ES240 Solid Mechanics Z. Suo. Principal stress. . Write in the matrix notion, and we have

Size: px
Start display at page:

Download "ES240 Solid Mechanics Z. Suo. Principal stress. . Write in the matrix notion, and we have"

Transcription

1 ES4 Sold Mehs Z Suo Prpl stress Prpl Stress Imge mterl prtle stte o stress The stte o stress s xed, but we represet the mterl prtle my wys by uttg ubes deret orettos For y gve stte o stress, t s lwys possble to ut ube sutble oretto, suh tht the stress ompoets o ll the ube es re orml to the es, d there re o sher stresses o the ube es These ube es re lled the prpl ples, the orml vetors to these es the prpl dretos, d the stresses o them the prpl stresses Exmples Uxl teso Equl bxl teso Hydrostt pressure Pure sher s the sme stte o stress s the ombto o pullg d pressg 45 Gve stress stte, how to d the prpl stresses? Whe ple s the prpl ple, the trto o the ple s orml to the ple, mely, the trto vetor t must be the sme dreto s the ut orml vetor Let the mgtude o the trto be O the prpl ple, the trto vetor s the dreto o the orml vetor, t Wrte the mtrx oto, d we hve t t t Here both t d re vetors, but s slr represetg the mgtude o the prpl stress Rell tht the trto vetor s the stress mtrx tmes the orml vetor, so tht Ths s egevlue problem Whe the stress stte s kow, e, the stress mtrx s gve, solve the bove egevlue problem to determe the egevlue d the egevetor The egevlue s the prpl stress, d the egevetor s the prpl dreto Ler lgebr o egevlues Beuse the stress tesor s by symmetr mtrx, you lwys d three rel egevlues, e, prpl stresses,, b, We dstgush three ses: () I the three prpl stresses re uequl, the three prpl dretos re orthogol (eg, pure sher stte) () I two prpl stresses re equl, but the thrd s deret, the two equl prpl stresses be y dretos ple, d the thrd prpl dreto s orml to the ple (eg, pure tesle stte) () I ll the three prpl stresses re equl, y dreto s prpl dreto Ths stress stte s lled hydrostt stte Mxmum orml stress Why do we re bout the prpl stress? Chlks re mde o brttle mterl: they brek by tesle stress, ot by sher stress Whe hlk s uder 9/8/ Prpl stress-

2 ES4 Sold Mehs Z Suo bedg, the tesle stress s log the xl dreto o the hlk, so tht the hlk breks o ple orml to the xl dreto Whe hlk s uder torso, the mxmum tesle stress s 45 rom the xl dreto, so tht the hlk breks dreto 45 rom the xl dreto (The rture sure o the hlk uder torso s ot ple, beuse o some D eets) We re bout the prpl stress beuse brttle mterls l by tesle stress, d we wt to d the mxmum tesle stress Let s order the three prpl stresses s b Ths orderg tkes to osderto the sgs: ompressve stress (egtve) s smller th tesle stress (postve) O rbtrry ple, the trto vetor my be deomposed to two ompoets: oe ompoet orml the ple (the orml stress), d the other ompoet prllel to the ple (the sher stress) Obvously, whe you look t ple wth deret orml vetor, you d deret orml d sher stresses You wll be delghted by the ollowg theorem: O ll ples, the prpl ple orrespodg to hs the mxmum orml stress Mxmum sher stress Why do we re bout the mxmum sher stress? Most metls re dutle mterls: they l by plst yeldg Whe mterl s uder omplex stress stte, t s kow emprlly tht yeldg rst ours o ple wth mxmum sher stress To d the mxmum sher stress d the prtulr ple, you re helped by the ollowg theorem: The mxmum sher stress s τ ( )/ mx τ mx ts o ple wth the orml vetor 45 rom the prpl dretos d A proo o the bove theorems s outled below Cosder system o oordtes tht ode wth three orthogol dretos o the prpl stresses,,, The osder rbtrry ple whose ut orml vetor hs ompoets,, ths oordte system The ompoets o the stress tesor ths oordte system s b Thus, o the ple wth ut vetor (,, ), the trto vetor s (, b, ) The orml stress o the ple s + + b + + We eed to mxmze uder the ostrt tht The sher stress o the ple τ s gve by ( ) + ( ) + ( ) ( + ) τ b b We eed to mxmze τ uder the ostrt tht b 9/8/ Prpl stress-

3 ES4 Sold Mehs Z Suo Chge o Coordtes The dreto-ose mtrx reltg two bses I the D spe, let e, e d e be orthoorml bss, mely, e e δ The bse vetors re ordered to ollow the rght-hd rule Let e, e, e be ew orthoorml bss, mely, e e δ Let the gle betwee the two vetors e d e be θ Deote the dreto ose o the two vetors by l e os We ollow the oveto tht the rst dex o l reers to oordte the old bss, d the seod to oordte the ew bss For the two bses, there re totl o 9 dreto oses We lst l s by mtrx By our oveto, the rows reer to the old bss, d the olums to the ew bss Note tht l s the ompoet o the vetor e proeted o the vetor e We express eh ew bse vetor s ler ombto o the three old bse vetors: e l e + l e + l e I you re tred o wrtg sums lke ths, you bbrevte t s e l e, wth the oveto tht repeted dex mples summto over,, Beuse the sum s the sme whtever the repeted dex s med, suh dex s lled dummy dex Smlrly, we express the old bss s ler ombto o the ew bss: e l e + le + le Usg the summto oveto, we wrte more osely s e e l Trsormto o ompoets o vetor due to hge o bss Let be vetor It s ler ombto o the bse vetors: e, where,, re the ompoets o the vetor, d re ommoly wrtte s olum Cosder the vetor potg rom Cmbrdge to Bosto Whe the bss s hged, the vetor betwee Cmbrdge d Bosto rems uhged, but the ompoets o the vetor do hge Let,, be the ompoets o the vetor the ew bss, mely, e Rell the trsormto betwee the two sets o bss, θ e l e, we wrte tht e l e A omprso betwee the two expressos gves tht l Thus, the ompoet olum the ew bss s the trspose o the dreto-ose mtrx tmes the ompoet olum the old bss Smlrly, we show tht 9/8/ Prpl stress-

4 ES4 Sold Mehs Z Suo l The ompoet olum the old bss s the dreto-ose mtrx tmes the ompoet olum the old bss Trsormto o stress ompoets due to hge o bss The stress tesor,, desrbes the stte o stress suered by mterl prtle Represet the mterl prtle by ube The stress ompoets re the ore per ut re o 6 es o the ube The stress tesor s represeted by by symmetr mtrx The stte o stress o mterl prtle s physl obet, d s depedet o your hoe o the bss (e, how you ut ube to represet the prtle) However, the ompoets o the stress tesor do deped o your hoe o the bss How do we trsorm the stress ompoets whe the bss s hged? Cosder the stress stte o mterl prtle, d the trto vetor o gve ple I the old bss e, e d e, deote the ompoets o the stress stte by, the ompoets o the ut vetor orml to the ple by, d the ompoets o the trto vetor o the ple by t Usg the summto oveto, we wrte the trto-stress equtos s t Rell tht we obted ths relto by the ble o ores o tetrhedro I the lguge o ler lgebr, we ll the stress s ler opertor tht mps the ut orml vetor o ple to the trto vetor tg o the ple Smlrly, the ew bsse, e, e, deote the ompoets o the stress stte by, the ompoets o the ut vetor orml to the ple by, d the ompoets o the trto vetor o the ple by t Fore ble requres tht t () We ow exme the reltos betwee the ompoets the old bss d those the ew bss The trto s vetor, so tht ts ompoets trsorm s t l t Isert t to the bove, d we obt tht t l l Cosequetly, we obt tht t l l The ut orml vetor trsorms s (b) Equtos () d (b) re vld or y hoe o the ple Cosequetly, we must requre tht l l Thus, the stress-ompoet mtrx the ew bss s the produt o three mtres: the trspose o the dreto-ose mtrx, the stress-ompoet mtrx the old bss, d the dreto-ose mtrx Slrs, vetors, d tesors Whe the bss s hged, slr (eg, temperture, eergy, d mss) does ot hge, the ompoets o vetor trsorm s l, d the ompoets o tesor trsorm s l l Ths trsormto dees the seod-rk tesor By logy, vetor s rst-rk tesor, d slr s zeroth-rk tesor We lso smlrly dee tesors o hgher rks Multler lgebr The rule o the bove trsormto s bsed o oly oe t: the stress s ler mp rom oe vetor to other vetor You geerte ew tesor rom 9/8/ Prpl stress-4

5 ES4 Sold Mehs Z Suo ler mp rom oe tesor to other tesor You lso geerte tesor by bler orm, eg, bler mp rom two vetors to slr O ourse, multler mp o severl tesors to tesor s yet other tesor Cosequetly, ll tesors ollow smlr rule uder hge o bss We wrte ths rule g or thrd-rk tesor: g g l l l γ k kγ Ivrts o tesor A slr s vrt uder y hge o bss Whe the bss hges, the ompoets o vetor hge, but the legth o the vetor s vrt Let be vetor, d be the ompoets o the vetor or gve bss The legth o the vetor s the squre root o The dex s dummy Thus, ths ombto o the ompoets o vetor s slr, whh s vrt uder y hge o bss For vetor, there s oly oe depedet vrt Ay other vrt o the vetor s uto o the legth o the vetor Ths observto be exteded to hgh-order tesors By deto, vrt o tesor s slr ormed by ombto o the ompoets o the tesor For exmple, or symmetr seod-rk tesor, we orm three depedet vrts:,, k k I eh se, ll des re dummy, resultg slr Ay other vrt o the tesor s uto o the bove three vrts Exerse For osymmetr seod-rk tesor, gve ll the depedet vrts Wrte eh vrt usg the summto oveto, d the expltly ll ts terms Exerse Gve ll the depedet vrts o thrd-rk tesor A spel se: the ew bss d the old bss der by gle θ roud the xs e The sg oveto or θ ollows the rght-hd rule The dreto oses re e osθ, e sθ, e, e e sθ, e osθ, e, e e, e, e e θ Cosequetly, the mtrx o the dreto oses s osθ sθ θ [ ] e l sθ osθ Thus, The ompoets o vetor trsorm s osθ sθ sθ osθ 9/8/ Prpl stress-5

6 ES4 Sold Mehs Z Suo Thus, The ompoets o stress stte trsorm s osθ sθ sθ osθ osθ + sθ + sθ osθ osθ sθ + + osθ + s θ + osθ s θ s θ + osθ osθ + sθ sθ + osθ sθ osθ Stte o ple stress A eve more spel se s tht the stress ompoets out o the ple re bset, mely, + + osθ + s θ + osθ s θ s θ + osθ I Beer s Seto 74, these equtos re represeted by grph (e, Mohr s rle) I ths se, e s oe prpl dreto, d the prpl stress ths dreto s zero To d the other two prpl dretos, we set, so tht the two prpl dretos re t the gle θ p rom the e d e dretos Ths gle s gve by τ t θ p The two prpl stresses re gve by + ± + We eed to order these two prpl stresses d the zero prpl stress the e dreto The mxmum sher stress s the hl o the deree betwee the mxmum prpl stress d the mmum prpl stress The stte o str o mterl prtle s seod-rk tesor I the old bss, the 9/8/ Prpl stress-6

7 ES4 Sold Mehs Z Suo oordtes o mterl prtle re ( x, x, x ) re u ( x, x, x, t) ( x, x, x ), d the ompoets o the dsplemet eld re u ( x, x, x, t) l u, d the ompoets o the dsplemet eld I the ew bss, the oordtes o the sme mterl prtle re u d x l x, so tht u x l u x x x l l u x Rell tht Thus, the grdets o the dsplemet eld, u / x, orm the ompoets o seod-rk tesor Cosequetly, the stte o str, beg the symmetr prt o the dsplemet grdet, s seod-rk tesor Whe the bss s hged, the ompoets o the str stte trsorm s ε ε l l 9/8/ Prpl stress-7

1 4 6 is symmetric 3 SPECIAL MATRICES 3.1 SYMMETRIC MATRICES. Defn: A matrix A is symmetric if and only if A = A, i.e., a ij =a ji i, j. Example 3.1.

1 4 6 is symmetric 3 SPECIAL MATRICES 3.1 SYMMETRIC MATRICES. Defn: A matrix A is symmetric if and only if A = A, i.e., a ij =a ji i, j. Example 3.1. SPECIAL MATRICES SYMMETRIC MATRICES Def: A mtr A s symmetr f d oly f A A, e,, Emple A s symmetr Def: A mtr A s skew symmetr f d oly f A A, e,, Emple A s skew symmetr Remrks: If A s symmetr or skew symmetr,

More information

CHAPTER 5 Vectors and Vector Space

CHAPTER 5 Vectors and Vector Space HAPTE 5 Vetors d Vetor Spe 5. Alger d eometry of Vetors. Vetor A ordered trple,,, where,, re rel umers. Symol:, B,, A mgtude d dreto.. Norm of vetor,, Norm =,, = = mgtude. Slr multplto Produt of slr d

More information

Chapter Gauss-Seidel Method

Chapter Gauss-Seidel Method Chpter 04.08 Guss-Sedel Method After redg ths hpter, you should be ble to:. solve set of equtos usg the Guss-Sedel method,. reogze the dvtges d ptflls of the Guss-Sedel method, d. determe uder wht odtos

More information

Matrix. Definition 1... a1 ... (i) where a. are real numbers. for i 1, 2,, m and j = 1, 2,, n (iii) A is called a square matrix if m n.

Matrix. Definition 1... a1 ... (i) where a. are real numbers. for i 1, 2,, m and j = 1, 2,, n (iii) A is called a square matrix if m n. Mtrx Defto () s lled order of m mtrx, umer of rows ( 橫行 ) umer of olums ( 直列 ) m m m where j re rel umers () B j j for,,, m d j =,,, () s lled squre mtrx f m (v) s lled zero mtrx f (v) s lled detty mtrx

More information

GENERALIZED OPERATIONAL RELATIONS AND PROPERTIES OF FRACTIONAL HANKEL TRANSFORM

GENERALIZED OPERATIONAL RELATIONS AND PROPERTIES OF FRACTIONAL HANKEL TRANSFORM S. Res. Chem. Commu.: (3 8-88 ISSN 77-669 GENERLIZED OPERTIONL RELTIONS ND PROPERTIES OF FRCTIONL NKEL TRNSFORM R. D. TYWDE *. S. GUDDE d V. N. MLLE b Pro. Rm Meghe Isttute o Teholog & Reserh Bder MRVTI

More information

Area and the Definite Integral. Area under Curve. The Partition. y f (x) We want to find the area under f (x) on [ a, b ]

Area and the Definite Integral. Area under Curve. The Partition. y f (x) We want to find the area under f (x) on [ a, b ] Are d the Defte Itegrl 1 Are uder Curve We wt to fd the re uder f (x) o [, ] y f (x) x The Prtto We eg y prttog the tervl [, ] to smller su-tervls x 0 x 1 x x - x -1 x 1 The Bsc Ide We the crete rectgles

More information

Chapter Unary Matrix Operations

Chapter Unary Matrix Operations Chpter 04.04 Ury trx Opertos After redg ths chpter, you should be ble to:. kow wht ury opertos mes,. fd the trspose of squre mtrx d t s reltoshp to symmetrc mtrces,. fd the trce of mtrx, d 4. fd the ermt

More information

ME 501A Seminar in Engineering Analysis Page 1

ME 501A Seminar in Engineering Analysis Page 1 Mtr Trsformtos usg Egevectors September 8, Mtr Trsformtos Usg Egevectors Lrry Cretto Mechcl Egeerg A Semr Egeerg Alyss September 8, Outle Revew lst lecture Trsformtos wth mtr of egevectors: = - A ermt

More information

Soo King Lim Figure 1: Figure 2: Figure 3: Figure 4: Figure 5: Figure 6: Figure 7: Figure 8: Figure 9: Figure 10: Figure 11:

Soo King Lim Figure 1: Figure 2: Figure 3: Figure 4: Figure 5: Figure 6: Figure 7: Figure 8: Figure 9: Figure 10: Figure 11: Soo Kg Lm 1.0 Nested Fctorl Desg... 1.1 Two-Fctor Nested Desg... 1.1.1 Alss of Vrce... Exmple 1... 5 1.1. Stggered Nested Desg for Equlzg Degree of Freedom... 7 1.1. Three-Fctor Nested Desg... 8 1.1..1

More information

3/20/2013. Splines There are cases where polynomial interpolation is bad overshoot oscillations. Examplef x. Interpolation at -4,-3,-2,-1,0,1,2,3,4

3/20/2013. Splines There are cases where polynomial interpolation is bad overshoot oscillations. Examplef x. Interpolation at -4,-3,-2,-1,0,1,2,3,4 // Sples There re ses where polyoml terpolto s d overshoot oslltos Emple l s Iterpolto t -,-,-,-,,,,,.... - - - Ide ehd sples use lower order polyomls to oet susets o dt pots mke oetos etwee djet sples

More information

In Calculus I you learned an approximation method using a Riemann sum. Recall that the Riemann sum is

In Calculus I you learned an approximation method using a Riemann sum. Recall that the Riemann sum is Mth Sprg 08 L Approxmtg Dete Itegrls I Itroducto We hve studed severl methods tht llow us to d the exct vlues o dete tegrls However, there re some cses whch t s ot possle to evlute dete tegrl exctly I

More information

Modeling uncertainty using probabilities

Modeling uncertainty using probabilities S 1571 Itroduto to I Leture 23 Modelg uertty usg probbltes Mlos Huskreht mlos@s.ptt.edu 5329 Seott Squre dmstrto Fl exm: Deember 11 2006 12:00-1:50pm 5129 Seott Squre Uertty To mke dgost feree possble

More information

ICS141: Discrete Mathematics for Computer Science I

ICS141: Discrete Mathematics for Computer Science I Uversty o Hw ICS: Dscrete Mthemtcs or Computer Scece I Dept. Iormto & Computer Sc., Uversty o Hw J Stelovsy bsed o sldes by Dr. Be d Dr. Stll Orgls by Dr. M. P. Fr d Dr. J.L. Gross Provded by McGrw-Hll

More information

A Technique for Constructing Odd-order Magic Squares Using Basic Latin Squares

A Technique for Constructing Odd-order Magic Squares Using Basic Latin Squares Itertol Jourl of Scetfc d Reserch Publctos, Volume, Issue, My 0 ISSN 0- A Techque for Costructg Odd-order Mgc Squres Usg Bsc Lt Squres Tomb I. Deprtmet of Mthemtcs, Mpur Uversty, Imphl, Mpur (INDIA) tombrom@gml.com

More information

Asymptotic Dominance Problems. is not constant but for n 0, f ( n) 11. 0, so that for n N f

Asymptotic Dominance Problems. is not constant but for n 0, f ( n) 11. 0, so that for n N f Asymptotc Domce Prolems Dsply ucto : N R tht s Ο( ) ut s ot costt 0 = 0 The ucto ( ) = > 0 s ot costt ut or 0, ( ) Dee the relto " " o uctos rom N to R y g d oly = Ο( g) Prove tht s relexve d trstve (Recll:

More information

MTH 146 Class 7 Notes

MTH 146 Class 7 Notes 7.7- Approxmte Itegrto Motvto: MTH 46 Clss 7 Notes I secto 7.5 we lered tht some defte tegrls, lke x e dx, cot e wrtte terms of elemetry fuctos. So, good questo to sk would e: How c oe clculte somethg

More information

Sequences and summations

Sequences and summations Lecture 0 Sequeces d summtos Istructor: Kgl Km CSE) E-ml: kkm0@kokuk.c.kr Tel. : 0-0-9 Room : New Mleum Bldg. 0 Lb : New Egeerg Bldg. 0 All sldes re bsed o CS Dscrete Mthemtcs for Computer Scece course

More information

SPH3UW Unit 7.5 Snell s Law Page 1 of Total Internal Reflection occurs when the incoming refraction angle is

SPH3UW Unit 7.5 Snell s Law Page 1 of Total Internal Reflection occurs when the incoming refraction angle is SPH3UW Uit 7.5 Sell s Lw Pge 1 of 7 Notes Physis Tool ox Refrtio is the hge i diretio of wve due to hge i its speed. This is most ommoly see whe wve psses from oe medium to other. Idex of refrtio lso lled

More information

Optimality of Strategies for Collapsing Expanded Random Variables In a Simple Random Sample Ed Stanek

Optimality of Strategies for Collapsing Expanded Random Variables In a Simple Random Sample Ed Stanek Optmlt of Strteges for Collpsg Expe Rom Vrles Smple Rom Smple E Stek troucto We revew the propertes of prectors of ler comtos of rom vrles se o rom vrles su-spce of the orgl rom vrles prtculr, we ttempt

More information

COMPLEX NUMBERS AND DE MOIVRE S THEOREM

COMPLEX NUMBERS AND DE MOIVRE S THEOREM COMPLEX NUMBERS AND DE MOIVRE S THEOREM OBJECTIVE PROBLEMS. s equl to b d. 9 9 b 9 9 d. The mgr prt of s 5 5 b 5. If m, the the lest tegrl vlue of m s b 8 5. The vlue of 5... s f s eve, f s odd b f s eve,

More information

Mathematically, integration is just finding the area under a curve from one point to another. It is b

Mathematically, integration is just finding the area under a curve from one point to another. It is b Numerl Metods or Eg [ENGR 9] [Lyes KADEM 7] CHAPTER VI Numerl Itegrto Tops - Rem sums - Trpezodl rule - Smpso s rule - Rrdso s etrpolto - Guss qudrture rule Mtemtlly, tegrto s just dg te re uder urve rom

More information

Available online through

Available online through Avlble ole through wwwmfo FIXED POINTS FOR NON-SELF MAPPINGS ON CONEX ECTOR METRIC SPACES Susht Kumr Moht* Deprtmet of Mthemtcs West Begl Stte Uverst Brst 4 PrgsNorth) Kolt 76 West Begl Id E-ml: smwbes@yhoo

More information

Differential Entropy 吳家麟教授

Differential Entropy 吳家麟教授 Deretl Etropy 吳家麟教授 Deto Let be rdom vrble wt cumultve dstrbuto ucto I F s cotuous te r.v. s sd to be cotuous. Let = F we te dervtve s deed. I te s clled te pd or. Te set were > 0 s clled te support set

More information

Chapter 7. Bounds for weighted sums of Random Variables

Chapter 7. Bounds for weighted sums of Random Variables Chpter 7. Bouds for weghted sums of Rdom Vrbles 7. Itroducto Let d 2 be two depedet rdom vrbles hvg commo dstrbuto fucto. Htczeko (998 d Hu d L (2000 vestgted the Rylegh dstrbuto d obted some results bout

More information

Lecture 3: Review of Linear Algebra and MATLAB

Lecture 3: Review of Linear Algebra and MATLAB eture 3: Revew of er Aler AAB Vetor mtr otto Vetors tres Vetor spes er trsformtos Eevlues eevetors AAB prmer Itrouto to Ptter Reoto Rro Guterrez-su Wrht Stte Uverst Vetor mtr otto A -mesol (olum) vetor

More information

Linear Algebra Concepts

Linear Algebra Concepts Ler Algebr Cocepts Ke Kreutz-Delgdo (Nuo Vscocelos) ECE 75A Wter 22 UCSD Vector spces Defto: vector spce s set H where ddto d sclr multplcto re defed d stsf: ) +( + ) (+ )+ 5) l H 2) + + H 6) 3) H, + 7)

More information

DATA FITTING. Intensive Computation 2013/2014. Annalisa Massini

DATA FITTING. Intensive Computation 2013/2014. Annalisa Massini DATA FITTING Itesve Computto 3/4 Als Mss Dt fttg Dt fttg cocers the problem of fttg dscrete dt to obt termedte estmtes. There re two geerl pproches two curve fttg: Iterpolto Dt s ver precse. The strteg

More information

Chapter 2. LOGARITHMS

Chapter 2. LOGARITHMS Chpter. LOGARITHMS Dte: - 009 A. INTRODUCTION At the lst hpter, you hve studied bout Idies d Surds. Now you re omig to Logrithms. Logrithm is ivers of idies form. So Logrithms, Idies, d Surds hve strog

More information

Introduction to Matrix Algebra

Introduction to Matrix Algebra Itrodutio to Mtri Alger George H Olso, Ph D Dotorl Progrm i Edutiol Ledership Applhi Stte Uiversit Septemer Wht is mtri? Dimesios d order of mtri A p q dimesioed mtri is p (rows) q (olums) rr of umers,

More information

xl yl m n m n r m r m r r! The inner sum in the last term simplifies because it is a binomial expansion of ( x + y) r : e +.

xl yl m n m n r m r m r r! The inner sum in the last term simplifies because it is a binomial expansion of ( x + y) r : e +. Ler Trsfortos d Group Represettos Hoework #3 (06-07, Aswers Q-Q re further exerses oer dots, self-dot trsfortos, d utry trsfortos Q3-6 volve roup represettos Of these, Q3 d Q4 should e quk Q5 s espelly

More information

The z-transform. LTI System description. Prof. Siripong Potisuk

The z-transform. LTI System description. Prof. Siripong Potisuk The -Trsform Prof. Srpog Potsuk LTI System descrpto Prevous bss fucto: ut smple or DT mpulse The put sequece s represeted s ler combto of shfted DT mpulses. The respose s gve by covoluto sum of the put

More information

Chapter 3 Supplemental Text Material

Chapter 3 Supplemental Text Material S3-. The Defto of Fctor Effects Chpter 3 Supplemetl Text Mterl As oted Sectos 3- d 3-3, there re two wys to wrte the model for sglefctor expermet, the mes model d the effects model. We wll geerlly use

More information

Chapter 1 Vector Spaces

Chapter 1 Vector Spaces Chpter Vetor pes - Vetor pes Ler Comtos Vetor spe V V s set over fel F f V F! + V. Eg. R s vetor spe. For R we hek -4=-4-4R -7=-7-7R et. Eg. how tht the set of ll polomls PF wth oeffets from F s vetor

More information

this is the indefinite integral Since integration is the reverse of differentiation we can check the previous by [ ]

this is the indefinite integral Since integration is the reverse of differentiation we can check the previous by [ ] Atervtves The Itegrl Atervtves Ojectve: Use efte tegrl otto for tervtves. Use sc tegrto rules to f tervtves. Aother mportt questo clculus s gve ervtve f the fucto tht t cme from. Ths s the process kow

More information

CURVE FITTING LEAST SQUARES METHOD

CURVE FITTING LEAST SQUARES METHOD Nuercl Alss for Egeers Ger Jord Uverst CURVE FITTING Although, the for of fucto represetg phscl sste s kow, the fucto tself ot be kow. Therefore, t s frequetl desred to ft curve to set of dt pots the ssued

More information

Linear Algebra Concepts

Linear Algebra Concepts Ler Algebr Cocepts Nuo Vscocelos (Ke Kreutz-Delgdo) UCSD Vector spces Defto: vector spce s set H where ddto d sclr multplcto re defed d stsf: ) +( + ) = (+ )+ 5) H 2) + = + H 6) = 3) H, + = 7) ( ) = (

More information

VECTORS VECTORS VECTORS VECTORS. 2. Vector Representation. 1. Definition. 3. Types of Vectors. 5. Vector Operations I. 4. Equal and Opposite Vectors

VECTORS VECTORS VECTORS VECTORS. 2. Vector Representation. 1. Definition. 3. Types of Vectors. 5. Vector Operations I. 4. Equal and Opposite Vectors 1. Defnton A vetor s n entt tht m represent phsl quntt tht hs mgntude nd dreton s opposed to slr tht ls dreton.. Vetor Representton A vetor n e represented grphll n rrow. The length of the rrow s the mgntude

More information

The Z-Transform in DSP Lecture Andreas Spanias

The Z-Transform in DSP Lecture Andreas Spanias The Z-Trsform DSP eture - Adres Ss ss@su.edu 6 Coyrght 6 Adres Ss -- Poles d Zeros of I geerl the trsfer futo s rtol; t hs umertor d deomtor olyoml. The roots of the umertor d deomtor olyomls re lled the

More information

Chapter 12-b Integral Calculus - Extra

Chapter 12-b Integral Calculus - Extra C - Itegrl Clulus Cpter - Itegrl Clulus - Etr Is Newto Toms Smpso BONUS Itroduto to Numerl Itegrto C - Itegrl Clulus Numerl Itegrto Ide s to do tegrl smll prts, lke te wy we preseted tegrto: summto. Numerl

More information

ON NILPOTENCY IN NONASSOCIATIVE ALGEBRAS

ON NILPOTENCY IN NONASSOCIATIVE ALGEBRAS Jourl of Algebr Nuber Theory: Advces d Applctos Volue 6 Nuber 6 ges 85- Avlble t http://scetfcdvces.co. DOI: http://dx.do.org/.864/t_779 ON NILOTENCY IN NONASSOCIATIVE ALGERAS C. J. A. ÉRÉ M. F. OUEDRAOGO

More information

Project 3: Using Identities to Rewrite Expressions

Project 3: Using Identities to Rewrite Expressions MAT 5 Projet 3: Usig Idetities to Rewrite Expressios Wldis I lger, equtios tht desrie properties or ptters re ofte lled idetities. Idetities desrie expressio e repled with equl or equivlet expressio tht

More information

PubH 7405: REGRESSION ANALYSIS REGRESSION IN MATRIX TERMS

PubH 7405: REGRESSION ANALYSIS REGRESSION IN MATRIX TERMS PubH 745: REGRESSION ANALSIS REGRESSION IN MATRIX TERMS A mtr s dspl of umbers or umercl quttes ld out rectgulr rr of rows d colums. The rr, or two-w tble of umbers, could be rectgulr or squre could be

More information

PROBLEM SET #4 SOLUTIONS by Robert A. DiStasio Jr.

PROBLEM SET #4 SOLUTIONS by Robert A. DiStasio Jr. PROBLM ST # SOLUTIONS y Roert. DStso Jr. Q. Prove tht the MP eergy s sze-osstet for two ftely seprted losed shell frgmets. The MP orrelto eergy s gve the sp-ortl ss s: vrt vrt MP orr Δ. or two moleulr

More information

Analytical Approach for the Solution of Thermodynamic Identities with Relativistic General Equation of State in a Mixture of Gases

Analytical Approach for the Solution of Thermodynamic Identities with Relativistic General Equation of State in a Mixture of Gases Itertol Jourl of Advced Reserch Physcl Scece (IJARPS) Volume, Issue 5, September 204, PP 6-0 ISSN 2349-7874 (Prt) & ISSN 2349-7882 (Ole) www.rcourls.org Alytcl Approch for the Soluto of Thermodymc Idettes

More information

Chapter 1. Infinite Sequences and Series. 1.1 Sequences. A sequence is a set of numbers written in a definite order

Chapter 1. Infinite Sequences and Series. 1.1 Sequences. A sequence is a set of numbers written in a definite order hpter Ite Sequeces d Seres. Sequeces A sequece s set o umers wrtte dete order,,,... The umer s clled the rst term, s clled the secod term, d geerl s th clled the term. Deto.. The sequece {,,...} s usull

More information

1. (25 points) Use the limit definition of the definite integral and the sum formulas to compute. [1 x + x2

1. (25 points) Use the limit definition of the definite integral and the sum formulas to compute. [1 x + x2 Mth 3, Clculus II Fil Exm Solutios. (5 poits) Use the limit defiitio of the defiite itegrl d the sum formuls to compute 3 x + x. Check your swer by usig the Fudmetl Theorem of Clculus. Solutio: The limit

More information

Chapter Simpson s 1/3 Rule of Integration. ( x)

Chapter Simpson s 1/3 Rule of Integration. ( x) Cpter 7. Smpso s / Rule o Itegrto Ater redg ts pter, you sould e le to. derve te ormul or Smpso s / rule o tegrto,. use Smpso s / rule t to solve tegrls,. develop te ormul or multple-segmet Smpso s / rule

More information

Section 11.5 Notes Page Partial Fraction Decomposition. . You will get: +. Therefore we come to the following: x x

Section 11.5 Notes Page Partial Fraction Decomposition. . You will get: +. Therefore we come to the following: x x Setio Notes Pge Prtil Frtio Deompositio Suppose we were sked to write the followig s sigle frtio: We would eed to get ommo deomitors: You will get: Distributig o top will give you: 8 This simplifies to:

More information

1.3 Continuous Functions and Riemann Sums

1.3 Continuous Functions and Riemann Sums mth riem sums, prt 0 Cotiuous Fuctios d Riem Sums I Exmple we sw tht lim Lower() = lim Upper() for the fuctio!! f (x) = + x o [0, ] This is o ccidet It is exmple of the followig theorem THEOREM Let f be

More information

Section 2:00 ~ 2:50 pm Thursday in Maryland 202 Sep. 29, 2005

Section 2:00 ~ 2:50 pm Thursday in Maryland 202 Sep. 29, 2005 Seto 2:00 ~ 2:50 pm Thursday Marylad 202 Sep. 29, 2005. Homework assgmets set ad 2 revews: Set : P. A box otas 3 marbles, red, gree, ad blue. Cosder a expermet that ossts of takg marble from the box, the

More information

B. Examples 1. Finite Sums finite sums are an example of Riemann Sums in which each subinterval has the same length and the same x i

B. Examples 1. Finite Sums finite sums are an example of Riemann Sums in which each subinterval has the same length and the same x i Mth 06 Clculus Sec. 5.: The Defiite Itegrl I. Riem Sums A. Def : Give y=f(x):. Let f e defied o closed itervl[,].. Prtitio [,] ito suitervls[x (i-),x i ] of legth Δx i = x i -x (i-). Let P deote the prtitio

More information

Regression. By Jugal Kalita Based on Chapter 17 of Chapra and Canale, Numerical Methods for Engineers

Regression. By Jugal Kalita Based on Chapter 17 of Chapra and Canale, Numerical Methods for Engineers Regresso By Jugl Klt Bsed o Chpter 7 of Chpr d Cle, Numercl Methods for Egeers Regresso Descrbes techques to ft curves (curve fttg) to dscrete dt to obt termedte estmtes. There re two geerl pproches two

More information

Addendum. Addendum. Vector Review. Department of Computer Science and Engineering 1-1

Addendum. Addendum. Vector Review. Department of Computer Science and Engineering 1-1 Addedum Addedum Vetor Review Deprtmet of Computer Siee d Egieerig - Coordite Systems Right hded oordite system Addedum y z Deprtmet of Computer Siee d Egieerig - -3 Deprtmet of Computer Siee d Egieerig

More information

Numerical Differentiation and Integration

Numerical Differentiation and Integration Numerl Deretto d Itegrto Overvew Numerl Deretto Newto-Cotes Itegrto Formuls Trpezodl rule Smpso s Rules Guss Qudrture Cheyshev s ormul Numerl Deretto Forwrd te dvded deree Bkwrd te dvded deree Ceter te

More information

Preliminary Examinations: Upper V Mathematics Paper 1

Preliminary Examinations: Upper V Mathematics Paper 1 relmr Emtos: Upper V Mthemtcs per Jul 03 Emer: G Evs Tme: 3 hrs Modertor: D Grgortos Mrks: 50 INSTRUCTIONS ND INFORMTION Ths questo pper sts of 0 pges, cludg swer Sheet pge 8 d Iformto Sheet pges 9 d 0

More information

Rendering Equation. Linear equation Spatial homogeneous Both ray tracing and radiosity can be considered special case of this general eq.

Rendering Equation. Linear equation Spatial homogeneous Both ray tracing and radiosity can be considered special case of this general eq. Rederg quto Ler equto Sptl homogeeous oth ry trcg d rdosty c be cosdered specl cse of ths geerl eq. Relty ctul photogrph Rdosty Mus Rdosty Rederg quls the dfferece or error mge http://www.grphcs.corell.edu/ole/box/compre.html

More information

Problem Set 4 Solutions

Problem Set 4 Solutions 4 Eoom Altos of Gme Theory TA: Youg wg /08/0 - Ato se: A A { B, } S Prolem Set 4 Solutos - Tye Se: T { α }, T { β, β} Se Plyer hs o rte formto, we model ths so tht her tye tke oly oe lue Plyer kows tht

More information

Dynamics of Marine Biological Resources * * * REVIEW OF SOME MATHEMATICS * * *

Dynamics of Marine Biological Resources * * * REVIEW OF SOME MATHEMATICS * * * Dmis o Mrie Biologil Resores A FUNCTION * * * REVIEW OF SOME MATHEMATICS * * * z () z g(,) A tio is rle or orml whih estlishes reltioshi etwee deedet vrile (z) d oe or more ideedet vriles (,) sh tht there

More information

Chapter 2 Intro to Math Techniques for Quantum Mechanics

Chapter 2 Intro to Math Techniques for Quantum Mechanics Wter 3 Chem 356: Itroductory Qutum Mechcs Chpter Itro to Mth Techques for Qutum Mechcs... Itro to dfferetl equtos... Boudry Codtos... 5 Prtl dfferetl equtos d seprto of vrbles... 5 Itroducto to Sttstcs...

More information

Numerical Analysis Topic 4: Least Squares Curve Fitting

Numerical Analysis Topic 4: Least Squares Curve Fitting Numerl Alss Top 4: Lest Squres Curve Fttg Red Chpter 7 of the tetook Alss_Numerk Motvto Gve set of epermetl dt: 3 5. 5.9 6.3 The reltoshp etwee d m ot e ler. Fd futo f tht est ft the dt 3 Alss_Numerk Motvto

More information

Chapter Linear Regression

Chapter Linear Regression Chpte 6.3 Le Regesso Afte edg ths chpte, ou should be ble to. defe egesso,. use sevel mmzg of esdul cte to choose the ght cteo, 3. deve the costts of le egesso model bsed o lest sques method cteo,. use

More information

St John s College. UPPER V Mathematics: Paper 1 Learning Outcome 1 and 2. Examiner: GE Marks: 150 Moderator: BT / SLS INSTRUCTIONS AND INFORMATION

St John s College. UPPER V Mathematics: Paper 1 Learning Outcome 1 and 2. Examiner: GE Marks: 150 Moderator: BT / SLS INSTRUCTIONS AND INFORMATION St Joh s College UPPER V Mthemtcs: Pper Lerg Outcome d ugust 00 Tme: 3 hours Emer: GE Mrks: 50 Modertor: BT / SLS INSTRUCTIONS ND INFORMTION Red the followg structos crefull. Ths questo pper cossts of

More information

The formulae in this booklet have been arranged according to the unit in which they are first

The formulae in this booklet have been arranged according to the unit in which they are first Fomule Booklet Fomule Booklet The fomule ths ooklet hve ee ge og to the ut whh the e fst toue. Thus te sttg ut m e eque to use the fomule tht wee toue peeg ut e.g. tes sttg C mght e epete to use fomule

More information

Objective of curve fitting is to represent a set of discrete data by a function (curve). Consider a set of discrete data as given in table.

Objective of curve fitting is to represent a set of discrete data by a function (curve). Consider a set of discrete data as given in table. CURVE FITTING Obectve curve ttg s t represet set dscrete dt b uct curve. Csder set dscrete dt s gve tble. 3 3 = T use the dt eectvel, curve epress s tted t the gve dt set, s = + = + + = e b ler uct plml

More information

A Novel Composite-rotating Consensus for Multi-agent System

A Novel Composite-rotating Consensus for Multi-agent System d Itertol Symposum o Computer, Commuto, Cotrol d Automto (CA ) A Novel Composte-rottg Cosesus for Mult-get System Gu L Shool of Aerouts d Astrouts Uversty of Eletro See d ehology of Ch ChegDu, Ch lgu@uestedu

More information

LECTURE 8: Topics in Chaos Ricker Equation. Period doubling bifurcation. Period doubling cascade. A Quadratic Equation Ricker Equation 1.0. x x 4 0.

LECTURE 8: Topics in Chaos Ricker Equation. Period doubling bifurcation. Period doubling cascade. A Quadratic Equation Ricker Equation 1.0. x x 4 0. LECTURE 8: Topcs Chaos Rcker Equato (t ) = (t ) ep( (t )) Perod doulg urcato Perod doulg cascade 9....... A Quadratc Equato Rcker Equato (t ) = (t ) ( (t ) ). (t ) = (t ) ep( (t )) 6. 9 9. The perod doulg

More information

Riemann Integral Oct 31, such that

Riemann Integral Oct 31, such that Riem Itegrl Ot 31, 2007 Itegrtio of Step Futios A prtitio P of [, ] is olletio {x k } k=0 suh tht = x 0 < x 1 < < x 1 < x =. More suitly, prtitio is fiite suset of [, ] otiig d. It is helpful to thik of

More information

ENGI 4421 Propagation of Error Page 8-01

ENGI 4421 Propagation of Error Page 8-01 ENGI 441 Propagato of Error Page 8-01 Propagato of Error [Navd Chapter 3; ot Devore] Ay realstc measuremet procedure cotas error. Ay calculatos based o that measuremet wll therefore also cota a error.

More information

Spring Ammar Abu-Hudrouss Islamic University Gaza

Spring Ammar Abu-Hudrouss Islamic University Gaza ١ ١ Chapter Chapter 4 Cyl Blo Cyl Blo Codes Codes Ammar Abu-Hudrouss Islam Uversty Gaza Spr 9 Slde ٢ Chael Cod Theory Cyl Blo Codes A yl ode s haraterzed as a lear blo ode B( d wth the addtoal property

More information

EXPONENTS AND LOGARITHMS

EXPONENTS AND LOGARITHMS 978--07-6- Mthemtis Stdrd Level for IB Diplom Eerpt EXPONENTS AND LOGARITHMS WHAT YOU NEED TO KNOW The rules of epoets: m = m+ m = m ( m ) = m m m = = () = The reltioship etwee epoets d rithms: = g where

More information

Outline. Finite Difference Grids. Numerical Analysis. Finite Difference Grids II. Finite Difference Grids III

Outline. Finite Difference Grids. Numerical Analysis. Finite Difference Grids II. Finite Difference Grids III Itrodcto to Nmercl Alyss Mrc, 9 Nmercl Metods or PDEs Lrry Cretto Meccl Egeerg 5B Semr Egeerg Alyss Mrc, 9 Otle Revew mdterm soltos Revew bsc mterl o mercl clcls Expressos or dervtves, error d error order

More information

14.2 Line Integrals. determines a partition P of the curve by points Pi ( xi, y

14.2 Line Integrals. determines a partition P of the curve by points Pi ( xi, y 4. Le Itegrls I ths secto we defe tegrl tht s smlr to sgle tegrl except tht sted of tegrtg over tervl [ ] we tegrte over curve. Such tegrls re clled le tegrls lthough curve tegrls would e etter termology.

More information

10.2 Series. , we get. which is called an infinite series ( or just a series) and is denoted, for short, by the symbol. i i n

10.2 Series. , we get. which is called an infinite series ( or just a series) and is denoted, for short, by the symbol. i i n 0. Sere I th ecto, we wll troduce ere tht wll be dcug for the ret of th chpter. Wht ere? If we dd ll term of equece, we get whch clled fte ere ( or jut ere) d deoted, for hort, by the ymbol or Doe t mke

More information

Econometric Methods. Review of Estimation

Econometric Methods. Review of Estimation Ecoometrc Methods Revew of Estmato Estmatg the populato mea Radom samplg Pot ad terval estmators Lear estmators Ubased estmators Lear Ubased Estmators (LUEs) Effcecy (mmum varace) ad Best Lear Ubased Estmators

More information

Level-2 BLAS. Matrix-Vector operations with O(n 2 ) operations (sequentially) BLAS-Notation: S --- single precision G E general matrix M V --- vector

Level-2 BLAS. Matrix-Vector operations with O(n 2 ) operations (sequentially) BLAS-Notation: S --- single precision G E general matrix M V --- vector evel-2 BS trx-vector opertos wth 2 opertos sequetlly BS-Notto: S --- sgle precso G E geerl mtrx V --- vector defes SGEV, mtrx-vector product: r y r α x β r y ther evel-2 BS: Solvg trgulr system x wth trgulr

More information

Stats & Summary

Stats & Summary Stts 443.3 & 85.3 Summr The Woodbur Theorem BCD B C D B D where the verses C C D B, d est. Block Mtrces Let the m mtr m q q m be rttoed to sub-mtrces,,,, Smlrl rtto the m k mtr B B B mk m B B l kl Product

More information

Some Unbiased Classes of Estimators of Finite Population Mean

Some Unbiased Classes of Estimators of Finite Population Mean Itertol Jourl O Mtemtcs Ad ttstcs Iveto (IJMI) E-IN: 3 4767 P-IN: 3-4759 Www.Ijms.Org Volume Issue 09 etember. 04 PP-3-37 ome Ubsed lsses o Estmtors o Fte Poulto Me Prvee Kumr Msr d s Bus. Dertmet o ttstcs,

More information

Section 6.3: Geometric Sequences

Section 6.3: Geometric Sequences 40 Chpter 6 Sectio 6.: Geometric Sequeces My jobs offer ul cost-of-livig icrese to keep slries cosistet with ifltio. Suppose, for exmple, recet college grdute fids positio s sles mger erig ul slry of $6,000.

More information

Analyzing Control Structures

Analyzing Control Structures Aalyzg Cotrol Strutures sequeg P, P : two fragmets of a algo. t, t : the tme they tae the tme requred to ompute P ;P s t t Θmaxt,t For loops for to m do P t: the tme requred to ompute P total tme requred

More information

Fibonacci and Lucas Numbers as Tridiagonal Matrix Determinants

Fibonacci and Lucas Numbers as Tridiagonal Matrix Determinants Rochester Isttute of echology RI Scholr Wors Artcles 8-00 bocc d ucs Nubers s rdgol trx Deterts Nth D. Chll Est Kod Copy Drre Nry Rochester Isttute of echology ollow ths d ddtol wors t: http://scholrwors.rt.edu/rtcle

More information

PROGRESSIONS AND SERIES

PROGRESSIONS AND SERIES PROGRESSIONS AND SERIES A sequece is lso clled progressio. We ow study three importt types of sequeces: () The Arithmetic Progressio, () The Geometric Progressio, () The Hrmoic Progressio. Arithmetic Progressio.

More information

2. Higher Order Consensus

2. Higher Order Consensus Prepared by F.L. Lews Updated: Wedesday, February 3, 0. Hgher Order Cosesus I Seto we dsussed ooperatve otrol o graphs for dyamal systems that have frstorder dyams, that s, a sgle tegrator or shft regster

More information

GRAPHING LINEAR EQUATIONS. Linear Equations. x l ( 3,1 ) _x-axis. Origin ( 0, 0 ) Slope = change in y change in x. Equation for l 1.

GRAPHING LINEAR EQUATIONS. Linear Equations. x l ( 3,1 ) _x-axis. Origin ( 0, 0 ) Slope = change in y change in x. Equation for l 1. GRAPHING LINEAR EQUATIONS Qudrt II Qudrt I ORDERED PAIR: The first umer i the ordered pir is the -coordite d the secod umer i the ordered pir is the y-coordite. (, ) Origi ( 0, 0 ) _-is Lier Equtios Qudrt

More information

Linear Open Loop Systems

Linear Open Loop Systems Colordo School of Me CHEN43 Trfer Fucto Ler Ope Loop Sytem Ler Ope Loop Sytem... Trfer Fucto for Smple Proce... Exmple Trfer Fucto Mercury Thermometer... 2 Derblty of Devto Vrble... 3 Trfer Fucto for Proce

More information

MA123, Chapter 9: Computing some integrals (pp )

MA123, Chapter 9: Computing some integrals (pp ) MA13, Chpter 9: Computig some itegrls (pp. 189-05) Dte: Chpter Gols: Uderstd how to use bsic summtio formuls to evlute more complex sums. Uderstd how to compute its of rtiol fuctios t ifiity. Uderstd how

More information

In an algebraic expression of the form (1), like terms are terms with the same power of the variables (in this case

In an algebraic expression of the form (1), like terms are terms with the same power of the variables (in this case Chpter : Algebr: A. Bckgroud lgebr: A. Like ters: I lgebric expressio of the for: () x b y c z x y o z d x... p x.. we cosider x, y, z to be vribles d, b, c, d,,, o,.. to be costts. I lgebric expressio

More information

ITERATIVE METHODS FOR SOLVING SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS

ITERATIVE METHODS FOR SOLVING SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS Numercl Alyss for Egeers Germ Jord Uversty ITERATIVE METHODS FOR SOLVING SYSTEMS OF LINEAR ALGEBRAIC EQUATIONS Numercl soluto of lrge systems of ler lgerc equtos usg drect methods such s Mtr Iverse, Guss

More information

The Algebraic Least Squares Fitting Of Ellipses

The Algebraic Least Squares Fitting Of Ellipses IOSR Jourl of Mthets (IOSR-JM) e-issn: 78-578 -ISSN: 39-765 Volue 4 Issue Ver II (Mr - Ar 8) PP 74-83 wwwosrjourlsorg he Algebr Lest Squres Fttg Of Ellses Abdelltf Betteb Dertet of Geerl Studes Jubl Idustrl

More information

Data Compression Techniques (Spring 2012) Model Solutions for Exercise 4

Data Compression Techniques (Spring 2012) Model Solutions for Exercise 4 58487 Dt Compressio Tehiques (Sprig 0) Moel Solutios for Exerise 4 If you hve y fee or orretios, plese ott jro.lo t s.helsii.fi.. Prolem: Let T = Σ = {,,, }. Eoe T usig ptive Huffm oig. Solutio: R 4 U

More information

12 Iterative Methods. Linear Systems: Gauss-Seidel Nonlinear Systems Case Study: Chemical Reactions

12 Iterative Methods. Linear Systems: Gauss-Seidel Nonlinear Systems Case Study: Chemical Reactions HK Km Slghtly moded //9 /8/6 Frstly wrtte t Mrch 5 Itertve Methods er Systems: Guss-Sedel Noler Systems Cse Study: Chemcl Rectos Itertve or ppromte methods or systems o equtos cosst o guessg vlue d the

More information

ψ ij has the eigenvalue

ψ ij has the eigenvalue Moller Plesset Perturbton Theory In Moller-Plesset (MP) perturbton theory one tes the unperturbed Hmltonn for n tom or molecule s the sum of the one prtcle Foc opertors H F() where the egenfunctons of

More information

Dynamics of Structures

Dynamics of Structures UNION Dymis of Strutures Prt Zbigiew Wójii Je Grosel Projet o-fied by Europe Uio withi Europe Soil Fud UNION Mtries Defiitio of mtri mtri is set of umbers or lgebri epressios rrged i retgulr form with

More information

Handout #2. Introduction to Matrix: Matrix operations & Geometric meaning

Handout #2. Introduction to Matrix: Matrix operations & Geometric meaning Hdout # Title: FAE Course: Eco 8/ Sprig/5 Istructor: Dr I-Mig Chiu Itroductio to Mtrix: Mtrix opertios & Geometric meig Mtrix: rectgulr rry of umers eclosed i pretheses or squre rckets It is covetiolly

More information

PAIR OF STRAIGHT LINES. will satisfy L1 L2 0, and thus L1 L. 0 represent? It is obvious that any point lying on L 1

PAIR OF STRAIGHT LINES. will satisfy L1 L2 0, and thus L1 L. 0 represent? It is obvious that any point lying on L 1 LOCUS 33 Seto - 3 PAIR OF STRAIGHT LINES Cosder two les L L Wht do ou thk wll L L represet? It s ovous tht pot lg o L d L wll stsf L L, d thus L L represets the set of pots osttutg oth the les,.e., L L

More information

Exponents and Radical

Exponents and Radical Expoets d Rdil Rule : If the root is eve d iside the rdil is egtive, the the swer is o rel umber, meig tht If is eve d is egtive, the Beuse rel umber multiplied eve times by itself will be lwys positive.

More information

Chapter System of Equations

Chapter System of Equations hpter 4.5 System of Equtios After redig th chpter, you should be ble to:. setup simulteous lier equtios i mtrix form d vice-vers,. uderstd the cocept of the iverse of mtrix, 3. kow the differece betwee

More information

Interval Estimation. Consider a random variable X with a mean of X. Let X be distributed as X X

Interval Estimation. Consider a random variable X with a mean of X. Let X be distributed as X X ECON 37: Ecoomercs Hypohess Tesg Iervl Esmo Wh we hve doe so fr s o udersd how we c ob esmors of ecoomcs reloshp we wsh o sudy. The queso s how comforble re we wh our esmors? We frs exme how o produce

More information

Solutions Manual for Polymer Science and Technology Third Edition

Solutions Manual for Polymer Science and Technology Third Edition Solutos ul for Polymer Scece d Techology Thrd Edto Joel R. Fred Uer Sddle Rver, NJ Bosto Idols S Frcsco New York Toroto otrel Lodo uch Prs drd Cetow Sydey Tokyo Sgore exco Cty Ths text s ssocted wth Fred/Polymer

More information

0 otherwise. sin( nx)sin( kx) 0 otherwise. cos( nx) sin( kx) dx 0 for all integers n, k.

0 otherwise. sin( nx)sin( kx) 0 otherwise. cos( nx) sin( kx) dx 0 for all integers n, k. . Computtio of Fourier Series I this sectio, we compute the Fourier coefficiets, f ( x) cos( x) b si( x) d b, i the Fourier series To do this, we eed the followig result o the orthogolity of the trigoometric

More information

3. REVIEW OF PROPERTIES OF EIGENVALUES AND EIGENVECTORS

3. REVIEW OF PROPERTIES OF EIGENVALUES AND EIGENVECTORS . REVIEW OF PROPERTIES OF EIGENVLUES ND EIGENVECTORS. EIGENVLUES ND EIGENVECTORS We hll ow revew ome bc fct from mtr theory. Let be mtr. clr clled egevlue of f there et ozero vector uch tht Emle: Let 9

More information