Conservative and Easily Implemented Finite Volume Semi-Lagrangian WENO Methods for 1D and 2D Hyperbolic Conservation Laws

Size: px
Start display at page:

Download "Conservative and Easily Implemented Finite Volume Semi-Lagrangian WENO Methods for 1D and 2D Hyperbolic Conservation Laws"

Transcription

1 Joural of Appled Mahemacs ad Physcs, 07, 5, 59-8 hp:// ISSN Ole: ISSN Pr: Coservave ad Easly Implemeed Fe Volume Sem-Lagraga WENO Mehods for D ad D Hyperbolc Coservao Laws Fuxg Hu Deparme of Mahemacs, Huzhou Uversy, Huzhou, Cha How o ce hs paper: Hu, F.X. (07) Coservave ad Easly Implemeed Fe Volume Sem-Lagraga WENO Mehods for D ad D Hyperbolc Coservao Laws. Joural of Appled Mahemacs ad Physcs, 5, hp://dx.do.org/0.436/amp Receved: December, 06 Acceped: Jauary 6, 07 Publshed: Jauary 9, 07 Copyrgh 07 by auhor ad Scefc Research Publshg Ic. Ths work s lcesed uder he Creave Commos Arbuo Ieraoal Lcese (CC BY 4.0). hp://creavecommos.org/lceses/by/4.0/ Ope Access Absrac The paper s devsed o propose fe volume sem-lagrage scheme for approxmag lear ad olear hyperbolc coservao laws. Based o he dea of sem-lagraga scheme, we rasform he egrao of flux me o he egrao space. Compared wh he radoal sem-lagrage scheme, he scheme devsed here res o drecly evaluae he average fluxes alog cell edges. I s hs dfferece ha makes he scheme hs paper smple o mpleme ad easly exed o olear cases. The procedure of evaluao of he average fluxes oly depeds o he hgh-order spaal erpolao. Hece he scheme ca be mplemeed as log as he spaal erpolao s avalable, ad o addoal emporal dscrezao s eeded. I hs paper, he hgh-order spaal dscrezao s chose o be he classcal 5horder weghed esseally o-oscllaory spaal erpolao. I he ed, D ad D umercal resuls show ha hs mehod s raher robus. I addo, o exhb he umercal resoluo ad effcecy of he proposed scheme, he umercal soluos of he classcal 5h-order WENO scheme combed wh he 3rd-order Ruge-Kua emporal dscrezao (WENOJS) are chose as he referece. We fd ha he scheme proposed he paper geeraes comparable soluos wh ha of WENOJS, bu wh less CPU me. Keywords Sem-Lagraga Mehod, Average Flux, WENO Scheme, Hgh-Order Scheme, Hyperbolc Coservao Laws. Iroduco The characersc of hyperbolc coservao laws s ha hey ca geerae dscouous soluos eve f he al codo s smooh. I s hs propery DOI: 0.436/amp Jauary 9, 07

2 ha leads o he challege developg he hgh-order umercal mehods. The ma dffculy of desgg hgh-order mehods s how o maa he hghorder accuracy aroud he smooh regos ad meawhle suppress he spurous oscllaos aroud he regos wh large grades. I he pas few decades, may hgh-order umercal mehods were developed o evolve he hyperbolc problem, e.g. he esseally o-oscllaory schemes (ENO) [] [] [3] [4], he weghed esseally o-oscllaory schemes (WENO) [5] [6] ad he dscouous Galerk fe eleme mehod [7] [8], ad so o. The dscrezao procedure of he classcal WENO schemes [5] ca be dvded o wo sages. Frs, hrough spaal dscrezao mplemeed by WENO recosruco, leavg he equaos couous me; hs leads o a sysem of ordary dffereal equaos me. The, ay umercal mehods for ordary dffereal equaos, e.g. Ruge-Kua mehods, ca be used o evolve hs sysem. I order o make he soluo sable oal varao orm, Shu ad Osher [3] ad Shu [9] devsed a se of TVD Ruge-Kua mehods as ODE solvers. Takg hree-sage TVD Ruge-Kua mehods for example, hree WENO recosruco processes are eeded o evolve oe me sep. Ad hey also suffer from a CFL me sep sably resrco. To fx he problem above, he sem-lagraga mehods [0] [] [] [3] avod he me dscrezao by characersc racg echque ad have more allevave resrco for CFL umber. Recely, he papers [4] [5] [6] [7], he auhors combed he dea of sem-lagraga wh WENO recosruco for solvg adveco problems. The sem-lagraga mehods above deped o he characersc racg. However, for geerally olear cases, s mpossble o fd he race pos exacly (eve fdg he race pos wh hgh accuracy s very hard). I s hs resrco ha makes he sem-lagraga mehods very hard o apply o olear problems. The auhors Huag ad Arbogas [8] devsed a sem-lagraga mehod for olear coservao laws. However, a cosly flux correco s eeded for keepg hgh accuracy ad umercal sably. I hs paper, we ry o drecly evaluae he average flux ( ( )) F = f u x, d, () where s he me sep ad x s he mesh boudary. The ma dea of evaluao of he average fluxes s he rasformao of he egrao of flux fuco me o he egrao space. A smlar rasformao had appeared [6]. The compuao for egrao space oly depeds o he spaal erpolao polyomal. Hece, he scheme here ca be mplemeed easly as log as he procedure of spaal erpolao s avalable. Several hgh-order polyomal erpolaos ca be chose, e.g. he PPM [9], ENO [] [] or WENO [5] [6], ec. I hs paper, we choose he classcal 5h-order WENO erpolao o recosruc he polyomal space ad we call he scheme here as WENOEL. I s oed ha he scheme s obvously coservave sce we drecly evaluae he average flux a each cell edge. As he sem-lagraga mehods preseed leraure, we also eed he rackg back pos alog cha- 60

3 racersc les o evaluae he average flux. Sce he characersc pos ca be racked back exacly (or wh hgh-order accuracy) oly for some smple lear equaos, we do o ry o fd he characersc pos wh hgh-order accuracy. For lear problems, he scheme ca acheve opmal accuracy because he average flux ca be evaluaed wh hgh order of accuracy. For olear problems, esg he order of accuracy for smooh soluo, o opmal accuracy ca be guaraeed. For esg he resoluo olear problems of he scheme, we choose he classcal WENOJS (he 5h-order WENO recosruco wh 3rd-order Ruge-Kua me dscrezao) as bechmark ad compare hem for several D ad D examples. We fd ha he scheme proposed he paper geeraes comparable soluos wh ha of WENOJS bu eeds less ha half compug me. The free CFL resrco s aoher advaage of sem-lagraga mehods. For adveco problems, he CFL umber ca be chose geerally larger ha. However, for olear hyperbolc coservao laws, he CFL > wll lead o umercal sably geerally f here exs shocks. I hs paper, he CFL = 0.6 s chose for he WENOEL scheme all he umercal examples. I he paper ha follows, we wll prese he evaluao procedure of he average flux Seco deal. I Seco 3, o show he hgh resoluo ad effcecy of our scheme, we compare he schemes WENOEL proposed here ad WENOJS for several D ad D examples. Ad from he comparsos of resoluo ad effcecy for hese D ad D examples, we ca fd ha he proposed mehod hs paper ca prese comparable resuls wh he classcal WENOJS scheme, bu wh less CPU me.. The Fe Volume WENOEL Scheme Cosder he coservao laws subec o al codo x( ) u x, f u x, = 0, a x b, 0 () (,0) = u x u x wh proper boudary codos. Iegrag he Equao () o corol volume x, x [, ] gves x = x u x, d x u x, dx x x Rearragg hs equao ad dvdg by x x u( x, ) d (, ) d x x= u x x x x x x Deoe he h cell average by 0 ( ( )) ( ( )) f u x, d f u x, d. x yelds ( f ( u( x, ) ) d f ( u( x, ) ) d ) (3) 6

4 ad average flux a cell edge x by he (3) ca be wre as The value x u = u( x, ) d, x x x ( ( )) f = f u x, d, (4) u = u f f x ( ). U wll approxmae he average value U (5) u. Gve he approx- maed cell average U, he formula (5) ells us ha a ex me sep ca be updaed f he me egrals o he rgh of (4) ca be evaluaed effcely. Deog he approxmaed flux fuco f by F he we oba.. The Lear Equao ( ( )) F f u x, d, U = U F F x ( ). Here, we maly cosder he 5h-order fe volume verso because of s populary ad oher cases ca be obaed smlarly. Cosder he lear adveco equao u x, cu x, = 0, a x b, 0. (7) =. For hs equao, he - u x smply propagaes rgh f c > 0 (or lef f c < 0 ) wh I hs case, he flux fuco f( u( x, )) cu( x, ) al codo 0 uchaged shape. x For evaluag he average flux f (4), we ca frsly apply a 5h-order N o oba - recosruco based o pecewse cosa average fluxes { f k } k= erpolao polyomal P ( x ) o cell I 5 ( ) = ( ) (6) f u x, P x x. (8) The 5h-order polyomal P ( x ) s recosruced over he secl S = { I, I, I, I, I }. Here, we assume he adveco velocy 0 o he rgh wh velocy c, whch gves for ay me [, ] f( u( x, )) a cell edge x s c >, he u x smply spreads, ( (, )) ( (, ) ) f u x = f u x c (9). Combg he Formulas (8) ad (9), he flow rae 5 ( ) = ( ( ) ) ( ) f u x, P x c x. (0) I hs case, he average flux f ca be expressed approxmaely as 6

5 ( ( )) f = f u x, d = P x c x x 5 = P ( x) d x ( x ). c x c 5 Omg he hgh-order erm ( x ) 5 ( ) d (), we oba he umercal flux F x P ( x ) d. x = c () x c The las equaly () s obaed by egrao of subsuo x = x c( ). From he Equao (), he egrao me [, ] s rasformed o egrao space x c x,. Due o he egrad P ( x ) s recosruco polyomal, he las egrao () ca be compued exacly. Remark. Ths rasformao s he ma dea of hs paper. Ad s smlar o he equao (3.9) [6] bu wh a slghly dffere way. The ma dfferece s ha he operao [6] rasforms he flux egrao me a cell ceer o he egrao of u( x, ) space x ( ( )) = f u x, d u x, d, x where x s he backward characersc po of cell ceer x. Ad here we rasform he flux egrao me a cell edge o he egrao of erpolao polyomal of flux fuco space. Ths dfferece makes he exeso of he scheme o olear cases much easer. I he followg of hs subseco, we wll prese he 5h-order WENO recosruco process o approxmae he egral () x x P x d. x x c The 5h-order WENO recosruco procedure s represeed as he covex combao of hree 3rd-order recosrucos. Frs, we ed o recosruc he 3rd-order coservave polyomals o cell I = x, x based o he pecewse cosa average fluxes. { f k }, k =,,. I s oed ha here are 3 hree-po secls coaed he cell I ca be used o recosruc he polyomals. We deoe hese secls respecvely by { } S = I, I, I, 0 { } S = I, I, I, { } S = I, I, I. The correspodg polyomal of each secl s P x = b0 bx bx, = 0,,, (3) where he subscrp deoes he polyomal o cell I ad superscrp 63

6 deoes he recosruco based o secl gve by (for smplcy, we om superscrp b 0 f 7 f f = 6 ( ) f f f x x f 3f f S. The coeffces (3) are f ) ( 3 ) ( ) = b x f f f = b x, f f f x, x f f f x where = 0,, ad x = x x s he legh of cell I. So far, we have P x o each secl x obaed he coservave erpolao polyomals S. I he ed, he egral () ca be expressed as where he lear opmal weghs x x = x c x c = 0 P x dx d P x d, x d are 0 3 d = λ λ, d = λ λ, d = λ λ, c where λ =. For allevag he effec of he o-smooh secls, he olear weghs ca be cosruced as x follows ad The w a a = a a a = 0 d. ε β β s he dcaor of smoohess based o he secl 0 β = S, 3 ( f f f ) ( 3f 4 f f ), 4 3 ( f f f ) ( f f ), 4 β = 3 ( f f f ) ( f 4f 3 f ). 4 β = Fally, he umercal flux should be expressed as F w P x x c x c = 0 Subsug he Formulas (3) o (6) gves, (4) (5) = x d. (6) 64

7 F w P x dx x = x c c = 0 0 ( λ ( ) λ( 3 3 ) ( 5 ) ) ( λ ( ) λ( 3 3 ) ( 5 ) ) ( λ ( ) λ( ) ( )) = w f f f f f f f f 6 w f f f f f f f f w f f f 3 f 9 f 6 f f 7 f f. I coras, whe he adveco velocy 0 wh velocy c, whch gves ad he flow rae c <,, f ( u( x, ) ) f ( u( x c( ), ) ) f( u x, ) a cell edge x s 5 ( ( )) = ( ( ) ) ( ) (7) u x spreads o he lef = (8) f u x, P x c x. (9) Smlarly, he average flux F ca be expressed as F w x c P ( x ) d. x c x = (0) = 0 The olear wegh w ca be cosruced smlarly as (4) ad (5). The lear opmal weghs are 0 3 d = λ λ, d = λ λ, d = λ λ Subsug he formula (3) o (0) gves ( λ ( ) λ( ) ( 7 )) ( λ ( ) λ( 3 3 ) ( 5 )) ( λ ( ) λ( 3 3 ) ( 5 )). F = w f f f f f f f f f 6 w f f f f f f f f w f f f f f f f f The scheme proposed he paper s coservave for lear ad olear cases. The propery of coservao s obvous sce he scheme (6) s represeed coservao form. Remark. I [6], he auhors Qu ad Shu preseed a sem-lagraga fe dfferece WENO mehod for adveco compressble flow. Acually, here are wo recosruco procedures eeded o oba he umercal flux a cell edge x. I s oed ha, for lear equao wh cosa coeffce, he formulas of average flux (7) ad () are oally same as oes [6]. However, hese wo mehods are devsed by oally dffere procedure. They maly have he followg dffereces: he mehod prese here s fe volume; our mehod ca be easly exeded o olear cases by freezg locally ad dealed descrpo s gve Subseco.3; here are always exs lear opmal weghs o cosruc he WENO schemes for our scheme whch s o sasfed he schemes [6]. () 65

8 .. Algorhm Here, we coclude he algorhm for compug umercal flux F a x = x durg a me sep =. ) Dsgush he propagao dreco of soluo a x = x used Rake-Hugoo ump codo or c = f ( u ) f u u u ) The propagao velocy ca be chose o be f u c = f c < 0. u= u u. f u c = u= u u f c > 0, 3) Iser he propagao velocy o (7) or () o ge umercal flux F..3. The Nolear Equaos I hs subseco, we wll exe he mehod above o olear case. Frsly, s oed ha for olear case he mehod here cao approach he opmal accuracy sce he soluo o loger smply raslaes uformly. Isead, deforms as evolves ad he characersc curves are o loger parallel sragh les, whch lead o he evaluao of average fluxes s hard o oba. Ad geerally he rackg back pos cao be foud exacly (eve cao fd he pos wh hgh accuracy). Hece for olear case, raher ha ryg o fd he rackg back pos, we freeze he equao o lear formao locally ad apply he procedure Subseco. o. For solvg he olear case, he propagao dreco s frsly dsgushed by Rake-Hugoo ump f ( u) codos ad propagao velocy s chose o be c = u= u u f ( u) c f propagao dreco < 0. ( f propagao dreco > 0) or = u= u u Remark 3. The sem-lagraga fe volume mehod proposed here s largely depede o he recosruco from he cell flux average x f = f( u( x, ) ) d. x x x For fe volume mehod, oly he cell average x u = u( x, ) dx x x s avalable. For lear problem, f( u( x, )) au( x, ) be apparely chose o be f = au =, he cell flux average ca However, for olear problem, he cell flux average mus be compued by some umercal quadraure. I hs paper, we choose Gauss quadraure o evaluae he cell flux average 66

9 x = = x k k x x k= k= 3 g g ( ) f f u x, d x A f u x,, g g where A k ad x k are he Gauss weghs ad Gauss pos, respecvely. For g smple, he value of u( x, ) a Gauss po x k ca be obaed by he 5horder Lagraga erpolao. I addo, for solvg Euler equaos, he Roe speed s used o defy he upwd dreco whch may lead o some umercal sables, especally for D cases. I Subseco 3.3, compug he umercal ess: double Mach refleco ad Mach 3 wd uel wh a sep, here deed exs umercal sables. I addo, s oed ha hs umercal sably o oly appears he WENOEL scheme, bu also appears he WENOJS scheme. I s sad ha he umercal sably s maly due o he choce of Roe speed. The dealed roducos for he umercal sables of upwd schemes are referred o [0] [] []. I order o elmae such kd of sables, he H-correco procedure [] s ake o solve hese flaws. For hese wo D problems, he umercal flux F, a he cell edge ( x, y) s compued as follows. [] ) If m ( λ,, λ, ) η,, he he umercal flux F, ca be chose o be (7) or () ad he average fluxes f k hese wo equaos are correspodgly subsued by fk, ( k =,, 3). The λ, s he egevalue ad he value η, s deermed by x y y y y η = max η, η, η, η, η, where,,,,,, x η, = u, u, a, a,, = y η,, v, v, a, a, ad a, s he speed of soud. ) Oherwse, a more dsspave Lax-Fredrch flux splg mehod s used o spl he flux f k, o posve ad egave fluxes f k, = ( fk, αuk, ), f k, = ( fk, αuk, ). For he posve ad egave fluxes, he propagao veloces are chose o be c = ( λk, α), c = ( λk, α). Iserg he f k,, c ad f k,, c o (7) ad (), respecvely, we ca ge he posve ad egave umercal fluxes F, ad F,. Fally, he umercal flux a cell edge ( x, y) s F = F F,,,. 67

10 3. Numercal Resuls I hs seco, we wll apply hs mehod o D ad D hyperbolc problems. A prese, he Srag dmesoal splg mehod [3] [4] s appled o D problems, whch s used o spl he D equao o wo D equao. I each coordae dreco, he equao s evolved by he proposed D WENOEL mehod. The dealed comparsos of resoluo ad effcecy are show bewee our mehod ad WENOJS mehod (5h-order spaal ad 3rd-order TVD RK emporal dscrezao). I he ed, s oed ha, he WENOJS mehod, he upwdg (o flux vecor splg) s used o cosruc he umercal flux. So he WENOJS mehod hs paper ca also be called by WENOJS-Roe. The dealed descrpo of WENOJS-Roe s referred o he procedure.4 o page 33 [5]. For he choce of CFL umber, I s foud ha whe 0 < CFL < he WENOEL scheme s umercally sable all he examples we have esed. Especally, we had chose CFL = 0.9 o smulae all he examples appeared hs paper ad o usable pheomeo had bee foud. For comparg he resoluo ad compug me bewee he WENOEL ad WENOJS schemes, we choose CFL = 0.6 for hese wo schemes for all he ess coaed he dscoues. Ths choce of CFL umber for he WENOJS scheme s also adoped may classcal leraures, e.g. [5]. For he problem () (3), whch s used o es he 53 order of accuracy of schemes, we choose = x for WENOJS order ha spaal error s doma bu sll le CFL = 0.6 for WENOEL. 3.. D Scalar Examples I hs subseco, we wll cosder lear adveco, Burger s ad Buckley-Levere equaos. For he lear adveco equao, wo al codos are used o es he schemes. We use a smooh al codo o es he order of accuracy of he scheme ad a codo coaed dscoues ad hgh-frequecy waves o es he performace of he scheme smulag dscouous ad large-grade soluo. For he Burger equao, we also cosder wo al codos whch commoly used o valdae he proposed scheme. For he ocovex Buckley-Levere equao, we sudy a smple model for wo-phase flud flow a porous medum. Excep for he comparso of resoluo bewee he WENOJS ad WENOEL schemes, he compug me s also show hs subseco Lear Adveco Equao Cosder he lear adveco equao u x, u x, = 0, x, 0, () x subec o wo al codos ad perodc boudary codos. Oe al codo s u x,0 = s π x, (3) 68

11 ad he oher s ( ( β δ) ( β δ) ( β )) G x,, z G x,, z 4 G x,, z x 0.6, 0.4 x 0., u( x,0) = 0x 0.0 x 0., ( F( x, α, a δ) F( x, α, a δ) 4 F( x, α, a) ) x 0.6, 0 oherwse, where G( x, β, z) = exp β( x z), F( x α a) ( α( x a) ) ad he parameers are gve by (4),, = max,0, l a = 0.5, z = 0.7, δ = 0.005, α = 0, δ =. 36δ The problem () (3) here s used o es he accuracy of our mehod lear case. The Table ad Table prese he comparso of errors ad accuracy bewee he WENOEL ad WENOJS mehods. The oupu me s chose o be = ad he me seps are chose o be = 0.6 x ad = ( x) 53 for he WENOEL ad WENOJS, respecvely. As he classcal WENOJS mehod, he WENOEL also arrves 5h-order of accuracy. For he l ad l errors, he WENOEL mehod shows much beer resuls ha he WENOJS mehod. Ths Table. The es of order of accuracy for he l ad l errors for al value problem () (3) wh WENOEL mehod. The me sep s chose o be = 0.6 x ad fal me s =. WENOEL N l r l r e e e e e e e e e e e e Table. The es of order of accuracy for he l ad l errors for al value problem () (3) wh WENOJS mehod. The me sep s chose o be = ( x) 53 ad fal me s =. WENOJS N l r l r e e e e e e e e e e e e

12 resul s expeced sce he rackg po ca be foud exacly ad he umercal flux s obaed much accuraely. The soluo of () (4) coas a dscouous square pulse ad several couous bu hgh-grade profles. Ths problem s coveoally employed o es hgh-resoluo schemes. The oupu me s chose o be = ad he me sep s chose o be = 0.6 x for he WENOEL ad WENOJS schemes. Fgure gves he soluos of he WENOEL ad WENOJS mehods wh cells N = 00. From Fgure, we ca fd ha he WENOEL ad WENOJS mehods ca boh capure he dscouous ad seep soluos. Ad for he frs ad hrd hgh-frequecy waves, he WENOEL performs slghly beer ha WENOJS mehod. Fgure s used o es he log-me behavor of hese wo mehods Fgure. The umercal soluos of () (4) s compued by WENOEL ad WENOJS mehods wh N = 00 ul me =. The blue ad red deoe he soluos of WENOEL ad WENOJS mehods, respecvely. Fgure. The umercal soluos of () (4) s compued by WENOEL ad WENOJS mehods wh N = 00 ul me = 0. The blue ad red deoe he soluos of WENOEL ad WENOJS mehods, respecvely. 70

13 afer 0 cycles,.e. = 0. Obvously, followg log-me evoluo, he WENOEL gves hgher-resoluo soluo aroud four waves ha ha of WENOJS mehod. I addo, we prese he comparso of CPU me ( secods) ad l error for hs problem bewee he WENOEL ad WENOJS mehods Burger Equao I hs subseco, we cosder he Burger s equao u u = 0, x, 0 subec o wo al codos. oe al codo s ad he oher s (,0) u x x x 0, = 0 0 x, ( x) (5) (6) u x,0 =.5 s π. (7) For he olear scalar equao, we frs use Rake-Hugoo ump codo o defy he upwdg dreco, he compue he average flux by (7) or (). I addo, a eropy fx s used o modfy he average flux whe rarefaco wave appears. For he problems (5) (6) ad (5) (7), we boh se 0.6 x f = for he WENOEL ad WENOJS schemes, where λ = max λ N u. For he problem (5) (6), he umercal soluos are compued wh cells N = 00 ul me =. From Fgure 3, he soluo of hs problem coas a rarefaco ad a shock, ad hese wo mehods arrve almos same resoluo. I Fgure 4, he problem (5) (7) has he same se bu he oupu me = 0.37, ad has he same cocluso wh las problem. I a word, for olear Burger s Fgure 3. The umercal soluos of (5) (6) are compued by he WENOEL ad WENOJS mehods wh N = 00 ul me =. The blue ad red deoe he soluos of WENOEL ad WENOJS mehods, respecvely. 7

14 Fgure 4. The umercal soluos of (5) (7) are compued by he WENOEL ad WENOJS mehods wh N = 00 ul me = The blue ad red deoe he soluos of WENOEL ad WENOJS mehods, respecvely. equao, he WENOEL scheme ca also oba comparable umercal resuls ad oly eed half CPU me. The preseao of CPU me s omed for savg space Buckley-Levere Equao As a example where ocovex flux fucos arse, we sudy a smple model for wo-phase flud flow a porous medum. Cosder he scalar coservao law u u = 0, x, 0, (8) u ( u) 4 x wh he al codo 0.5 x 0, u( x,0) = (9) 0 oher. Fgure 5 shows he soluos compued by he WENOEL ad WENOJS mehods wh cells N = 00 ul me = 0.4. Also, we choose he me seps 0.6 x f = for WENOEL ad WENOJS schemes, where λ = max λ N u. From Fgure 5 he WENOEL mehod geeraes he soluo whch s comparable wh ha of he WENOJS mehod. For he ocovex flux problem, he WENOEL scheme ca also have a robus performace as WENOJS scheme. 3.. The D Euler Equao I hs subseco, we cosder D Euler equaos sce oe of he ma applcao areas of hgh-resoluo scheme s compressble gas dyamcs, 7

15 Fgure 5. The umercal soluos of (8) (9) are compued by he WENOEL ad WENOJS mehods wh N = 00 ul me = 0.4. The blue ad red deoe he soluos of WENOEL ad WENOJS mehods, respecvely. ρ ρu E E p u ρu ρu p = ( ) x 0, (30) where ρ, u, p, E are desy, velocy, pressure ad oal eergy, respecvely. The sysem of equaos s closed by he equao of sae for a deal polyropc gas: p E = ρu, γ where he rao of specfc heas γ =.4. The followg hree al codos combed wh Euler Equaos (30) are cosdered, whch are ofe used o exame he mehods for solvg Euler equaos: ( ρ, u, p) ( ρ, v, p) 0.445, 0.698, 3.58, f 5 x < 0, = 0.5, 0, 0.57, f 0 x 5, ,,, f 5 x < 4, = ( 0. s ( 5 x), 0, ), f 4 x 5. ( ρ u p), 0,000, f 5 x < 4,,, =, 0, 0.0, f 4 x< 4,, 0,00, f 4 x 5, For solvg Euler equaos, Roe learzao (.e. Roe average) s used o locally freeze a olear sysem o a lear sysem. The hs sysem s decoupled o hree adveco equaos ad each equao s solved by procedure (3) (3) (33) 73

16 Seco 0. I s oed ha he propagao dreco of soluo of each adveco equao s dsgushed by correspodg egevalue of Roe marx. For he problem (30) (3), called Lax problem [6], we solve wh = 0.6 x λ for he WENOEL ad WENOJS mehods. Fgure 6 s compued wh cells N = 00 ad oupu me =.3. Apparely, he WENOEL mehod performs almos he same as WENOJS mehod ad preses a robus soluo for hs shock-ube problem. The exac soluo s obaed by he solver preseed [4]. The problem (30) (3), called shock eropy wave eraco [4], s usually used o es he hgh-order mehods for capurg he hgh-frequecy waves. The CFL umber s also se o be = 0.6 x λ for he WENOEL ad WENOJS mehods. We evolve he equaos up o =.8 wh cells N = 400. For hs problem, a Mach 3 shock wave moved rgh eracs wh se waves a desy whch lead o a feld obaed smooh ad dscouous srucures. The referece soluo Fgure 7 s compued by WENOJS mehod wh cells N = 000. I s plaly see from Fgure 7 ha, as WENOJS, he WENOEL mehod performs wh he hgh resoluo. Furhermore, from Fgure 8, we ca fd ha he par of hgh-frequecy waves he WENOEL mehod performs less dsspave ha he WENOJS mehod. The problem (30) (33) was orgally proposed as a bechmark for esg several umercal mehods by Woodward ad Colella [9]. The reflecve boudary codos are appled o boh boudares. The CFL umber s also se o be = 0.6 x λ for he WENOEL ad WENOJS mehods. We evolve he equaos up o = 0.38 wh cells N = 400. The referece soluo Fgure 9 s compued by WENOJS mehod wh cells N = 000. As he las wo problems, he WENOEL mehod gves almos he same resoluo as WENOJS mehod. Fgure 6. The shock-ube problem (30) (3) s compued by he WENOEL ad WENOJS mehods wh cells N = 00 ul me =.3. The blue ad red deoe he soluos of WENOEL ad WENOJS mehods, respecvely. 74

17 Fgure 7. The shock eropy wave problem (30) (3) s compued by he WENOEL ad WENOJS mehods wh cells N = 400 ul me =.8. The blue ad red deoe he soluos of WENOEL ad WENOJS mehods, respecvely. Fgure 8. The zoomed fgure of Fgure 7 aroud he hgh-frequecy waves The D Euler Sysem Fally, we cosder a umercal experme for D Euler equaos for gas dyamcs, ρ ρu ρv ρu ρu p ρuv = 0, ρv ρuv ρv p E ( E p) u ( E p) v x y where he equao of sae s p = ( γ ) E ρ( u v ), γ =.4. (34) 75

18 Fgure 9. The blas wave problem (30) (33) s compued by he WENOEL ad WENOJS mehods wh cells N = 400 ul me = The blue ad red deoe he soluos of WENOEL ad WENOJS mehods, respecvely Double Mach Refleco Here we frsly apply he WENOEL ad WENOJS schemes o he D double- Mach shock refleco problem where a srog vercal shock moves horzoally o a wedge whch cled wh some agle wh he rao of specfc heas γ =.4. Ially, hs problem was proposed by Woodward ad Colella [9] ad had bee ake exesvely as a es example for hgh-order schemes. The 0, 4 0, ad he reflecve wall les compuaoal doma s chose o be [ ] [ ] o he boom of he compuaoal doma for x 4. I he begg, a 6 Mach 0 shock, movg rgh, s locaed a x =, y = 0 ad makes a agle 6 60 wh he x -axs. For he boudary codos, he exac posshock codo s mposed for boom boudary from x = 0 o x =, ad he 6 reflecve boudary codo s mposed for he res; he flows are mposed o he op boudary such ha here s o eraco wh he Mach 0 shock; flow ad ouflow boudary codos are se for he lef ad rgh boudares respecvely. The ushocked flud has a desy of.4, a pressure of ad hs problem s ru ul = 0. wh cells I addo, here exss umercal sably compug hs problem by uwd mehods. A H-correco procedure preseed Subseco.3 s used o elmae hs sably. The H-correco procedure ecs much dsspao usable rego by he way of shfg he upwd scheme o flux splg scheme. The coour les of he desy are show Fgure 0. These wo mehods boh oba hgh-resoluo soluos. I rego of complcaed srucure, he WENOJS scheme performs beer ha our scheme. 76

19 Fgure 0. Double Mach problem. The desy ρ s show wh meshes equally spaced coour les are ploed from.73 o The op: WENOEL scheme. The boom: WENOJS scheme Mach 3 Tuel wh a Sep Ths wd problem s also orgally preseed [9]. Ths problem s se up as follows. The wd uel s legh u wde ad 3 legh us log. The sep s 0. legh us hgh ad s locaed 0.6 legh us from he lef-had ed of he uel. The problem s alzed by a uform rgh-gog Mach 3 flow. Reflecve boudary codos are appled alog he wall of he uel. The flow ad ouflow boudary codos are appled a he erace ad ex, respecvely. The corer of s a sgular po ad we use he same echque o correc [9], whch s based o he assumpo of a early seady flow he rego ear he corer. I addo, o elmae he umercal sably orgaed from he upwd scheme, he same H-correco procedure as las problem s used o elmae hs flaw. We evolve he al daa ul me 4 wh a grd of cells by he WENOEL ad WENOJS mehods. The CFL umber s chose o be 0.6 for hese mehods. The coour les of he desy are dsplayed Fgure. We observe he good resoluo ad srog 77

20 Fgure. Mach 3 uel wh a sep problem. The desy ρ s show wh meshes equally spaced coour les are ploed from 0. o 6.4. The op: WENOEL scheme. The boom: WENOJS scheme. reflecve waves hs es for hese mehods. Moreover, a beer resoluo ca be observed for he WENOJS mehod D Rema Problem Ths s a smple D Rema problem o square [ 0,] [ 0,] s used o es our mehod whch s orgally proposed [7]. The square s dvded o four quadras by sragh les 7x = 0.8 ad y = 0.8. Ially, four dffere cosa saes are defed o each of quadras ( ρ, uvp,, ) 0.533,.06, 0, 0.3, f 0 x< 0.8, 0.8 y,.5, 0, 0,.5, f 0.8 x, 0.8 y, = 0.38,.06,.06, 0.09, f 0 x< 0.8, 0 y < 0.8, 0.533, 0,.06, 0.3, f 0.8 < x, 0 y < 0.8. (35) We solve he problem ul = 0.8 wh cells The me seps s se o be = 0.6 x λ for he WENOEL ad WENOJS mehods. Fgure gves he desy profles compued by he WENOEL ad WENOJS mehods, respecvely, ad hese wo hgh-resoluo scheme boh perform well Raylegh-Taylor Isably Problem Fally, we cosder Raylegh-Taylor sably problem [8]. Ths problem descrbes he flow moos o he erface bewee fluds wh dffere desy. The heavy flud moves o he rego of he lgh flud wh a fgerg aure, whch lead o he bubbles of lgh flud rsg o he heavy flud ad he spkes of heavy flud fallg o he lgh flud. The compuaoal doma s 78

21 Fgure. The soluos of D Rema problem compued by he WENOEL ad WENOJS mehods. The lef: WENOEL scheme. The rgh: WENOJS scheme. 0, [ 0,] 4, ad he al codos s γ p, 0, 0.05 cos( 8π x), y, f 0 y, ρ < ( ρ, uvp,, ) = (36) γ p, 0, 0.05 cos( 8π x), y.5, f y, ρ 5 where he rao of specfc heas γ =. For he boudary codos, he 3 reflecve boudary codos are mposed o he lef ad rgh boudares; he flows are se as ( ρ, uvp,, ) = (, 0, 0,.5) ad ( ρ, uvp,, ) = (, 0, 0,) for he op ad boom boudares, respecvely. I addo, he source erms ρ ad ρ v are added o he rgh of he hrd ad fourh equaos of Euler equaos (34), respecvely. For hs problem, from Fgure 3, we ca fd ha he WENOEL ad WENOJS mehods boh geerae hgh-resoluo umercal soluos. From he performace of hese four D problems, as he D problems, we ca fd ha he smlar resoluo wh he WENOJS scheme ca be observed. 4. Cocluso I hs paper, we propose a smple ad easly mplemeed mehod o solve hyperbolc coversao laws. The ma dea of hs mehod s he rasformao of egrao of flux fuco me o egrao space. I s hs procedure ha leads o he average flux a cell edge whch ca be drecly evaluaed. I addo, he evaluao of he average flux s easly mplemeed ad ca be combed wh ay o-oscllaory spaal recosruco. Through he performace o los of classcal examples, we ca fd hs mehod s raher robus. We compare our scheme wh he classcal WENOJS scheme ad almos he same performace o resoluo s observed. Ad from he comparsos of resoluo ad effcecy for hese D ad D examples, we ca fd ha he 79

22 Fgure 3. The soluos of Raylegh-Taylor sably problem compued by he WENOEL ad WENOJS mehods wh cells The lef: WENOEL scheme. The rgh: WENOJS scheme. proposed mehod hs paper ca prese comparable resuls wh he classcal WENOJS scheme, bu wh less CPU me. Ackowledgemes Ths work was suppored by he Naoal Naural Scece Foudao of Cha (No. 5038), Naural Scece Foudao of Guagdog Provce (No. 0A030339) ad Suppored by he Maor Proec Foudao of Guagdog Provce Educao Deparme (No. 04KZDXM070). Refereces [] Hare, A., Egqus, B., Osher, S. ad Chakravarhy, S. (987) Uformly Hgh Order Esseally No-Oscllaory Schemes III. Joural of Compuaoal Physcs, 7, hps://do.org/0.06/00-999(87) [] Hare, A. ad Osher, S. (987) Uformly Hgh Order Esseally No-Oscllaory Schemes I. SIAM Joural o Numercal Aalyss, 4, hps://do.org/0.37/0740 [3] Shu, C.W. ad Osher, S. (988) Effce Implemeao of Esseally No-Oscllaory shock-capurg Schemes. Joural of Compuaoal Physcs, 77, hps://do.org/0.06/00-999(88) [4] Shu, C.W. ad Osher, S. (989) Effce Implemeao of Esseally No-Oscllaory Shock-Capurg Schemes II. Joural of Compuaoal Physcs, 83, hps://do.org/0.06/00-999(89)90- [5] Jag, G.S. ad Shu, C.W. (996) Effce Implemeao of Weghed ENO Schemes. Joural of Compuaoal Physcs, 6, 0-8. hps://do.org/0.006/cph

23 [6] Lu, X.D., Osher, S. ad Cha, T. (994) Weghed Esseally No-Oscllaory Schemes. Joural of Compuaoal Physcs, 5, 00-. hps://do.org/0.006/cph [7] Cockbur, B. ad Shu, C.W. (998) The Ruge-Kua Dscouous Galerk Mehod for Coservao Laws V: Muldmesoal Sysems. Joural of Compuaoal Physcs, 4, hps://do.org/0.006/cph [8] Cockbur, B. ad Shu, C.W. (989) TVB Ruge-Kua Local Proeco Dscouous Galerk Fe Eleme Mehod for Coservao Laws II: Geeral Framework. Mahemacs of Compuao, 5, [9] Shu, C.W. (998) Esseally No-Oscllaory ad Weghed Esseally No-Oscllaory Schemes for Hyperbolc Coservao Laws. I: Cockbur, B., Shu, C.-W., Johso, C. ad Tadmor, E., Eds., Advaced Numercal Approxmao of Nolear Hyperbolc Equaos, Lecure Noes Mahemacs, Sprger, Berl, hps://do.org/0.007/bfb [0] Arbogas, T. ad Huag, C. (006) A Fully Mass ad Volume Coservg Implemeao of a Characersc Mehod for Traspor Problems. SIAM Joural o Scefc Compug, 8, hps://do.org/0.37/ [] Arbogas, T. ad Wheeler, M.F. (995) A Characerscs-Mxed Fe Eleme Mehod for Adveco-Domaed Traspor Problems. SIAM Joural o Numercal Aalyss, 3, hps://do.org/0.37/07307 [] Douglas, J. ad Russell, T.F. (98) Numercal Mehods for Coveco-Domaed Dffuso Problems Based o Combg he Mehod of Characerscs wh Fe Eleme or Fe Dfferece Procedures. SIAM Joural o Numercal Aalyss, 9, hps://do.org/0.37/ [3] Wag, H. ad Al-Lawaa, M. (006) A Locally Coservave Eulera-Lagraga Corol-Volume Mehod for Trase Adveco-Dffuso Equaos. Numercal Mehods for Paral Dffereal Equaos,, hps://do.org/0.00/um.006 [4] Huag, C., Arbogas, T. ad Qu, J. (0) A Eulera-Lagraga WENO Fe Volume Scheme for Adveco Problems. Joural of Compuaoal Physcs, 3, hps://do.org/0.06/.cp [5] Qu, J.M. ad Chrsleb, A. (00) A Coservave Hgh Order Sem-Lagraga WENO Mehod for he Vlasov Equao. Joural of Compuaoal Physcs, 9, hps://do.org/0.06/.cp [6] Qu, J.M. ad Shu, C.W. (0) Coservave Hgh Order Sem-Lagraga Fe Dfferece WENO Mehods for Adveco Icompressble Flow. Joural of Compuaoal Physcs, 30, hps://do.org/0.06/.cp [7] Qu, J.M. ad Shu, C.W. (0) Coservave Sem-Lagraga Fe Dfferece WENO Formulaos wh Applcaos o he Vlasov Equao. Commucaos Compuaoal Physcs, 0, hps://do.org/0.408/ccp a [8] Huag, C. ad Arbogas, T. (06) A Eulera-Lagraga WENO Scheme for Nolear Coservao Laws. Numercal Mehods for Paral Dffereal Equaos, I Press. hps://do.org/0.00/um.09 [9] Woodward, P. ad Colella, P. (984) The Numercal Smulao of Two-Dmesoal Flud Flow wh Srog Shocks. Joural of Compuaoal Physcs, 54, hps://do.org/0.06/00-999(84)904-6 [0] Km, S., Km, C., Rho, O. ad Hog, S. (003) Cures for he Shock Isably: Developme of a Shock-Sable Roe Scheme. Joural of Compuaoal Physcs, 85, 8

24 hps://do.org/0.06/s00-999(0) [] Padolf, M. ad D Ambroso, D. (00) Numercal Isables Upwd Mehods: Aalyss ad Cures for he Carbucle Pheomeo. Joural of Compuaoal Physcs, 66, hps://do.org/0.006/cph [] Saders, R., Morao, E. ad Drugue, M. (998) Muldmesoal Dsspao for Upwd Schemes: Sably ad Applcaos o Gas Dyamcs. Joural of Compuaoal Physcs, 45, hps://do.org/0.006/cph [3] Srag, G. (968) O he Cosruco ad Comparso of Dfferece Schemes. SIAM Joural o Numercal Aalyss, 5, hps://do.org/0.37/ [4] Toro, E.F. (009) Rema Solver ad Numercal Mehods for Flud Dyamcs. 3rd Edo, Sprger, New York. hps://do.org/0.007/b7976 [5] Shu, C.W. (988) Toal-Varao-Dmshg Tme Dscrezaos. SIAM Joural o Scefc ad Sascal Compuao, 9, hps://do.org/0.37/ [6] Lax, P.D. (954) Weak Soluos of Nolear Hyperbolc Equaos ad Ther Numercal Compuao. Commucaos o Pure ad Appled Mahemacs, 7, hps://do.org/0.00/cpa [7] Schulz-Re, C.W., Colls, J.P. ad Glaz, H.M. (993) Numercal Soluo of he Rema Problems for Two-Dmeoal Gas Dyamcs. SIAM Joural o Scefc Compug, 4, hps://do.org/0.37/09408 [8] Garder, C.L., Glmm, J., McBrya, O., Mekoff, R., Sharp, D.H. ad Zhag, Q. (988) The Dyamcs of Bubble Growh for Raylegh-Taylor Usable Ierfaces. Physcs of Fluds, 3, hps://do.org/0.063/ Subm or recommed ex mauscrp o SCIRP ad we wll provde bes servce for you: Accepg pre-submsso qures hrough Emal, Facebook, LkedI, Twer, ec. A wde seleco of ourals (clusve of 9 subecs, more ha 00 ourals) Provdg 4-hour hgh-qualy servce User-fredly ole submsso sysem Far ad swf peer-revew sysem Effce ypeseg ad proofreadg procedure Dsplay of he resul of dowloads ad vss, as well as he umber of ced arcles Maxmum dssemao of your research work Subm your mauscrp a: hp://papersubmsso.scrp.org/ Or coac amp@scrp.org 8

VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS. Hunan , China,

VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS. Hunan , China, Mahemacal ad Compuaoal Applcaos Vol. 5 No. 5 pp. 834-839. Assocao for Scefc Research VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS Hoglag Lu Aguo Xao Yogxag Zhao School of Mahemacs

More information

Cyclone. Anti-cyclone

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

More information

Multiphase Flow Simulation Based on Unstructured Grid

Multiphase Flow Simulation Based on Unstructured Grid 200 Tuoral School o Flud Dyamcs: Topcs Turbulece Uversy of Marylad, May 24-28, 200 Oule Bacgroud Mulphase Flow Smulao Based o Usrucured Grd Bubble Pacg Mehod mehod Based o he Usrucured Grd Remar B CHEN,

More information

Key words: Fractional difference equation, oscillatory solutions,

Key words: Fractional difference equation, oscillatory solutions, OSCILLATION PROPERTIES OF SOLUTIONS OF FRACTIONAL DIFFERENCE EQUATIONS Musafa BAYRAM * ad Ayd SECER * Deparme of Compuer Egeerg, Isabul Gelsm Uversy Deparme of Mahemacal Egeerg, Yldz Techcal Uversy * Correspodg

More information

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

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

More information

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

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

More information

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

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

More information

FORCED VIBRATION of MDOF SYSTEMS

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

More information

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

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

More information

Partial Molar Properties of solutions

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

More information

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

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

More information

The algebraic immunity of a class of correlation immune H Boolean functions

The algebraic immunity of a class of correlation immune H Boolean functions Ieraoal Coferece o Advaced Elecroc Scece ad Techology (AEST 06) The algebrac mmuy of a class of correlao mmue H Boolea fucos a Jgla Huag ad Zhuo Wag School of Elecrcal Egeerg Norhwes Uversy for Naoales

More information

The Poisson Process Properties of the Poisson Process

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

More information

Mixed Integral Equation of Contact Problem in Position and Time

Mixed Integral Equation of Contact Problem in Position and Time Ieraoal Joural of Basc & Appled Sceces IJBAS-IJENS Vol: No: 3 ed Iegral Equao of Coac Problem Poso ad me. A. Abdou S. J. oaquel Deparme of ahemacs Faculy of Educao Aleadra Uversy Egyp Deparme of ahemacs

More information

4. THE DENSITY MATRIX

4. THE DENSITY MATRIX 4. THE DENSTY MATRX The desy marx or desy operaor s a alerae represeao of he sae of a quaum sysem for whch we have prevously used he wavefuco. Alhough descrbg a quaum sysem wh he desy marx s equvale o

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

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

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

More information

Fully Fuzzy Linear Systems Solving Using MOLP

Fully Fuzzy Linear Systems Solving Using MOLP World Appled Sceces Joural 12 (12): 2268-2273, 2011 ISSN 1818-4952 IDOSI Publcaos, 2011 Fully Fuzzy Lear Sysems Solvg Usg MOLP Tofgh Allahvraloo ad Nasser Mkaelvad Deparme of Mahemacs, Islamc Azad Uversy,

More information

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

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

More information

Fundamentals of Speech Recognition Suggested Project The Hidden Markov Model

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

More information

The Bernstein Operational Matrix of Integration

The Bernstein Operational Matrix of Integration Appled Mahemacal Sceces, Vol. 3, 29, o. 49, 2427-2436 he Berse Operaoal Marx of Iegrao Am K. Sgh, Vee K. Sgh, Om P. Sgh Deparme of Appled Mahemacs Isue of echology, Baaras Hdu Uversy Varaas -225, Ida Asrac

More information

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

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

More information

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse

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

More information

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

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

More information

Least squares and motion. Nuno Vasconcelos ECE Department, UCSD

Least squares and motion. Nuno Vasconcelos ECE Department, UCSD Leas squares ad moo uo Vascocelos ECE Deparme UCSD Pla for oda oda we wll dscuss moo esmao hs s eresg wo was moo s ver useful as a cue for recogo segmeao compresso ec. s a grea eample of leas squares problem

More information

Moments of Order Statistics from Nonidentically Distributed Three Parameters Beta typei and Erlang Truncated Exponential Variables

Moments of Order Statistics from Nonidentically Distributed Three Parameters Beta typei and Erlang Truncated Exponential Variables Joural of Mahemacs ad Sascs 6 (4): 442-448, 200 SSN 549-3644 200 Scece Publcaos Momes of Order Sascs from Nodecally Dsrbued Three Parameers Bea ype ad Erlag Trucaed Expoeal Varables A.A. Jamoom ad Z.A.

More information

Continuous Time Markov Chains

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

More information

Solving fuzzy linear programming problems with piecewise linear membership functions by the determination of a crisp maximizing decision

Solving fuzzy linear programming problems with piecewise linear membership functions by the determination of a crisp maximizing decision Frs Jo Cogress o Fuzzy ad Iellge Sysems Ferdows Uversy of Mashhad Ira 9-3 Aug 7 Iellge Sysems Scefc Socey of Ira Solvg fuzzy lear programmg problems wh pecewse lear membershp fucos by he deermao of a crsp

More information

14. Poisson Processes

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

More information

The Linear Regression Of Weighted Segments

The Linear Regression Of Weighted Segments The Lear Regresso Of Weghed Segmes George Dael Maeescu Absrac. We proposed a regresso model where he depede varable s made o up of pos bu segmes. Ths suao correspods o he markes hroughou he da are observed

More information

Asymptotic Regional Boundary Observer in Distributed Parameter Systems via Sensors Structures

Asymptotic Regional Boundary Observer in Distributed Parameter Systems via Sensors Structures Sesors,, 37-5 sesors ISSN 44-8 by MDPI hp://www.mdp.e/sesors Asympoc Regoal Boudary Observer Dsrbued Parameer Sysems va Sesors Srucures Raheam Al-Saphory Sysems Theory Laboraory, Uversy of Perpga, 5, aveue

More information

The Properties of Probability of Normal Chain

The Properties of Probability of Normal Chain I. J. Coep. Mah. Sceces Vol. 8 23 o. 9 433-439 HIKARI Ld www.-hkar.co The Properes of Proaly of Noral Cha L Che School of Maheacs ad Sascs Zheghou Noral Uversy Zheghou Cy Hea Provce 4544 Cha cluu6697@sa.co

More information

Midterm Exam. Tuesday, September hour, 15 minutes

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

More information

Numerical Methods for a Class of Hybrid. Weakly Singular Integro-Differential Equations.

Numerical Methods for a Class of Hybrid. Weakly Singular Integro-Differential Equations. Ale Mahemacs 7 8 956-966 h://www.scr.org/joural/am ISSN Ole: 5-7393 ISSN Pr: 5-7385 Numercal Mehos for a Class of Hybr Wealy Sgular Iegro-Dffereal Equaos Shhchug Chag Dearme of Face Chug Hua Uversy Hschu

More information

Cyclically Interval Total Colorings of Cycles and Middle Graphs of Cycles

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

More information

Fourth Order Runge-Kutta Method Based On Geometric Mean for Hybrid Fuzzy Initial Value Problems

Fourth Order Runge-Kutta Method Based On Geometric Mean for Hybrid Fuzzy Initial Value Problems IOSR Joural of Mahemacs (IOSR-JM) e-issn: 2278-5728, p-issn: 29-765X. Volume, Issue 2 Ver. II (Mar. - Apr. 27), PP 4-5 www.osrjourals.org Fourh Order Ruge-Kua Mehod Based O Geomerc Mea for Hybrd Fuzzy

More information

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

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

More information

Numerical Solution for the Variable Order Fractional Partial Differential

Numerical Solution for the Variable Order Fractional Partial Differential Numercal Soluo for he Varable Order Fracoal Paral Dffereal Equao wh Berse polyomals 1 Jsheg Wag, Lqg Lu, 3 Lechu Lu, 4 Ymg Che 1, Frs Auhor Yasha Uversy, wsheg010@163.com *,Correspodg Auhor Yasha Uversy,

More information

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

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

More information

An Exact Solution for the Differential Equation. Governing the Lateral Motion of Thin Plates. Subjected to Lateral and In-Plane Loadings

An Exact Solution for the Differential Equation. Governing the Lateral Motion of Thin Plates. Subjected to Lateral and In-Plane Loadings Appled Mahemacal Sceces, Vol., 8, o. 34, 665-678 A Eac Soluo for he Dffereal Equao Goverg he Laeral Moo of Th Plaes Subjeced o Laeral ad I-Plae Loadgs A. Karmpour ad D.D. Gaj Mazadara Uvers Deparme of

More information

Redundancy System Fault Sampling Under Imperfect Maintenance

Redundancy System Fault Sampling Under Imperfect Maintenance A publcao of CHEMICAL EGIEERIG TRASACTIOS VOL. 33, 03 Gues Edors: Erco Zo, Pero Barald Copyrgh 03, AIDIC Servz S.r.l., ISB 978-88-95608-4-; ISS 974-979 The Iala Assocao of Chemcal Egeerg Ole a: www.adc./ce

More information

Solving Non-Linear Rational Expectations Models: Approximations based on Taylor Expansions

Solving Non-Linear Rational Expectations Models: Approximations based on Taylor Expansions Work progress Solvg No-Lear Raoal Expecaos Models: Approxmaos based o Taylor Expasos Rober Kollma (*) Deparme of Ecoomcs, Uversy of Pars XII 6, Av. du Gééral de Gaulle; F-94 Créel Cedex; Frace rober_kollma@yahoo.com;

More information

On an algorithm of the dynamic reconstruction of inputs in systems with time-delay

On an algorithm of the dynamic reconstruction of inputs in systems with time-delay Ieraoal Joural of Advaces Appled Maemacs ad Mecacs Volume, Issue 2 : (23) pp. 53-64 Avalable ole a www.jaamm.com IJAAMM ISSN: 2347-2529 O a algorm of e dyamc recosruco of pus sysems w me-delay V. I. Maksmov

More information

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

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

More information

A Second Kind Chebyshev Polynomial Approach for the Wave Equation Subject to an Integral Conservation Condition

A Second Kind Chebyshev Polynomial Approach for the Wave Equation Subject to an Integral Conservation Condition SSN 76-7659 Eglad K Joural of forao ad Copug Scece Vol 7 No 3 pp 63-7 A Secod Kd Chebyshev olyoal Approach for he Wave Equao Subec o a egral Coservao Codo Soayeh Nea ad Yadollah rdokha Depare of aheacs

More information

GENERALIZED METHOD OF LIE-ALGEBRAIC DISCRETE APPROXIMATIONS FOR SOLVING CAUCHY PROBLEMS WITH EVOLUTION EQUATION

GENERALIZED METHOD OF LIE-ALGEBRAIC DISCRETE APPROXIMATIONS FOR SOLVING CAUCHY PROBLEMS WITH EVOLUTION EQUATION Joural of Appled Maemacs ad ompuaoal Mecacs 24 3(2 5-62 GENERALIZED METHOD OF LIE-ALGEBRAI DISRETE APPROXIMATIONS FOR SOLVING AUHY PROBLEMS WITH EVOLUTION EQUATION Arkad Kdybaluk Iva Frako Naoal Uversy

More information

Some Probability Inequalities for Quadratic Forms of Negatively Dependent Subgaussian Random Variables

Some Probability Inequalities for Quadratic Forms of Negatively Dependent Subgaussian Random Variables Joural of Sceces Islamc epublc of Ira 6(: 63-67 (005 Uvers of ehra ISSN 06-04 hp://scecesuacr Some Probabl Iequales for Quadrac Forms of Negavel Depede Subgaussa adom Varables M Am A ozorga ad H Zare 3

More information

Optimal Eye Movement Strategies in Visual Search (Supplement)

Optimal Eye Movement Strategies in Visual Search (Supplement) Opmal Eye Moveme Sraeges Vsual Search (Suppleme) Jr Naemk ad Wlso S. Gesler Ceer for Percepual Sysems ad Deparme of Psychology, Uversy of exas a Aus, Aus X 787 Here we derve he deal searcher for he case

More information

Real-time Classification of Large Data Sets using Binary Knapsack

Real-time Classification of Large Data Sets using Binary Knapsack Real-me Classfcao of Large Daa Ses usg Bary Kapsack Reao Bru bru@ds.uroma. Uversy of Roma La Sapeza AIRO 004-35h ANNUAL CONFERENCE OF THE ITALIAN OPERATIONS RESEARCH Sepember 7-0, 004, Lecce, Ialy Oule

More information

IMPROVED PORTFOLIO OPTIMIZATION MODEL WITH TRANSACTION COST AND MINIMAL TRANSACTION LOTS

IMPROVED PORTFOLIO OPTIMIZATION MODEL WITH TRANSACTION COST AND MINIMAL TRANSACTION LOTS Vol.7 No.4 (200) p73-78 Joural of Maageme Scece & Sascal Decso IMPROVED PORTFOLIO OPTIMIZATION MODEL WITH TRANSACTION COST AND MINIMAL TRANSACTION LOTS TIANXIANG YAO AND ZAIWU GONG College of Ecoomcs &

More information

As evident from the full-sample-model, we continue to assume that individual errors are identically and

As evident from the full-sample-model, we continue to assume that individual errors are identically and Maxmum Lkelhood smao Greee Ch.4; App. R scrp modsa, modsb If we feel safe makg assumpos o he sascal dsrbuo of he error erm, Maxmum Lkelhood smao (ML) s a aracve alerave o Leas Squares for lear regresso

More information

Stabilization of LTI Switched Systems with Input Time Delay. Engineering Letters, 14:2, EL_14_2_14 (Advance online publication: 16 May 2007) Lin Lin

Stabilization of LTI Switched Systems with Input Time Delay. Engineering Letters, 14:2, EL_14_2_14 (Advance online publication: 16 May 2007) Lin Lin Egeerg Leers, 4:2, EL_4_2_4 (Advace ole publcao: 6 May 27) Sablzao of LTI Swched Sysems wh Ipu Tme Delay L L Absrac Ths paper deals wh sablzao of LTI swched sysems wh pu me delay. A descrpo of sysems sablzao

More information

COMPARISON OF ESTIMATORS OF PARAMETERS FOR THE RAYLEIGH DISTRIBUTION

COMPARISON OF ESTIMATORS OF PARAMETERS FOR THE RAYLEIGH DISTRIBUTION COMPARISON OF ESTIMATORS OF PARAMETERS FOR THE RAYLEIGH DISTRIBUTION Eldesoky E. Affy. Faculy of Eg. Shbee El kom Meoufa Uv. Key word : Raylegh dsrbuo, leas squares mehod, relave leas squares, leas absolue

More information

Fresnel Equations cont.

Fresnel Equations cont. Lecure 12 Chaper 4 Fresel quaos co. Toal eral refleco ad evaesce waves Opcal properes of meals Laer: Famlar aspecs of he eraco of lgh ad maer Fresel quaos r 2 Usg Sell s law, we ca re-wre: r s s r a a

More information

Supplement Material for Inverse Probability Weighted Estimation of Local Average Treatment Effects: A Higher Order MSE Expansion

Supplement Material for Inverse Probability Weighted Estimation of Local Average Treatment Effects: A Higher Order MSE Expansion Suppleme Maeral for Iverse Probably Weged Esmao of Local Average Treame Effecs: A Hger Order MSE Expaso Sepe G. Doald Deparme of Ecoomcs Uversy of Texas a Aus Yu-C Hsu Isue of Ecoomcs Academa Sca Rober

More information

Stability Criterion for BAM Neural Networks of Neutral- Type with Interval Time-Varying Delays

Stability Criterion for BAM Neural Networks of Neutral- Type with Interval Time-Varying Delays Avalable ole a www.scecedrec.com Proceda Egeerg 5 (0) 86 80 Advaced Corol Egeergad Iformao Scece Sably Crero for BAM Neural Neworks of Neural- ype wh Ierval me-varyg Delays Guoqua Lu a* Smo X. Yag ab a

More information

Least Squares Fitting (LSQF) with a complicated function Theexampleswehavelookedatsofarhavebeenlinearintheparameters

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

More information

The textbook expresses the stock price as the present discounted value of the dividend paid and the price of the stock next period.

The textbook expresses the stock price as the present discounted value of the dividend paid and the price of the stock next period. ublc Affars 974 Meze D. Ch Fall Socal Sceces 748 Uversy of Wscos-Madso Sock rces, News ad he Effce Markes Hypohess (rev d //) The rese Value Model Approach o Asse rcg The exbook expresses he sock prce

More information

-distributed random variables consisting of n samples each. Determine the asymptotic confidence intervals for

-distributed random variables consisting of n samples each. Determine the asymptotic confidence intervals for Assgme Sepha Brumme Ocober 8h, 003 9 h semeser, 70544 PREFACE I 004, I ed o sped wo semesers o a sudy abroad as a posgraduae exchage sude a he Uversy of Techology Sydey, Ausrala. Each opporuy o ehace my

More information

Solving Fuzzy Equations Using Neural Nets with a New Learning Algorithm

Solving Fuzzy Equations Using Neural Nets with a New Learning Algorithm Joural of Advaces Compuer Research Quarerly ISSN: 28-6148 Sar Brach, Islamc Azad Uversy, Sar, I.R.Ira (Vol. 3, No. 4, November 212), Pages: 33-45 www.jacr.ausar.ac.r Solvg Fuzzy Equaos Usg Neural Nes wh

More information

Quintic B-Spline Collocation for Solving Abel's Integral Equation

Quintic B-Spline Collocation for Solving Abel's Integral Equation Quc B-Sple Collocao for Solvg Abel's Iegral Euao Zara Mamood * Te Deparme of Maemacs, Abar Brac, Islamc Azad Uversy, Abar, Ira. * Correspodg auor. Tel.: +98963; emal: z_mamood_a@yaoo.com Mauscrp submed

More information

Chapter 8. Simple Linear Regression

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

More information

Convexity Preserving C 2 Rational Quadratic Trigonometric Spline

Convexity Preserving C 2 Rational Quadratic Trigonometric Spline Ieraoal Joural of Scefc a Researc Publcaos, Volume 3, Issue 3, Marc 3 ISSN 5-353 Covexy Preservg C Raoal Quarac Trgoomerc Sple Mrula Dube, Pree Twar Deparme of Maemacs a Compuer Scece, R. D. Uversy, Jabalpur,

More information

EE 6885 Statistical Pattern Recognition

EE 6885 Statistical Pattern Recognition EE 6885 Sascal Paer Recogo Fall 005 Prof. Shh-Fu Chag hp://.ee.columba.edu/~sfchag Lecure 8 (/8/05 8- Readg Feaure Dmeso Reduco PCA, ICA, LDA, Chaper 3.8, 0.3 ICA Tuoral: Fal Exam Aapo Hyväre ad Erkk Oja,

More information

Pricing Asian Options with Fourier Convolution

Pricing Asian Options with Fourier Convolution Prcg Asa Opos wh Fourer Covoluo Cheg-Hsug Shu Deparme of Compuer Scece ad Iformao Egeerg Naoal Tawa Uversy Coes. Iroduco. Backgroud 3. The Fourer Covoluo Mehod 3. Seward ad Hodges facorzao 3. Re-ceerg

More information

Orbital Euclidean stability of the solutions of impulsive equations on the impulsive moments

Orbital Euclidean stability of the solutions of impulsive equations on the impulsive moments Pure ad Appled Mahemacs Joural 25 4(: -8 Publshed ole Jauary 23 25 (hp://wwwscecepublshggroupcom/j/pamj do: 648/jpamj254 ISSN: 2326-979 (Pr ISSN: 2326-982 (Ole Orbal ucldea sably of he soluos of mpulsve

More information

The Signal, Variable System, and Transformation: A Personal Perspective

The Signal, Variable System, and Transformation: A Personal Perspective The Sgal Varable Syem ad Traformao: A Peroal Perpecve Sherv Erfa 35 Eex Hall Faculy of Egeerg Oule Of he Talk Iroduco Mahemacal Repreeao of yem Operaor Calculu Traformao Obervao O Laplace Traform SSB A

More information

Newton-Product Integration for a Stefan Problem with Kinetics

Newton-Product Integration for a Stefan Problem with Kinetics Joural of Sceces Islamc Republc of Ira (): 6 () versy of ehra ISS 64 hp://scecesuacr ewoproduc Iegrao for a Sefa Problem wh Kecs B BabayarRazlgh K Ivaz ad MR Mokharzadeh 3 Deparme of Mahemacs versy of

More information

EMD Based on Independent Component Analysis and Its Application in Machinery Fault Diagnosis

EMD Based on Independent Component Analysis and Its Application in Machinery Fault Diagnosis 30 JOURNAL OF COMPUTERS, VOL. 6, NO. 7, JULY 0 EMD Based o Idepede Compoe Aalyss ad Is Applcao Machery Faul Dagoss Fegl Wag * College of Mare Egeerg, Dala Marme Uversy, Dala, Cha Emal: wagflsky997@sa.com

More information

Solution set Stat 471/Spring 06. Homework 2

Solution set Stat 471/Spring 06. Homework 2 oluo se a 47/prg 06 Homework a Whe he upper ragular elemes are suppressed due o smmer b Le Y Y Y Y A weep o he frs colum o oba: A ˆ b chagg he oao eg ad ec YY weep o he secod colum o oba: Aˆ YY weep o

More information

Competitive Facility Location Problem with Demands Depending on the Facilities

Competitive Facility Location Problem with Demands Depending on the Facilities Aa Pacc Maageme Revew 4) 009) 5-5 Compeve Facl Locao Problem wh Demad Depedg o he Facle Shogo Shode a* Kuag-Yh Yeh b Hao-Chg Ha c a Facul of Bue Admrao Kobe Gau Uver Japa bc Urba Plag Deparme Naoal Cheg

More information

General Complex Fuzzy Transformation Semigroups in Automata

General Complex Fuzzy Transformation Semigroups in Automata Joural of Advaces Compuer Research Quarerly pissn: 345-606x eissn: 345-6078 Sar Brach Islamc Azad Uversy Sar IRIra Vol 7 No May 06 Pages: 7-37 wwwacrausaracr Geeral Complex uzzy Trasformao Semgroups Auomaa

More information

McMaster University. Advanced Optimization Laboratory. Authors: Dinghui Yang, Ming Lu, Rushan Wu and Jiming Peng

McMaster University. Advanced Optimization Laboratory. Authors: Dinghui Yang, Ming Lu, Rushan Wu and Jiming Peng McMaser versy Advaced Opmao Laboraory Tle: A Opmal Nearly-Aalyc Dscree Mehod for D Acousc ad Elasc Wave Equaos Auhors: Dghu Yag Mg Lu Rusha Wu ad Jmg Peg AdvOl-Repor No. 004/9 July 004 Hamlo Oaro Caada

More information

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

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

More information

Survival Prediction Based on Compound Covariate under Cox Proportional Hazard Models

Survival Prediction Based on Compound Covariate under Cox Proportional Hazard Models Ieraoal Bomerc Coferece 22/8/3, Kobe JAPAN Survval Predco Based o Compoud Covarae uder Co Proporoal Hazard Models PLoS ONE 7. do:.37/oural.poe.47627. hp://d.plos.org/.37/oural.poe.47627 Takesh Emura Graduae

More information

A Constitutive Model for Multi-Line Simulation of Granular Material Behavior Using Multi-Plane Pattern

A Constitutive Model for Multi-Line Simulation of Granular Material Behavior Using Multi-Plane Pattern Joural of Compuer Scece 5 (): 8-80, 009 ISSN 549-009 Scece Publcaos A Cosuve Model for Mul-Le Smulao of Graular Maeral Behavor Usg Mul-Plae Paer S.A. Sadread, A. Saed Darya ad M. Zae KN Toos Uversy of

More information

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

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

More information

Neural Network Global Sliding Mode PID Control for Robot Manipulators

Neural Network Global Sliding Mode PID Control for Robot Manipulators Neural Newor Global Sldg Mode PID Corol for Robo Mapulaors. C. Kuo, Member, IAENG ad Y. J. Huag, Member, IAENG Absrac hs paper preses a eural ewor global PID-sldg mode corol mehod for he racg corol of

More information

Regression Approach to Parameter Estimation of an Exponential Software Reliability Model

Regression Approach to Parameter Estimation of an Exponential Software Reliability Model Amerca Joural of Theorecal ad Appled Sascs 06; 5(3): 80-86 hp://www.scecepublshggroup.com/j/ajas do: 0.648/j.ajas.060503. ISSN: 36-8999 (Pr); ISSN: 36-9006 (Ole) Regresso Approach o Parameer Esmao of a

More information

CONTROLLABILITY OF A CLASS OF SINGULAR SYSTEMS

CONTROLLABILITY OF A CLASS OF SINGULAR SYSTEMS 44 Asa Joural o Corol Vol 8 No 4 pp 44-43 December 6 -re Paper- CONTROLLAILITY OF A CLASS OF SINGULAR SYSTEMS Guagmg Xe ad Log Wag ASTRACT I hs paper several dere coceps o corollably are vesgaed or a class

More information

Stability of Cohen-Grossberg Neural Networks with Impulsive and Mixed Time Delays

Stability of Cohen-Grossberg Neural Networks with Impulsive and Mixed Time Delays 94 IJCSNS Ieraoal Joural of Compuer Scece ad Newor Secury VOL.8 No.2 February 28 Sably of Cohe-Grossberg Neural Newors wh Impulsve ad Mxed Tme Delays Zheag Zhao Qau Sog Deparme of Mahemacs Huzhou Teachers

More information

The textbook expresses the stock price as the present discounted value of the dividend paid and the price of the stock next period.

The textbook expresses the stock price as the present discounted value of the dividend paid and the price of the stock next period. coomcs 435 Meze. Ch Fall 07 Socal Sceces 748 Uversy of Wscos-Madso Sock rces, News ad he ffce Markes Hypohess The rese Value Model Approach o Asse rcg The exbook expresses he sock prce as he prese dscoued

More information

Linear Regression Linear Regression with Shrinkage

Linear Regression Linear Regression with Shrinkage Lear Regresso Lear Regresso h Shrkage Iroduco Regresso meas predcg a couous (usuall scalar oupu from a vecor of couous pus (feaures x. Example: Predcg vehcle fuel effcec (mpg from 8 arbues: Lear Regresso

More information

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

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

More information

The Optimal Combination Forecasting Based on ARIMA,VAR and SSM

The Optimal Combination Forecasting Based on ARIMA,VAR and SSM Advaces Compuer, Sgals ad Sysems (206) : 3-7 Clausus Scefc Press, Caada The Opmal Combao Forecasg Based o ARIMA,VAR ad SSM Bebe Che,a, Mgya Jag,b* School of Iformao Scece ad Egeerg, Shadog Uversy, Ja,

More information

Brownian Motion and Stochastic Calculus. Brownian Motion and Stochastic Calculus

Brownian Motion and Stochastic Calculus. Brownian Motion and Stochastic Calculus Browa Moo Sochasc Calculus Xogzh Che Uversy of Hawa a Maoa earme of Mahemacs Seember, 8 Absrac Ths oe s abou oob decomoso he bascs of Suare egrable margales Coes oob-meyer ecomoso Suare Iegrable Margales

More information

Quantitative Portfolio Theory & Performance Analysis

Quantitative Portfolio Theory & Performance Analysis 550.447 Quaave Porfolo heory & Performace Aalyss Week February 4 203 Coceps. Assgme For February 4 (hs Week) ead: A&L Chaper Iroduco & Chaper (PF Maageme Evrome) Chaper 2 ( Coceps) Seco (Basc eur Calculaos)

More information

Research on portfolio model based on information entropy theory

Research on portfolio model based on information entropy theory Avalable ole www.jocpr.com Joural of Chemcal ad Pharmaceucal esearch, 204, 6(6):286-290 esearch Arcle ISSN : 0975-7384 CODEN(USA) : JCPC5 esearch o porfolo model based o formao eropy heory Zhag Jusha,

More information

Continuous Indexed Variable Systems

Continuous Indexed Variable Systems Ieraoal Joural o Compuaoal cece ad Mahemacs. IN 0974-389 Volume 3, Number 4 (20), pp. 40-409 Ieraoal Research Publcao House hp://www.rphouse.com Couous Idexed Varable ysems. Pouhassa ad F. Mohammad ghjeh

More information

Space-Time Transformation in Flux-form Semi-Lagrangian Schemes

Space-Time Transformation in Flux-form Semi-Lagrangian Schemes Terr. Amos. Ocea. Sc., Vol., No., 7-6, ebruary 00 do: 0.339/TAO.009.05.5.0(IWNOP) Space-Tme Trasformao lux-form Sem-Lagraga Schemes Peer C. Chu * ad Chewu a Naval Ocea Aalyss ad Predco Laboraory, eparme

More information

Complementary Tree Paired Domination in Graphs

Complementary Tree Paired Domination in Graphs IOSR Joural of Mahemacs (IOSR-JM) e-issn: 2278-5728, p-issn: 239-765X Volume 2, Issue 6 Ver II (Nov - Dec206), PP 26-3 wwwosrjouralsorg Complemeary Tree Pared Domao Graphs A Meeaksh, J Baskar Babujee 2

More information

Bianchi Type II Stiff Fluid Tilted Cosmological Model in General Relativity

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

More information

A modified virtual multi-dimensional internal bonds model for geologic materials

A modified virtual multi-dimensional internal bonds model for geologic materials 47 ISSN 19107 MEHANIKA 015 Volume 1(5): 4751 A modfed vrual mul-dmesoal eral bods model for geologc maerals JFu Ke* AXag Wu** *Uversy of Scece ad Techology Bejg Bejg 10008 ha E-mal: kejfu@homalcom **Uversy

More information

Fault Tolerant Computing. Fault Tolerant Computing CS 530 Probabilistic methods: overview

Fault Tolerant Computing. Fault Tolerant Computing CS 530 Probabilistic methods: overview Probably 1/19/ CS 53 Probablsc mehods: overvew Yashwa K. Malaya Colorado Sae Uversy 1 Probablsc Mehods: Overvew Cocree umbers presece of uceray Probably Dsjo eves Sascal depedece Radom varables ad dsrbuos

More information

Average Consensus in Networks of Multi-Agent with Multiple Time-Varying Delays

Average Consensus in Networks of Multi-Agent with Multiple Time-Varying Delays I. J. Commucaos ewor ad Sysem Sceces 3 96-3 do:.436/jcs..38 Publshed Ole February (hp://www.scrp.org/joural/jcs/). Average Cosesus ewors of Mul-Age wh Mulple me-varyg Delays echeg ZHAG Hu YU Isue of olear

More information

Comparison of the Bayesian and Maximum Likelihood Estimation for Weibull Distribution

Comparison of the Bayesian and Maximum Likelihood Estimation for Weibull Distribution Joural of Mahemacs ad Sascs 6 (2): 1-14, 21 ISSN 1549-3644 21 Scece Publcaos Comarso of he Bayesa ad Maxmum Lkelhood Esmao for Webull Dsrbuo Al Omar Mohammed Ahmed, Hadeel Salm Al-Kuub ad Noor Akma Ibrahm

More information

Equivalent Finite Element Formulations for the Calculation of Eigenvalues Using Higher-Order Polynomials

Equivalent Finite Element Formulations for the Calculation of Eigenvalues Using Higher-Order Polynomials Appled Mahemacs: ; (: 3-3 DOI:. 593/.am.. Equvale Fe Eleme Formulaos for he Calculao of Egevalues Usg Hgher-Order Polyomals C. G. Provads Deparme of Mechacal Egeerg, Naoal echcal Uversy of Ahes, Ahes,

More information

Integral Φ0-Stability of Impulsive Differential Equations

Integral Φ0-Stability of Impulsive Differential Equations Ope Joural of Appled Sceces, 5, 5, 65-66 Publsed Ole Ocober 5 ScRes p://wwwscrporg/joural/ojapps p://ddoorg/46/ojapps5564 Iegral Φ-Sably of Impulsve Dffereal Equaos Aju Sood, Sajay K Srvasava Appled Sceces

More information

Probability Bracket Notation and Probability Modeling. Xing M. Wang Sherman Visual Lab, Sunnyvale, CA 94087, USA. Abstract

Probability Bracket Notation and Probability Modeling. Xing M. Wang Sherman Visual Lab, Sunnyvale, CA 94087, USA. Abstract Probably Bracke Noao ad Probably Modelg Xg M. Wag Sherma Vsual Lab, Suyvale, CA 94087, USA Absrac Ispred by he Drac oao, a ew se of symbols, he Probably Bracke Noao (PBN) s proposed for probably modelg.

More information

Efficient Estimators for Population Variance using Auxiliary Information

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

More information