Optimal Mapped Mesh on the Circle
|
|
- Bethany Howard
- 5 years ago
- Views:
Transcription
1 Koferece ANSYS 009 Optimal Mapped Mesh o the Circle doc. Ig. Jaroslav Štigler, Ph.D. Bro Uiversity of Techology, aculty of Mechaical gieerig, ergy Istitut, Abstract: This paper brigs out some ideas ad recommedatios how to build mapped mesh o the circle with high quality mesh cells. Keywords: Mapped mesh, circle, 1. Itroductio Quality of mesh sigificatly iflueces the solutio precisio ad covergece rate i case of every umerical solutio of fluid flow. There are several types of mesh. The best results ca be obtaied with Mapped mesh. The cell s shape i this mesh type is close to the square i case of d mesh or to the cube i case of 3d mesh. Whe we are solvig a fluid flow i pipes with the rouded cross-sectio the basic questios arise i our mid: ow we ca make a mapped mesh o circle? Is it possible to fid a optimal solutio how to make mapped mesh o the circuit? Let us try to aswer these questios i the ext chapters.. Differet types of mapped meshes There are two basic ways of mapped mesh creatig. The easiest way is to divide the border of circuit ito four pieces. This is very easy ad quick way. Bat there is a problem with the mesh quality i this case. Quality of such mesh is so bad that the solutio does ot start. This type of mesh is depicted o the fig. 01 a. a) b) ig. 01 Differet types of mapped mesh o circuit.
2 TechSoft gieerig & SVS M The ext way is more difficult. Area of the circuit has to be divided ito some umber of sub-areas which shape is more sufficiet for the mapped meshig. The five sub-areas will be used i our case. The circle cosists of square area i the middle of the circle ad four areas aroud this square. This type of mapped mesh o circuit is depicted i the fig. 01b. The first type of mapped mesh is useless because of their quality. Therefore our attetio will be focused o the secod type of mapped mesh usig mapped sub-areas. Dividig of circuit ito mapped sub-areas ad their dimesios is depicted i the fig.. a) b) ig. 0 Dimesios of mapped sub-areas o circuit. 3. Optimal mapped mesh o a circle with rectagular ier square. Basic ideas of optimal mesh creatig o the circle with ier rectagular square are outlied i detail i a techical report [1]. If we wat divide the circle ito mapped sub-areas, tha the legth of edge has to be kow. Ifluece of size of the edge is clear from the pictures i fig 03. Whe the is small the mesh is very dese i the middle square of circuit ad very rough at the border of circle. This is depicted i fig 03a. I opposite situatio whe the dge is big the cells ear edge are very deformed. The first task is to fid optimal size of edge. a) b) ig. 03 Ifluece of size of square iside of the circuit o the mesh.
3 Koferece ANSYS 009 The square iside circle is the best area for mapped mesh. The problem lies i the four sub-areas roud the square. I case of square the opposite sides have the same legth. But this is ot true i case of other sub-areas of circle. Now the attetio will be focused o oe of the peripheral sub areas of the circle. This sub-area is depicted o the fig. 0b. Now it will be useful to express the legths of edges,, ad. All these leghts will deped o the radius R or o the legth of edge or o both of them. π = R., = R, = R, I the best mapped mesh of such area will be obtaied whet the ext ratios are equal 1. = 1 ad = 1 It is obvious that these coditios caot be accomplished. Both of these coditios are i cotrary o oe to other. irst coditio will be fulfilled i case =0. The secod coditio will be fulfilled i case =R. π/. But caot be bigger tha R.. If it happes the the ier squared area exceeds the circle. Both these coditios caot be satisfied together. It is possible to receive the compromise solutio that both coditios will be equal. = We ca add previous expressios ito this coditio ad we receive quadratic equatio for..r. π + + R. π = 0 This equatio has two solutios i form. 1, π = R ± 1+. π 1 +. π We ca express this solutio as Where = 1, R. a1, a 1 = 3,56854, = 0,9646 0, 96 a Correct solutio is α, because its value lays i a iterval of acceptable values a 0,. The basic geometry of sub-areas is determied. Now we eed to kow a umber of elemets o edges,, ad to be able to create mapped mesh o circle. Numbers of elemets o edges will be siged,,,. I case of mapped mesh the umbers of opposite edges have to be same. It is assumed that successive ratio is 1 for all edges. Tha the umbers of elemets will be determied
4 TechSoft gieerig & SVS M form coditio that legths of elemets are as equal as it is possible. Legths of edges elemets are siged L, L, L, L. These legths ca be calculated L =, L =, L =, L = It is impossible for all edge elemets to be equal. But we ca foud some limits of their legths. These limits are. L L L or L L L or I case of mapped mesh = ad =. Whe all above relatio are take ito cosideratio we receive. 1 a 1 a 1 a 1 1, or 1 a Now it is possible to write that = β. The value of coefficiet b is o the itersectio of above itervals. a β a Number of elemets lies betwee these limit values mi a 1 a 1 = βmi. = 1., max = βmax. =. The umber of elemets is chose ad umber of elemets ca be calculated from above terms. The best way is to take average value of β. We ca calculate for three differet values of a a example. A β mi β max mi max av 0,83 0,3745 0, , ,3957 0, ,0 0, , Tab. 01 Calculatig of for =0 ad for differet value of a. I the case of ratio a opt = 0, optimal value, this iterval of β is oly oe value. Whe the ratio a is bigger tha a opt the iterval for β is empty. Whe the ratio a is smaller tha a opt tha the itersectio iterval is ot empty. The best value is the average valule of β mi ad β max.
5 Koferece ANSYS 009 valuatio of meshes is listed i table 0. The mai criterio C AS ad C VS is costat for all type of these meshes with its value 0,5. So these meshes have to be sorted by differet criterio for example criterio C AR. Usig this criterio the best meshes are for av or close to it. Best mesh is mesh for a=0,964 ad =7 for =0 i a global view. Mesh valuatio of mesh quality by differet criteria. /R N C AR C DR C R C AS C VS C MAS C S 5 800,580 1,0,800 0,5 0,5 0,56 0, ,88 1,0,000 0,5 0,5 0,59 0,40 0, ,665 1,0 1,760 0,5 0,5 0,60 0, ,594 1,0 1,704 0,5 0,5 0,61 0, ,776 1,0 1,900 0,5 0,5 0,61 0, ,500 1,0,660 0,5 0,5 0,63 0, ,500 1,0,700 0,5 0,5 0,55 0,5 0, ,564 1,0 1,704 0,5 0,5 0,59 0, ,79 1,0 1,950 0,5 0,5 0,60 0, ,3 1,0,500 0,5 0,5 0,55 0,48 1, ,58 1,0 1,665 0,5 0,5 0,58 0, ,704 1,0 1,873 0,5 0,5 0,59 0, ,46 1,0,680 0,5 0,5 0,61 0,49 Tab.0. valuatio of mesh quality for =0 ad differet value of a C AR -Aspect Ratio C VS -quisize Skew C DR -Diagoal Ratio C MAS -MidAgle Skew C R -dge Ratio C S -Stretch C AS -quiagle Skew 4. Optimal mapped mesh o a circle with bet ier square. The quality of mesh ca be icreased by usig ot rectagular ier square. The edges will ot be straight but they will be bet with radius r. This type of sub-areas is depicted i fig 04. The expressio for the legth of edge has to be modified ad the expressio of legth J has to be added. J 4.K + 4.K 1 1 = R K =. b a.k.arctg K. = ( 4.b + 1) b.arctg 0,5 b = 4.b
6 TechSoft gieerig & SVS M a) b) Where ig. 04 Dimesios of mapped sub-areas o circuit with bouded ier sub-area. b =. R Now we will take value of the a opt =0, The we will try to fid the optimal ratio b. This optimum value will be searched o the iterval b <0, 1 >. or the case b=bmi =0 it is obtaied rectagular square ier area. I the case b=b max = ( 1) it is obtaied ier area as circuit. This optimum was foud by evaluatig of set meshes with costat ratio a ad with differet values of b o the iterval <b mi, b max >. Results are listed i table 3. The umber of elemets o edge ( ) is calculated similar way as i the case of straight edge oly the legth of edge J is take ito cosideratio istead of edge. The iterval for coefficiet β is β <β bmi, β bmax >. Where β a = 1 b. a b mi, β b max = π a 1 a.m Where ( 4.b + 1) b M =.arctg..b. π 0,5 b There are depedeces of β bmi ad β bmax o the ratio b i the fig. 05. Results of evaluatig of meshes created uder previous coditios are listed i the table 03.
7 Koferece ANSYS 009 Mesh valuatio of mesh quality by differet criteria. b av N C AR C DR C R C AS C VS C MAS C S 0, ,644,100 1,644 0,50 0,50 0,63 0,9 0, ,644 1,90 1,644 0,44 0,44 0,57 0,6 0, ,637 1,744 1,637 0,39 0,39 0,51 0,9 0, ,564 1,616 1,564 0,34 0,34 0,44 0,6 0, ,546 1,665 1,546 0,33 0,33 0,46 0,6 0, ,540 1,679 1,540 0,33 0,33 0,47 0,5 0, ,534 1,70 1,534 0,34 0,34 0,49 0,5 0, ,516 1,784 1,516 0,36 0,36 0,5 0,4 0, ,498 1,846 1,498 0,38 0,38 0,54 0,4 0, ,485 1,910 1,485 0,40 0,40 0,57 0,3 0, ,480,300 1,480 0,50 0,50 0,68 0,3 0, ,480,860 1,480 0,59 0,59 0,78 0,5 0, ,39 3,700 1,39 0,69 0,69 0,86 0,7 0, ,316 5,100 1,316 0,78 0,78 0,9 0,8 0, ,316 7,930 1,316 0,87 0,87 0,96 0,8 0, ,70 17,000 1,70 0,96 0,96 0,99 0,9 Tab.03. valuatio of mesh quality for =30 ad value of a=0, rom both table 03 ad fig. 05 is clear, that umber is decreasig with ratio b icreasig. This is true oly i case that ratio a is a costat. It is possible to fid two optimal values of ratio b. irst is for value b= 0,0613. I this case it is a optimum for two criterio C DR a C MAS. The secod optimum is for value b=0,0675 ad i this case it is optimum for criterio C AS. What optimum will be take ito cosideratio i practice it depeds what criterio we prefer. The depedeces of these three criterios are depicted o the fir 06. The optimum is a itersectio of two differet curves i all three cases. It is obvious, because oe of the curve represets quality of elemets i the outer sub-area ad the secod oe represets quality of elemets of the ier sub-area. I case of criterio C AS it seems to be a itersectio of two straight lies. Whe we icrease bedig of edges of ier square we are gettig worse the elemets quatily of ier sub-area ad gettig better elemets quality of outer sub-area. ig. 05 Coefficiets for settig i depedece o ratio b
8 TechSoft gieerig & SVS M 5. Refereces ig. 06 Coefficiets for settig i depedece o ratio b Štigler, J., 004. Jak vytvořit mapovaou síť a kruhu. Techická zpráva VUT-U QR-03-05, VUT SI v Brě, Bro, pp Appedix Author tried to fid some commo priciples, how to create a optimal mapped mesh o the circle i this paper. Curretly it was foud that best mesh ca be made for these values of ratio a=0,964619, ratio b=0,675, i case that we prefer criterio C AS (quiagle Skew), ad with value of coefficiet β which is a average of β bmi ad β bmax, which is importat for calculatig. These iformatios ca be useful for first desig of mapped mesh o the circle ad ca be useful for automatic mesh geeratio. 7. Ackowledgemet Author is grateful to rat Agecy of Czech Republic for fudig of this research withi scope of project with umber A 101/09/1539 with title Mathematical ad Numerical Modelig of low i Pipe Juctio ad its Compariso with xperimet.
Force Network Analysis using Complementary Energy
orce Network Aalysis usig Complemetary Eergy Adrew BORGART Assistat Professor Delft Uiversity of Techology Delft, The Netherlads A.Borgart@tudelft.l Yaick LIEM Studet Delft Uiversity of Techology Delft,
More informationOnes Assignment Method for Solving Traveling Salesman Problem
Joural of mathematics ad computer sciece 0 (0), 58-65 Oes Assigmet Method for Solvig Travelig Salesma Problem Hadi Basirzadeh Departmet of Mathematics, Shahid Chamra Uiversity, Ahvaz, Ira Article history:
More informationArea As A Limit & Sigma Notation
Area As A Limit & Sigma Notatio SUGGESTED REFERENCE MATERIAL: As you work through the problems listed below, you should referece Chapter 5.4 of the recommeded textbook (or the equivalet chapter i your
More informationThe isoperimetric problem on the hypercube
The isoperimetric problem o the hypercube Prepared by: Steve Butler November 2, 2005 1 The isoperimetric problem We will cosider the -dimesioal hypercube Q Recall that the hypercube Q is a graph whose
More informationCreating Exact Bezier Representations of CST Shapes. David D. Marshall. California Polytechnic State University, San Luis Obispo, CA , USA
Creatig Exact Bezier Represetatios of CST Shapes David D. Marshall Califoria Polytechic State Uiversity, Sa Luis Obispo, CA 93407-035, USA The paper presets a method of expressig CST shapes pioeered by
More informationLU Decomposition Method
SOLUTION OF SIMULTANEOUS LINEAR EQUATIONS LU Decompositio Method Jamie Traha, Autar Kaw, Kevi Marti Uiversity of South Florida Uited States of America kaw@eg.usf.edu http://umericalmethods.eg.usf.edu Itroductio
More informationChapter 3 Classification of FFT Processor Algorithms
Chapter Classificatio of FFT Processor Algorithms The computatioal complexity of the Discrete Fourier trasform (DFT) is very high. It requires () 2 complex multiplicatios ad () complex additios [5]. As
More informationAlpha Individual Solutions MAΘ National Convention 2013
Alpha Idividual Solutios MAΘ Natioal Covetio 0 Aswers:. D. A. C 4. D 5. C 6. B 7. A 8. C 9. D 0. B. B. A. D 4. C 5. A 6. C 7. B 8. A 9. A 0. C. E. B. D 4. C 5. A 6. D 7. B 8. C 9. D 0. B TB. 570 TB. 5
More informationPattern Recognition Systems Lab 1 Least Mean Squares
Patter Recogitio Systems Lab 1 Least Mea Squares 1. Objectives This laboratory work itroduces the OpeCV-based framework used throughout the course. I this assigmet a lie is fitted to a set of poits usig
More informationOctahedral Graph Scaling
Octahedral Graph Scalig Peter Russell Jauary 1, 2015 Abstract There is presetly o strog iterpretatio for the otio of -vertex graph scalig. This paper presets a ew defiitio for the term i the cotext of
More informationThe golden search method: Question 1
1. Golde Sectio Search for the Mode of a Fuctio The golde search method: Questio 1 Suppose the last pair of poits at which we have a fuctio evaluatio is x(), y(). The accordig to the method, If f(x())
More informationMorgan Kaufmann Publishers 26 February, COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Interface. Chapter 5
Morga Kaufma Publishers 26 February, 28 COMPUTER ORGANIZATION AND DESIGN The Hardware/Software Iterface 5 th Editio Chapter 5 Set-Associative Cache Architecture Performace Summary Whe CPU performace icreases:
More informationRecursive Procedures. How can you model the relationship between consecutive terms of a sequence?
6. Recursive Procedures I Sectio 6.1, you used fuctio otatio to write a explicit formula to determie the value of ay term i a Sometimes it is easier to calculate oe term i a sequece usig the previous terms.
More information3D Model Retrieval Method Based on Sample Prediction
20 Iteratioal Coferece o Computer Commuicatio ad Maagemet Proc.of CSIT vol.5 (20) (20) IACSIT Press, Sigapore 3D Model Retrieval Method Based o Sample Predictio Qigche Zhag, Ya Tag* School of Computer
More informationCh 9.3 Geometric Sequences and Series Lessons
Ch 9.3 Geometric Sequeces ad Series Lessos SKILLS OBJECTIVES Recogize a geometric sequece. Fid the geeral, th term of a geometric sequece. Evaluate a fiite geometric series. Evaluate a ifiite geometric
More informationLecture 28: Data Link Layer
Automatic Repeat Request (ARQ) 2. Go ack N ARQ Although the Stop ad Wait ARQ is very simple, you ca easily show that it has very the low efficiecy. The low efficiecy comes from the fact that the trasmittig
More information1.2 Binomial Coefficients and Subsets
1.2. BINOMIAL COEFFICIENTS AND SUBSETS 13 1.2 Biomial Coefficiets ad Subsets 1.2-1 The loop below is part of a program to determie the umber of triagles formed by poits i the plae. for i =1 to for j =
More information9 x and g(x) = 4. x. Find (x) 3.6. I. Combining Functions. A. From Equations. Example: Let f(x) = and its domain. Example: Let f(x) = and g(x) = x x 4
1 3.6 I. Combiig Fuctios A. From Equatios Example: Let f(x) = 9 x ad g(x) = 4 f x. Fid (x) g ad its domai. 4 Example: Let f(x) = ad g(x) = x x 4. Fid (f-g)(x) B. From Graphs: Graphical Additio. Example:
More informationcondition w i B i S maximum u i
ecture 10 Dyamic Programmig 10.1 Kapsack Problem November 1, 2004 ecturer: Kamal Jai Notes: Tobias Holgers We are give a set of items U = {a 1, a 2,..., a }. Each item has a weight w i Z + ad a utility
More informationAn Efficient Algorithm for Graph Bisection of Triangularizations
A Efficiet Algorithm for Graph Bisectio of Triagularizatios Gerold Jäger Departmet of Computer Sciece Washigto Uiversity Campus Box 1045 Oe Brookigs Drive St. Louis, Missouri 63130-4899, USA jaegerg@cse.wustl.edu
More informationBig-O Analysis. Asymptotics
Big-O Aalysis 1 Defiitio: Suppose that f() ad g() are oegative fuctios of. The we say that f() is O(g()) provided that there are costats C > 0 ad N > 0 such that for all > N, f() Cg(). Big-O expresses
More informationUniversity of Waterloo Department of Electrical and Computer Engineering ECE 250 Algorithms and Data Structures
Uiversity of Waterloo Departmet of Electrical ad Computer Egieerig ECE 250 Algorithms ad Data Structures Midterm Examiatio ( pages) Istructor: Douglas Harder February 7, 2004 7:30-9:00 Name (last, first)
More informationCSE 417: Algorithms and Computational Complexity
Time CSE 47: Algorithms ad Computatioal Readig assigmet Read Chapter of The ALGORITHM Desig Maual Aalysis & Sortig Autum 00 Paul Beame aalysis Problem size Worst-case complexity: max # steps algorithm
More informationThe Platonic solids The five regular polyhedra
The Platoic solids The five regular polyhedra Ole Witt-Hase jauary 7 www.olewitthase.dk Cotets. Polygos.... Topologically cosideratios.... Euler s polyhedro theorem.... Regular ets o a sphere.... The dihedral
More informationLower Bounds for Sorting
Liear Sortig Topics Covered: Lower Bouds for Sortig Coutig Sort Radix Sort Bucket Sort Lower Bouds for Sortig Compariso vs. o-compariso sortig Decisio tree model Worst case lower boud Compariso Sortig
More informationAn Efficient Algorithm for Graph Bisection of Triangularizations
Applied Mathematical Scieces, Vol. 1, 2007, o. 25, 1203-1215 A Efficiet Algorithm for Graph Bisectio of Triagularizatios Gerold Jäger Departmet of Computer Sciece Washigto Uiversity Campus Box 1045, Oe
More informationA Note on Least-norm Solution of Global WireWarping
A Note o Least-orm Solutio of Global WireWarpig Charlie C. L. Wag Departmet of Mechaical ad Automatio Egieerig The Chiese Uiversity of Hog Kog Shati, N.T., Hog Kog E-mail: cwag@mae.cuhk.edu.hk Abstract
More informationPolynomial Functions and Models. Learning Objectives. Polynomials. P (x) = a n x n + a n 1 x n a 1 x + a 0, a n 0
Polyomial Fuctios ad Models 1 Learig Objectives 1. Idetify polyomial fuctios ad their degree 2. Graph polyomial fuctios usig trasformatios 3. Idetify the real zeros of a polyomial fuctio ad their multiplicity
More informationSection 7.2: Direction Fields and Euler s Methods
Sectio 7.: Directio ields ad Euler s Methods Practice HW from Stewart Tetbook ot to had i p. 5 # -3 9-3 odd or a give differetial equatio we wat to look at was to fid its solutio. I this chapter we will
More informationCMPT 125 Assignment 2 Solutions
CMPT 25 Assigmet 2 Solutios Questio (20 marks total) a) Let s cosider a iteger array of size 0. (0 marks, each part is 2 marks) it a[0]; I. How would you assig a poiter, called pa, to store the address
More informationA New Morphological 3D Shape Decomposition: Grayscale Interframe Interpolation Method
A ew Morphological 3D Shape Decompositio: Grayscale Iterframe Iterpolatio Method D.. Vizireau Politehica Uiversity Bucharest, Romaia ae@comm.pub.ro R. M. Udrea Politehica Uiversity Bucharest, Romaia mihea@comm.pub.ro
More informationCS 683: Advanced Design and Analysis of Algorithms
CS 683: Advaced Desig ad Aalysis of Algorithms Lecture 6, February 1, 2008 Lecturer: Joh Hopcroft Scribes: Shaomei Wu, Etha Feldma February 7, 2008 1 Threshold for k CNF Satisfiability I the previous lecture,
More informationCSC 220: Computer Organization Unit 11 Basic Computer Organization and Design
College of Computer ad Iformatio Scieces Departmet of Computer Sciece CSC 220: Computer Orgaizatio Uit 11 Basic Computer Orgaizatio ad Desig 1 For the rest of the semester, we ll focus o computer architecture:
More informationArithmetic Sequences
. Arithmetic Sequeces COMMON CORE Learig Stadards HSF-IF.A. HSF-BF.A.1a HSF-BF.A. HSF-LE.A. Essetial Questio How ca you use a arithmetic sequece to describe a patter? A arithmetic sequece is a ordered
More informationCubic Polynomial Curves with a Shape Parameter
roceedigs of the th WSEAS Iteratioal Coferece o Robotics Cotrol ad Maufacturig Techology Hagzhou Chia April -8 00 (pp5-70) Cubic olyomial Curves with a Shape arameter MO GUOLIANG ZHAO YANAN Iformatio ad
More informationIntro to Scientific Computing: Solutions
Itro to Scietific Computig: Solutios Dr. David M. Goulet. How may steps does it take to separate 3 objects ito groups of 4? We start with 5 objects ad apply 3 steps of the algorithm to reduce the pile
More informationEVALUATION OF TRIGONOMETRIC FUNCTIONS
EVALUATION OF TRIGONOMETRIC FUNCTIONS Whe first exposed to trigoometric fuctios i high school studets are expected to memorize the values of the trigoometric fuctios of sie cosie taget for the special
More informationLecture 7 7 Refraction and Snell s Law Reading Assignment: Read Kipnis Chapter 4 Refraction of Light, Section III, IV
Lecture 7 7 Refractio ad Sell s Law Readig Assigmet: Read Kipis Chapter 4 Refractio of Light, Sectio III, IV 7. History I Eglish-speakig coutries, the law of refractio is kow as Sell s Law, after the Dutch
More information27 Refraction, Dispersion, Internal Reflection
Chapter 7 Refractio, Dispersio, Iteral Reflectio 7 Refractio, Dispersio, Iteral Reflectio Whe we talked about thi film iterferece, we said that whe light ecouters a smooth iterface betwee two trasparet
More informationModule 8-7: Pascal s Triangle and the Binomial Theorem
Module 8-7: Pascal s Triagle ad the Biomial Theorem Gregory V. Bard April 5, 017 A Note about Notatio Just to recall, all of the followig mea the same thig: ( 7 7C 4 C4 7 7C4 5 4 ad they are (all proouced
More informationHomework 1 Solutions MA 522 Fall 2017
Homework 1 Solutios MA 5 Fall 017 1. Cosider the searchig problem: Iput A sequece of umbers A = [a 1,..., a ] ad a value v. Output A idex i such that v = A[i] or the special value NIL if v does ot appear
More informationUNIT 4 Section 8 Estimating Population Parameters using Confidence Intervals
UNIT 4 Sectio 8 Estimatig Populatio Parameters usig Cofidece Itervals To make ifereces about a populatio that caot be surveyed etirely, sample statistics ca be take from a SRS of the populatio ad used
More informationNormal Distributions
Normal Distributios Stacey Hacock Look at these three differet data sets Each histogram is overlaid with a curve : A B C A) Weights (g) of ewly bor lab rat pups B) Mea aual temperatures ( F ) i A Arbor,
More informationLecture 5. Counting Sort / Radix Sort
Lecture 5. Coutig Sort / Radix Sort T. H. Corme, C. E. Leiserso ad R. L. Rivest Itroductio to Algorithms, 3rd Editio, MIT Press, 2009 Sugkyukwa Uiversity Hyuseug Choo choo@skku.edu Copyright 2000-2018
More information1 Graph Sparsfication
CME 305: Discrete Mathematics ad Algorithms 1 Graph Sparsficatio I this sectio we discuss the approximatio of a graph G(V, E) by a sparse graph H(V, F ) o the same vertex set. I particular, we cosider
More informationA Resource for Free-standing Mathematics Qualifications
Ope.ls The first sheet is show elow. It is set up to show graphs with equatios of the form = m + c At preset the values of m ad c are oth zero. You ca chage these values usig the scroll ars. Leave the
More informationProtected points in ordered trees
Applied Mathematics Letters 008 56 50 www.elsevier.com/locate/aml Protected poits i ordered trees Gi-Sag Cheo a, Louis W. Shapiro b, a Departmet of Mathematics, Sugkyukwa Uiversity, Suwo 440-746, Republic
More informationBOOLEAN MATHEMATICS: GENERAL THEORY
CHAPTER 3 BOOLEAN MATHEMATICS: GENERAL THEORY 3.1 ISOMORPHIC PROPERTIES The ame Boolea Arithmetic was chose because it was discovered that literal Boolea Algebra could have a isomorphic umerical aspect.
More informationAlgorithm Design Techniques. Divide and conquer Problem
Algorithm Desig Techiques Divide ad coquer Problem Divide ad Coquer Algorithms Divide ad Coquer algorithm desig works o the priciple of dividig the give problem ito smaller sub problems which are similar
More informationThe Graphs of Polynomial Functions
Sectio 4.3 The Graphs of Polyomial Fuctios Objective 1: Uderstadig the Defiitio of a Polyomial Fuctio Defiitio Polyomial Fuctio 1 2 The fuctio ax a 1x a 2x a1x a0 is a polyomial fuctio of degree where
More informationAn (or ) is a sequence in which each term after the first differs from the preceding term by a fixed constant, called the.
Sectio.2 Arithmetic Sequeces ad Series -.2 Arithmetic Sequeces ad Series Arithmetic Sequeces Arithmetic Series Key Terms: arithmetic sequece (arithmetic progressio), commo differece, arithmetic series
More informationOur second algorithm. Comp 135 Machine Learning Computer Science Tufts University. Decision Trees. Decision Trees. Decision Trees.
Comp 135 Machie Learig Computer Sciece Tufts Uiversity Fall 2017 Roi Khardo Some of these slides were adapted from previous slides by Carla Brodley Our secod algorithm Let s look at a simple dataset for
More informationComputer Science Foundation Exam. August 12, Computer Science. Section 1A. No Calculators! KEY. Solutions and Grading Criteria.
Computer Sciece Foudatio Exam August, 005 Computer Sciece Sectio A No Calculators! Name: SSN: KEY Solutios ad Gradig Criteria Score: 50 I this sectio of the exam, there are four (4) problems. You must
More informationSD vs. SD + One of the most important uses of sample statistics is to estimate the corresponding population parameters.
SD vs. SD + Oe of the most importat uses of sample statistics is to estimate the correspodig populatio parameters. The mea of a represetative sample is a good estimate of the mea of the populatio that
More informationLecture 1: Introduction and Strassen s Algorithm
5-750: Graduate Algorithms Jauary 7, 08 Lecture : Itroductio ad Strasse s Algorithm Lecturer: Gary Miller Scribe: Robert Parker Itroductio Machie models I this class, we will primarily use the Radom Access
More information9.1. Sequences and Series. Sequences. What you should learn. Why you should learn it. Definition of Sequence
_9.qxd // : AM Page Chapter 9 Sequeces, Series, ad Probability 9. Sequeces ad Series What you should lear Use sequece otatio to write the terms of sequeces. Use factorial otatio. Use summatio otatio to
More informationCSC165H1 Worksheet: Tutorial 8 Algorithm analysis (SOLUTIONS)
CSC165H1, Witer 018 Learig Objectives By the ed of this worksheet, you will: Aalyse the ruig time of fuctios cotaiig ested loops. 1. Nested loop variatios. Each of the followig fuctios takes as iput a
More informationThe number n of subintervals times the length h of subintervals gives length of interval (b-a).
Simulator with MadMath Kit: Riema Sums (Teacher s pages) I your kit: 1. GeoGebra file: Ready-to-use projector sized simulator: RiemaSumMM.ggb 2. RiemaSumMM.pdf (this file) ad RiemaSumMMEd.pdf (educator's
More informationCMSC Computer Architecture Lecture 10: Caches. Prof. Yanjing Li University of Chicago
CMSC 22200 Computer Architecture Lecture 10: Caches Prof. Yajig Li Uiversity of Chicago Midterm Recap Overview ad fudametal cocepts ISA Uarch Datapath, cotrol Sigle cycle, multi cycle Pipeliig Basic idea,
More informationExamples and Applications of Binary Search
Toy Gog ITEE Uiersity of Queeslad I the secod lecture last week we studied the biary search algorithm that soles the problem of determiig if a particular alue appears i a sorted list of iteger or ot. We
More informationComputational Geometry
Computatioal Geometry Chapter 4 Liear programmig Duality Smallest eclosig disk O the Ageda Liear Programmig Slides courtesy of Craig Gotsma 4. 4. Liear Programmig - Example Defie: (amout amout cosumed
More informationLecture Notes 6 Introduction to algorithm analysis CSS 501 Data Structures and Object-Oriented Programming
Lecture Notes 6 Itroductio to algorithm aalysis CSS 501 Data Structures ad Object-Orieted Programmig Readig for this lecture: Carrao, Chapter 10 To be covered i this lecture: Itroductio to algorithm aalysis
More informationMath 3201 Notes Chapter 4: Rational Expressions & Equations
Learig Goals: See p. tet.. Equivalet Ratioal Epressios ( classes) Read Goal p. 6 tet. Math 0 Notes Chapter : Ratioal Epressios & Equatios. Defie ad give a eample of a ratioal epressio. p. 6. Defie o-permissible
More informationNumerical Methods Lecture 6 - Curve Fitting Techniques
Numerical Methods Lecture 6 - Curve Fittig Techiques Topics motivatio iterpolatio liear regressio higher order polyomial form expoetial form Curve fittig - motivatio For root fidig, we used a give fuctio
More informationAnalysis Metrics. Intro to Algorithm Analysis. Slides. 12. Alg Analysis. 12. Alg Analysis
Itro to Algorithm Aalysis Aalysis Metrics Slides. Table of Cotets. Aalysis Metrics 3. Exact Aalysis Rules 4. Simple Summatio 5. Summatio Formulas 6. Order of Magitude 7. Big-O otatio 8. Big-O Theorems
More informationCivil Engineering Computation
Civil Egieerig Computatio Fidig Roots of No-Liear Equatios March 14, 1945 World War II The R.A.F. first operatioal use of the Grad Slam bomb, Bielefeld, Germay. Cotets 2 Root basics Excel solver Newto-Raphso
More informationChapter 18: Ray Optics Questions & Problems
Chapter 18: Ray Optics Questios & Problems c -1 2 1 1 1 h s θr= θi 1siθ 1 = 2si θ 2 = θ c = si ( ) + = m = = v s s f h s 1 Example 18.1 At high oo, the su is almost directly above (about 2.0 o from the
More informationBehavioral Modeling in Verilog
Behavioral Modelig i Verilog COE 202 Digital Logic Desig Dr. Muhamed Mudawar Kig Fahd Uiversity of Petroleum ad Mierals Presetatio Outlie Itroductio to Dataflow ad Behavioral Modelig Verilog Operators
More informationCIS 121 Data Structures and Algorithms with Java Fall Big-Oh Notation Tuesday, September 5 (Make-up Friday, September 8)
CIS 11 Data Structures ad Algorithms with Java Fall 017 Big-Oh Notatio Tuesday, September 5 (Make-up Friday, September 8) Learig Goals Review Big-Oh ad lear big/small omega/theta otatios Practice solvig
More information. Perform a geometric (ray-optics) construction (i.e., draw in the rays on the diagram) to show where the final image is formed.
MASSACHUSETTS INSTITUTE of TECHNOLOGY Departmet of Electrical Egieerig ad Computer Sciece 6.161 Moder Optics Project Laboratory 6.637 Optical Sigals, Devices & Systems Problem Set No. 1 Geometric optics
More informationBezier curves. Figure 2 shows cubic Bezier curves for various control points. In a Bezier curve, only
Edited: Yeh-Liag Hsu (998--; recommeded: Yeh-Liag Hsu (--9; last updated: Yeh-Liag Hsu (9--7. Note: This is the course material for ME55 Geometric modelig ad computer graphics, Yua Ze Uiversity. art of
More informationGuide to Applying Online
Guide to Applyig Olie Itroductio Respodig to requests for additioal iformatio Reportig: submittig your moitorig or ed of grat Pledges: submittig your Itroductio This guide is to help charities submit their
More informationEM375 STATISTICS AND MEASUREMENT UNCERTAINTY LEAST SQUARES LINEAR REGRESSION ANALYSIS
EM375 STATISTICS AND MEASUREMENT UNCERTAINTY LEAST SQUARES LINEAR REGRESSION ANALYSIS I this uit of the course we ivestigate fittig a straight lie to measured (x, y) data pairs. The equatio we wat to fit
More informationWavelet Transform. CSE 490 G Introduction to Data Compression Winter Wavelet Transformed Barbara (Enhanced) Wavelet Transformed Barbara (Actual)
Wavelet Trasform CSE 49 G Itroductio to Data Compressio Witer 6 Wavelet Trasform Codig PACW Wavelet Trasform A family of atios that filters the data ito low resolutio data plus detail data high pass filter
More informationNTH, GEOMETRIC, AND TELESCOPING TEST
NTH, GEOMETRIC, AND TELESCOPING TEST Sectio 9. Calculus BC AP/Dual, Revised 08 viet.dag@humbleisd.et /4/08 0:0 PM 9.: th, Geometric, ad Telescopig Test SUMMARY OF TESTS FOR SERIES Lookig at the first few
More informationCS200: Hash Tables. Prichard Ch CS200 - Hash Tables 1
CS200: Hash Tables Prichard Ch. 13.2 CS200 - Hash Tables 1 Table Implemetatios: average cases Search Add Remove Sorted array-based Usorted array-based Balaced Search Trees O(log ) O() O() O() O(1) O()
More informationDerivation of perspective stereo projection matrices with depth, shape and magnification consideration
Derivatio of perspective stereo projectio matrices with depth, shape ad magificatio cosideratio Patrick Oberthür Jauary 2014 This essay will show how to costruct a pair of stereoscopic perspective projectio
More informationSwitching Hardware. Spring 2018 CS 438 Staff, University of Illinois 1
Switchig Hardware Sprig 208 CS 438 Staff, Uiversity of Illiois Where are we? Uderstad Differet ways to move through a etwork (forwardig) Read sigs at each switch (datagram) Follow a kow path (virtual circuit)
More information1. The lines intersect. There is one solution, the point where they intersect. The system is called a consistent system.
Commo Core Math 3 Notes Uit Day Systems I. Systems of Liear Equatios A system of two liear equatios i two variables is two equatios cosidered together. To solve a system is to fid all the ordered pairs
More informationMathematical Stat I: solutions of homework 1
Mathematical Stat I: solutios of homework Name: Studet Id N:. Suppose we tur over cards simultaeously from two well shuffled decks of ordiary playig cards. We say we obtai a exact match o a particular
More informationECE4050 Data Structures and Algorithms. Lecture 6: Searching
ECE4050 Data Structures ad Algorithms Lecture 6: Searchig 1 Search Give: Distict keys k 1, k 2,, k ad collectio L of records of the form (k 1, I 1 ), (k 2, I 2 ),, (k, I ) where I j is the iformatio associated
More information. Written in factored form it is easy to see that the roots are 2, 2, i,
CMPS A Itroductio to Programmig Programmig Assigmet 4 I this assigmet you will write a java program that determies the real roots of a polyomial that lie withi a specified rage. Recall that the roots (or
More informationHash Tables. Presentation for use with the textbook Algorithm Design and Applications, by M. T. Goodrich and R. Tamassia, Wiley, 2015.
Presetatio for use with the textbook Algorithm Desig ad Applicatios, by M. T. Goodrich ad R. Tamassia, Wiley, 2015 Hash Tables xkcd. http://xkcd.com/221/. Radom Number. Used with permissio uder Creative
More informationSolution printed. Do not start the test until instructed to do so! CS 2604 Data Structures Midterm Spring, Instructions:
CS 604 Data Structures Midterm Sprig, 00 VIRG INIA POLYTECHNIC INSTITUTE AND STATE U T PROSI M UNI VERSI TY Istructios: Prit your ame i the space provided below. This examiatio is closed book ad closed
More informationMAXIMUM MATCHINGS IN COMPLETE MULTIPARTITE GRAPHS
Fura Uiversity Electroic Joural of Udergraduate Matheatics Volue 00, 1996 6-16 MAXIMUM MATCHINGS IN COMPLETE MULTIPARTITE GRAPHS DAVID SITTON Abstract. How ay edges ca there be i a axiu atchig i a coplete
More informationHow to Select the Best Refractive Index
How to Select the Best Refractive Idex Jeffrey Bodycomb, Ph.D. HORIBA Scietific www.horiba.com/us/particle 2013HORIBA, Ltd. All rights reserved. Outlie Laser Diffractio Calculatios Importace of Refractive
More informationAlgorithms Chapter 3 Growth of Functions
Algorithms Chapter 3 Growth of Fuctios Istructor: Chig Chi Li 林清池助理教授 chigchi.li@gmail.com Departmet of Computer Sciece ad Egieerig Natioal Taiwa Ocea Uiversity Outlie Asymptotic otatio Stadard otatios
More informationPanel Methods : Mini-Lecture. David Willis
Pael Methods : Mii-Lecture David Willis 3D - Pael Method Examples Other Applicatios of Pael Methods http://www.flowsol.co.uk/ http://oe.mit.edu/flowlab/ Boudary Elemet Methods Pael methods belog to a broader
More informationCounting Regions in the Plane and More 1
Coutig Regios i the Plae ad More 1 by Zvezdelia Stakova Berkeley Math Circle Itermediate I Group September 016 1. Overarchig Problem Problem 1 Regios i a Circle. The vertices of a polygos are arraged o
More informationChapter 4. Procedural Abstraction and Functions That Return a Value. Copyright 2015 Pearson Education, Ltd.. All rights reserved.
Chapter 4 Procedural Abstractio ad Fuctios That Retur a Value Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 4.1 Top-Dow Desig 4.2 Predefied Fuctios 4.3 Programmer-Defied Fuctios 4.4
More informationHigher-order iterative methods free from second derivative for solving nonlinear equations
Iteratioal Joural of the Phsical Scieces Vol 6(8, pp 887-89, 8 April, Available olie at http://wwwacademicjouralsorg/ijps DOI: 5897/IJPS45 ISSN 99-95 Academic Jourals Full Legth Research Paper Higher-order
More informationMath Section 2.2 Polynomial Functions
Math 1330 - Sectio. Polyomial Fuctios Our objectives i workig with polyomial fuctios will be, first, to gather iformatio about the graph of the fuctio ad, secod, to use that iformatio to geerate a reasoably
More informationCHAPTER IV: GRAPH THEORY. Section 1: Introduction to Graphs
CHAPTER IV: GRAPH THEORY Sectio : Itroductio to Graphs Sice this class is called Number-Theoretic ad Discrete Structures, it would be a crime to oly focus o umber theory regardless how woderful those topics
More informationChapter 9. Pointers and Dynamic Arrays. Copyright 2015 Pearson Education, Ltd.. All rights reserved.
Chapter 9 Poiters ad Dyamic Arrays Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Overview 9.1 Poiters 9.2 Dyamic Arrays Copyright 2015 Pearso Educatio, Ltd.. All rights reserved. Slide 9-3
More informationBig-O Analysis. Asymptotics
Big-O Aalysis 1 Defiitio: Suppose that f() ad g() are oegative fuctios of. The we say that f() is O(g()) provided that there are costats C > 0 ad N > 0 such that for all > N, f() Cg(). Big-O expresses
More informationOn (K t e)-saturated Graphs
Noame mauscript No. (will be iserted by the editor O (K t e-saturated Graphs Jessica Fuller Roald J. Gould the date of receipt ad acceptace should be iserted later Abstract Give a graph H, we say a graph
More informationCONVERGENCE OF THE RATIO OF PERIMETER OF A REGULAR POLYGON TO THE LENGTH OF ITS LONGEST DIAGONAL AS THE NUMBER OF SIDES OF POLYGON INCREASES
CONVERGENCE OF THE RATIO OF PERIMETER OF A REGULAR POLYGON TO THE LENGTH OF ITS LONGEST DIAGONAL AS THE NUMBER OF SIDES OF POLYGON INCREASES Pawa Kumar Bishwakarma Idepedet Researcher Correspodig Author:
More informationA Study on the Performance of Cholesky-Factorization using MPI
A Study o the Performace of Cholesky-Factorizatio usig MPI Ha S. Kim Scott B. Bade Departmet of Computer Sciece ad Egieerig Uiversity of Califoria Sa Diego {hskim, bade}@cs.ucsd.edu Abstract Cholesky-factorizatio
More informationBasic allocator mechanisms The course that gives CMU its Zip! Memory Management II: Dynamic Storage Allocation Mar 6, 2000.
5-23 The course that gives CM its Zip Memory Maagemet II: Dyamic Storage Allocatio Mar 6, 2000 Topics Segregated lists Buddy system Garbage collectio Mark ad Sweep Copyig eferece coutig Basic allocator
More informationExact Minimum Lower Bound Algorithm for Traveling Salesman Problem
Exact Miimum Lower Boud Algorithm for Travelig Salesma Problem Mohamed Eleiche GeoTiba Systems mohamed.eleiche@gmail.com Abstract The miimum-travel-cost algorithm is a dyamic programmig algorithm to compute
More information