MATHEMATICAL MODELLING OF ARCH FORMATION IN GRANULAR MATERIALS

Size: px
Start display at page:

Download "MATHEMATICAL MODELLING OF ARCH FORMATION IN GRANULAR MATERIALS"

Transcription

1 6 th INTERNATIONAL MULTIDISCIPLINARY CONFERENCE MATHEMATICAL MODELLING OF ARCH FORMATION IN GRANULAR MATERIALS Istva eppler SZIE Faculty of Mechaics, H-2103 Gödöllő Páter. 1., Hugary Abstract: The mathematical modellig of formatio, stability ad damage of self-supportig stagat arch like structures iside bulk material discussed i this paper. Some experimetal methods will also be preseted, for the measuremet of material properties used i the mathematical model. We preset a algorithm for the determiatio of critical outlet size for a simplified model silo. eywords: graular material, archig, fiite elemet method, triaxial apparatus 1. INTRODUCTION Arcig occurs mostly durig the discharge of silos, but pressure actig o udergroud structures is also iflueced by archig, ad smaller tha the weight of the overburde. Earth pressure applied o retaiig wall sometimes also smaller tha the theoretical value, ad this pheomea are also caused by the archig actio. The arch formatio iside silos ca chage the wall pressure distributio i a large scale, ad sometimes the whole silo collapses because of this chage i pressure distributio. The outflow of graular materials from cotaiers is also cosidered to a sequece of formatio ad collapse of arches. The evaluatio of stresses i graular assemblies without takig the archig actio ito cosideratio, always gives false, iaccurate results. 2. MATHEMATICAL MODEL The classical method, used for the evaluatio of stresses withi the arch uses two theoretical solutios [1]. The first oe evaluates the stresses that cosolidate the graular material ad give rise to its stregth, the secod oe aalyzes the stresses that act i a arch regarded as a structural member. The evaluatio of stresses withi these speculative arches is based o

2 assumptios o the shape of these arches. The classical defiitio of archig follows from these aspects: archig refers to spotaeous formatio of a arch like supported stagat mass of bulk material [1], which is capable of bearig the pressure origiatig from the mass above it. For the mathematical model, first we eed to determie the stresses iside our model silo. The model silo was a simple rectagle shaped cotaier, with variable outlet size o its bottom. For the determiatio of stresses actig iside the graular mass, we used a used liear elastic, isotropic, homogeous cotiuum material model for the graular assembly. Our assumptios were: 1. The graular material fills out cotiuously the cotaier, ad its material properties are idepedet of space coordiates, time ad orietatio. 2. We assumed, that the coectio betwee the stress ad the deformatio tesor is liear i every poit of our model silo. 3. The load origiated oly from material self weight. 4. The wall-material frictio ca be eglected. 5. The rigidity of the silo side wall supposed to be ifiite. 6. We assumed plai strai state. Our aim was to determie the critical outlet size of this model silo. Critical outlet size meas a border-lie case, amely if the outlet size is bigger tha this critical values, stable arches ca ot be take form. Fig. 1: Triaxial apparatus Fig. 2: Triaxial compressio

3 2.1. Material properties ad failure criteria For the determiatio of stresses, the specime s Youg modulus (E) ad the Poisso s ratio ( ν ) had to be determie. The measuremet process of these material properties described i [2]. We eeded a other material property for the descriptio of the collapse of the arch. This is the critical stress belogig to biaxial stress state. The arch collapses, whe o its free boudary where the material is i biaxial stress state the compressive stress exceeds the critical value σ. We used a special triaxial apparatus (fig. 2) for the determiatio of material properties. The descriptio of this apparatus ca be foud i [3]. To measure the critical stress belogig to biaxial stress state, we applied two differet kid of load o the graular material. I the first step we applied a triaxial pre-compressio o the specime. The we removed oe of the lateral sprigs (fig. 3), ad icreased the vertical load util the collapse of the specime. With the removal of oe of the lateral sprigs, we realized the biaxial stress state, eeded for the measuremet of the critical stress. owig the material properties, the stresses arisig iside the model silo ca be determied usig fiite elemet method. The fiite elemet model of silo is i fig 3. After the determiatio of stresses iside the model silo, we have to aalyze the process of arch formatio. For this, we have to determie the failure criterios cotrollig the arch formatio ad collapse process. The failure criterio for arch formatio is simple for this rectagle shaped model silo: graular assemblies are uable to resist tesio. It is also simple to formulate this coditios i mathematical form. After the evaluatio of stresses, we have to compute the Fig 3: The fiite elemet model eigevalues of the stress tesor i every poit of the graular material. These eigevalues are the so called pricipal stresses. If the biggest pricipal stress is positive, tha i that poit of the material tesio occurs, ad the

4 cotiuity of the material fails. The material is fallig out from these poit through the ope outlet. The stability ad collapse of the arches depeds o two differet failure coditios. The firs failure coditio occurs, whe o the materials free boudary where the material is i biaxial stress state the compressive stress exceeds the critical value σ. The mathematical formulatio of this failure criterio is also i coectio with the pricipal stress values. If the third (smallest, ad i our case egative) pricipal stress value is smaller the the critical σ, i ay poits of the graular assembly s boudaries, tha the failure of the arch is due to happe. The value of this critical stress depeds o the magitude of pre-compressig stresses. The secod failure criterio is about the shear stresses actig iside the graular material. The value of the shear stresses iside graular materials caot be higher tha a critical value. The critical shear stress value is usually cosidered to be liear fuctio of the frictio agle ad cohesio of the graular material. Usig this failure coditios, it is possible to create a algorithm for the umerical simulatio of the archig process (fig 4) The algorithm 1. First we ope the outlet to a iitial size. 2. The determiatio of stresses iside the graular material comes ext. Usig fiite elemet method, this is possible; umerically. 3. owig the stresses, the eigevalues of stress tesors must be computed. 4. Usig the biggest eigevalues, the failure criterio for arch formatio must be applied. 5. After the removal of material elemets, where the first failure criterio prevailed, the domai, where the stresses were evaluated chaged, so the stresses must be evaluated agai. 6. owig the ew stresses, the eigevalues must be computed agai, ad the failure coditio for arch formatio must be applied. This goes util there are o more poits iside the material, where tesio occurs. 7. Whe there is o more tesio, the two failure criterio for arch collapse must be take ito accout. If oe of them comes to be true, the a stable arch formed. This arch belogs to the outlet size adjusted i step The outlet size ca be elarged, ad the the whole process starts agai from step The algorithm rus util oe of the arch failure criterios comes to be true. 10. Whe the arch collapse criterio occurs, the critical outlet size is determied.

5 ( ) Defie the domai T ad the boudary coditios. Evaluate the stresses: F + q = 0, 1 A = t + t, 2 [ ] 1 ν A = F FI E 2G 1+ ν. Solve the ( F σ E) = 0 eigevalue problem i T. σ 1 is the biggest, σ 3 is the smallest eigevalue of F. p T where σ 0? 1 > y Remove the elemets, where σ > 0 1 is true. The arch is stable, outlet size ca be elarged. p T, where σ 3 < σ < 0? (T is T-s boudary) y p T, where τ τ y The arch collapses Critical outlet size determied Fig 4.: The algorithm for determiatio of critical outlet size 3. RESULTS AND FURHTER RESEARCH A iterative method for modellig the archig actio i graular assemblies was developed. This method is differet, ad more efficiet tha ay methods existig i the literature for determiatio of critical outlet size i silos. Our further research will iclude the coic shaped cotaiers, where the possible slidig of the material at the cotaier wall must be also take ito accout.

6 4. REFERENCES 1. A. Drescher, A. J. Waters, C. A. Rhoades: Archig i Hoppers I-II., Powder Techology, 84, (1995), pp Csorba L., Balássy Z.Huszár I., Csizmadia B.: Determiatio of Poisso's ratio i elastic oedometer, 4th ICCPAM, Rostock, 1989, Proceedig, Volume 1, pp Csizmadia B. Oldal I. eppler I.: Quasi-Triaxial apparatus for the determiatio of mechaical properties of graular materials. 20th. Daubia Adria Symposium o Experimetal Methods i Solid Mechaics, September 24 27, Győr, Hugary. 2003

Analysis of composites with multiple rigid-line reinforcements by the BEM

Analysis of composites with multiple rigid-line reinforcements by the BEM Aalysis of composites with multiple rigid-lie reiforcemets by the BEM Piotr Fedeliski* Departmet of Stregth of Materials ad Computatioal Mechaics, Silesia Uiversity of Techology ul. Koarskiego 18A, 44-100

More information

Numerical Simulation of Thermomechanical Problems in Applied Mechanics: Application to Solidification Problem

Numerical Simulation of Thermomechanical Problems in Applied Mechanics: Application to Solidification Problem Leoardo Joural of Scieces ISSN 1583-0233 Issue 9, July-December 2006 p. 25-32 Numerical Simulatio of Thermomechaical Problems i Applied Mechaics: Applicatio to Solidificatio Problem Vicet Obiajulu OGWUAGWU

More information

DETERMINATION OF MECHANICAL PROPERTIES OF A NON- UNIFORM BEAM USING THE MEASUREMENT OF THE EXCITED LONGITUDINAL ELASTIC VIBRATIONS.

DETERMINATION OF MECHANICAL PROPERTIES OF A NON- UNIFORM BEAM USING THE MEASUREMENT OF THE EXCITED LONGITUDINAL ELASTIC VIBRATIONS. ICSV4 Cairs Australia 9- July 7 DTRMINATION OF MCHANICAL PROPRTIS OF A NON- UNIFORM BAM USING TH MASURMNT OF TH XCITD LONGITUDINAL LASTIC VIBRATIONS Pavel Aokhi ad Vladimir Gordo Departmet of the mathematics

More information

ANALYSIS OF DAMPING EFFECT ON BEAM VIBRATION

ANALYSIS OF DAMPING EFFECT ON BEAM VIBRATION Molecular ad Quatum Acoustics vol. 7, (6) 79 ANALYSIS OF DAMPING EFFECT ON BEAM VIBRATION Jerzy FILIPIAK 1, Lech SOLARZ, Korad ZUBKO 1 Istitute of Electroic ad Cotrol Systems, Techical Uiversity of Czestochowa,

More information

Chapter 9: Numerical Differentiation

Chapter 9: Numerical Differentiation 178 Chapter 9: Numerical Differetiatio Numerical Differetiatio Formulatio of equatios for physical problems ofte ivolve derivatives (rate-of-chage quatities, such as velocity ad acceleratio). Numerical

More information

THE SOLUTION OF NONLINEAR EQUATIONS f( x ) = 0.

THE SOLUTION OF NONLINEAR EQUATIONS f( x ) = 0. THE SOLUTION OF NONLINEAR EQUATIONS f( ) = 0. Noliear Equatio Solvers Bracketig. Graphical. Aalytical Ope Methods Bisectio False Positio (Regula-Falsi) Fied poit iteratio Newto Raphso Secat The root of

More information

CHAPTER 10 INFINITE SEQUENCES AND SERIES

CHAPTER 10 INFINITE SEQUENCES AND SERIES CHAPTER 10 INFINITE SEQUENCES AND SERIES 10.1 Sequeces 10.2 Ifiite Series 10.3 The Itegral Tests 10.4 Compariso Tests 10.5 The Ratio ad Root Tests 10.6 Alteratig Series: Absolute ad Coditioal Covergece

More information

EVALUATION OF GLASS FIBER/EPOXY INTERFACIAL STRENGTH BY THE CRUCIFORM SPECIMEN METHOD

EVALUATION OF GLASS FIBER/EPOXY INTERFACIAL STRENGTH BY THE CRUCIFORM SPECIMEN METHOD EVALUATION OF GLASS FIBER/EPOX INTERFACIAL STRENGTH B THE CRUCIFORM SPECIMEN METHOD Ju KOANAGI, Hajime KATO, Akihiro KASHIMA, uichi IGARASHI, Keichi WATANABE 3, Ichiro UENO 4 ad Shiji OGIHARA 4 Istitute

More information

10-701/ Machine Learning Mid-term Exam Solution

10-701/ Machine Learning Mid-term Exam Solution 0-70/5-78 Machie Learig Mid-term Exam Solutio Your Name: Your Adrew ID: True or False (Give oe setece explaatio) (20%). (F) For a cotiuous radom variable x ad its probability distributio fuctio p(x), it

More information

62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 +

62. Power series Definition 16. (Power series) Given a sequence {c n }, the series. c n x n = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + 62. Power series Defiitio 16. (Power series) Give a sequece {c }, the series c x = c 0 + c 1 x + c 2 x 2 + c 3 x 3 + is called a power series i the variable x. The umbers c are called the coefficiets of

More information

Sequences A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence

Sequences A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence Sequeces A sequece of umbers is a fuctio whose domai is the positive itegers. We ca see that the sequece 1, 1, 2, 2, 3, 3,... is a fuctio from the positive itegers whe we write the first sequece elemet

More information

Failure Theories Des Mach Elem Mech. Eng. Department Chulalongkorn University

Failure Theories Des Mach Elem Mech. Eng. Department Chulalongkorn University Failure Theories Review stress trasformatio Failure theories for ductile materials Maimum-Shear-Stress Theor Distortio-Eerg Theor Coulomb-Mohr Theor Failure theories for brittle materials Maimum-Normal-Stress

More information

A statistical method to determine sample size to estimate characteristic value of soil parameters

A statistical method to determine sample size to estimate characteristic value of soil parameters A statistical method to determie sample size to estimate characteristic value of soil parameters Y. Hojo, B. Setiawa 2 ad M. Suzuki 3 Abstract Sample size is a importat factor to be cosidered i determiig

More information

ECE-S352 Introduction to Digital Signal Processing Lecture 3A Direct Solution of Difference Equations

ECE-S352 Introduction to Digital Signal Processing Lecture 3A Direct Solution of Difference Equations ECE-S352 Itroductio to Digital Sigal Processig Lecture 3A Direct Solutio of Differece Equatios Discrete Time Systems Described by Differece Equatios Uit impulse (sample) respose h() of a DT system allows

More information

Chapter 14: Chemical Equilibrium

Chapter 14: Chemical Equilibrium hapter 14: hemical Equilibrium 46 hapter 14: hemical Equilibrium Sectio 14.1: Itroductio to hemical Equilibrium hemical equilibrium is the state where the cocetratios of all reactats ad products remai

More information

The axial dispersion model for tubular reactors at steady state can be described by the following equations: dc dz R n cn = 0 (1) (2) 1 d 2 c.

The axial dispersion model for tubular reactors at steady state can be described by the following equations: dc dz R n cn = 0 (1) (2) 1 d 2 c. 5.4 Applicatio of Perturbatio Methods to the Dispersio Model for Tubular Reactors The axial dispersio model for tubular reactors at steady state ca be described by the followig equatios: d c Pe dz z =

More information

Markov Decision Processes

Markov Decision Processes Markov Decisio Processes Defiitios; Statioary policies; Value improvemet algorithm, Policy improvemet algorithm, ad liear programmig for discouted cost ad average cost criteria. Markov Decisio Processes

More information

A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence

A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence Sequeces A sequece of umbers is a fuctio whose domai is the positive itegers. We ca see that the sequece,, 2, 2, 3, 3,... is a fuctio from the positive itegers whe we write the first sequece elemet as

More information

Boundary layer problem on conveyor belt. Gabriella Bognár University of Miskolc 3515 Miskolc-Egyetemváros, Hungary

Boundary layer problem on conveyor belt. Gabriella Bognár University of Miskolc 3515 Miskolc-Egyetemváros, Hungary Boudary layer problem o coveyor belt Gabriella Bogár Uiversity of Miskolc 355 Miskolc-Egyetemváros, Hugary e-mail: matvbg@ui-miskolc.hu Abstract: A techologically importat source of the boudary layer pheomeo

More information

An Analysis of a Certain Linear First Order. Partial Differential Equation + f ( x, by Means of Topology

An Analysis of a Certain Linear First Order. Partial Differential Equation + f ( x, by Means of Topology Iteratioal Mathematical Forum 2 2007 o. 66 3241-3267 A Aalysis of a Certai Liear First Order Partial Differetial Equatio + f ( x y) = 0 z x by Meas of Topology z y T. Oepomo Sciece Egieerig ad Mathematics

More information

The Method of Least Squares. To understand least squares fitting of data.

The Method of Least Squares. To understand least squares fitting of data. The Method of Least Squares KEY WORDS Curve fittig, least square GOAL To uderstad least squares fittig of data To uderstad the least squares solutio of icosistet systems of liear equatios 1 Motivatio Curve

More information

The Pendulum. Purpose

The Pendulum. Purpose The Pedulum Purpose To carry out a example illustratig how physics approaches ad solves problems. The example used here is to explore the differet factors that determie the period of motio of a pedulum.

More information

Sequences and Series of Functions

Sequences and Series of Functions Chapter 6 Sequeces ad Series of Fuctios 6.1. Covergece of a Sequece of Fuctios Poitwise Covergece. Defiitio 6.1. Let, for each N, fuctio f : A R be defied. If, for each x A, the sequece (f (x)) coverges

More information

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j The -Trasform 7. Itroductio Geeralie the complex siusoidal represetatio offered by DTFT to a represetatio of complex expoetial sigals. Obtai more geeral characteristics for discrete-time LTI systems. 7.

More information

Chapter 2 The Monte Carlo Method

Chapter 2 The Monte Carlo Method Chapter 2 The Mote Carlo Method The Mote Carlo Method stads for a broad class of computatioal algorithms that rely o radom sampligs. It is ofte used i physical ad mathematical problems ad is most useful

More information

Mathematical Notation Math Finite Mathematics

Mathematical Notation Math Finite Mathematics Mathematical Notatio Math 60 - Fiite Mathematics Use Word or WordPerfect to recreate the followig documets. Each article is worth 0 poits ad should be emailed to the istructor at james@richlad.edu. If

More information

DYNAMIC ANALYSIS OF BEAM-LIKE STRUCTURES SUBJECT TO MOVING LOADS

DYNAMIC ANALYSIS OF BEAM-LIKE STRUCTURES SUBJECT TO MOVING LOADS DYNAMIC ANALYSIS OF BEAM-LIKE STRUCTURES SUBJECT TO MOVING LOADS Ivaa Štimac 1, Ivica Kožar 1 M.Sc,Assistat, Ph.D. Professor 1, Faculty of Civil Egieerig, Uiverity of Rieka, Croatia INTRODUCTION The vehicle-iduced

More information

A CONFINEMENT MODEL OF HIGH STRENGTH CONCRETE

A CONFINEMENT MODEL OF HIGH STRENGTH CONCRETE 3 th World Coferece o Earthquake Egieerig Vacouver, B.C., Caada August -6, 24 Paper No. 873 A CONFINEMENT MODEL OF HIGH STRENGTH CONCRETE Nobutaka NAKAZAWA, Kazuhiko KAWASHIMA 2, Gakuho WATANABE 3, Ju-ichi

More information

Chapter 6 Sampling Distributions

Chapter 6 Sampling Distributions Chapter 6 Samplig Distributios 1 I most experimets, we have more tha oe measuremet for ay give variable, each measuremet beig associated with oe radomly selected a member of a populatio. Hece we eed to

More information

6.3 Testing Series With Positive Terms

6.3 Testing Series With Positive Terms 6.3. TESTING SERIES WITH POSITIVE TERMS 307 6.3 Testig Series With Positive Terms 6.3. Review of what is kow up to ow I theory, testig a series a i for covergece amouts to fidig the i= sequece of partial

More information

Analytic Continuation

Analytic Continuation Aalytic Cotiuatio The stadard example of this is give by Example Let h (z) = 1 + z + z 2 + z 3 +... kow to coverge oly for z < 1. I fact h (z) = 1/ (1 z) for such z. Yet H (z) = 1/ (1 z) is defied for

More information

Review Problems 1. ICME and MS&E Refresher Course September 19, 2011 B = C = AB = A = A 2 = A 3... C 2 = C 3 = =

Review Problems 1. ICME and MS&E Refresher Course September 19, 2011 B = C = AB = A = A 2 = A 3... C 2 = C 3 = = Review Problems ICME ad MS&E Refresher Course September 9, 0 Warm-up problems. For the followig matrices A = 0 B = C = AB = 0 fid all powers A,A 3,(which is A times A),... ad B,B 3,... ad C,C 3,... Solutio:

More information

Math 5311 Problem Set #5 Solutions

Math 5311 Problem Set #5 Solutions Math 5311 Problem Set #5 Solutios March 9, 009 Problem 1 O&S 11.1.3 Part (a) Solve with boudary coditios u = 1 0 x < L/ 1 L/ < x L u (0) = u (L) = 0. Let s refer to [0, L/) as regio 1 ad (L/, L] as regio.

More information

TESTING OF THE FORCES IN CABLE OF SUSPENSION STRUCTURE AND BRIDGES

TESTING OF THE FORCES IN CABLE OF SUSPENSION STRUCTURE AND BRIDGES TSTING OF TH FORCS IN CABL OF SUSPNSION STRUCTUR AND BRIDGS Zhou, M. 1, Liu, Z. ad Liu, J. 1 College of the Muicipal Techology, Guagzhou Uiversity, Guagzhou. Guagzhou Muicipal ad Ladscape gieerig Quality

More information

Recurrence Relations

Recurrence Relations Recurrece Relatios Aalysis of recursive algorithms, such as: it factorial (it ) { if (==0) retur ; else retur ( * factorial(-)); } Let t be the umber of multiplicatios eeded to calculate factorial(). The

More information

Infinite Sequences and Series

Infinite Sequences and Series Chapter 6 Ifiite Sequeces ad Series 6.1 Ifiite Sequeces 6.1.1 Elemetary Cocepts Simply speakig, a sequece is a ordered list of umbers writte: {a 1, a 2, a 3,...a, a +1,...} where the elemets a i represet

More information

Sequences, Mathematical Induction, and Recursion. CSE 2353 Discrete Computational Structures Spring 2018

Sequences, Mathematical Induction, and Recursion. CSE 2353 Discrete Computational Structures Spring 2018 CSE 353 Discrete Computatioal Structures Sprig 08 Sequeces, Mathematical Iductio, ad Recursio (Chapter 5, Epp) Note: some course slides adopted from publisher-provided material Overview May mathematical

More information

THEORETICAL RESEARCH REGARDING ANY STABILITY THEOREMS WITH APPLICATIONS. Marcel Migdalovici 1 and Daniela Baran 2

THEORETICAL RESEARCH REGARDING ANY STABILITY THEOREMS WITH APPLICATIONS. Marcel Migdalovici 1 and Daniela Baran 2 ICSV4 Cairs Australia 9- July, 007 THEORETICAL RESEARCH REGARDING ANY STABILITY THEOREMS WITH APPLICATIONS Marcel Migdalovici ad Daiela Bara Istitute of Solid Mechaics, INCAS Elie Carafoli, 5 C-ti Mille

More information

SECTION 2 Electrostatics

SECTION 2 Electrostatics SECTION Electrostatics This sectio, based o Chapter of Griffiths, covers effects of electric fields ad forces i static (timeidepedet) situatios. The topics are: Electric field Gauss s Law Electric potetial

More information

ln(i G ) 26.1 Review 26.2 Statistics of multiple breakdowns M Rows HBD SBD N Atoms Time

ln(i G ) 26.1 Review 26.2 Statistics of multiple breakdowns M Rows HBD SBD N Atoms Time EE650R: Reliability Physics of Naoelectroic Devices Lecture 26: TDDB: Statistics of Multiple Breadows Date: Nov 17, 2006 ClassNotes: Jaydeep P. Kulari Review: Pradeep R. Nair 26.1 Review I the last class

More information

Appendix: The Laplace Transform

Appendix: The Laplace Transform Appedix: The Laplace Trasform The Laplace trasform is a powerful method that ca be used to solve differetial equatio, ad other mathematical problems. Its stregth lies i the fact that it allows the trasformatio

More information

TR/46 OCTOBER THE ZEROS OF PARTIAL SUMS OF A MACLAURIN EXPANSION A. TALBOT

TR/46 OCTOBER THE ZEROS OF PARTIAL SUMS OF A MACLAURIN EXPANSION A. TALBOT TR/46 OCTOBER 974 THE ZEROS OF PARTIAL SUMS OF A MACLAURIN EXPANSION by A. TALBOT .. Itroductio. A problem i approximatio theory o which I have recetly worked [] required for its solutio a proof that the

More information

Sequences. Notation. Convergence of a Sequence

Sequences. Notation. Convergence of a Sequence Sequeces A sequece is essetially just a list. Defiitio (Sequece of Real Numbers). A sequece of real umbers is a fuctio Z (, ) R for some real umber. Do t let the descriptio of the domai cofuse you; it

More information

6.003 Homework #3 Solutions

6.003 Homework #3 Solutions 6.00 Homework # Solutios Problems. Complex umbers a. Evaluate the real ad imagiary parts of j j. π/ Real part = Imagiary part = 0 e Euler s formula says that j = e jπ/, so jπ/ j π/ j j = e = e. Thus the

More information

Provläsningsexemplar / Preview TECHNICAL REPORT INTERNATIONAL SPECIAL COMMITTEE ON RADIO INTERFERENCE

Provläsningsexemplar / Preview TECHNICAL REPORT INTERNATIONAL SPECIAL COMMITTEE ON RADIO INTERFERENCE TECHNICAL REPORT CISPR 16-4-3 2004 AMENDMENT 1 2006-10 INTERNATIONAL SPECIAL COMMITTEE ON RADIO INTERFERENCE Amedmet 1 Specificatio for radio disturbace ad immuity measurig apparatus ad methods Part 4-3:

More information

MONITORING THE STABILITY OF SLOPES BY GPS

MONITORING THE STABILITY OF SLOPES BY GPS MONITORING THE STABILITY OF SLOPES BY GPS Prof. S. Sakurai Costructio Egieerig Research Istitute Foudatio, Japa Prof. N. Shimizu Dept. of Civil Egieerig, Yamaguchi Uiversity, Japa ABSTRACT The stability

More information

Because it tests for differences between multiple pairs of means in one test, it is called an omnibus test.

Because it tests for differences between multiple pairs of means in one test, it is called an omnibus test. Math 308 Sprig 018 Classes 19 ad 0: Aalysis of Variace (ANOVA) Page 1 of 6 Itroductio ANOVA is a statistical procedure for determiig whether three or more sample meas were draw from populatios with equal

More information

Statistics 511 Additional Materials

Statistics 511 Additional Materials Cofidece Itervals o mu Statistics 511 Additioal Materials This topic officially moves us from probability to statistics. We begi to discuss makig ifereces about the populatio. Oe way to differetiate probability

More information

Measurement uncertainty of the sound absorption

Measurement uncertainty of the sound absorption Measuremet ucertaity of the soud absorptio coefficiet Aa Izewska Buildig Research Istitute, Filtrowa Str., 00-6 Warsaw, Polad a.izewska@itb.pl 6887 The stadard ISO/IEC 705:005 o the competece of testig

More information

First, note that the LS residuals are orthogonal to the regressors. X Xb X y = 0 ( normal equations ; (k 1) ) So,

First, note that the LS residuals are orthogonal to the regressors. X Xb X y = 0 ( normal equations ; (k 1) ) So, 0 2. OLS Part II The OLS residuals are orthogoal to the regressors. If the model icludes a itercept, the orthogoality of the residuals ad regressors gives rise to three results, which have limited practical

More information

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j.

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j. Eigevalue-Eigevector Istructor: Nam Su Wag eigemcd Ay vector i real Euclidea space of dimesio ca be uiquely epressed as a liear combiatio of liearly idepedet vectors (ie, basis) g j, j,,, α g α g α g α

More information

PRELIM PROBLEM SOLUTIONS

PRELIM PROBLEM SOLUTIONS PRELIM PROBLEM SOLUTIONS THE GRAD STUDENTS + KEN Cotets. Complex Aalysis Practice Problems 2. 2. Real Aalysis Practice Problems 2. 4 3. Algebra Practice Problems 2. 8. Complex Aalysis Practice Problems

More information

Precalculus MATH Sections 3.1, 3.2, 3.3. Exponential, Logistic and Logarithmic Functions

Precalculus MATH Sections 3.1, 3.2, 3.3. Exponential, Logistic and Logarithmic Functions Precalculus MATH 2412 Sectios 3.1, 3.2, 3.3 Epoetial, Logistic ad Logarithmic Fuctios Epoetial fuctios are used i umerous applicatios coverig may fields of study. They are probably the most importat group

More information

DYNAMIC STUDY OF THE CONTACT ANGLE HYSTERESIS IN THE PRESENCE OF PERIODIC DEFECTS *

DYNAMIC STUDY OF THE CONTACT ANGLE HYSTERESIS IN THE PRESENCE OF PERIODIC DEFECTS * 11 th Natioal Cogress o Theoretical ad Applied Mechaics, 2-5 Sept. 2009, Borovets, Bulgaria DYNAMIC STUDY OF THE CONTACT ANGLE HYSTERESIS IN THE PRESENCE OF PERIODIC DEFECTS * STANIMIR ILIEV, NINA PESHEVA

More information

Chapter 7 z-transform

Chapter 7 z-transform Chapter 7 -Trasform Itroductio Trasform Uilateral Trasform Properties Uilateral Trasform Iversio of Uilateral Trasform Determiig the Frequecy Respose from Poles ad Zeros Itroductio Role i Discrete-Time

More information

Principle Of Superposition

Principle Of Superposition ecture 5: PREIMINRY CONCEP O RUCUR NYI Priciple Of uperpositio Mathematically, the priciple of superpositio is stated as ( a ) G( a ) G( ) G a a or for a liear structural system, the respose at a give

More information

Chapter 4. Fourier Series

Chapter 4. Fourier Series Chapter 4. Fourier Series At this poit we are ready to ow cosider the caoical equatios. Cosider, for eample the heat equatio u t = u, < (4.) subject to u(, ) = si, u(, t) = u(, t) =. (4.) Here,

More information

(A sequence also can be thought of as the list of function values attained for a function f :ℵ X, where f (n) = x n for n 1.) x 1 x N +k x N +4 x 3

(A sequence also can be thought of as the list of function values attained for a function f :ℵ X, where f (n) = x n for n 1.) x 1 x N +k x N +4 x 3 MATH 337 Sequeces Dr. Neal, WKU Let X be a metric space with distace fuctio d. We shall defie the geeral cocept of sequece ad limit i a metric space, the apply the results i particular to some special

More information

Lesson 10: Limits and Continuity

Lesson 10: Limits and Continuity www.scimsacademy.com Lesso 10: Limits ad Cotiuity SCIMS Academy 1 Limit of a fuctio The cocept of limit of a fuctio is cetral to all other cocepts i calculus (like cotiuity, derivative, defiite itegrals

More information

Statistical Analysis on Uncertainty for Autocorrelated Measurements and its Applications to Key Comparisons

Statistical Analysis on Uncertainty for Autocorrelated Measurements and its Applications to Key Comparisons Statistical Aalysis o Ucertaity for Autocorrelated Measuremets ad its Applicatios to Key Comparisos Nie Fa Zhag Natioal Istitute of Stadards ad Techology Gaithersburg, MD 0899, USA Outlies. Itroductio.

More information

Alternating Series. 1 n 0 2 n n THEOREM 9.14 Alternating Series Test Let a n > 0. The alternating series. 1 n a n.

Alternating Series. 1 n 0 2 n n THEOREM 9.14 Alternating Series Test Let a n > 0. The alternating series. 1 n a n. 0_0905.qxd //0 :7 PM Page SECTION 9.5 Alteratig Series Sectio 9.5 Alteratig Series Use the Alteratig Series Test to determie whether a ifiite series coverges. Use the Alteratig Series Remaider to approximate

More information

Math Solutions to homework 6

Math Solutions to homework 6 Math 175 - Solutios to homework 6 Cédric De Groote November 16, 2017 Problem 1 (8.11 i the book): Let K be a compact Hermitia operator o a Hilbert space H ad let the kerel of K be {0}. Show that there

More information

PHY4905: Nearly-Free Electron Model (NFE)

PHY4905: Nearly-Free Electron Model (NFE) PHY4905: Nearly-Free Electro Model (NFE) D. L. Maslov Departmet of Physics, Uiversity of Florida (Dated: Jauary 12, 2011) 1 I. REMINDER: QUANTUM MECHANICAL PERTURBATION THEORY A. No-degeerate eigestates

More information

Model Theory 2016, Exercises, Second batch, covering Weeks 5-7, with Solutions

Model Theory 2016, Exercises, Second batch, covering Weeks 5-7, with Solutions Model Theory 2016, Exercises, Secod batch, coverig Weeks 5-7, with Solutios 3 Exercises from the Notes Exercise 7.6. Show that if T is a theory i a coutable laguage L, haso fiite model, ad is ℵ 0 -categorical,

More information

Lecture 6 Chi Square Distribution (χ 2 ) and Least Squares Fitting

Lecture 6 Chi Square Distribution (χ 2 ) and Least Squares Fitting Lecture 6 Chi Square Distributio (χ ) ad Least Squares Fittig Chi Square Distributio (χ ) Suppose: We have a set of measuremets {x 1, x, x }. We kow the true value of each x i (x t1, x t, x t ). We would

More information

Mechatronics. Time Response & Frequency Response 2 nd -Order Dynamic System 2-Pole, Low-Pass, Active Filter

Mechatronics. Time Response & Frequency Response 2 nd -Order Dynamic System 2-Pole, Low-Pass, Active Filter Time Respose & Frequecy Respose d -Order Dyamic System -Pole, Low-Pass, Active Filter R 4 R 7 C 5 e i R 1 C R 3 - + R 6 - + e out Assigmet: Perform a Complete Dyamic System Ivestigatio of the Two-Pole,

More information

Nonlinear regression

Nonlinear regression oliear regressio How to aalyse data? How to aalyse data? Plot! How to aalyse data? Plot! Huma brai is oe the most powerfull computatioall tools Works differetly tha a computer What if data have o liear

More information

10.6 ALTERNATING SERIES

10.6 ALTERNATING SERIES 0.6 Alteratig Series Cotemporary Calculus 0.6 ALTERNATING SERIES I the last two sectios we cosidered tests for the covergece of series whose terms were all positive. I this sectio we examie series whose

More information

Linear Elliptic PDE s Elliptic partial differential equations frequently arise out of conservation statements of the form

Linear Elliptic PDE s Elliptic partial differential equations frequently arise out of conservation statements of the form Liear Elliptic PDE s Elliptic partial differetial equatios frequetly arise out of coservatio statemets of the form B F d B Sdx B cotaied i bouded ope set U R. Here F, S deote respectively, the flux desity

More information

THE SYSTEMATIC AND THE RANDOM. ERRORS - DUE TO ELEMENT TOLERANCES OF ELECTRICAL NETWORKS

THE SYSTEMATIC AND THE RANDOM. ERRORS - DUE TO ELEMENT TOLERANCES OF ELECTRICAL NETWORKS R775 Philips Res. Repts 26,414-423, 1971' THE SYSTEMATIC AND THE RANDOM. ERRORS - DUE TO ELEMENT TOLERANCES OF ELECTRICAL NETWORKS by H. W. HANNEMAN Abstract Usig the law of propagatio of errors, approximated

More information

MAT1026 Calculus II Basic Convergence Tests for Series

MAT1026 Calculus II Basic Convergence Tests for Series MAT026 Calculus II Basic Covergece Tests for Series Egi MERMUT 202.03.08 Dokuz Eylül Uiversity Faculty of Sciece Departmet of Mathematics İzmir/TURKEY Cotets Mootoe Covergece Theorem 2 2 Series of Real

More information

Metric Space Properties

Metric Space Properties Metric Space Properties Math 40 Fial Project Preseted by: Michael Brow, Alex Cordova, ad Alyssa Sachez We have already poited out ad will recogize throughout this book the importace of compact sets. All

More information

Efficient GMM LECTURE 12 GMM II

Efficient GMM LECTURE 12 GMM II DECEMBER 1 010 LECTURE 1 II Efficiet The estimator depeds o the choice of the weight matrix A. The efficiet estimator is the oe that has the smallest asymptotic variace amog all estimators defied by differet

More information

Taylor expansion: Show that the TE of f(x)= sin(x) around. sin(x) = x - + 3! 5! L 7 & 8: MHD/ZAH

Taylor expansion: Show that the TE of f(x)= sin(x) around. sin(x) = x - + 3! 5! L 7 & 8: MHD/ZAH Taylor epasio: Let ƒ() be a ifiitely differetiable real fuctio. A ay poit i the eighbourhood of 0, the fuctio ƒ() ca be represeted by a power series of the followig form: X 0 f(a) f() f() ( ) f( ) ( )

More information

MATH 205 HOMEWORK #2 OFFICIAL SOLUTION. (f + g)(x) = f(x) + g(x) = f( x) g( x) = (f + g)( x)

MATH 205 HOMEWORK #2 OFFICIAL SOLUTION. (f + g)(x) = f(x) + g(x) = f( x) g( x) = (f + g)( x) MATH 205 HOMEWORK #2 OFFICIAL SOLUTION Problem 2: Do problems 7-9 o page 40 of Hoffma & Kuze. (7) We will prove this by cotradictio. Suppose that W 1 is ot cotaied i W 2 ad W 2 is ot cotaied i W 1. The

More information

Math 257: Finite difference methods

Math 257: Finite difference methods Math 257: Fiite differece methods 1 Fiite Differeces Remember the defiitio of a derivative f f(x + ) f(x) (x) = lim 0 Also recall Taylor s formula: (1) f(x + ) = f(x) + f (x) + 2 f (x) + 3 f (3) (x) +...

More information

1 Adiabatic and diabatic representations

1 Adiabatic and diabatic representations 1 Adiabatic ad diabatic represetatios 1.1 Bor-Oppeheimer approximatio The time-idepedet Schrödiger equatio for both electroic ad uclear degrees of freedom is Ĥ Ψ(r, R) = E Ψ(r, R), (1) where the full molecular

More information

DESIGN, PRODUCTION, AND APPLICATION OF A STAND FOR TESTING FRICTION OF THE BEARINGS

DESIGN, PRODUCTION, AND APPLICATION OF A STAND FOR TESTING FRICTION OF THE BEARINGS Tome V (year 7), Fascicole, (ISSN 1584 665) DESIGN, PRODUCTION, AND APPLICATION OF A STAND FOR TESTING FRICTION OF THE BEARINGS Pavlia KATSAROVA, Stilia NIKOLOV, Miltso TASHEV TECHNICAL UNIVERSITY SOFIA,BRANCH

More information

CHAPTER 8 FUNDAMENTAL SAMPLING DISTRIBUTIONS AND DATA DESCRIPTIONS. 8.1 Random Sampling. 8.2 Some Important Statistics

CHAPTER 8 FUNDAMENTAL SAMPLING DISTRIBUTIONS AND DATA DESCRIPTIONS. 8.1 Random Sampling. 8.2 Some Important Statistics CHAPTER 8 FUNDAMENTAL SAMPLING DISTRIBUTIONS AND DATA DESCRIPTIONS 8.1 Radom Samplig The basic idea of the statistical iferece is that we are allowed to draw ifereces or coclusios about a populatio based

More information

Damped Vibration of a Non-prismatic Beam with a Rotational Spring

Damped Vibration of a Non-prismatic Beam with a Rotational Spring Vibratios i Physical Systems Vol.6 (0) Damped Vibratio of a No-prismatic Beam with a Rotatioal Sprig Wojciech SOCHACK stitute of Mechaics ad Fudametals of Machiery Desig Uiversity of Techology, Czestochowa,

More information

Chapter 10 Partial Differential Equations and Fourier Series

Chapter 10 Partial Differential Equations and Fourier Series Math-33 Chapter Partial Differetial Equatios November 6, 7 Chapter Partial Differetial Equatios ad Fourier Series Math-33 Chapter Partial Differetial Equatios November 6, 7. Boudary Value Problems for

More information

REGRESSION (Physics 1210 Notes, Partial Modified Appendix A)

REGRESSION (Physics 1210 Notes, Partial Modified Appendix A) REGRESSION (Physics 0 Notes, Partial Modified Appedix A) HOW TO PERFORM A LINEAR REGRESSION Cosider the followig data poits ad their graph (Table I ad Figure ): X Y 0 3 5 3 7 4 9 5 Table : Example Data

More information

Chapter 6 Infinite Series

Chapter 6 Infinite Series Chapter 6 Ifiite Series I the previous chapter we cosidered itegrals which were improper i the sese that the iterval of itegratio was ubouded. I this chapter we are goig to discuss a topic which is somewhat

More information

Ma 530 Infinite Series I

Ma 530 Infinite Series I Ma 50 Ifiite Series I Please ote that i additio to the material below this lecture icorporated material from the Visual Calculus web site. The material o sequeces is at Visual Sequeces. (To use this li

More information

PH 425 Quantum Measurement and Spin Winter SPINS Lab 1

PH 425 Quantum Measurement and Spin Winter SPINS Lab 1 PH 425 Quatum Measuremet ad Spi Witer 23 SPIS Lab Measure the spi projectio S z alog the z-axis This is the experimet that is ready to go whe you start the program, as show below Each atom is measured

More information

CEE 522 Autumn Uncertainty Concepts for Geotechnical Engineering

CEE 522 Autumn Uncertainty Concepts for Geotechnical Engineering CEE 5 Autum 005 Ucertaity Cocepts for Geotechical Egieerig Basic Termiology Set A set is a collectio of (mutually exclusive) objects or evets. The sample space is the (collectively exhaustive) collectio

More information

Chapter 7: The z-transform. Chih-Wei Liu

Chapter 7: The z-transform. Chih-Wei Liu Chapter 7: The -Trasform Chih-Wei Liu Outlie Itroductio The -Trasform Properties of the Regio of Covergece Properties of the -Trasform Iversio of the -Trasform The Trasfer Fuctio Causality ad Stability

More information

Lecture 4. We also define the set of possible values for the random walk as the set of all x R d such that P(S n = x) > 0 for some n.

Lecture 4. We also define the set of possible values for the random walk as the set of all x R d such that P(S n = x) > 0 for some n. Radom Walks ad Browia Motio Tel Aviv Uiversity Sprig 20 Lecture date: Mar 2, 20 Lecture 4 Istructor: Ro Peled Scribe: Lira Rotem This lecture deals primarily with recurrece for geeral radom walks. We preset

More information

Lecture 6 Chi Square Distribution (χ 2 ) and Least Squares Fitting

Lecture 6 Chi Square Distribution (χ 2 ) and Least Squares Fitting Lecture 6 Chi Square Distributio (χ ) ad Least Squares Fittig Chi Square Distributio (χ ) Suppose: We have a set of measuremets {x 1, x, x }. We kow the true value of each x i (x t1, x t, x t ). We would

More information

Probability, Expectation Value and Uncertainty

Probability, Expectation Value and Uncertainty Chapter 1 Probability, Expectatio Value ad Ucertaity We have see that the physically observable properties of a quatum system are represeted by Hermitea operators (also referred to as observables ) such

More information

EXPERIMENT OF SIMPLE VIBRATION

EXPERIMENT OF SIMPLE VIBRATION EXPERIMENT OF SIMPLE VIBRATION. PURPOSE The purpose of the experimet is to show free vibratio ad damped vibratio o a system havig oe degree of freedom ad to ivestigate the relatioship betwee the basic

More information

Math 61CM - Solutions to homework 3

Math 61CM - Solutions to homework 3 Math 6CM - Solutios to homework 3 Cédric De Groote October 2 th, 208 Problem : Let F be a field, m 0 a fixed oegative iteger ad let V = {a 0 + a x + + a m x m a 0,, a m F} be the vector space cosistig

More information

Axioms of Measure Theory

Axioms of Measure Theory MATH 532 Axioms of Measure Theory Dr. Neal, WKU I. The Space Throughout the course, we shall let X deote a geeric o-empty set. I geeral, we shall ot assume that ay algebraic structure exists o X so that

More information

FACULTY OF MATHEMATICAL STUDIES MATHEMATICS FOR PART I ENGINEERING. Lectures

FACULTY OF MATHEMATICAL STUDIES MATHEMATICS FOR PART I ENGINEERING. Lectures FACULTY OF MATHEMATICAL STUDIES MATHEMATICS FOR PART I ENGINEERING Lectures MODULE 5 STATISTICS II. Mea ad stadard error of sample data. Biomial distributio. Normal distributio 4. Samplig 5. Cofidece itervals

More information

CSE 202 Homework 1 Matthias Springer, A Yes, there does always exist a perfect matching without a strong instability.

CSE 202 Homework 1 Matthias Springer, A Yes, there does always exist a perfect matching without a strong instability. CSE 0 Homework 1 Matthias Spriger, A9950078 1 Problem 1 Notatio a b meas that a is matched to b. a < b c meas that b likes c more tha a. Equality idicates a tie. Strog istability Yes, there does always

More information

Lecture 22: Review for Exam 2. 1 Basic Model Assumptions (without Gaussian Noise)

Lecture 22: Review for Exam 2. 1 Basic Model Assumptions (without Gaussian Noise) Lecture 22: Review for Exam 2 Basic Model Assumptios (without Gaussia Noise) We model oe cotiuous respose variable Y, as a liear fuctio of p umerical predictors, plus oise: Y = β 0 + β X +... β p X p +

More information

Product measures, Tonelli s and Fubini s theorems For use in MAT3400/4400, autumn 2014 Nadia S. Larsen. Version of 13 October 2014.

Product measures, Tonelli s and Fubini s theorems For use in MAT3400/4400, autumn 2014 Nadia S. Larsen. Version of 13 October 2014. Product measures, Toelli s ad Fubii s theorems For use i MAT3400/4400, autum 2014 Nadia S. Larse Versio of 13 October 2014. 1. Costructio of the product measure The purpose of these otes is to preset the

More information

(c) Write, but do not evaluate, an integral expression for the volume of the solid generated when R is

(c) Write, but do not evaluate, an integral expression for the volume of the solid generated when R is Calculus BC Fial Review Name: Revised 7 EXAM Date: Tuesday, May 9 Remiders:. Put ew batteries i your calculator. Make sure your calculator is i RADIAN mode.. Get a good ight s sleep. Eat breakfast. Brig:

More information

7.1 Convergence of sequences of random variables

7.1 Convergence of sequences of random variables Chapter 7 Limit theorems Throughout this sectio we will assume a probability space (Ω, F, P), i which is defied a ifiite sequece of radom variables (X ) ad a radom variable X. The fact that for every ifiite

More information

CS / MCS 401 Homework 3 grader solutions

CS / MCS 401 Homework 3 grader solutions CS / MCS 401 Homework 3 grader solutios assigmet due July 6, 016 writte by Jāis Lazovskis maximum poits: 33 Some questios from CLRS. Questios marked with a asterisk were ot graded. 1 Use the defiitio of

More information