Caractérisation dans le plan de matériaux isolants par thermographie infrarouge et méthode convolutive
|
|
- Mariah Gilbert
- 5 years ago
- Views:
Transcription
1 Journée SFT du Jeud 3 Jun 3 Caractérsaton Température / Température Caractérsaton dans le plan de matérau solants par termogrape nfrarouge et métode convolutve B. REMY, A. DEGIOVAI & D. MAIET B.Rémy, A.Degovann and D.Mallet " Measurement of te In-Plane Termal Dffusvty of Materals by Infrared Termograpy " (DOI:.7/s z Internatonal Journal of Termopyscs - Vol.6, n (5, pp EMTA - UMR 7563 (CRS Unversté de orrane ESEM avenue de la Forêt de Haye TSA VADOEUVRE CEDEX Emal : benjamn.remy@unv-lorrane.fr Journée SFT du Jeud 3 Jun 3
2 Te n-plane dffusvty measurement tecnques Soluton n te case of a sem-nfnte medum submtted to a eat step stmulaton : φ e ( t T, Assumptons: - Sem-nfnte medum - One drectonal eat transfer - Insulated T (, t φ at ep erfc λ π 4at 4at 4at a: termal dffusvty λ: termal conductvty Metod : poston and dfferent tmes (Steere, 966 & Harmaty, 964 T T (,t (, t erfc erfc at at Anoter tecnque: at e,5τ t m m m ( τ t ln( τ t m Steere, 967 Square pulse (duraton τ
3 Te n-plane dffusvty measurement tecnques Metod : dfferent postons at a gven tme (Katayama, 969 T πe ep erfc T 4at 4at 4at Drawbacks: - Heat Flu Dstrbuton must be perfectly known - Heatng element s deal (no capacty and n perfect contact wt te sample - Medum s assumed to be perfectly nsulated - D Heat transfer ( pt Metod : aplace transform (Kavanpour & Beck, 977 θ ( p ( T ( t T ( t ep dt θ T ( p a T t θ a p θ ( p ( p a ϕ ep λ p a, ln θ θ (, p (, p ( Te soluton s ndependent of te n-tme eat flu dstrbuton p a
4 Te n-plane dffusvty measurement tecnques Metod : Fn s metod (Hadsaroyo, 99 Unknown eat flu (, t T ( t T, ( e + S e. T S λ T t θ p a S λ ( T T + θ et a e l ln θ (, p (, p θ p S ( + a λ Unknown eat flu T (, t T (, t e Bot dffusvty a and eat losses are taken nto account (sem-nfnte medum s assumed l Interest of te nfrared camera: - on-necessary n space unform stmulaton - D transfer n te case of nsulatng materals
5 O J D D J J A J O Te Fn s metod n Transtory Regme To measure λ, te sample s stmulated n by a non necessary unform and constant eat flu ϕ(y,t or temperature step T (y,t. Te averaged temperature s ten consdered: O 6 6 T (, t T (, t T et 6 Heat Transfer Equaton : ( e + T T T e λ a t Boundares Condtons : n T λ ϕ ( t or T T ( t Tet n T λ ϕ ( t T or ( et T t T e << or y Fn s Appromaton Intal Condton : T at t
6 Teoretcal Model: Soluton n te aplace doman Te soluton s obtaned n te aplace doman (ntegral transform F ( pt ( p ( f ( t f ( t ep Te Quadrupole formulaton allows to lnearly lnks te aplace transforms of te nner and outer temperatures and flues: T Φ ϕ θ ( ( dt θ Φ A C θ Φ θ Φ e [ M ] [ M ] B D θ Φ e θ Φe A B C D sn λk cos ( k ( k λk ( k sn ( k p a Two reference temperature profles are cosen n and sn θ (, p θ( p F (, p + θ ( p F (, p wt: ( ( α( F, p sn( α( and F (, p ( α p a + eλ sn sn ( α( ( α(
7 Teoretcal Model: Soluton n te Tme doman In te tme doman, te soluton can be wrtten as a sum of two convoluton products: - ( t T ( t f (, t + T ( t f ( t wt: f (, t ( F ( p T,,, measured by nfrared camera f and f are functons of te unknown parameters: a and H..5 *//8 *//4 */3/8 *// *//8 *//4 */3/8 *//..5 * * * * f ( f (,t,t t * at/ t * at/
8 Drect Model: Test Case Test Case: square sample 4mm and emm a 5. 7 m s. λ W. m. K W. m. K Temperature step n Temperature * θ (, p In-tme Varatons: θ T θ ( p ( T T p et (, p cos( α( T p cos( α( et Insulated n * * Profle T ( lm p. θ ( p p In-space Varatons: cos cos ( α ( ( α ( T*(T-T et /(T -T et * *. * *.4 *.6 *.8 *. T*(T-T et /(T -T et t*. t*.78 t*.3 t*.6 t*. t * Steady-State Profle t * at/ * /
9 Inverse Model: Parameter Estmaton Ordnary east Squares Metod: T te ( t β T T te te ( t, β, ( t, β, Tte k, M M (, t, β S n t ( Tte ( t Tep ( t ( n + profles and:, β β T ep ( t T T T ep ep ep ( t, M ( k, t ( M, t a H wt: Unknown parameters k β j k n (, K k,n S β j ( t, β nt Tte te β β j ( T ( t, T ( t ( j ep X j β j T te β ( t β, j Senstvty Coeffcent Ideal case on-deal case T ep ( t T ( t, β + ε ( t te E( ε and ( ε V σ b β ˆ β + t t ( X X X ε( t ( t, β T (, t, β + ε ( t f (, t + ( t f ( t T, ep k, te k k ε ε ε k V E( ˆ β β t ( β σ ( X X ˆ b σ b Var Cov ( a Cov( a, H ( a, H Var( H σ σ Var( a σ σ Var( H a b. H b.
10 Optmal coce of te reference profles statc profles: movng profles: T * (T-T /(T -T et et X. a X H t * at/ T * (T-T /(T -T et et Var ( a Var ( H Cov ( a, H ρ ( a, H X a X H t * at/ 3 Drect Model General Model k k k k + atural & Optmal Coce: and
11 Effect of a non-unform eat transfer coeffcent T*(T-T /(T -T et et Sold : Dased : (.3/4*(/ / t * at/ In-space varyng eat transfer coeffcent wt: ( ( d (FEM Software - FlePDE
12 Effect of a non-unform eat transfer coeffcent a 4.98e-7 H 4 a 4.98e-7 H 5456 T * (T-T /(T -T et et ,96W. m. K T * (T-T /(T -T et et ,4w. m. K C Ste ( t * at/ t * at/ omnal values: 7 a 5. m. s and H 5 λ W. m. K W. m. K
13 Epermental Results Termograms (lne source stmulaton: Temperature profles and termograms: Estmaton: profle over
14 Conclusons An n-plane dffusvty estmaton metod by convoluton metod for low conductve materals as been presented. It s a very smple and sem-analytcal metod tat allows us usng two reference measured temperatures as boundary condtons To measure te n-plane dffusvty of low conductve materals Watever te In-Space and In-Tme stmulaton eat flu, And eat transfer coeffcent varatons are. Tank you for your attenton
Thermal-Fluids I. Chapter 18 Transient heat conduction. Dr. Primal Fernando Ph: (850)
hermal-fluds I Chapter 18 ransent heat conducton Dr. Prmal Fernando prmal@eng.fsu.edu Ph: (850) 410-6323 1 ransent heat conducton In general, he temperature of a body vares wth tme as well as poston. In
More informationUNIVERSITY OF BOLTON RAK ACADEMIC CENTRE BENG(HONS) MECHANICAL ENGINEERING SEMESTER TWO EXAMINATION 2017/2018 FINITE ELEMENT AND DIFFERENCE SOLUTIONS
OCD0 UNIVERSITY OF BOLTON RAK ACADEMIC CENTRE BENG(HONS) MECHANICAL ENGINEERING SEMESTER TWO EXAMINATION 07/08 FINITE ELEMENT AND DIFFERENCE SOLUTIONS MODULE NO. AME6006 Date: Wednesda 0 Ma 08 Tme: 0:00
More informationCHAPTER X PHASE-CHANGE PROBLEMS
Chapter X Phae-Change Problem December 3, 18 917 CHAPER X PHASE-CHANGE PROBLEMS X.1 Introducton Clacal Stefan Problem Geometry of Phae Change Problem Interface Condton X. Analytcal Soluton for Soldfcaton
More informationSolution for singularly perturbed problems via cubic spline in tension
ISSN 76-769 England UK Journal of Informaton and Computng Scence Vol. No. 06 pp.6-69 Soluton for sngularly perturbed problems va cubc splne n tenson K. Aruna A. S. V. Rav Kant Flud Dynamcs Dvson Scool
More information2 Finite difference basics
Numersche Methoden 1, WS 11/12 B.J.P. Kaus 2 Fnte dfference bascs Consder the one- The bascs of the fnte dfference method are best understood wth an example. dmensonal transent heat conducton equaton T
More informationDETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM
Ganj, Z. Z., et al.: Determnaton of Temperature Dstrbuton for S111 DETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM by Davood Domr GANJI
More informationInterconnect Modeling
Interconnect Modelng Modelng of Interconnects Interconnect R, C and computaton Interconnect models umped RC model Dstrbuted crcut models Hgher-order waveform n dstrbuted RC trees Accuracy and fdelty Prepared
More informationONE DIMENSIONAL TRIANGULAR FIN EXPERIMENT. Technical Advisor: Dr. D.C. Look, Jr. Version: 11/03/00
ONE IMENSIONAL TRIANGULAR FIN EXPERIMENT Techncal Advsor: r..c. Look, Jr. Verson: /3/ 7. GENERAL OJECTIVES a) To understand a one-dmensonal epermental appromaton. b) To understand the art of epermental
More informationThe Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction
ECONOMICS 5* -- NOTE (Summary) ECON 5* -- NOTE The Multple Classcal Lnear Regresson Model (CLRM): Specfcaton and Assumptons. Introducton CLRM stands for the Classcal Lnear Regresson Model. The CLRM s also
More informationThe Finite Element Method: A Short Introduction
Te Fnte Element Metod: A Sort ntroducton Wat s FEM? Te Fnte Element Metod (FEM) ntroduced by engneers n late 50 s and 60 s s a numercal tecnque for solvng problems wc are descrbed by Ordnary Dfferental
More informationElectrostatic Potential from Transmembrane Currents
Electrostatc Potental from Transmembrane Currents Let s assume that the current densty j(r, t) s ohmc;.e., lnearly proportonal to the electrc feld E(r, t): j = σ c (r)e (1) wth conductvty σ c = σ c (r).
More informationFormal solvers of the RT equation
Formal solvers of the RT equaton Formal RT solvers Runge- Kutta (reference solver) Pskunov N.: 979, Master Thess Long characterstcs (Feautrer scheme) Cannon C.J.: 970, ApJ 6, 55 Short characterstcs (Hermtan
More informationn α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0
MODULE 2 Topcs: Lnear ndependence, bass and dmenson We have seen that f n a set of vectors one vector s a lnear combnaton of the remanng vectors n the set then the span of the set s unchanged f that vector
More informationNumerical Transient Heat Conduction Experiment
Numercal ransent Heat Conducton Experment OBJECIVE 1. o demonstrate the basc prncples of conducton heat transfer.. o show how the thermal conductvty of a sold can be measured. 3. o demonstrate the use
More informationMultivariate Ratio Estimator of the Population Total under Stratified Random Sampling
Open Journal of Statstcs, 0,, 300-304 ttp://dx.do.org/0.436/ojs.0.3036 Publsed Onlne July 0 (ttp://www.scrp.org/journal/ojs) Multvarate Rato Estmator of te Populaton Total under Stratfed Random Samplng
More informationAsymptotics of the Solution of a Boundary Value. Problem for One-Characteristic Differential. Equation Degenerating into a Parabolic Equation
Nonl. Analyss and Dfferental Equatons, ol., 4, no., 5 - HIKARI Ltd, www.m-har.com http://dx.do.org/.988/nade.4.456 Asymptotcs of the Soluton of a Boundary alue Problem for One-Characterstc Dfferental Equaton
More informationImplementation of the Matrix Method
Computatonal Photoncs, Prof. Thomas Pertsch, Abbe School of Photoncs, FSU Jena Computatonal Photoncs Semnar 0 Implementaton of the Matr Method calculaton of the transfer matr calculaton of reflecton and
More informationA new Approach for Solving Linear Ordinary Differential Equations
, ISSN 974-57X (Onlne), ISSN 974-5718 (Prnt), Vol. ; Issue No. 1; Year 14, Copyrght 13-14 by CESER PUBLICATIONS A new Approach for Solvng Lnear Ordnary Dfferental Equatons Fawz Abdelwahd Department of
More informationAmplification and Relaxation of Electron Spin Polarization in Semiconductor Devices
Amplfcaton and Relaxaton of Electron Spn Polarzaton n Semconductor Devces Yury V. Pershn and Vladmr Prvman Center for Quantum Devce Technology, Clarkson Unversty, Potsdam, New York 13699-570, USA Spn Relaxaton
More informationThermal tomography on the basis of an information method
ttp://d.do.org/0.6/qrt.004.08 Termal tomograp on te bass of an nformaton metod *Karkov Natonal Unverst of Rado- Electroncs, Karkov, Ukrane Abstract B S. Melnk* A unfed (nformaton approac to te development
More informationThe Tangential Force Distribution on Inner Cylinder of Power Law Fluid Flowing in Eccentric Annuli with the Inner Cylinder Reciprocating Axially
Open Journal of Flud Dynamcs, 2015, 5, 183-187 Publshed Onlne June 2015 n ScRes. http://www.scrp.org/journal/ojfd http://dx.do.org/10.4236/ojfd.2015.52020 The Tangental Force Dstrbuton on Inner Cylnder
More informationStanford University CS254: Computational Complexity Notes 7 Luca Trevisan January 29, Notes for Lecture 7
Stanford Unversty CS54: Computatonal Complexty Notes 7 Luca Trevsan January 9, 014 Notes for Lecture 7 1 Approxmate Countng wt an N oracle We complete te proof of te followng result: Teorem 1 For every
More information2010 Black Engineering Building, Department of Mechanical Engineering. Iowa State University, Ames, IA, 50011
Interface Energy Couplng between -tungsten Nanoflm and Few-layered Graphene Meng Han a, Pengyu Yuan a, Jng Lu a, Shuyao S b, Xaolong Zhao b, Yanan Yue c, Xnwe Wang a,*, Xangheng Xao b,* a 2010 Black Engneerng
More informationThe Analysis of Convection Experiment
Internatonal Conference on Appled Scence and Engneerng Innovaton (ASEI 5) The Analyss of Convecton Experment Zlong Zhang School of North Chna Electrc Power Unversty, Baodng 7, Chna 469567@qq.com Keywords:
More informationAERODYNAMICS I LECTURE 6 AERODYNAMICS OF A WING FUNDAMENTALS OF THE LIFTING-LINE THEORY
LECTURE 6 AERODYNAMICS OF A WING FUNDAMENTALS OF THE LIFTING-LINE THEORY The Bot-Savart Law The velocty nduced by the sngular vortex lne wth the crculaton can be determned by means of the Bot- Savart formula
More informationrisk and uncertainty assessment
Optmal forecastng of atmospherc qualty n ndustral regons: rsk and uncertanty assessment Vladmr Penenko Insttute of Computatonal Mathematcs and Mathematcal Geophyscs SD RAS Goal Development of theoretcal
More informationA Spline based computational simulations for solving selfadjoint singularly perturbed two-point boundary value problems
ISSN 746-769 England UK Journal of Informaton and Computng Scence Vol. 7 No. 4 pp. 33-34 A Splne based computatonal smulatons for solvng selfadjont sngularly perturbed two-pont boundary value problems
More informationModel and program for the prediction of the indoor air temperature and the indoor air relative humidity
Insttute of Buldng Clmatology, Faculty of Archtecture, Dresden Unversty of Technology, Germany Model and program for the predcton of the ndoor ar temperature and the ndoor ar relatve humdty Dr.-Ing. A.
More informationECE 107: Electromagnetism
ECE 107: Electromagnetsm Set 8: Plane waves Instructor: Prof. Vtaly Lomakn Department of Electrcal and Computer Engneerng Unversty of Calforna, San Dego, CA 92093 1 Wave equaton Source-free lossless Maxwell
More informationDiffusion Mass Transfer
Dffuson Mass Transfer General onsderatons Mass transfer refers to mass n transt due to a speces concentraton gradent n a mture. Must have a mture of two or more speces for mass transfer to occur. The speces
More information8.022 (E&M) Lecture 4
Topcs: 8.0 (E&M) Lecture 4 More applcatons of vector calculus to electrostatcs: Laplacan: Posson and Laplace equaton url: concept and applcatons to electrostatcs Introducton to conductors Last tme Electrc
More informationPubH 7405: REGRESSION ANALYSIS. SLR: INFERENCES, Part II
PubH 7405: REGRESSION ANALSIS SLR: INFERENCES, Part II We cover te topc of nference n two sessons; te frst sesson focused on nferences concernng te slope and te ntercept; ts s a contnuaton on estmatng
More informationTransfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system
Transfer Functons Convenent representaton of a lnear, dynamc model. A transfer functon (TF) relates one nput and one output: x t X s y t system Y s The followng termnology s used: x y nput output forcng
More informationNumerical Simulation of One-Dimensional Wave Equation by Non-Polynomial Quintic Spline
IOSR Journal of Matematcs (IOSR-JM) e-issn: 78-578, p-issn: 319-765X. Volume 14, Issue 6 Ver. I (Nov - Dec 018), PP 6-30 www.osrournals.org Numercal Smulaton of One-Dmensonal Wave Equaton by Non-Polynomal
More informationSupplemental Material: Causal Entropic Forces
Supplemental Materal: Causal Entropc Forces A. D. Wssner-Gross 1, 2, and C. E. Freer 3 1 Insttute for Appled Computatonal Scence, Harvard Unversty, Cambrdge, Massachusetts 02138, USA 2 The Meda Laboratory,
More informationIntroduction to Antennas & Arrays
Introducton to Antennas & Arrays Antenna transton regon (structure) between guded eaves (.e. coaxal cable) and free space waves. On transmsson, antenna accepts energy from TL and radates t nto space. J.D.
More informationAnalysis of Discrete Time Queues (Section 4.6)
Analyss of Dscrete Tme Queues (Secton 4.6) Copyrght 2002, Sanjay K. Bose Tme axs dvded nto slots slot slot boundares Arrvals can only occur at slot boundares Servce to a job can only start at a slot boundary
More informationImplementation of the Matrix Method
Computatonal Photoncs, Prof. Thomas Pertsch, Abbe School of Photoncs, FSU Jena Computatonal Photoncs Semnar 0 Implementaton of the Matr Method calculaton of the transfer matr calculaton of reflecton and
More informationModelli Clamfim Equazioni differenziali 7 ottobre 2013
CLAMFIM Bologna Modell 1 @ Clamfm Equazon dfferenzal 7 ottobre 2013 professor Danele Rtell danele.rtell@unbo.t 1/18? Ordnary Dfferental Equatons A dfferental equaton s an equaton that defnes a relatonshp
More informationBinomial Distribution: Tossing a coin m times. p = probability of having head from a trial. y = # of having heads from n trials (y = 0, 1,..., m).
[7] Count Data Models () Some Dscrete Probablty Densty Functons Bnomal Dstrbuton: ossng a con m tmes p probablty of havng head from a tral y # of havng heads from n trals (y 0,,, m) m m! fb( y n) p ( p)
More informationStatistics for Business and Economics
Statstcs for Busness and Economcs Chapter 11 Smple Regresson Copyrght 010 Pearson Educaton, Inc. Publshng as Prentce Hall Ch. 11-1 11.1 Overvew of Lnear Models n An equaton can be ft to show the best lnear
More informationMaximum Likelihood Estimation of Binary Dependent Variables Models: Probit and Logit. 1. General Formulation of Binary Dependent Variables Models
ECO 452 -- OE 4: Probt and Logt Models ECO 452 -- OE 4 Mamum Lkelhood Estmaton of Bnary Dependent Varables Models: Probt and Logt hs note demonstrates how to formulate bnary dependent varables models for
More informationDigital Signal Processing
Dgtal Sgnal Processng Dscrete-tme System Analyss Manar Mohasen Offce: F8 Emal: manar.subh@ut.ac.r School of IT Engneerng Revew of Precedent Class Contnuous Sgnal The value of the sgnal s avalable over
More information16 Reflection and transmission, TE mode
16 Reflecton transmsson TE mode Last lecture we learned how to represent plane-tem waves propagatng n a drecton ˆ n terms of feld phasors such that η = Ẽ = E o e j r H = ˆ Ẽ η µ ɛ = ˆ = ω µɛ E o =0. Such
More information6.3.4 Modified Euler s method of integration
6.3.4 Modfed Euler s method of ntegraton Before dscussng the applcaton of Euler s method for solvng the swng equatons, let us frst revew the basc Euler s method of numercal ntegraton. Let the general from
More informationParametric fractional imputation for missing data analysis. Jae Kwang Kim Survey Working Group Seminar March 29, 2010
Parametrc fractonal mputaton for mssng data analyss Jae Kwang Km Survey Workng Group Semnar March 29, 2010 1 Outlne Introducton Proposed method Fractonal mputaton Approxmaton Varance estmaton Multple mputaton
More informationHomogenization of reaction-diffusion processes in a two-component porous medium with a non-linear flux-condition on the interface
Homogenzaton of reacton-dffuson processes n a two-component porous medum wth a non-lnear flux-condton on the nterface Internatonal Conference on Numercal and Mathematcal Modelng of Flow and Transport n
More informationStatistics for Managers Using Microsoft Excel/SPSS Chapter 13 The Simple Linear Regression Model and Correlation
Statstcs for Managers Usng Mcrosoft Excel/SPSS Chapter 13 The Smple Lnear Regresson Model and Correlaton 1999 Prentce-Hall, Inc. Chap. 13-1 Chapter Topcs Types of Regresson Models Determnng the Smple Lnear
More informationwhere I = (n x n) diagonal identity matrix with diagonal elements = 1 and off-diagonal elements = 0; and σ 2 e = variance of (Y X).
11.4.1 Estmaton of Multple Regresson Coeffcents In multple lnear regresson, we essentally solve n equatons for the p unnown parameters. hus n must e equal to or greater than p and n practce n should e
More informationA New Recursive Method for Solving State Equations Using Taylor Series
I J E E E C Internatonal Journal of Electrcal, Electroncs ISSN No. (Onlne) : 77-66 and Computer Engneerng 1(): -7(01) Specal Edton for Best Papers of Mcael Faraday IET Inda Summt-01, MFIIS-1 A New Recursve
More informationb ), which stands for uniform distribution on the interval a x< b. = 0 elsewhere
Fall Analyss of Epermental Measurements B. Esensten/rev. S. Errede Some mportant probablty dstrbutons: Unform Bnomal Posson Gaussan/ormal The Unform dstrbuton s often called U( a, b ), hch stands for unform
More informationThe Feynman path integral
The Feynman path ntegral Aprl 3, 205 Hesenberg and Schrödnger pctures The Schrödnger wave functon places the tme dependence of a physcal system n the state, ψ, t, where the state s a vector n Hlbert space
More informationπ e ax2 dx = x 2 e ax2 dx or x 3 e ax2 dx = 1 x 4 e ax2 dx = 3 π 8a 5/2 (a) We are considering the Maxwell velocity distribution function: 2πτ/m
Homework Solutons Problem In solvng ths problem, we wll need to calculate some moments of the Gaussan dstrbuton. The brute-force method s to ntegrate by parts but there s a nce trck. The followng ntegrals
More informationElectrical double layer: revisit based on boundary conditions
Electrcal double layer: revst based on boundary condtons Jong U. Km Department of Electrcal and Computer Engneerng, Texas A&M Unversty College Staton, TX 77843-318, USA Abstract The electrcal double layer
More informationDigital Modems. Lecture 2
Dgtal Modems Lecture Revew We have shown that both Bayes and eyman/pearson crtera are based on the Lkelhood Rato Test (LRT) Λ ( r ) < > η Λ r s called observaton transformaton or suffcent statstc The crtera
More informationProbability Theory. The nth coefficient of the Taylor series of f(k), expanded around k = 0, gives the nth moment of x as ( ik) n n!
8333: Statstcal Mechancs I Problem Set # 3 Solutons Fall 3 Characterstc Functons: Probablty Theory The characterstc functon s defned by fk ep k = ep kpd The nth coeffcent of the Taylor seres of fk epanded
More informationPhysics 181. Particle Systems
Physcs 181 Partcle Systems Overvew In these notes we dscuss the varables approprate to the descrpton of systems of partcles, ther defntons, ther relatons, and ther conservatons laws. We consder a system
More informationChapter 2 - The Simple Linear Regression Model S =0. e i is a random error. S β2 β. This is a minimization problem. Solution is a calculus exercise.
Chapter - The Smple Lnear Regresson Model The lnear regresson equaton s: where y + = β + β e for =,..., y and are observable varables e s a random error How can an estmaton rule be constructed for the
More informationQuasi-Static transient Thermal Stresses in a Robin's thin Rectangular plate with internal moving heat source
31-7871 Weely Scence Research Journal Orgnal Artcle Vol-1, Issue-44, May 014 Quas-Statc transent Theral Stresses n a Robn's n Rectangular late w nternal ovng heat source D. T. Solane and M.. Durge ABSTRACT
More informationScientific Research of the Institute of Mathematics and Computer Science 1(11) 2012, 23-30
Please te ts artle as: Grażyna Kałuża, Te numeral soluton of te transent eat onduton roblem usng te latte Boltzmann metod, Sentf Resear of te Insttute of Matemats and Comuter Sene,, Volume, Issue, ages
More informationImplicit Integration Henyey Method
Implct Integraton Henyey Method In realstc stellar evoluton codes nstead of a drect ntegraton usng for example the Runge-Kutta method one employs an teratve mplct technque. Ths s because the structure
More informationDr. Shalabh Department of Mathematics and Statistics Indian Institute of Technology Kanpur
Analyss of Varance and Desgn of Exerments-I MODULE III LECTURE - 2 EXPERIMENTAL DESIGN MODELS Dr. Shalabh Deartment of Mathematcs and Statstcs Indan Insttute of Technology Kanur 2 We consder the models
More informationmodeling of equilibrium and dynamic multi-component adsorption in a two-layered fixed bed for purification of hydrogen from methane reforming products
modelng of equlbrum and dynamc mult-component adsorpton n a two-layered fxed bed for purfcaton of hydrogen from methane reformng products Mohammad A. Ebrahm, Mahmood R. G. Arsalan, Shohreh Fatem * Laboratory
More informationSimulation of 2D Elastic Bodies with Randomly Distributed Circular Inclusions Using the BEM
Smulaton of 2D Elastc Bodes wth Randomly Dstrbuted Crcular Inclusons Usng the BEM Zhenhan Yao, Fanzhong Kong 2, Xaopng Zheng Department of Engneerng Mechancs 2 State Key Lab of Automotve Safety and Energy
More informationMean Field / Variational Approximations
Mean Feld / Varatonal Appromatons resented by Jose Nuñez 0/24/05 Outlne Introducton Mean Feld Appromaton Structured Mean Feld Weghted Mean Feld Varatonal Methods Introducton roblem: We have dstrbuton but
More informationAdaptive Kernel Estimation of the Conditional Quantiles
Internatonal Journal of Statstcs and Probablty; Vol. 5, No. ; 206 ISSN 927-7032 E-ISSN 927-7040 Publsed by Canadan Center of Scence and Educaton Adaptve Kernel Estmaton of te Condtonal Quantles Rad B.
More information(Online First)A Lattice Boltzmann Scheme for Diffusion Equation in Spherical Coordinate
Internatonal Journal of Mathematcs and Systems Scence (018) Volume 1 do:10.494/jmss.v1.815 (Onlne Frst)A Lattce Boltzmann Scheme for Dffuson Equaton n Sphercal Coordnate Debabrata Datta 1 *, T K Pal 1
More informationMaximum Likelihood Estimation of Binary Dependent Variables Models: Probit and Logit. 1. General Formulation of Binary Dependent Variables Models
ECO 452 -- OE 4: Probt and Logt Models ECO 452 -- OE 4 Maxmum Lkelhood Estmaton of Bnary Dependent Varables Models: Probt and Logt hs note demonstrates how to formulate bnary dependent varables models
More informationA comprehensive study: Boundary conditions for representative volume elements (RVE) of composites
Insttute of Structural Mechancs A comprehensve study: Boundary condtons for representatve volume elements (RVE) of compostes Srhar Kurukur A techncal report on homogenzaton technques A comprehensve study:
More information, rst we solve te PDE's L ad L ad n g g (x) = ; = ; ; ; n () (x) = () Ten, we nd te uncton (x), te lnearzng eedbac and coordnates transormaton are gve
Freedom n Coordnates Transormaton or Exact Lnearzaton and ts Applcaton to Transent Beavor Improvement Kenj Fujmoto and Tosaru Suge Dvson o Appled Systems Scence, Kyoto Unversty, Uj, Kyoto, Japan suge@robotuassyoto-uacjp
More informationWeek3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity
Week3, Chapter 4 Moton n Two Dmensons Lecture Quz A partcle confned to moton along the x axs moves wth constant acceleraton from x =.0 m to x = 8.0 m durng a 1-s tme nterval. The velocty of the partcle
More informationIn this section is given an overview of the common elasticity models.
Secton 4.1 4.1 Elastc Solds In ths secton s gven an overvew of the common elastcty models. 4.1.1 The Lnear Elastc Sold The classcal Lnear Elastc model, or Hooean model, has the followng lnear relatonshp
More informationTHE ROYAL STATISTICAL SOCIETY 2006 EXAMINATIONS SOLUTIONS HIGHER CERTIFICATE
THE ROYAL STATISTICAL SOCIETY 6 EXAMINATIONS SOLUTIONS HIGHER CERTIFICATE PAPER I STATISTICAL THEORY The Socety provdes these solutons to assst canddates preparng for the eamnatons n future years and for
More informationChapter 3. r r. Position, Velocity, and Acceleration Revisited
Chapter 3 Poston, Velocty, and Acceleraton Revsted The poston vector of a partcle s a vector drawn from the orgn to the locaton of the partcle. In two dmensons: r = x ˆ+ yj ˆ (1) The dsplacement vector
More information4.2 Chemical Driving Force
4.2. CHEMICL DRIVING FORCE 103 4.2 Chemcal Drvng Force second effect of a chemcal concentraton gradent on dffuson s to change the nature of the drvng force. Ths s because dffuson changes the bondng n a
More informationLab session: numerical simulations of sponateous polarization
Lab sesson: numercal smulatons of sponateous polarzaton Emerc Boun & Vncent Calvez CNRS, ENS Lyon, France CIMPA, Hammamet, March 2012 Spontaneous cell polarzaton: the 1D case The Hawkns-Voturez model for
More informationPHYS 705: Classical Mechanics. Calculus of Variations II
1 PHYS 705: Classcal Mechancs Calculus of Varatons II 2 Calculus of Varatons: Generalzaton (no constrant yet) Suppose now that F depends on several dependent varables : We need to fnd such that has a statonary
More informationSolving Fractional Nonlinear Fredholm Integro-differential Equations via Hybrid of Rationalized Haar Functions
ISSN 746-7659 England UK Journal of Informaton and Computng Scence Vol. 9 No. 3 4 pp. 69-8 Solvng Fractonal Nonlnear Fredholm Integro-dfferental Equatons va Hybrd of Ratonalzed Haar Functons Yadollah Ordokhan
More informationT E C O L O T E R E S E A R C H, I N C.
T E C O L O T E R E S E A R C H, I N C. B rdg n g En g neern g a nd Econo mcs S nce 1973 THE MINIMUM-UNBIASED-PERCENTAGE ERROR (MUPE) METHOD IN CER DEVELOPMENT Thrd Jont Annual ISPA/SCEA Internatonal Conference
More informationVARIATION OF CONSTANT SUM CONSTRAINT FOR INTEGER MODEL WITH NON UNIFORM VARIABLES
VARIATION OF CONSTANT SUM CONSTRAINT FOR INTEGER MODEL WITH NON UNIFORM VARIABLES BÂRZĂ, Slvu Faculty of Mathematcs-Informatcs Spru Haret Unversty barza_slvu@yahoo.com Abstract Ths paper wants to contnue
More informationLINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity
LINEAR REGRESSION ANALYSIS MODULE IX Lecture - 31 Multcollnearty Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur 6. Rdge regresson The OLSE s the best lnear unbased
More information11. Dynamics in Rotating Frames of Reference
Unversty of Rhode Island DgtalCommons@URI Classcal Dynamcs Physcs Course Materals 2015 11. Dynamcs n Rotatng Frames of Reference Gerhard Müller Unversty of Rhode Island, gmuller@ur.edu Creatve Commons
More informationECONOMICS 351*-A Mid-Term Exam -- Fall Term 2000 Page 1 of 13 pages. QUEEN'S UNIVERSITY AT KINGSTON Department of Economics
ECOOMICS 35*-A Md-Term Exam -- Fall Term 000 Page of 3 pages QUEE'S UIVERSITY AT KIGSTO Department of Economcs ECOOMICS 35* - Secton A Introductory Econometrcs Fall Term 000 MID-TERM EAM ASWERS MG Abbott
More informationTowards the modeling of microgalvanic coupling in aluminum alloys : the choice of boundary conditions
Presented at the COMSOL Conference 2008 Boston COMSOL Conference BOSTON November 9-11 2008 Towards the modelng of mcrogalvanc couplng n alumnum alloys : the choce of boundary condtons Ncolas Murer *1,
More informationThe Finite Element Method
The Fnte Element Method GENERAL INTRODUCTION Read: Chapters 1 and 2 CONTENTS Engneerng and analyss Smulaton of a physcal process Examples mathematcal model development Approxmate solutons and methods of
More informationELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM
ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM An elastc wave s a deformaton of the body that travels throughout the body n all drectons. We can examne the deformaton over a perod of tme by fxng our look
More informationGlobal Sensitivity. Tuesday 20 th February, 2018
Global Senstvty Tuesday 2 th February, 28 ) Local Senstvty Most senstvty analyses [] are based on local estmates of senstvty, typcally by expandng the response n a Taylor seres about some specfc values
More information3. Be able to derive the chemical equilibrium constants from statistical mechanics.
Lecture #17 1 Lecture 17 Objectves: 1. Notaton of chemcal reactons 2. General equlbrum 3. Be able to derve the chemcal equlbrum constants from statstcal mechancs. 4. Identfy how nondeal behavor can be
More informationON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION
Advanced Mathematcal Models & Applcatons Vol.3, No.3, 2018, pp.215-222 ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EUATION
More informationa. (All your answers should be in the letter!
Econ 301 Blkent Unversty Taskn Econometrcs Department of Economcs Md Term Exam I November 8, 015 Name For each hypothess testng n the exam complete the followng steps: Indcate the test statstc, ts crtcal
More informationModelli Clamfim Equazioni differenziali 22 settembre 2016
CLAMFIM Bologna Modell 1 @ Clamfm Equazon dfferenzal 22 settembre 2016 professor Danele Rtell danele.rtell@unbo.t 1/22? Ordnary Dfferental Equatons A dfferental equaton s an equaton that defnes a relatonshp
More informationOn a nonlinear compactness lemma in L p (0, T ; B).
On a nonlnear compactness lemma n L p (, T ; B). Emmanuel Matre Laboratore de Matématques et Applcatons Unversté de Haute-Alsace 4, rue des Frères Lumère 6893 Mulouse E.Matre@ua.fr 3t February 22 Abstract
More informationSimulation of Turbulent Flow Using FEM
Internatonal Journal of Engneerng and Technology Volume 2 No. 8, August, 2012 Smulaton of Turbulent Flow Usng FEM Sabah Tamm College of Computng, AlGhurar Unversty, Duba, Unted Arab Emrates. ABSTRACT An
More informationSome modelling aspects for the Matlab implementation of MMA
Some modellng aspects for the Matlab mplementaton of MMA Krster Svanberg krlle@math.kth.se Optmzaton and Systems Theory Department of Mathematcs KTH, SE 10044 Stockholm September 2004 1. Consdered optmzaton
More informationVideo Layer Extraction and Reconstruction
Vdeo Layer Extracton and Reconstructon Sylvan Pelleter 1, Françose Dbos 2 and Georges Koepfler 1 1 Unversty Pars Descartes, MAP5 (UMR CNRS 8145) 2 Unversty Pars Nord, LAGA (UMR CNRS 7539) MVA 2010-11 G.
More informationHow Differential Equations Arise. Newton s Second Law of Motion
page 1 CHAPTER 1 Frst-Order Dfferental Equatons Among all of the mathematcal dscplnes the theory of dfferental equatons s the most mportant. It furnshes the explanaton of all those elementary manfestatons
More informationSTUDY ON TWO PHASE FLOW IN MICRO CHANNEL BASED ON EXPERI- MENTS AND NUMERICAL EXAMINATIONS
Blucher Mechancal Engneerng Proceedngs May 0, vol., num. www.proceedngs.blucher.com.br/evento/0wccm STUDY ON TWO PHASE FLOW IN MICRO CHANNEL BASED ON EXPERI- MENTS AND NUMERICAL EXAMINATIONS Takahko Kurahash,
More information6 Supplementary Materials
6 Supplementar Materals 61 Proof of Theorem 31 Proof Let m Xt z 1:T : l m Xt X,z 1:t Wethenhave mxt z1:t ˆm HX Xt z 1:T mxt z1:t m HX Xt z 1:T + mxt z 1:T HX We consder each of the two terms n equaton
More informationNumerical Heat and Mass Transfer
Master degree n Mechancal Engneerng Numercal Heat and Mass Transfer 06-Fnte-Dfference Method (One-dmensonal, steady state heat conducton) Fausto Arpno f.arpno@uncas.t Introducton Why we use models and
More informationis the calculated value of the dependent variable at point i. The best parameters have values that minimize the squares of the errors
Multple Lnear and Polynomal Regresson wth Statstcal Analyss Gven a set of data of measured (or observed) values of a dependent varable: y versus n ndependent varables x 1, x, x n, multple lnear regresson
More information