Toni Alchofino ( ) Physics Department, Bandung Institute of Technology, Indonesia,

Size: px
Start display at page:

Download "Toni Alchofino ( ) Physics Department, Bandung Institute of Technology, Indonesia,"

Transcription

1 Study of Numercal alyss for Coductve System Usg Fte Dfferece lgortms for Smle Oe Dmesoal Heat-Coducto Problems Wt Costat Termal Dffusvtes To lcofo (53 Pyscs Deartmet, Badug Isttute of Tecology, Idoesa, 8 E-mal: To_lcofo@Studets.tb.ac.d Suervsed by : Dr. Eg. lamta Sgarmbu bstract Heat moves by coducto, covecto, radato ad advecto. Beeat te eart s teral structure, eat trasfer majorly by covecto ad coducto rocess. Wt geotermal reservor, eat trasferred from magma to a ermeable rocs system called bedroc. It s eat eergy te absorbed by water from aqufer system wc located above te bedroc. Tere, ot oly coductve rocess but also covectve occur. Ts eat coductve trasfer s oe of mortat rocess wc establs te geotermal reservor system. Most of roblems volvg eat ad mass trasfer are reducble to te soluto of artal dfferetal equato. To solve te dfferetal equato tat gover real yscal rocess are geerally very comlcated. Terefore a aroxmate codto smlest cases s very useful. To solve te dfferetal equato o a comuter, a roblem must be formulated umercally terms of some sutable artmetc oeratos. Heat-Coducto Problems wt geotermal reservor ca be formulated umercally. I. Itroducto te late 96s, may dfferetal equato are ossble to formulate umercally. umercal tecques allow us to determe a table of aroxmato values of te desred soluto. May metods ca be used to aroxmate some yscal rocess, suc aroaces as te fte-dfferece metod, stragt le metod, large-artcle metod, ad Mote Carlo metod. Heat ad mass trasfer are domat rocess occur wt te geotermal reservor. Some of te rocess ca be aroaced by artal dfferetal roblem wc formulated to umerc soluto. Wt umercally aroacmet, te roblems ca be solved wt el of a comuter. Nowadays, some geotermal modelers ave used reservor flud cotag varous cemcals ad oters ave cluded extra features ad more comlcated. Ts aer s a reelmary study of yscal rocess of geotermal. Te urose of ts aer s to revew umercal soluto to coduct a model smle reresetatve case study of eat-coductve trasfer eomea. Te goverg soluto of eat-coductve eomea s smle roblems ad t wll be used to descrbed te eomea troug a model buld based o te umercal soluto. Metod wc s used to gover te soluto s fte-dfferece wt costat termal dffusvtes. II. Te Defto of Fte-Dfferece Metod ad Classfcato of Geotermal system Fte-dfferece metod s a metod of soluto of dfferetal roblems wc dfferetal oerators are relaced by ter aroxmate values exressed terms of fucto at dvdual dscrete ots. Ts metod s also called te grd metod. (Nogotov 978. Tere are some mortat ts we we use fte-dfferece tecque. fter some dfferetal roblems relaced wt oter form, we sould test te stablty of t, weter ts covergece or ot. We ca aalze te stablty troug stablty aalyss by Fourer trasformato or by maxmum rcle. Tere are two geotermal system (Bowe 989 :. Covectve geotermal system. Coductve geotermal system Covectve geotermal systems are caracterzed by atural crculato of te worg flud, te majorty of te eat beg trasferred by crculatg fluds ad ot by coducto. Te covectve rocess romotes creased temeratures te uer art of te crculato system ad corresodg lowerg of temerature occurs te lower art. Covectve geotermal system ca be subdvded to ydrotermal ad crculato systems.

2 Coductve geotermal systems are cosst of lowtemerature, low-etaly aqufers, georessurzed zoes, ad ot dry roc. III. Smle Heat-Coducto Problems Heat flows from a ot body to a cold body, te rate wc eat s coducted troug a sold s roortoal to te temerature gradet. T T<T Heat er ut of tme eterg te elemet across ts face at s aq(, wereas te eat er ut tme leavg te elemet across ts face at δ s aq(δ. Exadg Q(δ a Taylor seres gves : ( Q Q ( Q(... ( I Taylor seres, te (δ ad tose of ger order are very small ad ca be gored. From eq. te et ga of eat er ut tme s Heat eterg across eat leavg across δ T aq( aq(δ -aδ(δq/δ (5 Pc.. Heat Flows Te rate of eat flow er ut area dow troug te late s roortoal to : T T Δ ( Te rate of eat flow er ut area u troug te late, Q, s roortoal to : Suose eat s geerated ts volume eemet at a rate er ut volume er ut tme. Te total amout of eat geerated er ut tme s te : aδ (6 Combg Eq (5 da (6, gves te total ga eat er ut tme : a a (7 T T Q Δ ( If te materal as desty ad secfc eat C, ad udergoes a temerature crease δt tme δt, te rate at wc eat s gaed s : : Termal Coductvty. Equato ( ca be wrtte to a dfferetal equato : Q (3 I cotext of te eart, s a det beeat te surface. s creases dowwards, a ostve temerature. Cosder te cture below : aq(z zδ aq(zδ Pc. Luas Permuaa a C, Ca (8 Te total ga eat er ut tme s equlable wt te rate at wc eat s gaed. From Eq (7 ad (8 we get : C (9 z Substtute te Eq (3 to Eq (9, gves : C C ( Eq. ( s a smle Heat-Coducto dfferetal equato roblem. I 3 dmeso, te equato becomes :

3 T C T ( For steady-state stuato, we tere s o cage temerature wt tme,eq becomes : We ca wrte Eq. ( as : a f (6 T ( IV. Numercal alyss For Steady State Codto Eq ( s dffuao eat flow equato steady state codto. For oe dmeso, equato ( becomes : (3 s te dstrbuto fucto of te eat sources. s te termal coductvty of materal. (,t, steady state codto, oly deeds o ot t. Terefore, to get te umercal soluto, we ca relaces te dervatves of Eq. (3 wt some dfferece relatos. Ts relacemet s based o te dervatve as te lmt T ( T ( lm If s fxed te above qualty, te aroxmate formula for te frst dervatve exressed terms of fte dfferece may be obtaed : T ( T ( ( T( T( T( T( T ( T ( T ( (5 V.Oe Dmesoal Heat Coducto Problems Wt Costat Termal Dffusvtes. Eq. ( s a smle coducto roblems oe codtoal roblems. C Were a f. s te termal dffusvty, ad Te, we sould formulate te dfferetal equato roblems to a dmesoless temerature, ( T T ΔT. T s fxed temerature, ad T s caracterstc temerature dfferece. If te rage of temerature roblem s ow, te : ( T T ( T T m. max m If te det L s over L, te wt troducto wt ew varables /L ad t t/l, te rego of te roblem may be reduced to terval. Eq. (6 may ow wrte as : a F. Were FL f (7 To solve te Eq. (7, te dfferetal equato (7 must be sulemeted wt boudary ad tal codtos. t eac boudares, te temerature (te frst-d boudary codto, or eat flux (te secod-d codto, or a combato of tese quattes (te trd boudary codto may be gve. I geeral case, te boudary codtos may be wrtte as : α β γ Tus, we α ad β, te boudary codto s of te frst d; α ad β s a secod boudary codto; ad α ad β s a trdd codto roblem. For smlcty, frst-d boudary codtos are assumed at ad : (,ψ( (,t ψ (t (,t ψ (t (8 VI. Fte Dfferece lgortms For Oe Dmesoal Heat Coducto Problems Wt Costat Termal Dffusvtes. Wt fte-dfferece tecque, we ca obta te soluto of eat coducto roblems (7 - (8. To troduce a uform dfferecg grd, te terval s dvded to J equal arts by,

4 ,,,3...,J, wt /J. Te soluto s sougt at te ots for tme stes t σ,,,... Te smlest ad most atural metod for roblems(7-(8 s based o a exlct aroxmato of te orgal dfferetal equato : a σ ψ ( ψ F J ψ (9 Te algortm for umercal soluto s exressed by ξ( ( ξ Wt Wt, aτ ξ,... τf ( ow, successve determato of s ot dffcult. Te comutatoal stablty requres te tme stes to be coformable wt τ ( a Substtuto of te exact soluto to ((9, followed by Taylor-seres exaso of (, t τ, (, t, (, t about te ot (, t redly gves te error exresso for te metod : τ a R (, t O( τ Te error s tus of te order O ( τ. It may easly be demostrated tat oe may select τ suc tat te order of te error s O(. Ideed, because of te form of te dfferetal equato (6, we may wrte F a Substtuto of ts exresso to te error formula gves aτ R (, t a O( τ ( Wc mles tat f τ s cose ad te 6a rgt-ad sde of Eq. (9 F τ F R O( F s relaced by Te olds. Te order of aroxmato s obvously s ot dsturbed uo te substtuto F ( F τ F F F F (3 a Sce stablty codto ( s satsfed wt τ, te ger accuracy sceme s stable. 6a VII. Coclusos ad Dscussos For steady state codto, te eat coducto roblems are oly trasformed to dfferece of dfferetal equato form. Ts umercal soluto s a smlest soluto for eat flow. I ts codto, te eat trasfer oly deeds o te det (, te temerature wll varey for every det ( value. Wt ts oter form sowed Eq.(5, we ca ow create a smulato a comuter to calculate ow te temerature varey for every det ( or eat source temerature. I o steady state codto, we frst smlyfy te Eq. (. Because of te eat flow deeds ot oly te tme but also te det ad te oters, ts roblems s a artal dfferetal equato wc we eed to solve t by some metod. I ts aer, t sows ow te roblem s aroaced by fte dfferetal metod. For costat dffusvtes were te coductvty factor, secfc eat ad te desty of materal are costat. d also we eed to comute we s te soluto form, Eq ( stabl. Ts s called comutatoal stablty. Usg ts aroacmet, we wll get te error value from eq (. Te error value sows ow te smulato aroac te real codto. Tese umercal aalyss oly gves te soluto a very smlfed stuato. I realty, we ow tat te dffusvtes factor are ot costat. It s because eart materals are uqe, tey ave varetes of desty ad coductvty value. Te geometry of te eart s also more comlcated, ad ts ot tat smle. We eed to ow te boudary codto of geometry we used.

5 VIII. Refereces Bowe, Robert Geotermal Resources d edto. Elsever Scece Publsg. Boas, Mary.L.983. Matematcal Metods Te Pyscal Sceces. Jo Wley&Sos. Fowler,C.M.R.99.Te Sold Eart : Itroducto to Global Geoyscs.d ed. Cambrdge Uoversty Press. Fser, Mcael E.988. Itroductory Numercal Metods wt Te NG Software Lbrary. Deartmet Matematcs Uversty of Wester ustrala. Fauz,Umar, Prad S. bdoessoe. Fsa Utu Geolog. ITB O Sullva, M.J., Pruess, K., ad Lma, M.J. (.Geotermal reservor smulato: Te state-of-te-ractce ad emergg treds. Lawrece Bereley Natoal Laboratory reort LBNL-699. Nogotov,E.F.978.lcato of Numercal Heat Trasfer. McGraw-Hll Boo Comay. Mattax, C. Calv.,Robert L. Dalto. 99. Reservor Smulato. Socety of Petroleum. Egeers. Putra,V.Doddy.5. las Metode P/ Utu alsa Cadaga Reservor Paas Bum Domas Ua. Setawa,gus.6. Pegatar Metode Numer. Yogyaarta : Peerbt d. emasy,m.w.,ad Dttma,R.H., Kalor da Termodama,eterjema Log,T.H.,986, Badug :ITB.

FREQUENCY ANALYSIS OF A DOUBLE-WALLED NANOTUBES SYSTEM

FREQUENCY ANALYSIS OF A DOUBLE-WALLED NANOTUBES SYSTEM Joural of Appled Matematcs ad Computatoal Mecacs 04, 3(4), 7-34 FREQUENCY ANALYSIS OF A DOUBLE-WALLED NANOTUBES SYSTEM Ata Cekot, Stasław Kukla Isttute of Matematcs, Czestocowa Uversty of Tecology Częstocowa,

More information

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

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

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

Reliability evaluation of distribution network based on improved non. sequential Monte Carlo method

Reliability evaluation of distribution network based on improved non. sequential Monte Carlo method 3rd Iteratoal Coferece o Mecatrocs, Robotcs ad Automato (ICMRA 205) Relablty evaluato of dstrbuto etwork based o mproved o sequetal Mote Carlo metod Je Zu, a, Cao L, b, Aog Tag, c Scool of Automato, Wua

More information

Asymptotic Formulas Composite Numbers II

Asymptotic Formulas Composite Numbers II Iteratoal Matematcal Forum, Vol. 8, 203, o. 34, 65-662 HIKARI Ltd, www.m-kar.com ttp://d.do.org/0.2988/mf.203.3854 Asymptotc Formulas Composte Numbers II Rafael Jakmczuk Dvsó Matemátca, Uversdad Nacoal

More information

IS 709/809: Computational Methods in IS Research. Simple Markovian Queueing Model

IS 709/809: Computational Methods in IS Research. Simple Markovian Queueing Model IS 79/89: Comutatoal Methods IS Research Smle Marova Queueg Model Nrmalya Roy Deartmet of Iformato Systems Uversty of Marylad Baltmore Couty www.umbc.edu Queueg Theory Software QtsPlus software The software

More information

Dr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur

Dr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur Aalyss of Varace ad Desg of Exermets-I MODULE II LECTURE - GENERAL LINEAR HYPOTHESIS AND ANALYSIS OF VARIANCE Dr Shalabh Deartmet of Mathematcs ad Statstcs Ida Isttute of Techology Kaur Tukey s rocedure

More information

A Numerical Patching Technique for Singularly Perturbed Nonlinear Differential-Difference Equations with a Negative Shift

A Numerical Patching Technique for Singularly Perturbed Nonlinear Differential-Difference Equations with a Negative Shift Aled Matematcs, (: - DOI:.593/j.am..4 A Numercal Patcg Tecque for Sgularl Perturbed Nolear Dfferetal-Dfferece Equatos wt a Negatve Sft R. Nageswar Rao, P. Pramod Cakravart Deartmet of Matematcs, Vsvesvaraa

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

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

Nonlinear Piecewise-Defined Difference Equations with Reciprocal Quadratic Terms

Nonlinear Piecewise-Defined Difference Equations with Reciprocal Quadratic Terms Joural of Matematcs ad Statstcs Orgal Researc Paper Nolear Pecewse-Defed Dfferece Equatos wt Recprocal Quadratc Terms Ramada Sabra ad Saleem Safq Al-Asab Departmet of Matematcs, Faculty of Scece, Jaza

More information

Idea is to sample from a different distribution that picks points in important regions of the sample space. Want ( ) ( ) ( ) E f X = f x g x dx

Idea is to sample from a different distribution that picks points in important regions of the sample space. Want ( ) ( ) ( ) E f X = f x g x dx Importace Samplg Used for a umber of purposes: Varace reducto Allows for dffcult dstrbutos to be sampled from. Sestvty aalyss Reusg samples to reduce computatoal burde. Idea s to sample from a dfferet

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

On the characteristics of partial differential equations

On the characteristics of partial differential equations Sur les caractérstques des équatos au dérvées artelles Bull Soc Math Frace 5 (897) 8- O the characterstcs of artal dfferetal equatos By JULES BEUDON Traslated by D H Delhech I a ote that was reseted to

More information

A stopping criterion for Richardson s extrapolation scheme. under finite digit arithmetic.

A stopping criterion for Richardson s extrapolation scheme. under finite digit arithmetic. A stoppg crtero for cardso s extrapoato sceme uder fte dgt artmetc MAKOO MUOFUSHI ad HIEKO NAGASAKA epartmet of Lbera Arts ad Sceces Poytecc Uversty 4-1-1 Hasmotoda,Sagamara,Kaagawa 229-1196 JAPAN Abstract:

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

Two Fuzzy Probability Measures

Two Fuzzy Probability Measures Two Fuzzy robablty Measures Zdeěk Karíšek Isttute of Mathematcs Faculty of Mechacal Egeerg Bro Uversty of Techology Techcká 2 66 69 Bro Czech Reublc e-mal: karsek@umfmevutbrcz Karel Slavíček System dmstrato

More information

å 1 13 Practice Final Examination Solutions - = CS109 Dec 5, 2018

å 1 13 Practice Final Examination Solutions - = CS109 Dec 5, 2018 Chrs Pech Fal Practce CS09 Dec 5, 08 Practce Fal Examato Solutos. Aswer: 4/5 8/7. There are multle ways to obta ths aswer; here are two: The frst commo method s to sum over all ossbltes for the rak of

More information

2. Independence and Bernoulli Trials

2. Independence and Bernoulli Trials . Ideedece ad Beroull Trals Ideedece: Evets ad B are deedet f B B. - It s easy to show that, B deedet mles, B;, B are all deedet ars. For examle, ad so that B or B B B B B φ,.e., ad B are deedet evets.,

More information

COMPUTERISED ALGEBRA USED TO CALCULATE X n COST AND SOME COSTS FROM CONVERSIONS OF P-BASE SYSTEM WITH REFERENCES OF P-ADIC NUMBERS FROM

COMPUTERISED ALGEBRA USED TO CALCULATE X n COST AND SOME COSTS FROM CONVERSIONS OF P-BASE SYSTEM WITH REFERENCES OF P-ADIC NUMBERS FROM U.P.B. Sc. Bull., Seres A, Vol. 68, No. 3, 6 COMPUTERISED ALGEBRA USED TO CALCULATE X COST AND SOME COSTS FROM CONVERSIONS OF P-BASE SYSTEM WITH REFERENCES OF P-ADIC NUMBERS FROM Z AND Q C.A. MURESAN Autorul

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

Outline. Numerical Heat Transfer. Review All Black Surfaces. Review View Factor, F i j or F ij. Review Gray Diffuse Opaque II

Outline. Numerical Heat Transfer. Review All Black Surfaces. Review View Factor, F i j or F ij. Review Gray Diffuse Opaque II umercao Heat raser ay 9 ad, 7 umercal Heat raser arry Caretto ecacal geerg 75 Heat raser ay 9 ad, 7 Outle Wat s umercal aalyss Cosderatos o coducto, covecto ad radato evew umercal aalyss bascs ervatve

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

Runge-Kutta discontinuous Galerkin finite element method for one-dimensional multimedium compressible flow

Runge-Kutta discontinuous Galerkin finite element method for one-dimensional multimedium compressible flow SSN 746-7659, Eglad, K Joural of formato ad Computg Scece Vol. 3, No. 3, 008, pp. 5-4 Ruge-Kutta dscotuous Galerk fte elemet metod for oe-dmesoal multmedum compressble flow Rogsa Ce + Departmet of Matematcs,

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

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

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

Module 1 : The equation of continuity. Lecture 5: Conservation of Mass for each species. & Fick s Law

Module 1 : The equation of continuity. Lecture 5: Conservation of Mass for each species. & Fick s Law Module : The equato of cotuty Lecture 5: Coservato of Mass for each speces & Fck s Law NPTEL, IIT Kharagpur, Prof. Sakat Chakraborty, Departmet of Chemcal Egeerg 2 Basc Deftos I Mass Trasfer, we usually

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

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

Sample Allocation under a Population Model and Stratified Inclusion Probability Proportionate to Size Sampling

Sample Allocation under a Population Model and Stratified Inclusion Probability Proportionate to Size Sampling Secto o Survey Researc Metods Sample Allocato uder a Populato Model ad Stratfed Icluso Probablty Proportoate to Sze Sampl Su Woo Km, Steve eera, Peter Soleberer 3 Statststcs, Douk Uversty, Seoul, Korea,

More information

2SLS Estimates ECON In this case, begin with the assumption that E[ i

2SLS Estimates ECON In this case, begin with the assumption that E[ i SLS Estmates ECON 3033 Bll Evas Fall 05 Two-Stage Least Squares (SLS Cosder a stadard lear bvarate regresso model y 0 x. I ths case, beg wth the assumto that E[ x] 0 whch meas that OLS estmates of wll

More information

Numerical Differentiation

Numerical Differentiation College o Egeerg ad Computer Scece Mecacal Egeerg Departmet Numercal Aalyss Notes November 4, 7 Istructor: Larry Caretto Numercal Deretato Itroducto Tese otes provde a basc troducto to umercal deretato

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

Random Variables. ECE 313 Probability with Engineering Applications Lecture 8 Professor Ravi K. Iyer University of Illinois

Random Variables. ECE 313 Probability with Engineering Applications Lecture 8 Professor Ravi K. Iyer University of Illinois Radom Varables ECE 313 Probablty wth Egeerg Alcatos Lecture 8 Professor Rav K. Iyer Uversty of Illos Iyer - Lecture 8 ECE 313 Fall 013 Today s Tocs Revew o Radom Varables Cumulatve Dstrbuto Fucto (CDF

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

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

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

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

BASIC PRINCIPLES OF STATISTICS

BASIC PRINCIPLES OF STATISTICS BASIC PRINCIPLES OF STATISTICS PROBABILITY DENSITY DISTRIBUTIONS DISCRETE VARIABLES BINOMIAL DISTRIBUTION ~ B 0 0 umber of successes trals Pr E [ ] Var[ ] ; BINOMIAL DISTRIBUTION B7 0. B30 0.3 B50 0.5

More information

Numerical Differentiation

Numerical Differentiation College o Egeerg ad Computer Scece Mecacal Egeerg Departmet ME 9 Numercal Aalyss Marc 4, 4 Istructor: Larry Caretto Numercal Deretato Itroducto Tese otes provde a basc troducto to umercal deretato usg

More information

This content has been downloaded from IOPscience. Please scroll down to see the full text.

This content has been downloaded from IOPscience. Please scroll down to see the full text. Ths cotet has bee dowloaded from IOPscece. Please scroll dow to see the full text. Dowload detals: IP Address: 48.5.3.83 Ths cotet was dowloaded o 4/09/08 at 04:0 Please ote that terms ad codtos aly. You

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

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

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

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

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

STRONG CONSISTENCY FOR SIMPLE LINEAR EV MODEL WITH v/ -MIXING

STRONG CONSISTENCY FOR SIMPLE LINEAR EV MODEL WITH v/ -MIXING Joural of tatstcs: Advaces Theory ad Alcatos Volume 5, Number, 6, Pages 3- Avalable at htt://scetfcadvaces.co. DOI: htt://d.do.org/.864/jsata_7678 TRONG CONITENCY FOR IMPLE LINEAR EV MODEL WITH v/ -MIXING

More information

Unit 9. The Tangent Bundle

Unit 9. The Tangent Bundle Ut 9. The Taget Budle ========================================================================================== ---------- The taget sace of a submafold of R, detfcato of taget vectors wth dervatos at

More information

Point Estimation: definition of estimators

Point Estimation: definition of estimators Pot Estmato: defto of estmators Pot estmator: ay fucto W (X,..., X ) of a data sample. The exercse of pot estmato s to use partcular fuctos of the data order to estmate certa ukow populato parameters.

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

Lecture 9. Some Useful Discrete Distributions. Some Useful Discrete Distributions. The observations generated by different experiments have

Lecture 9. Some Useful Discrete Distributions. Some Useful Discrete Distributions. The observations generated by different experiments have NM 7 Lecture 9 Some Useful Dscrete Dstrbutos Some Useful Dscrete Dstrbutos The observatos geerated by dfferet eermets have the same geeral tye of behavor. Cosequetly, radom varables assocated wth these

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

Minimizing Total Completion Time in a Flow-shop Scheduling Problems with a Single Server

Minimizing Total Completion Time in a Flow-shop Scheduling Problems with a Single Server Joural of Aled Mathematcs & Boformatcs vol. o.3 0 33-38 SSN: 79-660 (rt) 79-6939 (ole) Sceress Ltd 0 Mmzg Total omleto Tme a Flow-sho Schedulg Problems wth a Sgle Server Sh lg ad heg xue-guag Abstract

More information

Evolution Operators and Boundary Conditions for Propagation and Reflection Methods

Evolution Operators and Boundary Conditions for Propagation and Reflection Methods voluto Operators ad for Propagato ad Reflecto Methods Davd Yevck Departmet of Physcs Uversty of Waterloo Physcs 5/3/9 Collaborators Frak Schmdt ZIB Tlma Frese ZIB Uversty of Waterloo] atem l-refae Nortel

More information

Chapter 5 Properties of a Random Sample

Chapter 5 Properties of a Random Sample Lecture 6 o BST 63: Statstcal Theory I Ku Zhag, /0/008 Revew for the prevous lecture Cocepts: t-dstrbuto, F-dstrbuto Theorems: Dstrbutos of sample mea ad sample varace, relatoshp betwee sample mea ad sample

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

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

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

Probability and Statistics. What is probability? What is statistics?

Probability and Statistics. What is probability? What is statistics? robablt ad Statstcs What s robablt? What s statstcs? robablt ad Statstcs robablt Formall defed usg a set of aoms Seeks to determe the lkelhood that a gve evet or observato or measuremet wll or has haeed

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

Nonparametric Density Estimation Intro

Nonparametric Density Estimation Intro Noarametrc Desty Estmato Itro Parze Wdows No-Parametrc Methods Nether robablty dstrbuto or dscrmat fucto s kow Haes qute ofte All we have s labeled data a lot s kow easer salmo bass salmo salmo Estmate

More information

Lecture 3 Probability review (cont d)

Lecture 3 Probability review (cont d) STATS 00: Itroducto to Statstcal Iferece Autum 06 Lecture 3 Probablty revew (cot d) 3. Jot dstrbutos If radom varables X,..., X k are depedet, the ther dstrbuto may be specfed by specfyg the dvdual dstrbuto

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

Supplementary Material for Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices

Supplementary Material for Limits on Sparse Support Recovery via Linear Sketching with Random Expander Matrices Joata Scarlett ad Volka Cever Supplemetary Materal for Lmts o Sparse Support Recovery va Lear Sketcg wt Radom Expader Matrces (AISTATS 26, Joata Scarlett ad Volka Cever) Note tat all ctatos ere are to

More information

Semi-Riemann Metric on. the Tangent Bundle and its Index

Semi-Riemann Metric on. the Tangent Bundle and its Index t J Cotem Math Sceces ol 5 o 3 33-44 Sem-Rema Metrc o the Taet Budle ad ts dex smet Ayha Pamuale Uversty Educato Faculty Dezl Turey ayha@auedutr Erol asar Mers Uversty Art ad Scece Faculty 33343 Mers Turey

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

A Method for Damping Estimation Based On Least Square Fit

A Method for Damping Estimation Based On Least Square Fit Amerca Joural of Egeerg Research (AJER) 5 Amerca Joural of Egeerg Research (AJER) e-issn: 3-847 p-issn : 3-936 Volume-4, Issue-7, pp-5-9 www.ajer.org Research Paper Ope Access A Method for Dampg Estmato

More information

Chapter 3. Differentiation 3.3 Differentiation Rules

Chapter 3. Differentiation 3.3 Differentiation Rules 3.3 Dfferetato Rules 1 Capter 3. Dfferetato 3.3 Dfferetato Rules Dervatve of a Costat Fucto. If f as te costat value f(x) = c, te f x = [c] = 0. x Proof. From te efto: f (x) f(x + ) f(x) o c c 0 = 0. QED

More information

On the Behavior of Positive Solutions of a Difference. equation system:

On the Behavior of Positive Solutions of a Difference. equation system: Aled Mathematcs -8 htt://d.do.org/.6/am..9a Publshed Ole Setember (htt://www.scr.org/joural/am) O the Behavor of Postve Solutos of a Dfferece Equatos Sstem * Decu Zhag Weqag J # Lg Wag Xaobao L Isttute

More information

Lecture 07: Poles and Zeros

Lecture 07: Poles and Zeros Lecture 07: Poles ad Zeros Defto of poles ad zeros The trasfer fucto provdes a bass for determg mportat system respose characterstcs wthout solvg the complete dfferetal equato. As defed, the trasfer fucto

More information

= lim. (x 1 x 2... x n ) 1 n. = log. x i. = M, n

= lim. (x 1 x 2... x n ) 1 n. = log. x i. = M, n .. Soluto of Problem. M s obvously cotuous o ], [ ad ], [. Observe that M x,..., x ) M x,..., x ) )..) We ext show that M s odecreasg o ], [. Of course.) mles that M s odecreasg o ], [ as well. To show

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

We have already referred to a certain reaction, which takes place at high temperature after rich combustion.

We have already referred to a certain reaction, which takes place at high temperature after rich combustion. ME 41 Day 13 Topcs Chemcal Equlbrum - Theory Chemcal Equlbrum Example #1 Equlbrum Costats Chemcal Equlbrum Example #2 Chemcal Equlbrum of Hot Bured Gas 1. Chemcal Equlbrum We have already referred to a

More information

Application of Generating Functions to the Theory of Success Runs

Application of Generating Functions to the Theory of Success Runs Aled Mathematcal Sceces, Vol. 10, 2016, o. 50, 2491-2495 HIKARI Ltd, www.m-hkar.com htt://dx.do.org/10.12988/ams.2016.66197 Alcato of Geeratg Fuctos to the Theory of Success Rus B.M. Bekker, O.A. Ivaov

More information

AN EULER-MC LAURIN FORMULA FOR INFINITE DIMENSIONAL SPACES

AN EULER-MC LAURIN FORMULA FOR INFINITE DIMENSIONAL SPACES AN EULER-MC LAURIN FORMULA FOR INFINITE DIMENSIONAL SPACES Jose Javer Garca Moreta Graduate Studet of Physcs ( Sold State ) at UPV/EHU Address: P.O 6 890 Portugalete, Vzcaya (Spa) Phoe: (00) 3 685 77 16

More information

2/20/2013. Topics. Power Flow Part 1 Text: Power Transmission. Power Transmission. Power Transmission. Power Transmission

2/20/2013. Topics. Power Flow Part 1 Text: Power Transmission. Power Transmission. Power Transmission. Power Transmission /0/0 Topcs Power Flow Part Text: 0-0. Power Trassso Revsted Power Flow Equatos Power Flow Proble Stateet ECEGR 45 Power Systes Power Trassso Power Trassso Recall that for a short trassso le, the power

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

CHAPTER 4 SCRODINGER S EQUATION

CHAPTER 4 SCRODINGER S EQUATION CHAPTER 4 SCRODIGER S EQUATIO A. Itroducto The old quatum theory have elaed successfully about le sectral hydroge atom. Ths theary also have show hyscal heomea atomc ad subatomc order fulflled rcle ad

More information

A Conventional Approach for the Solution of the Fifth Order Boundary Value Problems Using Sixth Degree Spline Functions

A Conventional Approach for the Solution of the Fifth Order Boundary Value Problems Using Sixth Degree Spline Functions Appled Matheatcs, 1, 4, 8-88 http://d.do.org/1.4/a.1.448 Publshed Ole Aprl 1 (http://www.scrp.org/joural/a) A Covetoal Approach for the Soluto of the Ffth Order Boudary Value Probles Usg Sth Degree Sple

More information

Chapter 3 Sampling For Proportions and Percentages

Chapter 3 Sampling For Proportions and Percentages Chapter 3 Samplg For Proportos ad Percetages I may stuatos, the characterstc uder study o whch the observatos are collected are qualtatve ature For example, the resposes of customers may marketg surveys

More information

X ε ) = 0, or equivalently, lim

X ε ) = 0, or equivalently, lim Revew for the prevous lecture Cocepts: order statstcs Theorems: Dstrbutos of order statstcs Examples: How to get the dstrbuto of order statstcs Chapter 5 Propertes of a Radom Sample Secto 55 Covergece

More information

1D Lagrangian Gas Dynamics. g t

1D Lagrangian Gas Dynamics. g t Te KT Dfferece Sceme for Te KT Dfferece Sceme for D Laraa Gas Damcs t 0 t 0 0 0 t 0 Dfferece Sceme for D Dfferece Sceme for D Laraa Gas Damcs 0 t m 0 / / F F t t 0 / / F F t 0 / F F t Dfferece Sceme for

More information

Analysis of a Repairable (n-1)-out-of-n: G System with Failure and Repair Times Arbitrarily Distributed

Analysis of a Repairable (n-1)-out-of-n: G System with Failure and Repair Times Arbitrarily Distributed Amerca Joural of Mathematcs ad Statstcs. ; (: -8 DOI:.593/j.ajms.. Aalyss of a Reparable (--out-of-: G System wth Falure ad Repar Tmes Arbtrarly Dstrbuted M. Gherda, M. Boushaba, Departmet of Mathematcs,

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

The cross sections for inelastic neutron scattering and radiative capture in the field of a light wave.

The cross sections for inelastic neutron scattering and radiative capture in the field of a light wave. The cross sectos for elastc eutro scatterg ad radatve cature the feld of a lght wave EA Ayrya, AH Gevorgya, IV Dovga 3, KB Ogaesya,4 * *bsk@yerham Jot Isttute for Nuclear Research, LIT, Duba, Moscow Rego

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

Applying the condition for equilibrium to this equilibrium, we get (1) n i i =, r G and 5 i

Applying the condition for equilibrium to this equilibrium, we get (1) n i i =, r G and 5 i CHEMICAL EQUILIBRIA The Thermodyamc Equlbrum Costat Cosder a reversble reacto of the type 1 A 1 + 2 A 2 + W m A m + m+1 A m+1 + Assgg postve values to the stochometrc coeffcets o the rght had sde ad egatve

More information

Exponential B-Spline Solution of Convection-Diffusion Equations

Exponential B-Spline Solution of Convection-Diffusion Equations Appled Matematcs 3 4 933-944 ttp://dxdoorg/436/am3469 Publsed Ole Jue 3 (ttp://wwwscrporg/oural/am) Expoetal B-Sple Soluto of Covecto-Dffuso Equatos Reza Moammad Departmet of Matematcs Uversty of Neysabur

More information

Periodic Table of Elements. EE105 - Spring 2007 Microelectronic Devices and Circuits. The Diamond Structure. Electronic Properties of Silicon

Periodic Table of Elements. EE105 - Spring 2007 Microelectronic Devices and Circuits. The Diamond Structure. Electronic Properties of Silicon EE105 - Srg 007 Mcroelectroc Devces ad Crcuts Perodc Table of Elemets Lecture Semcoductor Bascs Electroc Proertes of Slco Slco s Grou IV (atomc umber 14) Atom electroc structure: 1s s 6 3s 3 Crystal electroc

More information

An Iterative Solution for Second Order Linear Fredholm Integro-Differential Equations

An Iterative Solution for Second Order Linear Fredholm Integro-Differential Equations Malasa Joural of Matematcal Sceces 8): 57-7 4) MLYSIN JOURNL OF MTHEMTICL SCIENCES Joural omeage: tt://esem.um.edu.m/oural Iteratve Soluto for Secod Order Lear Fredolm Itegro-Dfferetal Equatos * Elaaraa

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

D KL (P Q) := p i ln p i q i

D KL (P Q) := p i ln p i q i Cheroff-Bouds 1 The Geeral Boud Let P 1,, m ) ad Q q 1,, q m ) be two dstrbutos o m elemets, e,, q 0, for 1,, m, ad m 1 m 1 q 1 The Kullback-Lebler dvergece or relatve etroy of P ad Q s defed as m D KL

More information

A Remark on the Uniform Convergence of Some Sequences of Functions

A Remark on the Uniform Convergence of Some Sequences of Functions Advaces Pure Mathematcs 05 5 57-533 Publshed Ole July 05 ScRes. http://www.scrp.org/joural/apm http://dx.do.org/0.436/apm.05.59048 A Remark o the Uform Covergece of Some Sequeces of Fuctos Guy Degla Isttut

More information

MATH 247/Winter Notes on the adjoint and on normal operators.

MATH 247/Winter Notes on the adjoint and on normal operators. MATH 47/Wter 00 Notes o the adjot ad o ormal operators I these otes, V s a fte dmesoal er product space over, wth gve er * product uv, T, S, T, are lear operators o V U, W are subspaces of V Whe we say

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

Introducing Sieve of Eratosthenes as a Theorem

Introducing Sieve of Eratosthenes as a Theorem ISSN(Ole 9-8 ISSN (Prt - Iteratoal Joural of Iovatve Research Scece Egeerg ad echolog (A Hgh Imact Factor & UGC Aroved Joural Webste wwwrsetcom Vol Issue 9 Setember Itroducg Seve of Eratosthees as a heorem

More information

ρ < 1 be five real numbers. The

ρ < 1 be five real numbers. The Lecture o BST 63: Statstcal Theory I Ku Zhag, /0/006 Revew for the prevous lecture Deftos: covarace, correlato Examples: How to calculate covarace ad correlato Theorems: propertes of correlato ad covarace

More information

Analysis of ECT Synchronization Performance Based on Different Interpolation Methods

Analysis of ECT Synchronization Performance Based on Different Interpolation Methods Sesors & Trasducers, Vol. 62, Issue, Jauary 24, pp. 25-257 Sesors & Trasducers 24 by IFSA Publsg, S. L. ttp://www.sesorsportal.com Aalyss of ECT Sycrozato Performace Based o Dfferet Iterpolato Metods Yag

More information