 due to economies of scale; Variable cost for Plan B is $1,500 • See “Entries”...
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Variable Cost (Thousand dollar) Variable Cost (Million dollar) Investment (Million dollar) Salvage (Million dollar) Net value (Million dollar) Discount Factor @ 9.0% Present Value (Million dollar) NPV (Million dollar) 0 900 -900 1 -900.0 162.1 1 1 900 300 300 2 600 1.28 384 0 216 0.917431 198.2 2 1 900 600 600 2 1200 1...
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300 2 2 600 600 600 2 1200 1.5 900 300 -150 0.925926 -138.9 0 0.857339 0.0 3 3 900 900 900 2 1800 1.5 1350 300 750 0.793832 595.4 ESD.70J Engineering Economy Module - Session 1 23 Conclusion? • Which plan is better? – Plan A: $162.1M OR; – Plan B: $156.5M • Express this finding as the difference between NPVA and NPVB...
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) – What Excel was presumably invented for… • Charts • Goal seek ESD.70J Engineering Economy Module - Session 1 27 Data Tables • Use Data Tables to see how different input values affect the output • Data Tables provide a shortcut for calculating, viewing and comparing multiple versions in one calculation (what-if ...
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cell below the row of values ESD.70J Engineering Economy Module - Session 1 31 One-way Data Table (Cont) • Step 3: create new output values Select the range of cells containing the formulas and values (no labels!) – – Go to “Data” menu, select “Table” – – Data menu ⇒ ‘What-If Analysis’ in Excel 2007 • Reference “Col...
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questions… ESD.70J Engineering Economy Module - Session 1 35 Two-way Data Tables • Same idea as One-way, only now we explore output dependency on 2 inputs • Expect a 2-D matrix ESD.70J Engineering Economy Module - Session 1 36 Two-way Data Tables • Step 1: Create one column and one row varying input values for each...
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8 -71.24238649 -56.17608562 -41.1098 -85.99441135 -70.92811048 -55.8618 ESD.70J Engineering Economy Module - Session 1 39 Conditional formatting • You can vary text appearance with values • Step 1: Enter value range for varying number appearance (i.e.: min/max) • Step 2: Select the target formatting range • Step 3: ...
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curve of NPVA – NPVB as a function of discount rate for Plan B… ESD.70J Engineering Economy Module - Session 1 45 Chart example • Step 1: Chart Type – XY(Scatter) with data points connected • Step 2: Source Data • Step 3: Chart Options – Titles, Legend, etc… • Step 4: Chart Location – As object in “Entries” Sensiti...
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0J Engineering Economy Module - Session 1 49 Additional note: NPV function • You may use NPV(rate,value1,value2, ...) – “rate” is the discount rate for one time period – “value1”, “value2”, ... are values you wish to discount – Excel’s NPV function assumes that all cash flows occur at the END of their time period. I...
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.pdf • Excel 2007 for PC: http://office.microsoft.com/en- us/training/HA102255331033.aspx ESD.70J Engineering Economy Module - Session 1 55 Next class… With the deterministic base case NPV sheet finished, we proceed to Monte Carlo simulations CRITICAL PART OF THE COURSE See you tomorrow! ESD.70J Engineering Economy ...
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The heat and wave equations in 2D and 3D 18.303 Linear Partial Differential Equations Matthew J. Hancock Fall 2006 1 2D and 3D Heat Equation Ref: Myint-U & Debnath 2.3 – 2.5 § [Nov 2, 2006] Consider an arbitrary 3D subregion V of R3 (V defined at all points x = (x, y, z) find an equation governing u. The heat ener...
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negative. To compute the total heat energy flowing across the boundaries, we sum φ nˆ over the entire closed surface S, denoted by a double integral dS. Therefore, the conservation of energy principle becomes S · | · · | � � d dt V � � � cρu dV = nˆ dS + φ · − S � � V � � � Q dV (1) 1 1.1 Di...
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∂2F ∂z2 . Applying the Divergence theorem to (1) gives d dt V � � � cρu dV = − V ∇ · � � � φ dV + Q dV V � � � Since V is independent of time, the integrals can be combined as cρ V � � � � ∂u ∂t + φ − ∇ · Q dV = 0 � Since V is an arbitrary subregion of R3 and the integrand is assumed continuous, th...
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l2Q/K0. 2 2D and 3D Wave equation The 1D wave equation can be generalized to a 2D or 3D wave equation, in scaled coordinates, This models vibrations on a 2D membrane, reflection and refraction of electromagnetic (light) and acoustic (sound) waves in air, fluid, or other medium. utt = 2 u ∇ (6) 3 Separation of ...
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t > 0, (7) (8) (9) The 3D Heat Equation implies ′T T 2X = ∇ = X λ = const − (10) where λ = const since the l.h.s. depends solely on t and the middle X ′′/X depends solely on x. The 3D wave equation becomes On the boundaries, ′′ T T = ∇ 2X X = λ = const − X (x) = 0, ∂D x ∈ The Sturm-Liouville Probl...
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with solution Tn (t) = αn cos λn � and the corresponding normal mode is un (x, t) = Xn (x) Tn (t). �� �� t + βn sin � λn t 4 (13) (14) (15) (16) 5 Uniqueness of the 3D Heat Problem Ref: Guenther & Lee 10.3 § We now prove that the solution of the 3D Heat Problem u (x, 0) = f (x) , x D ∈ is unique. Let ...
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D dV dt (t) = 2 v v ∇ · nˆdS 2 − dV v 2 | D |∇ � � � ∂D � � But on ∂D, v = 0, so that the first integral on the r.h.s. vanishes. Thus Also, at t = 0, dV dt (t) = 2 − dV v 2 | 0 ≤ D |∇ � � � V (0) = v 2 (x, 0) dV = 0 (17) (18) D � � � ≤ ≥ 0 and dV /dt Thus V (0) = 0, V (t) 0, i.e. V (t) is a non...
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· 5 6 Sturm-Liouville problem § § Ref: Guenther & Lee 10.2, Myint-U & Debnath 7.1 – 7.3 Both the 3D Heat Equation and the 3D Wave Equation lead to the Sturm-Liouville problem ∇ 2X + λX = 0, X (x) = 0, D, ∂D. x x ∈ ∈ (19) 6.1 Green’s Formula and the Solvability Condition Ref: Guenther & L...
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applied to G = v1 and F = v2 gives ∇ (v1∇ v2) · nˆdS = S � � V � � � v1∇ � v1 gives 2 v2 + v2 · ∇ v1 ∇ dV � Result (22) applied to G = v2 and F = ∇ (v2∇ v1) · nˆdS = S � � V � � � 2 v1 + v2∇ v1 · ∇ v2 ∇ dV � � Subtracting (23) and (24) gives Green’s Formula (also known as Green’s second iden­ tity): (...
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∇ · nˆdS = S � � V � � � = v v � 2 v + ∇ v ∇ · ∇ v dV 2 v + v 2 | |∇ ∇ � dV. (26) V � � � Result (26) holds for any smooth function v defined on a volume V with closed smooth surface S. � � We now apply result (26) to a solution X (x) of the Sturm-Liouville problem (19). Letting v = X (x), S = ∂D and V...
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> 0. Thus (30) can be rearranged, � � � λ = � � � 2 X dV X 2dV ≥ | D |∇ D 0 (31) Since X is real, the the eigenvalue λ is also real. � � � ∇ ∈ X = 0 for all points in D, then integrating and imposing the BC X (x) = 0 X is nonzero ∂D gives X = 0 for all x ∇ dV > 0. Thus, If for x at some points in D, and ...
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1 = 0 = v2 on ∂D and λ2v2, then Eq. (25) becomes λ1v1 and 2v2 = 2v1 = ∇ − ∇ − 0 = (λ1 − λ2) � � � D v1v2dV Thus if λ1 = λ2, v1v2dV = 0, (32) and the eigenfunctions v1, v2 are orthogonal. � � � D 7 Heat and Wave problems on a 2D rectangle, ho­ mogeneous BCs Ref: Guenther & Lee [Nov 7, 2006] § 10.2, Myint-...
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positive a constant (we showed above that λ had to be both constant and positive). We employ separation of variables again, this time in x and y: substituting v (x, y) = X (x) Y (y) into the PDE (33) and dividing by X (x) Y (y) gives Y ′′ Y + λ = X ′′ − X Since the l.h.s. depends only on y and the r.h.s. only ...
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) = X (x0) = 0 0 x0 x ≤ (37) (38) We solved this problem in the chapter on the 1D Heat Equation. We found that for non-trivial solutions, µ had to be positive and the solution is Xm (x) = am sin � The problem for Y (y) is mπx x0 , � µm = mπ x0 � 2 , � m = 1, 2, 3, ... (39) ′′ Y + νY = 0, ≤ Y (0) = Y ...
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� 9 7.2 Solution to heat equation on 2D rectangle The heat problem on the 2D rectangle is the special case of (7), ut = ∂2u ∂x2 + u (x, y, t) = 0, ∂2u ∂y2 , (x, y) u (x, y, 0) = f (x, y) , (x, y) D, ∈ t > 0, ∂D, ∈ (x, y) D, ∈ where D is the rectangle D = . We reverse the separation of variables (9) ...
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mπx x0 sin � � nπy y0 � � −λmnt e (43) Setting t = 0 and imposing the initial condition u (x, y, 0) = f (x, y) gives f (x, y) = u (x, y, 0) = Amnvmn (x, y) = Amn sin ∞∞ ∞∞ m=1 n=1 � � m=1 n=1 � � mπx x0 sin � � nπy y0 � � nπy where vmn (x, y) = sin y0 Liouville problem on a rectangle, (33) – (35). M...
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πy ˆ y0 dx dy � nπy y0 0 � � � � x0y0/4, m = ˆm and n = ˆn � = � 0, otherwise 10 Thus (44) becomes f (x, y) vmˆ nˆ (x, y) dA = A ˆmnˆ 4 x0y0 D � � Since ˆm, ˆn are dummy variables, we replace ˆm by m and ˆn by n, and rearrange to obtain Amn = = 4 x0y0 4 x0y0...
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where D is the rectangle D = . We reverse the separation of variables (9) and substitute solutions (16) and (42) to the T (t) problem (15) and the Sturm Liouville problem (33) – (35), respectively, to obtain (x, y) : 0 { x0, 0 y0} ≤ ≤ ≤ ≤ x y umn (x, y, t) = sin = sin mπx x0 mπx x0 � � � � sin sin nπy...
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, y) ∞ ∞ ∞ ∞ =1 =1 m n � � = αmn sin m=1 n=1 � � � ∞ mπx x0 ∞ sin � � nπy y0 � g (x, y) = ut (x, y, 0) = λmn βmnvmn (x, y) =1 =1 m n � � λmnβmn sin � � mπx x0 sin � � nπy y0 � ∞ ∞ = =1 =1 m n � � sin � nπy y0 mπx x0 where vmn (x, y) = sin are the eigenfunctions of the 2D Sturm Li­ ouville prob...
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the special case where the subregion D is the unit circle (we may assume the circle has radius 1 by choosing the length scale l for the spatial coordinates as the original radius): The Sturm-Liouville Problem (19) becomes � D = (x, y) : x + y 2 2 1 ≤ � ∂2v ∂x2 + ∂2v ∂y2 + λv = 0, v (x, y) = 0, (x, y) D, ∈ x ...
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use separation of variables by substituting − w (1, θ) = 0, π θ < π. w (r, θ) = R (r) H (θ) (49) (50) (51) into the PDE (49) and multiplying by r2/ (R (r) H (θ)) and then rearranging to obtain r d dr r � 1 dR dr R (r) � + λr2 = d2H 1 − dθ2 H (θ) Again, since the l.h.s. depends only on r and the r.h.s....
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. − Substituting (51) gives H ( π) = H (π) , − dH dθ π) ( − = dH dθ (π) . (54) (55) The solution v (x, y) is also bounded on the circle, which implies R (r) must be bounded for 0 1. r ≤ ≤ 13 � The problem for H (θ) is d2H dθ2 + µH (θ) = 0; H ( π) = H (π) , − dH dθ π) ( − = dH dθ...
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λr2 − 2 m Rm = 0; Rm (1) = 0, Rm (0) | | < ∞ (57) We know already that λ > 0, so we can let � � so that (57) becomes 2 d2R¯m ds2 + s dR¯m ds s + 2 s − s = √λr, ¯ Rm (s) = Rm (r) m 2 R¯m = 0; R¯m √λ = 0, R¯m (0) < (58) ∞ � � � � The ODE is called Bessel’s Equation which, for each m = 0, 1, 2, ...
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� � � Rm (r) = cmJm √λr . [Nov 9, 2006] The Bessel Function Jm (s) of the first kind of order m has power series � � ( − 1)k s2k+m k! (k + m)!22k+m . Jm (s) = k=0 � (59) Jm (s) can be expressed in many ways, see Handbook of Mathematical Functions by Abramowitz and Stegun, for tables, plots, and equations. The...
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is L2(k+1)+m (k+1)!(k+1+m)!22(k+1)+m L2k+m k!(k+m)!22k+m = L2 L2 (k + 1) (k + 1 + m) 4 ≤ (k + 1) 4 2 L 2 (k + 1) 2 � = � � � � � � � Thus for k > N = , L/2 ⌉ ⌈ L2(k+1)+m (k+1)!(k+1+m)!22(k+1)+m L2k+m k!(k+m)!22k+m < L 2 (N + 1) 2 < 1 � � � � � � � � � � Since the upper bound is less than one and is...
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,2 = 5.5001 j1,2 = 7.016 3 j0,3 = 8.6537 j1,3 = 10.173 J0 (s) J1 (s) The second BC requires Rm (1) = Rm ¯ √λ = Jm √λ = 0 � This has an infinite number of solutions, namely √λ = jm,n for n = 1, 2, 3, .... Thus the eigenvalues are � � � λmn = m,n, m, n = 1, 2, 3, ... j2 with corresponding eigenfunctions Jm (...
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y) D, ∈ where D is the circle D = . We reverse the separation of vari­ 1 } ables (9) and substitute solutions (14) and (42) to the T (t) problem (13) and the Sturm Liouville problem (47) – (48), respectively, to obtain (x, y) : x2 + y2 { ≤ umn (x, y, t) = vmn (x, y) e −λmnt = vmn (x, y) e −J 2 m,n t where vmn is...
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βmn. 9 The Heat Problem on a square with inhomoge­ neous BC We now consider the case of the heat problem on the 2D unit square D = (x, y) : 0 { ≤ x, y , 1 } ≤ (62) 16 where a hot spot exists on the left side, ut = u (x, y, t) = 2 u, u0/ε, 0, ∇ � u (x, y, 0) = f (x, y) D (x, y) ∈ x = 0, { y y0| < ε/2 ...
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called Laplace’s equation. Laplace’s equation is an example of an elliptic PDE. The wave equation is an example of a hyperbolic PDE. The heat equation is a parabolic PDE. These are the three types of second order (i.e. involving double derivatives) PDEs: elliptic, hyperbolic and parabolic. We proceed via separation...
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An equivalent and more convenient way to write this is X (x) = c3 sinh nπ (1 x) + c4 cosh nπ (1 x) − − Imposing the BC at x = 1 gives X (1) = c4 = 0 and hence Thus the equilibrium solution to this point is X (x) = c3 sinh nπ (1 x) − ∞ uE (x, y) = An sinh (nπ (1 n=1 � x)) sin (nπy) − You can check that this sa...
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) y0+ε/2 y0−ε/2 � sin (mπy) dy y0+ε/2 y0−ε/2 � 2u0 cos (mπy) = = = ε sinh (mπ) − mπ � 2u0 εmπ sinh (mπ) 4u0 sin (mπy0) sin εmπ sinh (mπ) � mπε 2 � 18 (cos (mπ (y0 − ε/2)) − cos (mπ (y0 + ε/2))) Thus ∞ sin (nπy0) sin nπε 2 uE (x, y) = 4u0 επ n sinh (nπ) � To solve the transient problem...
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h nπ (1 − sinh nπ x) ≈ enπ(1−x) enπ = e −nπx Thus the terms decrease in magnitude (x > 0) and hence uE (x, y) can be approxi­ mated the first term in the series, uE (x, y) 4u0 sin (πy0) sin sinh (π) � ≈ επ πε 2 � sinh (π (1 − x)) sin (πy) A plot of sinh (π (1 the square is approximately − x)) sin (πy) is gi...
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− It turns out there is a much easier way to derive this last result. Consider a plate with BCs u = u0 on one side, and u = 0 on the other 3 sides. Let α = uE . Rotating the plate by 90o will not alter uE , since this is the center of the plate. � Let uEsum be the sums of the solutions corresponding to the BC u = ...
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(πy0) sin (πy0) sin (πy0) u0 4 u0 4 u0 2π 20 for small ε. Thus the steady-state center temperature is hottest when the hot spot is placed in the center of the side, i.e. y0 = 1/2. 9.5 Solution to inhomogeneous heat problem on square We now use the standard trick and solve the inhomogeneous Heat P...
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x0 = 1 = y0 in (43); don’t mix up the side length y0 in (43) with the location y0 of the hot spot in the homogeneous problem): ∞ ∞ v (x, y, t) = Amn sin (mπx) sin (nπy) e −π2(m +n2)t 2 where m=1 n=1 � � 1 1 Amn = 4 (f (x, y) 0 � Thus we have found the full solution u (x, y, t). � 0 − uE (x, y)) sin (mπx) s...
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, ∇ uE (x, y) = g (x, y) , (x, y) D, ∈ (x, y) ∂D. ∈ As before, switch to polar coordinates via x = r cos θ, y = r sin θ, wE (r, θ) = uE (x, y) for The problem for uE becomes 0 r ≤ ≤ 1, π − ≤ θ < π. 1 ∂ r ∂r r ∂wE ∂r + 1 ∂2wE r2 ∂θ2 = 0, � w (r, � π) = w (r, π) , − 0 r ≤ ≤ 1, π − ≤ θ < π wθ (r, ...
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d R (r) dr dR dr r � � = The problem for H (θ) is, as before, d2H 1 − dθ2 H (θ) = µ d2H dθ2 + µH (θ) = 0; H ( π) = H (π) , − dH dθ π) ( − = dH dθ (π) , 22 with eigen-solutions Hm (θ) = am cos (mθ) + bm sin (mθ) , m = 0, 1, 2, ... The problem for R (r) is 0 = r d dr dR dr − � r � 2R ...
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θ)) , m = 0, 1, 2, ... The full solution is the infinite sum of these over m, uE (x, y) = wE (r, θ) = We still need to find the Am, Bm. Imposing the BC (69) gives ∞ ∞ m=0 � r m (Am cos (mθ) + Bm sin (mθ)) (70) (Am cos (mθ) + Bm sin (mθ)) = gˆ (θ) (71) The orthogonality relations are m=0 � π cos (mθ) sin (nθ)...
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spot on boundary Suppose gˆ (θ) = � u0 π θ θ0+π − ≤ otherwise ≤ 0 θ0 which models a hot spot on the boundary. The Fourier coefficients in (72) are thus A0 = Bm = u0 2π , Am = u0 mπ (θ0 + π) sin (mθ0) u −mπ (θ 0 + π) 0 (cos (mθ0) 1)m) ( − − Thus the steady-state solution is uE = u0 + 2π ∞ r m m=1 � �...
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for some interesting cases. We draw the level curves (isotherms) uE = const as solid lines. Recall from vector calculus that the uE, is perpendicular to the level curves. Recall also gradient of uE, denoted by uE. Thus heat flows along from the physics that the flux of heat is proportional to uE. Note that the heat...
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hence u nl = 0. Thus there is no flux across lines of symmetry. Equivalently, u is parallel ∇ to the lines of symmetry. Thus the lines of symmetry are flow lines. Identifying the lines of symmetry help draw the level curves, which are perpendicular to the flow lines. Also, lines of symmetry can be thought of as an in...
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curves and heat flow lines. Note that the temperature at the hot point is infinite. See plot. The heat flux lines must go from a point of hot temperature to a point of low temperature. Since the temperature along boundary is zero except at 25 u=0 u=0 u=0 u=u0 /S u u 0 ST0 u of T0  T0 S T0 o S Fig...
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∇ v (x, y, t) = 0, 2 v, v (x, y, 0) = f (x, y) − (x, y) (x, y) D ∈ ∂D ∈ uE (x, y) This is the Heat Problem with homogeneous PDE and BCs. We found the solution to this problem above in (61), v (x, y, t) = ∞ ∞ m=1 n=1 � � Jm (rjm,n) (αmn cos (mθ) + βmn sin (mθ)) e −λmnt where αmn and βmn are found from orthogo...
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−π � Note that the curve radius R centered at (x0, y0). { (x0 + R cos θ, y0 + R sin θ) : π − ≤ θ < π } traces the circle of Proof: To prove the Mean Value Property, we first consider Laplace’s equation (74) on the unit circle centered at the origin (x, y) = (0, 0). We already solved this problem, above, when we ...
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− which is a disc of radius R centered at (x, y) = (x0, y0). Since B(x0,y0) (R) Laplace’s equation (74) holds on this disc. Thus � � 2 v = 0, ∇ (x, y) ∈ B(x0,y0) (R) . D, ⊆ (78) We make the change of variable xˆ = x x0 , − R yˆ = y y0 , − R uE (ˆx, yˆ) = v (x, y) (79) to map the circle B(x0,y0) (R) into t...
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at any point (x0, y0) in D equals the mean value of the temperature around any disc centered at (x0, y0) and contained in D. 12 Maximum Principle for Laplace’s Eq. Ref: Guenther & Lee 8.4, Myint-U & Debnath 8.2 § § Theorem [Maximum Principle] Suppose v (x, y) satisfies Laplace’s equation in a 2D domain D, 2 v =...
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circle must have value v (x0, y0). Since R > 0 is arbitrary, this holds for all values in the disc B(x0,y0)(R). Keep increasing R until the disc hits the boundary of D. Then v (x0, y0) is a value of v along the boundary of D. A similar argument holds for the minimum of v. � Corollary If v = 0 everywhere on the bou...
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problem ∇ 2 v + λv = 0, v = 0, D ∂D x x ∈ ∈ and consider the effect of the shape of the domain on the eigenvalues. Definition Rayleigh Quotient R (v) = vdV v · ∇ v2dV D ∇ D (80) Theorem Given a domain D � � � R3 and any function v that is piecewise smooth � � � on D, non-zero at some points on the inter...
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an orthonormal basis of eigenfunctions on D, i.e. all the functions φn ∇ 2φn + λnφn = 0, φn = 0, D ∂D x x ∈ ∈ 29 and φnφmdV = 1, m = n 0, m = n � � � � D We can expand v in the eigenfunctions, ∞ v (x) = Anφn (x) =1 n � where the An are constants. Assuming we can differentiate the...
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− � � � D 2vdV = v ∇ 2 λnAn ∞ n=1 � (85) Substituting (83) and (85) into (80) gives R (v) = � � � D ∇ D vdV v · ∇ v2dV = ∞ n=1 λnA2 ∞ A2 n=1 n n � We assume the eigenfunctions are arranged in increasing order. In particular, λn ≥ Thus ∞ λ1A2 n=1 ∞ A2 n=1 n ∞ A2 n=1 n = λ1. ∞ A2 n=1 n n = λ1 ...
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� In other words, the domain D smaller eigenvalue. that contains the sub-domain D is associated with a � � Proof: Note that the Sturm-Liouville problems are ∇ ∇ 2 v + λv = 0, v = 0, 2 v + λ v = 0, v = 0, �� � (x, y) (x, y) D ∂D ∈ ∈ (x, y) (x, y) D ∂D � ∈ ∈ Let v1 be the eigenfunction corresponding to λ1 on ...
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without proof]: the eigenfunction(s) corresponding to the are nonzero in the interior of D From the useful fact, ˆv1 cannot be an eigenfunction corresponding to λˆ1 on D , � (outside D). Thus, as the previous theorem states, � (87) λˆ1 < R (ˆv1) . since it is zero in the interior of D � � . 31 � Since ˆv1 = 0...
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for a circle of radius R, we’d rescale by the change of rˆ where ˆr goes from 0 to 1. Thus variable ˆr = r/R, so that Jm on the circle of radius R, the smallest eigenvalue is � = Jm √λr �� λ 2 R � � λ01 = J0,1 R 2 , J0,1 = 2.4048. � Suppose the rectangle is actually a square of side length 2R. Then � λ11 = ...
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since v (r) is smooth on D2, v (R) = 0 (zero on the � boundary of D2), and v is nonzero in the interior. � 32 13.1 Faber-Kahn inequality Thinking about the heat problem on a 2D plate, what shape of plate will cool the slowest? It is a geometrical fact that of all shapes of equal area, the circle (...
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x ∈ ∈ (89) Nodal lines are the curves where the eigenfunctions of the Sturm-Liouville problem are zero. For the solution to the vibrating membrane problem, the normal modes unm (x, y, t) are zero on the nodal lines, for all time. These are like nodes on the 1D string. Here we consider the nodal lines for the squar...
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eigenfunction with eigenvalue λmn, for any constants A, B. The nodal lines for fnm can be quite interesting. Examples: we draw the nodal lines on the interior and also the lines around the boundary, where vnm = 0. (i) m = 1, n = 1. πx a This is positive on the interior and zero on the boundary. Thus the nodal lin...
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/a2, this is a solution to SL problem (89) on D with λ = λ13. To find the nodal lines, we use the identity sin 3θ = (sin θ) 4 sin2 θ to write − 3 − � � v13 = sin v31 = sin v13 − v31 = 4 sin sin sin sin � � � � πy a πy a πy a πx a πx a πx a � � � 3 4 sin2 − πy a � � 3 � � − sin2 � � �� πx a �� sin2 ...
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with the nodal lines that intersect the interior of the square plate: y = x + ka y = x, y = x + a − v31 are the sides and diagonals of the square. Thus the nodal lines of v13 − Let DT be the isosceles right triangle whose hypotenuse lies on the bottom hor­ v31 is zero on the boundary ∂DT , izontal side of the ...
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boundary ∂Dc, positive on the interior of Dc, and thus the eigenfunction corresponding to the first (smallest) eigenvalue λ13 of the Sturm- Liouville problem (89) on Dc. πy a sin2 3 2 − = � � � � . (vii) Find the first eigenvalue on the right triangle DT 2 = 0 y ≤ ≤ √3x, x 0 ≤ ≤ � 1 . � Note that separat...
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the eigenvalues are given by λmn = π2 2 m 1 + 2 n 3 = π2 3 � � 3m 2 + n 2 We create a table of 3m2 + n2 and look for repeated values: � � n, m 1 2 3 4 5 1 4 7 12 19 28 2 13 16 21 28 37 4 3 28 31 36 43 The smallest repeated value of 3m2 + n2 is 28: λ31 = λ24 = λ15 = 28π2/3 The linear com...
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we seek the next largest repeated value of 3m2 + n2 and continue as above. If we can find (A, B, C) such that v = 0 on y = √3x, but v is zero on the interior of DT 2, then λ31 is not the smallest eigenvalue and we must pursue another method of finding the smallest eigenvalue. The Rayleigh quotient can help us identif...
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1. (iii) m = 1 , n = 1 and sine. v11S = J0 (rj1,1) sin θ The nodal lines are the boundary (circle of radius 1) and the line θ = (horizontal diameter). π, 0, π − 15 Steady-state temperature in a 3D cylinder Suppose a 3D cylinder of radius a and height L has temperature u (r, θ, z, t). We assume the axis of the c...
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2 v = ∇ 1 ∂ r ∂r r ∂v ∂r � � + 1 ∂2v r ∂θ2 + 2 ∂2v ∂z2 We separate variables as v (r, θ, z) = R (r) H (θ) Z (z) 37 so that (90) becomes 1 d rR (r) dr dR (r) dr r � � + 1 r2H(θ) d2H(θ) dθ2 + 1 Z (z) d2Z (z) dz2 = 0. Rearranging gives 1 d rR (r) dr dR (r) dr r � � + 1 r2H(θ) d2H(θ)...
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, up to a multiplicative constant, Zn (z) = sin , λn = , n = 1, 2, 3, ... nπz L 2 nπ L � � Multiplying Eq. (92) by r2 gives � � r d R (r) dr dR (r) dr r � − � 2 λnr = 1 −H(θ) d2H(θ) dθ2 = µ (93) where µ is constant since the l.h.s. depends only on r and the middle only on θ. We assume g (θ, z) is smo...
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of the first and second � � � � Rmn (r) = c1mIm r λn + c2mKm r λn Since the Im’s are regular (bounded) at r = 0, while the Km’s are singular (blow up), and since Rmn (r) must be bounded, we must have c2m = 0, or � � � � � � Rmn (r) = c1mIm r λn = c1mIm � Thus the general solution is, by combining constants, �...
https://ocw.mit.edu/courses/18-303-linear-partial-differential-equations-fall-2006/5faa7f7c21719c38fb701bc79ef4a29f_pde3d.pdf
(R|Ψ) = cos Ψ + sin Ψ = 2 1/2 cos(Ψ - π/4) 2. Identify Sample Space 0 π/2 ψ 3. Probability Law over Sample Space: Invoke isotropy implying uniformity of angle fΨ(ψ) 2/ π 0 π/2 ψ 4. Find CDF (cid:139) FR(r) = P{R < r} = P{21/2 cos(Ψ-π/4) < r} (cid:139) FR(r) = P{R < r} = P{cos(Ψ-π/4) < r/ 21/2 } g(Ψ) 1 r/21/2 1/21/2...
https://ocw.mit.edu/courses/1-203j-logistical-and-transportation-planning-methods-fall-2006/5fb3828ccf1c35471a4ae82804586d50_lec3.pdf
(cid:139) Median R = 1.306 (cid:139) E[R] = 4/ π = 1.273 (cid:139) σR/E[R] = 0.098, implies very robust A Quantization Problem NYC Marine Transfer Station Tug Delivers LIGHTS Tug Picks Up HEAVIES LIGHT and HEAVY Barges Stored Loading Loading Barge Barge Loading Loading Barge Barge Barges Shifted By Hand Or Tug Refuse...
https://ocw.mit.edu/courses/1-203j-logistical-and-transportation-planning-methods-fall-2006/5fb3828ccf1c35471a4ae82804586d50_lec3.pdf
) = fD(d)(1) = fD(d), d > 0, 0 <θ <1 θ 1 0 K = 0 K = 1 K = 2 1 2 K = 3 3 d 3. Joint Probability Distribution a) D and Θare independent. b) Θis uniformly distributed over [0, 1] fD,Θ(d, θ) = fD(d) fΘ(θ) = fD(d)(1) = fD(d), d > 0, 0 <θ <1 x θ 1 K = 0 K = 1 K = 2 1-x 0 1 x 1-x 2 K = 3 3 d 4. Working in the Joint Sample ...
https://ocw.mit.edu/courses/1-203j-logistical-and-transportation-planning-methods-fall-2006/5fb3828ccf1c35471a4ae82804586d50_lec3.pdf
18.445 Introduction to Stochastic Processes Lecture 17: Martingle: a.s convergence and Lp-convergence Hao Wu MIT 15 April 2015 Hao Wu (MIT) 18.445 15 April 2015 1 / 10 Recall Martingale : E[Xn | Fm] = Xm for n ≥ m. Optional Stopping Theorem : E[XT ] = E[X0] ? Today’s goal a.s.martingale convergence Doob’s maximal ineq...
https://ocw.mit.edu/courses/18-445-introduction-to-stochastic-processes-spring-2015/5fe9145062f4c67f4f675b6e18bc2065_MIT18_445S15_lecture17.pdf
the website. Corollary Let X = (Xn)n≥0 be a non-negative supermartingale. Then Xn converges a.s. to some a.s. finite limit. Hao Wu (MIT) 18.445 15 April 2015 4 / 10 Examples Example 1 Let (ξj )j≥1 be independent random variables with mean zero such that ∞ E[|ξj |] . Set < ∞ (cid:80) j= 1 X0 = 0, Xn = ξj . n (cid:88) j=...
https://ocw.mit.edu/courses/18-445-introduction-to-stochastic-processes-spring-2015/5fe9145062f4c67f4f675b6e18bc2065_MIT18_445S15_lecture17.pdf
n Xk . Then λP[X ∗ ≥n λ] ≤ E[Xn1[X ∗ ≥n λ]] ≤ E[Xn]. Theorem Let X = (Xn)n≥0 be a non-negative submartingale. Define X ∗ n = max0≤k ≤n Xk . Then, for all p > 1, we have ||X ∗||n p ≤ p p − 1 ||X n||p. Recall Hölder inequality : p > 1, q > 1 and 1/p + 1/q = 1, then E[|XY |] ≤ E[|X p 1| ] /p × E[|Y q 1| ] /q. Hao Wu (MIT) ...
https://ocw.mit.edu/courses/18-445-introduction-to-stochastic-processes-spring-2015/5fe9145062f4c67f4f675b6e18bc2065_MIT18_445S15_lecture17.pdf