Computational Fluid Dynamics II

Size: px
Start display at page:

Download "Computational Fluid Dynamics II"

Transcription

1 Computatonal Flud Dynamcs II Eercse 2 1. Gven s the PDE: u tt a 2 ou Formulate the CFL-condton for two possble eplct schemes. 2. The Euler equatons for 1-dmensonal, unsteady flows s dscretsed n the followng form: U n+1 U n + Fn +1 Fn, U = ρ ρu ρe For whch veloctes does ths scheme fulfll the CFL-condton? 3. Formulate for the lnear model equaton the followng soluton schemes: (a) eplct scheme, central dfferences (b) La-Wendroff scheme (c) Mac-Cormack scheme u t +au, F n = F(U n ) Determne the stablty condtons and truncaton errors. Show that the Mac-Cormack scheme and the La-Wendroff scheme are equvalent for ths lnear model equaton. 4. Check the consstency, stablty and convergence of an mplct method wth backward dfference n tme and central dfferences n space for the followng PDE: u t +au Specfy the soluton algorthm for that scheme, wth use of the boundary condtons u(=0)=u and u =L=0. 4

2 Computatonal Flud Dynamcs II Eercse 2 (soluton) 1. CFL condton: the numercal doman of nfluence has to enclose the physcal one. The characterstc lnes defne the physcal doman of nfluence, the dfference stencl defnes the numercal doman of nfluence. eplct scheme 1: 2u n +un 1 2 a 2 u n +1 2un +un physcal doman of nfluence: dt d C = ± 1 a 0 t,n 1/a 0 1/a 0, eplct scheme 2: numercal nfluence area physcal nfluence area numercal doman of nfluence: dt d = ± N CFL-condton: 1 a 0 2u n +un 1 2 a 2 u+1 n 1 2un 1 +u 1 n physcal doman of nfluence: dt d C = ± 1 a 0 t,n, 1/a 0 1/a 0 numercal nfluence area physcal nfluence area numercal doman of nfluence: CFL-condton: dt d N = ±2 1 2 a 0 5

3 2. 1D-Euler equatons: ρ t +(ρu) (ρu) t +(ρu 2 +p) (ρe) t +(u(ρe +p)) wth the equaton of state for deal gases: p = (κ 1)(ρE ρ 2 u2 ) and a 2 = κrt Dfferentate and convert n non-conservatve form: ρ t +uρ +ρu uρ t +ρu t +u(ρu) +ρuu +p (ρe) t +(uρe) +(up) Insert the contnuty equaton nto the momentum equaton and the contnuty, momentum, and equaton of state nto the energy equaton. After smplfcaton the followng form can be obtaned: ρ t +uρ +ρu u t +uu + 1 ρ p p t +up +ρa 2 u Characterstc lnes: Ω t +uω ρω Ω t +uω ρ Ω 0 ρa 2 Ω Ω t +uω (Ω t +uω ) 3 Ω 2 a 2 (Ω t +uω ) Ω t = d 1 dt = u Ω t = d 1 2,3 dt = u±a 2,3 CFL-condton: all characterstc lnes have to le n the numercal doman of nfluence: Ω Ω condton (sde ): u+a 0 n+1 condton (sde +1): t n u a t u+a u +1 u a.e.: a u a 6

4 3. Lnear model equaton u t +au (a) Eplct, central dfferences wth u n +a un +1 un 1 2 u n = u+u t u tt u ttt +... = u u n +1 = u+ u u u +... u n 1 = u u u 3 6 u +... follows Truncaton error u t u tt u ttt +a 2 u u 2 u t + 2 u tt u ttt +a(u u ) von Neumann analyss: u t +au = 2 u tt 2 6 u ttt a 2 6 u = O(, 2 ) Approach for the error functonǫ: ǫ n = φ=π φ=0 n (Φ)e ΦI, Φ = 2π λ, t = n, I = 1 apply the approach n the model equaton wth e ΦI n e ΦI +a n e (+1)ΦI n e ( 1)ΦI 2 1 n +a eφi e ΦI 2 e ΦI = cos(φ)+isn(φ) e ΦI = cos(φ) Isn(Φ) 7

5 follows G = 1 n +a 2Isn(Φ) 2 n = 1 a Isn(Φ) G 2 = 1+ n 1+a Isn(Φ) ( a sn(φ) ) 2 for a stable dfference scheme t s requred that G 2 1 scheme s unstable! (b) La-Wendroff scheme u n +a un +1 un 1 2 wth,u n,un +1 andun 1 (see (a)) follows u+u t u tt u ttt u + a 2 un +1 2un +un a (u+ u u u ) (u u u 3 6 u ) 2 a 2 (u+ u u u ) (2u)+(u u u 3 6 u ) 2 2 u+u t u tt u ttt u +a 2 u u 2 u t + 2 u tt u ttt +au +a 2 6 u a 2 2 u Truncaton error a u 2 2 u t +au = 2 u tt 2 6 u ttt a 2 6 u +a 2 2 u wth u tt = a 2 u von Neumann analyss: = a 2 2 u 2 6 u ttt a 2 6 u +a 2 2 u = 2 6 u ttt a 2 6 u = O( 2, 2 ) e ΦI n e ΦI 1 n +a eφi e ΦI 2 G = +a n e (+1)ΦI n e ( 1)ΦI 2 a 2 eφi 2+e ΦI 2 2 = n = 1 aisn(φ) a 2 n e (+1)ΦI 2 n e ΦI + n e ( 1)ΦI n +a 2Isn(Φ) a 2 2cos(Φ) a 2 2cos(Φ) 1 2 wth k = a 8

6 G 2 = (1+k 2 (cos(φ) 1)) 2 +( ksn(φ)) 2 = 1+2k 2 (cos(φ) 1)+k 4 (cos(φ) 1) 2 +k 2 sn 2 (Φ) = k 4 (1 cos(φ)) 2 +k 2 (sn 2 (Φ) 2+2cos(Φ))+1 = k 4 (1 cos(φ)) 2 +k 2 ( 1+2cos(Φ) cos 2 (Φ))+1 = k 4 (1 cos(φ)) 2 k 2 (1 2cos(Φ)+cos 2 (Φ))+1 = k 4 (1 cos(φ)) 2 k 2 (1 cos(φ)) 2 +1 = (k 4 k 2 )(1 cos(φ)) (for stablty) stable f G 2 1 = (k 4 k 2 )(1 cos(φ)) 2 0 } {{ } 0 k 2 (k 2 1) 0 k 2 1 a 1 (c) Mac-Cormack scheme Step 1 Step 2 ũ = u n a (un u n 1) wth follows = 1 2 (un +ũ ) 1 2 a (ũ +1 ũ ) ũ = u a ( u 2 2 u u ) ũ +1 = u+ u u u a ( u u u ) = 1 2 u+u a ( u 2 2 u u ) 1 2 a u+ u u u a ( u u u ) 1 2 a (u a ( u 2 2 u u )) = 1 2u a 2 ( u 2 2 u u ) a u u 2 2 u 3 6 u +a ( u u u ) a u+a ( u u 3 6 u ) 9

7 wth = 1 2 2u a ( u 2 2 u u ) a u 2 2 u 3 6 u +a 2 u = u+ 1 2 a u u 3 6 u a u 2 2 u 3 6 u +a 2 u = u+ 1 2 a 2 u 2 3 u +a 6 2 u = u+u t u tt u ttt u+u t u tt u ttt = u+ 1 2 a and u tt = a 2 u follows u t a2 u u ttt = 1 2 a Truncaton error 2 u 2 3 u +a 6 2 u 2 u 2 3 u +a 6 2 u u t +a 2 2 u u ttt = au a 2 6 u +a 2 2 u Alternatve: nsert step 1 nto step 2: 2 2 u t +au = 2 6 u ttt a 2 6 u = O( 2, 2 ) = 1 2 (un +u n a (un u n 1)) 1 2 a (un +1 a (un +1 u n ) u n +a (un u n 1)) = 2u n a (un u n 1) a (un +1 a (un +1 u n ) u n +a (un u n 1)) = 2u n a (un u n 1 +u n +1 u n )+a 2 2 2(un +1 u n u n +u n 1) 2 2u n +a (un +1 u n 1) a 2 2 2(un 1 2u n +u n +1) u n +a un +1 un 1 2 a 2 un 1 2un +un Truncaton error and stablty equvalent to that of the La-Wendroff scheme. 10

8 4. u t +au Implct scheme wth backward deducton n tme, central dfferences n space: wth u n +a un+1 +1 un u n = t un+1 tt +... ±1 = ± un+1 ± 3 6 un Consstency: lm L(u) L (u) = lm τ(u), 0, 0 L (u) = un+1 + t ( = t 2 un+1 tt +a L(u) = t +a Stablty: lm τ(u) = lm, un+1 tt, un+1 +a 2 un+1 ) 2 un+1 tt 2 6 un un+1 2 +O( 3, 2 ) +O( 3, 3 ) +O( 3, 2 ) scheme s consstent u n +a un+1 +1 un von Neumann analyss e IΦ n e IΦ +a e IΦ(+1) e IΦ( 1) 2 = 1 n = n +a 2IsnΦ 2 = 1 n +a (e IΦ e IΦ ) 2 n+1 +a snφi n 1 G = = 1+a snφi ( 1 G 2 = 1+ a ) 2 sn 2 Φ G 2 1 = ( 1+ a ) 2 1 stable sn 2 Φ } {{ } 0 11

9 La s theorem: consstency + stablty convergence The trdagonal equaton system, wth the unknownu a u 1 +b u +c u +1 = R = 2,...,m 1 has the followng form a 2 b 2 c 2 a 3 b 3 c u 1 u 2. = R 2 R 3. a m 1 b m 1 c m 1 u m R m 1 (m 2) equatons wth m unknown varables two boundary condtons have to be gven. Ths trdagonal system of equatons can be solved wth the followng recursve soluton approach (Thomas algorthm): wth E = u = E u +1 +F c a E 1 +b and F = R a F 1 a E 1 +b The ntal values fore 1 andf 1 follow from e.g. a Neumann boundary condton foruat = 1 u 1 = r 1 u 2 +s 1 = E 1 u 2 +F 1 E 1 = r 1 F 1 = s 1 After all coeffcentse,f are computed, the soluton foru s obtaned by back substtuton: u = E u +1 +F 12

8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by

8.5 UNITARY AND HERMITIAN MATRICES. The conjugate transpose of a complex matrix A, denoted by A*, is given by 6 CHAPTER 8 COMPLEX VECTOR SPACES 5. Fnd the kernel of the lnear transformaton gven n Exercse 5. In Exercses 55 and 56, fnd the mage of v, for the ndcated composton, where and are gven by the followng

More information

Consider a 1-D stationary state diffusion-type equation, which we will call the generalized diffusion equation from now on:

Consider a 1-D stationary state diffusion-type equation, which we will call the generalized diffusion equation from now on: Chapter 1 Boundary value problems Numercal lnear algebra technques can be used for many physcal problems. In ths chapter we wll gve some examples of how these technques can be used to solve certan boundary

More information

Imperial College London

Imperial College London F. Fang 1, C.C. Pan 1, I.M. Navon 2, M.D. Pggott 1, G.J. Gorman 1, P.A. Allson 1 and A.J.H. Goddard 1 1 Appled Modellng and Computaton Group Department of Earth Scence and Engneerng Imperal College London,

More information

1 Example 1: Axis-aligned rectangles

1 Example 1: Axis-aligned rectangles COS 511: Theoretcal Machne Learnng Lecturer: Rob Schapre Lecture # 6 Scrbe: Aaron Schld February 21, 2013 Last class, we dscussed an analogue for Occam s Razor for nfnte hypothess spaces that, n conjuncton

More information

Damage detection in composite laminates using coin-tap method

Damage detection in composite laminates using coin-tap method Damage detecton n composte lamnates usng con-tap method S.J. Km Korea Aerospace Research Insttute, 45 Eoeun-Dong, Youseong-Gu, 35-333 Daejeon, Republc of Korea yaeln@kar.re.kr 45 The con-tap test has the

More information

Analysis of Reactivity Induced Accident for Control Rods Ejection with Loss of Cooling

Analysis of Reactivity Induced Accident for Control Rods Ejection with Loss of Cooling Analyss of Reactvty Induced Accdent for Control Rods Ejecton wth Loss of Coolng Hend Mohammed El Sayed Saad 1, Hesham Mohammed Mohammed Mansour 2 Wahab 1 1. Nuclear and Radologcal Regulatory Authorty,

More information

Linear Circuits Analysis. Superposition, Thevenin /Norton Equivalent circuits

Linear Circuits Analysis. Superposition, Thevenin /Norton Equivalent circuits Lnear Crcuts Analyss. Superposton, Theenn /Norton Equalent crcuts So far we hae explored tmendependent (resste) elements that are also lnear. A tmendependent elements s one for whch we can plot an / cure.

More information

Immersed interface methods for moving interface problems

Immersed interface methods for moving interface problems Numercal Algorthms 14 (1997) 69 93 69 Immersed nterface methods for movng nterface problems Zhln L Department of Mathematcs, Unversty of Calforna at Los Angeles, Los Angeles, CA 90095, USA E-mal: zhln@math.ucla.edu

More information

Support Vector Machines

Support Vector Machines Support Vector Machnes Max Wellng Department of Computer Scence Unversty of Toronto 10 Kng s College Road Toronto, M5S 3G5 Canada wellng@cs.toronto.edu Abstract Ths s a note to explan support vector machnes.

More information

Description of the Force Method Procedure. Indeterminate Analysis Force Method 1. Force Method con t. Force Method con t

Description of the Force Method Procedure. Indeterminate Analysis Force Method 1. Force Method con t. Force Method con t Indeternate Analyss Force Method The force (flexblty) ethod expresses the relatonshps between dsplaceents and forces that exst n a structure. Prary objectve of the force ethod s to deterne the chosen set

More information

1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP)

1. Fundamentals of probability theory 2. Emergence of communication traffic 3. Stochastic & Markovian Processes (SP & MP) 6.3 / -- Communcaton Networks II (Görg) SS20 -- www.comnets.un-bremen.de Communcaton Networks II Contents. Fundamentals of probablty theory 2. Emergence of communcaton traffc 3. Stochastc & Markovan Processes

More information

An Overview of Computational Fluid Dynamics

An Overview of Computational Fluid Dynamics An Overvew of Computatonal Flud Dynamcs Joel Ducoste Assocate Professor Department of Cvl, Constructon, and Envronmental Engneerng MBR Tranng Semnar Ghent Unversty July 15 17, 2008 Outlne CFD? What s that?

More information

Actuator forces in CFD: RANS and LES modeling in OpenFOAM

Actuator forces in CFD: RANS and LES modeling in OpenFOAM Home Search Collectons Journals About Contact us My IOPscence Actuator forces n CFD: RANS and LES modelng n OpenFOAM Ths content has been downloaded from IOPscence. Please scroll down to see the full text.

More information

RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo.

RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL. Yaoqi FENG 1, Hanping QIU 1. China Academy of Space Technology (CAST) yaoqi.feng@yahoo. ICSV4 Carns Australa 9- July, 007 RESEARCH ON DUAL-SHAKER SINE VIBRATION CONTROL Yaoq FENG, Hanpng QIU Dynamc Test Laboratory, BISEE Chna Academy of Space Technology (CAST) yaoq.feng@yahoo.com Abstract

More information

POLYSA: A Polynomial Algorithm for Non-binary Constraint Satisfaction Problems with and

POLYSA: A Polynomial Algorithm for Non-binary Constraint Satisfaction Problems with and POLYSA: A Polynomal Algorthm for Non-bnary Constrant Satsfacton Problems wth and Mguel A. Saldo, Federco Barber Dpto. Sstemas Informátcos y Computacón Unversdad Poltécnca de Valenca, Camno de Vera s/n

More information

Finite difference method

Finite difference method grd ponts x = mesh sze = X NÜÆ Fnte dfference method Prncple: dervatves n the partal dfferental eqaton are approxmated by lnear combnatons of fncton vales at the grd ponts 1D: Ω = (0, X), (x ), = 0,1,...,

More information

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12

PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 12 14 The Ch-squared dstrbuton PSYCHOLOGICAL RESEARCH (PYC 304-C) Lecture 1 If a normal varable X, havng mean µ and varance σ, s standardsed, the new varable Z has a mean 0 and varance 1. When ths standardsed

More information

Recurrence. 1 Definitions and main statements

Recurrence. 1 Definitions and main statements Recurrence 1 Defntons and man statements Let X n, n = 0, 1, 2,... be a MC wth the state space S = (1, 2,...), transton probabltes p j = P {X n+1 = j X n = }, and the transton matrx P = (p j ),j S def.

More information

Extending Probabilistic Dynamic Epistemic Logic

Extending Probabilistic Dynamic Epistemic Logic Extendng Probablstc Dynamc Epstemc Logc Joshua Sack May 29, 2008 Probablty Space Defnton A probablty space s a tuple (S, A, µ), where 1 S s a set called the sample space. 2 A P(S) s a σ-algebra: a set

More information

Modern Problem Solving Techniques in Engineering with POLYMATH, Excel and MATLAB. Introduction

Modern Problem Solving Techniques in Engineering with POLYMATH, Excel and MATLAB. Introduction Modern Problem Solvng Tehnques n Engneerng wth POLYMATH, Exel and MATLAB. Introduton Engneers are fundamentally problem solvers, seekng to aheve some objetve or desgn among tehnal, soal eonom, regulatory

More information

PERRON FROBENIUS THEOREM

PERRON FROBENIUS THEOREM PERRON FROBENIUS THEOREM R. CLARK ROBINSON Defnton. A n n matrx M wth real entres m, s called a stochastc matrx provded () all the entres m satsfy 0 m, () each of the columns sum to one, m = for all, ()

More information

Simulating injection moulding of microfeatured components

Simulating injection moulding of microfeatured components Smulatng njecton mouldng of mcrofeatured components T. Tofteberg 1 * and E. Andreassen 1 1 SINTEF Materals and Chemstry, Oslo, Norway terje.tofteberg@sntef.no; erk.andreassen@sntef.no Numercal smulaton

More information

v a 1 b 1 i, a 2 b 2 i,..., a n b n i.

v a 1 b 1 i, a 2 b 2 i,..., a n b n i. SECTION 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS 455 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS All the vector spaces we have studed thus far n the text are real vector spaces snce the scalars are

More information

Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College

Feature selection for intrusion detection. Slobodan Petrović NISlab, Gjøvik University College Feature selecton for ntruson detecton Slobodan Petrovć NISlab, Gjøvk Unversty College Contents The feature selecton problem Intruson detecton Traffc features relevant for IDS The CFS measure The mrmr measure

More information

+ + + - - This circuit than can be reduced to a planar circuit

+ + + - - This circuit than can be reduced to a planar circuit MeshCurrent Method The meshcurrent s analog of the nodeoltage method. We sole for a new set of arables, mesh currents, that automatcally satsfy KCLs. As such, meshcurrent method reduces crcut soluton to

More information

Time Domain simulation of PD Propagation in XLPE Cables Considering Frequency Dependent Parameters

Time Domain simulation of PD Propagation in XLPE Cables Considering Frequency Dependent Parameters Internatonal Journal of Smart Grd and Clean Energy Tme Doman smulaton of PD Propagaton n XLPE Cables Consderng Frequency Dependent Parameters We Zhang a, Jan He b, Ln Tan b, Xuejun Lv b, Hong-Je L a *

More information

Ring structure of splines on triangulations

Ring structure of splines on triangulations www.oeaw.ac.at Rng structure of splnes on trangulatons N. Vllamzar RICAM-Report 2014-48 www.rcam.oeaw.ac.at RING STRUCTURE OF SPLINES ON TRIANGULATIONS NELLY VILLAMIZAR Introducton For a trangulated regon

More information

Method for Production Planning and Inventory Control in Oil

Method for Production Planning and Inventory Control in Oil Memors of the Faculty of Engneerng, Okayama Unversty, Vol.41, pp.20-30, January, 2007 Method for Producton Plannng and Inventory Control n Ol Refnery TakujImamura,MasamKonshandJunIma Dvson of Electronc

More information

A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm

A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):1884-1889 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel

More information

A Three-Point Combined Compact Difference Scheme

A Three-Point Combined Compact Difference Scheme JOURNAL OF COMPUTATIONAL PHYSICS 140, 370 399 (1998) ARTICLE NO. CP985899 A Three-Pont Combned Compact Derence Scheme Peter C. Chu and Chenwu Fan Department o Oceanography, Naval Postgraduate School, Monterey,

More information

Quantization Effects in Digital Filters

Quantization Effects in Digital Filters Quantzaton Effects n Dgtal Flters Dstrbuton of Truncaton Errors In two's complement representaton an exact number would have nfntely many bts (n general). When we lmt the number of bts to some fnte value

More information

Faraday's Law of Induction

Faraday's Law of Induction Introducton Faraday's Law o Inducton In ths lab, you wll study Faraday's Law o nducton usng a wand wth col whch swngs through a magnetc eld. You wll also examne converson o mechanc energy nto electrc energy

More information

Modelling of Hot Water Flooding

Modelling of Hot Water Flooding Unversty of Readng Modellng of Hot Water Floodng as an Enhanced Ol Recovery Method by Zenab Zargar August 013 Department of Mathematcs Submtted to the Department of Mathematcs, Unversty of Readng, n Partal

More information

The Noether Theorems: from Noether to Ševera

The Noether Theorems: from Noether to Ševera 14th Internatonal Summer School n Global Analyss and Mathematcal Physcs Satellte Meetng of the XVI Internatonal Congress on Mathematcal Physcs *** Lectures of Yvette Kosmann-Schwarzbach Centre de Mathématques

More information

Numerical Analysis on Rapid Decompression in Conventional Dry Gases using One- Dimensional Mathematical Modeling

Numerical Analysis on Rapid Decompression in Conventional Dry Gases using One- Dimensional Mathematical Modeling World Academy of Scence, Engneerng and Technology Internatonal Journal of Mathematcal, Computatonal, Physcal, Electrcal and Computer Engneerng Vol:6, o:3, 01 umercal Analyss on Rapd Decompresson n Conventonal

More information

GRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 -NORM

GRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 -NORM GRAVITY DATA VALIDATION AND OUTLIER DETECTION USING L 1 -NORM BARRIOT Jean-Perre, SARRAILH Mchel BGI/CNES 18.av.E.Beln 31401 TOULOUSE Cedex 4 (France) Emal: jean-perre.barrot@cnes.fr 1/Introducton The

More information

Analysis of Lattice Boltzmann Boundary Conditions

Analysis of Lattice Boltzmann Boundary Conditions Analyss of Lattce Boltzmann Boundary Condtons Dssertaton zur Erlangung des akademschen Grades des Doktors der Naturwssenschaften (Dr. rer. nat.) an der Unverstät Konstanz Mathematsch-Naturwssenschaftlche

More information

A high-order compact method for nonlinear Black-Scholes option pricing equations of American Options

A high-order compact method for nonlinear Black-Scholes option pricing equations of American Options Bergsche Unverstät Wuppertal Fachberech Mathematk und Naturwssenschaften Lehrstuhl für Angewandte Mathematk und Numersche Mathematk Lehrstuhl für Optmerung und Approxmaton Preprnt BUW-AMNA-OPAP 10/13 II

More information

Application of Quasi Monte Carlo methods and Global Sensitivity Analysis in finance

Application of Quasi Monte Carlo methods and Global Sensitivity Analysis in finance Applcaton of Quas Monte Carlo methods and Global Senstvty Analyss n fnance Serge Kucherenko, Nlay Shah Imperal College London, UK skucherenko@mperalacuk Daro Czraky Barclays Captal DaroCzraky@barclayscaptalcom

More information

Comparison of Control Strategies for Shunt Active Power Filter under Different Load Conditions

Comparison of Control Strategies for Shunt Active Power Filter under Different Load Conditions Comparson of Control Strateges for Shunt Actve Power Flter under Dfferent Load Condtons Sanjay C. Patel 1, Tushar A. Patel 2 Lecturer, Electrcal Department, Government Polytechnc, alsad, Gujarat, Inda

More information

TENSOR GAUGE FIELDS OF DEGREE THREE

TENSOR GAUGE FIELDS OF DEGREE THREE TENSOR GAUGE FIELDS OF DEGREE THREE E.M. CIOROIANU Department of Physcs, Unversty of Craova, A. I. Cuza 13, 2585, Craova, Romana, EU E-mal: manache@central.ucv.ro Receved February 2, 213 Startng from a

More information

Generalizing the degree sequence problem

Generalizing the degree sequence problem Mddlebury College March 2009 Arzona State Unversty Dscrete Mathematcs Semnar The degree sequence problem Problem: Gven an nteger sequence d = (d 1,...,d n ) determne f there exsts a graph G wth d as ts

More information

Research of concurrency control protocol based on the main memory database

Research of concurrency control protocol based on the main memory database Research of concurrency control protocol based on the man memory database Abstract Yonghua Zhang * Shjazhuang Unversty of economcs, Shjazhuang, Shjazhuang, Chna Receved 1 October 2014, www.cmnt.lv The

More information

Basic Equations of Fluid Dynamics

Basic Equations of Fluid Dynamics Basc Equatons of Flud Dynamcs Sergey Pankratov A lecture to the Practcal Course Scentfc Computng and Vsualzaton (June 17, 2004) Sergey Pankratov, TU München 1 Focus areas Euler and Lagrange descrptons

More information

Production. 2. Y is closed A set is closed if it contains its boundary. We need this for the solution existence in the profit maximization problem.

Production. 2. Y is closed A set is closed if it contains its boundary. We need this for the solution existence in the profit maximization problem. Producer Theory Producton ASSUMPTION 2.1 Propertes of the Producton Set The producton set Y satsfes the followng propertes 1. Y s non-empty If Y s empty, we have nothng to talk about 2. Y s closed A set

More information

CHAPTER-II WATER-FLOODING. Calculating Oil Recovery Resulting from Displ. by an Immiscible Fluid:

CHAPTER-II WATER-FLOODING. Calculating Oil Recovery Resulting from Displ. by an Immiscible Fluid: CHAPTER-II WATER-FLOODING Interfacal Tenson: Energy requred ncreasng te area of te nterface by one unt. Te metods of measurng IFT s nclude a rng tensometer, pendant drop and spnnng drop tecnques. IFT s

More information

Lecture 2 Sequence Alignment. Burr Settles IBS Summer Research Program 2008 bsettles@cs.wisc.edu www.cs.wisc.edu/~bsettles/ibs08/

Lecture 2 Sequence Alignment. Burr Settles IBS Summer Research Program 2008 bsettles@cs.wisc.edu www.cs.wisc.edu/~bsettles/ibs08/ Lecture 2 Sequence lgnment Burr Settles IBS Summer Research Program 2008 bsettles@cs.wsc.edu www.cs.wsc.edu/~bsettles/bs08/ Sequence lgnment: Task Defnton gven: a par of sequences DN or proten) a method

More information

Introduction to Differential Algebraic Equations

Introduction to Differential Algebraic Equations Dr. Abebe Geletu Ilmenau Unversty of Technology Department of Smulaton and Optmal Processes (SOP) Wnter Semester 2011/12 4.1 Defnton and Propertes of DAEs A system of equatons that s of the form F (t,

More information

NUMERICAL INVESTIGATION OF AIR FLOW INSIDE AN OFFICE ROOM UNDER VARIOUS VENTILATION CONDITIONS

NUMERICAL INVESTIGATION OF AIR FLOW INSIDE AN OFFICE ROOM UNDER VARIOUS VENTILATION CONDITIONS PAMUKKALE ÜNİ VERSİ TESİ MÜHENDİ SLİ K FAKÜLTESİ PAMUKKALE UNIVERSITY ENGINEERING COLLEGE MÜHENDİ SLİ K B İ L İ MLERİ DERGİ S İ JOURNAL OF ENGINEERING SCIENCES YIL CİLT SAYI SAYFA : : 12 : 1 : 87-95 NUMERICAL

More information

Rate Monotonic (RM) Disadvantages of cyclic. TDDB47 Real Time Systems. Lecture 2: RM & EDF. Priority-based scheduling. States of a process

Rate Monotonic (RM) Disadvantages of cyclic. TDDB47 Real Time Systems. Lecture 2: RM & EDF. Priority-based scheduling. States of a process Dsadvantages of cyclc TDDB47 Real Tme Systems Manual scheduler constructon Cannot deal wth any runtme changes What happens f we add a task to the set? Real-Tme Systems Laboratory Department of Computer

More information

A DATA MINING APPLICATION IN A STUDENT DATABASE

A DATA MINING APPLICATION IN A STUDENT DATABASE JOURNAL OF AERONAUTICS AND SPACE TECHNOLOGIES JULY 005 VOLUME NUMBER (53-57) A DATA MINING APPLICATION IN A STUDENT DATABASE Şenol Zafer ERDOĞAN Maltepe Ünversty Faculty of Engneerng Büyükbakkalköy-Istanbul

More information

Interlude: Interphase Mass Transfer

Interlude: Interphase Mass Transfer Interlude: Interphase Mass Transfer The transport of mass wthn a sngle phase depends drectly on the concentraton gradent of the transportng speces n that phase. Mass may also transport from one phase to

More information

Sharp-Crested Weir Discharge Coefficient

Sharp-Crested Weir Discharge Coefficient 2011, Scencelne Publcaton Journal of Cvl Engneerng and Urbansm Volume 3, Issue 3: 87-91 (2013) (Receved: December 13, 2012; Accepted: May 7, 2013; Publshed: May 30, 2013) ISSN-2252-0430 Sharp-Crested Wer

More information

Numerical Methods 數 值 方 法 概 說. Daniel Lee. Nov. 1, 2006

Numerical Methods 數 值 方 法 概 說. Daniel Lee. Nov. 1, 2006 Numercal Methods 數 值 方 法 概 說 Danel Lee Nov. 1, 2006 Outlnes Lnear system : drect, teratve Nonlnear system : Newton-lke Interpolatons : polys, splnes, trg polys Approxmatons (I) : orthogonal polys Approxmatons

More information

FINANCIAL MATHEMATICS. A Practical Guide for Actuaries. and other Business Professionals

FINANCIAL MATHEMATICS. A Practical Guide for Actuaries. and other Business Professionals FINANCIAL MATHEMATICS A Practcal Gude for Actuares and other Busness Professonals Second Edton CHRIS RUCKMAN, FSA, MAAA JOE FRANCIS, FSA, MAAA, CFA Study Notes Prepared by Kevn Shand, FSA, FCIA Assstant

More information

Exhaustive Regression. An Exploration of Regression-Based Data Mining Techniques Using Super Computation

Exhaustive Regression. An Exploration of Regression-Based Data Mining Techniques Using Super Computation Exhaustve Regresson An Exploraton of Regresson-Based Data Mnng Technques Usng Super Computaton Antony Daves, Ph.D. Assocate Professor of Economcs Duquesne Unversty Pttsburgh, PA 58 Research Fellow The

More information

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting

Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting Causal, Explanatory Forecastng Assumes cause-and-effect relatonshp between system nputs and ts output Forecastng wth Regresson Analyss Rchard S. Barr Inputs System Cause + Effect Relatonshp The job of

More information

An MILP model for planning of batch plants operating in a campaign-mode

An MILP model for planning of batch plants operating in a campaign-mode An MILP model for plannng of batch plants operatng n a campagn-mode Yanna Fumero Insttuto de Desarrollo y Dseño CONICET UTN yfumero@santafe-concet.gov.ar Gabrela Corsano Insttuto de Desarrollo y Dseño

More information

BERNSTEIN POLYNOMIALS

BERNSTEIN POLYNOMIALS On-Lne Geometrc Modelng Notes BERNSTEIN POLYNOMIALS Kenneth I. Joy Vsualzaton and Graphcs Research Group Department of Computer Scence Unversty of Calforna, Davs Overvew Polynomals are ncredbly useful

More information

Can Auto Liability Insurance Purchases Signal Risk Attitude?

Can Auto Liability Insurance Purchases Signal Risk Attitude? Internatonal Journal of Busness and Economcs, 2011, Vol. 10, No. 2, 159-164 Can Auto Lablty Insurance Purchases Sgnal Rsk Atttude? Chu-Shu L Department of Internatonal Busness, Asa Unversty, Tawan Sheng-Chang

More information

Finite Math Chapter 10: Study Guide and Solution to Problems

Finite Math Chapter 10: Study Guide and Solution to Problems Fnte Math Chapter 10: Study Gude and Soluton to Problems Basc Formulas and Concepts 10.1 Interest Basc Concepts Interest A fee a bank pays you for money you depost nto a savngs account. Prncpal P The amount

More information

LECTURES on COMPUTATIONAL NUMERICAL ANALYSIS of PARTIAL DIFFERENTIAL EQUATIONS

LECTURES on COMPUTATIONAL NUMERICAL ANALYSIS of PARTIAL DIFFERENTIAL EQUATIONS LECTURES on COMPUTATIONAL NUMERICAL ANALYSIS of PARTIAL DIFFERENTIAL EQUATIONS J. M. McDonough Departments of Mechancal Engneerng and Mathematcs Unversty of Kentucky c 1985, 00, 008 Contents 1 Introducton

More information

Portfolio Loss Distribution

Portfolio Loss Distribution Portfolo Loss Dstrbuton Rsky assets n loan ortfolo hghly llqud assets hold-to-maturty n the bank s balance sheet Outstandngs The orton of the bank asset that has already been extended to borrowers. Commtment

More information

HowHow to Find the Best Online Stock Broker

HowHow to Find the Best Online Stock Broker A GENERAL APPROACH FOR SECURITY MONITORING AND PREVENTIVE CONTROL OF NETWORKS WITH LARGE WIND POWER PRODUCTION Helena Vasconcelos INESC Porto hvasconcelos@nescportopt J N Fdalgo INESC Porto and FEUP jfdalgo@nescportopt

More information

IMPACT ANALYSIS OF A CELLULAR PHONE

IMPACT ANALYSIS OF A CELLULAR PHONE 4 th ASA & μeta Internatonal Conference IMPACT AALYSIS OF A CELLULAR PHOE We Lu, 2 Hongy L Bejng FEAonlne Engneerng Co.,Ltd. Bejng, Chna ABSTRACT Drop test smulaton plays an mportant role n nvestgatng

More information

s-domain Circuit Analysis

s-domain Circuit Analysis S-Doman naly -Doman rcut naly Tme doman t doman near rcut aplace Tranform omplex frequency doman doman Tranformed rcut Dfferental equaton lacal technque epone waveform aplace Tranform nvere Tranform -

More information

Period and Deadline Selection for Schedulability in Real-Time Systems

Period and Deadline Selection for Schedulability in Real-Time Systems Perod and Deadlne Selecton for Schedulablty n Real-Tme Systems Thdapat Chantem, Xaofeng Wang, M.D. Lemmon, and X. Sharon Hu Department of Computer Scence and Engneerng, Department of Electrcal Engneerng

More information

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..

More information

Energies of Network Nastsemble

Energies of Network Nastsemble Supplementary materal: Assessng the relevance of node features for network structure Gnestra Bancon, 1 Paolo Pn,, 3 and Matteo Marsl 1 1 The Abdus Salam Internatonal Center for Theoretcal Physcs, Strada

More information

Brigid Mullany, Ph.D University of North Carolina, Charlotte

Brigid Mullany, Ph.D University of North Carolina, Charlotte Evaluaton And Comparson Of The Dfferent Standards Used To Defne The Postonal Accuracy And Repeatablty Of Numercally Controlled Machnng Center Axes Brgd Mullany, Ph.D Unversty of North Carolna, Charlotte

More information

The circuit shown on Figure 1 is called the common emitter amplifier circuit. The important subsystems of this circuit are:

The circuit shown on Figure 1 is called the common emitter amplifier circuit. The important subsystems of this circuit are: polar Juncton Transstor rcuts Voltage and Power Amplfer rcuts ommon mtter Amplfer The crcut shown on Fgure 1 s called the common emtter amplfer crcut. The mportant subsystems of ths crcut are: 1. The basng

More information

THE METHOD OF LEAST SQUARES THE METHOD OF LEAST SQUARES

THE METHOD OF LEAST SQUARES THE METHOD OF LEAST SQUARES The goal: to measure (determne) an unknown quantty x (the value of a RV X) Realsaton: n results: y 1, y 2,..., y j,..., y n, (the measured values of Y 1, Y 2,..., Y j,..., Y n ) every result s encumbered

More information

L10: Linear discriminants analysis

L10: Linear discriminants analysis L0: Lnear dscrmnants analyss Lnear dscrmnant analyss, two classes Lnear dscrmnant analyss, C classes LDA vs. PCA Lmtatons of LDA Varants of LDA Other dmensonalty reducton methods CSCE 666 Pattern Analyss

More information

Least Squares Fitting of Data

Least Squares Fitting of Data Least Squares Fttng of Data Davd Eberly Geoetrc Tools, LLC http://www.geoetrctools.co/ Copyrght c 1998-2016. All Rghts Reserved. Created: July 15, 1999 Last Modfed: January 5, 2015 Contents 1 Lnear Fttng

More information

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).

benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ). REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or

More information

Global stability of Cohen-Grossberg neural network with both time-varying and continuous distributed delays

Global stability of Cohen-Grossberg neural network with both time-varying and continuous distributed delays Global stablty of Cohen-Grossberg neural network wth both tme-varyng and contnuous dstrbuted delays José J. Olvera Departamento de Matemátca e Aplcações and CMAT, Escola de Cêncas, Unversdade do Mnho,

More information

Mathematical modeling of water quality in river systems. Case study: Jajrood river in Tehran - Iran

Mathematical modeling of water quality in river systems. Case study: Jajrood river in Tehran - Iran European Water 7/8: 3-, 009. 009 E.W. Publcatons Mathematcal modelng of water qualty n rver systems. Case study: Jajrood rver n Tehran - Iran S.A. Mrbagher, M. Abaspour and K.H. Zaman 3 Department of Cvl

More information

CFD MODELLING BY DHI. Statement of Qualifications

CFD MODELLING BY DHI. Statement of Qualifications Statement of Qualfcatons CFD Modellng by DHI/hkh/hec-ybr/pot/ShortDescrptons 08/10 CFD Modellng by DHI The capablty of understandng and nvestgatng the motons of lquds and gasses n detal s of great mportance

More information

Applied Research Laboratory. Decision Theory and Receiver Design

Applied Research Laboratory. Decision Theory and Receiver Design Decson Theor and Recever Desgn Sgnal Detecton and Performance Estmaton Sgnal Processor Decde Sgnal s resent or Sgnal s not resent Nose Nose Sgnal? Problem: How should receved sgnals be rocessed n order

More information

Multiple stage amplifiers

Multiple stage amplifiers Multple stage amplfers Ams: Examne a few common 2-transstor amplfers: -- Dfferental amplfers -- Cascode amplfers -- Darlngton pars -- current mrrors Introduce formal methods for exactly analysng multple

More information

An Integrated Semantically Correct 2.5D Object Oriented TIN. Andreas Koch

An Integrated Semantically Correct 2.5D Object Oriented TIN. Andreas Koch An Integrated Semantcally Correct 2.5D Object Orented TIN Andreas Koch Unverstät Hannover Insttut für Photogrammetre und GeoInformaton Contents Introducton Integraton of a DTM and 2D GIS data Semantcs

More information

where the coordinates are related to those in the old frame as follows.

where the coordinates are related to those in the old frame as follows. Chapter 2 - Cartesan Vectors and Tensors: Ther Algebra Defnton of a vector Examples of vectors Scalar multplcaton Addton of vectors coplanar vectors Unt vectors A bass of non-coplanar vectors Scalar product

More information

Compiling for Parallelism & Locality. Dependence Testing in General. Algorithms for Solving the Dependence Problem. Dependence Testing

Compiling for Parallelism & Locality. Dependence Testing in General. Algorithms for Solving the Dependence Problem. Dependence Testing Complng for Parallelsm & Localty Dependence Testng n General Assgnments Deadlne for proect 4 extended to Dec 1 Last tme Data dependences and loops Today Fnsh data dependence analyss for loops General code

More information

Research Article Enhanced Two-Step Method via Relaxed Order of α-satisfactory Degrees for Fuzzy Multiobjective Optimization

Research Article Enhanced Two-Step Method via Relaxed Order of α-satisfactory Degrees for Fuzzy Multiobjective Optimization Hndaw Publshng Corporaton Mathematcal Problems n Engneerng Artcle ID 867836 pages http://dxdoorg/055/204/867836 Research Artcle Enhanced Two-Step Method va Relaxed Order of α-satsfactory Degrees for Fuzzy

More information

NPAR TESTS. One-Sample Chi-Square Test. Cell Specification. Observed Frequencies 1O i 6. Expected Frequencies 1EXP i 6

NPAR TESTS. One-Sample Chi-Square Test. Cell Specification. Observed Frequencies 1O i 6. Expected Frequencies 1EXP i 6 PAR TESTS If a WEIGHT varable s specfed, t s used to replcate a case as many tmes as ndcated by the weght value rounded to the nearest nteger. If the workspace requrements are exceeded and samplng has

More information

Computers and Mathematics with Applications. POD reduced-order unstructured mesh modeling applied to 2D and 3D fluid flow

Computers and Mathematics with Applications. POD reduced-order unstructured mesh modeling applied to 2D and 3D fluid flow Computers and Mathematcs wth Applcatons 65 (2013) 362 379 Contents lsts avalable at ScVerse ScenceDrect Computers and Mathematcs wth Applcatons journal homepage: www.elsever.com/locate/camwa POD reduced-order

More information

Depreciation of Business R&D Capital

Depreciation of Business R&D Capital Deprecaton of Busness R&D Captal U.S. Bureau of Economc Analyss Abstract R&D deprecaton rates are crtcal to calculatng the rates of return to R&D nvestments and captal servce costs, whch are mportant for

More information

On the Optimal Control of a Cascade of Hydro-Electric Power Stations

On the Optimal Control of a Cascade of Hydro-Electric Power Stations On the Optmal Control of a Cascade of Hydro-Electrc Power Statons M.C.M. Guedes a, A.F. Rbero a, G.V. Smrnov b and S. Vlela c a Department of Mathematcs, School of Scences, Unversty of Porto, Portugal;

More information

Implementation of Deutsch's Algorithm Using Mathcad

Implementation of Deutsch's Algorithm Using Mathcad Implementaton of Deutsch's Algorthm Usng Mathcad Frank Roux The followng s a Mathcad mplementaton of Davd Deutsch's quantum computer prototype as presented on pages - n "Machnes, Logc and Quantum Physcs"

More information

An Analysis of Pricing Methods for Baskets Options

An Analysis of Pricing Methods for Baskets Options An Analyss of Prcng Methods for Baskets Optons Martn Krekel, Johan de Kock, Ralf Korn, Tn-Kwa Man Fraunhofer ITWM, Department of Fnancal Mathematcs, 67653 Kaserslautern, Germany, emal: krekel@twm.fhg.de

More information

ESTIMATION OF RELAXATION AND THERMALIZATION TIMES IN MICROSCALE HEAT TRANSFER MODEL

ESTIMATION OF RELAXATION AND THERMALIZATION TIMES IN MICROSCALE HEAT TRANSFER MODEL JOURNAL OF THEORETICAL AND APPLIED MECHANICS 51, 4, pp. 837-845, Warsaw 2013 ESTIMATION OF RELAXATION AND THERMALIZATION TIMES IN MICROSCALE HEAT TRANSFER MODEL Bohdan Mochnack Częstochowa Unversty of

More information

Introduction. by a source term ( ) 242 / Vol. XXVIII, No. 2, April-June 2006 ABCM. Denise Maria V. Martinez et al

Introduction. by a source term ( ) 242 / Vol. XXVIII, No. 2, April-June 2006 ABCM. Denise Maria V. Martinez et al ρ ρ Dense Mara V. Martnez et al Dense Mara V. Martnez densevmartnez@yahoo.com.br Departamento de Matemátca Fundação Unversdade Federal do Ro Grande 9601-900 Ro Grande, RS, Brazl Edth Beatrz C. Schettn

More information

Sensor placement for leak detection and location in water distribution networks

Sensor placement for leak detection and location in water distribution networks Sensor placement for leak detecton and locaton n water dstrbuton networks ABSTRACT R. Sarrate*, J. Blesa, F. Near, J. Quevedo Automatc Control Department, Unverstat Poltècnca de Catalunya, Rambla de Sant

More information

Follow links for Class Use and other Permissions. For more information send email to: permissions@pupress.princeton.edu

Follow links for Class Use and other Permissions. For more information send email to: permissions@pupress.princeton.edu COPYRIGHT NOTICE: Jord Galí: Monetary Polcy, Inflaton, and the Busness Cycle s publshed by Prnceton Unversty Press and copyrghted, 28, by Prnceton Unversty Press. All rghts reserved. No part of ths book

More information

Form-finding of grid shells with continuous elastic rods

Form-finding of grid shells with continuous elastic rods Page of 0 Form-fndng of grd shells wth contnuous elastc rods Jan-Mn L PhD student Insttute of Buldng Structures and Structural Desgn (tke), Unversty Stuttgart Stuttgar, Germany quantumamn@gmal.com Jan

More information

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis

The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.

More information

Loop Parallelization

Loop Parallelization - - Loop Parallelzaton C-52 Complaton steps: nested loops operatng on arrays, sequentell executon of teraton space DECLARE B[..,..+] FOR I :=.. FOR J :=.. I B[I,J] := B[I-,J]+B[I-,J-] ED FOR ED FOR analyze

More information

The Proper Use of Risk Measures in Portfolio Theory

The Proper Use of Risk Measures in Portfolio Theory The Proper Use of Rsk Measures n Portfolo Theory Sergo Ortobell a, Svetlozar T. Rachev b, Stoyan Stoyanov c, Frank J. Fabozz d,* and Almra Bglova e a Unversty of Bergamo, Italy b Unversty of Calforna,

More information

Simulation of Under Water Explosion using MSC.Dytran

Simulation of Under Water Explosion using MSC.Dytran Smulaton of Under Water Exploson usng MSC.Dytran Peran Dng rjaan Bujk MSC.Software Corporaton 2300 Traverwood Drve nn rbor, MI 48105 (734) 994-3800 Ths paper descrbes the numercal smulaton of a cylnder

More information

An Analysis of Dynamic Severity and Population Size

An Analysis of Dynamic Severity and Population Size An Analyss of Dynamc Severty and Populaton Sze Karsten Wecker Unversty of Stuttgart, Insttute of Computer Scence, Bretwesenstr. 2 22, 7565 Stuttgart, Germany, emal: Karsten.Wecker@nformatk.un-stuttgart.de

More information