A New Iterative Method for Multi-Moving Boundary Problems Based Boundary Integral Method

Size: px
Start display at page:

Download "A New Iterative Method for Multi-Moving Boundary Problems Based Boundary Integral Method"

Transcription

1 Journal of Appled Maheac and Phyc, 5, 3, 6-37 Publhed Onlne Sepeber 5 n ScRe. hp:// hp://dx.do.org/.436/jap A New Ierae Mehod for Mul-Mong Boundary Proble Baed Boundary Inegral Mehod Kawher K. Al-Swa, Sad G. Ahed Deparen of Maheac and Sac, Faculy of Scence, Taf Unery, Taf, Kngdo of Saud Araba Eal: gahed9@hoal.co Receed 9 June 5; acceped 5 Sepeber 5; publhed 8 Sepeber 5 Copyrgh 5 by auhor and Scenfc Reearch Publhng Inc. Th work lcened under he Creae Coon Arbuon Inernaonal Lcene (CC BY). hp://creaecoon.org/lcene/by/4./ Abrac The preen paper deal wh ery poran praccal proble of wde range of applcaon. The an arge of he preen paper o rack all ong boundare ha appear hroughou he whole proce when dealng wh ul-ong boundary proble connuouly wh e up o he end of he proce wh hgh accuracy and nu nuber of eraon. A new nuercal erae chee baed he boundary negral equaon ehod deeloped o rack he ong boundare a well a copue all unknown n he proble. Three praccal applcaon, one for aporzaon and wo for ablaon were oled and her reul were copared wh fne eleen, hea balance negral and he ource and nk reul and a good agreeen were obaned. Keyword Mul-Mong Boundary Proble, Vaporzaon Proble, Ablaon Proble, Source and Snk Mehod, Fne Eleen Mehod, Hea Balance Inegral Mehod, Boundary Inegral Mehod. Inroducon The dfferenal equaon n a ceran doan afyng oe gen condon referred o a boundary-alue proble. If one or ore of he boundare are no known and ong wh e, he proble hen referred o a ong boundary proble [] []. Furherore, f he goernng equaon e ndependen a well a he boundary condon, hen he proble referred o a free boundary proble [3]. Phae change proble are praccal exaple of free and ong boundary proble, frequenly appear n ndural proce and oher proble of echnologcal nere uch a he deernaon of he deph of he fro or haw peneraon, de- Correpondng auhor. How o ce h paper: Al-Swa, K.K. and Ahed, S.G. (5) A New Ierae Mehod for Mul-Mong Boundary Proble Baed Boundary Inegral Mehod. Journal of Appled Maheac and Phyc, 3, hp://dx.do.org/.436/jap.5.394

2 gnng of he roadway or oher engneerng work n cold regon and he o-called re-enry proble of hyperonc le n aeronaucal cence [4] [5]. When a body expoed o hea flux he urface of he body change phae, he changed phae edaely reoed upon foraon. Th referred o ablaon proble [6]. A ajor dfference beween Sefan and ablaon proble ha he oerall doan n Sefan proble rean fxed n pace whle he doan n he ablaon proble arable and dnhe n ze wh e. Nuercal ehod becoe ore popular raher han analycal ehod. Soe of faou nuercal ehod are fne dfference [7], fne eleen [8], boundary eleen [9] and ore recen eh-le (eh-free) nuercal ehod []. In any apec, he boundary negral equaon ehod for olng boundary alue proble proe o be adanageou oer he conenonal nuercal ehod. The preen paper deal wh ery poran praccal proble of wde range of applcaon. The an arge of he preen paper o rack all ong boundare ha appear hroughou he whole proce when dealng wh ul-ong boundary proble connuouly wh e up o he end of he proce wh hgh accuracy and nu nuber of eraon. A new nuercal erae chee baed he boundary negral equaon ehod deeloped o rack he ong boundare a well a copue all unknown n he proble.. Maheacal Model A e-nfne old nally a unfor eperaure wh he followng conran, here no ub coolng, no uhy zone, old and lqud phae hae equal and conan propere and fnally no conecon. The aheacal forulaon con of hree dfferen age a follow: Heang age (, ) u( x, ) u x =, < x < α u( x,) u (, ) u q = K () = () u x, = u, = u (4) x A x = reache he elng eperaure, he econd age ar appearng. Lqud-old age Ga-lqud-old age (, ) (, ) u x u x =, < x< α (, ) u q = K (, ) (, ) u x u x =, ( ) < x< α (, ) (, ) x u( x, ) = u ( x, ) = u x= x= ( ) (, ) (, ) d u x = u = u (8) (9) u x u x = ρ = () d K K L, x (, ) (, ) u x u x =, < x< α (, ) (, ) u x u x =, < x< α (3) (5) (6) (7) () () 7

3 3. Boundary Inegral Forulaon (, ) (, ) u x u x =, ( ) < x< α (, ) (, ) x= x= ( ) u x u x u (3) = = (4) (, ) (, ) u x = u x = u (5) u d u K K = L d V ( ) ρ (6) (, ) (, ) Sarng by he weghed redual aeen for dffuon equaon a follow: In Equaon (8) u (, x;, ) u x = u x = u (7) τ u u k u ( ξ, x; τ, ) dω d = Ω (8) ξ τ he fundaenal oluon for dffuon equaon and defned a: ( ξ x) ( τ ) r, u ( ξ, x; τ, ) = exp 4πk( τ ) 4k In whch, r ( ξ, x) = X ( ξ) X ( x) and X ( ξ ) he ource pon whle Inegrang equaon (8) wce by par lead o: τ Ω u u k u ( ξ, x; τ, ) dωd ( ξ, ; τ, ) ( ξ, ; τ, ) X x he feld pon. = u x + u x Ω Γ = τ τ k ud d k q ( ξ, x; τ, ) ud d Ω Γ For one-denonal proble, Equaon () ake he followng for: In Equaon () ( ξ, ; τ, ) ( ξ, ; τ, ) u x u x τ τ k + ux dd k q ( ξ, x; τ, ux ) dd = ( ξ, ; τ, ) ( ξ, ; τ, ) u x u x k + = δ (9) () () () δ u = u (3) Makng ue of Equaon () and (3) no Equaon (), he la one ake he followng for: τ k u x q x u x u x x ( ξ τ ) ( ξ τ ), ;, d d,, ;, d = For any pon he negral equaon ake he followng for: τ τ ( ξ τ) = ( ξ τ ) + ( ξ τ ) ( ξ τ ) u, u x, u, x;, d x k u, x;, q x, dxd k q, x;, u x, dxd Dcrezaon of Te Equaon (5) afer he dcrezaon of e ake he followng for: (4) (5) 8

4 (, ) u ξ u x u ξ x x k u ξ x n u x, n =,, ; n, d + (, ; n, ) d = n u ( ξ, x ; n, ) k u( x, ) d n = Aue ha he poenal u and he flux q are conan whn each e ep herefore Equaon (6) can be wren a: F u( ξ, n) = u( x, ) u ( ξ, x ; n,) d x+ q( x, ) u ( ξ, x ; n, ) u( x, ) q ( ξ, x ; n, ) d (7) In Equaon (7), we hae wo dfferen e negral, hey are: The doan negral r a a ( ξ, ; n, ) d e e π { ( ) ( )} F k π I = u x = a a + erf a erf a (8) F I = q ( ξ, x; n, ) d = gn ( r) erf a erf a k (9) a r r = & a = 4k 4k ( ) ( ) n n (,) u x ξ ξ u ( x, ) u ( ξ, x; n,) dx = ( ) erf erf k n k n Now, he fnal for for he negral equaon correpondng o he dffuon equaon defned oer fxed doan wll be: (,) u x u ( ξ, ) erf erf q u d u q d n ξ ξ n = + x= x= k n k n = x = q u u q d n x= d x= = x= Slar procedure can be carred ou akng no conderaon he ong boundare and her noral eloce, herefore and accordng o [] [], and for he econd and hrd age, he negral equaon correpondng o he dffuon equaon wh ong boundare n a general fnal for wll be: ( x) ( ξ, ;, ) k u, u xk c( ξ) u( ξ, k) = α u ( ξ, x ; k, ) u( x, ) + u( x, ) u ( ξ, x ; k, ) Vn d α (33) j In Equaon (33), V n repreen he ouward noral elocy o he urface. In one-denonal proble, a d ( ) d ( ) n our cae udy, h elocy ay be or accordng o he phae underhand. d d 4. New Fxed-Mong-Fxed Algorh In he preen paper, a generalzed nuercal algorh and code for ul-ong boundary proble are deeloped, ung ual Forran 6.6. The an code con of an progra and hree ubroune. The flow char decrbng he an par of he propoed algorh hown n Fgure. x x (6) (3) (3) (3) 9

5 4.. Algorh and Subroune ONEPHASE Fgure. General fxed-ong-fxed negral algorh. In h ubroune, a ngle phae bounded by wo fxed boundare are oled, ung Equaon (3) and he oupu wll be he e a whch elng ar and he correpondng locaon of he fr ong boundary, epa-. rang he lqud and he old, Suggeed Algorh ) Inpu daa, old lengh, paal grd ze x and e ep. ) Apply he boundary negral equaon, gen by Equaon (3) a he end pon of he doan of nere o j j u x =,. j eae j 3) Check u x =,, =,,, N, f ye, hen go o he nex wo-phae ubroune, wh oupu, e of elng and he correpondng poon for he ong boundary eparang lqud and old. If no j+ j updae boh he paal and e arable x = x + x = + and repea ep - 3 ll he re- + +, 3

6 qured oupu of h ubroune acheed. 4.. Algorh and Subroune TWOPHASE Th ubroune concern anly wh wo phae each phae wll be bounded by one fxed and he econd ong are oled and he oupu wll be he e a whch apor ar and he correpondng locaon of he. fr and econd ong boundare and Suggeed Algorh ) The npu un here he oupu fro one-phae ubroune. ) Sole old phae ubjeced o elng eperaure a he ong boundary and nal eperaure a he u fxed end o ge. x ( ) d ( ) u u 3) By knowng and d o eae. j (, ) 4) Check ( j ) ( ) ( ) u x = u V, f ye, hen he oupu of h ubroune wll be he e a whch apor ar appearng wh he new poon of he ong boundary eparang lqud/old and he arng poon of he econd ong boundary eparang apor(ga)/lqud, f no updae he ong boundary eparang lqud/old Algorh and Subroune THREEPHASE Th ubroune for hree phae, he fr one bounded by wo boundare, one fxed and one ong, he econd phae bounded by wo ong boundare, and he hrd phae alo bounded by wo boundare one fxed and one ong. The oupu of h ubroune o rack all ong boundare, deernaon all unknown n all phae up o he end of he proce wh nu nuber of eraon and hgh precrbed accuracy. The flow char of h ubroune hown n Fgure. In h fgure, he abolue error E and E are defned a follow: 5. Nuercal Reul 5.. Vaporzaon Te Proble (, ) (, ) d u x u x E = K K L d ρ (34) ( ) u d u E = K K ρl (35) d In h econ, hree e proble are oled o check he aldy of he propoed algorh and he hgh accuracy expeced. The fr exaple a ul-ong boundary proble [3]. The hero-phycal propere are led below n Table. The old aeral heren of a low heral conducy and o he aporzaon occur before he ong boundary eparang lqud and old reache he adabac boundary. The reul due o he preen algorh hown n Fgure 3. In h fgure, boh apor/lqud and lqud/old ong boundare are ploed boh on he ae fgure. The lqud/old ong boundary n he lef de, whle he oher one on he rgh. Fro h fgure, one can clearly deerne he elng, apor and he e a whch he proce end. Thee e are deerned and uarzed n Table, a wo dfferen e ep. The abolue error beween he reul due o he preen ehod copared wh he fne eleen ehod are alo preened n he ae able. A we ee, he abolue error decreae by decreang he e ep. On he oher hand by decreang he e ep, he nuber of eraon ncreae. The nuber of eraon are hown n Table, correpondng o he wo e ep ued. I clear ha he ncreae n he nuber of eraon no o uch bu he accuracy proed o 3

7 Fgure. Flow char for THREEPHASE ubroune. Fgure 3. Mong boundare locaon for aporzaon e proble. 3

8 Table. Nuercal daa for aporzaon e proble. Paraeer Defnon Nuercal daa c Specfc hea for old c Specfc hea for lqud K Theral conducy for old.59 K Theral conducy for lqud.59 u Melng eperaure 454 u Vaporzaon eperaure 3 L Laen hea for elng 6 L Laen hea for aporzaon 37, u( x,) Inal eperaure 7 q( ) Inpu hea flux a he boundary x = 5 ρ Deny Table. Coparon beween elng, aporzaon and end e. Te ep Type of e FE Preen Abolue error =.5 = e e Aerage nuber of eraon nearly he half. 5.. Ablaon Te Proble- A old edu nally a unfor eperaure, u = 3 K, he boundary x = expoed o wo dfferen 6 4 cae of npu hea flux, conan, Q( ) = 5 and lnear, Q( ) = 3 repecely. The doan n he preen proble ll fxed whle appearng wo ong nerface, old-lqud and apor (ga)-lqud (Ablaon urface). The reul due o he preen algorh are hown n Fgure 4-6, repecely and he reul are copared wh he reul due o he ource and nk ehod [4]. Fgure 4 how he oeen of old-lqud due o conan npu hea flux, and he reulng ablaon urface due o he ae npu hea flux hown n Fgure 5. The ae reul due o lnear cae are ploed on he ae plo a hown n Fgure 6. Fro he copuaon and fgure, found ha he old-lqud nerface ha he ae behaor n boh conan and lnear cae of npu hea flux ha concae upward. In cae of lnear hea flux npu h concay becoe ore apparen han he conan cae. In he conrary, he apor (ga)/lqud nerface behae concae downward bu n lnear cae h concay ncreae Ablaon Te Proble- Th proble for a long enough old old nally a a unfor eperaure. The urface x = expoed o wo dfferen hgh npu hea flux, conan and lnear and he apor reoed a oon a foredablaon proble-. Two pecfc hea flux boundary condon are choen n he preen copuaon, naely, ( ) q =., c and he followng alue ued n he calculaon [5] (Table 3). The ablaon hckne due o he preen ehod copared wh he correpondng fro he hea balance negral ehod hown n Fgure 7. I clear ha he ablaon hckne concae downward n boh cae of 33

9 Sold/Lqud nerface (c) Exaple () Conan npu hea flux Sold-Lqud nerface Preen Mehod Source and Snk Mehod Te (Sec) Fgure 4. Sold/lqud due o Conan hea flux-proble-...9 Ablaed urface (c) Exaple () Conan npu hea flux Ablaed Surface Preen Mehod Source and Snk Mehod Te (Sec) Fgure 5. Ablaed urface due o conan hea flux-proble-. 34

10 Fgure 6. Sold/lqud and Ablaed urface due o lnear hea flux-proble-. Fgure 7. Ablaon hckne for ablaon e proble-. 35

11 Table 3. Thero-phycal paraeer. Sybol Phycal eannng Nuercal alue T α Theral dffuy. f / ec c Characerc e ec L characerc lengh. q r Reference hea flux Bu/ ec f T Teperaure dfference F Inere Sefan nuber T Reference e ec npu hea flux and a he ae e, he ablaon hckne n cae of lnear hea flux hgher han ha for conan cae. There a good agreeen beween he wo ehod n boh cae. 6. Concluon The porance of he preen paper coe fro dealng wh praccal applcaon of wde range of our daly lfe. The boundary negral equaon ehod no o new bu ued a a aheacal ool due o plcy n ue. Baed on h ehod, a generalzed nuercal algorh and copuer code are deeloped o ole uch applcaon. I found fro he copuaon ha he deeloped algorh and he code are o ple o handle and ha an accepable accuracy obaned. Alo by decreang he e ep, and a lle b ncreae of eraon, he abolue error are decreaed o he half nearly. Fnally, he algorh and ubequenly he code can be ealy odfed o coer hgher denonal proble wh accepable accuracy, whch can be proed by decreang he e ep, bu on he oher hand, ably hould be acheed. Reference [] Meaad, N.M.I. (4) Meh-Le Mehod and I Applcaon o Free and Mong Boundary Proble. M.Sc. The, Zagazg Unery, Zagazg. Superon S. G. Ahed. [] Crank, J. (984) Free and Mong Boundary Proble. Clarendon Pre, Oxford. [3] Mohad, N.A.E. () Boundary Eleen Mehod and I Non-Lnear Analy of Hydrofol. Superor: Prof. S. G. Ahed and Prof. A. F. Abd-Elgawad. Zagazg Unery, Zagazg. [4] Nofal, T.A. and Ahed, S.G. (5) An Inegral Mehod o Sole Phae-Change Proble wh/whou Muhy Zone. Journal of Appled Maheac and Maheac, II, [5] Ahed, S.G. and Mekey, M.L. () A Collocaon and Carean Grd Mehod Ung New Radal Ba Funcon o Sole Cla of Paral Dfferenal Equaon. Inernaonal Journal of Copuer Maheac, 87, [6] Mehrf, S.A. and Ahed, S.G. (7) Approxae Inegral Mehod Appled o Ablaon Proble n a Fne Slab. Inernaonal Sypou on Recen Adance n Maheac and I Applcaon (ISRAMA 7), Culcua, 5-7 Deceber 7, -. [7] Zerrouka, M. and Chawn, C.R. (994) Copuaonal Mong and Boundary Proble. Reearch Sude Pre Ld., Baldock. [8] Ruan, Y. and Zabara, N. (99) An Inere Fne Eleen Technque o Deerne The change of Phae Inerface Locaon n Two-Denonal Melng Proble. Councaon n Appled Nuercal Mehod, 7, hp://dx.do.org/./cn.6374 [9] Mohaed, W.A. () Adanced Maheacal Analy for Phae Change Proble wh and whou Muhy Zone. Superor: Prof. S. G. Ahed and Prof. M. E. Mohaed. Zagazg Unery, Zagazg. [] Lu, W., Chen, Y., Jun, S., Chen, J.-S., Belychko, T., Pan, C., Ura, R. and Chang, C. (996) Oerew and Applcaon of he Reproducng Kernel Parcle Mehod. Arche of Copuaonal Mehod n Engneerng: Sae of he Ar Reew, 3, 3-8. hp://dx.do.org/.7/bf7363 [] Ahed, S.G. (5) A New Algorh for Mong Boundary Proble Subjec o Perodc Boundary Condon. Inernaonal Journal of Nuercal Mehod for Hea and Flud Flow, 6, 8-7. [] Abd-El Faah, W.M. and Ahed, S.G. (6) Boundary Inegral Forulaon for Bnary Alloy fro a Coolng Sold 36

12 Wall. Inernaonal Journal of Copuaonal and Appled Maheac, 5, [3] Ahed, S.G. (3) A New Algorh for Fron Trackng of Ablaon Proble n Unbounded Doan. An Sha Unery, Egyp. [4] Mehd, A. and Heh, C.K. (994) Soluon of Ablaon and Cobnaon of Ablaon and Sefan Proble by a Source and Snk Mehod. Nuercal Hea Tranfer, Par A, 6, hp://dx.do.org/.8/ [5] Ahed, S.G. (3) A Nuercal Soluon for Nonlnear Hea Flow Proble Ung Boundary Inegral Mehod. 6h Inernaonal Conference of Copuer Mehod and Experenal Meaureen for Surface Treaen, Cree, March 3. Noenclaure u : Teperaure u : Fundaenal oluon α : Theral dffuy K : Conducy ρ : Deny q( ) : Inpu hea flux : Lqud-old nerface : Vapor-lqud nerface : Truncaed long enough boundary lengh L : Laen hea Subcrp : Sold : Lqud : Inal : Vapor : Melng 37

A DECOMPOSITION METHOD FOR SOLVING DIFFUSION EQUATIONS VIA LOCAL FRACTIONAL TIME DERIVATIVE

A DECOMPOSITION METHOD FOR SOLVING DIFFUSION EQUATIONS VIA LOCAL FRACTIONAL TIME DERIVATIVE S13 A DECOMPOSITION METHOD FOR SOLVING DIFFUSION EQUATIONS VIA LOCAL FRACTIONAL TIME DERIVATIVE by Hossen JAFARI a,b, Haleh TAJADODI c, and Sarah Jane JOHNSTON a a Deparen of Maheacal Scences, Unversy

More information

Cooling of a hot metal forging. , dt dt

Cooling of a hot metal forging. , dt dt Tranen Conducon Uneady Analy - Lumped Thermal Capacy Model Performed when; Hea ranfer whn a yem produced a unform emperaure drbuon n he yem (mall emperaure graden). The emperaure change whn he yem condered

More information

DEFROST CONTROL METHOD FOR AIR HEAT PUMP BASED ON AVERAGE HEATING CAPACITY

DEFROST CONTROL METHOD FOR AIR HEAT PUMP BASED ON AVERAGE HEATING CAPACITY DEFROS CONROL MEHOD FOR AIR HEA PUMP BASED ON AVERAGE HEAING CAPACIY LI Chun-Ln, Maer, heral Engneerng Deparen, nghua Unery, Bejng 100084, Chna LI Jun-Mng, Aocae Profeor, heral Engneerng Deparen, nghua

More information

ESS 265 Spring Quarter 2005 Kinetic Simulations

ESS 265 Spring Quarter 2005 Kinetic Simulations SS 65 Spng Quae 5 Knec Sulaon Lecue une 9 5 An aple of an lecoagnec Pacle Code A an eaple of a knec ulaon we wll ue a one denonal elecoagnec ulaon code called KMPO deeloped b Yohhau Oua and Hoh Mauoo.

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

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

Application of the PageRank algorithm for ranking locations of a production network

Application of the PageRank algorithm for ranking locations of a production network Applcaon of he PageRank algorh for rankng locaon of a producon nework Bernd Scholz-Reer (2), Faban Wrh 2, Sergey Dahkovky 3, hoa Makuchewz, Mchael Koykov 3, Mchael Schönlen 2 Plannng and Conrol of Producon

More information

Normal Random Variable and its discriminant functions

Normal Random Variable and its discriminant functions Noral Rando Varable and s dscrnan funcons Oulne Noral Rando Varable Properes Dscrnan funcons Why Noral Rando Varables? Analycally racable Works well when observaon coes for a corruped snle prooype 3 The

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

New Oscillation Results for Forced Second Order Differential Equations with Mixed Nonlinearities

New Oscillation Results for Forced Second Order Differential Equations with Mixed Nonlinearities Appled Maheac,, 3, 47-53 hp://dxdoorg/436/a33 Publhed Onlne February (hp://wwwscrporg/ournal/a) New Ocllaon Reul for Forced Second Order Dfferenal Equaon wh Mxed Nonlneare Ercan Tunç, Adl Kayaz Deparen

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

PHYSICS 151 Notes for Online Lecture #4

PHYSICS 151 Notes for Online Lecture #4 PHYSICS 5 Noe for Online Lecure #4 Acceleraion The ga pedal in a car i alo called an acceleraor becaue preing i allow you o change your elociy. Acceleraion i how fa he elociy change. So if you ar fro re

More information

H = d d q 1 d d q N d d p 1 d d p N exp

H = d d q 1 d d q N d d p 1 d d p N exp 8333: Sacal Mechanc I roblem Se # 7 Soluon Fall 3 Canoncal Enemble Non-harmonc Ga: The Hamlonan for a ga of N non neracng parcle n a d dmenonal box ha he form H A p a The paron funcon gven by ZN T d d

More information

SSRG International Journal of Thermal Engineering (SSRG-IJTE) Volume 4 Issue 1 January to April 2018

SSRG International Journal of Thermal Engineering (SSRG-IJTE) Volume 4 Issue 1 January to April 2018 SSRG Inernaonal Journal of Thermal Engneerng (SSRG-IJTE) Volume 4 Iue 1 January o Aprl 18 Opmal Conrol for a Drbued Parameer Syem wh Tme-Delay, Non-Lnear Ung he Numercal Mehod. Applcaon o One- Sded Hea

More information

Numerical Study of Large-area Anti-Resonant Reflecting Optical Waveguide (ARROW) Vertical-Cavity Semiconductor Optical Amplifiers (VCSOAs)

Numerical Study of Large-area Anti-Resonant Reflecting Optical Waveguide (ARROW) Vertical-Cavity Semiconductor Optical Amplifiers (VCSOAs) USOD 005 uecal Sudy of Lage-aea An-Reonan Reflecng Opcal Wavegude (ARROW Vecal-Cavy Seconduco Opcal Aplfe (VCSOA anhu Chen Su Fung Yu School of Eleccal and Eleconc Engneeng Conen Inoducon Vecal Cavy Seconduco

More information

2/20/2013. EE 101 Midterm 2 Review

2/20/2013. EE 101 Midterm 2 Review //3 EE Mderm eew //3 Volage-mplfer Model The npu ressance s he equalen ressance see when lookng no he npu ermnals of he amplfer. o s he oupu ressance. I causes he oupu olage o decrease as he load ressance

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

A. Inventory model. Why are we interested in it? What do we really study in such cases.

A. Inventory model. Why are we interested in it? What do we really study in such cases. Some general yem model.. Inenory model. Why are we nereed n? Wha do we really udy n uch cae. General raegy of machng wo dmlar procee, ay, machng a fa proce wh a low one. We need an nenory or a buffer or

More information

Learning Objectives. Self Organization Map. Hamming Distance(1/5) Introduction. Hamming Distance(3/5) Hamming Distance(2/5) 15/04/2015

Learning Objectives. Self Organization Map. Hamming Distance(1/5) Introduction. Hamming Distance(3/5) Hamming Distance(2/5) 15/04/2015 /4/ Learnng Objecves Self Organzaon Map Learnng whou Exaples. Inroducon. MAXNET 3. Cluserng 4. Feaure Map. Self-organzng Feaure Map 6. Concluson 38 Inroducon. Learnng whou exaples. Daa are npu o he syse

More information

CHAPTER II AC POWER CALCULATIONS

CHAPTER II AC POWER CALCULATIONS CHAE AC OWE CACUAON Conens nroducon nsananeous and Aerage ower Effece or M alue Apparen ower Coplex ower Conseraon of AC ower ower Facor and ower Facor Correcon Maxu Aerage ower ransfer Applcaons 3 nroducon

More information

(,,, ) (,,, ). In addition, there are three other consumers, -2, -1, and 0. Consumer -2 has the utility function

(,,, ) (,,, ). In addition, there are three other consumers, -2, -1, and 0. Consumer -2 has the utility function MACROECONOMIC THEORY T J KEHOE ECON 87 SPRING 5 PROBLEM SET # Conder an overlappng generaon economy le ha n queon 5 on problem e n whch conumer lve for perod The uly funcon of he conumer born n perod,

More information

Control Systems. Mathematical Modeling of Control Systems.

Control Systems. Mathematical Modeling of Control Systems. Conrol Syem Mahemacal Modelng of Conrol Syem chbum@eoulech.ac.kr Oulne Mahemacal model and model ype. Tranfer funcon model Syem pole and zero Chbum Lee -Seoulech Conrol Syem Mahemacal Model Model are key

More information

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

[ ] 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

EECE 301 Signals & Systems Prof. Mark Fowler

EECE 301 Signals & Systems Prof. Mark Fowler EECE 31 Signal & Syem Prof. Mark Fowler Noe Se #27 C-T Syem: Laplace Tranform Power Tool for yem analyi Reading Aignmen: Secion 6.1 6.3 of Kamen and Heck 1/18 Coure Flow Diagram The arrow here how concepual

More information

A Nonlinear ILC Schemes for Nonlinear Dynamic Systems To Improve Convergence Speed

A Nonlinear ILC Schemes for Nonlinear Dynamic Systems To Improve Convergence Speed IJCSI Inernaonal Journal of Compuer Scence Iue, Vol. 9, Iue 3, No, ay ISSN (Onlne): 694-84 www.ijcsi.org 8 A Nonlnear ILC Scheme for Nonlnear Dynamc Syem o Improve Convergence Speed Hoen Babaee, Alreza

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

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

NONLOCAL BOUNDARY VALUE PROBLEM FOR SECOND ORDER ANTI-PERIODIC NONLINEAR IMPULSIVE q k INTEGRODIFFERENCE EQUATION

NONLOCAL BOUNDARY VALUE PROBLEM FOR SECOND ORDER ANTI-PERIODIC NONLINEAR IMPULSIVE q k INTEGRODIFFERENCE EQUATION Euroean Journal of ahemac an Comuer Scence Vol No 7 ISSN 59-995 NONLOCAL BOUNDARY VALUE PROBLE FOR SECOND ORDER ANTI-PERIODIC NONLINEAR IPULSIVE - INTEGRODIFFERENCE EQUATION Hao Wang Yuhang Zhang ngyang

More information

THEORETICAL AUTOCORRELATIONS. ) if often denoted by γ. Note that

THEORETICAL AUTOCORRELATIONS. ) if often denoted by γ. Note that THEORETICAL AUTOCORRELATIONS Cov( y, y ) E( y E( y))( y E( y)) ρ = = Var( y) E( y E( y)) =,, L ρ = and Cov( y, y ) s ofen denoed by whle Var( y ) f ofen denoed by γ. Noe ha γ = γ and ρ = ρ and because

More information

LIABILITY VALUATION FOR LIFE INSURANCE CONTRACTS:THE CASE OF A NON HOMOGENEOUS PORTFOLIO

LIABILITY VALUATION FOR LIFE INSURANCE CONTRACTS:THE CASE OF A NON HOMOGENEOUS PORTFOLIO LIABILITY VALUATION FOR LIFE INSURANCE CONTRACTS:THE CASE OF A NON HOMOGENEOUS PORTFOLIO Albna Orlando and Aleandro Trudda 2 C.n.r. Iuoper le Applcazon del Calcolo. Napol (e-al: a.orlando@na.ac.cnr.) 2

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

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

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

Graduate Macroeconomics 2 Problem set 5. - Solutions

Graduate Macroeconomics 2 Problem set 5. - Solutions Graduae Macroeconomcs 2 Problem se. - Soluons Queson 1 To answer hs queson we need he frms frs order condons and he equaon ha deermnes he number of frms n equlbrum. The frms frs order condons are: F K

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

Physics 240: Worksheet 16 Name

Physics 240: Worksheet 16 Name Phyic 4: Workhee 16 Nae Non-unifor circular oion Each of hee proble involve non-unifor circular oion wih a conan α. (1) Obain each of he equaion of oion for non-unifor circular oion under a conan acceleraion,

More information

THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, OF THE ROMANIAN ACADEMY Volume 9, Number 1/2008, pp

THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMANIAN ACADEMY, Series A, OF THE ROMANIAN ACADEMY Volume 9, Number 1/2008, pp THE PUBLISHING HOUSE PROCEEDINGS OF THE ROMNIN CDEMY, Seres, OF THE ROMNIN CDEMY Volue 9, Nuber /008, pp. 000 000 ON CIMMINO'S REFLECTION LGORITHM Consann POP Ovdus Unversy of Consana, Roana, E-al: cpopa@unv-ovdus.ro

More information

GMM parameter estimation. Xiaoye Lu CMPS290c Final Project

GMM parameter estimation. Xiaoye Lu CMPS290c Final Project GMM paraeer esaon Xaoye Lu M290c Fnal rojec GMM nroducon Gaussan ure Model obnaon of several gaussan coponens Noaon: For each Gaussan dsrbuon:, s he ean and covarance ar. A GMM h ures(coponens): p ( 2π

More information

Chapter 7 AC Power and Three-Phase Circuits

Chapter 7 AC Power and Three-Phase Circuits Chaper 7 AC ower and Three-hae Crcu Chaper 7: Oulne eance eacance eal power eacve power ower n AC Crcu ower and Energy Gven nananeou power p, he oal energy w ranferred o a load beween and : w p d The average

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

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

CTLS 4 SNR. Multi Reference CTLS Method for Passive Localization of Radar Targets

CTLS 4 SNR. Multi Reference CTLS Method for Passive Localization of Radar Targets دا ند رعا ل» ی و ناوری ج ه ع ی و ی «ع وم 79-85 9 C 4 * Donloaded from ad.r a 9:06 +040 on Frda arch nd 09-4 - - - - (9/06/4 : 90/05/7 : ) DOA. DOA. C DOA.. C.. C SR.. C.C DOA : ul Reference C ehod for

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

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

A NEW TECHNIQUE FOR SOLVING THE 1-D BURGERS EQUATION

A NEW TECHNIQUE FOR SOLVING THE 1-D BURGERS EQUATION S19 A NEW TECHNIQUE FOR SOLVING THE 1-D BURGERS EQUATION by Xaojun YANG a,b, Yugu YANG a*, Carlo CATTANI c, and Mngzheng ZHU b a Sae Key Laboraory for Geomechancs and Deep Underground Engneerng, Chna Unversy

More information

ELEC 201 Electric Circuit Analysis I Lecture 9(a) RLC Circuits: Introduction

ELEC 201 Electric Circuit Analysis I Lecture 9(a) RLC Circuits: Introduction //6 All le courey of Dr. Gregory J. Mazzaro EE Elecrc rcu Analy I ecure 9(a) rcu: Inroucon THE ITADE, THE MIITAY OEGE OF SOUTH AOINA 7 Moulre Sree, harleon, S 949 V Sere rcu: Analog Dcoery _ 5 Ω pf eq

More information

New Optimization Method, the Algorithms of Changes, for Heat Exchanger Design

New Optimization Method, the Algorithms of Changes, for Heat Exchanger Design CHINESE JOURNA OF MECHANICA ENGINEERING Vol. 5aNo. a0 DOI: 0.390/CJME.0.0.*** avalable onlne a www.cjene.co; www.cjene.co.cn New Opzaon Mehod he Algorh of Change for Hea Exchanger Degn TAM Houkuan * TAM

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

A Modified Genetic Algorithm Comparable to Quantum GA

A Modified Genetic Algorithm Comparable to Quantum GA A Modfed Genec Algorh Coparable o Quanu GA Tahereh Kahookar Toos Ferdows Unversy of Mashhad _k_oos@wal.u.ac.r Habb Rajab Mashhad Ferdows Unversy of Mashhad h_rajab@ferdows.u.ac.r Absrac: Recenly, researchers

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 Demand System for Input Factors when there are Technological Changes in Production

A Demand System for Input Factors when there are Technological Changes in Production A Demand Syem for Inpu Facor when here are Technologcal Change n Producon Movaon Due o (e.g.) echnologcal change here mgh no be a aonary relaonhp for he co hare of each npu facor. When emang demand yem

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

Displacement, Velocity, and Acceleration. (WHERE and WHEN?)

Displacement, Velocity, and Acceleration. (WHERE and WHEN?) Dsplacemen, Velocy, and Acceleraon (WHERE and WHEN?) Mah resources Append A n your book! Symbols and meanng Algebra Geomery (olumes, ec.) Trgonomery Append A Logarhms Remnder You wll do well n hs class

More information

Sklar: Sections (4.4.2 is not covered).

Sklar: Sections (4.4.2 is not covered). COSC 44: Dgal Councaons Insrucor: Dr. Ar Asf Deparen of Copuer Scence and Engneerng York Unversy Handou # 6: Bandpass Modulaon opcs:. Phasor Represenaon. Dgal Modulaon Schees: PSK FSK ASK APK ASK/FSK)

More information

Lecture 6: Learning for Control (Generalised Linear Regression)

Lecture 6: Learning for Control (Generalised Linear Regression) Lecure 6: Learnng for Conrol (Generalsed Lnear Regresson) Conens: Lnear Mehods for Regresson Leas Squares, Gauss Markov heorem Recursve Leas Squares Lecure 6: RLSC - Prof. Sehu Vjayakumar Lnear Regresson

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

Testing a new idea to solve the P = NP problem with mathematical induction

Testing a new idea to solve the P = NP problem with mathematical induction Tesng a new dea o solve he P = NP problem wh mahemacal nducon Bacground P and NP are wo classes (ses) of languages n Compuer Scence An open problem s wheher P = NP Ths paper ess a new dea o compare he

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

How to Solve System Dynamic s Problems

How to Solve System Dynamic s Problems How o Solve Sye Dynaic Proble A ye dynaic proble involve wo or ore bodie (objec) under he influence of everal exernal force. The objec ay uliaely re, ove wih conan velociy, conan acceleraion or oe cobinaion

More information

Temporal and spatial Lagrangean decompositions in multi-site, multi-period production planning problems with sequence-dependent changeovers

Temporal and spatial Lagrangean decompositions in multi-site, multi-period production planning problems with sequence-dependent changeovers Teporal and paal Lagrangean decopoon n ul-e, ul-perod producon plannng proble wh equence-dependen changeover Sebaan Terraza-Moreno a, Phlpp Troer b, Ignaco E. Groann a* a Carnege Mellon Unvery, 5000 Forbe

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

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

Homework 2 Solutions

Homework 2 Solutions Mah 308 Differenial Equaions Fall 2002 & 2. See he las page. Hoework 2 Soluions 3a). Newon s secon law of oion says ha a = F, an we know a =, so we have = F. One par of he force is graviy, g. However,

More information

RAMIFICATIONS of POSITION SERVO LOOP COMPENSATION

RAMIFICATIONS of POSITION SERVO LOOP COMPENSATION RAMIFICATIONS f POSITION SERO LOOP COMPENSATION Gerge W. Yunk, P.E. Lfe Fellw IEEE Indural Cnrl Cnulg, Inc. Fnd du Lac, Wcn Fr many year dural pg er dre dd n ue er cmpena he frward p lp. Th wa referred

More information

Lecture VI Regression

Lecture VI Regression Lecure VI Regresson (Lnear Mehods for Regresson) Conens: Lnear Mehods for Regresson Leas Squares, Gauss Markov heorem Recursve Leas Squares Lecure VI: MLSC - Dr. Sehu Vjayakumar Lnear Regresson Model M

More information

System in Weibull Distribution

System in Weibull Distribution Internatonal Matheatcal Foru 4 9 no. 9 94-95 Relablty Equvalence Factors of a Seres-Parallel Syste n Webull Dstrbuton M. A. El-Dacese Matheatcs Departent Faculty of Scence Tanta Unversty Tanta Egypt eldacese@yahoo.co

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

Rate Constitutive Theories of Orders n and 1 n for Internal Polar Non-Classical Thermofluids without Memory

Rate Constitutive Theories of Orders n and 1 n for Internal Polar Non-Classical Thermofluids without Memory Appled Maheac, 6, 7, 33-77 hp://www.crp.org/ournal/a ISSN Onlne: 5-7393 ISSN Prn: 5-7385 Rae Conuve heore of Order n and n for Inernal Polar Non-Clacal heroflud whou Meory Karan S. Surana, Sephen W. Long,

More information

Algorithmic Discrete Mathematics 6. Exercise Sheet

Algorithmic Discrete Mathematics 6. Exercise Sheet Algorihmic Dicree Mahemaic. Exercie Shee Deparmen of Mahemaic SS 0 PD Dr. Ulf Lorenz 7. and 8. Juni 0 Dipl.-Mah. David Meffer Verion of June, 0 Groupwork Exercie G (Heap-Sor) Ue Heap-Sor wih a min-heap

More information

8th WSEAS International Conference on SIMULATION, MODELLING and OPTIMIZATION (SMO '08) Santander, Cantabria, Spain, September 23-25, 2008

8th WSEAS International Conference on SIMULATION, MODELLING and OPTIMIZATION (SMO '08) Santander, Cantabria, Spain, September 23-25, 2008 8h WSEAS Inernaonal Conference on SIMULAION, MODELLING and OPIMIZAION (SMO 08) Sanander, Canabra, San, Seeber 3-5, 008 Obervably of 4h Order Dynacal Sye Jerzy Sefan Reonde Faculy of Auoac Conrol, Elecronc

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

Fundamentals of PLLs (I)

Fundamentals of PLLs (I) Phae-Locked Loop Fundamenal of PLL (I) Chng-Yuan Yang Naonal Chung-Hng Unvery Deparmen of Elecrcal Engneerng Why phae-lock? - Jer Supreon - Frequency Synhe T T + 1 - Skew Reducon T + 2 T + 3 PLL fou =

More information

Laplace Transformation of Linear Time-Varying Systems

Laplace Transformation of Linear Time-Varying Systems Laplace Tranformaon of Lnear Tme-Varyng Syem Shervn Erfan Reearch Cenre for Inegraed Mcroelecronc Elecrcal and Compuer Engneerng Deparmen Unvery of Wndor Wndor, Onaro N9B 3P4, Canada Aug. 4, 9 Oulne of

More information

A TWO-LEVEL LOAN PORTFOLIO OPTIMIZATION PROBLEM

A TWO-LEVEL LOAN PORTFOLIO OPTIMIZATION PROBLEM Proceedngs of he 2010 Wner Sulaon Conference B. Johansson, S. Jan, J. Monoya-Torres, J. Hugan, and E. Yücesan, eds. A TWO-LEVEL LOAN PORTFOLIO OPTIMIZATION PROBLEM JanQang Hu Jun Tong School of Manageen

More information

Motion of Wavepackets in Non-Hermitian. Quantum Mechanics

Motion of Wavepackets in Non-Hermitian. Quantum Mechanics Moon of Wavepaces n Non-Herman Quanum Mechancs Nmrod Moseyev Deparmen of Chemsry and Mnerva Cener for Non-lnear Physcs of Complex Sysems, Technon-Israel Insue of Technology www.echnon echnon.ac..ac.l\~nmrod

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

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

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

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

Outline. Probabilistic Model Learning. Probabilistic Model Learning. Probabilistic Model for Time-series Data: Hidden Markov Model

Outline. Probabilistic Model Learning. Probabilistic Model Learning. Probabilistic Model for Time-series Data: Hidden Markov Model Probablsc Model for Tme-seres Daa: Hdden Markov Model Hrosh Mamsuka Bonformacs Cener Kyoo Unversy Oulne Three Problems for probablsc models n machne learnng. Compung lkelhood 2. Learnng 3. Parsng (predcon

More information

PHY2053 Summer C 2013 Exam 1 Solutions

PHY2053 Summer C 2013 Exam 1 Solutions PHY053 Sue C 03 E Soluon. The foce G on o G G The onl cobnon h e '/ = doubln.. The peed of lh le 8fulon c 86,8 le 60 n 60n h 4h d 4d fonh.80 fulon/ fonh 3. The dnce eled fo he ene p,, 36 (75n h 45 The

More information

SINGLE CHANNEL SOURCE SEPARATION USING STATIC AND DYNAMIC FEATURES IN THE POWER DOMAIN

SINGLE CHANNEL SOURCE SEPARATION USING STATIC AND DYNAMIC FEATURES IN THE POWER DOMAIN SINGLE CHANNEL SOURCE SEPARATION USING STATIC AND DYNAMIC FEATURES IN THE POWER DOMAIN Ilya Poa ± Alexey Ozerov ± Deparen of Muc Technology Acouc Technologcal Educaonal Inue of Cree E. Dakalak - Pervola

More information

Four-channel force-reflecting teleoperation with impedance control. Nam Duc Do* Toru Namerikawa

Four-channel force-reflecting teleoperation with impedance control. Nam Duc Do* Toru Namerikawa 38 In. J. Advanced Mecharonc Sye, Vol., No. 5/6, 00 Four-channel force-reflecng eleoperaon wh pedance conrol Na Duc Do* Dvon of Elecrcal Engneerng and Copuer Scence, Graduae School of Naural Scence and

More information

II The Z Transform. Topics to be covered. 1. Introduction. 2. The Z transform. 3. Z transforms of elementary functions

II The Z Transform. Topics to be covered. 1. Introduction. 2. The Z transform. 3. Z transforms of elementary functions II The Z Trnsfor Tocs o e covered. Inroducon. The Z rnsfor 3. Z rnsfors of eleenry funcons 4. Proeres nd Theory of rnsfor 5. The nverse rnsfor 6. Z rnsfor for solvng dfference equons II. Inroducon The

More information

Supporting information How to concatenate the local attractors of subnetworks in the HPFP

Supporting information How to concatenate the local attractors of subnetworks in the HPFP n Effcen lgorh for Idenfyng Prry Phenoype rcors of Lrge-Scle Boolen Newor Sng-Mo Choo nd Kwng-Hyun Cho Depren of Mhecs Unversy of Ulsn Ulsn 446 Republc of Kore Depren of Bo nd Brn Engneerng Kore dvnced

More information

Chapter 6: AC Circuits

Chapter 6: AC Circuits Chaper 6: AC Crcus Chaper 6: Oulne Phasors and he AC Seady Sae AC Crcus A sable, lnear crcu operang n he seady sae wh snusodal excaon (.e., snusodal seady sae. Complee response forced response naural response.

More information

Discussion Session 2 Constant Acceleration/Relative Motion Week 03

Discussion Session 2 Constant Acceleration/Relative Motion Week 03 PHYS 100 Dicuion Seion Conan Acceleraion/Relaive Moion Week 03 The Plan Today you will work wih your group explore he idea of reference frame (i.e. relaive moion) and moion wih conan acceleraion. You ll

More information

Method of upper lower solutions for nonlinear system of fractional differential equations and applications

Method of upper lower solutions for nonlinear system of fractional differential equations and applications Malaya Journal of Maemak, Vol. 6, No. 3, 467-472, 218 hps://do.org/1.26637/mjm63/1 Mehod of upper lower soluons for nonlnear sysem of fraconal dfferenal equaons and applcaons D.B. Dhagude1 *, N.B. Jadhav2

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

Problem #1. Known: All required parameters. Schematic: Find: Depth of freezing as function of time. Strategy:

Problem #1. Known: All required parameters. Schematic: Find: Depth of freezing as function of time. Strategy: BEE 3500 013 Prelm Soluton Problem #1 Known: All requred parameter. Schematc: Fnd: Depth of freezng a functon of tme. Strategy: In thee mplfed analy for freezng tme, a wa done n cla for a lab geometry,

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

Chapter 3: Vectors and Two-Dimensional Motion

Chapter 3: Vectors and Two-Dimensional Motion Chape 3: Vecos and Two-Dmensonal Moon Vecos: magnude and decon Negae o a eco: eese s decon Mulplng o ddng a eco b a scala Vecos n he same decon (eaed lke numbes) Geneal Veco Addon: Tangle mehod o addon

More information

Fall 2010 Graduate Course on Dynamic Learning

Fall 2010 Graduate Course on Dynamic Learning Fall 200 Graduae Course on Dynamc Learnng Chaper 4: Parcle Flers Sepember 27, 200 Byoung-Tak Zhang School of Compuer Scence and Engneerng & Cognve Scence and Bran Scence Programs Seoul aonal Unversy hp://b.snu.ac.kr/~bzhang/

More information

( )a = "t = 1 E =" B E = 5016 V. E = BHv # 3. 2 %r. c.) direction of induced current in the loop for : i.) "t < 1

( )a = t = 1 E = B E = 5016 V. E = BHv # 3. 2 %r. c.) direction of induced current in the loop for : i.) t < 1 99 3 c dr b a µ r.? d b µ d d cdr a r & b d & µ c µ c b dr µ c µ c b & ' ln' a +*+* b ln r ln a a r a ' µ c b 'b* µ c ln' * & ln, &a a+ ncreang no he page o nduced curren wll creae a - feldou of he page

More information

Quick Visit to Bernoulli Land

Quick Visit to Bernoulli Land Although we have een the Bernoull equaton and een t derved before, th next note how t dervaton for an uncopreble & nvcd flow. The dervaton follow that of Kuethe &Chow ot cloely (I lke t better than Anderon).

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

Design of Controller for Robot Position Control

Design of Controller for Robot Position Control eign of Conroller for Robo oiion Conrol Two imporan goal of conrol: 1. Reference inpu racking: The oupu mu follow he reference inpu rajecory a quickly a poible. Se-poin racking: Tracking when he reference

More information

NUMERICAL PROCEDURE FOR SHIP HYDROELASTIC ANALYSIS

NUMERICAL PROCEDURE FOR SHIP HYDROELASTIC ANALYSIS Inernaonal Conference on Copuaonal Mehod n Marne Engneerng MARIE 009 T. Kvadal, B. Peeren, P. Bergan, E. Oñae and J. García (Ed) CIME, Barcelona, 009 UMERICAL PROCEDURE FOR HIP HYDROELATIC AALYI I. EJAOVIĆ

More information