ERT 318 UNIT OPERATIONS

Size: px
Start display at page:

Download "ERT 318 UNIT OPERATIONS"

Transcription

1 ERT 318 UNIT OPERATIONS DISTILLATION W. L. McCabe, J. C. Smith, P. Harriot, Uit Operatios of Chemical Egieerig, 7 th editio,

2 Outlie: Batch distillatio (pg. 724) Cotiuous distillatio with reflux (pg. 666) Material balace i plate colum (pg. 670) McCabe-Thiele Method (pg. 672) Determiatio of the umber of plates usig ethalpycompositio diagram (pg. 694) Itroductio to multicompoet distillatio Phase Equilibria i Multicompoet Distillatio (Pg. 737) Flash Distillatio of Multicompoet Mixtures (pg. 741) Fractioatio of Multicompoet Mixtures (pg. 742) Azeotropic ad Extractive Distillatio (pg. 759) 2

3 Batch Distillatio Vapor Fig : Simple distillatio i a batch still Ofte used i small plats to recover volatile products from liquid. Vapor: - equilibrium with the liquid i the still - Richer with volatile compoet - compositio liquid & vapor are ot costat 3

4 Batch Distillatio 4

5 Batch Distillatio 5

6 Batch Distillatio 6

7 Batch Distillatio 7

8 Cotiuous Distillatio with Reflux Ofte used for large-scale productio, far more commo tha batch distillatio. y = vapor leavig plate x = Liquid leavig plate y +1 = vapor eterig plate x +1 = liquid eterig plate V = vapor phase y = cocetratio of vapor L = Liquid phase x = cocetratio of liquid T -1 < T < T +1 8 Fig. 21.3: Material-balace diagram for plate Fig. 21.4: Boilig-poit diagram showig rectificatio o ideal plates

9 Cotiuous Distillatio with Reflux Combiatio rectificatio ad strippig Why feed is i the cetral? What is feed plate? To purify by repeated distillatio Reflux provides the dowflowig liquid i the rectifyig sectio that is eeded to act o the upflowig vapor. No reflux o rectificatio Physical separatio where more compoets are removed from a liquid stream by vapor stream If o azeotropes,both overhead ad bottom products obtaied i ay desired purity if eough plates ad adequate reflux are provided. Fig. 21.5: Cotiuous fractioatig colum with rectifyig ad strippig sectios. 9

10 Cotiuous Distillatio with Reflux Material Balaces i Plate colums Overall material balace for two-compoet systems Total material balace: F = D + B Compoet A balace: Fx F = Dx D + Bx B Elimiatig B: D/F = (x F -x B ) / (x D -x B ) Elimiatig D: B/F = (x D -x F ) / (x D -x B ) (21.6) (21.7) (21.8) (21.9) Eq & 21.9 are true for all values of the flows of vapor ad liquid withi the colum Net flow rates: D = V a -L a D = V +1 -L Dx D = V a y a L a x a = V +1 y +1 -L x B = L b V b = L m Vm+1 Bx B = L b x b V b y b = L m x m - V m+1 y m+1 (21.10) (21.11) (21.12) (21.13) (21.14) Fig. 21.6: Material-balace diagram for cotiuous fractioatio colum

11 Cotiuous Distillatio with Reflux a a a a V x L y V x V L y D V Dx x V L y D L Dx x D L L y D 1 Operatig lies : Because there are 2 sectios i the colum, there are also 2 operatig lies; 1 rectifyig sectio ad 1 strippig sectio. Compoet A balace: Fx F = Dx D + Bx B From Eq. (21.7): From Eq. (21.9): (21.15) (21.16) (21.17) The slope defied by Eq. (21.6) the ratio of liquid to the vapor stream: by elimiatig V +1

12 Cotiuous Distillatio with Reflux Operatig lies: Material balace over cotrol surface II, below the feed plate: V y m1 m1 L m x m Bx B (21.18) I a differet form, this becomes y m1 L V m m1 x m Bx V B m1 (21.19) This is the equatio for the operatig lie i the strippig sectio. Slope =liquid flow / vapor flow. Elimiatig V m+1 from Eq (21.19) & (21.13) gives: y m1 L Lm m B x m BxB L B m (21.20)

13 Cotiuous Distillatio with Reflux Number of ideal Plates; McCabe-Thiele Method ASPEN : Computer desig program used to idetify the umber of plates required for a distillatio problem. Mc Cabe-Thiele Method : A simplified graphical method for calculatig the umber of plates. Whe the operatig lies used Eqs. (21.17) ad (21.20) are plotted withi the equilirium curve o the xy diagram, the McCabe-Thiele step-by-step costructio ca be used to compute the umber of ideal plates Eqs. (21.17) ad (21.20), show that uless L ad L m are costat, the operatig lies are curved ad ca be plotted oly if the chage i these iteral streams with cocetratio is kow. Ethalpy balaces are required i the geeral case to determie the positio of a curved operatig lie. See Example Tutorial 1: Problem 21.11

14 Example 21.2

15 Example 21.2: Solutio

16 Example 21.2: Solutio

17 Example 21.2: Solutio

18 Example 21.2: Solutio

19 Example 21.2: Solutio

20 Example 21.2: Solutio

21 Determiatio of the umber of plates usig ethalpycompositio diagram

22 Ethalpy Balaces Variatios i V ad L streams deped o the ethalpies. Ethalpy data may be available from a ethalpy-cocetratio diagram (e.g., Fig. 21.2) or data bak from i computer program. T b, bezee = 80 o C T b, toluee = o C Temp. rage = o C Ofte distillatio colums are desiged usig computers, the basic ethalpy balace equatio are give. Refer to Example 21.5, which illustrate the small differece this makes i the McCabe-Thiele diagram for a typical ideal system. Bezee-toluee solutios are ideal. Fig : Ethalpy-cocetratio diagram for bezee-toluee at 1atm. For: Liquid bubble poit Vapor dew poit Temperature for x = 0.5 ad y = 0.5 is ot the same! (Refer to ext slide) Slight curvature i Fig is due to the oliear chage i the bubble-poit ad dewpoit with mole fractio bezee. 22

23 Ethalpy Balaces Figure 1: T-x-y diagram for Bezee-Toluee 1atm 23

24 Ethalpy Balaces Cosider a overall ethalpy balace for system show i Fig (REPEAT) FH F + q r = DH D + BH B +q c H F = ethalpy of feed H D = ethalpy of overhead product H B = ethalpy of bottom product q c = heat removed from codeser = q r (21.48) Fig. 21.6: Material-balace diagram for cotiuous fractioatio colum For give feed ad product streams, oly 1 of heat effects, q r or q c. Normally, q c is chose i desigig a colum to correspod to the desired reflux ratio ad moles of the overhead vapor. The, q r ca be calculated usig Eq. (21.48). I operatig colum, q r is ofte varied to chage the vapor flow rate ad reflux ratio, ad chages i q c the follow. 24

25 Ethalpy Balaces Ethalpy balaces i rectifyig ad strippig sectios 25

26 Ethalpy Balaces Ethalpy balaces i rectifyig ad strippig sectios 26

27 Ethalpy Balaces Ethalpy balaces i rectifyig ad strippig sectios 27

28 Example 21.5 A mixture of 50 mol percet bezee ad toluee is to be separated by distillatio at atmospheric pressure ito products of 98% purity usig a reflux ratio 1.2 times the miimum value. The feed is liquid at the boilig poit. Use ethalpy balaces (Table 21.3) to calculate the flows of liquid ad vapor at the top, middle, ad bottom of the colum, ad compare these values with those based o molal overflow. Estimate the differece i the umber of theoretical plates for the methods. Table 21.3: Data for Example 21.5 Compoet Ethalpy of vaporizatio, cal/g mol Specific heat at costat pressure, cal/g mol. C Liquid Vapor Boilig poit, C Bezee Toluee 7,360 7,

29 Tutorial 2 Problems: Due Thursday, 08/10/

Multiple Modes for the Operation of a Binary Distillation Column

Multiple Modes for the Operation of a Binary Distillation Column Id. Eg. Chem. Res. 1996, 35, 2327-2333 2327 Multiple Modes for the Operatio of a Biary Distillatio Colum J. Christia Scho1 ad Bjare Adrese*, Ørsted Laboratory, Uiversity of Copehage, Uiversitetsparke 5,

More information

CHEE 221: Chemical Processes and Systems

CHEE 221: Chemical Processes and Systems CHEE 221: Chemical Processes ad Systems Module 3. Material Balaces with Reactio Part a: Stoichiometry ad Methodologies (Felder & Rousseau Ch 4.6 4.8 ot 4.6c ) Material Balaces o Reactive Processes What

More information

Vapor-liquid Separation Process MULTICOMPONENT DISTILLATION

Vapor-liquid Separation Process MULTICOMPONENT DISTILLATION Vapor-liquid Separation Process MULTICOMPONENT DISTILLATION Outline: Introduction to multicomponent distillation Phase Equilibria in Multicomponent Distillation (Pg. 737) Bubble-point and dew-point calculation

More information

Multicomponent-Liquid-Fuel Vaporization with Complex Configuration

Multicomponent-Liquid-Fuel Vaporization with Complex Configuration Multicompoet-Liquid-Fuel Vaporizatio with Complex Cofiguratio William A. Sirigao Guag Wu Uiversity of Califoria, Irvie Major Goals: for multicompoet-liquid-fuel vaporizatio i a geeral geometrical situatio,

More information

Lesson 10: Limits and Continuity

Lesson 10: Limits and Continuity www.scimsacademy.com Lesso 10: Limits ad Cotiuity SCIMS Academy 1 Limit of a fuctio The cocept of limit of a fuctio is cetral to all other cocepts i calculus (like cotiuity, derivative, defiite itegrals

More information

SNAP Centre Workshop. Basic Algebraic Manipulation

SNAP Centre Workshop. Basic Algebraic Manipulation SNAP Cetre Workshop Basic Algebraic Maipulatio 8 Simplifyig Algebraic Expressios Whe a expressio is writte i the most compact maer possible, it is cosidered to be simplified. Not Simplified: x(x + 4x)

More information

Material Balances on Reactive Processes F&R

Material Balances on Reactive Processes F&R Material Balaces o Reactive Processes F&R 4.6-4.8 What does a reactio do to the geeral balace equatio? Accumulatio = I Out + Geeratio Cosumptio For a reactive process at steady-state, the geeral balace

More information

Properties and Tests of Zeros of Polynomial Functions

Properties and Tests of Zeros of Polynomial Functions Properties ad Tests of Zeros of Polyomial Fuctios The Remaider ad Factor Theorems: Sythetic divisio ca be used to fid the values of polyomials i a sometimes easier way tha substitutio. This is show by

More information

Chapter 14: Chemical Equilibrium

Chapter 14: Chemical Equilibrium hapter 14: hemical Equilibrium 46 hapter 14: hemical Equilibrium Sectio 14.1: Itroductio to hemical Equilibrium hemical equilibrium is the state where the cocetratios of all reactats ad products remai

More information

AME 513. " Lecture 3 Chemical thermodynamics I 2 nd Law

AME 513.  Lecture 3 Chemical thermodynamics I 2 nd Law AME 513 Priciples of Combustio " Lecture 3 Chemical thermodyamics I 2 d Law Outlie" Why do we eed to ivoke chemical equilibrium? Degrees Of Reactio Freedom (DORFs) Coservatio of atoms Secod Law of Thermodyamics

More information

We will conclude the chapter with the study a few methods and techniques which are useful

We will conclude the chapter with the study a few methods and techniques which are useful Chapter : Coordiate geometry: I this chapter we will lear about the mai priciples of graphig i a dimesioal (D) Cartesia system of coordiates. We will focus o drawig lies ad the characteristics of the graphs

More information

3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense,

3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense, 3. Z Trasform Referece: Etire Chapter 3 of text. Recall that the Fourier trasform (FT) of a DT sigal x [ ] is ω ( ) [ ] X e = j jω k = xe I order for the FT to exist i the fiite magitude sese, S = x [

More information

10.6 ALTERNATING SERIES

10.6 ALTERNATING SERIES 0.6 Alteratig Series Cotemporary Calculus 0.6 ALTERNATING SERIES I the last two sectios we cosidered tests for the covergece of series whose terms were all positive. I this sectio we examie series whose

More information

Kinetics of Complex Reactions

Kinetics 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 information

Mechatronics. Time Response & Frequency Response 2 nd -Order Dynamic System 2-Pole, Low-Pass, Active Filter

Mechatronics. Time Response & Frequency Response 2 nd -Order Dynamic System 2-Pole, Low-Pass, Active Filter Time Respose & Frequecy Respose d -Order Dyamic System -Pole, Low-Pass, Active Filter R 4 R 7 C 5 e i R 1 C R 3 - + R 6 - + e out Assigmet: Perform a Complete Dyamic System Ivestigatio of the Two-Pole,

More information

1. Linearization of a nonlinear system given in the form of a system of ordinary differential equations

1. Linearization of a nonlinear system given in the form of a system of ordinary differential equations . Liearizatio of a oliear system give i the form of a system of ordiary differetial equatios We ow show how to determie a liear model which approximates the behavior of a time-ivariat oliear system i a

More information

Simple Linear Regression

Simple Linear Regression Chapter 2 Simple Liear Regressio 2.1 Simple liear model The simple liear regressio model shows how oe kow depedet variable is determied by a sigle explaatory variable (regressor). Is is writte as: Y i

More information

Chapter 10: Power Series

Chapter 10: Power Series Chapter : Power Series 57 Chapter Overview: Power Series The reaso series are part of a Calculus course is that there are fuctios which caot be itegrated. All power series, though, ca be itegrated because

More information

Chapter 9: Numerical Differentiation

Chapter 9: Numerical Differentiation 178 Chapter 9: Numerical Differetiatio Numerical Differetiatio Formulatio of equatios for physical problems ofte ivolve derivatives (rate-of-chage quatities, such as velocity ad acceleratio). Numerical

More information

Introduction to Signals and Systems, Part V: Lecture Summary

Introduction to Signals and Systems, Part V: Lecture Summary EEL33: Discrete-Time Sigals ad Systems Itroductio to Sigals ad Systems, Part V: Lecture Summary Itroductio to Sigals ad Systems, Part V: Lecture Summary So far we have oly looked at examples of o-recursive

More information

is also known as the general term of the sequence

is also known as the general term of the sequence Lesso : Sequeces ad Series Outlie Objectives: I ca determie whether a sequece has a patter. I ca determie whether a sequece ca be geeralized to fid a formula for the geeral term i the sequece. I ca determie

More information

Definitions and Theorems. where x are the decision variables. c, b, and a are constant coefficients.

Definitions 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 information

ECE Spring Prof. David R. Jackson ECE Dept. Notes 20

ECE Spring Prof. David R. Jackson ECE Dept. Notes 20 ECE 6341 Sprig 016 Prof. David R. Jackso ECE Dept. Notes 0 1 Spherical Wave Fuctios Cosider solvig ψ + k ψ = 0 i spherical coordiates z φ θ r y x Spherical Wave Fuctios (cot.) I spherical coordiates we

More information

Nernst Equation. Nernst Equation. Electric Work and Gibb's Free Energy. Skills to develop. Electric Work. Gibb's Free Energy

Nernst Equation. Nernst Equation. Electric Work and Gibb's Free Energy. Skills to develop. Electric Work. Gibb's Free Energy Nerst Equatio Skills to develop Eplai ad distiguish the cell potetial ad stadard cell potetial. Calculate cell potetials from kow coditios (Nerst Equatio). Calculate the equilibrium costat from cell potetials.

More information

Distillation. This is often given as the definition of relative volatility, it can be calculated directly from vapor-liquid equilibrium data.

Distillation. This is often given as the definition of relative volatility, it can be calculated directly from vapor-liquid equilibrium data. Distillation Distillation may be defined as the separation of the components of a liquid mixture by a process involving partial vaporization. The vapor evolved is usually recovered by condensation. Volatility

More information

Statistics 511 Additional Materials

Statistics 511 Additional Materials Cofidece Itervals o mu Statistics 511 Additioal Materials This topic officially moves us from probability to statistics. We begi to discuss makig ifereces about the populatio. Oe way to differetiate probability

More information

Mass Transfer Operations I Prof. Bishnupada Mandal Department of Chemical Engineering Indian Institute of Technology, Guwahati

Mass Transfer Operations I Prof. Bishnupada Mandal Department of Chemical Engineering Indian Institute of Technology, Guwahati Mass Transfer Operations I Prof. Bishnupada Mandal Department of Chemical Engineering Indian Institute of Technology, Guwahati Module - 5 Distillation Lecture - 5 Fractional Distillation Welcome to the

More information

Random Variables, Sampling and Estimation

Random Variables, Sampling and Estimation Chapter 1 Radom Variables, Samplig ad Estimatio 1.1 Itroductio This chapter will cover the most importat basic statistical theory you eed i order to uderstad the ecoometric material that will be comig

More information

Ma 530 Introduction to Power Series

Ma 530 Introduction to Power Series Ma 530 Itroductio to Power Series Please ote that there is material o power series at Visual Calculus. Some of this material was used as part of the presetatio of the topics that follow. What is a Power

More information

Time-Domain Representations of LTI Systems

Time-Domain Representations of LTI Systems 2.1 Itroductio Objectives: 1. Impulse resposes of LTI systems 2. Liear costat-coefficiets differetial or differece equatios of LTI systems 3. Bloc diagram represetatios of LTI systems 4. State-variable

More information

Some examples of vector spaces

Some examples of vector spaces Roberto s Notes o Liear Algebra Chapter 11: Vector spaces Sectio 2 Some examples of vector spaces What you eed to kow already: The te axioms eeded to idetify a vector space. What you ca lear here: Some

More information

Measures of Spread: Variance and Standard Deviation

Measures of Spread: Variance and Standard Deviation Lesso 1-6 Measures of Spread: Variace ad Stadard Deviatio BIG IDEA Variace ad stadard deviatio deped o the mea of a set of umbers. Calculatig these measures of spread depeds o whether the set is a sample

More information

Math 312 Lecture Notes One Dimensional Maps

Math 312 Lecture Notes One Dimensional Maps Math 312 Lecture Notes Oe Dimesioal Maps Warre Weckesser Departmet of Mathematics Colgate Uiversity 21-23 February 25 A Example We begi with the simplest model of populatio growth. Suppose, for example,

More information

Summary: CORRELATION & LINEAR REGRESSION. GC. Students are advised to refer to lecture notes for the GC operations to obtain scatter diagram.

Summary: CORRELATION & LINEAR REGRESSION. GC. Students are advised to refer to lecture notes for the GC operations to obtain scatter diagram. Key Cocepts: 1) Sketchig of scatter diagram The scatter diagram of bivariate (i.e. cotaiig two variables) data ca be easily obtaied usig GC. Studets are advised to refer to lecture otes for the GC operatios

More information

We are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists. International authors and editors

We are IntechOpen, the world s leading publisher of Open Access books Built by scientists, for scientists. International authors and editors We are ItechOpe, the world s leadig publisher of Ope Access books uilt by scietists, for scietists 3,800 116,000 120M Ope access books available Iteratioal authors ad editors Dowloads Our authors are amog

More information

Chapter 8: Estimating with Confidence

Chapter 8: Estimating with Confidence Chapter 8: Estimatig with Cofidece Sectio 8.2 The Practice of Statistics, 4 th editio For AP* STARNES, YATES, MOORE Chapter 8 Estimatig with Cofidece 8.1 Cofidece Itervals: The Basics 8.2 8.3 Estimatig

More information

Chapter 4. Fourier Series

Chapter 4. Fourier Series Chapter 4. Fourier Series At this poit we are ready to ow cosider the caoical equatios. Cosider, for eample the heat equatio u t = u, < (4.) subject to u(, ) = si, u(, t) = u(, t) =. (4.) Here,

More information

Linear Regression Demystified

Linear Regression Demystified Liear Regressio Demystified Liear regressio is a importat subject i statistics. I elemetary statistics courses, formulae related to liear regressio are ofte stated without derivatio. This ote iteds to

More information

Exam II Covers. STA 291 Lecture 19. Exam II Next Tuesday 5-7pm Memorial Hall (Same place as exam I) Makeup Exam 7:15pm 9:15pm Location CB 234

Exam II Covers. STA 291 Lecture 19. Exam II Next Tuesday 5-7pm Memorial Hall (Same place as exam I) Makeup Exam 7:15pm 9:15pm Location CB 234 STA 291 Lecture 19 Exam II Next Tuesday 5-7pm Memorial Hall (Same place as exam I) Makeup Exam 7:15pm 9:15pm Locatio CB 234 STA 291 - Lecture 19 1 Exam II Covers Chapter 9 10.1; 10.2; 10.3; 10.4; 10.6

More information

Math 21B-B - Homework Set 2

Math 21B-B - Homework Set 2 Math B-B - Homework Set Sectio 5.:. a) lim P k= c k c k ) x k, where P is a partitio of [, 5. x x ) dx b) lim P k= 4 ck x k, where P is a partitio of [,. 4 x dx c) lim P k= ta c k ) x k, where P is a partitio

More information

NUMERICAL METHODS FOR SOLVING EQUATIONS

NUMERICAL METHODS FOR SOLVING EQUATIONS Mathematics Revisio Guides Numerical Methods for Solvig Equatios Page 1 of 11 M.K. HOME TUITION Mathematics Revisio Guides Level: GCSE Higher Tier NUMERICAL METHODS FOR SOLVING EQUATIONS Versio:. Date:

More information

Problem Cosider the curve give parametrically as x = si t ad y = + cos t for» t» ß: (a) Describe the path this traverses: Where does it start (whe t =

Problem Cosider the curve give parametrically as x = si t ad y = + cos t for» t» ß: (a) Describe the path this traverses: Where does it start (whe t = Mathematics Summer Wilso Fial Exam August 8, ANSWERS Problem 1 (a) Fid the solutio to y +x y = e x x that satisfies y() = 5 : This is already i the form we used for a first order liear differetial equatio,

More information

METRO EAST EDUCATION DISTRICT NATIONAL SENIOR CERTIFICATE GRADE 12 MATHEMATICS PAPER 1 SEPTEMBER 2014

METRO EAST EDUCATION DISTRICT NATIONAL SENIOR CERTIFICATE GRADE 12 MATHEMATICS PAPER 1 SEPTEMBER 2014 METRO EAST EDUCATION DISTRICT NATIONAL SENIOR CERTIFICATE GRADE MATHEMATICS PAPER SEPTEMBER 04 MARKS: 50 TIME: 3 hours This paper cosists of 7 pages ad a iformatio sheet. GR Mathematics- P MEED September

More information

Course Outline. Designing Control Systems. Proportional Controller. Amme 3500 : System Dynamics and Control. Root Locus. Dr. Stefan B.

Course Outline. Designing Control Systems. Proportional Controller. Amme 3500 : System Dynamics and Control. Root Locus. Dr. Stefan B. Amme 3500 : System Dyamics ad Cotrol Root Locus Course Outlie Week Date Cotet Assigmet Notes Mar Itroductio 8 Mar Frequecy Domai Modellig 3 5 Mar Trasiet Performace ad the s-plae 4 Mar Block Diagrams Assig

More information

9.4.3 Fundamental Parameters. Concentration Factor. Not recommended. See Extraction factor. Decontamination Factor

9.4.3 Fundamental Parameters. Concentration Factor. Not recommended. See Extraction factor. Decontamination Factor 9.4.3 Fudametal Parameters Cocetratio Factor Not recommeded. See Extractio factor. Decotamiatio Factor The ratio of the proportio of cotamiat to product before treatmet to the proportio after treatmet.

More information

Castiel, Supernatural, Season 6, Episode 18

Castiel, Supernatural, Season 6, Episode 18 13 Differetial Equatios the aswer to your questio ca best be epressed as a series of partial differetial equatios... Castiel, Superatural, Seaso 6, Episode 18 A differetial equatio is a mathematical equatio

More information

THE SOLUTION OF NONLINEAR EQUATIONS f( x ) = 0.

THE SOLUTION OF NONLINEAR EQUATIONS f( x ) = 0. THE SOLUTION OF NONLINEAR EQUATIONS f( ) = 0. Noliear Equatio Solvers Bracketig. Graphical. Aalytical Ope Methods Bisectio False Positio (Regula-Falsi) Fied poit iteratio Newto Raphso Secat The root of

More information

Sequences, Mathematical Induction, and Recursion. CSE 2353 Discrete Computational Structures Spring 2018

Sequences, Mathematical Induction, and Recursion. CSE 2353 Discrete Computational Structures Spring 2018 CSE 353 Discrete Computatioal Structures Sprig 08 Sequeces, Mathematical Iductio, ad Recursio (Chapter 5, Epp) Note: some course slides adopted from publisher-provided material Overview May mathematical

More information

HOMEWORK #10 SOLUTIONS

HOMEWORK #10 SOLUTIONS Math 33 - Aalysis I Sprig 29 HOMEWORK # SOLUTIONS () Prove that the fuctio f(x) = x 3 is (Riema) itegrable o [, ] ad show that x 3 dx = 4. (Without usig formulae for itegratio that you leart i previous

More information

Chemical Engineering 160/260 Polymer Science and Engineering. Model for Polymer Solutions February 5, 2001

Chemical Engineering 160/260 Polymer Science and Engineering. Model for Polymer Solutions February 5, 2001 Chemical Egieerig 60/60 Polymer Sciece ad Egieerig Lecture 9 - Flory-Huggis Model for Polymer Solutios February 5, 00 Read Sperlig, Chapter 4 Objectives! To develop the classical Flory-Huggis theory for

More information

FAILURE CRITERIA: MOHR S CIRCLE AND PRINCIPAL STRESSES

FAILURE CRITERIA: MOHR S CIRCLE AND PRINCIPAL STRESSES LECTURE Third Editio FAILURE CRITERIA: MOHR S CIRCLE AND PRINCIPAL STRESSES A. J. Clark School of Egieerig Departmet of Civil ad Evirometal Egieerig Chapter 7.4 b Dr. Ibrahim A. Assakkaf SPRING 3 ENES

More information

What is Physical Chemistry. Physical Chemistry for Chemical Engineers CHEM251. Basic Characteristics of a Gas

What is Physical Chemistry. Physical Chemistry for Chemical Engineers CHEM251. Basic Characteristics of a Gas 7/6/0 hysical Chemistry for Chemical Egieers CHEM5 What is hysical Chemistry hysical Chemistry is the study of the uderlyig physical priciples that gover the properties ad behaviour of chemical systems

More information

Mathematics of the Variation and Mole Ratio Methods of Complex Determination

Mathematics of the Variation and Mole Ratio Methods of Complex Determination Joural of the Arkasas Academy of Sciece Volume 22 Article 18 1968 Mathematics of the Variatio ad Mole Ratio Methods of omplex Determiatio James O. Wear Souther Research Support eter Follow this ad additioal

More information

ENGI Series Page 6-01

ENGI Series Page 6-01 ENGI 3425 6 Series Page 6-01 6. Series Cotets: 6.01 Sequeces; geeral term, limits, covergece 6.02 Series; summatio otatio, covergece, divergece test 6.03 Stadard Series; telescopig series, geometric series,

More information

New Correlation for Calculating Critical Pressure of Petroleum Fractions

New Correlation for Calculating Critical Pressure of Petroleum Fractions IARJSET ISSN (Olie) 2393-8021 ISSN (Prit) 2394-1588 Iteratioal Advaced Research Joural i Sciece, Egieerig ad Techology New Correlatio for Calculatig Critical Pressure of Petroleum Fractios Sayed Gomaa,

More information

R is a scalar defined as follows:

R is a scalar defined as follows: Math 8. Notes o Dot Product, Cross Product, Plaes, Area, ad Volumes This lecture focuses primarily o the dot product ad its may applicatios, especially i the measuremet of agles ad scalar projectio ad

More information

NAME: ALGEBRA 350 BLOCK 7. Simplifying Radicals Packet PART 1: ROOTS

NAME: ALGEBRA 350 BLOCK 7. Simplifying Radicals Packet PART 1: ROOTS NAME: ALGEBRA 50 BLOCK 7 DATE: Simplifyig Radicals Packet PART 1: ROOTS READ: A square root of a umber b is a solutio of the equatio x = b. Every positive umber b has two square roots, deoted b ad b or

More information

What Is Required? You need to determine the hydronium ion concentration in an aqueous solution. K w = [H 3 O + ][OH ] =

What Is Required? You need to determine the hydronium ion concentration in an aqueous solution. K w = [H 3 O + ][OH ] = Calculatig the [H3O + ] or [OH ] i Aqueous Solutio (Studet textbook page 500) 11. The cocetratio of hydroxide ios, OH (aq), i a solutio at 5C is 0.150 /. Determie the cocetratio of hydroium ios, H 3 O

More information

Lecture 1 Probability and Statistics

Lecture 1 Probability and Statistics Wikipedia: Lecture 1 Probability ad Statistics Bejami Disraeli, British statesma ad literary figure (1804 1881): There are three kids of lies: lies, damed lies, ad statistics. popularized i US by Mark

More information

DISTILLATION. Keywords: Phase Equilibrium, Isothermal Flash, Adiabatic Flash, Batch Distillation

DISTILLATION. Keywords: Phase Equilibrium, Isothermal Flash, Adiabatic Flash, Batch Distillation 25 DISTILLATION Keywords: Phase Equilibrium, Isothermal Flash, Adiabatic Flash, Batch Distillation Distillation refers to the physical separation of a mixture into two or more fractions that have different

More information

Lecture 7: Density Estimation: k-nearest Neighbor and Basis Approach

Lecture 7: Density Estimation: k-nearest Neighbor and Basis Approach STAT 425: Itroductio to Noparametric Statistics Witer 28 Lecture 7: Desity Estimatio: k-nearest Neighbor ad Basis Approach Istructor: Ye-Chi Che Referece: Sectio 8.4 of All of Noparametric Statistics.

More information

6.867 Machine learning, lecture 7 (Jaakkola) 1

6.867 Machine learning, lecture 7 (Jaakkola) 1 6.867 Machie learig, lecture 7 (Jaakkola) 1 Lecture topics: Kerel form of liear regressio Kerels, examples, costructio, properties Liear regressio ad kerels Cosider a slightly simpler model where we omit

More information

A New Solution Method for the Finite-Horizon Discrete-Time EOQ Problem

A New Solution Method for the Finite-Horizon Discrete-Time EOQ Problem This is the Pre-Published Versio. A New Solutio Method for the Fiite-Horizo Discrete-Time EOQ Problem Chug-Lu Li Departmet of Logistics The Hog Kog Polytechic Uiversity Hug Hom, Kowloo, Hog Kog Phoe: +852-2766-7410

More information

Chapter Vectors

Chapter 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 information

Statistical Pattern Recognition

Statistical Pattern Recognition Statistical Patter Recogitio Classificatio: No-Parametric Modelig Hamid R. Rabiee Jafar Muhammadi Sprig 2014 http://ce.sharif.edu/courses/92-93/2/ce725-2/ Ageda Parametric Modelig No-Parametric Modelig

More information

3.2 Properties of Division 3.3 Zeros of Polynomials 3.4 Complex and Rational Zeros of Polynomials

3.2 Properties of Division 3.3 Zeros of Polynomials 3.4 Complex and Rational Zeros of Polynomials Math 60 www.timetodare.com 3. Properties of Divisio 3.3 Zeros of Polyomials 3.4 Complex ad Ratioal Zeros of Polyomials I these sectios we will study polyomials algebraically. Most of our work will be cocered

More information

Signals & Systems Chapter3

Signals & Systems Chapter3 Sigals & Systems Chapter3 1.2 Discrete-Time (D-T) Sigals Electroic systems do most of the processig of a sigal usig a computer. A computer ca t directly process a C-T sigal but istead eeds a stream of

More information

Zeros of Polynomials

Zeros of Polynomials Math 160 www.timetodare.com 4.5 4.6 Zeros of Polyomials I these sectios we will study polyomials algebraically. Most of our work will be cocered with fidig the solutios of polyomial equatios of ay degree

More information

PAPER : IIT-JAM 2010

PAPER : 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 information

Chemical Kinetics CHAPTER 14. Chemistry: The Molecular Nature of Matter, 6 th edition By Jesperson, Brady, & Hyslop. CHAPTER 14 Chemical Kinetics

Chemical Kinetics CHAPTER 14. Chemistry: The Molecular Nature of Matter, 6 th edition By Jesperson, Brady, & Hyslop. CHAPTER 14 Chemical Kinetics Chemical Kietics CHAPTER 14 Chemistry: The Molecular Nature of Matter, 6 th editio By Jesperso, Brady, & Hyslop CHAPTER 14 Chemical Kietics Learig Objectives: Factors Affectig Reactio Rate: o Cocetratio

More information

Lecture 6 Chi Square Distribution (χ 2 ) and Least Squares Fitting

Lecture 6 Chi Square Distribution (χ 2 ) and Least Squares Fitting Lecture 6 Chi Square Distributio (χ ) ad Least Squares Fittig Chi Square Distributio (χ ) Suppose: We have a set of measuremets {x 1, x, x }. We kow the true value of each x i (x t1, x t, x t ). We would

More information

Inverse Matrix. A meaning that matrix B is an inverse of matrix A.

Inverse Matrix. A meaning that matrix B is an inverse of matrix A. Iverse Matrix Two square matrices A ad B of dimesios are called iverses to oe aother if the followig holds, AB BA I (11) The otio is dual but we ofte write 1 B A meaig that matrix B is a iverse of matrix

More information

1 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

1 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 information

RADICAL EXPRESSION. If a and x are real numbers and n is a positive integer, then x is an. n th root theorems: Example 1 Simplify

RADICAL EXPRESSION. If a and x are real numbers and n is a positive integer, then x is an. n th root theorems: Example 1 Simplify Example 1 Simplify 1.2A Radical Operatios a) 4 2 b) 16 1 2 c) 16 d) 2 e) 8 1 f) 8 What is the relatioship betwee a, b, c? What is the relatioship betwee d, e, f? If x = a, the x = = th root theorems: RADICAL

More information

(7 One- and Two-Sample Estimation Problem )

(7 One- and Two-Sample Estimation Problem ) 34 Stat Lecture Notes (7 Oe- ad Two-Sample Estimatio Problem ) ( Book*: Chapter 8,pg65) Probability& Statistics for Egieers & Scietists By Walpole, Myers, Myers, Ye Estimatio 1 ) ( ˆ S P i i Poit estimate:

More information

CEE 522 Autumn Uncertainty Concepts for Geotechnical Engineering

CEE 522 Autumn Uncertainty Concepts for Geotechnical Engineering CEE 5 Autum 005 Ucertaity Cocepts for Geotechical Egieerig Basic Termiology Set A set is a collectio of (mutually exclusive) objects or evets. The sample space is the (collectively exhaustive) collectio

More information

Round-off Errors and Computer Arithmetic - (1.2)

Round-off Errors and Computer Arithmetic - (1.2) Roud-off Errors ad Comuter Arithmetic - (1.) 1. Roud-off Errors: Roud-off errors is roduced whe a calculator or comuter is used to erform real umber calculatios. That is because the arithmetic erformed

More information

All Excuses must be taken to 233 Loomis before 4:15, Monday, April 30.

All Excuses must be taken to 233 Loomis before 4:15, Monday, April 30. Miscellaeous Notes The ed is ear do t get behid. All Excuses must be take to 233 Loomis before 4:15, Moday, April 30. The PYS 213 fial exam times are * 8-10 AM, Moday, May 7 * 8-10 AM, Tuesday, May 8 ad

More information

Chimica Inorganica 3

Chimica Inorganica 3 himica Iorgaica Irreducible Represetatios ad haracter Tables Rather tha usig geometrical operatios, it is ofte much more coveiet to employ a ew set of group elemets which are matrices ad to make the rule

More information

Unit 5. Gases (Answers)

Unit 5. Gases (Answers) Uit 5. Gases (Aswers) Upo successful completio of this uit, the studets should be able to: 5. Describe what is meat by gas pressure.. The ca had a small amout of water o the bottom to begi with. Upo heatig

More information

(3) If you replace row i of A by its sum with a multiple of another row, then the determinant is unchanged! Expand across the i th row:

(3) If you replace row i of A by its sum with a multiple of another row, then the determinant is unchanged! Expand across the i th row: Math 50-004 Tue Feb 4 Cotiue with sectio 36 Determiats The effective way to compute determiats for larger-sized matrices without lots of zeroes is to ot use the defiitio, but rather to use the followig

More information

To the use of Sellmeier formula

To the use of Sellmeier formula To the use of Sellmeier formula by Volkmar Brücker Seior Experte Service (SES) Bo ad HfT Leipzig, Germay Abstract Based o dispersio of pure silica we proposed a geeral Sellmeier formula for various dopats

More information

Q-BINOMIALS AND THE GREATEST COMMON DIVISOR. Keith R. Slavin 8474 SW Chevy Place, Beaverton, Oregon 97008, USA.

Q-BINOMIALS AND THE GREATEST COMMON DIVISOR. Keith R. Slavin 8474 SW Chevy Place, Beaverton, Oregon 97008, USA. INTEGERS: ELECTRONIC JOURNAL OF COMBINATORIAL NUMBER THEORY 8 2008, #A05 Q-BINOMIALS AND THE GREATEST COMMON DIVISOR Keith R. Slavi 8474 SW Chevy Place, Beaverto, Orego 97008, USA slavi@dsl-oly.et Received:

More information

Discrete Mathematics for CS Spring 2008 David Wagner Note 22

Discrete Mathematics for CS Spring 2008 David Wagner Note 22 CS 70 Discrete Mathematics for CS Sprig 2008 David Wager Note 22 I.I.D. Radom Variables Estimatig the bias of a coi Questio: We wat to estimate the proportio p of Democrats i the US populatio, by takig

More information

Lecture 6 Chi Square Distribution (χ 2 ) and Least Squares Fitting

Lecture 6 Chi Square Distribution (χ 2 ) and Least Squares Fitting Lecture 6 Chi Square Distributio (χ ) ad Least Squares Fittig Chi Square Distributio (χ ) Suppose: We have a set of measuremets {x 1, x, x }. We kow the true value of each x i (x t1, x t, x t ). We would

More information

Algebra of Least Squares

Algebra of Least Squares October 19, 2018 Algebra of Least Squares Geometry of Least Squares Recall that out data is like a table [Y X] where Y collects observatios o the depedet variable Y ad X collects observatios o the k-dimesioal

More information

A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence

A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence Sequeces A sequece of umbers is a fuctio whose domai is the positive itegers. We ca see that the sequece,, 2, 2, 3, 3,... is a fuctio from the positive itegers whe we write the first sequece elemet as

More information

Median and IQR The median is the value which divides the ordered data values in half.

Median and IQR The median is the value which divides the ordered data values in half. STA 666 Fall 2007 Web-based Course Notes 4: Describig Distributios Numerically Numerical summaries for quatitative variables media ad iterquartile rage (IQR) 5-umber summary mea ad stadard deviatio Media

More information

EE260: Digital Design, Spring n MUX Gate n Rudimentary functions n Binary Decoders. n Binary Encoders n Priority Encoders

EE260: Digital Design, Spring n MUX Gate n Rudimentary functions n Binary Decoders. n Binary Encoders n Priority Encoders EE260: Digital Desig, Sprig 2018 EE 260: Itroductio to Digital Desig MUXs, Ecoders, Decoders Yao Zheg Departmet of Electrical Egieerig Uiversity of Hawaiʻi at Māoa Overview of Ecoder ad Decoder MUX Gate

More information

Ray Optics Theory and Mode Theory. Dr. Mohammad Faisal Dept. of EEE, BUET

Ray Optics Theory and Mode Theory. Dr. Mohammad Faisal Dept. of EEE, BUET Ray Optics Theory ad Mode Theory Dr. Mohammad Faisal Dept. of, BUT Optical Fiber WG For light to be trasmitted through fiber core, i.e., for total iteral reflectio i medium, > Ray Theory Trasmissio Ray

More information

n 3 ln n n ln n is convergent by p-series for p = 2 > 1. n2 Therefore we can apply Limit Comparison Test to determine lutely convergent.

n 3 ln n n ln n is convergent by p-series for p = 2 > 1. n2 Therefore we can apply Limit Comparison Test to determine lutely convergent. 06 微甲 0-04 06-0 班期中考解答和評分標準. ( poits) Determie whether the series is absolutely coverget, coditioally coverget, or diverget. Please state the tests which you use. (a) ( poits) (b) ( poits) (c) ( poits)

More information

µ and π p i.e. Point Estimation x And, more generally, the population proportion is approximately equal to a sample proportion

µ and π p i.e. Point Estimation x And, more generally, the population proportion is approximately equal to a sample proportion Poit Estimatio Poit estimatio is the rather simplistic (ad obvious) process of usig the kow value of a sample statistic as a approximatio to the ukow value of a populatio parameter. So we could for example

More information

P.3 Polynomials and Special products

P.3 Polynomials and Special products Precalc Fall 2016 Sectios P.3, 1.2, 1.3, P.4, 1.4, P.2 (radicals/ratioal expoets), 1.5, 1.6, 1.7, 1.8, 1.1, 2.1, 2.2 I Polyomial defiitio (p. 28) a x + a x +... + a x + a x 1 1 0 1 1 0 a x + a x +... +

More information

Mathematical Description of Discrete-Time Signals. 9/10/16 M. J. Roberts - All Rights Reserved 1

Mathematical Description of Discrete-Time Signals. 9/10/16 M. J. Roberts - All Rights Reserved 1 Mathematical Descriptio of Discrete-Time Sigals 9/10/16 M. J. Roberts - All Rights Reserved 1 Samplig ad Discrete Time Samplig is the acquisitio of the values of a cotiuous-time sigal at discrete poits

More information

Miscellaneous Notes. Lecture 19, p 1

Miscellaneous Notes. Lecture 19, p 1 Miscellaeous Notes The ed is ear do t get behid. All Excuses must be take to 233 Loomis before oo, Thur, Apr. 25. The PHYS 213 fial exam times are * 8-10 AM, Moday, May 6 * 1:30-3:30 PM, Wed, May 8 The

More information

Data Analysis and Statistical Methods Statistics 651

Data Analysis and Statistical Methods Statistics 651 Data Aalysis ad Statistical Methods Statistics 651 http://www.stat.tamu.edu/~suhasii/teachig.html Suhasii Subba Rao Review of testig: Example The admistrator of a ursig home wats to do a time ad motio

More information

Chapter 4 : Laplace Transform

Chapter 4 : Laplace Transform 4. Itroductio Laplace trasform is a alterative to solve the differetial equatio by the complex frequecy domai ( s = σ + jω), istead of the usual time domai. The DE ca be easily trasformed ito a algebraic

More information

Sequences A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence

Sequences A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence Sequeces A sequece of umbers is a fuctio whose domai is the positive itegers. We ca see that the sequece 1, 1, 2, 2, 3, 3,... is a fuctio from the positive itegers whe we write the first sequece elemet

More information

Curve Sketching Handout #5 Topic Interpretation Rational Functions

Curve Sketching Handout #5 Topic Interpretation Rational Functions Curve Sketchig Hadout #5 Topic Iterpretatio Ratioal Fuctios A ratioal fuctio is a fuctio f that is a quotiet of two polyomials. I other words, p ( ) ( ) f is a ratioal fuctio if p ( ) ad q ( ) are polyomials

More information

Linearly Independent Sets, Bases. Review. Remarks. A set of vectors,,, in a vector space is said to be linearly independent if the vector equation

Linearly Independent Sets, Bases. Review. Remarks. A set of vectors,,, in a vector space is said to be linearly independent if the vector equation Liearly Idepedet Sets Bases p p c c p Review { v v vp} A set of vectors i a vector space is said to be liearly idepedet if the vector equatio cv + c v + + c has oly the trivial solutio = = { v v vp} The

More information