22.05 Reactor Physics - Part Twenty. Extension of Group Theory to Reactors of Multiple Regions One Energy Group *

Size: px
Start display at page:

Download "22.05 Reactor Physics - Part Twenty. Extension of Group Theory to Reactors of Multiple Regions One Energy Group *"

Transcription

1 22.5 eaor Phyi - Par Tweny Exenion o Group Theory o eaor o Muliple egion One Energy Group *. Baground: The objeive reain o deerine Φ ( or reaor o inie ize. The ir uh ae ha we exained wa a bare hoogeneou ore. The ajor ep in he oluion were o: Modiy he oninuou energy diuion equaion, in whih ro-eion and lux were union o r and E or a hoogeneou ediu. Hene, ro-eion beoe union o E alone. Flux reain a union o r and E. Aue eparabiliy o he energy and paial union o he lux. Tha i Φ( = ( E). Subiue he eparabiliy aupion ino he hoogenized diuion equaion and eparae er o ha a union o poiion equal a union o energy. Thi i only poible i boh union equal a onan. Thi 2 onan i alled he buling,. Solve or he paial oluion. B r Subiue he paial oluion ino he hoogenized diuion equaion. Deine group onan wihin eah energy group. Solve or he energy dependene o he lux. Thi equene i unique o a bare (unreleed) ore and i NOT he general ae. Speiially, or ore o uliple region (uel/oderaor and releo, he eparabiliy aupion doe no hold. A a reul, he equene or obaining a oluion or Φ ( hange. In pariular, he energy dependene i obained beore he paial dependene. * Maerial in hi eion ollow ha o Henry pp Porion ha are verbai are indiaed by quoaion.

2 The proble i onidered here or a wo region reaor wih one energy group being aued. In he nex eion o hee noe, we onider a wo region reaor wih wo energy group. Finally, we exend he idea o uliple region reaor wih uliple energy group. 2. One Energy Group: The er one-group heory i ued o deribe everal dieren ehod o oluion in reaor phyi. Earlier (Seion o hee noe) we derived a oneveloiy odel and ued i o olve or he paial lux in bare ore. Tha approah i oen alled one-group heory beaue he ingle veloiy orrepond o a ingle energy group. Bu, a diinion hould be ade beween ha derivaion and wha we will do nex beaue, even hough he reul i he ae, he ehod o derivaion eployed here i ar ore rigorou. The aring poin i he oninuou energy diuion equaion whih we reae below: D( r, E) Φ( r, E) + Σ = χ j j j (E) ν Σ j ( r, E ) + Σ ( r, E) Φ( r, E) For a hoogeneou ediu, hi beoe: ( r, E E) Φ ( r, E )de 2 D(E) Φ( + Σ (E) Φ( = (E) (E ) (E E) (,E )de χ νσ + Σ λ Φ r We wih o apply hi equaion o a wo region reaor ubje o he aupion ha eah region i hoogeneou. Thu, we odiy he above equaion by adding a uperrip o eah paraeer (D, Σ, Σ, Σ,e.). A given value o hi uperrip orrepond o a pariular region. For exaple, = igh be ore/oderaor; =2 igh be releor, =3 igh be hielding, e. The equaion beoe: D (E) Φ( + Σ (E) Φ( = (E) (E ) (E E) (,E )de χ νσ + Σ Φ r λ ( =, 2, 3,..., K) For he ae a hand, = 2 beaue here are wo phyial region. (Noe: The one in one-group heory reer o he nuber o energy group and hene here i one energy union (E) ha will apply o eah region.) We an now ee why he eparabiliy aupion ( Φ (=(ψ(e)) ha wa ued or he (A) 2

3 hoogeneou bare ore (=) will no wor or a uli-region reaor ( 2). Eah region ha i own e o aerial properie (i.e., D, Σ, e.) A ingle union ψ(e) anno aiy dieren e o properie. A preerred approah, and one ha i viable, i o reognize ha aer a ew olliion, neuron behavior i independen o neuron origin. Thu, he neuron energy peru in a given region hould be haraerii o only he hoogenized aerial ha are preen in ha region. Thu, we aue eparabiliy wihin eah region. Here he word wihin iplie a ew ean pah inide a given region. Thu, we aue: Φ( (E) (B) Where (E) i an energy peru union or region. Thi i he eenial aupion o one-group diuion heory. A a reul o aing i, we an urher aue ha, wihin a given region, he ype o analyi done or he bare hoogeneou reaor reain relevan. Thu, he eenial raegy o one-group diuion heory i: ) aue ha eparabily (equaion B above) i valid wihin eah region ; 2) ind an appropriae peru union ψ (E) or eah region; and 3) onne he paial union ( or eah region o he orreponding paial union o neighboring region. (Henry, p. 46). Given he above raegy, we expe ha he leaage er an be approxiaed a: ( B ) 2 2 ( B ) (,E) D (E) Φ( = D (E) Φ r Where i a nuber and i alled he aerial buling. For he ingle 2 region reaor, we enounered a iilar quaniy, B r, whih depended on he geoery o he reaor and wa ered he geoeri buling. The aerial buling i dieren. Speiially, ( B ) 2 ha nohing o do wih eiher he geoery o he reaor or o an individual region. I i ound by reognizing ha eah region i par o a riial reaor or whih λ i uniy. Hene, ( B ) 2 i ound by wriing he hoogeneou diuion equaion or eah region a: D (E) 2 ( B ) + Σ (E) Φ( r,e) = χ (E) νσ (E ) + Σ (E E) Φ( r,e )de λ or r in he inerior o region, 3

4 ) 2 and eleing ( B a he eigenvalue ha yield an everywhere poiive oluion or he lux. I i iporan o underand he phyial eaning o hi nuber and we quoe ro Henry (p. 46): ( ) 2 B The nuber i haraerii o he ixure o aerial aing up region and, or ha reaon, i alled he aerial buling. Maheaially i i an eigenvalue o he hoogeneou equaion. A an be een ro ha equaion, i ee on neuron balane i o regulae he leaage rae o ha he porion o he reaor in he inerior o region behave in a uained, riial ahion. I he o ha region exeed uniy, he nuber o neuron reoved ro de dv per eond by ou-leaage, aering, and aborpion will equal he nuber inrodued ino de dv by iioning and aering ro oher energie; while, i he i le han uniy, he nuber reoved by aering and aborpion will equal he nuber inrodued by iioning, aering, and leaage ino he region. Thu, i he or region- aerial i le han uniy, ( ) 2 B will be a negaive nuber o ha he exra neuron needed or overall balane will be upplied by negaive leaage, i.e., by ne leaage ino dv. In releor aerial, or whih ( ) 2 νσ ( E) =, will alway be negaive. (Henry, pp ) B We now ubiue Φ( = (E) ino he odiied hoogeneou diuion equaion or region, eliinae he paial union, and obain: D (E) 2 ( B ) (E) + Σ (E) (E) = [ χ (E) νσ (E ) + Σ (E E) ] (E )de (C) Thi relaion an be olved uing he ehod developed earlier (Seion 6 o hee noe) o ind (E). I will be realled ha he approah i o divide he energy range (- MeV) ino G group where G igh be a large a 3. The widh o eah group, ΔE g, i eleed o ha ro-eion properie will be onan over ha group. Thi allow a urher aupion ha he lux (E) will be onan over eah group. Group onan an now be deined. Thee are o he or: g E g Eg Σg Eg Σ E (E) g g Noe ha hee group onan are deined: ) or an aued lux hape, (E) and 2) a narrow energy range, Δ E g. Thi will be in onra o a dieren e o 4

5 group onan ha we will deine laer when we olve or paial lux hape. Ue o he above group onan allow u o rewrie Equaion (C) a a e o algebrai relaion, whih are readily olvable nuerially. So, a hi poin we an obain (E). The objeive hereore beoe o obain he paial lux hape. Thu ar he derivaion ha been rigorou. Bu a proble now arie in ha we have o rea he inerae beween region. The preerred boundary ondiion are he andard one ha lux and he noral oponen o he urren be oninuou a all energie. However, hi in poible beaue he (E) dier or eah region. To quoe Henry (p. 47), The bai proble i ha he eparable or (E) (=,2, K,), whih are good approxiaion o Φ(r, E) in he inerior porion o he region, anno be valid near inerae beween region, ine, i uperrip and l deignae wo adjaen region o dieren opoiion o ha (E) and l (E) are dieren union o E, hen, i r i any poin on he inerae beween hee region, ( r ) (E) anno equal ( r ) (E) or all energie. (I i did, hen (E) would have o have he ae energy hape (E). Thu, auing ha he eparable or (E) i valid hroughou eah region ae i ipoible o ee he oninuiy-o-lux boundary ondiion a he inerae beween region. The be one an do i o adop he uh weaer boundary ondiion ha he inegral over all energie o Φ ( and n Φ(r, E) be oninuou. Thi boundary ondiion i enirely onien wih he oninuiy o Φ ( and n D Φ( a all energie ine, i here were oninuiy a eah energy, he inegral over all energie would erainly be oninuou. (The revere ipliaion anno, o oure, be drawn.) To be peii, one-group heory i baed on he ollowing aupion:. Φ( r,e) = ( (E) hroughou eah opoiion, (E) being ound by olving Equaion C a deribed above. 2. I and l indiae any wo adjaen opoiion and r i a poin on he inerae, we require ha and de de n ( r ) D (E) = (E) [ ( r ) (E)] = den D (E) [ de ( r ) (E) ( r ) (E) Noe: I (E) i noralized o ha =, hen hee ondiion beoe: ] 5

6 and ( r ) = ( r ) D (E) n ( r ) = D (E) n ( r ) We now ubiue he eparabiliy relaion (equaion labeled a B above) ino he hoogenized diuion equaion or eah region (equaion labeled a (A) above) and inegrae over all energie o a o oply wih he boundary ondiion. The reul i: = χ λ D (E) (E) (E ) (E )de νσ (E ) (E )de = νσ λ + + de de (E E) (E ) Σ (E ) (E )de + Σ Σ (E) Nex, we deine a e o one-group ro-eion: (D) D Σ νσ Σ Σ Σ D (E ) Σ (E ) Σ = Σ Σ (E ) νσ (E ) a Thee nuber are independen o boh pae and energy. They ay be opued or any region one we have deerined he nulear onenraion n j and he iroopi ro-eion σ j (E) o he aerial in region and have obained he peru union (E). (Henry, pp ) I i iporan o reognize he dierene beween hee group onan ha are ued o obain he paial lux hape ro he one deined earlier o obain he energy lux hape. Fir, he urren group onan (paial alulaion) are 6

7 inegraed over a very wide energy range. Here, ha range i o. The ore oon range and he one ha we ue laer on are heral, epiheral, and a. Seond, he hape o (E) i nown. Thi i wha allow evaluaion o he inegraion over uh wide range. One oher lariiaion i appropriae. The word group a ued here reer o he nuber o energy range over whih he above inegraion are perored. For he preen e o leure noe, here i one range ( o ) and hene one group. The ore oon approah, a i already noed, i or hree range (heral, epiheral, and a) and hene hree group. Upon ubiuion o hoe one-group ro-eion, we obain: D + Σ Wih boundary ondiion: n ( r ) = ( r ) D ( r ) = n = νσ λ D ( r ) The ondiion ha he lux i o vanih on he exernal urae o he reaor i e by requiring ha he appropriae ( vanih or any r on ha urae. Finally, ine ( i everywhere oninuou hroughou he reaor, he uperrip i redundan. The poin r auoaially peiie he region. Aordingly, we hall replae all he ( by he ingle union Φ(, he onegroup alar lux. (Noe ha Φ( i no a lux per uni energy; i uni are (peed) x (neuron/) = neuron per quare per e.) Wih hi hange in noaion he one-group diuion equaion or a reaor opoed o everal hoogeneou region beoe D Φ( + Σ Φ( = νσ λ Wih he ollowing boundary ondiion: Φ(. Φ ( and he noral oponen n D Φ( are oninuou aro inerae beween dieren opoiion; 2. Φ = on he ouer boundary o he reaor. 7

8 The above equaion i oeie alled he one-veloiy diuion equaion ine i an alo be derived by auing ha all he neuron are raveling a a ingle peed. The rouble wih ha approah i ha i provide no yeai proedure or inding he one-group onan D, Σ, and νσ, and ae i hard o aoun or uh ee a a iion, reonane apure, and a-neuron leaage. I alo ae one-group heory appear uh ruder han i aually i. Aording o he view we have adoped, he one-group heory aually provide a very deailed energy-dependen lux, naely, (E) Φ(, in eah region. The eenial approxiaion oni o a very rude reaen o he raniion zone beween he dieren aerial opoiion. In hee zone he rue alar lux deniy Φ ( aually hange gradually ro he (E) appropriae o he inerior par o one region o ha appropriae o he inerior par o he nex. We replae hi gradual hange by an abrup one and in o doing ae an error in he ne leaage rae ro one region o he nex. (Henry, pp. 49-5) I i iporan o reognize ha or hi uli-region reaor exaple, he peral (or energy) union are ideniied beore he paial oluion i obained. The laer i done nuerially uing inie dierene equaion. 3. Suary. Conider he reaor ha i o be analyzed and he deired auray o he oluion. Deerine: a) The nuber o diin region ino whih he reaor will be divided (i.e., uel/oderaor; releor; hield) b) The nuber o energy group ha will be ued when obaining he hape o he paial lux. (Noe: The nuber ued o deerine he hape o he energy lux i norally everal houand.) 2. Wrie ou he oninuou energy diuion equaion or eah region. Aue hoogeneiy wihin eah region. 3. Aue eparabiliy o he lux (i.e., Φ( (E)) wihin eah region. 4. Approxiae he leaage er via he relaion: 2 ( B ) (,E) D (E) Φ( = D (E) Φ r 8

9 Thi i obained by analogy wih he bare hoogeneou ae where we were able o olve direly or he paial par. 5. Subiue eparabiliy (ep 3) ino he equaion ep (4) and eliinae (. Solve he reuling equaion or (E) by dividing he ull energy range ino everal houand group, aing he lux hape a onan over eah group, and deining group onan over eah Δ E. 6. Sele boundary ondiion in an inegral ene. The range() o inegraion on he boundary ondiion i he ae a he range() hoen or he nuber o energy group ued o opue he paial lux. 7. Cobine he eparabiliy relaion, he oluion or (E), and he deiniion o he boundary ondiion o obain he equaion labeled a D in he noe. 8. Deine a e o group ro-eion ha are o be inegraed over he energy range() eleed or he paial lux deerinaion. Evaluae hee group onan hi i poible beaue (E) i now nown. 9. ewrie he inegral equaion labeled a D a a e o algebrai one. Solve, nuerially.. eadju uel onenraion, e., and repea he alulaion unil a deign or whih λ= i obained. When deigning an aual reaor, i i oon praie o do ep () (5) o he above equene only one. I i hen aued ha (E) i ineniive o all hange in aerial onenraion and/or geoery. Sep (6) () are hen done any ie unil a riial oniguraion i ideniied. Thi approah redue opuer ie beaue Sep 5 whih involve houand o group i only done one. g 9

Direct Sequence Spread Spectrum II

Direct Sequence Spread Spectrum II DS-SS II 7. Dire Sequene Spread Speru II ER One igh hink ha DS-SS would have he following drawak. Sine he RF andwidh i ie ha needed for a narrowand PSK ignal a he ae daa rae R, here will e ie a uh noie

More information

How to Solve System Dynamic s Problems

How to Solve System Dynamic s Problems How o Solve Sye Dynaic Proble A ye dynaic proble involve wo or ore bodie (objec) under he influence of everal exernal force. The objec ay uliaely re, ove wih conan velociy, conan acceleraion or oe cobinaion

More information

Notes on MRI, Part II

Notes on MRI, Part II BME 483 MRI Noe : page 1 Noe on MRI, Par II Signal Recepion in MRI The ignal ha we deec in MRI i a volage induced in an RF coil by change in agneic flu fro he preceing agneizaion in he objec. One epreion

More information

8.1. a) For step response, M input is u ( t) Taking inverse Laplace transform. as α 0. Ideal response, K c. = Kc Mτ D + For ramp response, 8-1

8.1. a) For step response, M input is u ( t) Taking inverse Laplace transform. as α 0. Ideal response, K c. = Kc Mτ D + For ramp response, 8-1 8. a For ep repone, inpu i u, U Y a U α α Y a α α Taking invere Laplae ranform a α e e / α / α A α 0 a δ 0 e / α a δ deal repone, α d Y i Gi U i δ Hene a α 0 a i For ramp repone, inpu i u, U Soluion anual

More information

Linear Motion, Speed & Velocity

Linear Motion, Speed & Velocity Add Iporan Linear Moion, Speed & Velociy Page: 136 Linear Moion, Speed & Velociy NGSS Sandard: N/A MA Curriculu Fraework (2006): 1.1, 1.2 AP Phyic 1 Learning Objecive: 3.A.1.1, 3.A.1.3 Knowledge/Underanding

More information

Physics 240: Worksheet 16 Name

Physics 240: Worksheet 16 Name Phyic 4: Workhee 16 Nae Non-unifor circular oion Each of hee proble involve non-unifor circular oion wih a conan α. (1) Obain each of he equaion of oion for non-unifor circular oion under a conan acceleraion,

More information

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 31 Signal & Syem Prof. Mark Fowler Noe Se #27 C-T Syem: Laplace Tranform Power Tool for yem analyi Reading Aignmen: Secion 6.1 6.3 of Kamen and Heck 1/18 Coure Flow Diagram The arrow here how concepual

More information

Bayesian Designs for Michaelis-Menten kinetics

Bayesian Designs for Michaelis-Menten kinetics Bayeian Deign for ichaeli-enen kineic John ahew and Gilly Allcock Deparen of Saiic Univeriy of Newcale upon Tyne.n..ahew@ncl.ac.uk Reference ec. on hp://www.a.ncl.ac.uk/~nn/alk/ile.h Enzyology any biocheical

More information

More on ODEs by Laplace Transforms October 30, 2017

More on ODEs by Laplace Transforms October 30, 2017 More on OE b Laplace Tranfor Ocober, 7 More on Ordinar ifferenial Equaion wih Laplace Tranfor Larr areo Mechanical Engineering 5 Seinar in Engineering nali Ocober, 7 Ouline Review la cla efiniion of Laplace

More information

Exponential Sawtooth

Exponential Sawtooth ECPE 36 HOMEWORK 3: PROPERTIES OF THE FOURIER TRANSFORM SOLUTION. Exponenial Sawooh: The eaie way o do hi problem i o look a he Fourier ranform of a ingle exponenial funcion, () = exp( )u(). From he able

More information

Homework 2 Solutions

Homework 2 Solutions Mah 308 Differenial Equaions Fall 2002 & 2. See he las page. Hoework 2 Soluions 3a). Newon s secon law of oion says ha a = F, an we know a =, so we have = F. One par of he force is graviy, g. However,

More information

Amit Mehra. Indian School of Business, Hyderabad, INDIA Vijay Mookerjee

Amit Mehra. Indian School of Business, Hyderabad, INDIA Vijay Mookerjee RESEARCH ARTICLE HUMAN CAPITAL DEVELOPMENT FOR PROGRAMMERS USING OPEN SOURCE SOFTWARE Ami Mehra Indian Shool of Business, Hyderabad, INDIA {Ami_Mehra@isb.edu} Vijay Mookerjee Shool of Managemen, Uniersiy

More information

Discussion Session 2 Constant Acceleration/Relative Motion Week 03

Discussion Session 2 Constant Acceleration/Relative Motion Week 03 PHYS 100 Dicuion Seion Conan Acceleraion/Relaive Moion Week 03 The Plan Today you will work wih your group explore he idea of reference frame (i.e. relaive moion) and moion wih conan acceleraion. You ll

More information

Introduction to Numerical Analysis. In this lesson you will be taken through a pair of techniques that will be used to solve the equations of.

Introduction to Numerical Analysis. In this lesson you will be taken through a pair of techniques that will be used to solve the equations of. Inroducion o Nuerical Analysis oion In his lesson you will be aen hrough a pair of echniques ha will be used o solve he equaions of and v dx d a F d for siuaions in which F is well nown, and he iniial

More information

Second-Order Boundary Value Problems of Singular Type

Second-Order Boundary Value Problems of Singular Type JOURNAL OF MATEMATICAL ANALYSIS AND APPLICATIONS 226, 4443 998 ARTICLE NO. AY98688 Seond-Order Boundary Value Probles of Singular Type Ravi P. Agarwal Deparen of Maheais, Naional Uniersiy of Singapore,

More information

2. VECTORS. R Vectors are denoted by bold-face characters such as R, V, etc. The magnitude of a vector, such as R, is denoted as R, R, V

2. VECTORS. R Vectors are denoted by bold-face characters such as R, V, etc. The magnitude of a vector, such as R, is denoted as R, R, V ME 352 VETS 2. VETS Vecor algebra form he mahemaical foundaion for kinemaic and dnamic. Geomer of moion i a he hear of boh he kinemaic and dnamic of mechanical em. Vecor anali i he imehonored ool for decribing

More information

Linear Quadratic Regulator (LQR) - State Feedback Design

Linear Quadratic Regulator (LQR) - State Feedback Design Linear Quadrai Regulaor (LQR) - Sae Feedbak Design A sysem is expressed in sae variable form as x = Ax + Bu n m wih x( ) R, u( ) R and he iniial ondiion x() = x A he sabilizaion problem using sae variable

More information

Notes on cointegration of real interest rates and real exchange rates. ρ (2)

Notes on cointegration of real interest rates and real exchange rates. ρ (2) Noe on coinegraion of real inere rae and real exchange rae Charle ngel, Univeriy of Wiconin Le me ar wih he obervaion ha while he lieraure (mo prominenly Meee and Rogoff (988) and dion and Paul (993))

More information

Randomized Perfect Bipartite Matching

Randomized Perfect Bipartite Matching Inenive Algorihm Lecure 24 Randomized Perfec Biparie Maching Lecurer: Daniel A. Spielman April 9, 208 24. Inroducion We explain a randomized algorihm by Ahih Goel, Michael Kapralov and Sanjeev Khanna for

More information

To become more mathematically correct, Circuit equations are Algebraic Differential equations. from KVL, KCL from the constitutive relationship

To become more mathematically correct, Circuit equations are Algebraic Differential equations. from KVL, KCL from the constitutive relationship Laplace Tranform (Lin & DeCarlo: Ch 3) ENSC30 Elecric Circui II The Laplace ranform i an inegral ranformaion. I ranform: f ( ) F( ) ime variable complex variable From Euler > Lagrange > Laplace. Hence,

More information

CHAPTER. Forced Equations and Systems { } ( ) ( ) 8.1 The Laplace Transform and Its Inverse. Transforms from the Definition.

CHAPTER. Forced Equations and Systems { } ( ) ( ) 8.1 The Laplace Transform and Its Inverse. Transforms from the Definition. CHAPTER 8 Forced Equaion and Syem 8 The aplace Tranform and I Invere Tranform from he Definiion 5 5 = b b {} 5 = 5e d = lim5 e = ( ) b {} = e d = lim e + e d b = (inegraion by par) = = = = b b ( ) ( )

More information

EE Control Systems LECTURE 2

EE Control Systems LECTURE 2 Copyrigh F.L. Lewi 999 All righ reerved EE 434 - Conrol Syem LECTURE REVIEW OF LAPLACE TRANSFORM LAPLACE TRANSFORM The Laplace ranform i very ueful in analyi and deign for yem ha are linear and ime-invarian

More information

12. Nyquist Sampling, Pulse-Amplitude Modulation, and Time- Division Multiplexing

12. Nyquist Sampling, Pulse-Amplitude Modulation, and Time- Division Multiplexing Nyqui Sapling, Pule-Apliude Modulaion, and Tie Diviion Muliplexing on Mac 2. Nyqui Sapling, Pule-Apliude Modulaion, and Tie- Diviion Muliplexing Many analogue counicaion ye are ill in wide ue oday. Thee

More information

Mass Transfer Coefficients (MTC) and Correlations I

Mass Transfer Coefficients (MTC) and Correlations I Mass Transfer Mass Transfer Coeffiiens (MTC) and Correlaions I 7- Mass Transfer Coeffiiens and Correlaions I Diffusion an be desribed in wo ways:. Deailed physial desripion based on Fik s laws and he diffusion

More information

5.2 Design for Shear (Part I)

5.2 Design for Shear (Part I) 5. Design or Shear (Par I) This seion overs he ollowing opis. General Commens Limi Sae o Collapse or Shear 5..1 General Commens Calulaion o Shear Demand The objeive o design is o provide ulimae resisane

More information

Theory of! Partial Differential Equations!

Theory of! Partial Differential Equations! hp://www.nd.edu/~gryggva/cfd-course/! Ouline! Theory o! Parial Dierenial Equaions! Gréar Tryggvason! Spring 011! Basic Properies o PDE!! Quasi-linear Firs Order Equaions! - Characerisics! - Linear and

More information

-6 1 kg 100 cm m v 15µm = kg 1 hr s. Similarly Stokes velocity can be determined for the 25 and 150 µm particles:

-6 1 kg 100 cm m v 15µm = kg 1 hr s. Similarly Stokes velocity can be determined for the 25 and 150 µm particles: 009 Pearon Educaion, Inc., Upper Saddle Rier, NJ. All righ reered. Thi publicaion i proeced by Copyrigh and wrien periion hould be obained fro he publiher prior o any prohibied reproducion, orage in a

More information

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes

23.2. Representing Periodic Functions by Fourier Series. Introduction. Prerequisites. Learning Outcomes Represening Periodic Funcions by Fourier Series 3. Inroducion In his Secion we show how a periodic funcion can be expressed as a series of sines and cosines. We begin by obaining some sandard inegrals

More information

Theory of! Partial Differential Equations-I!

Theory of! Partial Differential Equations-I! hp://users.wpi.edu/~grear/me61.hml! Ouline! Theory o! Parial Dierenial Equaions-I! Gréar Tryggvason! Spring 010! Basic Properies o PDE!! Quasi-linear Firs Order Equaions! - Characerisics! - Linear and

More information

PHYSICS 151 Notes for Online Lecture #4

PHYSICS 151 Notes for Online Lecture #4 PHYSICS 5 Noe for Online Lecure #4 Acceleraion The ga pedal in a car i alo called an acceleraor becaue preing i allow you o change your elociy. Acceleraion i how fa he elociy change. So if you ar fro re

More information

u(t) Figure 1. Open loop control system

u(t) Figure 1. Open loop control system Open loop conrol v cloed loop feedbac conrol The nex wo figure preen he rucure of open loop and feedbac conrol yem Figure how an open loop conrol yem whoe funcion i o caue he oupu y o follow he reference

More information

Derivation of longitudinal Doppler shift equation between two moving bodies in reference frame at rest

Derivation of longitudinal Doppler shift equation between two moving bodies in reference frame at rest Deriaion o longiudinal Doppler shi equaion beween wo moing bodies in reerene rame a res Masanori Sao Honda Eleronis Co., d., Oyamazuka, Oiwa-ho, Toyohashi, ihi 44-393, Japan E-mail: msao@honda-el.o.jp

More information

mywbut.com Lesson 11 Study of DC transients in R-L-C Circuits

mywbut.com Lesson 11 Study of DC transients in R-L-C Circuits mywbu.om esson Sudy of DC ransiens in R--C Ciruis mywbu.om Objeives Be able o wrie differenial equaion for a d iruis onaining wo sorage elemens in presene of a resisane. To develop a horough undersanding

More information

NEUTRON DIFFUSION THEORY

NEUTRON DIFFUSION THEORY NEUTRON DIFFUSION THEORY M. Ragheb 4//7. INTRODUCTION The diffuion heory model of neuron ranpor play a crucial role in reacor heory ince i i imple enough o allow cienific inigh, and i i ufficienly realiic

More information

Algorithmic Discrete Mathematics 6. Exercise Sheet

Algorithmic Discrete Mathematics 6. Exercise Sheet Algorihmic Dicree Mahemaic. Exercie Shee Deparmen of Mahemaic SS 0 PD Dr. Ulf Lorenz 7. and 8. Juni 0 Dipl.-Mah. David Meffer Verion of June, 0 Groupwork Exercie G (Heap-Sor) Ue Heap-Sor wih a min-heap

More information

Lecture 26. Lucas and Stokey: Optimal Monetary and Fiscal Policy in an Economy without Capital (JME 1983) t t

Lecture 26. Lucas and Stokey: Optimal Monetary and Fiscal Policy in an Economy without Capital (JME 1983) t t Lecure 6. Luca and Sokey: Opimal Moneary and Fical Policy in an Economy wihou Capial (JME 983. A argued in Kydland and Preco (JPE 977, Opimal governmen policy i likely o be ime inconien. Fiher (JEDC 98

More information

Moment Analysis of Hadronic Vacuum Polarization Proposal for a lattice QCD evaluation of g µ 2

Moment Analysis of Hadronic Vacuum Polarization Proposal for a lattice QCD evaluation of g µ 2 Moen Analysis of Hadronic Vacuu Polarizaion Proposal for a laice QCD evaluaion of g Eduardo de Rafael Cenre de Physique Théorique CNRS-Luiny, Marseille 7h June 04 NAPLES Seinar Moivaion a (E8 BNL) = 6

More information

Laplace Transform. Inverse Laplace Transform. e st f(t)dt. (2)

Laplace Transform. Inverse Laplace Transform. e st f(t)dt. (2) Laplace Tranform Maoud Malek The Laplace ranform i an inegral ranform named in honor of mahemaician and aronomer Pierre-Simon Laplace, who ued he ranform in hi work on probabiliy heory. I i a powerful

More information

CHAPTER 7: SECOND-ORDER CIRCUITS

CHAPTER 7: SECOND-ORDER CIRCUITS EEE5: CI RCUI T THEORY CHAPTER 7: SECOND-ORDER CIRCUITS 7. Inroducion Thi chaper conider circui wih wo orage elemen. Known a econd-order circui becaue heir repone are decribed by differenial equaion ha

More information

Soviet Rail Network, 1955

Soviet Rail Network, 1955 7.1 Nework Flow Sovie Rail Nework, 19 Reerence: On he hiory o he ranporaion and maximum low problem. lexander Schrijver in Mah Programming, 91: 3, 00. (See Exernal Link ) Maximum Flow and Minimum Cu Max

More information

Analysis of Members with Axial Loads and Moments. (Length effects Disregarded, Short Column )

Analysis of Members with Axial Loads and Moments. (Length effects Disregarded, Short Column ) Analyi o emer wih Axial Loa an omen (Lengh ee Diregare, Shor Column ) A. Reaing Aignmen Chaper 9 o ex Chaper 10 o ACI B. reenaion o he INTERACTION DIAGRA or FAILURE ENVELO We have een ha a given eion an

More information

Math 10B: Mock Mid II. April 13, 2016

Math 10B: Mock Mid II. April 13, 2016 Name: Soluions Mah 10B: Mock Mid II April 13, 016 1. ( poins) Sae, wih jusificaion, wheher he following saemens are rue or false. (a) If a 3 3 marix A saisfies A 3 A = 0, hen i canno be inverible. True.

More information

Optimal Transition to Backstop Substitutes for Nonrenewable Resources

Optimal Transition to Backstop Substitutes for Nonrenewable Resources Opimal raniion o Bakop ubiue for Nonrenewable Reoure Yaov ur 1 and Amo Zemel 2 Abra: : We haraerize he opimal raniion from a primary, nonrenewable reoure o a bakop ubiue for a la of problem haraerized

More information

CHAPTER 12 DIRECT CURRENT CIRCUITS

CHAPTER 12 DIRECT CURRENT CIRCUITS CHAPTER 12 DIRECT CURRENT CIUITS DIRECT CURRENT CIUITS 257 12.1 RESISTORS IN SERIES AND IN PARALLEL When wo resisors are conneced ogeher as shown in Figure 12.1 we said ha hey are conneced in series. As

More information

Network Flows: Introduction & Maximum Flow

Network Flows: Introduction & Maximum Flow CSC 373 - lgorihm Deign, nalyi, and Complexiy Summer 2016 Lalla Mouaadid Nework Flow: Inroducion & Maximum Flow We now urn our aenion o anoher powerful algorihmic echnique: Local Search. In a local earch

More information

Consider a Binary antipodal system which produces data of δ (t)

Consider a Binary antipodal system which produces data of δ (t) Modulaion Polem PSK: (inay Phae-hi keying) Conide a inay anipodal yem whih podue daa o δ ( o + δ ( o inay and epeively. Thi daa i paed o pule haping ile and he oupu o he pule haping ile i muliplied y o(

More information

A-B-Cs of Sun-Synchronous Orbit Mission Design

A-B-Cs of Sun-Synchronous Orbit Mission Design A-B-Cs of Sun-Synhronous Orbi Mission Design Ronald J. Boain Je Propulsion aboraory California nsiue of Tehnology AAS/AAA Spae Fligh Mehanis Conferene Maui, Hawaii 8-12 February 24 9 February 24 1 W S

More information

Problem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow.

Problem Set If all directed edges in a network have distinct capacities, then there is a unique maximum flow. CSE 202: Deign and Analyi of Algorihm Winer 2013 Problem Se 3 Inrucor: Kamalika Chaudhuri Due on: Tue. Feb 26, 2013 Inrucion For your proof, you may ue any lower bound, algorihm or daa rucure from he ex

More information

Traveling Waves. Chapter Introduction

Traveling Waves. Chapter Introduction Chaper 4 Traveling Waves 4.1 Inroducion To dae, we have considered oscillaions, i.e., periodic, ofen harmonic, variaions of a physical characerisic of a sysem. The sysem a one ime is indisinguishable from

More information

Solutions from Chapter 9.1 and 9.2

Solutions from Chapter 9.1 and 9.2 Soluions from Chaper 9 and 92 Secion 9 Problem # This basically boils down o an exercise in he chain rule from calculus We are looking for soluions of he form: u( x) = f( k x c) where k x R 3 and k is

More information

13.1 Accelerating Objects

13.1 Accelerating Objects 13.1 Acceleraing Objec A you learned in Chaper 12, when you are ravelling a a conan peed in a raigh line, you have uniform moion. However, mo objec do no ravel a conan peed in a raigh line o hey do no

More information

Final Spring 2007

Final Spring 2007 .615 Final Spring 7 Overview The purpose of he final exam is o calculae he MHD β limi in a high-bea oroidal okamak agains he dangerous n = 1 exernal ballooning-kink mode. Effecively, his corresponds o

More information

Math 221: Mathematical Notation

Math 221: Mathematical Notation Mah 221: Mahemaical Noaion Purpose: One goal in any course is o properly use he language o ha subjec. These noaions summarize some o he major conceps and more diicul opics o he uni. Typing hem helps you

More information

Derivation of the Missing Equations of Special Relativity from de-broglie s Matter Wave Concept and the Correspondence between Them

Derivation of the Missing Equations of Special Relativity from de-broglie s Matter Wave Concept and the Correspondence between Them Asian Journa of Aied Siene and Engineering, Voue, No /3 ISSN 35-95X(); 37-9584(e) Deriaion of he Missing Equaions of Seia Reaiiy fro de-brogie s Maer Wae Cone and he Corresondene beween The M.O.G. Taukder,

More information

Admin MAX FLOW APPLICATIONS. Flow graph/networks. Flow constraints 4/30/13. CS lunch today Grading. in-flow = out-flow for every vertex (except s, t)

Admin MAX FLOW APPLICATIONS. Flow graph/networks. Flow constraints 4/30/13. CS lunch today Grading. in-flow = out-flow for every vertex (except s, t) /0/ dmin lunch oday rading MX LOW PPLIION 0, pring avid Kauchak low graph/nework low nework direced, weighed graph (V, ) poiive edge weigh indicaing he capaciy (generally, aume ineger) conain a ingle ource

More information

Two Coupled Oscillators / Normal Modes

Two Coupled Oscillators / Normal Modes Lecure 3 Phys 3750 Two Coupled Oscillaors / Normal Modes Overview and Moivaion: Today we ake a small, bu significan, sep owards wave moion. We will no ye observe waves, bu his sep is imporan in is own

More information

KEY. Math 334 Midterm I Fall 2008 sections 001 and 003 Instructor: Scott Glasgow

KEY. Math 334 Midterm I Fall 2008 sections 001 and 003 Instructor: Scott Glasgow 1 KEY Mah 4 Miderm I Fall 8 secions 1 and Insrucor: Sco Glasgow Please do NOT wrie on his eam. No credi will be given for such work. Raher wrie in a blue book, or on our own paper, preferabl engineering

More information

Boyce/DiPrima 9 th ed, Ch 6.1: Definition of. Laplace Transform. In this chapter we use the Laplace transform to convert a

Boyce/DiPrima 9 th ed, Ch 6.1: Definition of. Laplace Transform. In this chapter we use the Laplace transform to convert a Boye/DiPrima 9 h ed, Ch 6.: Definiion of Laplae Transform Elemenary Differenial Equaions and Boundary Value Problems, 9 h ediion, by William E. Boye and Rihard C. DiPrima, 2009 by John Wiley & Sons, In.

More information

Lecture #6: Continuous-Time Signals

Lecture #6: Continuous-Time Signals EEL5: Discree-Time Signals and Sysems Lecure #6: Coninuous-Time Signals Lecure #6: Coninuous-Time Signals. Inroducion In his lecure, we discussed he ollowing opics:. Mahemaical represenaion and ransormaions

More information

Module 2: Analysis of Stress

Module 2: Analysis of Stress Module/Leon Module : Anali of Sre.. INTRODUCTION A bod under he acion of eernal force, undergoe diorion and he effec due o hi em of force i ranmied hroughou he bod developing inernal force in i. To eamine

More information

KEY. Math 334 Midterm III Winter 2008 section 002 Instructor: Scott Glasgow

KEY. Math 334 Midterm III Winter 2008 section 002 Instructor: Scott Glasgow KEY Mah 334 Miderm III Winer 008 secion 00 Insrucor: Sco Glasgow Please do NOT wrie on his exam. No credi will be given for such work. Raher wrie in a blue book, or on your own paper, preferably engineering

More information

8. Basic RL and RC Circuits

8. Basic RL and RC Circuits 8. Basic L and C Circuis This chaper deals wih he soluions of he responses of L and C circuis The analysis of C and L circuis leads o a linear differenial equaion This chaper covers he following opics

More information

Rectilinear Kinematics

Rectilinear Kinematics Recilinear Kinemaic Coninuou Moion Sir Iaac Newon Leonard Euler Oeriew Kinemaic Coninuou Moion Erraic Moion Michael Schumacher. 7-ime Formula 1 World Champion Kinemaic The objecie of kinemaic i o characerize

More information

INTRODUCTION TO INERTIAL CONFINEMENT FUSION

INTRODUCTION TO INERTIAL CONFINEMENT FUSION INTODUCTION TO INETIAL CONFINEMENT FUSION. Bei Lecure 7 Soluion of he imple dynamic igniion model ecap from previou lecure: imple dynamic model ecap: 1D model dynamic model ρ P() T enhalpy flux ino ho

More information

Generalized electromagnetic energy-momentum tensor and scalar curvature of space at the location of charged particle

Generalized electromagnetic energy-momentum tensor and scalar curvature of space at the location of charged particle Generalized eleromagnei energy-momenum ensor and salar urvaure of spae a he loaion of harged parile A.L. Kholmeskii 1, O.V. Missevih and T. Yarman 3 1 Belarus Sae Universiy, Nezavisimosi Avenue, 0030 Minsk,

More information

LAPLACE TRANSFORMS. 1. Basic transforms

LAPLACE TRANSFORMS. 1. Basic transforms LAPLACE TRANSFORMS. Bic rnform In hi coure, Lplce Trnform will be inroduced nd heir properie exmined; ble of common rnform will be buil up; nd rnform will be ued o olve ome dierenil equion by rnforming

More information

EE202 Circuit Theory II

EE202 Circuit Theory II EE202 Circui Theory II 2017-2018, Spring Dr. Yılmaz KALKAN I. Inroducion & eview of Fir Order Circui (Chaper 7 of Nilon - 3 Hr. Inroducion, C and L Circui, Naural and Sep epone of Serie and Parallel L/C

More information

Motion In One Dimension. Graphing Constant Speed

Motion In One Dimension. Graphing Constant Speed Moion In One Dimenion PLATO AND ARISTOTLE GALILEO GALILEI LEANING TOWER OF PISA Graphing Conan Speed Diance v. Time for Toy Car (0-5 ec.) be-fi line (from TI calculaor) d = 207.7 12.6 Diance (cm) 1000

More information

Introduction to SLE Lecture Notes

Introduction to SLE Lecture Notes Inroducion o SLE Lecure Noe May 13, 16 - The goal of hi ecion i o find a ufficien condiion of λ for he hull K o be generaed by a imple cure. I urn ou if λ 1 < 4 hen K i generaed by a imple curve. We will

More information

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle Chaper 2 Newonian Mechanics Single Paricle In his Chaper we will review wha Newon s laws of mechanics ell us abou he moion of a single paricle. Newon s laws are only valid in suiable reference frames,

More information

Chapter 6. Laplace Transforms

Chapter 6. Laplace Transforms 6- Chaper 6. Laplace Tranform 6.4 Shor Impule. Dirac Dela Funcion. Parial Fracion 6.5 Convoluion. Inegral Equaion 6.6 Differeniaion and Inegraion of Tranform 6.7 Syem of ODE 6.4 Shor Impule. Dirac Dela

More information

Challenge Problems. DIS 203 and 210. March 6, (e 2) k. k(k + 2). k=1. f(x) = k(k + 2) = 1 x k

Challenge Problems. DIS 203 and 210. March 6, (e 2) k. k(k + 2). k=1. f(x) = k(k + 2) = 1 x k Challenge Problems DIS 03 and 0 March 6, 05 Choose one of he following problems, and work on i in your group. Your goal is o convince me ha your answer is correc. Even if your answer isn compleely correc,

More information

ū(e )(1 γ 5 )γ α v( ν e ) v( ν e )γ β (1 + γ 5 )u(e ) tr (1 γ 5 )γ α ( p ν m ν )γ β (1 + γ 5 )( p e + m e ).

ū(e )(1 γ 5 )γ α v( ν e ) v( ν e )γ β (1 + γ 5 )u(e ) tr (1 γ 5 )γ α ( p ν m ν )γ β (1 + γ 5 )( p e + m e ). PHY 396 K. Soluion for problem e #. Problem (a: A poin of noaion: In he oluion o problem, he indice µ, e, ν ν µ, and ν ν e denoe he paricle. For he Lorenz indice, I hall ue α, β, γ, δ, σ, and ρ, bu never

More information

1 Motivation and Basic Definitions

1 Motivation and Basic Definitions CSCE : Deign and Analyi of Algorihm Noe on Max Flow Fall 20 (Baed on he preenaion in Chaper 26 of Inroducion o Algorihm, 3rd Ed. by Cormen, Leieron, Rive and Sein.) Moivaion and Baic Definiion Conider

More information

From Complex Fourier Series to Fourier Transforms

From Complex Fourier Series to Fourier Transforms Topic From Complex Fourier Series o Fourier Transforms. Inroducion In he previous lecure you saw ha complex Fourier Series and is coeciens were dened by as f ( = n= C ne in! where C n = T T = T = f (e

More information

What is maximum Likelihood? History Features of ML method Tools used Advantages Disadvantages Evolutionary models

What is maximum Likelihood? History Features of ML method Tools used Advantages Disadvantages Evolutionary models Wha i maximum Likelihood? Hiory Feaure of ML mehod Tool ued Advanage Diadvanage Evoluionary model Maximum likelihood mehod creae all he poible ree conaining he e of organim conidered, and hen ue he aiic

More information

Math 2142 Exam 1 Review Problems. x 2 + f (0) 3! for the 3rd Taylor polynomial at x = 0. To calculate the various quantities:

Math 2142 Exam 1 Review Problems. x 2 + f (0) 3! for the 3rd Taylor polynomial at x = 0. To calculate the various quantities: Mah 4 Eam Review Problems Problem. Calculae he 3rd Taylor polynomial for arcsin a =. Soluion. Le f() = arcsin. For his problem, we use he formula f() + f () + f ()! + f () 3! for he 3rd Taylor polynomial

More information

Introduction to Congestion Games

Introduction to Congestion Games Algorihmic Game Theory, Summer 2017 Inroducion o Congeion Game Lecure 1 (5 page) Inrucor: Thoma Keelheim In hi lecure, we ge o know congeion game, which will be our running example for many concep in game

More information

Chapter 6. Systems of First Order Linear Differential Equations

Chapter 6. Systems of First Order Linear Differential Equations Chaper 6 Sysems of Firs Order Linear Differenial Equaions We will only discuss firs order sysems However higher order sysems may be made ino firs order sysems by a rick shown below We will have a sligh

More information

3. Differential Equations

3. Differential Equations 3. Differenial Equaions 3.. inear Differenial Equaions of Firs rder A firs order differenial equaion is an equaion of he form d() d ( ) = F ( (),) (3.) As noed above, here will in general be a whole la

More information

ARTIFICIAL INTELLIGENCE. Markov decision processes

ARTIFICIAL INTELLIGENCE. Markov decision processes INFOB2KI 2017-2018 Urech Univeriy The Neherland ARTIFICIAL INTELLIGENCE Markov deciion procee Lecurer: Silja Renooij Thee lide are par of he INFOB2KI Coure Noe available from www.c.uu.nl/doc/vakken/b2ki/chema.hml

More information

Chapter 6. Laplace Transforms

Chapter 6. Laplace Transforms Chaper 6. Laplace Tranform Kreyzig by YHLee;45; 6- An ODE i reduced o an algebraic problem by operaional calculu. The equaion i olved by algebraic manipulaion. The reul i ranformed back for he oluion of

More information

SOLUTIONS TO ECE 3084

SOLUTIONS TO ECE 3084 SOLUTIONS TO ECE 384 PROBLEM 2.. For each sysem below, specify wheher or no i is: (i) memoryless; (ii) causal; (iii) inverible; (iv) linear; (v) ime invarian; Explain your reasoning. If he propery is no

More information

THE BERNOULLI NUMBERS. t k. = lim. = lim = 1, d t B 1 = lim. 1+e t te t = lim t 0 (e t 1) 2. = lim = 1 2.

THE BERNOULLI NUMBERS. t k. = lim. = lim = 1, d t B 1 = lim. 1+e t te t = lim t 0 (e t 1) 2. = lim = 1 2. THE BERNOULLI NUMBERS The Bernoulli numbers are defined here by he exponenial generaing funcion ( e The firs one is easy o compue: (2 and (3 B 0 lim 0 e lim, 0 e ( d B lim 0 d e +e e lim 0 (e 2 lim 0 2(e

More information

!!"#"$%&#'()!"#&'(*%)+,&',-)./0)1-*23)

!!#$%&#'()!#&'(*%)+,&',-)./0)1-*23) "#"$%&#'()"#&'(*%)+,&',-)./)1-*) #$%&'()*+,&',-.%,/)*+,-&1*#$)()5*6$+$%*,7&*-'-&1*(,-&*6&,7.$%$+*&%'(*8$&',-,%'-&1*(,-&*6&,79*(&,%: ;..,*&1$&$.$%&'()*1$$.,'&',-9*(&,%)?%*,('&5

More information

Homework 4 (Stats 620, Winter 2017) Due Tuesday Feb 14, in class Questions are derived from problems in Stochastic Processes by S. Ross.

Homework 4 (Stats 620, Winter 2017) Due Tuesday Feb 14, in class Questions are derived from problems in Stochastic Processes by S. Ross. Homework 4 (Sas 62, Winer 217) Due Tuesday Feb 14, in class Quesions are derived from problems in Sochasic Processes by S. Ross. 1. Le A() and Y () denoe respecively he age and excess a. Find: (a) P{Y

More information

18.03SC Unit 3 Practice Exam and Solutions

18.03SC Unit 3 Practice Exam and Solutions Sudy Guide on Sep, Dela, Convoluion, Laplace You can hink of he ep funcion u() a any nice mooh funcion which i for < a and for > a, where a i a poiive number which i much maller han any ime cale we care

More information

EE40 Summer 2005: Lecture 2 Instructor: Octavian Florescu 1. Measuring Voltages and Currents

EE40 Summer 2005: Lecture 2 Instructor: Octavian Florescu 1. Measuring Voltages and Currents Announemens HW # Due oday a 6pm. HW # posed online oday and due nex Tuesday a 6pm. Due o sheduling onflis wih some sudens, lasses will resume normally his week and nex. Miderm enaively 7/. EE4 Summer 5:

More information

Optimal Transition to Backstop Substitutes for Nonrenewable Resources *

Optimal Transition to Backstop Substitutes for Nonrenewable Resources * Opimal Traniion o Bakop ubiue for Nonrenewable Reoure Yaov Tur 1 and Amo Zemel 2 Abra: We analyze he opimal raniion from a primary, nonrenewable reoure o a bakop ubiue for a la of problem haraerized by

More information

A New Formulation of Electrodynamics

A New Formulation of Electrodynamics . Eleromagnei Analysis & Appliaions 1 457-461 doi:1.436/jemaa.1.86 Published Online Augus 1 hp://www.sirp.org/journal/jemaa A New Formulaion of Elerodynamis Arbab I. Arbab 1 Faisal A. Yassein 1 Deparmen

More information

KEY. Math 334 Midterm III Fall 2008 sections 001 and 003 Instructor: Scott Glasgow

KEY. Math 334 Midterm III Fall 2008 sections 001 and 003 Instructor: Scott Glasgow KEY Mah 334 Miderm III Fall 28 secions and 3 Insrucor: Sco Glasgow Please do NOT wrie on his exam. No credi will be given for such work. Raher wrie in a blue book, or on your own paper, preferably engineering

More information

13.1 Circuit Elements in the s Domain Circuit Analysis in the s Domain The Transfer Function and Natural Response 13.

13.1 Circuit Elements in the s Domain Circuit Analysis in the s Domain The Transfer Function and Natural Response 13. Chaper 3 The Laplace Tranform in Circui Analyi 3. Circui Elemen in he Domain 3.-3 Circui Analyi in he Domain 3.4-5 The Tranfer Funcion and Naural Repone 3.6 The Tranfer Funcion and he Convoluion Inegral

More information

FROM STEADY-STATE AND DYNAMIC ANALYSIS TO ADAPTIVE CONTROL OF THE CSTR REACTOR

FROM STEADY-STATE AND DYNAMIC ANALYSIS TO ADAPTIVE CONTROL OF THE CSTR REACTOR FROM SEADY-SAE AND DYNAMIC ANALYSIS O ADAPIVE CONROL OF HE CSR REACOR Jiri Vojeek and Per Doal Deparmen o Proe Conrol Iniue o Proe Conrol and Applied Inormai oma Baa Univeriy in Zlin Nam..G.M. 75, 76 7

More information

Algorithms and Data Structures 2011/12 Week 9 Solutions (Tues 15th - Fri 18th Nov)

Algorithms and Data Structures 2011/12 Week 9 Solutions (Tues 15th - Fri 18th Nov) Algorihm and Daa Srucure 2011/ Week Soluion (Tue 15h - Fri 18h No) 1. Queion: e are gien 11/16 / 15/20 8/13 0/ 1/ / 11/1 / / To queion: (a) Find a pair of ube X, Y V uch ha f(x, Y) = f(v X, Y). (b) Find

More information

23.5. Half-Range Series. Introduction. Prerequisites. Learning Outcomes

23.5. Half-Range Series. Introduction. Prerequisites. Learning Outcomes Half-Range Series 2.5 Inroducion In his Secion we address he following problem: Can we find a Fourier series expansion of a funcion defined over a finie inerval? Of course we recognise ha such a funcion

More information

3, so θ = arccos

3, so θ = arccos Mahemaics 210 Professor Alan H Sein Monday, Ocober 1, 2007 SOLUTIONS This problem se is worh 50 poins 1 Find he angle beween he vecors (2, 7, 3) and (5, 2, 4) Soluion: Le θ be he angle (2, 7, 3) (5, 2,

More information

Graphs III - Network Flow

Graphs III - Network Flow Graph III - Nework Flow Flow nework eup graph G=(V,E) edge capaciy w(u,v) 0 - if edge doe no exi, hen w(u,v)=0 pecial verice: ource verex ; ink verex - no edge ino and no edge ou of Aume every verex v

More information

Calculus Tricks #1. So if you understand derivatives, you ll understand the course material much better. a few preliminaries exponents

Calculus Tricks #1. So if you understand derivatives, you ll understand the course material much better. a few preliminaries exponents Calculus Tricks # Eric Doviak Calculus is no a pre-requisie or his course. However, he oundaions o economics are based on calculus, so wha we ll be discussing over he course o he semeser is he inuiion

More information

On the approximation of particular solution of nonhomogeneous linear differential equation with Legendre series

On the approximation of particular solution of nonhomogeneous linear differential equation with Legendre series The Journal of Applied Science Vol. 5 No. : -9 [6] วารสารว ทยาศาสตร ประย กต doi:.446/j.appsci.6.8. ISSN 53-785 Prined in Thailand Research Aricle On he approxiaion of paricular soluion of nonhoogeneous

More information

THE SINE INTEGRAL. x dt t

THE SINE INTEGRAL. x dt t THE SINE INTEGRAL As one learns in elemenary calculus, he limi of sin(/ as vanishes is uniy. Furhermore he funcion is even and has an infinie number of zeros locaed a ±n for n1,,3 Is plo looks like his-

More information