CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE

Size: px
Start display at page:

Download "CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE"

Transcription

1 CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE Analytcal soluton s usually not possble when exctaton vares arbtrarly wth tme or f the system s nonlnear. Such problems can be solved by numercal tmesteppng methods for ntegraton of dfferental equatons. Tme-Steppng Method The equaton to be solved s or ( ) && & for lnearly elastc system mu + cu + ku = p t S (, ) ( ) && & & for nelastc system mu + cu + f u u = p t wth ntal condton u ( 0) = u0 u& ( 0) = u& 0 The appled force s gven by a set of dscrete values p = p( t ) where =0 to N. The tme nterval Δ t = t t + s usually constant, although ths s not necessary. The response s determned at dscrete tme nstant t. The dsplacement, velocty and acceleraton at tme t, denoted by u, u&, and u&&, respectvely, are assumed to be known and satsfy the equaton mu&& + cu& + ku = p 5 -

2 The numercal procedure to be presented wll enable us to determne the response quanttes u +, u & +, and u && + at tme + whch satsfy the equaton mu&& + cu& + ku = p We frst apply the procedure to tme = 0 to determne response at tme = and repeat the procedure agan to determne response at tme = 2 and so on. Therefore, ths progressve calculaton s called tme-steppng method. The response at tme + determned from response at tme s usually not exact. Many approxmate procedures mplemented numercally are possble. The requrements for a numercal procedure are () Convergence the numercal soluton should approach the exact soluton as the tme step decreases (2) Stablty the numercal soluton should be stable even f there s some round-off error or approxmaton. (3) Accuracy the numercal soluton should provde results that are close enough to the exact soluton. 5-2

3 These ssues are very mportant n numercal methods of solvng equatons. They wll govern the lmtaton of tmesteppng procedures. Three types of methods wll be dscussed: ) Method based on nterpolaton of exctaton 2) Method based on fnte dfference expresson of velocty and acceleraton 3) Method based on assumed varaton of acceleraton. 5-3

4 Method Based on Interpolaton of Exctaton Ths method s hghly effcent by nterpolaton exctaton durng a tme step as a lnearly varyng functon. p Δp ( τ ) p = + Δ t where Δ p = p + p and the tme varable τ vares from 0 to τ Δ t. For smplcty, we wll show dervaton of ths procedure for a system wthout dampng, although ths procedure can be extended to damped systems. The equaton to be solved s mu&& ku p Δp + = + t τ Δ The response u( τ ) over tme 0 τ Δ t s the sum of three parts: ) Free vbraton due to ntal dsplacement u and velocty u& at τ = 0 2) Response to step force p wth zero ntal condton Δp Δt τ 3) Response to ramp force wth zero ntal condton 5-4

5 Analytcal soluton derved n Chapter 3 can be used to determned the above three parts of responses and we wll get These formulae are derved from exact soluton of the equaton of moton. Therefore the result s exact f the exctaton s actually vares lnearly durng each tme step as usually assumed for earthquake ground exctaton whch s recorded at closely spaced tme ntervals. The exact soluton used n dervng ths procedure s avalable only f the system s lnear. The only restrcton on the sze of tme step s that t permts a close approxmaton to the exctaton functon and t provdes response results at closely spaced tme ntervals so that the response peaks are not mssed. 5-5

6 If the tme step Δ t s constant, the coeffcents A, B, D ' n ths procedure need to be computed only once. 5-6

7 5-7

8 5-8

9 Central Dfference Method Ths method s based on a fnte dfference approxmaton of the tme dervatves of dsplacements, whch are velocty and acceleraton. Suppose Δ t s constant Δ t. The central dfference expresson for velocty and acceleraton at tme are u u 2Δt + & = and u u&& u 2u + u = + 2 ( Δt) Substtutng these n the equaton of moton at tme, we get u+ 2u + u u+ u m + c + ku 2 = p 2Δt ( Δt) We assume that u and u are known from prevous steps. Transferrng known quanttes to the rght hand sde, we get or where m c m c 2m + u = p u k u ( Δt) 2Δt + ( Δt) 2Δt ( Δt) kˆ ( Δt) 2 ku ˆ m c = + 2 Δ t = + pˆ m c 2m pˆ = p u k u ( Δt) 2Δt ( Δt) 2 2 The unknown u + s then gven by u + = pˆ k ˆ 5-9

10 Note that u + s obtaned wthout usng equaton of moton at tme + but from equaton of moton at tme. And u + can be computed explctly from the known dsplacement u and u. Such method s called an explct method. When = 0, u s needed for computng u, so we consder u u 2Δt & 0 = and u u&& u 2u + u = ( Δt) Usng the frst equaton to elmnate u n the second equaton, we then have ( Δt ) 2 u = uo Δ t( u& 0) + u&& 0 2 And consder equaton of moton at tme = 0 we get mu&& + cu& + ku = p u&& = p cu& ku m to be used for determnng u The procedure s summarzed next 5-0

11 Ths central dfference method wll gve meanngless results, called unstable, f the tme step s not short enough. The requrement for stablty of ths procedure s that Δ t < T π n However, ths requrement s never a constrant because the tme step needs to be much shorter, typcally Δt/ T n 0., to obtan acceptable accuracy of results. In analyss of earthquake response, a tme step about sec up to 0.02 sec s chosen to defne ground exctaton. 5 -

12 5-2

13 Newmark s Method Ths method s developed by Nathan M. Newmark n 959 based on the followng equatons: ( γ) ( γ ) u & = u & + Δ t u && + Δt u && + + ( ) ( 0.5 β)( ) β( ) = + Δ & + Δ && + Δ && + u u t u t u t u The parameters β and γ defne the varaton of acceleraton over a tme step and determne the stablty and accuracy characterstcs of the method. Typcal selecton s γ =0.5 and β

14 Specal Cases. Average acceleraton If 2 u + γ = and β = 4 are chosen, the above equatons for u + and & corresponds to the specal case that acceleraton durng the tme step s constant and equal to the average of u&& and u && + as can be shown below. 2. Lnear acceleraton If 2 u + γ = and β = 6 are chosen, the above equatons for u + and & corresponds to the specal case that acceleraton durng the tme step vares lnearly between u&& and u && + as can be shown below. 5-4

15 Tme-Steppng Formula Ths method uses equlbrum equaton at tme and tme +, whch nvolves response quanttes at tme +,.e. u +, u & +, and u && +. Such method s called an mplct method. Let us defne the ncremental form Δ u = u+ u Δ u = u+ u & & & Δ u&& = u&& + u&& Δ p = p + p From the bass equatons of Newmark and Solve for ( γ) ( γ ) ( ) ( γ ) Δ u & = Δ t u && + Δ t u && = Δ t u && + Δt Δu && + ( ) ( 0.5 β)( ) β( ) 2 2 & && && + Δ u = Δ t u + Δ t u + Δt u Δ&& u and substtute ( ) ( Δt) 2 ( ) = Δ t u& + u&& + β Δt Δu&& 2 Δ u&& = Δu u& u&& β t βδt 2β ( Δ ) 2 Δ&& u n equaton for Δ u& γ γ γ Δ u & = Δu u +Δt u βδt β & 2 β && Then, substtute Δ u& and equaton of moton 2 Δ&& u n the ncremental form of mδ u&& + cδ u& + kδ u =Δp It can be wrtten as kˆ Δ u =Δ pˆ We obtan Δpˆ Δ u = k ˆ 5-5

16 where and Once γ ˆk = k + c+ m βδt β ( Δt) 2 γ γ Δ pˆ =Δ p + m c u m t c u + β t β & + +Δ Δ 2β 2β && Δ u s known, u Δ &, Δ&& u, u +, u & +, and u && + can be computed u = u +Δ + u u & = u & +Δ + u & u&& = u&& +Δ + u&& Alternatvely, u && + can be computed from u&& + = p cu& ku m

17 Newmark s method s stable f Δt T π 2 γ 2β For Average acceleraton method γ = and β = 2 4 n Δ t < T Ths mples that average acceleraton method s stable for any Δ t, although results would not be accurate for large Δ t. n For Lnear acceleraton method Δ t γ = 2 and β = 6 < 0.55 T Ths requrement s not sgnfcant because a much smaller tme step s requred for accurate representaton of exctaton and response. n 5-7

18 5-8

19 5-9

20 Stablty Numercal procedures that gve bounded results f tme step s shorter than a certan lmt are called condtonally stable. Numercal procedures that gve bounded results regardless of tme step sze, no matter how large, are called uncondtonally stable. Stablty of the method s mportant for mult-degree-offreedom system where a uncondtonally stable method s sometmes necessary. Computatonal Error Error s nherent n any numercal method both from round-off error and approxmaton of soluton. Let us consder solutons of free vbraton usng dfferent procedures dscussed earler; Δ t = 0.T n ; and compare to the exact analytcal soluton. 5-20

21 All numercal methods gve results that have ampltude decay, mplyng that these procedures ntroduce numercal dampng. Most methods make the perod of vbraton longer except the central dfference method, whch gves result that has shorter perod than the exact result. Perod shortenng n the central dfference method s hghly sgnfcant when Δ t Ts close to ts stablty lmt /π. / n 5-2

22 The lnear acceleraton Newmark s method seems to be most accurate n the sense of least perod elongaton error for these methods consdered for lnear SDF system. The choce of methods would be dfferent for MDF system or nonlnear response analyss. The choce of tme step also depends on the tme varaton of the dynamc exctaton and natural perod of the system. Δ t = 0.T n gves reasonably accurate results, but t also has to be small enough to avod dstorton of the exctaton functon. For earthquake exctaton Δ t s usually less than 0.02 sec. A useful technque for selectng the tme step s to solve the problem wth a tme step that seems reasonable and resolve the problem wth a small tme step. The tme step s deemed small enough f results from two analyses are essentally the same, otherwse reduce the tme step and repeat such comparson untl two successve solutons are close enough. 5-22

NUMERICAL DIFFERENTIATION

NUMERICAL DIFFERENTIATION NUMERICAL DIFFERENTIATION 1 Introducton Dfferentaton s a method to compute the rate at whch a dependent output y changes wth respect to the change n the ndependent nput x. Ths rate of change s called the

More information

November 5, 2002 SE 180: Earthquake Engineering SE 180. Final Project

November 5, 2002 SE 180: Earthquake Engineering SE 180. Final Project SE 8 Fnal Project Story Shear Frame u m Gven: u m L L m L L EI ω ω Solve for m Story Bendng Beam u u m L m L Gven: m L L EI ω ω Solve for m 3 3 Story Shear Frame u 3 m 3 Gven: L 3 m m L L L 3 EI ω ω ω

More information

Handout # 6 (MEEN 617) Numerical Integration to Find Time Response of SDOF mechanical system. and write EOM (1) as two first-order Eqs.

Handout # 6 (MEEN 617) Numerical Integration to Find Time Response of SDOF mechanical system. and write EOM (1) as two first-order Eqs. Handout # 6 (MEEN 67) Numercal Integraton to Fnd Tme Response of SDOF mechancal system State Space Method The EOM for a lnear system s M X + DX + K X = F() t () t = X = X X = X = V wth ntal condtons, at

More information

4DVAR, according to the name, is a four-dimensional variational method.

4DVAR, according to the name, is a four-dimensional variational method. 4D-Varatonal Data Assmlaton (4D-Var) 4DVAR, accordng to the name, s a four-dmensonal varatonal method. 4D-Var s actually a drect generalzaton of 3D-Var to handle observatons that are dstrbuted n tme. The

More information

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons

More information

Lecture 21: Numerical methods for pricing American type derivatives

Lecture 21: Numerical methods for pricing American type derivatives Lecture 21: Numercal methods for prcng Amercan type dervatves Xaoguang Wang STAT 598W Aprl 10th, 2014 (STAT 598W) Lecture 21 1 / 26 Outlne 1 Fnte Dfference Method Explct Method Penalty Method (STAT 598W)

More information

The equation of motion of a dynamical system is given by a set of differential equations. That is (1)

The equation of motion of a dynamical system is given by a set of differential equations. That is (1) Dynamcal Systems Many engneerng and natural systems are dynamcal systems. For example a pendulum s a dynamcal system. State l The state of the dynamcal system specfes t condtons. For a pendulum n the absence

More information

Difference Equations

Difference Equations Dfference Equatons c Jan Vrbk 1 Bascs Suppose a sequence of numbers, say a 0,a 1,a,a 3,... s defned by a certan general relatonshp between, say, three consecutve values of the sequence, e.g. a + +3a +1

More information

NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS

NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS IJRRAS 8 (3 September 011 www.arpapress.com/volumes/vol8issue3/ijrras_8_3_08.pdf NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS H.O. Bakodah Dept. of Mathematc

More information

Additional Codes using Finite Difference Method. 1 HJB Equation for Consumption-Saving Problem Without Uncertainty

Additional Codes using Finite Difference Method. 1 HJB Equation for Consumption-Saving Problem Without Uncertainty Addtonal Codes usng Fnte Dfference Method Benamn Moll 1 HJB Equaton for Consumpton-Savng Problem Wthout Uncertanty Before consderng the case wth stochastc ncome n http://www.prnceton.edu/~moll/ HACTproect/HACT_Numercal_Appendx.pdf,

More information

Solution of Equilibrium Equation in Dynamic Analysis. Mode Superposition. Dominik Hauswirth Method of Finite Elements II Page 1

Solution of Equilibrium Equation in Dynamic Analysis. Mode Superposition. Dominik Hauswirth Method of Finite Elements II Page 1 Soluton of Equlbrum Equaton n Dynamc Analyss Mode Superposton Domnk Hauswrth..7 Method of Fnte Elements II Page Contents. Mode Superposton: Idea and Equatons. Example 9.7 3. Modes 4. Include Dampng 5.

More information

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module 3 LOSSY IMAGE COMPRESSION SYSTEMS Verson ECE IIT, Kharagpur Lesson 6 Theory of Quantzaton Verson ECE IIT, Kharagpur Instructonal Objectves At the end of ths lesson, the students should be able to:

More information

Appendix B. The Finite Difference Scheme

Appendix B. The Finite Difference Scheme 140 APPENDIXES Appendx B. The Fnte Dfference Scheme In ths appendx we present numercal technques whch are used to approxmate solutons of system 3.1 3.3. A comprehensve treatment of theoretcal and mplementaton

More information

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system

Transfer 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 information

coordinates. Then, the position vectors are described by

coordinates. Then, the position vectors are described by Revewng, what we have dscussed so far: Generalzed coordnates Any number of varables (say, n) suffcent to specfy the confguraton of the system at each nstant to tme (need not be the mnmum number). In general,

More information

Irregular vibrations in multi-mass discrete-continuous systems torsionally deformed

Irregular vibrations in multi-mass discrete-continuous systems torsionally deformed (2) 4 48 Irregular vbratons n mult-mass dscrete-contnuous systems torsonally deformed Abstract In the paper rregular vbratons of dscrete-contnuous systems consstng of an arbtrary number rgd bodes connected

More information

MMA and GCMMA two methods for nonlinear optimization

MMA and GCMMA two methods for nonlinear optimization MMA and GCMMA two methods for nonlnear optmzaton Krster Svanberg Optmzaton and Systems Theory, KTH, Stockholm, Sweden. krlle@math.kth.se Ths note descrbes the algorthms used n the author s 2007 mplementatons

More information

Lecture 12: Discrete Laplacian

Lecture 12: Discrete Laplacian Lecture 12: Dscrete Laplacan Scrbe: Tanye Lu Our goal s to come up wth a dscrete verson of Laplacan operator for trangulated surfaces, so that we can use t n practce to solve related problems We are mostly

More information

Errors for Linear Systems

Errors for Linear Systems Errors for Lnear Systems When we solve a lnear system Ax b we often do not know A and b exactly, but have only approxmatons  and ˆb avalable. Then the best thng we can do s to solve ˆx ˆb exactly whch

More information

The Finite Element Method

The 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 information

A new Approach for Solving Linear Ordinary Differential Equations

A 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 information

EEE 241: Linear Systems

EEE 241: Linear Systems EEE : Lnear Systems Summary #: Backpropagaton BACKPROPAGATION The perceptron rule as well as the Wdrow Hoff learnng were desgned to tran sngle layer networks. They suffer from the same dsadvantage: they

More information

Some modelling aspects for the Matlab implementation of MMA

Some 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 information

2 Finite difference basics

2 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 information

6.3.7 Example with Runga Kutta 4 th order method

6.3.7 Example with Runga Kutta 4 th order method 6.3.7 Example wth Runga Kutta 4 th order method Agan, as an example, 3 machne, 9 bus system shown n Fg. 6.4 s agan consdered. Intally, the dampng of the generators are neglected (.e. d = 0 for = 1, 2,

More information

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4)

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4) I. Classcal Assumptons Econ7 Appled Econometrcs Topc 3: Classcal Model (Studenmund, Chapter 4) We have defned OLS and studed some algebrac propertes of OLS. In ths topc we wll study statstcal propertes

More information

Numerical Solution of Ordinary Differential Equations

Numerical Solution of Ordinary Differential Equations Numercal Methods (CENG 00) CHAPTER-VI Numercal Soluton of Ordnar Dfferental Equatons 6 Introducton Dfferental equatons are equatons composed of an unknown functon and ts dervatves The followng are examples

More information

Numerical Heat and Mass Transfer

Numerical 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 information

Application of B-Spline to Numerical Solution of a System of Singularly Perturbed Problems

Application of B-Spline to Numerical Solution of a System of Singularly Perturbed Problems Mathematca Aeterna, Vol. 1, 011, no. 06, 405 415 Applcaton of B-Splne to Numercal Soluton of a System of Sngularly Perturbed Problems Yogesh Gupta Department of Mathematcs Unted College of Engneerng &

More information

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1 P. Guterrez Physcs 5153 Classcal Mechancs D Alembert s Prncple and The Lagrangan 1 Introducton The prncple of vrtual work provdes a method of solvng problems of statc equlbrum wthout havng to consder the

More information

6.3.4 Modified Euler s method of integration

6.3.4 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 information

Chapter 12. Ordinary Differential Equation Boundary Value (BV) Problems

Chapter 12. Ordinary Differential Equation Boundary Value (BV) Problems Chapter. Ordnar Dfferental Equaton Boundar Value (BV) Problems In ths chapter we wll learn how to solve ODE boundar value problem. BV ODE s usuall gven wth x beng the ndependent space varable. p( x) q(

More information

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could

More information

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number

More information

Solution of Linear System of Equations and Matrix Inversion Gauss Seidel Iteration Method

Solution of Linear System of Equations and Matrix Inversion Gauss Seidel Iteration Method Soluton of Lnear System of Equatons and Matr Inverson Gauss Sedel Iteraton Method It s another well-known teratve method for solvng a system of lnear equatons of the form a + a22 + + ann = b a2 + a222

More information

One-sided finite-difference approximations suitable for use with Richardson extrapolation

One-sided finite-difference approximations suitable for use with Richardson extrapolation Journal of Computatonal Physcs 219 (2006) 13 20 Short note One-sded fnte-dfference approxmatons sutable for use wth Rchardson extrapolaton Kumar Rahul, S.N. Bhattacharyya * Department of Mechancal Engneerng,

More information

Visco-Rubber Elastic Model for Pressure Sensitive Adhesive

Visco-Rubber Elastic Model for Pressure Sensitive Adhesive Vsco-Rubber Elastc Model for Pressure Senstve Adhesve Kazuhsa Maeda, Shgenobu Okazawa, Koj Nshgch and Takash Iwamoto Abstract A materal model to descrbe large deformaton of pressure senstve adhesve (PSA

More information

Start with the equation of motion for a linear multi-degree of freedom system with base ground excitation:

Start with the equation of motion for a linear multi-degree of freedom system with base ground excitation: SE 80 Earthquake Enneern November 3, 00 STEP-BY-STEP PROCEDURE FOR SETTING UP A SPREADSHEET FOR USING NEWMARK S METHOD AND MODAL ANALYSIS TO SOLVE FOR THE RESPONSE OF A MULTI-DEGREE OF FREEDOM (MDOF) SYSTEM

More information

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity

Week3, 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 information

ME 501A Seminar in Engineering Analysis Page 1

ME 501A Seminar in Engineering Analysis Page 1 umercal Solutons of oundary-value Problems n Os ovember 7, 7 umercal Solutons of oundary- Value Problems n Os Larry aretto Mechancal ngneerng 5 Semnar n ngneerng nalyss ovember 7, 7 Outlne Revew stff equaton

More information

The optimal delay of the second test is therefore approximately 210 hours earlier than =2.

The optimal delay of the second test is therefore approximately 210 hours earlier than =2. THE IEC 61508 FORMULAS 223 The optmal delay of the second test s therefore approxmately 210 hours earler than =2. 8.4 The IEC 61508 Formulas IEC 61508-6 provdes approxmaton formulas for the PF for smple

More information

Consistency & Convergence

Consistency & Convergence /9/007 CHE 374 Computatonal Methods n Engneerng Ordnary Dfferental Equatons Consstency, Convergence, Stablty, Stffness and Adaptve and Implct Methods ODE s n MATLAB, etc Consstency & Convergence Consstency

More information

On a direct solver for linear least squares problems

On a direct solver for linear least squares problems ISSN 2066-6594 Ann. Acad. Rom. Sc. Ser. Math. Appl. Vol. 8, No. 2/2016 On a drect solver for lnear least squares problems Constantn Popa Abstract The Null Space (NS) algorthm s a drect solver for lnear

More information

8.592J: Solutions for Assignment 7 Spring 2005

8.592J: Solutions for Assignment 7 Spring 2005 8.59J: Solutons for Assgnment 7 Sprng 5 Problem 1 (a) A flament of length l can be created by addton of a monomer to one of length l 1 (at rate a) or removal of a monomer from a flament of length l + 1

More information

9.2 Seismic Loads Using ASCE Standard 7-93

9.2 Seismic Loads Using ASCE Standard 7-93 CHAPER 9: Wnd and Sesmc Loads on Buldngs 9.2 Sesmc Loads Usng ASCE Standard 7-93 Descrpton A major porton of the Unted States s beleved to be subject to sesmc actvty suffcent to cause sgnfcant structural

More information

Research Article Cubic B-Spline Collocation Method for One-Dimensional Heat and Advection-Diffusion Equations

Research Article Cubic B-Spline Collocation Method for One-Dimensional Heat and Advection-Diffusion Equations Appled Mathematcs Volume 22, Artcle ID 4587, 8 pages do:.55/22/4587 Research Artcle Cubc B-Splne Collocaton Method for One-Dmensonal Heat and Advecton-Dffuson Equatons Joan Goh, Ahmad Abd. Majd, and Ahmad

More information

Formal solvers of the RT equation

Formal 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 information

Physics 5153 Classical Mechanics. Principle of Virtual Work-1

Physics 5153 Classical Mechanics. Principle of Virtual Work-1 P. Guterrez 1 Introducton Physcs 5153 Classcal Mechancs Prncple of Vrtual Work The frst varatonal prncple we encounter n mechancs s the prncple of vrtual work. It establshes the equlbrum condton of a mechancal

More information

Inductance Calculation for Conductors of Arbitrary Shape

Inductance Calculation for Conductors of Arbitrary Shape CRYO/02/028 Aprl 5, 2002 Inductance Calculaton for Conductors of Arbtrary Shape L. Bottura Dstrbuton: Internal Summary In ths note we descrbe a method for the numercal calculaton of nductances among conductors

More information

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction

The 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 information

n 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

n 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 information

Feature Selection: Part 1

Feature Selection: Part 1 CSE 546: Machne Learnng Lecture 5 Feature Selecton: Part 1 Instructor: Sham Kakade 1 Regresson n the hgh dmensonal settng How do we learn when the number of features d s greater than the sample sze n?

More information

Chapter Newton s Method

Chapter Newton s Method Chapter 9. Newton s Method After readng ths chapter, you should be able to:. Understand how Newton s method s dfferent from the Golden Secton Search method. Understand how Newton s method works 3. Solve

More information

Report on Image warping

Report on Image warping Report on Image warpng Xuan Ne, Dec. 20, 2004 Ths document summarzed the algorthms of our mage warpng soluton for further study, and there s a detaled descrpton about the mplementaton of these algorthms.

More information

PARTICIPATION FACTOR IN MODAL ANALYSIS OF POWER SYSTEMS STABILITY

PARTICIPATION FACTOR IN MODAL ANALYSIS OF POWER SYSTEMS STABILITY POZNAN UNIVE RSITY OF TE CHNOLOGY ACADE MIC JOURNALS No 86 Electrcal Engneerng 6 Volodymyr KONOVAL* Roman PRYTULA** PARTICIPATION FACTOR IN MODAL ANALYSIS OF POWER SYSTEMS STABILITY Ths paper provdes a

More information

DETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM

DETERMINATION 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 information

Computers and Mathematics with Applications

Computers and Mathematics with Applications Computers and Mathematcs wth Applcatons 56 (2008 3204 3220 Contents lsts avalable at ScenceDrect Computers and Mathematcs wth Applcatons journal homepage: www.elsever.com/locate/camwa An nnovatve egenvalue

More information

Assessment of Site Amplification Effect from Input Energy Spectra of Strong Ground Motion

Assessment of Site Amplification Effect from Input Energy Spectra of Strong Ground Motion Assessment of Ste Amplfcaton Effect from Input Energy Spectra of Strong Ground Moton M.S. Gong & L.L Xe Key Laboratory of Earthquake Engneerng and Engneerng Vbraton,Insttute of Engneerng Mechancs, CEA,

More information

Finite Element Modelling of truss/cable structures

Finite Element Modelling of truss/cable structures Pet Schreurs Endhoven Unversty of echnology Department of Mechancal Engneerng Materals echnology November 3, 214 Fnte Element Modellng of truss/cable structures 1 Fnte Element Analyss of prestressed structures

More information

MATH 5630: Discrete Time-Space Model Hung Phan, UMass Lowell March 1, 2018

MATH 5630: Discrete Time-Space Model Hung Phan, UMass Lowell March 1, 2018 MATH 5630: Dscrete Tme-Space Model Hung Phan, UMass Lowell March, 08 Newton s Law of Coolng Consder the coolng of a well strred coffee so that the temperature does not depend on space Newton s law of collng

More information

The Finite Element Method: A Short Introduction

The 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 information

NON LINEAR ANALYSIS OF STRUCTURES ACCORDING TO NEW EUROPEAN DESIGN CODE

NON LINEAR ANALYSIS OF STRUCTURES ACCORDING TO NEW EUROPEAN DESIGN CODE October 1-17, 008, Bejng, Chna NON LINEAR ANALYSIS OF SRUCURES ACCORDING O NEW EUROPEAN DESIGN CODE D. Mestrovc 1, D. Czmar and M. Pende 3 1 Professor, Dept. of Structural Engneerng, Faculty of Cvl Engneerng,

More information

Digital Signal Processing

Digital 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 information

Second Order Analysis

Second Order Analysis Second Order Analyss In the prevous classes we looked at a method that determnes the load correspondng to a state of bfurcaton equlbrum of a perfect frame by egenvalye analyss The system was assumed to

More information

Finite Differences, Interpolation, and Numerical Differentiation

Finite Differences, Interpolation, and Numerical Differentiation 4 Fnte Dfferences, Interpolaton, and Numercal Dfferentaton 4. INTRODUCTION Lnear nterpolaton s dscussed n the precedng chapter as a method for fndng a partcular root of a polynomal, or, transcendental

More information

Note 10. Modeling and Simulation of Dynamic Systems

Note 10. Modeling and Simulation of Dynamic Systems Lecture Notes of ME 475: Introducton to Mechatroncs Note 0 Modelng and Smulaton of Dynamc Systems Department of Mechancal Engneerng, Unversty Of Saskatchewan, 57 Campus Drve, Saskatoon, SK S7N 5A9, Canada

More information

SIO 224. m(r) =(ρ(r),k s (r),µ(r))

SIO 224. m(r) =(ρ(r),k s (r),µ(r)) SIO 224 1. A bref look at resoluton analyss Here s some background for the Masters and Gubbns resoluton paper. Global Earth models are usually found teratvely by assumng a startng model and fndng small

More information

Implicit Integration Henyey Method

Implicit 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 information

Limited Dependent Variables

Limited Dependent Variables Lmted Dependent Varables. What f the left-hand sde varable s not a contnuous thng spread from mnus nfnty to plus nfnty? That s, gven a model = f (, β, ε, where a. s bounded below at zero, such as wages

More information

Lecture 13 APPROXIMATION OF SECOMD ORDER DERIVATIVES

Lecture 13 APPROXIMATION OF SECOMD ORDER DERIVATIVES COMPUTATIONAL FLUID DYNAMICS: FDM: Appromaton of Second Order Dervatves Lecture APPROXIMATION OF SECOMD ORDER DERIVATIVES. APPROXIMATION OF SECOND ORDER DERIVATIVES Second order dervatves appear n dffusve

More information

Flow Induced Vibration

Flow Induced Vibration Flow Induced Vbraton Project Progress Report Date: 16 th November, 2005 Submtted by Subhrajt Bhattacharya Roll no.: 02ME101 Done under the gudance of Prof. Anrvan Dasgupta Department of Mechancal Engneerng,

More information

As it can be observed from Fig. a) and b), applying Newton s Law for the tangential force component results into: mg sin mat

As it can be observed from Fig. a) and b), applying Newton s Law for the tangential force component results into: mg sin mat PHY4HF Exercse : Numercal ntegraton methods The Pendulum Startng wth small angles of oscllaton, you wll get expermental data on a smple pendulum and wll wrte a Python program to solve the equaton of moton.

More information

Chapter 3. Estimation of Earthquake Load Effects

Chapter 3. Estimation of Earthquake Load Effects Chapter 3. Estmaton of Earthquake Load Effects 3.1 Introducton Sesmc acton on chmneys forms an addtonal source of natural loads on the chmney. Sesmc acton or the earthquake s a short and strong upheaval

More information

Chapter - 2. Distribution System Power Flow Analysis

Chapter - 2. Distribution System Power Flow Analysis Chapter - 2 Dstrbuton System Power Flow Analyss CHAPTER - 2 Radal Dstrbuton System Load Flow 2.1 Introducton Load flow s an mportant tool [66] for analyzng electrcal power system network performance. Load

More information

FTCS Solution to the Heat Equation

FTCS Solution to the Heat Equation FTCS Soluton to the Heat Equaton ME 448/548 Notes Gerald Recktenwald Portland State Unversty Department of Mechancal Engneerng gerry@pdx.edu ME 448/548: FTCS Soluton to the Heat Equaton Overvew 1. Use

More information

Linear Approximation with Regularization and Moving Least Squares

Linear Approximation with Regularization and Moving Least Squares Lnear Approxmaton wth Regularzaton and Movng Least Squares Igor Grešovn May 007 Revson 4.6 (Revson : March 004). 5 4 3 0.5 3 3.5 4 Contents: Lnear Fttng...4. Weghted Least Squares n Functon Approxmaton...

More information

Solving Fractional Nonlinear Fredholm Integro-differential Equations via Hybrid of Rationalized Haar Functions

Solving 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 information

High resolution entropy stable scheme for shallow water equations

High resolution entropy stable scheme for shallow water equations Internatonal Symposum on Computers & Informatcs (ISCI 05) Hgh resoluton entropy stable scheme for shallow water equatons Xaohan Cheng,a, Yufeng Ne,b, Department of Appled Mathematcs, Northwestern Polytechncal

More information

New Method for Solving Poisson Equation. on Irregular Domains

New Method for Solving Poisson Equation. on Irregular Domains Appled Mathematcal Scences Vol. 6 01 no. 8 369 380 New Method for Solvng Posson Equaton on Irregular Domans J. Izadan and N. Karamooz Department of Mathematcs Facult of Scences Mashhad BranchIslamc Azad

More information

CHAPTER 6. LAGRANGE S EQUATIONS (Analytical Mechanics)

CHAPTER 6. LAGRANGE S EQUATIONS (Analytical Mechanics) CHAPTER 6 LAGRANGE S EQUATIONS (Analytcal Mechancs) 1 Ex. 1: Consder a partcle movng on a fxed horzontal surface. r P Let, be the poston and F be the total force on the partcle. The FBD s: -mgk F 1 x O

More information

PHYS 705: Classical Mechanics. Calculus of Variations II

PHYS 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 information

THE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructions

THE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructions THE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructons by George Hardgrove Chemstry Department St. Olaf College Northfeld, MN 55057 hardgrov@lars.acc.stolaf.edu Copyrght George

More information

Chapter 4 The Wave Equation

Chapter 4 The Wave Equation Chapter 4 The Wave Equaton Another classcal example of a hyperbolc PDE s a wave equaton. The wave equaton s a second-order lnear hyperbolc PDE that descrbes the propagaton of a varety of waves, such as

More information

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity

LINEAR 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 information

Identification of Instantaneous Modal Parameters of A Nonlinear Structure Via Amplitude-Dependent ARX Model

Identification of Instantaneous Modal Parameters of A Nonlinear Structure Via Amplitude-Dependent ARX Model Identfcaton of Instantaneous Modal Parameters of A Nonlnear Structure Va Ampltude-Dependent ARX Model We Chh Su(NCHC), Chung Shann Huang(NCU), Chng Yu Lu(NCU) Outlne INRODUCION MEHODOLOGY NUMERICAL VERIFICAION

More information

Tensor Smooth Length for SPH Modelling of High Speed Impact

Tensor Smooth Length for SPH Modelling of High Speed Impact Tensor Smooth Length for SPH Modellng of Hgh Speed Impact Roman Cherepanov and Alexander Gerasmov Insttute of Appled mathematcs and mechancs, Tomsk State Unversty 634050, Lenna av. 36, Tomsk, Russa RCherepanov82@gmal.com,Ger@npmm.tsu.ru

More information

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity LINEAR REGRESSION ANALYSIS MODULE IX Lecture - 30 Multcollnearty Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur 2 Remedes for multcollnearty Varous technques have

More information

Numerical Simulation of One-Dimensional Wave Equation by Non-Polynomial Quintic Spline

Numerical 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 information

where the sums are over the partcle labels. In general H = p2 2m + V s(r ) V j = V nt (jr, r j j) (5) where V s s the sngle-partcle potental and V nt

where the sums are over the partcle labels. In general H = p2 2m + V s(r ) V j = V nt (jr, r j j) (5) where V s s the sngle-partcle potental and V nt Physcs 543 Quantum Mechancs II Fall 998 Hartree-Fock and the Self-consstent Feld Varatonal Methods In the dscusson of statonary perturbaton theory, I mentoned brey the dea of varatonal approxmaton schemes.

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 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 information

ACTM State Calculus Competition Saturday April 30, 2011

ACTM State Calculus Competition Saturday April 30, 2011 ACTM State Calculus Competton Saturday Aprl 30, 2011 ACTM State Calculus Competton Sprng 2011 Page 1 Instructons: For questons 1 through 25, mark the best answer choce on the answer sheet provde Afterward

More information

2.29 Numerical Fluid Mechanics Fall 2011 Lecture 12

2.29 Numerical Fluid Mechanics Fall 2011 Lecture 12 REVIEW Lecture 11: 2.29 Numercal Flud Mechancs Fall 2011 Lecture 12 End of (Lnear) Algebrac Systems Gradent Methods Krylov Subspace Methods Precondtonng of Ax=b FINITE DIFFERENCES Classfcaton of Partal

More information

Integrals and Invariants of Euler-Lagrange Equations

Integrals and Invariants of Euler-Lagrange Equations Lecture 16 Integrals and Invarants of Euler-Lagrange Equatons ME 256 at the Indan Insttute of Scence, Bengaluru Varatonal Methods and Structural Optmzaton G. K. Ananthasuresh Professor, Mechancal Engneerng,

More information

In this section is given an overview of the common elasticity models.

In 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 information

Discretization. Consistency. Exact Solution Convergence x, t --> 0. Figure 5.1: Relation between consistency, stability, and convergence.

Discretization. Consistency. Exact Solution Convergence x, t --> 0. Figure 5.1: Relation between consistency, stability, and convergence. Chapter 5 Theory The numercal smulaton of PDE s requres careful consderatons of propertes of the approxmate soluton. A necessary condton for the scheme used to model a physcal problem s the consstency

More information

This column is a continuation of our previous column

This column is a continuation of our previous column Comparson of Goodness of Ft Statstcs for Lnear Regresson, Part II The authors contnue ther dscusson of the correlaton coeffcent n developng a calbraton for quanttatve analyss. Jerome Workman Jr. and Howard

More information

Suppose that there s a measured wndow of data fff k () ; :::; ff k g of a sze w, measured dscretely wth varable dscretzaton step. It s convenent to pl

Suppose that there s a measured wndow of data fff k () ; :::; ff k g of a sze w, measured dscretely wth varable dscretzaton step. It s convenent to pl RECURSIVE SPLINE INTERPOLATION METHOD FOR REAL TIME ENGINE CONTROL APPLICATIONS A. Stotsky Volvo Car Corporaton Engne Desgn and Development Dept. 97542, HA1N, SE- 405 31 Gothenburg Sweden. Emal: astotsky@volvocars.com

More information

Statistical Energy Analysis for High Frequency Acoustic Analysis with LS-DYNA

Statistical Energy Analysis for High Frequency Acoustic Analysis with LS-DYNA 14 th Internatonal Users Conference Sesson: ALE-FSI Statstcal Energy Analyss for Hgh Frequency Acoustc Analyss wth Zhe Cu 1, Yun Huang 1, Mhamed Soul 2, Tayeb Zeguar 3 1 Lvermore Software Technology Corporaton

More information

Bezier curves. Michael S. Floater. August 25, These notes provide an introduction to Bezier curves. i=0

Bezier curves. Michael S. Floater. August 25, These notes provide an introduction to Bezier curves. i=0 Bezer curves Mchael S. Floater August 25, 211 These notes provde an ntroducton to Bezer curves. 1 Bernsten polynomals Recall that a real polynomal of a real varable x R, wth degree n, s a functon of the

More information

Chapter 13: Multiple Regression

Chapter 13: Multiple Regression Chapter 13: Multple Regresson 13.1 Developng the multple-regresson Model The general model can be descrbed as: It smplfes for two ndependent varables: The sample ft parameter b 0, b 1, and b are used to

More information