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

Size: px
Start display at page:

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

Transcription

1 Terr. Amos. Ocea. Sc., Vol., No., 7-6, ebruary 00 do: 0.339/TAO (IWNOP) Space-Tme Trasformao lux-form Sem-Lagraga Schemes Peer C. Chu * ad Chewu a Naval Ocea Aalyss ad Predco Laboraory, eparme of Oceaography, Naval Posgraduae School, Moerey, CA 93943, USA Receved Jue 008, acceped 5 May 009 Absrac Wh a fe volume approach, a flux-form sem-lagraga (TSL) scheme wh space-me rasformao was developed o provde sable ad accurae algorhm solvg he adveco-dffuso equao. ffere from he exsg fluxform sem-lagraga schemes, he emporal egrao of he flux from he prese o he ex me sep s rasformed o a spaal egrao of he flux a he sde of a grd cell (space) for he prese me sep usg he characersc-le cocep. The TSL scheme o oly eeps he good feaures of he sem-lagraga schemes (o Coura umber lmao), bu also has hgher accuracy (of a secod order boh me ad space). The capably of he TSL scheme s demosraed by he smulao of he equaoral Rossby-solo propagao. Compuaoal sably ad hgh accuracy maes hs scheme useful ocea modelg, compuaoal flud dyamcs, ad umercal weaher predco. Key words: TSL scheme, lux-form sem-lagraga scheme, Characersc le, Adveco-dffuso equao, e volume, Coservave fe dfferece, Equaoral Rossby solo. Cao: Chu, P. C. ad C. a, 00: Space-me rasformao flux-form sem-lagraga schemes. Terr. Amos. Ocea. Sc.,, 7-6, do: 0.339/ TAO (IWNOP). Iroduco rom a physcal po of vew, adveco of a passve racer s he smple raso of a quay whou dffuso ad dsperso. Numercal approaches amospherc ad oceac modelg evably roduce dffuso (or dsspao) ad dsperso o he approxmae soluo. The umercal dffuso ad dsperso are ales o he process ha s beg modeled (Chu ad a 998, 999). As appled o a cosue adveco problem, hese umercal arfacs mafes hemselves as ophyscal mxg by umercal dffuso, ophyscal hghs ad lows he cosue feld caused by dsperso, ad ophyscal racer specra caused by rappg opropagag small spaal scales (Rood 987). or example, he commoly used upwd scheme s codoally sable (wh he Coura umber beg much smaller ha ) ad some arfcal vscosy s roduced. Hece, less he umercal dffuso ad dsperso errors equaes o beer model performace. May umercal algorhms have bee proposed o reduce umercal dffuso ad dsperso errors ad o eep * Correspodg auhor E-mal: pcchu@ps.edu he umercal sably. The flux-form sem-lagraga scheme s amog hem. Usg he flux-form sem-lagraga schemes, arfcal vscosy s reduced ad sably s ep whou he lmao of a Coura umber (Casull 990, 999). I hs sudy, we use a fe volume approach o develop me-space rasformed flux-form sem-lagraga (TSL) scheme. Ths scheme has a explc form ad much less dffuso ad dsperso errors. The sably ad accuracy of umercal schemes for ocea models are usually verfed usg he propagao of a Rossby solo o a equaoral bea-plae. I prcple, he solo propagaes o he wes a a fxed phase speed, whou a chage of shape. Sce he uform propagao ad shape preservao of he solo are acheved hrough a delcae balace bewee lear wave dyamcs ad oleary. I oher words, he Rossby solo s o-dffusve ad o-dspersve (Boyd 980), whch maes a perfec es case for verfcao of umercal schemes ocea models sce ay dffuso ad dsperso he umercal soluo of he Rossby solo are compuaoal errors. Ieresed readers are referred o he webse: hp://mare. rugers.edu/po/dex.php?modeles-problems.

2 Repor ocumeao Page orm Approved OMB No Publc reporg burde for he colleco of formao s esmaed o average hour per respose, cludg he me for revewg srucos, searchg exsg daa sources, gaherg ad maag he daa eeded, ad compleg ad revewg he colleco of formao. Sed commes regardg hs burde esmae or ay oher aspec of hs colleco of formao, cludg suggesos for reducg hs burde, o Washgo Headquarers Servces, recorae for Iformao Operaos ad Repors, 5 Jefferso avs Hghway, Sue 04, Arlgo VA Respodes should be aware ha owhsadg ay oher provso of law, o perso shall be subjec o a pealy for falg o comply wh a colleco of formao f does o dsplay a currely vald OMB corol umber.. REPORT ATE JUN 008. REPORT TYPE 3. ATES COVERE o TITLE AN SUBTITLE Space-Tme Trasformao lux-form Sem-Lagraga Schemes 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e. TASK NUMBER 5f. WORK UNIT NUMBER 7. PERORMING ORGANIZATION NAME(S) AN ARESS(ES) Naval Posgraduae School,eparme of Oceaography,Moerey,CA, PERORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AN ARESS(ES) 0. SPONSOR/MONITOR S ACRONYM(S). ISTRIBUTION/AVAILABILITY STATEMENT Approved for publc release; dsrbuo ulmed 3. SUPPLEMENTARY NOTES. SPONSOR/MONITOR S REPORT NUMBER(S) 4. ABSTRACT Wh a fe volume approach, a flux-form sem-lagraga (TSL) scheme wh space-me rasformao was developed o provde sable ad accurae algorhm solvg he adveco-dffuso equao. ffere from he exsg flux-form sem-lagraga schemes, he emporal egrao of he flux from he prese o he ex me sep s rasformed o a spaal egrao of he flux a he sde of a grd cell (space) for he prese me sep usg he characersc-le cocep. The TSL scheme o oly eeps he good feaures of he sem-lagraga schemes (o Coura umber lmao), bu also has hgher accuracy (of a secod order boh me ad space). The capably of he TSL scheme s demosraed by he smulao of he equaoral Rossby-solo propagao. Compuaoal sably ad hgh accuracy maes hs scheme useful ocea modelg, compuaoal flud dyamcs, ad umercal weaher predco. 5. SUBJECT TERMS 6. SECURITY CLASSIICATION O: 7. LIMITATION O ABSTRACT a. REPORT uclassfed b. ABSTRACT uclassfed c. THIS PAGE uclassfed Same as Repor (SAR) 8. NUMBER O PAGES 0 9a. NAME O RESPONSIBLE PERSON Sadard orm 98 (Rev. 8-98) Prescrbed by ANSI Sd Z39-8

3 8 Peer C. Chu & Chewu a To show he beef of usg he TSL scheme, we frs show sably ad large dffuso ad dsperso errors umercal soluo of he Rossby solo usg he exsg schemes such as he flux-form upwd, flux-form ceral, Lax-Wedroff, ad flux-form sem-lagraga schemes. The, we wll descrbe he procedures of he TSL scheme developme ad verfcao. The res of paper s orgazed as follows. Seco descrbes he equaoral Rossby solo ad s usefuless for a ocea model verfcao. Seco 3 shows he falure of he hree exsg schemes (upwd, ceral, Lax-Wedroff, sem-largaga) smulag he equaoral Rossby solo. Seco 4 roduces he TSL scheme. Seco 5 derves he aalycal form of he amplfcao facor of he TSL-scheme. Seco 6 shows he capably of he TSL-scheme smulag he equaoral Rossby solo. Seco 7 preses our coclusos.. Rossby Solo Le X be he agular frequecy of earh s roao ad R be he earh radus, ad le (x, y) be he spaal coordaes wh u vecors (, j) ad be he me. Cosder a sgle layer of homogeeous ocea layer wh deph of H. Lamb s parameer s defed by E 4 X gh R () where g s he gravaoal accelerao. The legh ad me are o-dmesoalzed by 4 / R E L 4 /, T () E X or he mea ocea deph H 4 m, he earh radus R 6370 m, ad X π / (86400 s), he legh ad me scale are L 543 m, T.39 hr. Le (x, y) be he o-dmesoal Caresa coordaes, (u, v) be he o-dmesoal velocy compoes he merdoal ad laudal drecos, ad φ be he o-dmesoal surface elevao. Afer defg s/x - c (3) ad rasformg he olear shallow waer wave equaos o a frame of referece movg wh he lear wave, he flow varables (u, v, φ) for he mode- wave ca be represeed by (Boyd 980) (6y - 9) y usy (,,) 4 h( s, )expc- m (4a) h(,) s y vsy (,,) y exp c- m s (4b) ( 6y 3) y z(, sy,) 4 h( s, ) exp c- m (4c) ad he varable h ( s, ) sasfes 3 h h h -fh - f 3 0 s s f. 5366, f (5) whch s he Koreweg-de Vres (KV) equao wh he exac soluo, h( s, ) Asech 6 B( s B A 0. 77B, B , (6) Subsuo of he exac soluo Eq. (6) o he hrd erm he lefhad sde of Eq. (5) leads o h h - f h S (7) s 3 h S f 3 (8) s where S s reaed as a source/s erm. Evdely Eq. (7) has he aalycal soluo Eq. (6). Sce he aalycal soluo Eq. (6) exss, he Rossby solo Eq. (7) s a perfec es case for verfyg he sably ad accuracy of umercal schemes sce he dffuso erm has bee chaged o he gve source/s erm. To do so, he flud s assumed o occupy he equaoral rego surroudg he earh. The zoal dreco s dscrezed o 0 cells (.e., resoluo a 3 logude). The creme Δs s gve by rr s 0L (9) The depede varables (s, ) are dscrezed by s s - Δs, - Δ,,,...;,,..., wh Δ he me sep. The depede varable (η) a (s, ) s represeed by h / h( s, ). 3. Several Exsg Schemes Equao (7) ca be dscrezed usg he flux-form upwd scheme,

4 Space-Tme Trasformao Schemes 9 f h h 6 ( h ) -(- Q (0) x he flux-form ceral scheme, f h h 6 ( h /) -( h - Q () x he Lax-Wedroff scheme, C ( C) ( ) ( ) Q h h - h - h h - h h - - () ad he sem-lagraga scheme, f * * h h ^h / - h- / h Q (3) x wh Af 4 Q / # Ssd (, ) sech ( Y) 3sec h ( Y) 6 (4a) f h C /, Y / B( s B ) (4b) s * h / ( /) ( /) / 6 h h / / h / - C (4c) / I order o compare he dfferece bewee umercal ad exac soluos (a wesward propagag Rossby solo), he zoal equaoral srp s assumed o be fely log. Whe he Rossby solo ravels over 0 cells, goes aroud he earh oce mes (called cycles). The exac soluo a 0 s ae as he al codo, h (, s 0) Asec h ( Bs) (5) wh s 0 deog 0 logude. Three dfferece Eqs. (0) - () are solved umercally from he al codo Eq. (5) represeg he upwd, ceral, ad Lax-Wedroff schemes (Lax ad Wedroff 960) wh varyg Δ a each me sep for a gve Coura Cs umber (C 0.75), /. Seleco of C 0.75 f max_ h s due o he fac ha he proposed TSL scheme wll be reduced o he Lax-Wedroff scheme for C 0.5 [see Eq. (36). Afer obag he umercal soluo, h ( x, ), subsug o Eq. (4c) yelds φ(s, y j, ). The accuracy of he schemes ca be verfed hrough her capably predcg he wesward propagao of he Rossby solo. To do so, he surface elevao φ(s, y j, ) s ploed wh coour values of.3, 4.6, 6.4, 8.53, 0.66,.79, 4.93, ad 7.06 cm. All he umercal schemes grealy dsor he Rossby solo (g. ). Whe he rao of he roo-mea square error versus he roo-mea of he aalycal soluo s greaer ha 00%, he umercal soluo s cosdered dvergece. gure shows ha he umercal soluo dverges a 7 45 W usg he flux-form ceral scheme, a W usg he Lax-Wedroff scheme, ad a 30 W afer oe cycle aroud he earh usg he flux-form upwd scheme. Comparg gs.b - d o g. a, he umercal soluos are oally dffere from he aalycal soluo. 4. TSL-Scheme 4. Sem-Lagraga Mehod Cosder he adveco of a passve scalar φ(x, ) by he velocy u(x, ). The Eulera formulao s gve by z z / u $ dz S (6) where x s he poso vecor, / deoes he maeral dervave, whle he Lagraga couerpar s dz p dx p d S, d ux ( p,) (7) where he subscrp p shows he flud parcle Lagraga sese. Alhough Eqs. (6) ad (7) carry he same physcal formao, her dscrezao ad umercal mplemeao s dffere: Eq. (6) s dscrezed o a Eulera grd wh a fe umber of grd pos ad he me-advaced, whle Eq. (7) s egraed for a fe umber of flud parcles. Sem-Lagraga mehods combe boh Eulera ad Lagraga pos of vew; he scalar feld s dscrezed o a Eulera grd, bu s advaced me usg Eq. (7). The ey eleme accomplshg hs s he defcao of each grd po x as he arrval po, for sace, a, of a parcle orgag from x * a me. The algorhm has hree seps: (a) The parcle assocaed wh each grd po x a me s raced bac o s locao x * a me, x * x- # u() x dx (8) (b) The scalar value a (x *, ) s obaed by erpolag he ow values a eghborg grd pos, * z( x, ) P6 z( x (9)

5 0 Peer C. Chu & Chewu a where P s ay erpolao operaor ad ( x ) deoes he se of erpolao pos assocaed wh x *, for example, he odes of he cell coag x * ; (c) ally, he scalar s updaed, z( x, ) z( x *, ) Q (0) Thus, he ma ssues of he sem-lagraga mehod are he bacward egrao sep (a) ad he erpolao sep (b). 4. lux orm Equao (6) ca be rewre he flux form wh cluso of dffuso, z 4$ S, - uz l 4z () where ĸ s he dffuso coeffce. Le he depede varable φ(x, ) be defed o he space X, 0 x L x, 0 y L y, 0 z L z. wh (L x, L y, L z ) he leghs (x, y, z) drecos. Le L x L y Lz x N, y N, z x y N be he uform spaal cremes wh (N x, N y, N z ) he grd umbers. Iegra- z g Eq. () for he fe volume, X j [x - / x x /, x y j - / y y j /, z - / z z /, x ± / / x ±, yj ± / y z / y j ±, z ± / / z ±, from o, we oba he fe dfferece equao of he flux-averaged raspor, (a) (b) (c) (d) g.. Surface elevao φ(s, y, ) of he Rossby solos obaed from a (a) exac soluo, ad umercal egrao wh C 0.75 usg he (b) flux-form upwd scheme, (c) flux-form ceral scheme, ad (d) Lax-Wedroff scheme. Noe ha he umercal soluo dverges a 30 W afer oe cycle usg he flux-form upwd scheme, a 7 45 W usg he flux-form ceral scheme, ad a W usg he Lax-Wedroff scheme.

6 Space-Tme Trasformao Schemes zu (, ) (, ) (, ) - zu j / j /, j, G -, j /, - G x y, j,,,,, (, ) -, j - /, (, ) ( ) H / H,, j, -, j, - / S, j, () z where (, G, H) are compoes of he vecor, ad (, ) # d (3) represes he emporal average (from o ). The lde represes he volume average over X, zu j ### zdxdydz (4a) x y z Xj The ha represes he combed volume ( X j) ad emporal average (from o ), S ### j x y z j # S dxdydzd (4b) Xj or he fe volume X j, he flux a x x - / ad s calculaed by - /, j, z y / j / z # # cl -uzm y z z - / yj - / x x x dydz (5) - / To solve Eq. () umercally, we eed o compue he emporally egraed fluxes, (, ) /, (, ) /, G (, ) (, ), j, -, j,, j /,, G, j - /,, (, ) (, ) H, j, /, H, j, - /. If hese fluxes are compued usg he sem-lagraga mehod, s called he flux-form sem- Lagraga scheme (Casull 990, 999; L ad Rood 996). 4.3 Trasformao of Temporal Iegrao o Spaal Mea or smplcy ad o loss of geeraly, we cosder oe dmesoal problem of Eq. () whou source/s erm (.e., S j 0), I he exsg flux-form sem-lagraga schemes, he (, ) (, ) emporally egraed flux - / [smlar for / s gve by he mea value a he wo me seps ad (e.g., Casull 990; Taguay e al. 990), (, ) - / ^ - / - / h (8a) Usg he characersc-le cocep, he flux a me sep ad locao x - / ca be rasformed o he flux a me sep ad locao x - / - C (g. ), -- C (8b) - / / Subsuo of Eq. (8b) o Eq. (8a) gves (, ) - / ^ - / - / - Ch (8c), wh he mea flux - / sep. Here ( ) deermed a he curre me u C (9) x s he Coura umber. Here, we propose a ew mehod o compue he emporally averaged flux - / wh he rasformao o (, ) spaal averaged flux, x - / / x ( /, d ) x (, ) dx # C # (30) x - / -c (, ) - / - Subsuo of Eq. (9) o Eq. (30) leads o (, ) - / Z - / - / - C f C # m - / d ^- - - h.[ d / ^ - / -h dm ^-m - / - Ch f C \ (3) (, ), zu - zu / - - x ( ) / rom he sem-lagraga cosderao, we have (, ) (, ) * / / z u ( x, ) z u - - ( x, ) x (6) (7) where m - m : C-, d / C, d C, dm -d / - / d (3) The brace [ represes he roud-off eger. Smlarly, he emporally averaged flux a he rgh boudary (x x / )

7 Peer C. Chu & Chewu a Z.[ d \ (, ) / / ^ / / / C f C # m - / d ^- - h h dm ^ - m / -Ch f C - (33) (, ) (, ) The emporally averaged fluxes - / ad / (from o ) are rasformed o he spaally averaged fluxes over mulple grds a me sep wh weghs of δ /, δ,..., δ m. If he characersc le a s beyod he boudary, he (, ) boudary codo ca be used o calculae - / (g. 3), g.. Temporally varyg flux a he boudary x - / from o s rasformed o spaally varyg flux a from x - / - C o x - / usg he characersc-le cocep. (, ) 3 / ^ 3/ h bc - l^ b h C (34) where b s he boudary value bewee ad, ad s erpolaed by C b - l C (35) b Subsuo of Eqs. (3) ad (33) o he dfferece Eq. (6) leads o z Z C C - ^z -z - h ^z - z z -h, C # - m m 4 ^z - z -h- ^z z - -z - -z - - h z [ -b - l m m m m z - -z - - z z - - ^ h- ^ h 8 ^z - z z - \ h, C (36) whch s called he Trasformed lux-formed Sem-Lagraga (TSL) scheme for he adveco-dffuso Eq. (). Here, C - m - /. The major dfferece bewee he exsg flux-form sem-lagraga scheme ad he TSL scheme comes from he dffere calculao of he emporally averaged flux (, ) - / : Eq. (8c) for he exsg fluxform sem-lagraga scheme ad Eq. (3) for he TSL scheme. or C, he TSL scheme s he same as he Lax- Wedroff scheme. Compared o he ceral dfferece (CE), he TSL-scheme has a exra posve erm, C TSL-CE ( z - z z - ) (37) for C /. Ths erm ca be regarded as he umercal (posve) dffuso whch leads o compuaoal sably. g. 3. Same as g. excep a he lef boudary of he egrao doma. ffere schemes have dffere algorhms o compue he (, ) (, ) emporally averaged fluxes - / ad / (from o ). The TSL scheme has secod order accuracy boh me ad space. 5. Sably of he TSL Scheme The sably of umercal schemes s a mpora ssue solvg he adveco Eq. (6). I seco 3, we showed he sably of he exsg schemes (upwd, ceral, ad Lax-Wedroff). To deerme he sably of he TSL scheme Eq. (36), he ourer seres expaso s used. ecay or growh of a amplfcao facor dcaes wheher or o he umercal algorhm s sable (vo Neuma ad Rchmyer 950). Assumg ha a ay me sep, he compue soluo z s he sum of he exac soluo ( ex) z ad error f, z z f (38) ( ex) ad subsug Eq. (38) o Eq. (36), we oba f Z C C - ^ f -f - h ^ f - f f -h, C # - ^ m m 4 f - f -h- ^ f f - -f - -f - - h f [ -b - l m m m m f - -f - - f f - - ^ h- ^ h \ ^ 8 f - f f -h, C (39)

8 Space-Tme Trasformao Schemes 3 The fe mesh fuco, f, ca be decomposed o a ourer seres, Nx f / aj exp( I), jr Nx (40) j-nx wh I / -, (a j, θ) beg he amplude ad phase agle of he jh harmoc. Subsug Eq. (40) o Eq. (39) yelds a g(, Ca ) where (4) Z -C ( -cos ) - IC s, C # 4 ( - cos) b - l cos( m) b - l cos[( m -) g(, C) [ cos[( m -) - I ' b - l s( m) b - l s[( m -) s[( m -) 0, C \ (4) s called he amplfcao facor, whose magude s gve by g(, C) Z [ -C ( - cos) C s, C # 6 ( - cos ) b - l 4 b - l 4 ( -cos ) ' b - l cos( m) [ b - l cos[( m -) cos[( m -) 0 ( - ) b - l cos b - l \ cos( ), C (43) The TSL-scheme s compuaoally sable f g(, C) # ad compuaoally usable f g(, C). gure 4 shows ha g(, C) # for all θ ad C (larger ha 0), whch mples ha he TSL-scheme Eq. (36) s sable for all he C values (whou Coura umber resrco). 6. Smulag he Rossby Solo Usg he TSL Scheme The TSL-scheme Eq. (36) s oly for a spaally vara ad emporally vara u. Whe u [or -f η Eq. (7) a x - / vares wh me from o, cocep of vara characersc les ca be used o deerme u(x - /, ) wh sub me-seps (δ /, δ,..., δ m ) (bewee ad ) from u(x, ) a grd pos (x -,..., x - m, x * ), ad for u > 0 he me from he lef eghborg grd x - [ o x - s gve by (g. 5), x - dx x d # ux (, ) u x- [ # dz - g - z C l( - g- ) g C g- g- ( 3...), 0. 5,,,..., m (44) where - u - u ( ) x x - x ( ), g u, - C u x (45) The parameer C - s he Coura umber for sub me seps. A formula smlar o Eq. (44) ca be obaed for u < 0 (usg he rgh eghborg grd). The emporally averaged (, ) fluxes from o ca be calculaed by {ag - / [see Eq. (3) as he example}... d - m -m -m -m- dm - d m (46) (, ) - / / : d / Equao (7) for he Rossby solo s dscrezed usg he flux form, h - h - s (, ) (, ) / - / S (47) where S s he emporally-spaally averaged source erm / S / Ssdsd (,) # # (48) s - / s s wh S(s, ) gve by Eq. (8). The dfferece, Eq. (47), s solved umercally from he al codo Eq. (5) usg he TSL-scheme. To compare wh he exsg flux-form sem-lagraga scheme, he Coura umber s se o.5.

9 4 Peer C. Chu & Chewu a g. 4. epedece of he amplfcao facor g(, C) of he TSL scheme o θ ad C. Afer he umercal soluo η(x, ) s obaed, subsug o Eq. (4c) yelds φ(s, y, ) as show g. 6. Noe ha he flux-form sem-lagraga scheme s hghly dsored (g. 6) wh he umercal soluo dvergg a W, whch may be caused by he error accumulao. However, he TSL-scheme s que sable ad accurae. Afer propagag wesward aroud he earh he umercal Rossby solo (usg he TSL scheme) appears o be almos o-dffusve ad o-dspersve. To show he qualy of he TSL-scheme, he dfferece Eq. (47) s egraed for C.5 for a log me perod correspodg o he Rossby solo propagaes wesward aroud he earh 5 mes. The soluo φ(s, y, ) s sable all he me (g. 7). The relave roo-mea-square error (rrmse), rrmse() g. 5. Same as g. excep for emporally varyg u. Ns Ny ( um) ( ex) NN//7 z ( s, yj,) - z ( s, yj,) A s y j max z ( ex) ( s, y,) j (49) s calculaed o llusrae he accuracy of he TSL scheme. Table shows RRMSE a he ed of frs fve cycles aroud he earh. The error vares from.66% for he frs cycle o 3.53% for he ffh cycle. 7. Coclusos () Ths sudy shows ha he TSL scheme s a promsg sable ad accurae mehod for solvg he advecodffuso equao. The ourer aalyss shows ha he TSL scheme has secod-order accuracy me ad space. Ths scheme reas he good feaures of sem- Lagraga schemes (o Coura umber lmao) wh hgher accuracy. Compuaoal sably ad hgher accuracy ha he wdely used schemes (ceral, upwd, Lax-Wedroff, sem-lagraga) maes hs echque useful ocea modelg, compuaoal flud dyamcs, ad umercal weaher predco. () Several major feaures dsgush he TSL scheme from exsg schemes, boh Eulera ad sem-lagraga. rs, he flux () a he sde of each grd cell s compued o from a sgle me sep (prese or ex) bu from a emporal egrao from he prese me sep o he ex me sep. Secod, hs emporal egrao s rasformed o a spaal egrao a he prese me sep usg he characersc le mehod. (3) The equaoral Rossby solo s used o es he capably of he TSL scheme sce has exac soluo. The equao s solved umercally from he solo ally locaed a he equaor ad 0 logude wh a overall Coura umber of The upwd, ceral, ad Lax-Wedroff schemes grealy dsor he Rossby solo ad dverge as propagaes. However, he TSL scheme does o dsor he Rossby solo ad coverges as propagaes may cycles aroud he earh. Wh a overall Coura umber of.5, he umercal Rossby solo ca sll propagae may cycles aroud he earh usg he TSL scheme, bu dverges a W usg he flux-form sem-lagraga scheme. (4) Applcao of he TSL scheme o he amospherc ad

10 Space-Tme Trasformao Schemes 5 (a) (b) (c) g. 6. Surface elevao φ(s, y, ) of he Rossby solo obaed from (a) exac soluo, ad umercal egrao wh C.5 usg (b) TSLscheme, ad (c) flux-form sem-lagraga scheme. The soluos φ(s, y, ) are ploed a four me saces for he Rossby solo (exac soluo) wesward propagag 90, 80, 70, ad 360 (reur o he al locao). g. 7. Surface elevao φ(s, y, ) of he Rossby solo afer - 5 cycles aroud he earh obaed from umercal egrao wh C.5 usg he TSL scheme.

11 6 Peer C. Chu & Chewu a Table. RRMSE of he surface elevao predced usg he TSLscheme afer he frs fve cycles aroud he earh. Cycle RRMSE (%) oceac models eeds more research. Ths s because ha he hghly accurae reame of he source erm eabled good performace of he TSL scheme. However, hs s a very specal case because he aalycal soluo of S (source erm) s ow for hs sysem. I ocea modelg, compuaoal flud dyamcs, or umercal weaher predco, source erm aalycal soluos are usually uow ad hus several erao processes wll be requred for he deparure/arrval po esmao as well as he source erm esmao (for spaal ad emporal averagg), whch causes he loss of effcecy ad accuracy. (5) The TSL scheme was developed o he bass of a fe volume approach. I s relavely easy o exed oe-dmesoal space-me rasformao Eqs. (8b) ad (8c) o hree-dmesoal rasformaos. The space egrao of he flux s coduced over he wodmesoal surface of he fe volume, ad he me egrao s for ha volume (see seco 4.). Ths wll be repored a separae paper he ear fuure. Acowledgemes The Offce of Naval Research, he Naval Oceaographc Offce, ad he Naval Posgraduae School suppored hs sudy. Refereces Boyd, J. P., 980: Equaoral solary waves. Par-: Rossby solos. J. Phys. Oceaogr., 0, , do: 0. 75/ (980)00<699:ESWPIR>.0.CO;. [L Casull, V., 990: Sem-mplc dfferece mehods for he wo-dmesoal shallow waer equaos. J. Compu. Phys., 86, 56-74, do: 0.06/00-999(90)9009-E. [L Casull, V., 999: A sem-mplc fe dfferece mehod for o-hydrosac, free surface flows. I. J. Numer. Mehods luds, 30, , do: 0.00/(SICI) ( )30:4<45::AI-L847>3.0.CO; -. [L Chu, P. C. ad C. W. a, 998: A hree-po combed compac dfferece scheme. J. Compu. Phys., 40, , do: 0.006/jcph [L Chu, P. C. ad C. W. a, 999: A hree-po o-uform combed compac dfferece scheme. J. Compu. Phys., 48, , do: 0.006/jcph [L Lax, P. ad B. Wedroff, 960: Sysems of coservao laws. Commu. Pure Appl. Mah., 3, 7-37, do: 0.00/cpa [L L S. ad R. B. Rood, 996: Muldmesoal flux-form sem-lagraga rasporao schemes. Mo. Weaher Rev., 4, , do: 0.75/ (99 6)4<046:MSLT>.0.CO;. [L Rood, R. B., 987: Numercal adveco algorhms ad her role amospherc raspor ad chemsry models. Rev. Geophys., 5, 7-00, do: 0.09/RG0500p [L Taguay, M., A. Rober, ad R. Laprse, 990: A semmplc sem-lagraga fully compressble regoal forecas model. Mo. Weaher Rev., 8, , do: 0.75/ (990)8<970:ASISL>.0. CO;. [L vo Neuma, J. ad R.. Rchmyer, 950: A mehod for he umercal calculao of hydrodyamc shocs. J. Appl. Phys.,, 3, do:0.063/ [L

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

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

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

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

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

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

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

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

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

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

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

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 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

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 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

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

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

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

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

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

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

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

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

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

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

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

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

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

Conservative and Easily Implemented Finite Volume Semi-Lagrangian WENO Methods for 1D and 2D Hyperbolic Conservation Laws Joural of Appled Mahemacs ad Physcs, 07, 5, 59-8 hp://www.scrp.org/oural/amp ISSN Ole: 37-4379 ISSN Pr: 37-435 Coservave ad Easly Implemeed Fe Volume Sem-Lagraga WENO Mehods for D ad D Hyperbolc Coservao

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

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

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

More information

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

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

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

(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

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

Transformed Flux-form Semi-Lagrangian Scheme

Transformed Flux-form Semi-Lagrangian Scheme Trasformed Flux-form Sem-Lagraga Scheme Peter C. Chu ad Chewu Fa Naval Ocea Aalyss ad Predcto Laboratory Departmet of Oceaography, Naval Postgraduate School Moterey, CA 93943, USA Report Documetato Page

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

SYRIAN SEISMIC CODE :

SYRIAN SEISMIC CODE : SYRIAN SEISMIC CODE 2004 : Two sac mehods have bee ssued Syra buldg code 2004 o calculae he laeral sesmc forces he buldg. The Frs Sac Mehod: I s he same mehod he prevous code (995) wh few modfcaos. I s

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

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

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

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

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

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

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

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

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

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

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

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

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

4. Runge-Kutta Formula For Differential Equations. A. Euler Formula B. Runge-Kutta Formula C. An Example for Fourth-Order Runge-Kutta Formula

4. Runge-Kutta Formula For Differential Equations. A. Euler Formula B. Runge-Kutta Formula C. An Example for Fourth-Order Runge-Kutta Formula NCTU Deprme o Elecrcl d Compuer Egeerg Seor Course By Pro. Yo-Pg Ce. Ruge-Ku Formul For Derel Equos A. Euler Formul B. Ruge-Ku Formul C. A Emple or Four-Order Ruge-Ku Formul

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

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

Mathematical Formulation

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

More information

4. Runge-Kutta Formula For Differential Equations

4. Runge-Kutta Formula For Differential Equations NCTU Deprme o Elecrcl d Compuer Egeerg 5 Sprg Course by Pro. Yo-Pg Ce. Ruge-Ku Formul For Derel Equos To solve e derel equos umerclly e mos useul ormul s clled Ruge-Ku ormul

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

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

Nature and Science, 5(1), 2007, Han and Xu, Multi-variable Grey Model based on Genetic Algorithm and its Application in Urban Water Consumption

Nature and Science, 5(1), 2007, Han and Xu, Multi-variable Grey Model based on Genetic Algorithm and its Application in Urban Water Consumption Naure ad Scece, 5, 7, Ha ad u, ul-varable Grey odel based o Geec Algorhm ad s Applcao Urba Waer Cosumpo ul-varable Grey odel based o Geec Algorhm ad s Applcao Urba Waer Cosumpo Ha Ya*, u Shguo School of

More information

RATIO ESTIMATORS USING CHARACTERISTICS OF POISSON DISTRIBUTION WITH APPLICATION TO EARTHQUAKE DATA

RATIO ESTIMATORS USING CHARACTERISTICS OF POISSON DISTRIBUTION WITH APPLICATION TO EARTHQUAKE DATA The 7 h Ieraoal as of Sascs ad Ecoomcs Prague Sepember 9-0 Absrac RATIO ESTIMATORS USING HARATERISTIS OF POISSON ISTRIBUTION WITH APPLIATION TO EARTHQUAKE ATA Gamze Özel Naural pulaos bolog geecs educao

More information

NUMERICAL EVALUATION of DYNAMIC RESPONSE

NUMERICAL EVALUATION of DYNAMIC RESPONSE NUMERICAL EVALUATION of YNAMIC RESPONSE Aalycal solo of he eqao of oo for a sgle degree of freedo syse s sally o ossble f he excao aled force or grod accelerao ü g -vares arbrarly h e or f he syse s olear.

More information

Model for Optimal Management of the Spare Parts Stock at an Irregular Distribution of Spare Parts

Model for Optimal Management of the Spare Parts Stock at an Irregular Distribution of Spare Parts Joural of Evromeal cece ad Egeerg A 7 (08) 8-45 do:0.765/6-598/08.06.00 D DAVID UBLIHING Model for Opmal Maageme of he pare ars ock a a Irregular Dsrbuo of pare ars veozar Madzhov Fores Research Isue,

More information

EE 6885 Statistical Pattern Recognition

EE 6885 Statistical Pattern Recognition EE 6885 Sascal Paer Recogo Fall 005 Prof. Shh-Fu Chag hp://www.ee.columba.edu/~sfchag Lecure 5 (9//05 4- Readg Model Parameer Esmao ML Esmao, Chap. 3. Mure of Gaussa ad EM Referece Boo, HTF Chap. 8.5 Teboo,

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

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

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

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

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

More information

Parameter identification of hyperelastic and hyper-viscoelastic models

Parameter identification of hyperelastic and hyper-viscoelastic models Parameer defcao of hyperelasc ad hyper-vscoelasc models *Y Feg Wu ), A Qu L ) ad Hao Wag 3) ), ), 3) School of Cvl Egeerg, Souheas Uversy, Najg, 0096 ) Bejg Uversy of Cvl Egeerg ad Archecure, Bejg,00044

More information

Final Exam Applied Econometrics

Final Exam Applied Econometrics Fal Eam Appled Ecoomercs. 0 Sppose we have he followg regresso resl: Depede Varable: SAT Sample: 437 Iclded observaos: 437 Whe heeroskedasc-cosse sadard errors & covarace Varable Coeffce Sd. Error -Sasc

More information

Computational Fluid Dynamics CFD. Solving system of equations, Grid generation

Computational Fluid Dynamics CFD. Solving system of equations, Grid generation Compaoal ld Dyamcs CD Solvg sysem of eqaos, Grd geerao Basc seps of CD Problem Dscrezao Resl Gov. Eq. BC I. Cod. Solo OK??,,... Solvg sysem of eqaos he ype of eqaos decdes solo sraegy Marchg problems Eqlbrm

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

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

Probability Bracket Notation, Probability Vectors, Markov Chains and Stochastic Processes. Xing M. Wang Sherman Visual Lab, Sunnyvale, CA, USA

Probability Bracket Notation, Probability Vectors, Markov Chains and Stochastic Processes. Xing M. Wang Sherman Visual Lab, Sunnyvale, CA, USA Probably Bracke Noao, Probably Vecors, Markov Chas ad Sochasc Processes Xg M. Wag Sherma Vsual Lab, Suyvale, CA, USA Table of Coes Absrac page1 1. Iroduco page. PBN ad Tme-depede Dscree Radom Varable.1.

More information

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

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

More information

CS344: Introduction to Artificial Intelligence

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

More information

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

-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

Application of the stochastic self-training procedure for the modelling of extreme floods

Application of the stochastic self-training procedure for the modelling of extreme floods The Exremes of he Exremes: Exraordary Floods (Proceedgs of a symposum held a Reyjav, Icelad, July 000). IAHS Publ. o. 7, 00. 37 Applcao of he sochasc self-rag procedure for he modellg of exreme floods

More information

Common MidPoint (CMP) Records and Stacking

Common MidPoint (CMP) Records and Stacking Evromeal ad Explorao Geophyscs II Commo MdPo (CMP) Records ad Sackg om.h.wlso om.wlso@mal.wvu.edu Deparme of Geology ad Geography Wes rga Uversy Morgaow, W Commo Mdpo (CMP) gaher, also ofe referred o as

More information

A note on Turán number Tk ( 1, kn, )

A note on Turán number Tk ( 1, kn, ) A oe o Turá umber T (,, ) L A-Pg Beg 00085, P.R. Cha apl000@sa.com Absrac: Turá umber s oe of prmary opcs he combaorcs of fe ses, hs paper, we wll prese a ew upper boud for Turá umber T (,, ). . Iroduco

More information

An Efficient Dual to Ratio and Product Estimator of Population Variance in Sample Surveys

An Efficient Dual to Ratio and Product Estimator of Population Variance in Sample Surveys "cece as True Here" Joural of Mahemacs ad ascal cece, Volume 06, 78-88 cece gpos Publshg A Effce Dual o Rao ad Produc Esmaor of Populao Varace ample urves ubhash Kumar Yadav Deparme of Mahemacs ad ascs

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

Voltage Sensitivity Analysis in MV Distribution Networks

Voltage Sensitivity Analysis in MV Distribution Networks Proceedgs of he 6h WSEAS/IASME I. Cof. o Elecrc Power Sysems, Hgh olages, Elecrc Maches, Teerfe, Spa, December 6-8, 2006 34 olage Sesvy Aalyss M Dsrbuo Neworks S. CONTI, A.M. GRECO, S. RAITI Dparmeo d

More information