The Development of a Three-Dimensional Material Point Method Computer Simulation Algorithm for Bullet Impact Studies

Size: px
Start display at page:

Download "The Development of a Three-Dimensional Material Point Method Computer Simulation Algorithm for Bullet Impact Studies"

Transcription

1 MERIN JOURN OF UNDERGRDUTE RESERH VO. 9, NOS. & 3 ( The Develomen of a Three-Dmensonal Maeral on Mehod omuer Smulaon lgorhm for ulle Imac Sudes M.J. onnolly, E. Maldonado and M.W. Roh Dearmen of hyscs Unversy of Norhern Iowa edar Falls, Iowa US Receved November, 8 cceed March 7, 9 STRT The wo-dmensonal Maeral on Mehod (MM algorhm oulned by hen and rannon has been exended o hree dmensons. The develomen of he code s dscussed as well as alcaons for smulang bulle mac on bologcal and non-bologcal sysems. I. INTRODUTION The sudy of bulle macs on varous sysems s a currenly acve research feld whose resuls have moran meanng for he healh and safey of eole. Due esecally o he desrucve naure of bulle nsul, comuer smulaons rove o be very useful n undersandng and redcng he behavor of sysems nvolved n such macs. I s of arcular morance o sudy sysems whose comonens are elasc and can fal. Ths nvolves he bulle and arge beng comosed of eher a fne elemen grd or acual arcles. In order o sudy maeral deformaon and falure, we chose he laer scenaro. One sgnfcan challenge n smulang mac wh sysems comosed of arcles s ha nernal forces need o be communcaed hroughou he obec when deforms. In order o acheve such communcaon s normally hough ha a collson algorhm beween he arcles consung he sysem s requred whch, n hree dmensons s que me consumng. There exss, however a wo-dmensonal (D Maeral on Mehod (MM algorhm evaluaed by han and rannon [] whch allows modelng of elasc behavor and falure wh no conac algorhm, as dscussed laer. The urose of hs work s o develo a hree-dmensonal (3D MM algorhm and o demonsrae s uly for mac smulaons. II. THE MTERI OINT METHOD We began wh he D Maeral on Mehod (MM algorhm oulned and evaluaed by Z. hen and R. rannon []. MM s advanageous because doesn' requre a comlex me consumng algorhm o smulae collsons or maeral falure. Insead, MM mas he mass and momenum of grous of arcles n he smulaon o a background grd and ulzes he conservaon equaon of mass as well as conservaon of momenum o ulmaely advance he sysem hrough me. The use of he background grd also avods enanglemen assocaed wh oher conac based algorhms. To begn wh, he nal condons for he smulaon nclude a collecon of arcles wh nal osons { { x }, veloces v } and boundary condons chosen so as o reflec he moran hyscs of he acual sysem as much as ossble. Nex, he background grd s defned, where comuaonal sace s searaed no a defned number of grd cells n whch nodes are laced n each corner of each cell. The mass M of each arcle a me s 33

2 MERIN JOURN OF UNDERGRDUTE RESERH VO. 9, NOS. & 3 ( maed o he nodes of he grd cells based on he shae funcon N ( resulng n he mass m of node a me : x, m N M N (x. ( The same s done for he momenum (Mv of he arcles:. ( The D rogram uses recangular cells o dvde u sace, wh for nodes one a each verex of he square. Shae funcons hen are used o rovde weghed orons of a arcle s mass and momenum o he grd nodes. Our shae funcons N ( x are calculaed n he followng way, usng egh verces of a box. The coordnaes of he box conanng a arcle are normalzed so ha hey ake on exreme values of or a verces of he box, as shown n Fg.. So f a arcular box has a verex a (x,y,z and anoher verex a (x + x,y + y,z + z across s dagonal, he normalzed coordnaes are ( x x x ( y y y ( z z z (3 and he egh shae funcons used n he arcle o node mangs are calculaed from he normalzed coordnaes as shown n Table so ha hey are equal o uny for a verex (node where he arcle s a and s zero for a gven node f he arcle s a any oher node. Once he mangs n equaons ( and ( s comleed hen he forces a each node mus be calculaed. The nernal force (f arses from elasc deformaon of he obec and s calculaed as Fgure. secon of he MM grd. The gray arcle s n he mddle of s box and so s roeres are oroned ou o he box verces wh weghng funcons bu he whe arcle has he enrey of s roeres assgned o he verex s sng on. ( f n N G ( x s M. (4 The exernal force (f mlemened s hen calculaed a each node f ex c M gm (5 noe ha gravy can be exlcly aken no accoun n equaon 5. Then he nodal acceleraons are obaned usng f a m where he oal force s gven by f n f f ex are hen udaed n me. The node momena ( mv ( mv f, (6 and subsequenly he knemac varables assocaed wh each arcle n he smulaon are udaed usng node o arcle mangs: 34

3 MERIN JOURN OF UNDERGRDUTE RESERH VO. 9, NOS. & 3 ( Node oordnaes Shae Funcon (,, (-(-(- (,, (-(- (,, (- (,, (-(- v a x Nn Nn f m N ( x ( mv N ( x m x v (7 (8 (9 (,, (-(- (,, (- (,, (,, (- Table. Exressons for he egh shae funcons used o ma arcle roeres o each of he egh verces of he grd cube n whch resdes. The new arcle knemac varables n eqs. (7-9 are maed back ono he nodes o oban udaed nodal veloces. Now because he smulaed maeral(s may have deformed n beng udaed, he elasc roeres of he sysem mus be aken no accoun. The rae of sran ensor e s now calculaed from he velocy gradens: e ' ' x x. Here he rmed varables reresen velocy comonens and, exlcly n 3D we have e u x v v y x u w z x u v y x v y u u y y u w z x v w z y w z ( Subsequenly, he 3D elasc sress sran relaonsh s ulzed o calculae he s s udaed sress ensor, where s. Dfferen kl s kl yes of sran n 3D are vsualzed n Fg. and sress s shown n Fg. 3. There are several secal cases of he elasc ensor as well as sran ensor whch wll be dscussed. The algorhm hen reurns o mang arcle roeres o he grd (eq. and s reeaed unl a desred me lm s kl reached. III. SEI SES OF THE ESTIITY TENSOR There form of he elasc ensor s relaed o he symmery roeres of he maeral beng modeled [3]. In he mos general case, he maeral we are dealng wh may have no lanes of symmery a all. In ha case he elasc ensor requres unque elemens o descrbe he elasc 35

4 MERIN JOURN OF UNDERGRDUTE RESERH VO. 9, NOS. & 3 ( 36 Fgure. Dfferen yes of maeral deformaon. Normal comresson or exenson (lef resuls n a volume change for he maeral and s relaed o dagonal elemens of he sran ensor; shear sran (rgh conserves volume and relaes o off-dagonal elemens []. resonse of he maeral. The ensor s necessarly symmerc and so he lower dagonal block s omed bu mled: U T S R Q O N M K J I H G F E D. ( Now suose he maeral has one lane of symmery. I s ermed monoclnc and he number of elemens of he elasc ensor needed are now only 3. Ths arses from he fac ha he maeral roeres do no change uon a mrror reflecon abou he (x,y lane so he sresses are dencal for he srans and T ', where. The resul s U S Q O K H G F. ( n orhoroc maeral has 3 lanes of symmery and hen he elasc ensor s furher reduced o nne elemens: U S H G. (3 Now furher assume ha he maeral has 3 lanes of symmery and one s soroc. Then only fve ndeenden consans are needed

5 MERIN JOURN OF UNDERGRDUTE RESERH VO. 9, NOS. & 3 ( 37 Fgure 3. Vsualzaon of maeral sress. [3] The e are un ouward normals o he cube of maeral and he elemens of he sress ensor σ are he sresses n drecon acng on he face of he cube sanned by he angen vecos T ( normal o he un vecors e wh coordnae x = consan. (. (4 Now suose ha he maeral s enrely soroc. Then he number of consans reduces o wo: ( ( (. (5

6 MERIN JOURN OF UNDERGRDUTE RESERH VO. 9, NOS. & 3 ( 38 In our smulaons we assume soroc meda and so he elasc ensor akes for form of equaon (5 and he sress-sran relaonsh can be exressed exlcly n erms of relevan maeral roeres: xz yz xy z y x zx yz xy z y x E ( (. (6 Here E s he elasc modulus and s osson s rao. In he case where a flud s beng modeled, sheer forces are comleely absen and he elasc ensor s wren as. (7 SEI SES OF STRIN There are also mes when he geomery of srucures beng consdered has a coordnae whose behavor can be gnored [4]. Ths s usually he case, for examle, when he dmensons of an obec on one dmenson are much larger han n wo ohers. The resuls s lane sran, where he sran ensor akes he form D, (8 and he corresondng sress ensor s wren as e d c b a. (9 For ceran symmeres here may be anlane sran where h g f c. ( Noe for anlane sran ha he resonse of he maeral s urely shear. SIMUTIONS The 3D smulaons develoed here were valdaed by monorng oal mechancal energy conservaon of wo colldng elasc sheres. s shown n Fgure 4, he algorhm conserves oal mechancal energy and ncely descrbes he collson que well. The frs maor alcaon of he 3D MM mehod s bulle mac on a muscle / bone comose srucure. Fgure 5 shows a relmnary smulaon where a roecle nsuls a smulaed muscle / bone comlex. The MM mehod has also been used o smulae bulle mac on

7 MERIN JOURN OF UNDERGRDUTE RESERH VO. 9, NOS. & 3 ( Fgure 4. Knec energy (snusodal curve sarng a uer lef, elasc oenal energy (snusodal curve sarng a lower lef and oal mechancal energy (horzonal lne a o for he wo-shere collson valdaon run. Fgure 5. Sequence s o lef o boom rgh. Snashos from a relmnary muscle/bone mac smulaon. The bulle eners a lef; muscle ssue s dark gray and bone s whe; all maerals have dfferen elasc roeres. 39

8 MERIN JOURN OF UNDERGRDUTE RESERH VO. 9, NOS. & 3 ( Fgure 6. ulle mac on ceramc / Kevlar comose ves for varous fracons of maeral breakng ons. ceramc/kevlar comose vess; a ycal run s shown below where he sensvy of he resuls o he maerals elasc breakng ons s examned. REFERENES. Z hen, RM rannon, Sanda Naonal aboraores (SND-48,. Mahemacs of Sran and Sran Rae, eded by sbørn Søylen, Norwegan Unversy of Scence and Technology: h://folk.nnu.no/soylen/sranrae/mahemahcs/ 3. Infnesmal Sran Theory, Wkeda arcle: h://en.wkeda.org/wk/sran_ensor 4. Hgh Srengh omoses by cha Rusmee, webage Unversy of Uah, Dearmen of Mechancal Engneerng: h:// moses.hml 4

Solution in semi infinite diffusion couples (error function analysis)

Solution in semi infinite diffusion couples (error function analysis) Soluon n sem nfne dffuson couples (error funcon analyss) Le us consder now he sem nfne dffuson couple of wo blocks wh concenraon of and I means ha, n a A- bnary sysem, s bondng beween wo blocks made of

More information

Lecture 18: The Laplace Transform (See Sections and 14.7 in Boas)

Lecture 18: The Laplace Transform (See Sections and 14.7 in Boas) Lecure 8: The Lalace Transform (See Secons 88- and 47 n Boas) Recall ha our bg-cure goal s he analyss of he dfferenal equaon, ax bx cx F, where we emloy varous exansons for he drvng funcon F deendng on

More information

A Cell Decomposition Approach to Online Evasive Path Planning and the Video Game Ms. Pac-Man

A Cell Decomposition Approach to Online Evasive Path Planning and the Video Game Ms. Pac-Man Cell Decomoson roach o Onlne Evasve Pah Plannng and he Vdeo ame Ms. Pac-Man reg Foderaro Vram Raju Slva Ferrar Laboraory for Inellgen Sysems and Conrols LISC Dearmen of Mechancal Engneerng and Maerals

More information

FI 3103 Quantum Physics

FI 3103 Quantum Physics /9/4 FI 33 Quanum Physcs Aleander A. Iskandar Physcs of Magnesm and Phooncs Research Grou Insu Teknolog Bandung Basc Conces n Quanum Physcs Probably and Eecaon Value Hesenberg Uncerany Prncle Wave Funcon

More information

2.1 Constitutive Theory

2.1 Constitutive Theory Secon.. Consuve Theory.. Consuve Equaons Governng Equaons The equaons governng he behavour of maerals are (n he spaal form) dρ v & ρ + ρdv v = + ρ = Conservaon of Mass (..a) d x σ j dv dvσ + b = ρ v& +

More information

PHYS 705: Classical Mechanics. Canonical Transformation

PHYS 705: Classical Mechanics. Canonical Transformation PHYS 705: Classcal Mechancs Canoncal Transformaon Canoncal Varables and Hamlonan Formalsm As we have seen, n he Hamlonan Formulaon of Mechancs,, are ndeenden varables n hase sace on eual foong The Hamlon

More information

V.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS

V.Abramov - FURTHER ANALYSIS OF CONFIDENCE INTERVALS FOR LARGE CLIENT/SERVER COMPUTER NETWORKS R&RATA # Vol.) 8, March FURTHER AALYSIS OF COFIDECE ITERVALS FOR LARGE CLIET/SERVER COMPUTER ETWORKS Vyacheslav Abramov School of Mahemacal Scences, Monash Unversy, Buldng 8, Level 4, Clayon Campus, Wellngon

More information

CH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC

CH.3. COMPATIBILITY EQUATIONS. Continuum Mechanics Course (MMC) - ETSECCPB - UPC CH.3. COMPATIBILITY EQUATIONS Connuum Mechancs Course (MMC) - ETSECCPB - UPC Overvew Compably Condons Compably Equaons of a Poenal Vecor Feld Compably Condons for Infnesmal Srans Inegraon of he Infnesmal

More information

[ ] 2. [ ]3 + (Δx i + Δx i 1 ) / 2. Δx i-1 Δx i Δx i+1. TPG4160 Reservoir Simulation 2018 Lecture note 3. page 1 of 5

[ ] 2. [ ]3 + (Δx i + Δx i 1 ) / 2. Δx i-1 Δx i Δx i+1. TPG4160 Reservoir Simulation 2018 Lecture note 3. page 1 of 5 TPG460 Reservor Smulaon 08 page of 5 DISCRETIZATIO OF THE FOW EQUATIOS As we already have seen, fne dfference appromaons of he paral dervaves appearng n he flow equaons may be obaned from Taylor seres

More information

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD

HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Journal of Appled Mahemacs and Compuaonal Mechancs 3, (), 45-5 HEAT CONDUCTION PROBLEM IN A TWO-LAYERED HOLLOW CYLINDER BY USING THE GREEN S FUNCTION METHOD Sansław Kukla, Urszula Sedlecka Insue of Mahemacs,

More information

( ) () we define the interaction representation by the unitary transformation () = ()

( ) () we define the interaction representation by the unitary transformation () = () Hgher Order Perurbaon Theory Mchael Fowler 3/7/6 The neracon Represenaon Recall ha n he frs par of hs course sequence, we dscussed he chrödnger and Hesenberg represenaons of quanum mechancs here n he chrödnger

More information

GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS. Youngwoo Ahn and Kitae Kim

GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS. Youngwoo Ahn and Kitae Kim Korean J. Mah. 19 (2011), No. 3, pp. 263 272 GENERATING CERTAIN QUINTIC IRREDUCIBLE POLYNOMIALS OVER FINITE FIELDS Youngwoo Ahn and Kae Km Absrac. In he paper [1], an explc correspondence beween ceran

More information

On One Analytic Method of. Constructing Program Controls

On One Analytic Method of. Constructing Program Controls Appled Mahemacal Scences, Vol. 9, 05, no. 8, 409-407 HIKARI Ld, www.m-hkar.com hp://dx.do.org/0.988/ams.05.54349 On One Analyc Mehod of Consrucng Program Conrols A. N. Kvko, S. V. Chsyakov and Yu. E. Balyna

More information

EP2200 Queuing theory and teletraffic systems. 3rd lecture Markov chains Birth-death process - Poisson process. Viktoria Fodor KTH EES

EP2200 Queuing theory and teletraffic systems. 3rd lecture Markov chains Birth-death process - Poisson process. Viktoria Fodor KTH EES EP Queung heory and eleraffc sysems 3rd lecure Marov chans Brh-deah rocess - Posson rocess Vora Fodor KTH EES Oulne for oday Marov rocesses Connuous-me Marov-chans Grah and marx reresenaon Transen and

More information

Lecture 9: Dynamic Properties

Lecture 9: Dynamic Properties Shor Course on Molecular Dynamcs Smulaon Lecure 9: Dynamc Properes Professor A. Marn Purdue Unversy Hgh Level Course Oulne 1. MD Bascs. Poenal Energy Funcons 3. Inegraon Algorhms 4. Temperaure Conrol 5.

More information

THE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS

THE PREDICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS THE PREICTION OF COMPETITIVE ENVIRONMENT IN BUSINESS INTROUCTION The wo dmensonal paral dfferenal equaons of second order can be used for he smulaon of compeve envronmen n busness The arcle presens he

More information

Variants of Pegasos. December 11, 2009

Variants of Pegasos. December 11, 2009 Inroducon Varans of Pegasos SooWoong Ryu bshboy@sanford.edu December, 009 Youngsoo Cho yc344@sanford.edu Developng a new SVM algorhm s ongong research opc. Among many exng SVM algorhms, we wll focus on

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs Physcs 5 Lecure 9 Hamlonan Equaons of Moon (Chaper 8) Wha We Dd Las Tme Consruced Hamlonan formalsm H ( q, p, ) = q p L( q, q, ) H p = q H q = p H = L Equvalen o Lagrangan formalsm Smpler, bu

More information

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION

UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 2017 EXAMINATION INTERNATIONAL TRADE T. J. KEHOE UNIVERSITAT AUTÒNOMA DE BARCELONA MARCH 27 EXAMINATION Please answer wo of he hree quesons. You can consul class noes, workng papers, and arcles whle you are workng on he

More information

Scattering at an Interface: Oblique Incidence

Scattering at an Interface: Oblique Incidence Course Insrucor Dr. Raymond C. Rumpf Offce: A 337 Phone: (915) 747 6958 E Mal: rcrumpf@uep.edu EE 4347 Appled Elecromagnecs Topc 3g Scaerng a an Inerface: Oblque Incdence Scaerng These Oblque noes may

More information

Mechanics Physics 151

Mechanics Physics 151 Mechancs Physcs 5 Lecure 9 Hamlonan Equaons of Moon (Chaper 8) Wha We Dd Las Tme Consruced Hamlonan formalsm Hqp (,,) = qp Lqq (,,) H p = q H q = p H L = Equvalen o Lagrangan formalsm Smpler, bu wce as

More information

J i-1 i. J i i+1. Numerical integration of the diffusion equation (I) Finite difference method. Spatial Discretization. Internal nodes.

J i-1 i. J i i+1. Numerical integration of the diffusion equation (I) Finite difference method. Spatial Discretization. Internal nodes. umercal negraon of he dffuson equaon (I) Fne dfference mehod. Spaal screaon. Inernal nodes. R L V For hermal conducon le s dscree he spaal doman no small fne spans, =,,: Balance of parcles for an nernal

More information

NPTEL Project. Econometric Modelling. Module23: Granger Causality Test. Lecture35: Granger Causality Test. Vinod Gupta School of Management

NPTEL Project. Econometric Modelling. Module23: Granger Causality Test. Lecture35: Granger Causality Test. Vinod Gupta School of Management P age NPTEL Proec Economerc Modellng Vnod Gua School of Managemen Module23: Granger Causaly Tes Lecure35: Granger Causaly Tes Rudra P. Pradhan Vnod Gua School of Managemen Indan Insue of Technology Kharagur,

More information

Anisotropic Behaviors and Its Application on Sheet Metal Stamping Processes

Anisotropic Behaviors and Its Application on Sheet Metal Stamping Processes Ansoropc Behavors and Is Applcaon on Shee Meal Sampng Processes Welong Hu ETA-Engneerng Technology Assocaes, Inc. 33 E. Maple oad, Sue 00 Troy, MI 48083 USA 48-79-300 whu@ea.com Jeanne He ETA-Engneerng

More information

John Geweke a and Gianni Amisano b a Departments of Economics and Statistics, University of Iowa, USA b European Central Bank, Frankfurt, Germany

John Geweke a and Gianni Amisano b a Departments of Economics and Statistics, University of Iowa, USA b European Central Bank, Frankfurt, Germany Herarchcal Markov Normal Mxure models wh Applcaons o Fnancal Asse Reurns Appendx: Proofs of Theorems and Condonal Poseror Dsrbuons John Geweke a and Gann Amsano b a Deparmens of Economcs and Sascs, Unversy

More information

Water Hammer in Pipes

Water Hammer in Pipes Waer Haer Hydraulcs and Hydraulc Machnes Waer Haer n Pes H Pressure wave A B If waer s flowng along a long e and s suddenly brough o res by he closng of a valve, or by any slar cause, here wll be a sudden

More information

Motion in Two Dimensions

Motion in Two Dimensions Phys 1 Chaper 4 Moon n Two Dmensons adzyubenko@csub.edu hp://www.csub.edu/~adzyubenko 005, 014 A. Dzyubenko 004 Brooks/Cole 1 Dsplacemen as a Vecor The poson of an objec s descrbed by s poson ecor, r The

More information

Robust and Accurate Cancer Classification with Gene Expression Profiling

Robust and Accurate Cancer Classification with Gene Expression Profiling Robus and Accurae Cancer Classfcaon wh Gene Expresson Proflng (Compuaonal ysems Bology, 2005) Auhor: Hafeng L, Keshu Zhang, ao Jang Oulne Background LDA (lnear dscrmnan analyss) and small sample sze problem

More information

Linear Response Theory: The connection between QFT and experiments

Linear Response Theory: The connection between QFT and experiments Phys540.nb 39 3 Lnear Response Theory: The connecon beween QFT and expermens 3.1. Basc conceps and deas Q: ow do we measure he conducvy of a meal? A: we frs nroduce a weak elecrc feld E, and hen measure

More information

National Exams December 2015 NOTES: 04-BS-13, Biology. 3 hours duration

National Exams December 2015 NOTES: 04-BS-13, Biology. 3 hours duration Naonal Exams December 205 04-BS-3 Bology 3 hours duraon NOTES: f doub exss as o he nerpreaon of any queson he canddae s urged o subm wh he answer paper a clear saemen of any assumpons made 2 Ths s a CLOSED

More information

THE POLYNOMIAL TENSOR INTERPOLATION

THE POLYNOMIAL TENSOR INTERPOLATION Pease ce hs arce as: Grzegorz Berna, Ana Ceo, The oynoma ensor neroaon, Scenfc Research of he Insue of Mahemacs and Comuer Scence, 28, oume 7, Issue, ages 5-. The webse: h://www.amcm.cz./ Scenfc Research

More information

Let s treat the problem of the response of a system to an applied external force. Again,

Let s treat the problem of the response of a system to an applied external force. Again, Page 33 QUANTUM LNEAR RESPONSE FUNCTON Le s rea he problem of he response of a sysem o an appled exernal force. Agan, H() H f () A H + V () Exernal agen acng on nernal varable Hamlonan for equlbrum sysem

More information

How about the more general "linear" scalar functions of scalars (i.e., a 1st degree polynomial of the following form with a constant term )?

How about the more general linear scalar functions of scalars (i.e., a 1st degree polynomial of the following form with a constant term )? lmcd Lnear ransformaon of a vecor he deas presened here are que general hey go beyond he radonal mar-vecor ype seen n lnear algebra Furhermore, hey do no deal wh bass and are equally vald for any se of

More information

THERMODYNAMICS 1. The First Law and Other Basic Concepts (part 2)

THERMODYNAMICS 1. The First Law and Other Basic Concepts (part 2) Company LOGO THERMODYNAMICS The Frs Law and Oher Basc Conceps (par ) Deparmen of Chemcal Engneerng, Semarang Sae Unversy Dhon Harano S.T., M.T., M.Sc. Have you ever cooked? Equlbrum Equlbrum (con.) Equlbrum

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

Inverse Joint Moments of Multivariate. Random Variables

Inverse Joint Moments of Multivariate. Random Variables In J Conem Mah Scences Vol 7 0 no 46 45-5 Inverse Jon Momens of Mulvarae Rom Varables M A Hussan Dearmen of Mahemacal Sascs Insue of Sascal Sudes Research ISSR Caro Unversy Egy Curren address: Kng Saud

More information

EVALUATION OF FORCE COEFFICIENTS FOR A 2-D ANGLE SECTION USING REALIZABLE k-ε TURBULENCE MODEL

EVALUATION OF FORCE COEFFICIENTS FOR A 2-D ANGLE SECTION USING REALIZABLE k-ε TURBULENCE MODEL The Sevenh Asa-Pacfc Conference on Wnd Engneerng, November 8-, 009, Tape, Tawan EVALUATION OF FORCE COEFFICIENTS FOR A -D ANGLE SECTION USING REALIZABLE k-ε TURBULENCE MODEL S. Chra Ganapah, P. Harkrshna,

More information

Cubic Bezier Homotopy Function for Solving Exponential Equations

Cubic Bezier Homotopy Function for Solving Exponential Equations Penerb Journal of Advanced Research n Compung and Applcaons ISSN (onlne: 46-97 Vol. 4, No.. Pages -8, 6 omoopy Funcon for Solvng Eponenal Equaons S. S. Raml *,,. Mohamad Nor,a, N. S. Saharzan,b and M.

More information

. The geometric multiplicity is dim[ker( λi. number of linearly independent eigenvectors associated with this eigenvalue.

. The geometric multiplicity is dim[ker( λi. number of linearly independent eigenvectors associated with this eigenvalue. Lnear Algebra Lecure # Noes We connue wh he dscusson of egenvalues, egenvecors, and dagonalzably of marces We wan o know, n parcular wha condons wll assure ha a marx can be dagonalzed and wha he obsrucons

More information

Department of Economics University of Toronto

Department of Economics University of Toronto Deparmen of Economcs Unversy of Torono ECO408F M.A. Economercs Lecure Noes on Heeroskedascy Heeroskedascy o Ths lecure nvolves lookng a modfcaons we need o make o deal wh he regresson model when some of

More information

Performance Analysis for a Network having Standby Redundant Unit with Waiting in Repair

Performance Analysis for a Network having Standby Redundant Unit with Waiting in Repair TECHNI Inernaonal Journal of Compung Scence Communcaon Technologes VOL.5 NO. July 22 (ISSN 974-3375 erformance nalyss for a Nework havng Sby edundan Un wh ang n epar Jendra Sngh 2 abns orwal 2 Deparmen

More information

A New Generalized Gronwall-Bellman Type Inequality

A New Generalized Gronwall-Bellman Type Inequality 22 Inernaonal Conference on Image, Vson and Comung (ICIVC 22) IPCSIT vol. 5 (22) (22) IACSIT Press, Sngaore DOI:.7763/IPCSIT.22.V5.46 A New Generalzed Gronwall-Bellman Tye Ineualy Qnghua Feng School of

More information

Existence and Uniqueness Results for Random Impulsive Integro-Differential Equation

Existence and Uniqueness Results for Random Impulsive Integro-Differential Equation Global Journal of Pure and Appled Mahemacs. ISSN 973-768 Volume 4, Number 6 (8), pp. 89-87 Research Inda Publcaons hp://www.rpublcaon.com Exsence and Unqueness Resuls for Random Impulsve Inegro-Dfferenal

More information

Approximate Analytic Solution of (2+1) - Dimensional Zakharov-Kuznetsov(Zk) Equations Using Homotopy

Approximate Analytic Solution of (2+1) - Dimensional Zakharov-Kuznetsov(Zk) Equations Using Homotopy Arcle Inernaonal Journal of Modern Mahemacal Scences, 4, (): - Inernaonal Journal of Modern Mahemacal Scences Journal homepage: www.modernscenfcpress.com/journals/jmms.aspx ISSN: 66-86X Florda, USA Approxmae

More information

Chapter Lagrangian Interpolation

Chapter Lagrangian Interpolation Chaper 5.4 agrangan Inerpolaon Afer readng hs chaper you should be able o:. dere agrangan mehod of nerpolaon. sole problems usng agrangan mehod of nerpolaon and. use agrangan nerpolans o fnd deraes and

More information

Comparison of Differences between Power Means 1

Comparison of Differences between Power Means 1 In. Journal of Mah. Analyss, Vol. 7, 203, no., 5-55 Comparson of Dfferences beween Power Means Chang-An Tan, Guanghua Sh and Fe Zuo College of Mahemacs and Informaon Scence Henan Normal Unversy, 453007,

More information

Ordinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s

Ordinary Differential Equations in Neuroscience with Matlab examples. Aim 1- Gain understanding of how to set up and solve ODE s Ordnary Dfferenal Equaons n Neuroscence wh Malab eamples. Am - Gan undersandng of how o se up and solve ODE s Am Undersand how o se up an solve a smple eample of he Hebb rule n D Our goal a end of class

More information

Pavel Azizurovich Rahman Ufa State Petroleum Technological University, Kosmonavtov St., 1, Ufa, Russian Federation

Pavel Azizurovich Rahman Ufa State Petroleum Technological University, Kosmonavtov St., 1, Ufa, Russian Federation VOL., NO. 5, MARCH 8 ISSN 89-668 ARN Journal of Engneerng and Aled Scences 6-8 Asan Research ublshng Nework ARN. All rghs reserved. www.arnjournals.com A CALCULATION METHOD FOR ESTIMATION OF THE MEAN TIME

More information

NATIONAL UNIVERSITY OF SINGAPORE PC5202 ADVANCED STATISTICAL MECHANICS. (Semester II: AY ) Time Allowed: 2 Hours

NATIONAL UNIVERSITY OF SINGAPORE PC5202 ADVANCED STATISTICAL MECHANICS. (Semester II: AY ) Time Allowed: 2 Hours NATONAL UNVERSTY OF SNGAPORE PC5 ADVANCED STATSTCAL MECHANCS (Semeser : AY 1-13) Tme Allowed: Hours NSTRUCTONS TO CANDDATES 1. Ths examnaon paper conans 5 quesons and comprses 4 prned pages.. Answer all

More information

P R = P 0. The system is shown on the next figure:

P R = P 0. The system is shown on the next figure: TPG460 Reservor Smulaon 08 page of INTRODUCTION TO RESERVOIR SIMULATION Analycal and numercal soluons of smple one-dmensonal, one-phase flow equaons As an nroducon o reservor smulaon, we wll revew he smples

More information

Including the ordinary differential of distance with time as velocity makes a system of ordinary differential equations.

Including the ordinary differential of distance with time as velocity makes a system of ordinary differential equations. Soluons o Ordnary Derenal Equaons An ordnary derenal equaon has only one ndependen varable. A sysem o ordnary derenal equaons consss o several derenal equaons each wh he same ndependen varable. An eample

More information

Diffusion of Heptane in Polyethylene Vinyl Acetate: Modelisation and Experimentation

Diffusion of Heptane in Polyethylene Vinyl Acetate: Modelisation and Experimentation IOSR Journal of Appled hemsry (IOSR-JA) e-issn: 78-5736.Volume 7, Issue 6 Ver. I. (Jun. 4), PP 8-86 Dffuson of Hepane n Polyehylene Vnyl Aceae: odelsaon and Expermenaon Rachd Aman *, Façal oubarak, hammed

More information

OP = OO' + Ut + Vn + Wb. Material We Will Cover Today. Computer Vision Lecture 3. Multi-view Geometry I. Amnon Shashua

OP = OO' + Ut + Vn + Wb. Material We Will Cover Today. Computer Vision Lecture 3. Multi-view Geometry I. Amnon Shashua Comuer Vson 27 Lecure 3 Mul-vew Geomer I Amnon Shashua Maeral We Wll Cover oa he srucure of 3D->2D rojecon mar omograh Marces A rmer on rojecve geomer of he lane Eolar Geomer an Funamenal Mar ebrew Unvers

More information

Notes on the stability of dynamic systems and the use of Eigen Values.

Notes on the stability of dynamic systems and the use of Eigen Values. Noes on he sabl of dnamc ssems and he use of Egen Values. Source: Macro II course noes, Dr. Davd Bessler s Tme Seres course noes, zarads (999) Ineremporal Macroeconomcs chaper 4 & Techncal ppend, and Hamlon

More information

CHAPTER 10: LINEAR DISCRIMINATION

CHAPTER 10: LINEAR DISCRIMINATION CHAPER : LINEAR DISCRIMINAION Dscrmnan-based Classfcaon 3 In classfcaon h K classes (C,C,, C k ) We defned dscrmnan funcon g j (), j=,,,k hen gven an es eample, e chose (predced) s class label as C f g

More information

Density Matrix Description of NMR BCMB/CHEM 8190

Density Matrix Description of NMR BCMB/CHEM 8190 Densy Marx Descrpon of NMR BCMBCHEM 89 Operaors n Marx Noaon Alernae approach o second order specra: ask abou x magnezaon nsead of energes and ranson probables. If we say wh one bass se, properes vary

More information

Planar truss bridge optimization by dynamic programming and linear programming

Planar truss bridge optimization by dynamic programming and linear programming IABSE-JSCE Jon Conference on Advances n Brdge Engneerng-III, Augus 1-, 015, Dhaka, Bangladesh. ISBN: 978-984-33-9313-5 Amn, Oku, Bhuyan, Ueda (eds.) www.abse-bd.org Planar russ brdge opmzaon by dynamc

More information

ELASTIC MODULUS ESTIMATION OF CHOPPED CARBON FIBER TAPE REINFORCED THERMOPLASTICS USING THE MONTE CARLO SIMULATION

ELASTIC MODULUS ESTIMATION OF CHOPPED CARBON FIBER TAPE REINFORCED THERMOPLASTICS USING THE MONTE CARLO SIMULATION THE 19 TH INTERNATIONAL ONFERENE ON OMPOSITE MATERIALS ELASTI MODULUS ESTIMATION OF HOPPED ARBON FIBER TAPE REINFORED THERMOPLASTIS USING THE MONTE ARLO SIMULATION Y. Sao 1*, J. Takahash 1, T. Masuo 1,

More information

Density Matrix Description of NMR BCMB/CHEM 8190

Density Matrix Description of NMR BCMB/CHEM 8190 Densy Marx Descrpon of NMR BCMBCHEM 89 Operaors n Marx Noaon If we say wh one bass se, properes vary only because of changes n he coeffcens weghng each bass se funcon x = h< Ix > - hs s how we calculae

More information

Robustness Experiments with Two Variance Components

Robustness Experiments with Two Variance Components Naonal Insue of Sandards and Technology (NIST) Informaon Technology Laboraory (ITL) Sascal Engneerng Dvson (SED) Robusness Expermens wh Two Varance Componens by Ana Ivelsse Avlés avles@ns.gov Conference

More information

Gear System Time-varying Reliability Analysis Based on Elastomer Dynamics

Gear System Time-varying Reliability Analysis Based on Elastomer Dynamics A publcaon of CHEMICAL ENGINEERING TRANSACTIONS VOL. 33, 013 Gues Edors: Enrco Zo, Pero Barald Copyrgh 013, AIDIC Servz S.r.l., ISBN 978-88-95608-4-; ISSN 1974-9791 The Ialan Assocaon of Chemcal Engneerng

More information

APPLICATION OF FLEX-COMPRESSIVE PIEZOELECTRIC ENERGY HARVESTING CELL IN RAILWAY SYSTEM

APPLICATION OF FLEX-COMPRESSIVE PIEZOELECTRIC ENERGY HARVESTING CELL IN RAILWAY SYSTEM 1 s Inernaonal Conference on Comose Maerals X an, -5 h Augus 17 APPLICATION OF FLEX-COMPRESSIVE PIEZOELECTRIC ENERGY HARVESTING CELL IN RAILWAY SYSTEM Xanfeng Wang 1 and Zhfe Sh 1 1 School of Cvl Engneerng,

More information

Chapter 2 Linear dynamic analysis of a structural system

Chapter 2 Linear dynamic analysis of a structural system Chaper Lnear dynamc analyss of a srucural sysem. Dynamc equlbrum he dynamc equlbrum analyss of a srucure s he mos general case ha can be suded as akes no accoun all he forces acng on. When he exernal loads

More information

. The geometric multiplicity is dim[ker( λi. A )], i.e. the number of linearly independent eigenvectors associated with this eigenvalue.

. The geometric multiplicity is dim[ker( λi. A )], i.e. the number of linearly independent eigenvectors associated with this eigenvalue. Mah E-b Lecure #0 Noes We connue wh he dscusson of egenvalues, egenvecors, and dagonalzably of marces We wan o know, n parcular wha condons wll assure ha a marx can be dagonalzed and wha he obsrucons are

More information

Advanced time-series analysis (University of Lund, Economic History Department)

Advanced time-series analysis (University of Lund, Economic History Department) Advanced me-seres analss (Unvers of Lund, Economc Hsor Dearmen) 3 Jan-3 Februar and 6-3 March Lecure 4 Economerc echnues for saonar seres : Unvarae sochasc models wh Box- Jenns mehodolog, smle forecasng

More information

FTCS Solution to the Heat Equation

FTCS Solution to the Heat Equation FTCS Soluon o he Hea Equaon ME 448/548 Noes Gerald Reckenwald Porland Sae Unversy Deparmen of Mechancal Engneerng gerry@pdxedu ME 448/548: FTCS Soluon o he Hea Equaon Overvew Use he forward fne d erence

More information

Time-interval analysis of β decay. V. Horvat and J. C. Hardy

Time-interval analysis of β decay. V. Horvat and J. C. Hardy Tme-nerval analyss of β decay V. Horva and J. C. Hardy Work on he even analyss of β decay [1] connued and resuled n he developmen of a novel mehod of bea-decay me-nerval analyss ha produces hghly accurae

More information

Foundations of State Estimation Part II

Foundations of State Estimation Part II Foundaons of Sae Esmaon Par II Tocs: Hdden Markov Models Parcle Flers Addonal readng: L.R. Rabner, A uoral on hdden Markov models," Proceedngs of he IEEE, vol. 77,. 57-86, 989. Sequenal Mone Carlo Mehods

More information

10. A.C CIRCUITS. Theoretically current grows to maximum value after infinite time. But practically it grows to maximum after 5τ. Decay of current :

10. A.C CIRCUITS. Theoretically current grows to maximum value after infinite time. But practically it grows to maximum after 5τ. Decay of current : . A. IUITS Synopss : GOWTH OF UNT IN IUIT : d. When swch S s closed a =; = d. A me, curren = e 3. The consan / has dmensons of me and s called he nducve me consan ( τ ) of he crcu. 4. = τ; =.63, n one

More information

Imperfect Information

Imperfect Information Imerfec Informaon Comlee Informaon - all layers know: Se of layers Se of sraeges for each layer Oucomes as a funcon of he sraeges Payoffs for each oucome (.e. uly funcon for each layer Incomlee Informaon

More information

CS286.2 Lecture 14: Quantum de Finetti Theorems II

CS286.2 Lecture 14: Quantum de Finetti Theorems II CS286.2 Lecure 14: Quanum de Fne Theorems II Scrbe: Mara Okounkova 1 Saemen of he heorem Recall he las saemen of he quanum de Fne heorem from he prevous lecure. Theorem 1 Quanum de Fne). Le ρ Dens C 2

More information

Computing Relevance, Similarity: The Vector Space Model

Computing Relevance, Similarity: The Vector Space Model Compung Relevance, Smlary: The Vecor Space Model Based on Larson and Hears s sldes a UC-Bereley hp://.sms.bereley.edu/courses/s0/f00/ aabase Managemen Sysems, R. Ramarshnan ocumen Vecors v ocumens are

More information

Dynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005

Dynamic Team Decision Theory. EECS 558 Project Shrutivandana Sharma and David Shuman December 10, 2005 Dynamc Team Decson Theory EECS 558 Proec Shruvandana Sharma and Davd Shuman December 0, 005 Oulne Inroducon o Team Decson Theory Decomposon of he Dynamc Team Decson Problem Equvalence of Sac and Dynamc

More information

MALAYSIAN JOURNAL OF MATHEMATICAL SCIENCES. Institute for Mathematical Research, Universiti Putra Malaysia, UPM Serdang, Selangor, Malaysia

MALAYSIAN JOURNAL OF MATHEMATICAL SCIENCES. Institute for Mathematical Research, Universiti Putra Malaysia, UPM Serdang, Selangor, Malaysia Malaysan Journal of Mahemacal Scences 9(2): 277-300 (2015) MALAYSIAN JOURNAL OF MATHEMATICAL SCIENCES Journal homeage: h://ensemumedumy/journal A Mehod for Deermnng -Adc Orders of Facorals 1* Rafka Zulkal,

More information

Shear Stress-Slip Model for Steel-CFRP Single-Lap Joints under Thermal Loading

Shear Stress-Slip Model for Steel-CFRP Single-Lap Joints under Thermal Loading Shear Sress-Slp Model for Seel-CFRP Sngle-Lap Jons under Thermal Loadng *Ank Agarwal 1), Eha Hamed 2) and Sephen J Foser 3) 1), 2), 3) Cenre for Infrasrucure Engneerng and Safey, School of Cvl and Envronmenal

More information

A New Method for Computing EM Algorithm Parameters in Speaker Identification Using Gaussian Mixture Models

A New Method for Computing EM Algorithm Parameters in Speaker Identification Using Gaussian Mixture Models 0 IACSI Hong Kong Conferences IPCSI vol. 9 (0) (0) IACSI Press, Sngaore A New ehod for Comung E Algorhm Parameers n Seaker Idenfcaon Usng Gaussan xure odels ohsen Bazyar +, Ahmad Keshavarz, and Khaoon

More information

Physical Simulation Using FEM, Modal Analysis and the Dynamic Equilibrium Equation

Physical Simulation Using FEM, Modal Analysis and the Dynamic Equilibrium Equation Physcal Smulaon Usng FEM, Modal Analyss and he Dynamc Equlbrum Equaon Paríca C. T. Gonçalves, Raquel R. Pnho, João Manuel R. S. Tavares Opcs and Expermenal Mechancs Laboraory - LOME, Mechancal Engneerng

More information

Volatility Interpolation

Volatility Interpolation Volaly Inerpolaon Prelmnary Verson March 00 Jesper Andreasen and Bran Huge Danse Mares, Copenhagen wan.daddy@danseban.com brno@danseban.com Elecronc copy avalable a: hp://ssrn.com/absrac=69497 Inro Local

More information

Numerical Simulation of the Dispersion of a Plume of Exhaust Gases from Diesel and Petrol Engine Vehicles

Numerical Simulation of the Dispersion of a Plume of Exhaust Gases from Diesel and Petrol Engine Vehicles World Academy of Scence, Engneerng and Technology 67 01 Numercal Smulaon of he Dsperson of a Plume of Exhaus Gases from Desel and Perol Engne Vehcles H. ZAHLOUL, and M. MERIEM-BENZIANE Absrac The obecve

More information

New M-Estimator Objective Function. in Simultaneous Equations Model. (A Comparative Study)

New M-Estimator Objective Function. in Simultaneous Equations Model. (A Comparative Study) Inernaonal Mahemacal Forum, Vol. 8, 3, no., 7 - HIKARI Ld, www.m-hkar.com hp://dx.do.org/.988/mf.3.3488 New M-Esmaor Objecve Funcon n Smulaneous Equaons Model (A Comparave Sudy) Ahmed H. Youssef Professor

More information

OMXS30 Balance 20% Index Rules

OMXS30 Balance 20% Index Rules OMX30 Balance 0% ndex Rules Verson as of 30 March 009 Copyrgh 008, The NADAQ OMX Group, nc. All rghs reserved. NADAQ OMX, The NADAQ ock Marke and NADAQ are regsered servce/rademarks of The NADAQ OMX Group,

More information

Outline. Energy-Efficient Target Coverage in Wireless Sensor Networks. Sensor Node. Introduction. Characteristics of WSN

Outline. Energy-Efficient Target Coverage in Wireless Sensor Networks. Sensor Node. Introduction. Characteristics of WSN Ener-Effcen Tare Coverae n Wreless Sensor Newors Presened b M Trà Tá -4-4 Inroducon Bacround Relaed Wor Our Proosal Oulne Maxmum Se Covers (MSC) Problem MSC Problem s NP-Comlee MSC Heursc Concluson Sensor

More information

Single-loop System Reliability-Based Design & Topology Optimization (SRBDO/SRBTO): A Matrix-based System Reliability (MSR) Method

Single-loop System Reliability-Based Design & Topology Optimization (SRBDO/SRBTO): A Matrix-based System Reliability (MSR) Method 10 h US Naonal Congress on Compuaonal Mechancs Columbus, Oho 16-19, 2009 Sngle-loop Sysem Relably-Based Desgn & Topology Opmzaon (SRBDO/SRBTO): A Marx-based Sysem Relably (MSR) Mehod Tam Nguyen, Junho

More information

Chapter 3: Signed-rank charts

Chapter 3: Signed-rank charts Chaer : gned-ran chars.. The hewhar-ye conrol char... Inroducon As menoned n Chaer, samles of fxed sze are aen a regular nervals and he long sasc s hen loed. The queson s: Whch qualy arameer should be

More information

Homework 8: Rigid Body Dynamics Due Friday April 21, 2017

Homework 8: Rigid Body Dynamics Due Friday April 21, 2017 EN40: Dynacs and Vbraons Hoework 8: gd Body Dynacs Due Frday Aprl 1, 017 School of Engneerng Brown Unversy 1. The earh s roaon rae has been esaed o decrease so as o ncrease he lengh of a day a a rae of

More information

On computing differential transform of nonlinear non-autonomous functions and its applications

On computing differential transform of nonlinear non-autonomous functions and its applications On compung dfferenal ransform of nonlnear non-auonomous funcons and s applcaons Essam. R. El-Zahar, and Abdelhalm Ebad Deparmen of Mahemacs, Faculy of Scences and Humanes, Prnce Saam Bn Abdulazz Unversy,

More information

Response of MDOF systems

Response of MDOF systems Response of MDOF syses Degree of freedo DOF: he nu nuber of ndependen coordnaes requred o deerne copleely he posons of all pars of a syse a any nsan of e. wo DOF syses hree DOF syses he noral ode analyss

More information

Numerical simulation of a solar chimney power plant in the southern region of Iran

Numerical simulation of a solar chimney power plant in the southern region of Iran Energy Equp. Sys./ Vol. 5/No.4/December 2017/ 431-437 Energy Equpmen and Sysems hp://energyequpsys.u.ac.r www.energyequpsys.com Numercal smulaon of a solar chmney power plan n he souhern regon of Iran

More information

Online Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading

Online Supplement for Dynamic Multi-Technology. Production-Inventory Problem with Emissions Trading Onlne Supplemen for Dynamc Mul-Technology Producon-Invenory Problem wh Emssons Tradng by We Zhang Zhongsheng Hua Yu Xa and Baofeng Huo Proof of Lemma For any ( qr ) Θ s easy o verfy ha he lnear programmng

More information

Part II CONTINUOUS TIME STOCHASTIC PROCESSES

Part II CONTINUOUS TIME STOCHASTIC PROCESSES Par II CONTINUOUS TIME STOCHASTIC PROCESSES 4 Chaper 4 For an advanced analyss of he properes of he Wener process, see: Revus D and Yor M: Connuous marngales and Brownan Moon Karazas I and Shreve S E:

More information

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4

CS434a/541a: Pattern Recognition Prof. Olga Veksler. Lecture 4 CS434a/54a: Paern Recognon Prof. Olga Veksler Lecure 4 Oulne Normal Random Varable Properes Dscrmnan funcons Why Normal Random Varables? Analycally racable Works well when observaon comes form a corruped

More information

Dynamic Model of the Axially Moving Viscoelastic Belt System with Tensioner Pulley Yanqi Liu1, a, Hongyu Wang2, b, Dongxing Cao3, c, Xiaoling Gai1, d

Dynamic Model of the Axially Moving Viscoelastic Belt System with Tensioner Pulley Yanqi Liu1, a, Hongyu Wang2, b, Dongxing Cao3, c, Xiaoling Gai1, d Inernaonal Indsral Informacs and Comper Engneerng Conference (IIICEC 5) Dynamc Model of he Aally Movng Vscoelasc Bel Sysem wh Tensoner Plley Yanq L, a, Hongy Wang, b, Dongng Cao, c, Xaolng Ga, d Bejng

More information

ID-1193 STUDY ON IMPACT BEHAVIOR OF COMPOSITES USING THE FINITE ELEMENT METHOD INTRODUCTION

ID-1193 STUDY ON IMPACT BEHAVIOR OF COMPOSITES USING THE FINITE ELEMENT METHOD INTRODUCTION ID-1193 STUDY ON IMPACT BEHAVIOR OF COMPOSITES USING THE FINITE ELEMENT METHOD Volne Ta and Jonas de Carvalho Deparmen of Mechancal Engneerng, S. Carlos Engneerng School, Unversy of S. Paulo, Brazl SUMMARY:

More information

Survival Analysis and Reliability. A Note on the Mean Residual Life Function of a Parallel System

Survival Analysis and Reliability. A Note on the Mean Residual Life Function of a Parallel System Communcaons n Sascs Theory and Mehods, 34: 475 484, 2005 Copyrgh Taylor & Francs, Inc. ISSN: 0361-0926 prn/1532-415x onlne DOI: 10.1081/STA-200047430 Survval Analyss and Relably A Noe on he Mean Resdual

More information

Lecture 11 SVM cont

Lecture 11 SVM cont Lecure SVM con. 0 008 Wha we have done so far We have esalshed ha we wan o fnd a lnear decson oundary whose margn s he larges We know how o measure he margn of a lnear decson oundary Tha s: he mnmum geomerc

More information

TSS = SST + SSE An orthogonal partition of the total SS

TSS = SST + SSE An orthogonal partition of the total SS ANOVA: Topc 4. Orhogonal conrass [ST&D p. 183] H 0 : µ 1 = µ =... = µ H 1 : The mean of a leas one reamen group s dfferen To es hs hypohess, a basc ANOVA allocaes he varaon among reamen means (SST) equally

More information

G. =, etc.

G. =, etc. Maerial Models υ υ3 0 0 0 υ υ 3 0 0 0 υ3 υ3 0 0 0 = 0 0 0 0 0 0 0 0 0 0 3 0 0 0 0 0 3 l (9..4) he subscris denoe he maerial axes, i.e., υ = υ and = (9..5) i j xi xj ii xi Since l is symmeric υ υ =, ec.

More information

Handout # 6 (MEEN 617) Numerical Integration to Find Time Response of SDOF mechanical system Y X (2) and write EOM (1) as two first-order Eqs.

Handout # 6 (MEEN 617) Numerical Integration to Find Time Response of SDOF mechanical system Y X (2) and write EOM (1) as two first-order Eqs. Handou # 6 (MEEN 67) Numercal Inegraon o Fnd Tme Response of SDOF mechancal sysem Sae Space Mehod The EOM for a lnear sysem s M X DX K X F() () X X X X V wh nal condons, a 0 0 ; 0 Defne he followng varables,

More information

VEHICLE DYNAMIC MODELING & SIMULATION: COMPARING A FINITE- ELEMENT SOLUTION TO A MULTI-BODY DYNAMIC SOLUTION

VEHICLE DYNAMIC MODELING & SIMULATION: COMPARING A FINITE- ELEMENT SOLUTION TO A MULTI-BODY DYNAMIC SOLUTION 21 NDIA GROUND VEHICLE SYSTEMS ENGINEERING AND TECHNOLOGY SYMPOSIUM MODELING & SIMULATION, TESTING AND VALIDATION (MSTV) MINI-SYMPOSIUM AUGUST 17-19 DEARBORN, MICHIGAN VEHICLE DYNAMIC MODELING & SIMULATION:

More information

F-Tests and Analysis of Variance (ANOVA) in the Simple Linear Regression Model. 1. Introduction

F-Tests and Analysis of Variance (ANOVA) in the Simple Linear Regression Model. 1. Introduction ECOOMICS 35* -- OTE 9 ECO 35* -- OTE 9 F-Tess and Analyss of Varance (AOVA n he Smple Lnear Regresson Model Inroducon The smple lnear regresson model s gven by he followng populaon regresson equaon, or

More information