Cascade theory. The theory in this lecture comes from: Fluid Mechanics of Turbomachinery by George F. Wislicenus Dover Publications, INC.
|
|
- Ariel Roberts
- 5 years ago
- Views:
Transcription
1 Caade theory The theory i thi leture ome from: Fluid Mehai of Turbomahiery by George F. Wilieu Dover Publiatio, INC. 1965
2 d = dt 0 = + Y ρ 0 = p + = kot. F Y d F X X Cotour i the hage of loity due to the vae The otour i large ompared to the
3
4 Deompoe the veloity i the ormal ad the tagetial diretio of the otour = = ( oα + ) + ( i α + ) ( o α + i α) + v ( oα + i α) + + = + ( oα + i α) +
5 Beroulli equatio ( ) ( ) 0 0 i o p p p p + α α + + ρ + = ρ + =
6 Fore i the x-diretio The fore i the x-diretio atig o the elemet d a be alulated a a fore omig from preure ad impule. df x = p oα ρ ρ ( ) ( ) oα + oα + o ( oα + ) ( i α + ) i α α Flow Rate, Q Veloity i x-diretio, x
7 Fore i the x-diretio We iert the equatio for the preure, p from Beroulli equatio. p = p ρ ( oα + i α) ( + + ) 0 + df x = p oα ρ ρ ( ) ( ) oα + oα + o ( oα + ) ( i α + ) i α α
8 Fore i the x-diretio We iert the equatio for the preure, p from Beroulli equatio. p = p ρ ( oα + i α) ( + + ) 0 + df x = p 0 ρ + ρ ρ oα ( oα + i α) ( + + ) ( ) ( ) oα + oα + o ( oα + ) ( i α + ) i α oα α
9 Fore i the x-diretio df x = p 0 + ρ ρ ρ oα oα + o α + oα i α + oα 3 ( o α + oα + o α) ( oα i α + i α + oα i α + i α)
10 Fore i the x-diretio The hage of veloity, i very mall beaue the large ditae from the airfoil to the otour. We eglet the term that ha the eod order of. df x = p 0 + ρ ρ ρ oα oα + o α + oα i α + oα 3 ( o α + oα + o α) ( oα i α + i α + oα i α + i α)
11 Fore i the x-diretio df x = p 0 oα + ρ 1 oα o α i α ρ o α + i α df x = p 0 oα ρ oα ρ Thi i the fore atig i the x-diretio o a mall elemet, d of the otour.
12 Fore i the x-diretio df x = p0 oα ρ oα ρ By itegratig aroud the otour, we will fid the total fore atig i the x-diretio. =0 =0 F x = p 0 oα ρ oα ρ F x = ρ
13 d Alembert paradox Fx = ρ = 0 The term d i the flow rate through the otour. If the flow i iompreible, the itegral of the term d aroud the otour will be zero. A body i a two-dimeioal ad oviou flow with otat eergy will ot exert a fore i the diretio parallel uditurbed flow,
14 Fore i the y-diretio The fore i the y-diretio atig o the elemet d a be alulated a a fore omig from preure ad impule. df y = p i α ρ ρ ( ) ( ) oα + oα + i α ( oα + ) ( oα + ) oα
15 Fore i the y-diretio df y = p0 i α ρ i α ρ Thi i the fore atig i the y-diretio o a mall elemet, d of the otour.
16 Krefter i y-retig df y = p0 i α ρ i α ρ By itegratig aroud the otour, we will fid the total fore atig i the y-diretio. =0 =0 F y = p 0 i α ρ i α ρ F y = ρ
17 Lift F y = ρ
18 Cirulatio Γ = d
19 Lift F y = ρ Γ
20 The law of the irulatory flow about a defletig body I the abee of ay defletig body iide the hathed area of the otour the fore i y- diretio mut eearily be zero. Thi lead to the theorem that: For a flow of otat eergy the irulatio aroud ay loed otour ot eloig ay fore-tramittig body mut be zero.
21 The law of the irulatory flow about a defletig body Let the irulatio aroud the outer otour i the figure be: Γ 1 = Let the irulatio aroud the ier otour i the figure be: Γ =
22 The law of the irulatory flow about a defletig body Let the irulatio aroud the ier ad outer otour be oeted alog the lie A-B. The irulatio aroud the hathed area a ow be writte a: Γ B 1 = Γ1 + Γ + d A D C
23 The law of the irulatory flow about a defletig body From the figure we a ee that: B A = D C The irulatio aroud the hathed area a ow be writte a: Γ = Γ Γ 1 1
24 The law of the irulatory flow about a defletig body Sie we do ot have ay body iide the hathed area: Γ1 = Γ1 Γ = 0 Whih give: Γ = Γ 1
25 The law of the irulatory flow about a defletig body Γ = Γ 1 Thi lead to the theorem: For a give flow oditio (with otat eergy), the irulatio aroud the defletig body i idepedet of the ize ad hape of the otour alog whih the irulatio i meaured.
26 The law of the irulatory flow about a defletig body The mea veloity for the irulatio aroud a otour havig the legth i: Γ = m = For a otat value of the irulatio, the mea veloity, m ha to dereae if the legth ireae. The irulatio i i ivere ratio to the ditae of the
27 Cirulatio about everal defletig bodie We have 3 wig profile i a twodimeioal aade ad make a otour aroud the whole aade. Thi otour i marked ABGDEF. E Γ1 = = + AEF A A E B Γ = = ABDE A D B E D A E D Γ3 = = + BGD B B D
28 Cirulatio about everal defletig bodie From the figure we a ee that: E A = A E D B = B D
29 Cirulatio about everal defletig bodie Cirulatio aroud 3 wig profile i a aade beome: A B Γ1 + Γ + Γ3 = E A D B E D Γ 1 + Γ + Γ3 = Γ0
30 Caade i a axial flow turbie Let u look at the ylidrial etio AB through the axial flow turbie.
31 Caade i a axial flow turbie By ufoldig the ylidrial etio AB from the lat lide, we a look at the blade i a aade
32 Caade i a axial flow turbie Cirulatio aroud the blade i: (where Z i the umber of blade) Γ = ZΓ i = b b + a b + a a + b a
33 Caade i a axial flow turbie From the figure we a ee that: b b = Π r u a a = Π r u1
34 Caade i a axial flow turbie Γ = ZΓ i = Π r u + a b Π r u1 + b a
35 Caade i a axial flow turbie Γ = ZΓ i = Π r u From the figure we a ee that: + a b b a Π r = a b u1 + b a
36 Caade i a axial flow turbie The irulatio beome: Γ = Π r Π r u u1
37 Caade i a axial flow turbie The hage of agular mometum i related to the vae irulatio by the equatio: Z Γ Π = r u r u1
38 Caade i a axial flow turbie By multiplyig the hage of agular mometum from the uptream to the dowtream ide of a turbie ruer i the torque atig o the turbie haft with the agular veloity of the ruer we will reogize Euler turbie equatio. E = ω r u ω r u1 = ZΓ Π E = u u u 1 u1
Fluids Lecture 2 Notes
Fluids Leture Notes. Airfoil orte Sheet Models. Thi-Airfoil Aalysis Problem Readig: Aderso.,.7 Airfoil orte Sheet Models Surfae orte Sheet Model A aurate meas of represetig the flow about a airfoil i a
More informationFig. 1: Streamline coordinates
1 Equatio of Motio i Streamlie Coordiate Ai A. Soi, MIT 2.25 Advaced Fluid Mechaic Euler equatio expree the relatiohip betwee the velocity ad the preure field i ivicid flow. Writte i term of treamlie coordiate,
More informationBio-Systems Modeling and Control
Bio-Sytem Modelig ad otrol Leture Ezyme ooperatio i Ezyme Dr. Zvi Roth FAU Ezyme with Multiple Bidig Site May ezyme have more tha oe bidig ite for ubtrate moleule. Example: Hemoglobi Hb, the oxygearryig
More informationMath 213b (Spring 2005) Yum-Tong Siu 1. Explicit Formula for Logarithmic Derivative of Riemann Zeta Function
Math 3b Sprig 005 Yum-og Siu Expliit Formula for Logarithmi Derivative of Riema Zeta Futio he expliit formula for the logarithmi derivative of the Riema zeta futio i the appliatio to it of the Perro formula
More informationChap.4 Ray Theory. The Ray theory equations. Plane wave of homogeneous medium
The Ra theor equatio Plae wave of homogeeou medium Chap.4 Ra Theor A plae wave ha the dititive propert that it tregth ad diretio of propagatio do ot var a it propagate through a homogeeou medium p vae
More informationClass #25 Wednesday, April 19, 2018
Cla # Wedesday, April 9, 8 PDE: More Heat Equatio with Derivative Boudary Coditios Let s do aother heat equatio problem similar to the previous oe. For this oe, I ll use a square plate (N = ), but I m
More informationFluid Physics 8.292J/12.330J % (1)
Fluid Physics 89J/133J Problem Set 5 Solutios 1 Cosider the flow of a Euler fluid i the x directio give by for y > d U = U y 1 d for y d U + y 1 d for y < This flow does ot vary i x or i z Determie the
More informationPhysics 324, Fall Dirac Notation. These notes were produced by David Kaplan for Phys. 324 in Autumn 2001.
Physics 324, Fall 2002 Dirac Notatio These otes were produced by David Kapla for Phys. 324 i Autum 2001. 1 Vectors 1.1 Ier product Recall from liear algebra: we ca represet a vector V as a colum vector;
More informationBernoulli Numbers. n(n+1) = n(n+1)(2n+1) = n(n 1) 2
Beroulli Numbers Beroulli umbers are amed after the great Swiss mathematiia Jaob Beroulli5-705 who used these umbers i the power-sum problem. The power-sum problem is to fid a formula for the sum of the
More informationWind Energy Explained, 2 nd Edition Errata
Wid Eergy Explaied, d Editio Errata This summarizes the ko errata i Wid Eergy Explaied, d Editio. The errata ere origially compiled o July 6, 0. Where possible, the chage or locatio of the chage is oted
More informationu t u 0 ( 7) Intuitively, the maximum principles can be explained by the following observation. Recall
Oct. Heat Equatio M aximum priciple I thi lecture we will dicu the maximum priciple ad uiquee of olutio for the heat equatio.. Maximum priciple. The heat equatio alo ejoy maximum priciple a the Laplace
More informationBasic Waves and Optics
Lasers ad appliatios APPENDIX Basi Waves ad Optis. Eletromageti Waves The eletromageti wave osists of osillatig eletri ( E ) ad mageti ( B ) fields. The eletromageti spetrum is formed by the various possible
More informationChapter 7, Solution 1C.
hapter 7, Solutio 1. he velocity of the fluid relative to the immered olid body ufficietly far away from a body i called the free-tream velocity,. he uptream or approach velocity i the velocity of the
More informationUnbiased Estimation. February 7-12, 2008
Ubiased Estimatio February 7-2, 2008 We begi with a sample X = (X,..., X ) of radom variables chose accordig to oe of a family of probabilities P θ where θ is elemet from the parameter space Θ. For radom
More informationMATHEMATICS. 61. The differential equation representing the family of curves where c is a positive parameter, is of
MATHEMATICS 6 The differetial equatio represetig the family of curves where c is a positive parameter, is of Order Order Degree (d) Degree (a,c) Give curve is y c ( c) Differetiate wrt, y c c y Hece differetial
More information1 1 2 = show that: over variables x and y. [2 marks] Write down necessary conditions involving first and second-order partial derivatives for ( x0, y
Questio (a) A square matrix A= A is called positive defiite if the quadratic form waw > 0 for every o-zero vector w [Note: Here (.) deotes the traspose of a matrix or a vector]. Let 0 A = 0 = show that:
More informationPoornima University, For any query, contact us at: ,18
AIEEE/1/MAHS 1 S. No Questios Solutios Q.1 he circle passig through (1, ) ad touchig the axis of x at (, ) also passes through the poit (a) (, ) (b) (, ) (c) (, ) (d) (, ) Q. ABCD is a trapezium such that
More informationThe Born-Oppenheimer approximation
The Bor-Oppeheimer approximatio 1 Re-writig the Schrödiger equatio We will begi from the full time-idepedet Schrödiger equatio for the eigestates of a molecular system: [ P 2 + ( Pm 2 + e2 1 1 2m 2m m
More informationI. Existence of photon
I. Existee of photo MUX DEMUX 1 ight is a eletromageti wave of a high frequey. Maxwell s equatio H t E 0 E H 0 t E 0 H 0 1 E E E Aos( kzt ) t propagatig eletrial field while osillatig light frequey (Hz)
More informationPAPER : IIT-JAM 2010
MATHEMATICS-MA (CODE A) Q.-Q.5: Oly oe optio is correct for each questio. Each questio carries (+6) marks for correct aswer ad ( ) marks for icorrect aswer.. Which of the followig coditios does NOT esure
More informationEE 508 Lecture 6. Scaling, Normalization and Transformation
EE 508 Lecture 6 Scalig, Normalizatio ad Traformatio Review from Lat Time Dead Network X IN T X OUT T X OUT N T = D D The dead etwork of ay liear circuit i obtaied by ettig ALL idepedet ource to zero.
More informationThe Stokes Theorem. (Sect. 16.7) The curl of a vector field in space
The tokes Theorem. (ect. 6.7) The curl of a vector field i space. The curl of coservative fields. tokes Theorem i space. Idea of the proof of tokes Theorem. The curl of a vector field i space Defiitio
More informationSECTION 2 Electrostatics
SECTION Electrostatics This sectio, based o Chapter of Griffiths, covers effects of electric fields ad forces i static (timeidepedet) situatios. The topics are: Electric field Gauss s Law Electric potetial
More informationChapter 2 Solutions. Prob. 2.1 (a&b) Sketch a vacuum tube device. Graph photocurrent I versus retarding voltage V for several light intensities.
Chapter Solutios Prob..1 (a&b) Sketh a vauum tube devie. Graph photourret I versus retardig voltage V for several light itesities. I light itesity V o V Note that V o remais same for all itesities. ()
More information20. CONFIDENCE INTERVALS FOR THE MEAN, UNKNOWN VARIANCE
20. CONFIDENCE INTERVALS FOR THE MEAN, UNKNOWN VARIANCE If the populatio tadard deviatio σ i ukow, a it uually will be i practice, we will have to etimate it by the ample tadard deviatio. Sice σ i ukow,
More informationTHE SOLAR SYSTEM. We begin with an inertial system and locate the planet and the sun with respect to it. Then. F m. Then
THE SOLAR SYSTEM We now want to apply what we have learned to the olar ytem. Hitorially thi wa the great teting ground for mehani and provided ome of it greatet triumph, uh a the diovery of the outer planet.
More informationState space systems analysis
State pace ytem aalyi Repreetatio of a ytem i tate-pace (tate-pace model of a ytem To itroduce the tate pace formalim let u tart with a eample i which the ytem i dicuio i a imple electrical circuit with
More informationChapter Vectors
Chapter 4. Vectors fter readig this chapter you should be able to:. defie a vector. add ad subtract vectors. fid liear combiatios of vectors ad their relatioship to a set of equatios 4. explai what it
More informationStat 3411 Spring 2011 Assignment 6 Answers
Stat 3411 Sprig 2011 Aigmet 6 Awer (A) Awer are give i 10 3 cycle (a) 149.1 to 187.5 Sice 150 i i the 90% 2-ided cofidece iterval, we do ot reject H 0 : µ 150 v i favor of the 2-ided alterative H a : µ
More information4. Optical Resonators
S. Blair September 3, 2003 47 4. Optial Resoators Optial resoators are used to build up large itesities with moderate iput. Iput Iteral Resoators are typially haraterized by their quality fator: Q w stored
More informationSEISMIC COLLAPSE BEHAVIOUR OF DAMAGED DAMS
13 th World Coferee o Earthquake Egieerig Vaouver, B.C., Caada Augut 1-6, 2004 Paper No. 1958 SEISMIC COLLAPSE BEHAVIOUR O DAMAGED DAMS O. A. PEKAU 1 ad Yuzhu CUI 2 SUMMARY I reet year muh work ha bee
More information1.3 Convergence Theorems of Fourier Series. k k k k. N N k 1. With this in mind, we state (without proof) the convergence of Fourier series.
.3 Covergece Theorems of Fourier Series I this sectio, we preset the covergece of Fourier series. A ifiite sum is, by defiitio, a limit of partial sums, that is, a cos( kx) b si( kx) lim a cos( kx) b si(
More informationMATH Exam 1 Solutions February 24, 2016
MATH 7.57 Exam Solutios February, 6. Evaluate (A) l(6) (B) l(7) (C) l(8) (D) l(9) (E) l() 6x x 3 + dx. Solutio: D We perform a substitutio. Let u = x 3 +, so du = 3x dx. Therefore, 6x u() x 3 + dx = [
More informationMechanics Physics 151
Mechaics Physics 151 Lecture 4 Cotiuous Systems ad Fields (Chapter 13) What We Did Last Time Built Lagragia formalism for cotiuous system Lagragia L = L dxdydz d L L Lagrage s equatio = dx η, η Derived
More informationPhysics 232 Gauge invariance of the magnetic susceptibilty
Physics 232 Gauge ivariace of the magetic susceptibilty Peter Youg (Dated: Jauary 16, 2006) I. INTRODUCTION We have see i class that the followig additioal terms appear i the Hamiltoia o addig a magetic
More informationDigital Signal Processing, Fall 2010
Digital Sigal Proeig, Fall 2 Leture 3: Samplig ad reotrutio, traform aalyi of LTI ytem tem Zheg-ua Ta Departmet of Eletroi Sytem Aalborg Uiverity, Demar t@e.aau.d Coure at a glae MM Direte-time igal ad
More informationProfessor: Mihnea UDREA DIGITAL SIGNAL PROCESSING. Grading: Web: MOODLE. 1. Introduction. General information
Geeral iformatio DIGITL SIGL PROCESSIG Profeor: ihea UDRE B29 mihea@comm.pub.ro Gradig: Laboratory: 5% Proect: 5% Tet: 2% ial exam : 5% Coure quiz: ±% Web: www.electroica.pub.ro OODLE 2 alog igal proceig
More informationx z Increasing the size of the sample increases the power (reduces the probability of a Type II error) when the significance level remains fixed.
] z-tet for the mea, μ If the P-value i a mall or maller tha a pecified value, the data are tatitically igificat at igificace level. Sigificace tet for the hypothei H 0: = 0 cocerig the ukow mea of a populatio
More informationMATHEMATICS Code No. 13 INSTRUCTIONS
DO NOT OPEN THIS TEST BOOKLET UNTIL YOU ARE ASKED TO DO SO COMBINED COMPETITIVE (PRELIMINARY) EXAMINATION, 0 Serial No. MATHEMATICS Code No. A Time Allowed : Two Hours Maimum Marks : 00 INSTRUCTIONS. IMMEDIATELY
More informationFINALTERM EXAMINATION Fall 9 Calculus & Aalytical Geometry-I Questio No: ( Mars: ) - Please choose oe Let f ( x) is a fuctio such that as x approaches a real umber a, either from left or right-had-side,
More informationECE 330:541, Stochastic Signals and Systems Lecture Notes on Limit Theorems from Probability Fall 2002
ECE 330:541, Stochastic Sigals ad Systems Lecture Notes o Limit Theorems from robability Fall 00 I practice, there are two ways we ca costruct a ew sequece of radom variables from a old sequece of radom
More informationPhys 6303 Final Exam Solutions December 19, 2012
Phys 633 Fial Exam s December 19, 212 You may NOT use ay book or otes other tha supplied with this test. You will have 3 hours to fiish. DO YOUR OWN WORK. Express your aswers clearly ad cocisely so that
More informationPulsed Magnet Crimping
Puled Magnet Crimping Fred Niell 4/5/00 1 Magnetic Crimping Magnetoforming i a metal fabrication technique that ha been in ue for everal decade. A large capacitor bank i ued to tore energy that i ued to
More informationEE 508 Lecture 6. Dead Networks Scaling, Normalization and Transformations
EE 508 Lecture 6 Dead Network Scalig, Normalizatio ad Traformatio Filter Cocept ad Termiology 2-d order polyomial characterizatio Biquadratic Factorizatio Op Amp Modelig Stability ad Itability Roll-off
More informationMathematics Extension 2
009 HIGHER SCHOOL CERTIFICATE EXAMINATION Mathematics Etesio Geeral Istructios Readig time 5 miutes Workig time hours Write usig black or blue pe Board-approved calculators may be used A table of stadard
More informationCollective modes in superfluid helium when there is a relative velocity between the normal and superfluid components
Fizika Nizkikh emperatur, 008, v 3, No /5, p 357 366 Colletive mode i uperfluid helium he there i a relative veloity betee the ormal ad uperfluid ompoet IN Adameko, KE Nemheko, ad VA lipko VN Karazi Kharkov
More informationHidden Markov Model Parameters
.PPT 5/04/00 Lecture 6 HMM Traiig Traiig Hidde Markov Model Iitial model etimate Viterbi traiig Baum-Welch traiig 8.7.PPT 5/04/00 8.8 Hidde Markov Model Parameter c c c 3 a a a 3 t t t 3 c a t A Hidde
More informationBrief Review of Linear System Theory
Brief Review of Liear Sytem heory he followig iformatio i typically covered i a coure o liear ytem theory. At ISU, EE 577 i oe uch coure ad i highly recommeded for power ytem egieerig tudet. We have developed
More informationEECE 301 Signals & Systems Prof. Mark Fowler
EECE 30 Sigal & Sytem Prof. Mark Fowler Note Set #8 C-T Sytem: Laplace Traform Solvig Differetial Equatio Readig Aigmet: Sectio 6.4 of Kame ad Heck / Coure Flow Diagram The arrow here how coceptual flow
More informationSTUDENT S t-distribution AND CONFIDENCE INTERVALS OF THE MEAN ( )
STUDENT S t-distribution AND CONFIDENCE INTERVALS OF THE MEAN Suppoe that we have a ample of meaured value x1, x, x3,, x of a igle uow quatity. Aumig that the meauremet are draw from a ormal ditributio
More informationPHYS-3301 Lecture 7. CHAPTER 4 Structure of the Atom. Rutherford Scattering. Sep. 18, 2018
CHAPTER 4 Structure of the Atom PHYS-3301 Lecture 7 4.1 The Atomic Models of Thomso ad Rutherford 4.2 Rutherford Scatterig 4.3 The Classic Atomic Model 4.4 The Bohr Model of the Hydroge Atom 4.5 Successes
More informationj=1 dz Res(f, z j ) = 1 d k 1 dz k 1 (z c)k f(z) Res(f, c) = lim z c (k 1)! Res g, c = f(c) g (c)
Problem. Compute the itegrals C r d for Z, where C r = ad r >. Recall that C r has the couter-clockwise orietatio. Solutio: We will use the idue Theorem to solve this oe. We could istead use other (perhaps
More informationMath 113, Calculus II Winter 2007 Final Exam Solutions
Math, Calculus II Witer 7 Fial Exam Solutios (5 poits) Use the limit defiitio of the defiite itegral ad the sum formulas to compute x x + dx The check your aswer usig the Evaluatio Theorem Solutio: I this
More informationFundamental Concepts: Surfaces and Curves
UNDAMENTAL CONCEPTS: SURACES AND CURVES CHAPTER udametal Cocepts: Surfaces ad Curves. INTRODUCTION This chapter describes two geometrical objects, vi., surfaces ad curves because the pla a ver importat
More information17. Joint distributions of extreme order statistics Lehmann 5.1; Ferguson 15
17. Joit distributios of extreme order statistics Lehma 5.1; Ferguso 15 I Example 10., we derived the asymptotic distributio of the maximum from a radom sample from a uiform distributio. We did this usig
More informationSolutions to Final Exam Review Problems
. Let f(x) 4+x. Solutios to Fial Exam Review Problems Math 5C, Witer 2007 (a) Fid the Maclauri series for f(x), ad compute its radius of covergece. Solutio. f(x) 4( ( x/4)) ( x/4) ( ) 4 4 + x. Sice the
More informationAfter the completion of this section the student. V.4.2. Power Series Solution. V.4.3. The Method of Frobenius. V.4.4. Taylor Series Solution
Chapter V ODE V.4 Power Series Solutio Otober, 8 385 V.4 Power Series Solutio Objetives: After the ompletio of this setio the studet - should reall the power series solutio of a liear ODE with variable
More informationChemistry 2. Assumed knowledge. Learning outcomes. The particle on a ring j = 3. Lecture 4. Cyclic π Systems
Chemistry Leture QuatitativeMO Theoryfor Begiers: Cyli Systems Assumed kowledge Be able to predit the umber of eletros ad the presee of ougatio i a rig otaiig arbo ad/or heteroatoms suh as itroge ad oxyge.
More informationThis section is optional.
4 Momet Geeratig Fuctios* This sectio is optioal. The momet geeratig fuctio g : R R of a radom variable X is defied as g(t) = E[e tx ]. Propositio 1. We have g () (0) = E[X ] for = 1, 2,... Proof. Therefore
More informationChapter 8.2. Interval Estimation
Chapter 8.2. Iterval Etimatio Baic of Cofidece Iterval ad Large Sample Cofidece Iterval 1 Baic Propertie of Cofidece Iterval Aumptio: X 1, X 2,, X are from Normal ditributio with a mea of µ ad tadard deviatio.
More informationA Mean Paradox. John Konvalina, Jack Heidel, and Jim Rogers. Department of Mathematics University of Nebraska at Omaha Omaha, NE USA
A Mea Paradox by Joh Kovalia, Jac Heidel, ad Jim Rogers Departmet of Mathematics Uiversity of Nebrasa at Omaha Omaha, NE 6882-243 USA Phoe: (42) 554-2836 Fax: (42) 554-2975 E-mail: joho@uomaha.edu A Mea
More informationLast time: Completed solution to the optimum linear filter in real-time operation
6.3 tochatic Etimatio ad Cotrol, Fall 4 ecture at time: Completed olutio to the oimum liear filter i real-time operatio emi-free cofiguratio: t D( p) F( p) i( p) dte dp e π F( ) F( ) ( ) F( p) ( p) 4444443
More informationCapacitors and PN Junctions. Lecture 8: Prof. Niknejad. Department of EECS University of California, Berkeley. EECS 105 Fall 2003, Lecture 8
CS 15 Fall 23, Lecture 8 Lecture 8: Capacitor ad PN Juctio Prof. Nikejad Lecture Outlie Review of lectrotatic IC MIM Capacitor No-Liear Capacitor PN Juctio Thermal quilibrium lectrotatic Review 1 lectric
More information24 MATH 101B: ALGEBRA II, PART D: REPRESENTATIONS OF GROUPS
24 MATH 101B: ALGEBRA II, PART D: REPRESENTATIONS OF GROUPS Corollary 2.30. Suppose that the semisimple decompositio of the G- module V is V = i S i. The i = χ V,χ i Proof. Sice χ V W = χ V + χ W, we have:
More informationIIT JAM Mathematical Statistics (MS) 2006 SECTION A
IIT JAM Mathematical Statistics (MS) 6 SECTION A. If a > for ad lim a / L >, the which of the followig series is ot coverget? (a) (b) (c) (d) (d) = = a = a = a a + / a lim a a / + = lim a / a / + = lim
More informationJEE(Advanced) 2018 TEST PAPER WITH SOLUTION (HELD ON SUNDAY 20 th MAY, 2018)
JEE(Advaced) 08 TEST PAPER WITH SOLUTION (HELD ON SUNDAY 0 th MAY, 08) PART- : JEE(Advaced) 08/Paper- SECTION. For ay positive iteger, defie ƒ : (0, ) as ƒ () j ta j j for all (0, ). (Here, the iverse
More informationBernoulli s equation may be developed as a special form of the momentum or energy equation.
BERNOULLI S EQUATION Bernoulli equation may be developed a a pecial form of the momentum or energy equation. Here, we will develop it a pecial cae of momentum equation. Conider a teady incompreible flow
More informationKinetics of Complex Reactions
Kietics of Complex Reactios by Flick Colema Departmet of Chemistry Wellesley College Wellesley MA 28 wcolema@wellesley.edu Copyright Flick Colema 996. All rights reserved. You are welcome to use this documet
More informationMathematics 170B Selected HW Solutions.
Mathematics 17B Selected HW Solutios. F 4. Suppose X is B(,p). (a)fidthemometgeeratigfuctiom (s)of(x p)/ p(1 p). Write q = 1 p. The MGF of X is (pe s + q), sice X ca be writte as the sum of idepedet Beroulli
More information4. Basic probability theory
Cotets Basic cocepts Discrete radom variables Discrete distributios (br distributios) Cotiuous radom variables Cotiuous distributios (time distributios) Other radom variables Lect04.ppt S-38.45 - Itroductio
More informationTopic 5 [434 marks] (i) Find the range of values of n for which. (ii) Write down the value of x dx in terms of n, when it does exist.
Topic 5 [44 marks] 1a (i) Fid the rage of values of for which eists 1 Write dow the value of i terms of 1, whe it does eist Fid the solutio to the differetial equatio 1b give that y = 1 whe = π (cos si
More informationLecture 16. Kinetics and Mass Transfer in Crystallization
Leture 16. Kineti and Ma Tranfer in Crytallization Crytallization Kineti Superaturation Nuleation - Primary nuleation - Seondary nuleation Crytal Growth - Diffuion-reation theory - Srew-diloation theory
More informationCOMPUTING SUMS AND THE AVERAGE VALUE OF THE DIVISOR FUNCTION (x 1) + x = n = n.
COMPUTING SUMS AND THE AVERAGE VALUE OF THE DIVISOR FUNCTION Abstract. We itroduce a method for computig sums of the form f( where f( is ice. We apply this method to study the average value of d(, where
More informationCHAPTER 8 SYSTEMS OF PARTICLES
CHAPTER 8 SYSTES OF PARTICLES CHAPTER 8 COLLISIONS 45 8. CENTER OF ASS The ceter of mass of a system of particles or a rigid body is the poit at which all of the mass are cosidered to be cocetrated there
More informationCOMPUTING FOURIER SERIES
COMPUTING FOURIER SERIES Overview We have see i revious otes how we ca use the fact that si ad cos rereset comlete orthogoal fuctios over the iterval [-,] to allow us to determie the coefficiets of a Fourier
More informationLecture 7: Properties of Random Samples
Lecture 7: Properties of Radom Samples 1 Cotiued From Last Class Theorem 1.1. Let X 1, X,...X be a radom sample from a populatio with mea µ ad variace σ
More informationIntroduction to Astrophysics Tutorial 2: Polytropic Models
Itroductio to Astrophysics Tutorial : Polytropic Models Iair Arcavi 1 Summary of the Equatios of Stellar Structure We have arrived at a set of dieretial equatios which ca be used to describe the structure
More informationG. Monti 1 and S. Alessandri 2. Professor, Dept. of Structural Engineering and Geotechnics, Sapienza, University of Rome, Rome, Italy 2
The 4 th World Coferee o Earthquake Egieerig Otober -7, 008, Beijig, Chia DESIGN EQUATIONS FOR EVALUATION OF STRENGTH AND DEFORMATION CAPACITY FOR UNSTRENGTHENED AND FRP STRENGTHENED RC RECTANGULAR COLUMNS
More informationSolution of EECS 315 Final Examination F09
Solutio of EECS 315 Fial Examiatio F9 1. Fid the umerical value of δ ( t + 4ramp( tdt. δ ( t + 4ramp( tdt. Fid the umerical sigal eergy of x E x = x[ ] = δ 3 = 11 = ( = ramp( ( 4 = ramp( 8 = 8 [ ] = (
More informationLast time: Ground rules for filtering and control system design
6.3 Stochatic Etimatio ad Cotrol, Fall 004 Lecture 7 Lat time: Groud rule for filterig ad cotrol ytem deig Gral ytem Sytem parameter are cotaied i w( t ad w ( t. Deired output i grated by takig the igal
More informationPrincipal Component Analysis. Nuno Vasconcelos ECE Department, UCSD
Priipal Compoet Aalysis Nuo Vasoelos ECE Departmet, UCSD Curse of dimesioality typial observatio i Bayes deisio theory: error ireases whe umber of features is large problem: eve for simple models (e.g.
More informationThe axial dispersion model for tubular reactors at steady state can be described by the following equations: dc dz R n cn = 0 (1) (2) 1 d 2 c.
5.4 Applicatio of Perturbatio Methods to the Dispersio Model for Tubular Reactors The axial dispersio model for tubular reactors at steady state ca be described by the followig equatios: d c Pe dz z =
More informationDiscrete Mathematics for CS Spring 2007 Luca Trevisan Lecture 22
CS 70 Discrete Mathematics for CS Sprig 2007 Luca Trevisa Lecture 22 Aother Importat Distributio The Geometric Distributio Questio: A biased coi with Heads probability p is tossed repeatedly util the first
More informationCS284A: Representations and Algorithms in Molecular Biology
CS284A: Represetatios ad Algorithms i Molecular Biology Scribe Notes o Lectures 3 & 4: Motif Discovery via Eumeratio & Motif Represetatio Usig Positio Weight Matrix Joshua Gervi Based o presetatios by
More informationLecture 8. Dirac and Weierstrass
Leture 8. Dira ad Weierstrass Audrey Terras May 5, 9 A New Kid of Produt of Futios You are familiar with the poitwise produt of futios de ed by f g(x) f(x) g(x): You just tae the produt of the real umbers
More informationPHY4905: Nearly-Free Electron Model (NFE)
PHY4905: Nearly-Free Electro Model (NFE) D. L. Maslov Departmet of Physics, Uiversity of Florida (Dated: Jauary 12, 2011) 1 I. REMINDER: QUANTUM MECHANICAL PERTURBATION THEORY A. No-degeerate eigestates
More informationESTIMATION OF MACHINING ERRORS ON GLEASON BEVEL
5 th INTERNATIONAL MEETING OF THE CARPATHIAN REGION SPECIALISTS IN THE FIELD OF GEARS ESTIMATION OF MACHINING ERRORS ON GLEASON BEVEL GEAR CUTTING BOB, Daila UNIO SA Satu Mare - 35, Luia Blaga Blvd, 39
More information16th International Symposium on Ballistics San Francisco, CA, September 1996
16th Iteratioal Symposium o Ballistis Sa Fraiso, CA, 3-8 September 1996 GURNEY FORULAS FOR EXPLOSIVE CHARGES SURROUNDING RIGID CORES William J. Flis, Dya East Corporatio, 36 Horizo Drive, Kig of Prussia,
More informationLesson 03 Heat Equation with Different BCs
PDE & Complex Variables P3- esso 3 Heat Equatio with Differet BCs ( ) Physical meaig (SJF ) et u(x, represet the temperature of a thi rod govered by the (coductio) heat equatio: u t =α u xx (3.) where
More informationHeat Equation: Maximum Principles
Heat Equatio: Maximum Priciple Nov. 9, 0 I thi lecture we will dicu the maximum priciple ad uiquee of olutio for the heat equatio.. Maximum priciple. The heat equatio alo ejoy maximum priciple a the Laplace
More information2.1. The Algebraic and Order Properties of R Definition. A binary operation on a set F is a function B : F F! F.
CHAPTER 2 The Real Numbers 2.. The Algebraic ad Order Properties of R Defiitio. A biary operatio o a set F is a fuctio B : F F! F. For the biary operatios of + ad, we replace B(a, b) by a + b ad a b, respectively.
More informationMath 5C Discussion Problems 2 Selected Solutions
Math 5 iscussio Problems 2 elected olutios Path Idepedece. Let be the striaght-lie path i 2 from the origi to (3, ). efie f(x, y) = xye xy. (a) Evaluate f dr. olutio. (b) Evaluate olutio. (c) Evaluate
More informationMath 155 (Lecture 3)
Math 55 (Lecture 3) September 8, I this lecture, we ll cosider the aswer to oe of the most basic coutig problems i combiatorics Questio How may ways are there to choose a -elemet subset of the set {,,,
More informationDefinitions and Theorems. where x are the decision variables. c, b, and a are constant coefficients.
Defiitios ad Theorems Remember the scalar form of the liear programmig problem, Miimize, Subject to, f(x) = c i x i a 1i x i = b 1 a mi x i = b m x i 0 i = 1,2,, where x are the decisio variables. c, b,
More informationChapter 9. Key Ideas Hypothesis Test (Two Populations)
Chapter 9 Key Idea Hypothei Tet (Two Populatio) Sectio 9-: Overview I Chapter 8, dicuio cetered aroud hypothei tet for the proportio, mea, ad tadard deviatio/variace of a igle populatio. However, ofte
More informationSociété de Calcul Mathématique, S. A. Algorithmes et Optimisation
Société de Calcul Mathématique S A Algorithme et Optimiatio Radom amplig of proportio Berard Beauzamy Jue 2008 From time to time we fid a problem i which we do ot deal with value but with proportio For
More informationExponential Families and Bayesian Inference
Computer Visio Expoetial Families ad Bayesia Iferece Lecture Expoetial Families A expoetial family of distributios is a d-parameter family f(x; havig the followig form: f(x; = h(xe g(t T (x B(, (. where
More informationIndian Institute of Information Technology, Allahabad. End Semester Examination - Tentative Marking Scheme
Idia Istitute of Iformatio Techology, Allahabad Ed Semester Examiatio - Tetative Markig Scheme Course Name: Mathematics-I Course Code: SMAT3C MM: 75 Program: B.Tech st year (IT+ECE) ate of Exam:..7 ( st
More informationEDEXCEL NATIONAL CERTIFICATE UNIT 4 MATHEMATICS FOR TECHNICIANS OUTCOME 4 - CALCULUS
EDEXCEL NATIONAL CERTIFICATE UNIT 4 MATHEMATICS FOR TECHNICIANS OUTCOME 4 - CALCULUS TUTORIAL 1 - DIFFERENTIATION Use the elemetary rules of calculus arithmetic to solve problems that ivolve differetiatio
More informationCS 270 Algorithms. Oliver Kullmann. Growth of Functions. Divide-and- Conquer Min-Max- Problem. Tutorial. Reading from CLRS for week 2
Geeral remarks Week 2 1 Divide ad First we cosider a importat tool for the aalysis of algorithms: Big-Oh. The we itroduce a importat algorithmic paradigm:. We coclude by presetig ad aalysig two examples.
More information