Numerical simulation of various flows over a square cavity

Size: px
Start display at page:

Download "Numerical simulation of various flows over a square cavity"

Transcription

1 Iteratoal Joural of Mechacal Egeerg ad Research, ISSN Vol. 5 No.1 (2015) Research Ida Publcatos; Numercal smulato of varous flows over a square cavty N.Sethl Kumar 1, M.Revath 2, P.Raju 3 Assstat Professor Abstract Numercal smulato of Euler equatos ad Naver-Stoke equato s carred out the preset work where for each smulato we took oe or more example problem say Quas-Oe- Dmesoal ozzle flow for Euler equatos ad vscous compressble flow over a square cavty, square cylder ad tall buldg for Naver-Stoke equato. The etre problems are solved here umercally ad vestgated. Here dfferet computatoal methods are appled for each problem ad show the results. Fte dfferece method ad Fte Volume method both are studed ad appled here for solvg the Euler ad Naver-Stoke Equatos respectvely for the respectve problem. All the problems are solved umercally the physcal plae tself wthout trasferrg t to the computatoal plae usg structured grd. I the preset vestgato, we got reasoably good agreemet betwee the umercal ad the aalytcal result. Keywords: Numercal smulato, Dmesoal ozzle flow, CFD. 1. INTRODCTION expesve, tme-cosumg or eve dagerous Numercal smulato usg computers expermets laboratores or o ste. or computatoal smulato has creasgly become a very mportat approach for solvg complex practcal problems egeerg ad Numercal smulato wth computers plays a valuable role provdg a valdato for theores offers sghts to the expermetal scece. Numercal smulato traslates results ad asssts the terpretato or eve mportat aspects of a physcal problem to a dscrete form of mathematcal descrpto, recreates ad solves the problem o a computer, ad reveals pheomea vrtually the dscovery of ew pheomea. It acts also as a brdge betwee the expermetal models ad the theoretcal predctos. The overall goal of the feld of accordg to the requremets of the aalysts. umercal smulato s the desg ad Rather tha adoptg the tradtoal aalyss of techques to gve approxmate but theoretcal practce of costructg layers of accurate solutos to hard problems. The assumptos ad approxmato, ths moder Netlb repostory cotas varous collectos umercal approach attacks the orgal of software routes for umercal problems, problem all ts detal wthout makg too may assumptos, wth the help of the mostly FORTRAN ad C. Commercal products mplemetg creasg computer power. Numercal may dfferet umercal algorthms clude smulato provdes a alteratve tool of scetfc vestgato, stead of carryg out the IMSL ad NAG lbrares; a free alteratve s the GN Scetfc Lbrary. There are 1 1

2 Iteratoal Joural of Mechacal Egeerg ad Research, ISSN Vol. 5 No.1 (2015) Research Ida Publcatos; several popular umercal computg applcatos such as MATLAB, S-PLS, Lab VIEW, ad IDL as well as free ad ope source alteratves such as Free Mat, Sclab, GN Octave (smlar to Matlab), IT++ (a C++ lbrary), R (smlar to S-PLS) ad certa varats of Pytho. Performace vares wdely: whle vector ad matrx operatos are usually fast, scalar loops may vary speed by more tha a order of magtude. May computer algebra systems such as Mathematc also beeft from the avalablty of arbtrary precso arthmetc whch ca provde more accurate results. 2. COMPTATIONAL METHODS The fte dfferece scheme for the umercal smulato of quas oe dmesoal ozzle flow problem cossts of followg methods. Here, both explct ad mplct methods are used for the same problem for uderstadg the dea ad usage. 1) Mac-Cormack s Predctor Corrector Method Mac Cormack s techque s a explct fte dfferece techque, whch s secod order accurate both space ad tme. The tme marchg soluto usg Mac Cormack s techque for the Euler equatos [1] proceeds as follows: The value of the soluto vector at tme +1 s obtaed as: t 1 t Where value of t u t av s a represetatve mea betwee tmes ad +1.Ths average tme dervatve s obtaed from a predctor corrector phlosophy as Follows: Predctor Step: I the goverg equato the spatal dervatves are replaced by forward dffereces to gve: F 1 F H t x I ths equato all the values at tme are kow.e. the RHS s kow. Now, a predcted value of s obtaed from the frst two terms of a Taylor seres as: t 1 t I eq. (3.3) s kow ad kow from eq. (3.2). Hece readly obtaed. However, 1 1 t s ca be s oly a predcted value ad s oly frst order accurate sce eq. (3.3) cotas oly frst two terms the Taylor seres. sg, H F F( ) H( ) ad ca be foud out. Corrector Step: I the corrector steps a predcted value of the tme dervatve at tme +1 s obtaed by substtutg the predcted value of the equato, replacg the spatal dervatves by rearward dffereces. F 1 F H t x... (3.17) 2 191

3 Iteratoal Joural of Mechacal Egeerg ad Research, ISSN Vol. 5 No.1 (2015) Research Ida Publcatos; The average value of the tme dervatve of s ow obtaed from the arthmetc mea of 3 u a ad t 1 (3.4) respectvely. obtaed from eq. (3.2) ad eq. 1 1 t av 2 t t... (3.18) Thus the fal corrected value of ca be obtaed from eq. (3.1), repeated below: t 1 t I Mac Cormack s techque the use of forward dffereces o the predctor step ad rearward dffereces o the corrector step s ot sacrosact; the same order of accuracy s obtaed by usg rearward dffereces o the predctor ad forward dffereces o the corrector. Ideed, a tme marchg soluto ca be carred out by alteratg betwee these two sequeces at every other tme step. 2) Crak Ncolso method wth Beam ad Warmg learzato techque Quas Lear formulato: As F=F () by the cha rule of F F dfferetato: x x F Deotg A, A s called the Jacoba of the flux vector. It s obtaed by dfferetatg each of the elemets of flux vector F oe by oe by each of the elemets of vector. Equato show above s ow wrtte as: A H 0 t x Case 1: Coverget-Dverget ozzle (Fg : Nozzle -1 show above) doma wth Purely subsoc flow Nozzle cross secto area A(x) =1+ (2.2*(x- 1.5)*(x-1.5)); 0 x 3 ft. No. of grd pots: 31.e. step sze x = 0.1 Courat No. = a) usg Coservato form of goverg equato (after 1400 tme steps) b) usg o coservato form of goverg equato (after 1400 tme steps) Case 2 : Coverget-Dverget ozzle (fg: Nozzle-2 show above) doma wth subsoc-supersoc setropc flow Nozzle cross secto area a) sg Coservato form of goverg equato (after 5000 tme steps) 192

4 Iteratoal Joural of Mechacal Egeerg ad Research, ISSN Vol. 5 No.1 (2015) Research Ida Publcatos; Case 3a: Coverget-Dverget ozzle (fg: Nozzle-1 show above) doma wth subsoc-supersoc flow wth ormal shock sde (wthout Artfcal vscosty) The umercal results were obtaed usg Naver- Stokes equato based o Cosstet Flux Recostructo cocept as descrbed chapter 4 for uformly dstrbuted grd. The covergece crtero of was appled. Fgure 2a). Pressure cotours ad Streamles patter for Reyolds umber 75 Valdato of the results for Re 75,150 &150 ad blockage rato of 11% Reyolds Grd Drag Co Lft Co Number Sze effcets effcets Numercal calculatos of lamar flow past a square cylder for varous Reyolds umber (say 75,150,500) are doe by solvg the Naver-Stoke equato ad the results are obtaed. The drag ad lft coeffcets are calculated for all the flow cases ad tabulated above. If compared wth the results of some the research papers for the approprate blockage rato, Reyolds umber, grd sze ad where the square cylder was located, some results get matched. Fgure 2b). Pressure cotours ad Streamles patter for Reyolds umber 150 Refereces A.K.Saha, G.Bswas, K.Muraldhar S. Turk, H. Abbass, Reyolds umber Grd Sze 178 X X 77 Drag Co effce t Fgure 2c). Pressure cotours ad Streamles patter for Reyolds umber 500 R.Frake, W.Rod ad B.Schoug X

5 Iteratoal Joural of Mechacal Egeerg ad Research, ISSN Vol. 5 No.1 (2015) Research Ida Publcatos; 3. CONCLSION derstadg of the mplemetato of varous CFD techques to varous problems ad got the umercal results matchg wth aalytcal results. I Quas oe dmesoal ozzle flow problem, the Euler equatos wll be solved umercally usg fte dfferece scheme. For uderstadg of the mplemetato of fte volume method (CFR Scheme) to develop a compressble Naver- Stokes solver for two dmesoal geometres usg structured grd, flow over a square cavty problem was studed ad matched the umercal result wth joural paper results. REFERENCES 1. ABDALLAH S Numercal soluto for the pressure Posso equato wth Neuma boudary codto usg a o staggered grd, I. Joural of Computatoal Physcs; 70: ABDALLAH S.1987 Numercal solutos for the compressble Naver Stokes equato prmtve varables usg a o-staggered grd, Joural of Computatoal Physcs;70: A.B.HARICHANDRAN et al, CFR: A fte volume approach for computg compressble vscous flow, Joural of Appled flud mechacs. 4. AHMAD SOHANKAR, C. NORBERG, AND L. DAVIDSON 1999, Smulato of three-dmesoal flow aroud a square cylder at moderate Reyolds umber Physcs of fluds 11, AKHILESH K.SAH, R.P.CHHABRA, V.ESWARAN Two-dmesoal usteady lamar flow of a power law flud across a square cylder. Joural of No-Newtoa Flud Mechacs 160, 6. A. ROY et al., 2006 A fte volume method for vscous compressble flows usg a cosstet flux recostructo scheme, Iteratoal joural for umercal methods fluds, Volume 52, Issue 3, pages B.GALLETTI, C.H.BRNEA, L.ZANNETTI, A.IOLLO, 2004 Loworder modelg of lamar flow regmes past a cofed square cylder, Joural of Flud Mech, Vol.503, pages CHENG M. TAN S. H. HNG K.C, 2005, Lear shear flow over a square cylder at low Reyolds umber Physcs of fluds, Volume 17. Pages DENG GB, PIQET J, QETEY P, VISONNEA M Icompressble flow calculatos wth a cosstet physcal terpolato fte volume approach. Computers ad Fluds; 23(8): FRANKE.R. RODI.W. SCHNNG.B. 19, Numercal calculato of lamar vortex sheddg Flow past cylders, Joural of Wd Egeerg ad Idustral Aerodyamcs, Volume 35. Pages GERA.B.PAVAN K. SHARMA,SINGH.R.K 2010,CFD aalyss of 2D usteady flow aroud a square cylder Iteratoal Joural of Appled Egeerg Research, Ddgul Volume1, 12. GRESHO PM Some curret CFD ssues relevat to the compressble Naver Stokes equatos. Computer Methods Appled Mechacs ad Egeerg; 87: HARLOW FH, WELCH JE. 1965, Numercal calculato of tme-depedet vscous compressble flow of flud wth free surface. Physcs of Fluds; 8(12):

Beam Warming Second-Order Upwind Method

Beam Warming Second-Order Upwind Method Beam Warmg Secod-Order Upwd Method Petr Valeta Jauary 6, 015 Ths documet s a part of the assessmet work for the subject 1DRP Dfferetal Equatos o Computer lectured o FNSPE CTU Prague. Abstract Ths documet

More information

The numerical simulation of compressible flow in a Shubin nozzle using schemes of Bean-Warming and flux vector splitting

The numerical simulation of compressible flow in a Shubin nozzle using schemes of Bean-Warming and flux vector splitting The umercal smulato of compressble flow a Shub ozzle usg schemes of Bea-Warmg ad flux vector splttg Gh. Paygaeh a, A. Hadd b,*, M. Hallaj b ad N. Garjas b a Departmet of Mechacal Egeerg, Shahd Rajaee Teacher

More information

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory ROAD MAP... AE301 Aerodyamcs I UNIT C: 2-D Arfols C-1: Aerodyamcs of Arfols 1 C-2: Aerodyamcs of Arfols 2 C-3: Pael Methods C-4: Th Arfol Theory AE301 Aerodyamcs I Ut C-3: Lst of Subects Problem Solutos?

More information

End of Finite Volume Methods Cartesian grids. Solution of the Navier-Stokes Equations. REVIEW Lecture 17: Higher order (interpolation) schemes

End of Finite Volume Methods Cartesian grids. Solution of the Navier-Stokes Equations. REVIEW Lecture 17: Higher order (interpolation) schemes REVIEW Lecture 17: Numercal Flud Mechacs Sprg 2015 Lecture 18 Ed of Fte Volume Methods Cartesa grds Hgher order (terpolato) schemes Soluto of the Naver-Stokes Equatos Dscretzato of the covectve ad vscous

More information

Cubic Nonpolynomial Spline Approach to the Solution of a Second Order Two-Point Boundary Value Problem

Cubic Nonpolynomial Spline Approach to the Solution of a Second Order Two-Point Boundary Value Problem Joural of Amerca Scece ;6( Cubc Nopolyomal Sple Approach to the Soluto of a Secod Order Two-Pot Boudary Value Problem W.K. Zahra, F.A. Abd El-Salam, A.A. El-Sabbagh ad Z.A. ZAk * Departmet of Egeerg athematcs

More information

Functions of Random Variables

Functions of Random Variables Fuctos of Radom Varables Chapter Fve Fuctos of Radom Varables 5. Itroducto A geeral egeerg aalyss model s show Fg. 5.. The model output (respose) cotas the performaces of a system or product, such as weght,

More information

ECE 595, Section 10 Numerical Simulations Lecture 19: FEM for Electronic Transport. Prof. Peter Bermel February 22, 2013

ECE 595, Section 10 Numerical Simulations Lecture 19: FEM for Electronic Transport. Prof. Peter Bermel February 22, 2013 ECE 595, Secto 0 Numercal Smulatos Lecture 9: FEM for Electroc Trasport Prof. Peter Bermel February, 03 Outle Recap from Wedesday Physcs-based devce modelg Electroc trasport theory FEM electroc trasport

More information

Analysis of Lagrange Interpolation Formula

Analysis of Lagrange Interpolation Formula P IJISET - Iteratoal Joural of Iovatve Scece, Egeerg & Techology, Vol. Issue, December 4. www.jset.com ISS 348 7968 Aalyss of Lagrage Iterpolato Formula Vjay Dahya PDepartmet of MathematcsMaharaja Surajmal

More information

Fourth Order Four-Stage Diagonally Implicit Runge-Kutta Method for Linear Ordinary Differential Equations ABSTRACT INTRODUCTION

Fourth Order Four-Stage Diagonally Implicit Runge-Kutta Method for Linear Ordinary Differential Equations ABSTRACT INTRODUCTION Malasa Joural of Mathematcal Sceces (): 95-05 (00) Fourth Order Four-Stage Dagoall Implct Ruge-Kutta Method for Lear Ordar Dfferetal Equatos Nur Izzat Che Jawas, Fudzah Ismal, Mohamed Sulema, 3 Azm Jaafar

More information

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines It J Cotemp Math Sceces, Vol 5, 2010, o 19, 921-929 Solvg Costraed Flow-Shop Schedulg Problems wth Three Maches P Pada ad P Rajedra Departmet of Mathematcs, School of Advaced Sceces, VIT Uversty, Vellore-632

More information

Bounds on the expected entropy and KL-divergence of sampled multinomial distributions. Brandon C. Roy

Bounds on the expected entropy and KL-divergence of sampled multinomial distributions. Brandon C. Roy Bouds o the expected etropy ad KL-dvergece of sampled multomal dstrbutos Brado C. Roy bcroy@meda.mt.edu Orgal: May 18, 2011 Revsed: Jue 6, 2011 Abstract Iformato theoretc quattes calculated from a sampled

More information

Lecture 12 APPROXIMATION OF FIRST ORDER DERIVATIVES

Lecture 12 APPROXIMATION OF FIRST ORDER DERIVATIVES FDM: Appromato of Frst Order Dervatves Lecture APPROXIMATION OF FIRST ORDER DERIVATIVES. INTRODUCTION Covectve term coservato equatos volve frst order dervatves. The smplest possble approach for dscretzato

More information

Finite Difference Approximations for Fractional Reaction-Diffusion Equations and the Application In PM2.5

Finite Difference Approximations for Fractional Reaction-Diffusion Equations and the Application In PM2.5 Iteratoal Symposum o Eergy Scece ad Chemcal Egeerg (ISESCE 5) Fte Dfferece Appromatos for Fractoal Reacto-Dffuso Equatos ad the Applcato I PM5 Chagpg Xe, a, Lag L,b, Zhogzha Huag,c, Jya L,d, PegLag L,e

More information

Comparing Different Estimators of three Parameters for Transmuted Weibull Distribution

Comparing Different Estimators of three Parameters for Transmuted Weibull Distribution Global Joural of Pure ad Appled Mathematcs. ISSN 0973-768 Volume 3, Number 9 (207), pp. 55-528 Research Ida Publcatos http://www.rpublcato.com Comparg Dfferet Estmators of three Parameters for Trasmuted

More information

CH E 374 Computational Methods in Engineering Fall 2007

CH E 374 Computational Methods in Engineering Fall 2007 CH E 7 Computatoal Methods Egeerg Fall 007 Sample Soluto 5. The data o the varato of the rato of stagato pressure to statc pressure (r ) wth Mach umber ( M ) for the flow through a duct are as follows:

More information

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions Iteratoal Joural of Computatoal Egeerg Research Vol, 0 Issue, Estmato of Stress- Stregth Relablty model usg fte mxture of expoetal dstrbutos K.Sadhya, T.S.Umamaheswar Departmet of Mathematcs, Lal Bhadur

More information

A NEW NUMERICAL APPROACH FOR SOLVING HIGH-ORDER LINEAR AND NON-LINEAR DIFFERANTIAL EQUATIONS

A NEW NUMERICAL APPROACH FOR SOLVING HIGH-ORDER LINEAR AND NON-LINEAR DIFFERANTIAL EQUATIONS Secer, A., et al.: A New Numerıcal Approach for Solvıg Hıgh-Order Lıear ad No-Lıear... HERMAL SCIENCE: Year 8, Vol., Suppl., pp. S67-S77 S67 A NEW NUMERICAL APPROACH FOR SOLVING HIGH-ORDER LINEAR AND NON-LINEAR

More information

Generalized One-Step Third Derivative Implicit Hybrid Block Method for the Direct Solution of Second Order Ordinary Differential Equation

Generalized One-Step Third Derivative Implicit Hybrid Block Method for the Direct Solution of Second Order Ordinary Differential Equation Appled Mathematcal Sceces, Vol. 1, 16, o. 9, 417-4 HIKARI Ltd, www.m-hkar.com http://dx.do.org/1.1988/ams.16.51667 Geeralzed Oe-Step Thrd Dervatve Implct Hybrd Block Method for the Drect Soluto of Secod

More information

BERNSTEIN COLLOCATION METHOD FOR SOLVING NONLINEAR DIFFERENTIAL EQUATIONS. Aysegul Akyuz Dascioglu and Nese Isler

BERNSTEIN COLLOCATION METHOD FOR SOLVING NONLINEAR DIFFERENTIAL EQUATIONS. Aysegul Akyuz Dascioglu and Nese Isler Mathematcal ad Computatoal Applcatos, Vol. 8, No. 3, pp. 293-300, 203 BERNSTEIN COLLOCATION METHOD FOR SOLVING NONLINEAR DIFFERENTIAL EQUATIONS Aysegul Ayuz Dascoglu ad Nese Isler Departmet of Mathematcs,

More information

ESS Line Fitting

ESS Line Fitting ESS 5 014 17. Le Fttg A very commo problem data aalyss s lookg for relatoshpetwee dfferet parameters ad fttg les or surfaces to data. The smplest example s fttg a straght le ad we wll dscuss that here

More information

UNIT 2 SOLUTION OF ALGEBRAIC AND TRANSCENDENTAL EQUATIONS

UNIT 2 SOLUTION OF ALGEBRAIC AND TRANSCENDENTAL EQUATIONS Numercal Computg -I UNIT SOLUTION OF ALGEBRAIC AND TRANSCENDENTAL EQUATIONS Structure Page Nos..0 Itroducto 6. Objectves 7. Ital Approxmato to a Root 7. Bsecto Method 8.. Error Aalyss 9.4 Regula Fals Method

More information

2006 Jamie Trahan, Autar Kaw, Kevin Martin University of South Florida United States of America

2006 Jamie Trahan, Autar Kaw, Kevin Martin University of South Florida United States of America SOLUTION OF SYSTEMS OF SIMULTANEOUS LINEAR EQUATIONS Gauss-Sedel Method 006 Jame Traha, Autar Kaw, Kev Mart Uversty of South Florda Uted States of Amerca kaw@eg.usf.edu Itroducto Ths worksheet demostrates

More information

A MLPG Meshless Method for Numerical Simulaton of Unsteady Incompressible Flows

A MLPG Meshless Method for Numerical Simulaton of Unsteady Incompressible Flows Joural of Appled Flud Mechacs, Vol. x, No. x, pp. x-x, 00x. Avalable ole at www.afmole.et, ISSN 735-3645. A MLPG Meshless Method for Numercal Smulato of Usteady Icompressble Flows Ira Saeedpaah Assstat

More information

DKA method for single variable holomorphic functions

DKA method for single variable holomorphic functions DKA method for sgle varable holomorphc fuctos TOSHIAKI ITOH Itegrated Arts ad Natural Sceces The Uversty of Toushma -, Mamhosama, Toushma, 770-8502 JAPAN Abstract: - Durad-Kerer-Aberth (DKA method for

More information

Simple Linear Regression

Simple Linear Regression Statstcal Methods I (EST 75) Page 139 Smple Lear Regresso Smple regresso applcatos are used to ft a model descrbg a lear relatoshp betwee two varables. The aspects of least squares regresso ad correlato

More information

On Modified Interval Symmetric Single-Step Procedure ISS2-5D for the Simultaneous Inclusion of Polynomial Zeros

On Modified Interval Symmetric Single-Step Procedure ISS2-5D for the Simultaneous Inclusion of Polynomial Zeros It. Joural of Math. Aalyss, Vol. 7, 2013, o. 20, 983-988 HIKARI Ltd, www.m-hkar.com O Modfed Iterval Symmetrc Sgle-Step Procedure ISS2-5D for the Smultaeous Icluso of Polyomal Zeros 1 Nora Jamalud, 1 Masor

More information

Analysis of Variance with Weibull Data

Analysis of Variance with Weibull Data Aalyss of Varace wth Webull Data Lahaa Watthaacheewaul Abstract I statstcal data aalyss by aalyss of varace, the usual basc assumptos are that the model s addtve ad the errors are radomly, depedetly, ad

More information

Towards developing a reacting- DNS code Design and numerical issues

Towards developing a reacting- DNS code Design and numerical issues Towards developg a reactg- DNS code Desg ad umercal ssues Rx Yu 20-03-09 20-03-09 FM teral semar Motvatos Why we eed a Reactg DNS code No model for both flow (turbulece) ad combusto Study applcatos of

More information

Ordinary Least Squares Regression. Simple Regression. Algebra and Assumptions.

Ordinary Least Squares Regression. Simple Regression. Algebra and Assumptions. Ordary Least Squares egresso. Smple egresso. Algebra ad Assumptos. I ths part of the course we are gog to study a techque for aalysg the lear relatoshp betwee two varables Y ad X. We have pars of observatos

More information

ENGI 3423 Simple Linear Regression Page 12-01

ENGI 3423 Simple Linear Regression Page 12-01 ENGI 343 mple Lear Regresso Page - mple Lear Regresso ometmes a expermet s set up where the expermeter has cotrol over the values of oe or more varables X ad measures the resultg values of aother varable

More information

Comparison of Dual to Ratio-Cum-Product Estimators of Population Mean

Comparison of Dual to Ratio-Cum-Product Estimators of Population Mean Research Joural of Mathematcal ad Statstcal Sceces ISS 30 6047 Vol. 1(), 5-1, ovember (013) Res. J. Mathematcal ad Statstcal Sc. Comparso of Dual to Rato-Cum-Product Estmators of Populato Mea Abstract

More information

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best Error Aalyss Preamble Wheever a measuremet s made, the result followg from that measuremet s always subject to ucertaty The ucertaty ca be reduced by makg several measuremets of the same quatty or by mprovg

More information

Bootstrap Method for Testing of Equality of Several Coefficients of Variation

Bootstrap Method for Testing of Equality of Several Coefficients of Variation Cloud Publcatos Iteratoal Joural of Advaced Mathematcs ad Statstcs Volume, pp. -6, Artcle ID Sc- Research Artcle Ope Access Bootstrap Method for Testg of Equalty of Several Coeffcets of Varato Dr. Navee

More information

Research Article A New Derivation and Recursive Algorithm Based on Wronskian Matrix for Vandermonde Inverse Matrix

Research Article A New Derivation and Recursive Algorithm Based on Wronskian Matrix for Vandermonde Inverse Matrix Mathematcal Problems Egeerg Volume 05 Artcle ID 94757 7 pages http://ddoorg/055/05/94757 Research Artcle A New Dervato ad Recursve Algorthm Based o Wroska Matr for Vadermode Iverse Matr Qu Zhou Xja Zhag

More information

Numerical Simulations of the Complex Modied Korteweg-de Vries Equation. Thiab R. Taha. The University of Georgia. Abstract

Numerical Simulations of the Complex Modied Korteweg-de Vries Equation. Thiab R. Taha. The University of Georgia. Abstract Numercal Smulatos of the Complex Moded Korteweg-de Vres Equato Thab R. Taha Computer Scece Departmet The Uversty of Georga Athes, GA 002 USA Tel 0-542-2911 e-mal thab@cs.uga.edu Abstract I ths paper mplemetatos

More information

ANALYSIS ON THE NATURE OF THE BASIC EQUATIONS IN SYNERGETIC INTER-REPRESENTATION NETWORK

ANALYSIS ON THE NATURE OF THE BASIC EQUATIONS IN SYNERGETIC INTER-REPRESENTATION NETWORK Far East Joural of Appled Mathematcs Volume, Number, 2008, Pages Ths paper s avalable ole at http://www.pphm.com 2008 Pushpa Publshg House ANALYSIS ON THE NATURE OF THE ASI EQUATIONS IN SYNERGETI INTER-REPRESENTATION

More information

Dynamic Analysis of Axially Beam on Visco - Elastic Foundation with Elastic Supports under Moving Load

Dynamic Analysis of Axially Beam on Visco - Elastic Foundation with Elastic Supports under Moving Load Dyamc Aalyss of Axally Beam o Vsco - Elastc Foudato wth Elastc Supports uder Movg oad Saeed Mohammadzadeh, Seyed Al Mosayeb * Abstract: For dyamc aalyses of ralway track structures, the algorthm of soluto

More information

On the convergence of derivatives of Bernstein approximation

On the convergence of derivatives of Bernstein approximation O the covergece of dervatves of Berste approxmato Mchael S. Floater Abstract: By dfferetatg a remader formula of Stacu, we derve both a error boud ad a asymptotc formula for the dervatves of Berste approxmato.

More information

d dt d d dt dt Also recall that by Taylor series, / 2 (enables use of sin instead of cos-see p.27 of A&F) dsin

d dt d d dt dt Also recall that by Taylor series, / 2 (enables use of sin instead of cos-see p.27 of A&F) dsin Learzato of the Swg Equato We wll cover sectos.5.-.6 ad begg of Secto 3.3 these otes. 1. Sgle mache-fte bus case Cosder a sgle mache coected to a fte bus, as show Fg. 1 below. E y1 V=1./_ Fg. 1 The admttace

More information

PGE 310: Formulation and Solution in Geosystems Engineering. Dr. Balhoff. Interpolation

PGE 310: Formulation and Solution in Geosystems Engineering. Dr. Balhoff. Interpolation PGE 30: Formulato ad Soluto Geosystems Egeerg Dr. Balhoff Iterpolato Numercal Methods wth MATLAB, Recktewald, Chapter 0 ad Numercal Methods for Egeers, Chapra ad Caale, 5 th Ed., Part Fve, Chapter 8 ad

More information

EVALUATION OF FUNCTIONAL INTEGRALS BY MEANS OF A SERIES AND THE METHOD OF BOREL TRANSFORM

EVALUATION OF FUNCTIONAL INTEGRALS BY MEANS OF A SERIES AND THE METHOD OF BOREL TRANSFORM EVALUATION OF FUNCTIONAL INTEGRALS BY MEANS OF A SERIES AND THE METHOD OF BOREL TRANSFORM Jose Javer Garca Moreta Ph. D research studet at the UPV/EHU (Uversty of Basque coutry) Departmet of Theoretcal

More information

1. A real number x is represented approximately by , and we are told that the relative error is 0.1 %. What is x? Note: There are two answers.

1. A real number x is represented approximately by , and we are told that the relative error is 0.1 %. What is x? Note: There are two answers. PROBLEMS A real umber s represeted appromately by 63, ad we are told that the relatve error s % What s? Note: There are two aswers Ht : Recall that % relatve error s What s the relatve error volved roudg

More information

Comparison of Parameters of Lognormal Distribution Based On the Classical and Posterior Estimates

Comparison of Parameters of Lognormal Distribution Based On the Classical and Posterior Estimates Joural of Moder Appled Statstcal Methods Volume Issue Artcle 8 --03 Comparso of Parameters of Logormal Dstrbuto Based O the Classcal ad Posteror Estmates Raja Sulta Uversty of Kashmr, Sragar, Ida, hamzasulta8@yahoo.com

More information

1 0, x? x x. 1 Root finding. 1.1 Introduction. Solve[x^2-1 0,x] {{x -1},{x 1}} Plot[x^2-1,{x,-2,2}] 3

1 0, x? x x. 1 Root finding. 1.1 Introduction. Solve[x^2-1 0,x] {{x -1},{x 1}} Plot[x^2-1,{x,-2,2}] 3 Adrew Powuk - http://www.powuk.com- Math 49 (Numercal Aalyss) Root fdg. Itroducto f ( ),?,? Solve[^-,] {{-},{}} Plot[^-,{,-,}] Cubc equato https://e.wkpeda.org/wk/cubc_fucto Quartc equato https://e.wkpeda.org/wk/quartc_fucto

More information

MOLECULAR VIBRATIONS

MOLECULAR VIBRATIONS MOLECULAR VIBRATIONS Here we wsh to vestgate molecular vbratos ad draw a smlarty betwee the theory of molecular vbratos ad Hückel theory. 1. Smple Harmoc Oscllator Recall that the eergy of a oe-dmesoal

More information

ECE606: Solid State Devices Lecture 13 Solutions of the Continuity Eqs. Analytical & Numerical

ECE606: Solid State Devices Lecture 13 Solutions of the Continuity Eqs. Analytical & Numerical ECE66: Sold State Devces Lecture 13 Solutos of the Cotuty Eqs. Aalytcal & Numercal Gerhard Klmeck gekco@purdue.edu Outle Aalytcal Solutos to the Cotuty Equatos 1) Example problems ) Summary Numercal Solutos

More information

Part 4b Asymptotic Results for MRR2 using PRESS. Recall that the PRESS statistic is a special type of cross validation procedure (see Allen (1971))

Part 4b Asymptotic Results for MRR2 using PRESS. Recall that the PRESS statistic is a special type of cross validation procedure (see Allen (1971)) art 4b Asymptotc Results for MRR usg RESS Recall that the RESS statstc s a specal type of cross valdato procedure (see Alle (97)) partcular to the regresso problem ad volves fdg Y $,, the estmate at the

More information

Multi-Step Methods Applied to Nonlinear Equations of Power Networks

Multi-Step Methods Applied to Nonlinear Equations of Power Networks Electrcal ad Electroc Egeerg 03, 3(5): 8-3 DOI: 0.593/j.eee.030305.0 Mult-Step s Appled to olear Equatos of Power etworks Rubé llafuerte D.,*, Rubé A. llafuerte S., Jesús Meda C. 3, Edgar Meja S. 3 Departmet

More information

DIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS

DIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS DIFFERENTIAL GEOMETRIC APPROACH TO HAMILTONIAN MECHANICS Course Project: Classcal Mechacs (PHY 40) Suja Dabholkar (Y430) Sul Yeshwath (Y444). Itroducto Hamltoa mechacs s geometry phase space. It deals

More information

Median as a Weighted Arithmetic Mean of All Sample Observations

Median as a Weighted Arithmetic Mean of All Sample Observations Meda as a Weghted Arthmetc Mea of All Sample Observatos SK Mshra Dept. of Ecoomcs NEHU, Shllog (Ida). Itroducto: Iumerably may textbooks Statstcs explctly meto that oe of the weakesses (or propertes) of

More information

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model Lecture 7. Cofdece Itervals ad Hypothess Tests the Smple CLR Model I lecture 6 we troduced the Classcal Lear Regresso (CLR) model that s the radom expermet of whch the data Y,,, K, are the outcomes. The

More information

Lecture Note to Rice Chapter 8

Lecture Note to Rice Chapter 8 ECON 430 HG revsed Nov 06 Lecture Note to Rce Chapter 8 Radom matrces Let Y, =,,, m, =,,, be radom varables (r.v. s). The matrx Y Y Y Y Y Y Y Y Y Y = m m m s called a radom matrx ( wth a ot m-dmesoal dstrbuto,

More information

The Mathematical Appendix

The Mathematical Appendix The Mathematcal Appedx Defto A: If ( Λ, Ω, where ( λ λ λ whch the probablty dstrbutos,,..., Defto A. uppose that ( Λ,,..., s a expermet type, the σ-algebra o λ λ λ are defed s deoted by ( (,,...,, σ Ω.

More information

Mu Sequences/Series Solutions National Convention 2014

Mu Sequences/Series Solutions National Convention 2014 Mu Sequeces/Seres Solutos Natoal Coveto 04 C 6 E A 6C A 6 B B 7 A D 7 D C 7 A B 8 A B 8 A C 8 E 4 B 9 B 4 E 9 B 4 C 9 E C 0 A A 0 D B 0 C C Usg basc propertes of arthmetc sequeces, we fd a ad bm m We eed

More information

Block-Based Compact Thermal Modeling of Semiconductor Integrated Circuits

Block-Based Compact Thermal Modeling of Semiconductor Integrated Circuits Block-Based Compact hermal Modelg of Semcoductor Itegrated Crcuts Master s hess Defese Caddate: Jg Ba Commttee Members: Dr. Mg-Cheg Cheg Dr. Daqg Hou Dr. Robert Schllg July 27, 2009 Outle Itroducto Backgroud

More information

Numerical Analysis Formulae Booklet

Numerical Analysis Formulae Booklet Numercal Aalyss Formulae Booklet. Iteratve Scemes for Systems of Lear Algebrac Equatos:.... Taylor Seres... 3. Fte Dfferece Approxmatos... 3 4. Egevalues ad Egevectors of Matrces.... 3 5. Vector ad Matrx

More information

CHAPTER VI Statistical Analysis of Experimental Data

CHAPTER VI Statistical Analysis of Experimental Data Chapter VI Statstcal Aalyss of Expermetal Data CHAPTER VI Statstcal Aalyss of Expermetal Data Measuremets do ot lead to a uque value. Ths s a result of the multtude of errors (maly radom errors) that ca

More information

Stability For a stable numerical scheme, the errors in the initial condition will not grow unboundedly with time.

Stability For a stable numerical scheme, the errors in the initial condition will not grow unboundedly with time. .3.5. Stablty Aalyss Readg: Taehll et al. Secto 3.6. Stablty For a stable umercal scheme, the errors the tal codto wll ot grow uboudedly wth tme. I ths secto, we dscuss the methods for determg the stablty

More information

A Robust Total Least Mean Square Algorithm For Nonlinear Adaptive Filter

A Robust Total Least Mean Square Algorithm For Nonlinear Adaptive Filter A Robust otal east Mea Square Algorthm For Nolear Adaptve Flter Ruxua We School of Electroc ad Iformato Egeerg X'a Jaotog Uversty X'a 70049, P.R. Cha rxwe@chare.com Chogzhao Ha, azhe u School of Electroc

More information

Introduction to local (nonparametric) density estimation. methods

Introduction to local (nonparametric) density estimation. methods Itroducto to local (oparametrc) desty estmato methods A slecture by Yu Lu for ECE 66 Sprg 014 1. Itroducto Ths slecture troduces two local desty estmato methods whch are Parze desty estmato ad k-earest

More information

Third handout: On the Gini Index

Third handout: On the Gini Index Thrd hadout: O the dex Corrado, a tala statstca, proposed (, 9, 96) to measure absolute equalt va the mea dfferece whch s defed as ( / ) where refers to the total umber of dvduals socet. Assume that. The

More information

Application of Calibration Approach for Regression Coefficient Estimation under Two-stage Sampling Design

Application of Calibration Approach for Regression Coefficient Estimation under Two-stage Sampling Design Authors: Pradp Basak, Kaustav Adtya, Hukum Chadra ad U.C. Sud Applcato of Calbrato Approach for Regresso Coeffcet Estmato uder Two-stage Samplg Desg Pradp Basak, Kaustav Adtya, Hukum Chadra ad U.C. Sud

More information

Fractional Order Finite Difference Scheme For Soil Moisture Diffusion Equation And Its Applications

Fractional Order Finite Difference Scheme For Soil Moisture Diffusion Equation And Its Applications IOS Joural of Mathematcs (IOS-JM e-iss: 78-578. Volume 5, Issue 4 (Ja. - Feb. 3, PP -8 www.osrourals.org Fractoal Order Fte Dfferece Scheme For Sol Mosture Dffuso quato Ad Its Applcatos S.M.Jogdad, K.C.Takale,

More information

EECE 301 Signals & Systems

EECE 301 Signals & Systems EECE 01 Sgals & Systems Prof. Mark Fowler Note Set #9 Computg D-T Covoluto Readg Assgmet: Secto. of Kame ad Heck 1/ Course Flow Dagram The arrows here show coceptual flow betwee deas. Note the parallel

More information

MULTIDIMENSIONAL HETEROGENEOUS VARIABLE PREDICTION BASED ON EXPERTS STATEMENTS. Gennadiy Lbov, Maxim Gerasimov

MULTIDIMENSIONAL HETEROGENEOUS VARIABLE PREDICTION BASED ON EXPERTS STATEMENTS. Gennadiy Lbov, Maxim Gerasimov Iteratoal Boo Seres "Iformato Scece ad Computg" 97 MULTIIMNSIONAL HTROGNOUS VARIABL PRICTION BAS ON PRTS STATMNTS Geady Lbov Maxm Gerasmov Abstract: I the wors [ ] we proposed a approach of formg a cosesus

More information

A Note on Ratio Estimators in two Stage Sampling

A Note on Ratio Estimators in two Stage Sampling Iteratoal Joural of Scetfc ad Research Publcatos, Volume, Issue, December 0 ISS 0- A ote o Rato Estmators two Stage Samplg Stashu Shekhar Mshra Lecturer Statstcs, Trdet Academy of Creatve Techology (TACT),

More information

Transforms that are commonly used are separable

Transforms that are commonly used are separable Trasforms s Trasforms that are commoly used are separable Eamples: Two-dmesoal DFT DCT DST adamard We ca the use -D trasforms computg the D separable trasforms: Take -D trasform of the rows > rows ( )

More information

hp calculators HP 30S Statistics Averages and Standard Deviations Average and Standard Deviation Practice Finding Averages and Standard Deviations

hp calculators HP 30S Statistics Averages and Standard Deviations Average and Standard Deviation Practice Finding Averages and Standard Deviations HP 30S Statstcs Averages ad Stadard Devatos Average ad Stadard Devato Practce Fdg Averages ad Stadard Devatos HP 30S Statstcs Averages ad Stadard Devatos Average ad stadard devato The HP 30S provdes several

More information

A nonsmooth Levenberg-Marquardt method for generalized complementarity problem

A nonsmooth Levenberg-Marquardt method for generalized complementarity problem ISSN 746-7659 Egla UK Joural of Iformato a Computg Scece Vol. 7 No. 4 0 pp. 67-7 A osmooth Leveberg-Marquart metho for geeralze complemetarty problem Shou-qag Du College of Mathematcs Qgao Uversty Qgao

More information

Newton s Power Flow algorithm

Newton s Power Flow algorithm Power Egeerg - Egll Beedt Hresso ewto s Power Flow algorthm Power Egeerg - Egll Beedt Hresso The ewto s Method of Power Flow 2 Calculatos. For the referece bus #, we set : V = p.u. ad δ = 0 For all other

More information

Chapter 9 Jordan Block Matrices

Chapter 9 Jordan Block Matrices Chapter 9 Jorda Block atrces I ths chapter we wll solve the followg problem. Gve a lear operator T fd a bass R of F such that the matrx R (T) s as smple as possble. f course smple s a matter of taste.

More information

Convergence of the Desroziers scheme and its relation to the lag innovation diagnostic

Convergence of the Desroziers scheme and its relation to the lag innovation diagnostic Covergece of the Desrozers scheme ad ts relato to the lag ovato dagostc chard Méard Evromet Caada, Ar Qualty esearch Dvso World Weather Ope Scece Coferece Motreal, August 9, 04 o t t O x x x y x y Oservato

More information

F. Inequalities. HKAL Pure Mathematics. 進佳數學團隊 Dr. Herbert Lam 林康榮博士. [Solution] Example Basic properties

F. Inequalities. HKAL Pure Mathematics. 進佳數學團隊 Dr. Herbert Lam 林康榮博士. [Solution] Example Basic properties 進佳數學團隊 Dr. Herbert Lam 林康榮博士 HKAL Pure Mathematcs F. Ieualtes. Basc propertes Theorem Let a, b, c be real umbers. () If a b ad b c, the a c. () If a b ad c 0, the ac bc, but f a b ad c 0, the ac bc. Theorem

More information

Chapter 4 (Part 1): Non-Parametric Classification (Sections ) Pattern Classification 4.3) Announcements

Chapter 4 (Part 1): Non-Parametric Classification (Sections ) Pattern Classification 4.3) Announcements Aoucemets No-Parametrc Desty Estmato Techques HW assged Most of ths lecture was o the blacboard. These sldes cover the same materal as preseted DHS Bometrcs CSE 90-a Lecture 7 CSE90a Fall 06 CSE90a Fall

More information

6.867 Machine Learning

6.867 Machine Learning 6.867 Mache Learg Problem set Due Frday, September 9, rectato Please address all questos ad commets about ths problem set to 6.867-staff@a.mt.edu. You do ot eed to use MATLAB for ths problem set though

More information

A tighter lower bound on the circuit size of the hardest Boolean functions

A tighter lower bound on the circuit size of the hardest Boolean functions Electroc Colloquum o Computatoal Complexty, Report No. 86 2011) A tghter lower boud o the crcut sze of the hardest Boolea fuctos Masak Yamamoto Abstract I [IPL2005], Fradse ad Mlterse mproved bouds o the

More information

( ) = ( ) ( ) Chapter 13 Asymptotic Theory and Stochastic Regressors. Stochastic regressors model

( ) = ( ) ( ) Chapter 13 Asymptotic Theory and Stochastic Regressors. Stochastic regressors model Chapter 3 Asmptotc Theor ad Stochastc Regressors The ature of eplaator varable s assumed to be o-stochastc or fed repeated samples a regresso aalss Such a assumpto s approprate for those epermets whch

More information

Derivation of 3-Point Block Method Formula for Solving First Order Stiff Ordinary Differential Equations

Derivation of 3-Point Block Method Formula for Solving First Order Stiff Ordinary Differential Equations Dervato of -Pot Block Method Formula for Solvg Frst Order Stff Ordary Dfferetal Equatos Kharul Hamd Kharul Auar, Kharl Iskadar Othma, Zara Bb Ibrahm Abstract Dervato of pot block method formula wth costat

More information

A Collocation Method for Solving Abel s Integral Equations of First and Second Kinds

A Collocation Method for Solving Abel s Integral Equations of First and Second Kinds A Collocato Method for Solvg Abel s Itegral Equatos of Frst ad Secod Kds Abbas Saadatmad a ad Mehd Dehgha b a Departmet of Mathematcs, Uversty of Kasha, Kasha, Ira b Departmet of Appled Mathematcs, Faculty

More information

Kernel-based Methods and Support Vector Machines

Kernel-based Methods and Support Vector Machines Kerel-based Methods ad Support Vector Maches Larr Holder CptS 570 Mache Learg School of Electrcal Egeerg ad Computer Scece Washgto State Uverst Refereces Muller et al. A Itroducto to Kerel-Based Learg

More information

L5 Polynomial / Spline Curves

L5 Polynomial / Spline Curves L5 Polyomal / Sple Curves Cotets Coc sectos Polyomal Curves Hermte Curves Bezer Curves B-Sples No-Uform Ratoal B-Sples (NURBS) Mapulato ad Represetato of Curves Types of Curve Equatos Implct: Descrbe a

More information

NUMERICAL SIMULATIONS OF LOW REYNOLDS NUMBER FLOWS PAST ELASTICALLY MOUNTED CYLINDER

NUMERICAL SIMULATIONS OF LOW REYNOLDS NUMBER FLOWS PAST ELASTICALLY MOUNTED CYLINDER NUMERICAL SIMULATIONS OF LOW REYNOLDS NUMBER FLOWS PAST ELASTICALLY MOUNTED CYLINDER R. A. Goçalves a, P. R. F. Texera b, ad E. Dder c, d a, b Uversdade Federal do Ro Grade Escola de Egehara Campus Carreros

More information

DATE: 21 September, 1999 TO: Jim Russell FROM: Peter Tkacik RE: Analysis of wide ply tube winding as compared to Konva Kore CC: Larry McMillan

DATE: 21 September, 1999 TO: Jim Russell FROM: Peter Tkacik RE: Analysis of wide ply tube winding as compared to Konva Kore CC: Larry McMillan M E M O R A N D U M DATE: 1 September, 1999 TO: Jm Russell FROM: Peter Tkack RE: Aalyss of wde ply tube wdg as compared to Kova Kore CC: Larry McMlla The goal of ths report s to aalyze the spral tube wdg

More information

The internal structure of natural numbers, one method for the definition of large prime numbers, and a factorization test

The internal structure of natural numbers, one method for the definition of large prime numbers, and a factorization test Fal verso The teral structure of atural umbers oe method for the defto of large prme umbers ad a factorzato test Emmaul Maousos APM Isttute for the Advacemet of Physcs ad Mathematcs 3 Poulou str. 53 Athes

More information

A Study of the Reproducibility of Measurements with HUR Leg Extension/Curl Research Line

A Study of the Reproducibility of Measurements with HUR Leg Extension/Curl Research Line HUR Techcal Report 000--9 verso.05 / Frak Borg (borgbros@ett.f) A Study of the Reproducblty of Measuremets wth HUR Leg Eteso/Curl Research Le A mportat property of measuremets s that the results should

More information

A new algorithm for the simulation of the boltzmann equation using the direct simulation monte-carlo method

A new algorithm for the simulation of the boltzmann equation using the direct simulation monte-carlo method Joural of Mechacal Scece ad echology 3 (009) 86~870 Joural of Mechacal Scece ad echology wwwsprgerlkcom/cotet/738-494x DOI 0007/s06-009-0803-8 A ew algorthm for the smulato of the boltzma equato usg the

More information

Uniform asymptotical stability of almost periodic solution of a discrete multispecies Lotka-Volterra competition system

Uniform asymptotical stability of almost periodic solution of a discrete multispecies Lotka-Volterra competition system Iteratoal Joural of Egeerg ad Advaced Research Techology (IJEART) ISSN: 2454-9290, Volume-2, Issue-1, Jauary 2016 Uform asymptotcal stablty of almost perodc soluto of a dscrete multspeces Lotka-Volterra

More information

Multiple Choice Test. Chapter Adequacy of Models for Regression

Multiple Choice Test. Chapter Adequacy of Models for Regression Multple Choce Test Chapter 06.0 Adequac of Models for Regresso. For a lear regresso model to be cosdered adequate, the percetage of scaled resduals that eed to be the rage [-,] s greater tha or equal to

More information

A FINITE DIFFERENCE SCHEME FOR A FLUID DYNAMIC TRAFFIC FLOW MODEL APPENDED WITH TWO-POINT BOUNDARY CONDITION

A FINITE DIFFERENCE SCHEME FOR A FLUID DYNAMIC TRAFFIC FLOW MODEL APPENDED WITH TWO-POINT BOUNDARY CONDITION GANIT J. Bagladesh Math. Soc. (ISSN 66-3694 3 ( 43-5 A FINITE DIFFERENCE SCHEME FOR A FLUID DYNAMIC TRAFFIC FLOW MODEL APPENDED WITH TWO-POINT BOUNDARY CONDITION M. O. Ga, M. M. Hossa ad L. S. Adallah

More information

An Introduction to. Support Vector Machine

An Introduction to. Support Vector Machine A Itroducto to Support Vector Mache Support Vector Mache (SVM) A classfer derved from statstcal learg theory by Vapk, et al. 99 SVM became famous whe, usg mages as put, t gave accuracy comparable to eural-etwork

More information

General Method for Calculating Chemical Equilibrium Composition

General Method for Calculating Chemical Equilibrium Composition AE 6766/Setzma Sprg 004 Geeral Metod for Calculatg Cemcal Equlbrum Composto For gve tal codtos (e.g., for gve reactats, coose te speces to be cluded te products. As a example, for combusto of ydroge wt

More information

Confidence Intervals for Double Exponential Distribution: A Simulation Approach

Confidence Intervals for Double Exponential Distribution: A Simulation Approach World Academy of Scece, Egeerg ad Techology Iteratoal Joural of Physcal ad Mathematcal Sceces Vol:6, No:, 0 Cofdece Itervals for Double Expoetal Dstrbuto: A Smulato Approach M. Alrasheed * Iteratoal Scece

More information

5 Short Proofs of Simplified Stirling s Approximation

5 Short Proofs of Simplified Stirling s Approximation 5 Short Proofs of Smplfed Strlg s Approxmato Ofr Gorodetsky, drtymaths.wordpress.com Jue, 20 0 Itroducto Strlg s approxmato s the followg (somewhat surprsg) approxmato of the factoral,, usg elemetary fuctos:

More information

Multivariate Transformation of Variables and Maximum Likelihood Estimation

Multivariate Transformation of Variables and Maximum Likelihood Estimation Marquette Uversty Multvarate Trasformato of Varables ad Maxmum Lkelhood Estmato Dael B. Rowe, Ph.D. Assocate Professor Departmet of Mathematcs, Statstcs, ad Computer Scece Copyrght 03 by Marquette Uversty

More information

Research on SVM Prediction Model Based on Chaos Theory

Research on SVM Prediction Model Based on Chaos Theory Advaced Scece ad Techology Letters Vol.3 (SoftTech 06, pp.59-63 http://dx.do.org/0.457/astl.06.3.3 Research o SVM Predcto Model Based o Chaos Theory Sog Lagog, Wu Hux, Zhag Zezhog 3, College of Iformato

More information

2.3. Quantitative Properties of Finite Difference Schemes. Reading: Tannehill et al. Sections and

2.3. Quantitative Properties of Finite Difference Schemes. Reading: Tannehill et al. Sections and .3. Quattatve Propertes of Fte Dfferece Schemes.3.1. Cosstecy, Covergece ad Stablty of F.D. schemes Readg: Taehll et al. Sectos 3.3.3 ad 3.3.4. Three mportat propertes of F.D. schemes: Cosstecy A F.D.

More information

The equation is sometimes presented in form Y = a + b x. This is reasonable, but it s not the notation we use.

The equation is sometimes presented in form Y = a + b x. This is reasonable, but it s not the notation we use. INTRODUCTORY NOTE ON LINEAR REGREION We have data of the form (x y ) (x y ) (x y ) These wll most ofte be preseted to us as two colum of a spreadsheet As the topc develops we wll see both upper case ad

More information

A New Family of Transformations for Lifetime Data

A New Family of Transformations for Lifetime Data Proceedgs of the World Cogress o Egeerg 4 Vol I, WCE 4, July - 4, 4, Lodo, U.K. A New Famly of Trasformatos for Lfetme Data Lakhaa Watthaacheewakul Abstract A famly of trasformatos s the oe of several

More information

A Combination of Adaptive and Line Intercept Sampling Applicable in Agricultural and Environmental Studies

A Combination of Adaptive and Line Intercept Sampling Applicable in Agricultural and Environmental Studies ISSN 1684-8403 Joural of Statstcs Volume 15, 008, pp. 44-53 Abstract A Combato of Adaptve ad Le Itercept Samplg Applcable Agrcultural ad Evrometal Studes Azmer Kha 1 A adaptve procedure s descrbed for

More information

Entropy ISSN by MDPI

Entropy ISSN by MDPI Etropy 2003, 5, 233-238 Etropy ISSN 1099-4300 2003 by MDPI www.mdp.org/etropy O the Measure Etropy of Addtve Cellular Automata Hasa Aı Arts ad Sceces Faculty, Departmet of Mathematcs, Harra Uversty; 63100,

More information