Scaling Friction and Inertia Losses for the Performance Prediction of Turbomachines

Size: px
Start display at page:

Download "Scaling Friction and Inertia Losses for the Performance Prediction of Turbomachines"

Transcription

1 Scag Frco a Iera Losses or he Perormace Preco o Turbomaches Peer F Pez 1 a chae Heß 1 1 Char o Fu Sysems Techoogy Techsche Uersä Darmsa Darmsa, Germay Phoe: , FAX: , E-ma: peerpez@su-armsae NOENCLATURE a C a P p Re Y=gH spee o sou power coece ameer roughess hegh, reae roughess hegh scae acor ach umber roaoa sha spee power sac pressure Reyos umber p cearace hegh, reae p cearace hegh oume ow oss srbuo acor specc wor Gree symbos α expoe hcess η ececy emac scosy κ geomery scag acor λ rco acor ψ pressure coece ρ esy φ ow umber Subscrps u rco oss era oss ea oss m moe mache mech mechaca rs rea sze mache p scous w reae eocy INTRODUCTION I pracce measuremes urg he esg process or or a specos oe cao be carre ou o u scae maches osy s oo cosy o bu a ow es rg or each mache, so es rgs wh saarze ameers a measurg equpme are use Somemes he ameers o he rea scae maches are so arge ha a measureme s uery mpossbe Exampes are waer urbes or as use or coog power pas hese maches may hae ameers o seera meers a requre a brae respecey re power he W rage O he oppose maches wh ameers o oy a ew mmeers o o aow he operao o esabshe ase measurg echques such as Po-ubes, e hoe probes or ho wre aemomery because o he sgca uece o he probes o he ow e Hece measuremes o eerme he perormace are carre ou o moes whch are ow or up scae As was show by Spur (199) a u smary bewee moe a prooype mache s he coex o urbomaches possbe as og as he ach umber s sma, e he compressby ca be egece SIILARITY To proe raseraby o measuremes o scae moes o he rea sze maches he smary bewee moe a prooype has o be cosere Scag he geomerc meas scag o a mesos such as ameer, bae egh, chor egh o roor a gue aes, surace roughess hegh, p cearace hegh wh he same scae acor '/, where he moe aa here a he oowg are cae by a ash Ee so u geomerc smary s possbe, he smary reae roughess / a reae p cearace / are somemes sacrce Foowg he Brgma posuae, o he absoue sgcace o reae magues (190) u smary s reache whe he reae magues o a sysem, whch are cae mesoess proucs oay, are eca or he moe a prooype sysem Oe exampe or a geomerc reae mague s he reae p cearace / Oe exampe or a emac reae mague or mesoess prouc s he ow coece 4 / I he rs exampe he p cearace s o measure mmeer or ch, bu mupes o he mpeer ameer I he seco exampe he oume ow rae s measure mupes o he mache ypca ow rae ~ O he oher ha he roaoa spee s measure o Herz or reouos per mue bu mupes o he erse o a scose uso me /, whch eas o he Reyos umber Re / Foowg he Bucgham -heorem (1914) he oa specc wor Y gh, a,,,,, s equae o, a,, where here a he oowg he roughess a p cearace are reae quaes: /, / For he ow ach umber case, e eary compressbe ow, a / a pays o roe a he pressure coece -1-

2 : gh / s ge by,, (1) The sspae eergy per u me P s a uco o P P P,, a,,,,, whch s equae o P / P P, a,, / P For a pump, a or compressor he ececy s ee as 1 P / P a he power coece s C /, P s mechaca power raserre by he sha o 1 he mpeer For a urbe he ececy s (1 / P), a he power coece C P eoes he mechaca power raserre rom he mpeer o he sha Aga or sma ach umber he ececy boh cases ca be wre as,, () Equaos (1) a () uy escrbe he perormace o a urbomache Hece, as og as he mesoess argumes,, are he same, moe a prooype show he same pressure coece a ececy Aga he moe s eoe by a ash he raos, or scag acors '/ /( ), Re' / Re hae o be oe Ths eas o he sysem 4 o equaos P Hece, prcpe compee smary s accessbe I pracce seera probems arse Assumg a geomerc scae acor o κ = 1/10, he roaoa spee a he power ceupe, whereas he oume ow wou be a eh Esmag a usua urbomache wh a ouer ameer o 5 m 1 a a roaoa spee o 500 rpm (crcumerea spee a p 10 m/s), prog geomerc smary wou requre scag he reae roughess a reae gap wh o a eh o he rea sze mache I s possbe o achee such sma mesos, bu s a eas ery cosy Usg Eq (7) o (11) by assumg compee smary wou ea o a roaoa spee o rpm (p spee 110 m/s) respecey a oume specc power he area o seera GW/m or he moe mache whch s mpossbe o achee The meoe probem o ureachabe compee smary ca oy be aoe by gg up smary o a mesoess proucs I hs case aoher scae acor ca be chose ree Usuay he smary Reyos umber a reae roughess s sacrce a he pressure rse s ep cosa As a resu he pressure coece a he ececy s ere moe a prooype mache For exampe ', Re', Re ', Re', Re or Re' Re a LOSSES 1, 1, () (4) 1, or see scae acors, where hree ca be chose arbrary For he same u moe a prooype = 1 hos Wh = / = κ as he geomerca scae acor hs resus : 1, (5) (6), (7), (8), (9) s (10) Wh hose scae acors, he scae acor or he hea chage becomes (11) gh The scae acor or he mechaca power resus 1 Hece he oume specc power o he P gh mache wou scaes as 4 (1) P/ Fg 1: Loss coece or ppes a ere Reyos umbers a reae wa roughess Sacrcg he Reyos umber smary meas, ha he smary he reae bouary ayer hcesses s sacrce Hece or Re' Re he reae bouary ayer o he prooype s her comparso o he moe Hece scag he moe o he prooype he reae rco osses are ecrease whch resus a hgher ececy Ths s a as og as he scous sub ayer / w / (Spur, 008) s hcer ha he surace roughess The wa shear sress scaes as w ~ (1 ) wh he we ow rco acor ( Re w, / ) show Fg 1 / w ~ (1 ) Re 5 (1) he rco osses w be epee o he Reyos umber For he hyrauc smooh case he emprca Basus aw (Spur, 008) 1/ 4 ~ Re or / 5 (14) s a approprae approach For hgher Reyos umber ow, whe he scous sub ayer becomes her ha he surace roughess, he rco osses w become epee o he 1 whereas ormer meoe waer urbes or power pa as cou reach ameers o 10 m a more --

3 Reyos umber Hece or he hyrauc rough surace he rco aw (Spur, 008) h ˆ c, (0) g 174 or / 70 (1) s approprae Sce or he purpose o up scag oy he reae chage rco has o be cosere, s easbe o wor wh he aboe meoe rco aws Aer hs reca o he gs o Pra, o Kármá a Basus oe has o rase he queso wha o o wh hose cassca resus he coex o scag Sce pressure coece a ececy boh epe o he Reyos umber, reae roughess a reae p cearace so has he power coece C (, ) / (here or he exampe o a compressor, a or pump) Neerheess or axa maches he power coece s epee o Reyos umber, reae roughess a p cearace whch was corme by expermes oer a we parameer rage (Hess, Pez, 009) Hece '/ '/ hos or he same ow umber or a a, compressor or pump a ' ' hos or a urbe Thus here s oy oe scag meho or pressure coece a ececy Oe approach o ga a scag meho s a physca aayss o he possbe osses They are reae as ae o Reyos umber or scosy epee, e rco osses a Reyos umber epee or scosy epee osses whch are cae era osses:, ψ, ψ ψ, (16) Acere (ühema, 1948) cae he rco osses scaabe osses a rouce he oss srbuo acor (,, ) : 1 (17) whch was se by Acere o he xe aue o 05 Bu rom (16) becomes cear, ha s a raher crue assumpo o x he aue o 05 I s he ma as o hs corbuo, o ga a physca moae oss srbuo uco, whch w epe o he Reyos a ow umber Beore og so s worhwhe o scuss he era osses ee urher They ca be sp up a oss par ue o he ow bewee casg a p a a par ue o cece osses: ψ ψ, 0 (18) The rs par was rs scusse by Aber Bez (196) or axa maches Foowg hs houghs he ressace s ue o mxg a a uce ressace cause by he p orex Ths uce ressace has o be a ee uco o he ow umber or gog urher has o be a ee uco o he ea mache perormace a has o ash or zero p cearace Hece he asaz s, b ψ (19) s moae by hs assumpo or sma reae p cearace Ee hough we o o use (19) he oowg mgh be a eresg hough o scae he reae p cearace The heoreca mache characerscs s obae by he measure pressure coece a ececy, h where b,ˆ, c are mesoess mache cosas Fgure shows he ay o equao (0) or a axa a From he measureme aa he cosas ˆ, c are easy eerme Foowg hs scusso he p osses are maxmum or sma ow umber a he sope o he osses approach zero ψ / 0 or 0 The seco par o he era oss 0 shows a mmum a he esg po 0 / 0 a 0 o he mache For par a oeroa he cece osses crease a rs assumpo proporoa o ( ) 0 FIRST ODEL FOR THE LOSS DISTRIBUTION FACTOR To ga a oss srbuo acor, whch aes a eas he epeece o he oss srbuo wh ow umber o accou, s, Re promsg o suy he shape o he ececy cure whch ca be wre as: 1 1 ˆ c For sma ow umber 1 he rco moe h (1) (, ) ( ) ~ ( ) or 1 () s a reasoabe approxmao Hece (1) s or hs approxmao equae o ( Re) ( ) 1 ˆ c Para ereag wh respec o φ eas o Re h / c 1 h h c 1 () (4) Rearragg a egrag rom φ op where he ececy s maxma o φ yes o ( ) ( op) h c1 (5) op Re Iegrag by pars usg he reao ψ = ψ h η resus ( ) ( ) ( ) ( op) op c op (6) Hece by oog oy a oe characersc cure (ececy a pressure rse) a oe roaoa spee, e Reyos umber s possbe o eerme he oss acor he orm : ( ) ( ) ( ) c op op op (7) Fgure show a sgca mproeme he scag o he ececy by usg he oss srbuo acor (7) comparso o a xe aue o 05 as Acere Oe major aaage o he resu (7) s ha here s o g parameer use The oe rawbac shou be meoe cocerg he aboe erao --

4 easuremes show, ha he bes operao po o a urbomache shows a sh o hgher ow rae coeces wh creasg roaoa spee, e Reyos umber (see Fg ) Ths scag eec wou o be coere usg Eq (7) Hece s worhwhe o scuss a aerae way o ga he rao := ψ / ψ reae p cearace / o 01% a a reae roughess / o 6E-06, Re = 06E06 respecey 1E-06, Re = 65E06 The expoe α s se o 0 SECOND ODEL FOR THE LOSS DISTRIBUTION FAC- TOR The crca assumpo oe so ar was ha he rco osses are epee o he ow rae coece Essea or he osses he bae passage s he reae eocy, e he erece bewee absoue a crcumerea eocy: w c u Hece he square o he eocy mague s ge by w² = u² (φ² + 1) Sce he rco osses are ue o bouary ayer rco, hey are o he orm 1 ( w /, / ) b 1 ( / ), b (8) wh he ow mg behaour ψ ~ (φ² + 1) Re -α or 5δ ν a ψ ~ (φ² + 1) or >> 5δ ν The mesoess cosa b s aga a mesoess geomery quay escrbg he mache Hece he rao := ψ / ψ s ow ge by 1 b ( / ) (9) 1 Usg he meoe measuremes by Hess a Pez o eerme he cosa b eas o a aue o approxmaey 11 Fg 4 o Fg 6 show scae-up or ececy respecey pressure coece usg Eq (9) Fg Comparso o ececy scae-up usg Eq () a (7) wh measuremes a he scae-up meho by Acere Ahough he cacuae aues are s smaer ha he measure oes a crease o accuracy compare o Acere s obae Fg shows scae-up o he pressure coece where he same eecy s sbe I s assume, ha he power coece eeps cosa wh creasg Reyos umber (Hess a Pez, 009) a he pressure coece behaes he orm / ' / ' GENERAL SCALE UP ETHOD We ow compare moe, eoe by a prme ( ) a prooype mache From (16) a (1) oows 1 1' ' ' ' ' ' (0) Wh he acor = ψ / ψ we e up wh he scag ormua 1 ( / ) ' 1 ' ' ( ',( / )') ' Re (1) For he speca case where he reae p cearace or boh maches are he same ψ / ψ 1 he resu Fg Comparso o pressure coece scae-up wh Eq () a (7), measuremes a he scae-up meho by Acere 1 ( / ) 1 ' 1 1' ( Re',( / )') () s obae where s ge by he xe aue o 05 (Acere) or ow by eher Eq (7) or Eq (9) The absoue aue o he rco acor λ Eq () s o requre, sce oy he quoe o he rco acors s eee Assumg smary he reae roughess Eq () smpes or he hyrauc smooh case o: 1 Re 1 ' 1 () 1' Re' Fg compares scae-up wh Eq () usg Eq (7) o eerme he acor wh measuremes o a axa urbomache by Hess a Pez (009) a a commo scae-up meho by Acere (ühema, 1948) The measuremes were carre ou wh a Fg 4 Comparso o ececy scae-up usg Eq () a (9) -4-

5 wh measuremes a he scae-up meho by Acere Sprger, Ber Spur, J H, Ase, N, 008, Fu echacs, Sprger, Ber Fg 5 Comparso o pressure coece scae-up wh Eq () a (9), measuremes a he scae-up meho by Acere Ee goo resus are reache case o ower ereces Reyos umber show Fg 6 Fg 6 Comparso o ececy scae-up usg Eq () a (9) wh measuremes a he scae-up meho by Acere O he oe ha a urher crease o accuracy compare o meho oe or eermg he acor s sbe O he oher ha measuremes a ere Reyos umbers are eee or eermg he mesoess cosa b Reereces Bez, A, 196, Über e orgäge a e Schaueee o Kapa-Turbe, Hyrausche Probeme, S 161, DI-erag, Ber Brgma, P W, 196, Dmesoa Aayss New Hae: Yae Uersy Press Bucgham, E: O physcay smar sysems; Iusrao o he use o mesoa equaos Phys Re, 4 (1914) JD Deo, 199, Loss mechasms Turbomaches, ASE Joura o Turbomachery, o 115, pp Hess,, Pez, P F, 009, Comparso o easuremes o Axa Fas a Perormace Preco usg Commo Scae-Up ehos a Par- a Oeroa, ASE Fus Egeerg Dso Summer eeg, Paper FEDS ühema, E, 1948 Zur Auwerug es Wrugsgraes o Überruc-Wasserurbe Schwezersche Bauzeug 66 Jahrg, 4 Sorer, JA, Cumpsy NA, 1994, A Approxmae Aayss a Preco eho or Tp Cearace Loss Axa Compressors, ASE Joura o Turbomachery, o 116, pp Spur, J H, 199, Dmesosaayse er Srömugsehre, -5-

Continuous Time Markov Chains

Continuous Time Markov Chains Couous me Markov chas have seay sae probably soluos f a oly f hey are ergoc, us lke scree me Markov chas. Fg he seay sae probably vecor for a couous me Markov cha s o more ffcul ha s he scree me case,

More information

Least Squares Fitting (LSQF) with a complicated function Theexampleswehavelookedatsofarhavebeenlinearintheparameters

Least Squares Fitting (LSQF) with a complicated function Theexampleswehavelookedatsofarhavebeenlinearintheparameters Leas Squares Fg LSQF wh a complcaed fuco Theeampleswehavelookedasofarhavebeelearheparameers ha we have bee rg o deerme e.g. slope, ercep. For he case where he fuco s lear he parameers we ca fd a aalc soluo

More information

Chapter 1 - Free Vibration of Multi-Degree-of-Freedom Systems - I

Chapter 1 - Free Vibration of Multi-Degree-of-Freedom Systems - I CEE49b Chaper - Free Vbrao of M-Degree-of-Freedo Syses - I Free Udaped Vbrao The basc ype of respose of -degree-of-freedo syses s free daped vbrao Aaogos o sge degree of freedo syses he aayss of free vbrao

More information

Reliability Equivalence of a Parallel System with Non-Identical Components

Reliability Equivalence of a Parallel System with Non-Identical Components Ieraoa Mahemaca Forum 3 8 o. 34 693-7 Reaby Equvaece of a Parae Syem wh No-Ideca ompoe M. Moaer ad mmar M. Sarha Deparme of Sac & O.R. oege of Scece Kg Saud Uvery P.O.ox 455 Ryadh 45 Saud raba aarha@yahoo.com

More information

Upper Bound For Matrix Operators On Some Sequence Spaces

Upper Bound For Matrix Operators On Some Sequence Spaces Suama Uer Bou formar Oeraors Uer Bou For Mar Oeraors O Some Sequece Saces Suama Dearme of Mahemacs Gaah Maa Uersy Yogyaara 558 INDONESIA Emal: suama@ugmac masomo@yahoocom Isar D alam aer aa susa masalah

More information

Midterm Exam. Tuesday, September hour, 15 minutes

Midterm Exam. Tuesday, September hour, 15 minutes Ecoomcs of Growh, ECON560 Sa Fracsco Sae Uvers Mchael Bar Fall 203 Mderm Exam Tuesda, Sepember 24 hour, 5 mues Name: Isrucos. Ths s closed boo, closed oes exam. 2. No calculaors of a d are allowed. 3.

More information

Chapter 3: Maximum-Likelihood & Bayesian Parameter Estimation (part 1)

Chapter 3: Maximum-Likelihood & Bayesian Parameter Estimation (part 1) Aoucemes Reags o E-reserves Proec roosal ue oay Parameer Esmao Bomercs CSE 9-a Lecure 6 CSE9a Fall 6 CSE9a Fall 6 Paer Classfcao Chaer 3: Mamum-Lelhoo & Bayesa Parameer Esmao ar All maerals hese sles were

More information

The ray paths and travel times for multiple layers can be computed using ray-tracing, as demonstrated in Lab 3.

The ray paths and travel times for multiple layers can be computed using ray-tracing, as demonstrated in Lab 3. C. Trael me cures for mulple reflecors The ray pahs ad rael mes for mulple layers ca be compued usg ray-racg, as demosraed Lab. MATLAB scrp reflec_layers_.m performs smple ray racg. (m) ref(ms) ref(ms)

More information

Quantum Mechanics II Lecture 11 Time-dependent perturbation theory. Time-dependent perturbation theory (degenerate or non-degenerate starting state)

Quantum Mechanics II Lecture 11 Time-dependent perturbation theory. Time-dependent perturbation theory (degenerate or non-degenerate starting state) Pro. O. B. Wrgh, Auum Quaum Mechacs II Lecure Tme-depede perurbao heory Tme-depede perurbao heory (degeerae or o-degeerae sarg sae) Cosder a sgle parcle whch, s uperurbed codo wh Hamloa H, ca exs a superposo

More information

Available online Journal of Scientific and Engineering Research, 2014, 1(1): Research Article

Available online  Journal of Scientific and Engineering Research, 2014, 1(1): Research Article Avalable ole wwwjsaercom Joural o Scec ad Egeerg Research, 0, ():0-9 Research Arcle ISSN: 39-630 CODEN(USA): JSERBR NEW INFORMATION INEUALITIES ON DIFFERENCE OF GENERALIZED DIVERGENCES AND ITS APPLICATION

More information

14. Poisson Processes

14. Poisson Processes 4. Posso Processes I Lecure 4 we roduced Posso arrvals as he lmg behavor of Bomal radom varables. Refer o Posso approxmao of Bomal radom varables. From he dscusso here see 4-6-4-8 Lecure 4 " arrvals occur

More information

8. Queueing systems lect08.ppt S Introduction to Teletraffic Theory - Fall

8. Queueing systems lect08.ppt S Introduction to Teletraffic Theory - Fall 8. Queueg sysems lec8. S-38.45 - Iroduco o Teleraffc Theory - Fall 8. Queueg sysems Coes Refresher: Smle eleraffc model M/M/ server wag laces M/M/ servers wag laces 8. Queueg sysems Smle eleraffc model

More information

Reliability and Sensitivity Analysis of a System with Warm Standbys and a Repairable Service Station

Reliability and Sensitivity Analysis of a System with Warm Standbys and a Repairable Service Station Ieraoa Joura of Operaos Research Vo. 1, No. 1, 61 7 (4) Reaby ad Sesvy Aayss of a Sysem wh Warm Sadbys ad a Reparabe Servce Sao Kuo-Hsug Wag, u-ju a, ad Jyh-B Ke Deparme of Apped Mahemacs, Naoa Chug-Hsg

More information

-HYBRID LAPLACE TRANSFORM AND APPLICATIONS TO MULTIDIMENSIONAL HYBRID SYSTEMS. PART II: DETERMINING THE ORIGINAL

-HYBRID LAPLACE TRANSFORM AND APPLICATIONS TO MULTIDIMENSIONAL HYBRID SYSTEMS. PART II: DETERMINING THE ORIGINAL UPB Sc B See A Vo 72 I 3 2 ISSN 223-727 MUTIPE -HYBRID APACE TRANSORM AND APPICATIONS TO MUTIDIMENSIONA HYBRID SYSTEMS PART II: DETERMININ THE ORIINA Ve PREPEIŢĂ Te VASIACHE 2 Ace co copeeă oă - pce he

More information

Partial Molar Properties of solutions

Partial Molar Properties of solutions Paral Molar Properes of soluos A soluo s a homogeeous mxure; ha s, a soluo s a oephase sysem wh more ha oe compoe. A homogeeous mxures of wo or more compoes he gas, lqud or sold phase The properes of a

More information

Fresnel Dragging Explained

Fresnel Dragging Explained Fresel Draggig Explaied 07/05/008 Decla Traill Decla@espace.e.au The Fresel Draggig Coefficie required o explai he resul of he Fizeau experime ca be easily explaied by usig he priciples of Eergy Field

More information

Solutions for HW4. x k n+1. k! n(n + 1) (n + k 1) =.

Solutions for HW4. x k n+1. k! n(n + 1) (n + k 1) =. Exercse 13 (a Proe Soutos for HW4 (1 + x 1 + x 2 1 + (1 + x 2 + x 2 2 + (1 + x + x 2 + by ducto o M(Sν x S x ν(x Souto: Frst ote that sce the mutsets o {x 1 } are determed by ν(x 1 the set of mutsets o

More information

Stat 6863-Handout 5 Fundamentals of Interest July 2010, Maurice A. Geraghty

Stat 6863-Handout 5 Fundamentals of Interest July 2010, Maurice A. Geraghty S 6863-Hou 5 Fuels of Ieres July 00, Murce A. Gerghy The pror hous resse beef cl occurreces, ous, ol cls e-ulero s ro rbles. The fl copoe of he curl oel oles he ecooc ssupos such s re of reur o sses flo.

More information

Real-Time Systems. Example: scheduling using EDF. Feasibility analysis for EDF. Example: scheduling using EDF

Real-Time Systems. Example: scheduling using EDF. Feasibility analysis for EDF. Example: scheduling using EDF EDA/DIT6 Real-Tme Sysems, Chalmers/GU, 0/0 ecure # Updaed February, 0 Real-Tme Sysems Specfcao Problem: Assume a sysem wh asks accordg o he fgure below The mg properes of he asks are gve he able Ivesgae

More information

AML710 CAD LECTURE 12 CUBIC SPLINE CURVES. Cubic Splines Matrix formulation Normalised cubic splines Alternate end conditions Parabolic blending

AML710 CAD LECTURE 12 CUBIC SPLINE CURVES. Cubic Splines Matrix formulation Normalised cubic splines Alternate end conditions Parabolic blending CUIC SLINE CURVES Cubc Sples Marx formulao Normalsed cubc sples Alerae ed codos arabolc bledg AML7 CAD LECTURE CUIC SLINE The ame sple comes from he physcal srume sple drafsme use o produce curves A geeral

More information

Novel Bounds for Solutions of Nonlinear Differential Equations

Novel Bounds for Solutions of Nonlinear Differential Equations Appe Mahemacs, 5, 6, 8-94 Pubshe Oe Jauary 5 ScRes. hp://www.scrp.org/joura/am hp://.o.org/.436/am.5.68 Nove Bous for Souos of Noear Dfferea Equaos A. A. Maryyu S.P. Tmosheo Isue of Mechacs of NAS of Urae,

More information

QR factorization. Let P 1, P 2, P n-1, be matrices such that Pn 1Pn 2... PPA

QR factorization. Let P 1, P 2, P n-1, be matrices such that Pn 1Pn 2... PPA QR facorzao Ay x real marx ca be wre as AQR, where Q s orhogoal ad R s upper ragular. To oba Q ad R, we use he Householder rasformao as follows: Le P, P, P -, be marces such ha P P... PPA ( R s upper ragular.

More information

Lecture 3 Topic 2: Distributions, hypothesis testing, and sample size determination

Lecture 3 Topic 2: Distributions, hypothesis testing, and sample size determination Lecure 3 Topc : Drbuo, hypohe eg, ad ample ze deermao The Sude - drbuo Coder a repeaed drawg of ample of ze from a ormal drbuo of mea. For each ample, compue,,, ad aoher ac,, where: The ac he devao of

More information

Modeling of the linear time-variant channel. Sven-Gustav Häggman

Modeling of the linear time-variant channel. Sven-Gustav Häggman Moelg of he lear me-vara chael Sve-Gusav Häggma 2 1. Characerzao of he lear me-vara chael 3 The rasmsso chael (rao pah) of a rao commucao sysem s mos cases a mulpah chael. Whe chages ae place he propagao

More information

National Conference on Recent Trends in Synthesis and Characterization of Futuristic Material in Science for the Development of Society

National Conference on Recent Trends in Synthesis and Characterization of Futuristic Material in Science for the Development of Society ABSTRACT Naoa Coferece o Rece Tred Syhe ad Characerzao of Fuurc Maera Scece for he Deveome of Socey (NCRDAMDS-208) I aocao wh Ieraoa Joura of Scefc Reearch Scece ad Techoogy Some New Iegra Reao of I- Fuco

More information

Mathematical Formulation

Mathematical Formulation Mahemacal Formulao The purpose of a fe fferece equao s o appromae he paral ffereal equao (PE) whle maag he physcal meag. Eample PE: p c k FEs are usually formulae by Taylor Seres Epaso abou a po a eglecg

More information

CS344: Introduction to Artificial Intelligence

CS344: Introduction to Artificial Intelligence C344: Iroduco o Arfcal Iellgece Puhpa Bhaacharyya CE Dep. IIT Bombay Lecure 3 3 32 33: Forward ad bacward; Baum elch 9 h ad 2 March ad 2 d Aprl 203 Lecure 27 28 29 were o EM; dae 2 h March o 8 h March

More information

Reliability Analysis of Sparsely Connected Consecutive-k Systems: GERT Approach

Reliability Analysis of Sparsely Connected Consecutive-k Systems: GERT Approach Relably Aalyss of Sparsely Coece Cosecuve- Sysems: GERT Approach Pooa Moha RMSI Pv. L Noa-2131 poalovely@yahoo.com Mau Agarwal Deparme of Operaoal Research Uversy of Delh Delh-117, Ia Agarwal_maulaa@yahoo.com

More information

Fundamentals of Speech Recognition Suggested Project The Hidden Markov Model

Fundamentals of Speech Recognition Suggested Project The Hidden Markov Model . Projec Iroduco Fudameals of Speech Recogo Suggesed Projec The Hdde Markov Model For hs projec, s proposed ha you desg ad mpleme a hdde Markov model (HMM) ha opmally maches he behavor of a se of rag sequeces

More information

PHYS 1443 Section 001 Lecture #4

PHYS 1443 Section 001 Lecture #4 PHYS 1443 Secon 001 Lecure #4 Monda, June 5, 006 Moon n Two Dmensons Moon under consan acceleraon Projecle Moon Mamum ranges and heghs Reerence Frames and relae moon Newon s Laws o Moon Force Newon s Law

More information

Density estimation III. Linear regression.

Density estimation III. Linear regression. Lecure 6 Mlos Hauskrec mlos@cs.p.eu 539 Seo Square Des esmao III. Lear regresso. Daa: Des esmao D { D D.. D} D a vecor of arbue values Obecve: r o esmae e uerlg rue probabl srbuo over varables X px usg

More information

CHAPTER 5. Shallow water theory

CHAPTER 5. Shallow water theory Damcal Oceaograph CAPTER 5 Shallow waer heor I he shallow waer he characersc eph s much smaller ha he horoal scale o moos (5) I s cosere ha he low oes o epe o eph Ths s eacl rue or baroropc ( cos ) o-rcoal

More information

Determination of Antoine Equation Parameters. December 4, 2012 PreFEED Corporation Yoshio Kumagae. Introduction

Determination of Antoine Equation Parameters. December 4, 2012 PreFEED Corporation Yoshio Kumagae. Introduction refeed Soluos for R&D o Desg Deermao of oe Equao arameers Soluos for R&D o Desg December 4, 0 refeed orporao Yosho Kumagae refeed Iroduco hyscal propery daa s exremely mpora for performg process desg ad

More information

P a g e 5 1 of R e p o r t P B 4 / 0 9

P a g e 5 1 of R e p o r t P B 4 / 0 9 P a g e 5 1 of R e p o r t P B 4 / 0 9 J A R T a l s o c o n c l u d e d t h a t a l t h o u g h t h e i n t e n t o f N e l s o n s r e h a b i l i t a t i o n p l a n i s t o e n h a n c e c o n n e

More information

International Journal Of Engineering And Computer Science ISSN: Volume 5 Issue 12 Dec. 2016, Page No.

International Journal Of Engineering And Computer Science ISSN: Volume 5 Issue 12 Dec. 2016, Page No. www.jecs. Ieraoal Joural Of Egeerg Ad Compuer Scece ISSN: 19-74 Volume 5 Issue 1 Dec. 16, Page No. 196-1974 Sofware Relably Model whe mulple errors occur a a me cludg a faul correco process K. Harshchadra

More information

Solution. The straightforward approach is surprisingly difficult because one has to be careful about the limits.

Solution. The straightforward approach is surprisingly difficult because one has to be careful about the limits. ose ad Varably Homewor # (8), aswers Q: Power spera of some smple oses A Posso ose A Posso ose () s a sequee of dela-fuo pulses, eah ourrg depedely, a some rae r (More formally, s a sum of pulses of wdh

More information

A Remark on Generalized Free Subgroups. of Generalized HNN Groups

A Remark on Generalized Free Subgroups. of Generalized HNN Groups Ieraoal Mahemacal Forum 5 200 o 503-509 A Remar o Geeralzed Free Subroup o Geeralzed HNN Group R M S Mahmood Al Ho Uvery Abu Dhab POBo 526 UAE raheedmm@yahoocom Abrac A roup ermed eeralzed ree roup a ree

More information

Chapter 5. Long Waves

Chapter 5. Long Waves ape 5. Lo Waes Wae e s o compaed ae dep: < < L π Fom ea ae eo o s s ; amos ozoa moo z p s ; dosac pesse Dep-aeaed coseao o mass

More information

c- : r - C ' ',. A a \ V

c- : r - C ' ',. A a \ V HS PAGE DECLASSFED AW EO 2958 c C \ V A A a HS PAGE DECLASSFED AW EO 2958 HS PAGE DECLASSFED AW EO 2958 = N! [! D!! * J!! [ c 9 c 6 j C v C! ( «! Y y Y ^ L! J ( ) J! J ~ n + ~ L a Y C + J " J 7 = [ " S!

More information

Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations

Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations Joural of aheacs ad copuer Scece (4 39-38 Soluo of Ipulsve Dffereal Equaos wh Boudary Codos Ters of Iegral Equaos Arcle hsory: Receved Ocober 3 Acceped February 4 Avalable ole July 4 ohse Rabba Depare

More information

Fracture analysis of cracked thermopiezoelectric materials by BEM

Fracture analysis of cracked thermopiezoelectric materials by BEM Q. H. Q / Eero Joura o ouar Eee Vo. No.. 83-3 3 Fraure aa o rae heroeoeer aera E Q-Hua Q Deare o eha a Uver a 37 P.R. Cha E-a: Qh@u.eu. ra he ouar eee oruao or aa rae heroeoeer aera ue o hera a eeroea

More information

The Poisson Process Properties of the Poisson Process

The Poisson Process Properties of the Poisson Process Posso Processes Summary The Posso Process Properes of he Posso Process Ierarrval mes Memoryless propery ad he resdual lfeme paradox Superposo of Posso processes Radom seleco of Posso Pos Bulk Arrvals ad

More information

P a g e 3 6 of R e p o r t P B 4 / 0 9

P a g e 3 6 of R e p o r t P B 4 / 0 9 P a g e 3 6 of R e p o r t P B 4 / 0 9 p r o t e c t h um a n h e a l t h a n d p r o p e r t y fr om t h e d a n g e rs i n h e r e n t i n m i n i n g o p e r a t i o n s s u c h a s a q u a r r y. J

More information

Chapters 2 Kinematics. Position, Distance, Displacement

Chapters 2 Kinematics. Position, Distance, Displacement Chapers Knemacs Poson, Dsance, Dsplacemen Mechancs: Knemacs and Dynamcs. Knemacs deals wh moon, bu s no concerned wh he cause o moon. Dynamcs deals wh he relaonshp beween orce and moon. The word dsplacemen

More information

THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, OF THE ROMANIAN ACADEMY Volume 10, Number 2/2009, pp

THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, OF THE ROMANIAN ACADEMY Volume 10, Number 2/2009, pp THE PUBLIHING HOUE PROCEEDING OF THE ROMANIAN ACADEMY, eres A, OF THE ROMANIAN ACADEMY Volume 0, Number /009,. 000-000 ON ZALMAI EMIPARAMETRIC DUALITY MODEL FOR MULTIOBJECTIVE FRACTIONAL PROGRAMMING WITH

More information

H STO RY OF TH E SA NT

H STO RY OF TH E SA NT O RY OF E N G L R R VER ritten for the entennial of th e Foundin g of t lair oun t y on ay 8 82 Y EEL N E JEN K RP O N! R ENJ F ] jun E 3 1 92! Ph in t ed b y h e t l a i r R ep u b l i c a n O 4 1922

More information

Use of Non-Conventional Measures of Dispersion for Improved Estimation of Population Mean

Use of Non-Conventional Measures of Dispersion for Improved Estimation of Population Mean Amerca Joural of Operaoal esearch 06 6(: 69-75 DOI: 0.59/.aor.06060.0 Use of o-coveoal Measures of Dsperso for Improve Esmao of Populao Mea ubhash Kumar aav.. Mshra * Alok Kumar hukla hak Kumar am agar

More information

(1) Cov(, ) E[( E( ))( E( ))]

(1) Cov(, ) E[( E( ))( E( ))] Impac of Auocorrelao o OLS Esmaes ECON 3033/Evas Cosder a smple bvarae me-seres model of he form: y 0 x The four key assumpos abou ε hs model are ) E(ε ) = E[ε x ]=0 ) Var(ε ) =Var(ε x ) = ) Cov(ε, ε )

More information

Density estimation III.

Density estimation III. Lecure 6 esy esmao III. Mlos Hausrec mlos@cs..eu 539 Seo Square Oule Oule: esy esmao: Bomal srbuo Mulomal srbuo ormal srbuo Eoeal famly aa: esy esmao {.. } a vecor of arbue values Objecve: ry o esmae e

More information

The Mean Residual Lifetime of (n k + 1)-out-of-n Systems in Discrete Setting

The Mean Residual Lifetime of (n k + 1)-out-of-n Systems in Discrete Setting Appled Mahemacs 4 5 466-477 Publshed Ole February 4 (hp//wwwscrporg/oural/am hp//dxdoorg/436/am45346 The Mea Resdual Lfeme of ( + -ou-of- Sysems Dscree Seg Maryam Torab Sahboom Deparme of Sascs Scece ad

More information

A L A BA M A L A W R E V IE W

A L A BA M A L A W R E V IE W A L A BA M A L A W R E V IE W Volume 52 Fall 2000 Number 1 B E F O R E D I S A B I L I T Y C I V I L R I G HT S : C I V I L W A R P E N S I O N S A N D TH E P O L I T I C S O F D I S A B I L I T Y I N

More information

I. OBJECTIVE OF THE EXPERIMENT.

I. OBJECTIVE OF THE EXPERIMENT. I. OBJECTIVE OF THE EXPERIMENT. Swissmero raels a high speeds hrough a unnel a low pressure. I will hereore undergo ricion ha can be due o: ) Viscosiy o gas (c. "Viscosiy o gas" eperimen) ) The air in

More information

θ = θ Π Π Parametric counting process models θ θ θ Log-likelihood: Consider counting processes: Score functions:

θ = θ Π Π Parametric counting process models θ θ θ Log-likelihood: Consider counting processes: Score functions: Paramerc coug process models Cosder coug processes: N,,..., ha cou he occurreces of a eve of eres for dvduals Iesy processes: Lelhood λ ( ;,,..., N { } λ < Log-lelhood: l( log L( Score fucos: U ( l( log

More information

Square law expression is non linear between I D and V GS. Need to operate in appropriate region for linear behaviour. W L

Square law expression is non linear between I D and V GS. Need to operate in appropriate region for linear behaviour. W L MOS Feld-Effec Trassrs (MOSFETs ecure # 4 MOSFET as a Amplfer k ( S Square law express s lear bewee ad. Need perae apprprae reg fr lear behaur. Cpyrgh 004 by Oxfrd Uersy Press, c. MOSFET as a Amplfer S

More information

Big O Notation for Time Complexity of Algorithms

Big O Notation for Time Complexity of Algorithms BRONX COMMUNITY COLLEGE of he Ciy Uiversiy of New York DEPARTMENT OF MATHEMATICS AND COMPUTER SCIENCE CSI 33 Secio E01 Hadou 1 Fall 2014 Sepember 3, 2014 Big O Noaio for Time Complexiy of Algorihms Time

More information

Cyclone. Anti-cyclone

Cyclone. Anti-cyclone Adveco Cycloe A-cycloe Lorez (963) Low dmesoal aracors. Uclear f hey are a good aalogy o he rue clmae sysem, bu hey have some appealg characerscs. Dscusso Is he al codo balaced? Is here a al adjusme

More information

ELEC 6041 LECTURE NOTES WEEK 3 Dr. Amir G. Aghdam Concordia University

ELEC 6041 LECTURE NOTES WEEK 3 Dr. Amir G. Aghdam Concordia University ecre Noe Prepared b r G. ghda EE 64 ETUE NTE WEE r. r G. ghda ocorda Uer eceraled orol e - Whe corol heor appled o a e ha co of geographcall eparaed copoe or a e cog of a large ber of p-op ao ofe dered

More information

On Metric Dimension of Two Constructed Families from Antiprism Graph

On Metric Dimension of Two Constructed Families from Antiprism Graph Mah S Le 2, No, -7 203) Mahemaal Sees Leers A Ieraoal Joural @ 203 NSP Naural Sees Publhg Cor O Mer Dmeso of Two Cosrued Famles from Aprm Graph M Al,2, G Al,2 ad M T Rahm 2 Cere for Mahemaal Imagg Tehques

More information

Analysis of error propagation in profile measurement by using stitching

Analysis of error propagation in profile measurement by using stitching Ay o error propgto proe eureet y ug ttchg Ttuy KUME, Kzuhro ENAMI, Yuo HIGASHI, Kej UENO - Oho, Tuu, Ir, 35-8, JAPAN Atrct Sttchg techque whch ee oger eureet rge o proe ro eer eure proe hg prty oerppe

More information

176 5 t h Fl oo r. 337 P o ly me r Ma te ri al s

176 5 t h Fl oo r. 337 P o ly me r Ma te ri al s A g la di ou s F. L. 462 E l ec tr on ic D ev el op me nt A i ng er A.W.S. 371 C. A. M. A l ex an de r 236 A d mi ni st ra ti on R. H. (M rs ) A n dr ew s P. V. 326 O p ti ca l Tr an sm is si on A p ps

More information

Search algorithm for a Common design of a Robotic End-Effector for a Set of 3D objects

Search algorithm for a Common design of a Robotic End-Effector for a Set of 3D objects Search algorhm for a Commo esg of a Roboc E-Effecor for a Se of 3D obecs Avsha Sov a Amr Shapro Deparme of Mechacal Egeerg, Be-Guro Uversy of he Negev, Beer Sheva 8405, Israel. sova@pos.bgu.ac.l, ashapro@bgu.ac.l

More information

New approach for numerical solution of Fredholm integral equations system of the second kind by using an expansion method

New approach for numerical solution of Fredholm integral equations system of the second kind by using an expansion method Ieraoal Reearch Joural o Appled ad Bac Scece Avalable ole a wwwrabcom ISSN 5-88X / Vol : 8- Scece xplorer Publcao New approach or umercal oluo o Fredholm eral equao yem o he ecod d by u a expao mehod Nare

More information

Speech, NLP and the Web

Speech, NLP and the Web peech NL ad he Web uhpak Bhaacharyya CE Dep. IIT Bombay Lecure 38: Uuperved learg HMM CFG; Baum Welch lecure 37 wa o cogve NL by Abh Mhra Baum Welch uhpak Bhaacharyya roblem HMM arg emac ar of peech Taggg

More information

FORCED VIBRATION of MDOF SYSTEMS

FORCED VIBRATION of MDOF SYSTEMS FORCED VIBRAION of DOF SSES he respose of a N DOF sysem s govered by he marx equao of moo: ] u C] u K] u 1 h al codos u u0 ad u u 0. hs marx equao of moo represes a sysem of N smulaeous equaos u ad s me

More information

Chapter 8. Simple Linear Regression

Chapter 8. Simple Linear Regression Chaper 8. Smple Lear Regresso Regresso aalyss: regresso aalyss s a sascal mehodology o esmae he relaoshp of a respose varable o a se of predcor varable. whe here s jus oe predcor varable, we wll use smple

More information

Analog of the Method of Boundary Layer Function for the Solution of the Lighthill s Model Equation with the Regular Singular Point

Analog of the Method of Boundary Layer Function for the Solution of the Lighthill s Model Equation with the Regular Singular Point Aerca Joura of Maheacs a Sascs 3, 3(): 53-6 DOI: 593/as338 Aaog of he Meho of Bouary Layer Fuco for he Souo of he Lghh s Moe Equao wh he Reguar Sguar Po Kebay Ayuov Depare of Agebra a Geoery, Osh Sae Uversy,

More information

A New Dynamic Random Fuzzy DEA Model to Predict Performance of Decision Making Units

A New Dynamic Random Fuzzy DEA Model to Predict Performance of Decision Making Units Jo o Ozo I Egg 6 75-9 A w D Ro Fzz DEA Mo o P Po o Do Mg U A gho * Mgho A Azoh S Sgh A Poo D o I Egg F o Egg P--oo U Th I Poo D o I Mg Ah T U Th I A Poo D o I Egg F o Egg P--oo U Th I R Oo 4; R 3 J 5;

More information

FALL HOMEWORK NO. 6 - SOLUTION Problem 1.: Use the Storage-Indication Method to route the Input hydrograph tabulated below.

FALL HOMEWORK NO. 6 - SOLUTION Problem 1.: Use the Storage-Indication Method to route the Input hydrograph tabulated below. Jorge A. Ramírez HOMEWORK NO. 6 - SOLUTION Problem 1.: Use he Sorage-Idcao Mehod o roue he Ipu hydrograph abulaed below. Tme (h) Ipu Hydrograph (m 3 /s) Tme (h) Ipu Hydrograph (m 3 /s) 0 0 90 450 6 50

More information

Extremal graph theory II: K t and K t,t

Extremal graph theory II: K t and K t,t Exremal graph heory II: K ad K, Lecure Graph Theory 06 EPFL Frak de Zeeuw I his lecure, we geeralize he wo mai heorems from he las lecure, from riagles K 3 o complee graphs K, ad from squares K, o complee

More information

Hamilton s principle for non-holonomic systems

Hamilton s principle for non-holonomic systems Das Hamltosche Przp be chtholoome Systeme, Math. A. (935), pp. 94-97. Hamlto s prcple for o-holoomc systems by Georg Hamel Berl Traslate by: D. H. Delphech I the paper Le prcpe e Hamlto et l holoomsme,

More information

Bianchi Type II Stiff Fluid Tilted Cosmological Model in General Relativity

Bianchi Type II Stiff Fluid Tilted Cosmological Model in General Relativity Ieraoal Joural of Mahemacs esearch. IN 0976-50 Volume 6, Number (0), pp. 6-7 Ieraoal esearch Publcao House hp://www.rphouse.com Bach ype II ff Flud led Cosmologcal Model Geeral elay B. L. Meea Deparme

More information

_ J.. C C A 551NED. - n R ' ' t i :. t ; . b c c : : I I .., I AS IEC. r '2 5? 9

_ J.. C C A 551NED. - n R ' ' t i :. t ; . b c c : : I I .., I AS IEC. r '2 5? 9 C C A 55NED n R 5 0 9 b c c \ { s AS EC 2 5? 9 Con 0 \ 0265 o + s ^! 4 y!! {! w Y n < R > s s = ~ C c [ + * c n j R c C / e A / = + j ) d /! Y 6 ] s v * ^ / ) v } > { ± n S = S w c s y c C { ~! > R = n

More information

Solution to Some Open Problems on E-super Vertex Magic Total Labeling of Graphs

Solution to Some Open Problems on E-super Vertex Magic Total Labeling of Graphs Aalable a hp://paed/aa Appl Appl Mah ISS: 9-9466 Vol 0 Isse (Deceber 0) pp 04- Applcaos ad Appled Maheacs: A Ieraoal Joral (AAM) Solo o Soe Ope Probles o E-sper Verex Magc Toal Labelg o Graphs G Marh MS

More information

Physics Notes - Ch. 2 Motion in One Dimension

Physics Notes - Ch. 2 Motion in One Dimension Physics Noes - Ch. Moion in One Dimension I. The naure o physical quaniies: scalars and ecors A. Scalar quaniy ha describes only magniude (how much), NOT including direcion; e. mass, emperaure, ime, olume,

More information

A stopping criterion for Richardson s extrapolation scheme. under finite digit arithmetic.

A stopping criterion for Richardson s extrapolation scheme. under finite digit arithmetic. A stoppg crtero for cardso s extrapoato sceme uder fte dgt artmetc MAKOO MUOFUSHI ad HIEKO NAGASAKA epartmet of Lbera Arts ad Sceces Poytecc Uversty 4-1-1 Hasmotoda,Sagamara,Kaagawa 229-1196 JAPAN Abstract:

More information

EMA5001 Lecture 3 Steady State & Nonsteady State Diffusion - Fick s 2 nd Law & Solutions

EMA5001 Lecture 3 Steady State & Nonsteady State Diffusion - Fick s 2 nd Law & Solutions EMA5 Lecue 3 Seady Sae & Noseady Sae ffuso - Fck s d Law & Soluos EMA 5 Physcal Popees of Maeals Zhe heg (6) 3 Noseady Sae ff Fck s d Law Seady-Sae ffuso Seady Sae Seady Sae = Equlbum? No! Smlay: Sae fuco

More information

Estimation for Nonnegative First-Order Autoregressive Processes with an Unknown Location Parameter

Estimation for Nonnegative First-Order Autoregressive Processes with an Unknown Location Parameter Appe Maheacs 0 3 33-47 hp://oorg/0436/a03a94 Pubshe Oe Deceber 0 (hp://wwwscrporg/oura/a) Esao for Noegave Frs-Orer Auoregressve Processes wh a Uow Locao Paraeer Arew Bare Wa McCorc Uversy of Georga Ahes

More information

total distance cov ered time int erval v = average speed (m/s)

total distance cov ered time int erval v = average speed (m/s) Physics Suy Noes Lesson 4 Linear Moion 1 Change an Moion a. A propery common o eeryhing in he unierse is change. b. Change is so imporan ha he funamenal concep of ime woul be meaningless wihou i. c. Since

More information

4.1 Schrödinger Equation in Spherical Coordinates

4.1 Schrödinger Equation in Spherical Coordinates Phs 34 Quu Mehs D 9 9 Mo./ Wed./ Thus /3 F./4 Mo., /7 Tues. / Wed., /9 F., /3 4.. -. Shodge Sphe: Sepo & gu (Q9.) 4..-.3 Shodge Sphe: gu & d(q9.) Copuo: Sphe Shodge s 4. Hdoge o (Q9.) 4.3 gu Moeu 4.4.-.

More information

Hyperbolic Heat Equation as Mathematical Model for Steel Quenching of L-shape and T-shape Samples, Direct and Inverse Problems

Hyperbolic Heat Equation as Mathematical Model for Steel Quenching of L-shape and T-shape Samples, Direct and Inverse Problems SEAS RANSACIONS o HEA MASS RANSER Bos M Be As Bs Hpeo He Eo s Me Moe o See Qe o L-spe -spe Spes De Iese Poes ABIA BOBINSKA o Pss Mes es o L Ze See 8 L R LAIA e@o MARARIA BIKE ANDRIS BIKIS Ise o Mes Cope

More information

SUMMATION OF INFINITE SERIES REVISITED

SUMMATION OF INFINITE SERIES REVISITED SUMMATION OF INFINITE SERIES REVISITED I several aricles over he las decade o his web page we have show how o sum cerai iiie series icludig he geomeric series. We wa here o eed his discussio o he geeral

More information

ONE APPROACH FOR THE OPTIMIZATION OF ESTIMATES CALCULATING ALGORITHMS A.A. Dokukin

ONE APPROACH FOR THE OPTIMIZATION OF ESTIMATES CALCULATING ALGORITHMS A.A. Dokukin Iero Jor "Iforo Theore & co" Vo 463 ONE PPROH FOR THE OPTIIZTION OF ETITE UTING GORITH Do rc: I h rce he ew roch for ozo of eo ccg gorh ggeed I c e ed for fdg he correc gorh of coexy he coex of gerc roch

More information

AN IMMERSED BOUNDARY METHOD WITH FEEDBACK FORCING FOR SIMULATION OF FLOW AROUND AN ARBITRARILY MOVING BODY

AN IMMERSED BOUNDARY METHOD WITH FEEDBACK FORCING FOR SIMULATION OF FLOW AROUND AN ARBITRARILY MOVING BODY 7- Augus, 7, Daejeo, KOREA A IMMERSED BOUDARY METHOD WITH EEDBACK ORCIG OR SIMUATIO O OW AROUD A ARBITRARIY MOVIG BODY S. J. Sh, W. -. Huag, H. J. Sug Deparme o Mechaca Egeerg, Korea Advaced Isue o Scece

More information

Abstract. 1. Introduction

Abstract. 1. Introduction Joura of Mathematca Sceces: Advaces ad Appcatos Voume 4 umber 2 2 Pages 33-34 COVERGECE OF HE PROJECO YPE SHKAWA ERAO PROCESS WH ERRORS FOR A FE FAMY OF OSEF -ASYMPOCAY QUAS-OEXPASVE MAPPGS HUA QU ad S-SHEG

More information

Probabilistic Graphical Models

Probabilistic Graphical Models Pros Grh Moes 0708 Lerg Coeey Oserve Uree Grh Moes Er Xg Leure O 9 005 Reg: MJCh. 990 Re: or Bs I we ssue he reers or eh CPD re goy eee oes re uy oserve he he kehoo uo eooses o su o o ers oe er oe: D D

More information

Parameters Estimation in a General Failure Rate Semi-Markov Reliability Model

Parameters Estimation in a General Failure Rate Semi-Markov Reliability Model Joura of Saca Theory ad Appcao Vo. No. (Sepember ) - Parameer Emao a Geera Faure Rae Sem-Marov Reaby Mode M. Fahzadeh ad K. Khorhda Deparme of Sac Facuy of Mahemaca Scece Va-e-Ar Uvery of Rafaja Rafaja

More information

Calculus Limits. Limit of a function.. 1. One-Sided Limits...1. Infinite limits 2. Vertical Asymptotes...3. Calculating Limits Using the Limit Laws.

Calculus Limits. Limit of a function.. 1. One-Sided Limits...1. Infinite limits 2. Vertical Asymptotes...3. Calculating Limits Using the Limit Laws. Limi of a fucio.. Oe-Sided..... Ifiie limis Verical Asympoes... Calculaig Usig he Limi Laws.5 The Squeeze Theorem.6 The Precise Defiiio of a Limi......7 Coiuiy.8 Iermediae Value Theorem..9 Refereces..

More information

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse P a g e Vol Issue7Ver,oveber Global Joural of Scece Froer Research Asypoc Behavor of Soluos of olear Delay Dffereal Equaos Wh Ipulse Zhag xog GJSFR Classfcao - F FOR 3 Absrac Ths paper sudes he asypoc

More information

Conquering kings their titles take ANTHEM FOR CONGREGATION AND CHOIR

Conquering kings their titles take ANTHEM FOR CONGREGATION AND CHOIR Coquerg gs her es e NTHEM FOR CONGREGTION ND CHOIR I oucg hs hm-hem, whch m be cuded Servce eher s Hm or s hem, he Cogrego m be referred o he No. of he Hm whch he words pper, d ved o o sgg he 1 s, 4 h,

More information

Exact Solutions of Axially Symmetric Bianchi Type-I Cosmological Model in Lyra Geometry

Exact Solutions of Axially Symmetric Bianchi Type-I Cosmological Model in Lyra Geometry IOSR Joura of ed Physcs (IOSR-JP) e-issn: 78-86. Voume 5, Issue 6 (Ja. ), PP -5 ac Souos of ay Symmerc ach Tye-I Cosmooca Mode Lyra Geomery. sar, M. sar earme of Mahemacs, Norh-aser H Uversy, Permae Camus,

More information

For the plane motion of a rigid body, an additional equation is needed to specify the state of rotation of the body.

For the plane motion of a rigid body, an additional equation is needed to specify the state of rotation of the body. The kecs of rgd bodes reas he relaoshps bewee he exeral forces acg o a body ad he correspodg raslaoal ad roaoal moos of he body. he kecs of he parcle, we foud ha wo force equaos of moo were requred o defe

More information

xp (X = x) = P (X = 1) = θ. Hence, the method of moments estimator of θ is

xp (X = x) = P (X = 1) = θ. Hence, the method of moments estimator of θ is Exercise 7 / page 356 Noe ha X i are ii from Beroulli(θ where 0 θ a Meho of momes: Sice here is oly oe parameer o be esimae we ee oly oe equaio where we equae he rs sample mome wih he rs populaio mome,

More information

Efficient Estimators for Population Variance using Auxiliary Information

Efficient Estimators for Population Variance using Auxiliary Information Global Joural of Mahemacal cece: Theor ad Praccal. IN 97-3 Volume 3, Number (), pp. 39-37 Ieraoal Reearch Publcao Houe hp://www.rphoue.com Effce Emaor for Populao Varace ug Aular Iformao ubhah Kumar Yadav

More information

Anouncements. Conjugate Gradients. Steepest Descent. Outline. Steepest Descent. Steepest Descent

Anouncements. Conjugate Gradients. Steepest Descent. Outline. Steepest Descent. Steepest Descent oucms Couga Gas Mchal Kazha (6.657) Ifomao abou h Sma (6.757) hav b pos ol: hp://www.cs.hu.u/~msha Tch Spcs: o M o Tusay afoo. o Two paps scuss ach w. o Vos fo w s caa paps u by Thusay vg. Oul Rvw of Sps

More information

Using Linnik's Identity to Approximate the Prime Counting Function with the Logarithmic Integral

Using Linnik's Identity to Approximate the Prime Counting Function with the Logarithmic Integral Usig Lii's Ideiy o Approimae he Prime Couig Fucio wih he Logarihmic Iegral Naha McKezie /26/2 aha@icecreambreafas.com Summary:This paper will show ha summig Lii's ideiy from 2 o ad arragig erms i a cerai

More information

9.6 Spherical Wave Solutions of the Scalar. Chapter 9: Radiating Systems, Multipole Fields and Radiation

9.6 Spherical Wave Solutions of the Scalar. Chapter 9: Radiating Systems, Multipole Fields and Radiation Cha 9: Raag Syss, Muo Fs a Raao A Ovvw of Chas o EM Wavs :(ov hs ous sou wav quao bouay Ch. 7 o a wav sa o wo s- sas saa by h - y a Ch. 8 o oug was - Ch. 9 J, ~ ougog g wav o sb, as a aa - Ch. J, ~ ougog

More information

Debabrata Dey and Atanu Lahiri

Debabrata Dey and Atanu Lahiri RESEARCH ARTICLE QUALITY COMPETITION AND MARKET SEGMENTATION IN THE SECURITY SOFTWARE MARKET Debabrata Dey ad Atau Lahr Mchael G. Foster School of Busess, Uersty of Washgto, Seattle, Seattle, WA 9895 U.S.A.

More information

JORIND 9(2) December, ISSN

JORIND 9(2) December, ISSN JORIND 9() December, 011. ISSN 1596 8308. www.rascampus.org., www.ajol.o/jourals/jord THE EXONENTIAL DISTRIBUTION AND THE ALICATION TO MARKOV MODELS Usma Yusu Abubakar Deparme o Mahemacs/Sascs Federal

More information

Analytical Evaluation of Multicenter Nuclear Attraction Integrals for Slater-Type Orbitals Using Guseinov Rotation-Angular Function

Analytical Evaluation of Multicenter Nuclear Attraction Integrals for Slater-Type Orbitals Using Guseinov Rotation-Angular Function I. J. Cop. Mh. S Vo. 5 o. 7 39-3 Ay Evuo of Mu u Ao Ig fo S-yp O Ug Guov Roo-Agu uo Rz Y M Ag Dp of Mh uy of uo fo g A-Khj Uvy Kgo of Su A Dp of Mh uy of S o B Auh Uvy Kgo of Su A A. Ug h Guov oo-gu fuo

More information

Cyclically Interval Total Colorings of Cycles and Middle Graphs of Cycles

Cyclically Interval Total Colorings of Cycles and Middle Graphs of Cycles Ope Joural of Dsree Mahemas 2017 7 200-217 hp://wwwsrporg/joural/ojdm ISSN Ole: 2161-7643 ISSN Pr: 2161-7635 Cylally Ierval Toal Colorgs of Cyles Mddle Graphs of Cyles Yogqag Zhao 1 Shju Su 2 1 Shool of

More information