Positivity-Preserving Well-Balanced Discontinuous Galerkin Methods for the Shallow Water Equations on Unstructured Triangular Meshes

Size: px
Start display at page:

Download "Positivity-Preserving Well-Balanced Discontinuous Galerkin Methods for the Shallow Water Equations on Unstructured Triangular Meshes"

Transcription

1 J Sc Comput 23 57:9 4 DOI.7/s y Postvty-Preservng Well-Balanced Dscontnuous Galerkn Methods for the Shallow Water Equatons on Unstructured Trangular Meshes Yulong Xng Xangxong Zhang Receved: 9 November 22 / Revsed: 25 January 23 / Accepted: 4 February 23 / Publshed onlne: 2 March 23 Sprnger Scence+Busness Meda New York 23 Abstract The shallow water equatons model flows n rvers and coastal areas and have wde applcatons n ocean, hydraulc engneerng, and atmospherc modelng. In Xng et al. Adv. Water Resourc. 33: , 2, the authors constructed hgh order dscontnuous Galerkn methods for the shallow water equatons whch can mantan the stll water steady state exactly, and at the same tme can preserve the non-negatvty of the water heght wthout loss of mass conservaton. In ths paper, we explore the extenson of these methods on unstructured trangular meshes. The smple postvty-preservng lmter s reformulated, and we prove that the resultng scheme guarantees the postvty of the water depth. Extensve numercal examples are provded to verfy the postvty-preservng property, well-balanced property, hgh-order accuracy, and good resoluton for smooth and dscontnuous solutons. eywords Shallow water equatons Dscontnuous Galerkn method Hgh order accuracy Well-balanced Postvty-preservng methods Wettng and dryng treatment Introducton The man goal of ths paper s to present hgh order accurate dscontnuous Galerkn DG methods for the shallow water equatons on unstructured trangular meshes, whch are not only well-balanced for the stll water steady-state solutons, but also preserve the non-negatvty Y. Xng B Computer Scence and Mathematcs Dvson, Oak Rdge Natonal Laboratory, Oak Rdge, TN 3783, USA e-mal: xngy@math.utk.edu Y. Xng Department of Mathematcs, Unversty of Tennessee, noxvlle, TN 37996, USA X. Zhang Department of Mathematcs, Massachusetts Insttute of Technology, Cambrdge, MA 239, USA e-mal: zhangxx@math.mt.edu

2 2 J Sc Comput 23 57:9 4 of the water depth. The shallow water equatons wth a non-flat bottom topography play a crtcal role n the modelng and smulaton of flows n rvers, lakes and coastal areas. They have wde applcatons n ocean, hydraulc engneerng and atmospherc modelng. The two-dmensonal shallow water equatons take the form h t + hu x + hv y = hu t + hu gh2 x + huv y = ghb x hv t + huv x +. hv gh2 y = ghb y, where h denotes the water heght, u,v T s the velocty vector, b represents the bottom topography and g s the gravtatonal constant. Other terms, such as a frcton term, could also be added n.. Due to the large scentfc and engneerng applcatons of the shallow water equatons, research on effectve and accurate numercal methods for ther solutons has attracted great attenton n the past two decades. One dffculty encountered s the treatment of the source terms. An essental part for the shallow water equatons and other conservaton laws wth source terms s that they often admt steady-state solutons n whch the flux gradents are exactly balanced by the source term. For the shallow water equatons, people are partcularly nterested n the stll water steady-state soluton, whch represents a stll flat water surface, and often referred as lake at rest soluton: u = v = and h + b = const..2 Tradtonal numercal schemes wth a straghtforward handlng of the source term cannot balance the effect of the source term and the flux, and usually fal to capture the steady state well. They wll ntroduce spurous oscllatons near the steady state. The well-balanced schemes are specally desgned to preserve exactly these steady-state solutons up to machne error wth relatvely coarse meshes, and therefore t s desrable to desgn numercal methods whch have the well-balanced property. The other major dffculty often encountered n the smulatons of the shallow water equatons s the appearance of dry areas n many engneerng applcatons ncludng the dam break problem and flood waves etc. Specal attenton needs to be pad near the dry/wet front, otherwse they may produce non-physcal negatve water heght, whch becomes problematc when calculatng the egenvalues u ± gh and v ± gh to determne the tme step sze t, and renders the system not hyperbolc and not well posed. In the past decade, many well-balanced numercal methods have been developed for the shallow water equatons, see, e.g. [3,,22,2,26,25] and the references theren. There are also a number of postvty-preservng schemes [4,4,7,7,9,6] proposed for., and a few of them[2,,4,8] can resolve both dffcultes at the same tme. Recently, hghorder accurate DG methods have attracted ncreasng attenton n many computatonal felds, ncludng the geophyscal flud dynamcs. DG method s a class of fnte element methods usng dscontnuous pecewse polynomal space as the soluton and test functon spaces see [] for a hstorc revew. Several advantages of the DG method, ncludng ts accuracy, hgh parallel effcency, flexblty for hp-adaptvty and arbtrary geometry and meshes, make t partcularly suted for the shallow water equatons, see the frst work by Schwaneberg and ongeter [29], followed by [5,3,8,23] and others. Recently, several well-balanced DG methods have been proposed, by Xng and Shu [33,34,36], Ern et al. [4], Rhebergen et al. [27] and other researchers [2]. Also, some dscussons on DG methods nvolvng wettng and dryng treatments for the shallow water equatons can be found n [5,4,9]. In [36], hgh order accurate DG methods, whch can mantan the stll water steady state exactly, and at the same tme can preserve the non-negatvty of the water heght, are developed

3 J Sc Comput 23 57:9 4 2 for the shallow water equatons on one-dmensonal and two-dmensonal rectangular meshes. Due to the complex geometry of the computatonal domans n many real-world applcatons, trangular meshes are often used. In ths paper, we are nterested n the extenson of the postvty-preservng well-balanced methods developed n [36] on unstructured trangular meshes. A smple source term dscretzaton wll be presented, and shown to be balanced wth the numercal fluxes at the steady-state soluton. Wth the ntroducton of a specal desgned Gaussan quadrature rule, we wll demonstrate that the smple postvty-preservng lmter used n [39] s stll plausble on trangular meshes, and does not affect the hgh order accuracy, as well as the mass conservaton. Ths paper s organzed as follows. In Sect. 2, we present the well-balanced DG methods for the shallow water equatons on trangular meshes, followng the technque proposed n [34]. The postvty-preservng well-balanced DG methods are presented n Sect. 3, whch nvolves a smple postvty-preservng lmter. Secton 4 contans extensve numercal smulaton results to demonstrate the behavor of our DG methods for two-dmensonal shallow water equatons on trangular meshes, verfyng hgh order accuracy, the well-balanced property, postvty-preservng property, and good resoluton for smooth and dscontnuous solutons. Concludng remarks are gven n Sect Well-Balanced DG Methods In ths secton, we frst renstate the classcal Runge-utta dscontnuous Galerkn RDG methods appled for the shallow water equatons. A few well-balanced DG methods have been developed recently, see the recent book chapter [25] for a revew and the references theren. In ths paper, we consder the approach developed by one of the authors n [34], where we observed that the classcal RDG methods are well-balanced for the stll water soluton.2, f a hydrostatc reconstructon s employed on the flux. The same technque s also used n [4,2,36] to derve well-balanced postvty-preservng methods. Ths s one of the smplest approaches to obtan a hgh order well-balanced scheme, and the extra computatonal cost due to the well-balanced property s neglgble. Its extenson to a trangulaton wll be ntroduced n ths secton, and ths scheme wll serve as the bass for the postvty-preservng technque presented n Sect. 3. Let T τ be a famly of parttons of the computatonal doman parameterzed by τ>. For any trangle T τ,wedefneτ := dam and τ := max τ. For each edge T τ e =, 2, 3 of, we denote ts length by l, and outward unt normal vector by ν.let be the neghborng trangle along the edge e and be the area of the trangle. For the ease of presentaton, we denote the shallow water equatons.by U t + f U x + gu y = sh, b, or U t + FU = sh, b, where U = h, hu, hv T wth the superscrpt T denotng the transpose, f U, gu or FU = f U, gu are the flux and sh, b s the source term. In a hgh order DG method, we seek an approxmaton, stll denoted by U wth an abuse of notaton, whch belongs to the fnte dmensonal space { } V τ = Vτ k w L 2 ; w P k T τ, 2. where P k denotes the space of polynomals on of degree at most k. Weprojectthe bottom functon b nto the same space V τ, to obtan an approxmaton whch s stll denoted

4 22 J Sc Comput 23 57:9 4 by b, agan wth an abuse of notaton. Let x denote x, y, then the numercal scheme s gven by t Uw dx FU wdx + F e ν w ds = sh, bw dx, 2.2 = e where wx s a test functon from the test space V τ. The numercal flux F s defned by F e ν U = F nt, U ext,ν, 2.3 where U nt and U ext are the approxmatons to the values on the edge e obtaned from the nteror and the exteror of. We could, for example, use the smple global Lax-Fredrchs flux Fa, a 2,ν= [ ] Fa ν + Fa 2 ν αa 2 a, 2 α = max u + gh, v + gh ν, 2.4 where the maxmum s taken over the whole regon. It satsfes the conservatvty and consstency Fa, a 2,ν= Fa 2, a, ν, Fa, a,ν= Fa ν. 2.5 A smple Euler forward tme dscretzaton of 2.2 gves the fully dscretzed scheme U n+ U n w dx FU wdx + F t e = e ν w ds = sh, bw dx. 2.6 Total varaton dmnshng TVD hgh order Runge-utta tme dscretzaton [3] s used n practce for stablty and to ncrease temporal accuracy. For example, the thrd order TVD Runge-utta method s used n the smulaton n ths paper: U = U n + tlu n U 2 = 3 4 U n + U + tlu 4 U n+ = 3 U n + 2 U 2 + tlu 2, where LU s the spatal operator. In order to acheve the well-balanced property, we are nterested n preservng the stll water statonary soluton.2 exactly. Followng the technque presented n [34], our wellbalanced numercal scheme, modfed from the classcal verson 2.6, takes the form: U n+ U n w dx FU wdx + F t e ν w ds = sh, bw dx, = e 2.8

5 J Sc Comput 23 57: or equvalently, U n+ U n t w dx = sh, bw dx + FU w dx + = e F e ν w ds = e F F e ν w ds. 2.9 Theleftsdeof2.9 s the classcal RDG scheme, and the rght sde s our approxmaton to the source term. The flux F s computed based on the hydrostatc reconstructon technque [] and wll be explaned later. However we pont out here that the dfference F F s a hgh order correcton term at the level of Oh k+ regardless of the smoothness of the soluton U. Therefore, the scheme 2.8 s a spatally k + -th order conservatve scheme and wll converge to the weak soluton. After computng boundary values U nt on the edge e,weset h,nt h,ext = max = max and U ext, h nt + b nt max b nt, b ext, h ext + b ext max b nt, b ext 2. and redefne the nteror and exteror values of U as: h,nt U,nt = h,nt = h,nt U,ext = Introducng the notatons δ,x =, g nt 2 g h 2 2 u nt h,nt v nt h,ext h,ext u ext h,ext v ext h nt = h,ext h ext,nt 2, T h, δ,y =,, g 2 on the edge e,theflux F s then gven by: F e ν U = F,nt, U,ext,ν U nt, U ext. 2. h nt 2 g 2,nt 2 T h + δ,x,δ,y ν. 2.2 We also requre that all the ntegrals n formula 2.8 should be calculated exactly at the stll water state. Ths can be easly acheved by usng sutable Gauss-quadrature rules snce the numercal solutons h, b and w are polynomals at the stll water state n each trangle, hence FU and sh, b are both polynomals. We can prove that the above methods 2.8, combned wth the choce of fluxes 2.2, are actually well-balanced for the stll water steady state of the shallow water equatons. The key dea s to show that, at the stll water steady state.2, the numercal fluxes F becomes FU nt on the edge e. We refer to [34]for the techncal detals of the proof. When appled to problems whch contan dscontnuous soluton, RDG methods may generate oscllaton and even nonlnear nstablty. We often apply nonlnear lmters to control these oscllatons. Many lmters have been studed n the lterature. In ths paper, we use

6 24 J Sc Comput 23 57:9 4 the classcal characterstc-wse total varaton bounded TVB lmter n [2,3], wth a corrected mnmod functon defned by { a, f a ma,, a n = M x 2, ma,, a n, otherwse, 2.3 where M s the TVB parameter to be chosen adequately [] and the mnmod functon m s gven by { s mn a ma,, a n =, f s = sgna = =sgna n,, otherwse. Usually, the lmter s appled on the functon U after each nner stage n the Runge-utta tme steppng. For the shallow water system, we perform the lmtng n the local characterstc varables. However, ths lmter procedure mght destroy the preservaton of the stll water steady state h + b = const, snce f the lmter s enacted, the resultng modfed soluton h may no longer satsfy ths steady-state relaton. Therefore, followng the dea presented n [33,36], we present the followng strategy to perform the lmter, whch works well wth the well-balance property. As explaned n [36], we note that the TVB lmter procedure actually nvolves two steps: the frst one s to check whether any lmtng s needed n a specfc cell; and, f the answer s yes, the second step s to apply the TVB lmter on the varables n ths cell. We frst check f the lmtng s needed, based on h+b, hu, hv T. If a certan cell s flagged by ths procedure needng lmtng, then the actual TVB lmter s mplemented on the varables h, hu, hv T. Note that f n a steady-state regon where h + b = const and u = v =, we frst check f the lmtng s needed based on h + b, hu, hv T = const,, T,whch demonstrates that lmtng s not needed n ths cell. Therefore the flat surface h + b = const wll not be affected by the lmter procedure and the well-balanced property s mantaned. Also, we observe that ths procedure wll not destroy the conservatvty of h, whch wll be mantaned durng the lmter process. When the lmtng procedure s mplemented ths way, numercal results show that ths choce of the TVB lmter does not destroy the well-balanced property, and also t works well wth the postvty-preservng lmter presented n the next secton. 3 Postvty-Preservng Lmter In ths secton, we present a smple postvty-preservng lmter on trangular meshes, and couple t wth the well-balanced DG methods developed for the shallow water equatons n Secton 2. We wll start by showng the postvty of a frst order scheme wth the wellbalanced flux, and later generalze the dea to hgh order schemes. For the ease of presentaton, Euler forward tme dscretzaton 2.8 wll be dscussed, but all the results hold for the TVD hgh order Runge-utta and mult-step tme dscretzatons. 3. Prelmnares For convenence, let F and F e ν denote the frst components of F and F e ν respectvely. Then F e ν = F U,nt, U,ext, ν by 2.2. Takng the test functon as w n2.8, we get the the scheme satsfed by the cell averages for the water heght h:

7 J Sc Comput 23 57: h n+ = h n t = e F U,nt, U,ext,ν ds, 3. where h n stands for the average of h over the trangle at tme level n. Suppose we use L-pont Gaussan quadrature for the lne ntegral n 2.8 and3., and the subscrpt,βwll denote the pont value at the β-th quadrature pont of the -th edge. Let w β denote the Gauss quadrature weght on the nterval [ /2, /2].Then3. becomes h n+ 3.2 Frst order schemes = h n t L = β= F U,nt,β, U,ext,β,ν w β l. 3.2 To nvestgate the postvty of a hgh order scheme 3.2, we need to study ts frst order counterpart. Gven pecewse constants U n for the soluton and b for the bottom on each trangle at tme level n, consder a frst order scheme for the water heght, where h n+ = h n t U,nt = F U,nt, U,ext = h, h n U n, U,ext = h, h n,ν U n, wth h, = max, h n + b maxb, b, h,, = max h n + b maxb, b, Lemma 3. Under the CFL condton t α 3 l, wth α = max = l, 3.3 u + gh, v + gh ν, 3.4 f h n s non-negatve for any, then hn+ s non-negatve n the frst order scheme 3.3. Proof By 2.4, the flux n 3.3s F U,nt, U,ext,ν = 2 [ h, h n hu n,hvn h n ν + h, And the scheme 3.3 can be wrtten as [ h n+ = t 2 + t 2 = = l l h, h n ] hu n,hvn ν α h, h,. α + u n ],vn ν h n h, h n α u n,vn ν h n 3.5

8 26 J Sc Comput 23 57:9 4 Fg. The quadrature ponts on a trangle for P 2 polynomals. There are 24 dstnct ponts. Three ponts near the centrod of the trangle are very close to one another Notce that h, /hn, h, /hn [, ]. And we have un, vn ν αfor any by 3.4. Therefore, 3.5 s a lnear combnaton of h n and hn wth non-negatve coeffcents. Thus, h n+ s non-negatve f h n and hn are non-negatve. 3.3 Hgh order schemes Followng the approach n [39], the frst step s to decompose the cell average h n as a convex combnaton of pont values of the DG polynomal h x, y by a quadrature satsfyng: The quadrature rule s exact for ntegraton of h x, y on. The quadrature ponts nclude all L-pont Gauss quadrature ponts for each edge e. All the quadrature weghts should be postve. Ths partcular quadrature rule can be constructed by a transformaton of the tensor product of M-pont Gauss-Lobatto and L-pont Gauss quadrature, whch s summarzed below see [39] for detals. Let {v β : β =,, L} denote the Gauss quadrature ponts on [ 2, 2 ] wth weghts w β,and{û α : α =,, M} denote the Gauss-Lobatto quadrature ponts on [ 2, 2 ] wth weghts ŵ α. In the barycentrc coordnates, the set of quadrature ponts S can be wrtten as { S = 2 + vβ, 2 + ûα 2 vβ, 2 ûα 2 vβ, 2 ûα 2 vβ, 2 + vβ, 2 + ûα 2 vβ, 2 + ûα 2 vβ, 2 ûα 2 vβ, 2 + vβ : α =,, M; β =,, L}. 3.6 In partcular, for the P 2 -DG method used n numercal tests of ths paper, 4-pont Gauss quadrature rule s needed so that the lne ntegral n 2.8 s exactly calculated for the stll water state. And the 3-pont Gauss-Lobatto quadrature s suffcent to construct S.SeeFg. for the quadrature ponts.

9 J Sc Comput 23 57: Let h x, y denote the DG polynomal for the water heght at tme level n and w x denote the quadrature weght for the pont x S of the quadrature rule 3.6. Let h nt,β denote the pont value of h x at the β-th Gauss quadrature pont of the -th edge of. Then the quadrature weght for h nt,β s 2w β ŵ /3, see [39] for the detal. The cell average h n can now be wrtten as a convex combnaton of pont values of h x va the quadrature rule S, h n = h x dx = x S h xw x = = β= L 2 3 w βŵ h nt,β + h xw x, 3.7 x S where S s the set of the ponts n S that le n the nteror of the trangle. Theorem 3.2 For the scheme 3.2 to be postvty preservng,.e., h n+, a suffcent condton s that h x, x S for all, under the CFL condton α t l 2 3 ŵ. 3.8 = Here h x denotes the polynomal for water heght at tme level n, ŵ s the quadrature weght of the M-pont Gauss-Lobatto rule on [ /2, /2] for the frst quadrature pont. For k = 2, 3, ŵ = /6 and for k = 4, 5, ŵ = /2. Proof Rewrte the scheme 3.2as h n+ = h n t = h n t L = β= L β= w β = F U,nt,β, U,ext,β Then decompose the flux term nsde the bracket. Let = F U,nt,β, U,ext,β,ν l = F U,nt,β, U,ext,β,ν l + F +F U,nt 3,β, U,ext 3,β,ν 3 l 3 = F U,nt,β, U,ext,β,ν +F U,nt, U,nt,β,ν +F U,nt, U,nt 3,β,ν 3 +F U,nt 3,β, U,nt, ν 3,ν F U,nt,β, U,ext,β w β l,ν U,nt, U,ext,ν 2 l 2 l + F U,nt,β, U,nt, ν l + F U,nt, U,ext,ν 2 l 3 l 3 + F l. 3.9 l l 2 U,nt 3,β, U,ext 3,β,ν 3 l 3, 3. where we have used the conservatvty of the flux 2.5.

10 28 J Sc Comput 23 57:9 4 Pluggng 3.7and3. nto3.9, we get the monotone form L h n+ 2 = 3 w βŵ h nt,β + h xw x = β= x S t L w β β= = = L h xw x + x S β= where H,β, H, and H 3,β are H,β = h nt,β 3 t 2ŵ H = h nt 3 t 2ŵ H 3,β = h nt 3,β 3 t 2ŵ x S w x F U,nt,β, U,ext,β,ν l 2 [ 3 w βŵ H,β + H + H 3,β ], 3. [F U,nt,β, U,ext,β,ν l + F U,nt,β, U,nt, ν l [F U,nt, U,nt,β,ν + F U,nt, U,ext + F U,nt, U,nt [F U,nt 3,β, U,nt, ν 3,ν 2 3,β,ν 3 l 3 + F U,nt 3,β, U,ext 3,β,ν 3 ] l, l 2 ] l 3 ] l 3. Followng Lemma 3., under the CFL condton 3.8, H fh nt,β, h ext,β. The postvty of H,β and H 3,β follows the analyss of one-dmensonal frst order postvtypreservng methods presented n [36, Lemma3.]. Therefore, f all the pont values nvolved n 3., h nt,β, h ext,β and h x for x S are non-negatve, whch s equvalent to h x, x S for all,thenwehavethe postvty h n+ n3.. Remark 3.3 As mentoned n [35,38], for those ponts n S, nstead of requrng h x, x S, t suffces to requre x S h xw x to have postvty of h n+ n 3.. Notce that x S h xw x / x S w x s a convex combnaton of pont values of h x, thus by the Mean Value Theorem, there exsts some pont x such that h x = x S w x x S h xw x.by3.7, we have h x L = h xw x = h n+ 2ŵ 2 3 w βŵ h nt,β, 3.2 x S = β= where we use the fact x S w x = 3 Lβ= 2 = 3 w β ŵ = 2ŵ. So a more relaxed but less ntutve suffcent condton for 3.2 to satsfy h n+ s, h n, hnt,β, h ext,β, h x wth the CFL condton 3.8, where h x s defned n 3.2.

11 J Sc Comput 23 57: The Lmter At tme level n, gven the water heght DG polynomal h x wth ts cell average h n, to enforce the suffcent condton h x, x S, the lmter n [39] can be used drectly,.e., replacng h x by a lnear scalng around the cell average: h x = θ h x h n + h n, 3.3 where θ [, ] s determned by θ = mn x S θ x, { h n } θ x = mn, h n h. 3.4 x Ths lmter s conservatve the cell average of p s stll h n, postvty-preservng h x, x S and hgh order accurate. See [37,39,36] for the dscusson of the lmter. An alternatve lmter s to enforce the relaxed condton n Remark 3.3. Let S denote the ponts n S whch le on the edges of, then we can use 3.3 wth { } θ = mn θ x, mn θ x, θ x = mn x S {, h n h n h x }. 3.5 Compared to 3.4, evaluatng h x, x S s avoded n 3.5 snceh x can be obtaned by 3.2, whch s preferred snce these pont values are not Gaussan quadrature ponts on a trangle thus not used n the DG scheme 2.8. Notce that the postvty-preservng lmter 3.3 or3.4 wll not take any effect f the DG polynomals satsfy.2. So the postvty-preservng lmter does not affect the well-balanced property. 3.5 The Algorthm for Runge-utta Tme Dscretzatons At the end, we present the algorthm flowchart of our postvty-preservng well-balanced methods, when coupled wth thrd order TVD Runge-utta methods. Frst of all, one notces that, for Euler forward tme dscretzaton, the CFL constrant 3.8 s suffcent rather than necessary for preservng postvty. Second, for a Runge-utta tme dscretzaton, to enforce the CFL condton rgorously, we need to obtan an accurate estmaton of 3.4 for all the stages of Runge-utta based only on the numercal soluton at tme level n, whch s very dffcult n most of test examples. So an effcent mplementaton s, f a prelmnary calculaton to the next tme step produces negatve water heght, we restart the computaton from the tme step n wth half of the tme step sze. The algorthm of postvty-preservng well-balanced dscontnuous Galerkn method wth the thrd order TVD Runge-utta tme dscretzaton on trangular meshes can be summarzed as below:. Gven the DG polynomals U x at tme step n satsfyng the cell average of h s nonnegatve and h x >, x S, calculate α = max u + gh, v + gh ν, where the maxmum of u,v,h s taken over S and the maxmum of ν s taken over ν for all. Set the tme step t = mn 2 ŵ 3 α 3 = l.

12 3 J Sc Comput 23 57:9 4 Table L and L errors for the statonary soluton n Sect. 4. L error L error h hu hv h hu hv 4.72E 3.E 2.3E E E 2.9E 2. Calculate the frst stage wth U x based on 2.8 wth the numercal fluxes 2.2. Let U x denote the soluton of the frst stage. Modfy t by frst the TVB lmter then the postvty lmter 3.3or3.4ntoŨ x. 3. Calculate the second stage wth Ũ x. LetU 2 x denote the soluton of the second stage. If ts cell average of water heght s negatve by Theorem 3.2, ths means that α calculated based on U x s smaller than the one of Ũ x, then go back to step two and restart wth half tme step; otherwse, modfy t by the lmters nto Ũ 2 x. 4. Calculate the thrd stage wth Ũ 2 x.letu 3 x denote the soluton of the thrd stage. If ts cell average of water heght s negatve by Theorem 3.2, ths means that α calculated based on U x s smaller than the one of Ũ 2 x, then go back to step two and restart wth half tme step; otherwse, modfy t by the lmters nto Ũ 3 x, whch s the soluton at tme step n +. 4 Numercal Examples In ths secton we present numercal results of our postvty-preservng well-balanced DG methods when appled to the two-dmensonal shallow water equatons on unstructured trangular meshes. The thrd order fnte element DG method.e. k = 2, coupled wth the thrd order TVD Runge-utta tme dscretzaton 2.7, s mplemented n the examples. Global Lax-Fredrchs numercal flux s used, and the gravtaton constant g s fxed as 9.82 m/s 2 except the test n Subsect The tme step s taken as ndcated by the CFL condton 3.8. All the meshes are unstructured, and generated by EasyMesh [24]. 4. Well-Balanced Test The purpose of the frst test problem s to verfy the well-balanced property of our algorthm towards the steady-state soluton. We consder a rectangular computatonal doman [, ] [, ]. The bottom functon s chosen as: bx, y = max, x 5 2 y 5 2, 4. and the ntal data s the statonary soluton: hx, y, = 2 bx, y, hux, y, = hvx, y, =. A perodc boundary condton s used. Ths steady state should be exactly preserved, and the surface should reman flat. We compute the soluton untl t =.5 on the trangular meshes wth the mesh sze τ =.25. In order to demonstrate that the stll water soluton s ndeed mantaned up to round-off error, we use the double-precson to perform the computaton, and show the L and L errors for the water heght h note: h n ths case s not a constant functon! and the dscharges hu, hv n Table. We can clearly see that all errors are at the level of round-off errors, whch verfes the well-balanced property.

13 J Sc Comput 23 57: Fg. 2 The computatonal doman and unstructured trangular meshes of the accuracy test problem n Sect Left wth mesh sze τ =.; rght wth mesh sze τ = Accuracy Test In ths example we wll test the hgh order accuracy of our schemes when appled to the followng two-dmensonal problem. The computatonal doman s set as a unt square [, ] 2. The bottom topography and the ntal data are gven by: 2πx+y 2π bx, y = sn 2 x + y, hx, y, = 5 + e, cos 2 2 hux, y, = hvx, y, = 2 sn cos 2πx + y, whch are obtaned by rotatng the setup of the one-dmensonal accuracy test n [32,35] by an angle of 45. Perodc boundary condtons are consdered here for smplcty. The fnal tme s set as t =.5 to avod the appearance of shocks n the soluton. Snce the exact soluton s also not known explctly for ths case, we use the one-dmensonal well-balanced DG methods presented n [34], wth a refned 2,8 unform cells, to compute a reference soluton. After rotatng that soluton by an angle of 45, ths reference soluton s treated as the exact soluton n computng the numercal errors. The TVB constant M n the TVB lmter 2.3 stakenashere. Thecomputatonaldoman, andtheunstructuredtrangular mesh wth τ =.,.25, are shown n Fg. 2. Table2 contans the L errors and orders of accuracy for the cell averages. We can clearly see that, n ths two-dmensonal test case, thrd order accuracy s acheved for the RDG scheme. 4.3 A Small Perturbaton of a Steady-State Soluton Ths s a classcal example to show the capablty of the proposed scheme for the perturbaton of the statonary state. Ths test was gven by LeVeque [22], and has also been used n [32,34,8]. We solve the system n the rectangular doman [, 2] [, ]. The bottom topography s an solated ellptcal shaped hump: bx, y =.8 exp 5x.9 2 5y

14 32 J Sc Comput 23 57:9 4 Table 2 L errors and numercal orders of accuracy for the example n Sect. 4.2 Meshsze h hu hv τ L error Order L error Order L error Order E E E E E E E E E E E E E E E 2.3E E E E 3.27E E E The ntal condton s gven by: { bx, y +., f.5 x.5, hx, y, = bx, y, otherwse, hux, y, = hvx, y, =. 4.3 Intally, the surface s almost flat except for.5 x.5, where h s perturbed upward by a small magntude of.. Theoretcally, ths dsturbance should splt nto two waves, propagatng left and rght at the characterstc speeds ± gh. We use the outlet boundary condton on the left and rght, and reflecton boundary condtons on the top and bottom sdes. TVB constant M s taken as ten n the test. Fgure 3, left, dsplays the rght-gong dsturbance as t propagates past the hump on the trangular meshes wth τ =.625. The surface level h + b s presented at dfferent tmes. The results ndcate that our schemes can resolve the complex small features of the flow very well. As a comparson, we refer to [8, Fg. 5] for the output f a non-well-balanced method s used. Next, we ncrease the heght of the bottom topography to reach the water surface. The modfed bottom topography takes the form: bx, y = exp 5x.9 2 5y The other set up remans the same. We repeat the smulaton and plot the surface level at dfferent tmes n Fg. 3, rght. As one can see, the general structure of the soluton s well resolved. For small tme when the rght-gong wave does not reach the bottom hump, the surface stays the same for these two smulatons wth dfferent bottom topography. Obvous dfference can be observed as the wave reaches and passes the hump. 4.4 Crcular Dam-Break Problem Ths s a classcal test case for testng the complete break of a crcular dam separatng a basn of water and dry bed. It has been prevously tested n [6,6]. We consder a square computatnal doman [, ] [, ] wth a flat bottom topography.e. b =. The dam s located at r = x 2 + y 2 = 6, and the water heght h s ntally set as ten nsde the dam and zero outsde. Both components of the velocty u and v are set to zero ntally. At tme t =, the crcular wall formng the dam collapses. We dscretze the doman wth the trangular meshes and τ s set as one. A 3D vew and contour lnes of the water heght at tme t =.75 are shown n Fg. 4. We can observe an almost perfectly symmetrc soluton, and there s no oscllaton maxh = n the numercal results.

15 J Sc Comput 23 57: Surface level at tme t=.2 Surface level at tme t= Surface level at tme t= Surface level at tme t= Surface level at tme t=.48 Surface level at tme t= Surface level at tme t= Surface level at tme t= Surface level at tme t= Surface level at tme t= Fg. 3 The contours of the surface level h + b for the problem n Sect Unformly spaced contour lnes. From top to bottom at tme t =.2 from to.7; at tme t =.24 from.9999 to.; at tme t =.36 from.9998 to.2; at tme t =.48 from to.5; and at tme t =.6 from.9999 to.. Left results wth the bottom 4.2. Rght results wth the bottom 4.4

16 34 J Sc Comput 23 57:9 4 5 Y Fg. 4 Numercal results at tme t =.75 of the crcular dam-break problem n Sect Left 3D vew of the surface level; rght the contours of the surface level wth 3 unformly spaced contour lnes between zero and ten 4.5 Water Drop Problem Next, we apply our methods to a numercal test case whch smulates the water drop problem. Followng the setup n [28], we consder the 2D Gaussan shaped peak ntal condton gven by: hx, y, = +.exp x y.5 2, hux, y, = hvx, y, =, 4.5 n the computatonal doman [, ] 2. The reflectve boundary condtons are employed. The ntal Gaussan shaped water drop generates a wave that reflects off the boundary. We have provded the evoluton of water surface at varous tmes n Fg. 5, whch shows that the wave s well smulated by our methods. As a comparson, we also repeat the test wth a non-zero bottom topography: bx, y =.5 exp x y The results are shown n Fg. 6, where we can observe the effect of the bottom on the propagaton of the wave. 4.6 Floodng on a Channel wth Three Mounds In ths test example, we consder the smulaton of a flow through a channel whch contans three mounds on ts bottom [7,7]. The length of the channel s 75 and wdth s 3. The bottom topography takes the form of bx, y = max, m x, y, m 2 x, y, m 3 x, y, 4.7

17 J Sc Comput 23 57: Fg. 5 The water surface level n the water drop problem wth the flat bottom topography at dfferent tmes where m x, y =. x y , m 2 x, y =. x y 7.5 2, m x, y = x y 5 2. Intally, the doman s set as dry,.e. h = hu = hv =. We mpose the reflectng boundary condton on the upper and lower boundares n y-drecton. The rght x-boundary s a open-wall outflow boundary. At the left x-boundary, we mpose an nflow of the form: u =, v= and the water heght h =.5 for the tme t 3, h = whent 3. We test our well-balanced postvty-preservng methods on ths problem wth trangulaton of mesh sze τ =.5. The numercal results obtaned at dfferent tmes are shown n Fg. 7.

18 36 J Sc Comput 23 57:9 4 Fg. 6 The water surface level n the water drop problem wth the bottom topography 4.6 at dfferent tmes 4.7 Flows n Convergng Dvergng Channels In the last example, we consder the water flow n an open convergng dvergng channel. The test s frst dscussed n[9] and recently used n [8]. The gravtaton constant g s taken as one n ths test. The computatonal doman s defned on the convergng dvergng channel of length 3 wth a half-cosne constrcton centered at x =.5. It takes the form of [, 3] [ y b x, y b x], where y b x = {.5.5 d cos 2 πx.5, f x.5.5,.5, otherwse, 4.8 and d s the mnmum channel breadth. Two values of the channel breadth d,.9 and.6, are tested n ths example. The computatonal doman wth d =.6 s shown n Fg. 8, left.

19 J Sc Comput 23 57: Fg. 7 The water surface level n the floodng problem on a channel wth three mounds at dfferent tmes t = 8, 3, 3 and 54 from top to bottom. Left 3D vew, color spannng between and.2; rght the 2D contours wth 3 unformly spaced contour lnes between and.2 We consder a bottom topography whch conssts of two ellptc Gausssan mounds: bx, y = B exp x.9 2 5y exp 2x y +.2 2, 4.9 where B wll be specfed later. Ths topography wth B = s shown n Fg. 8, rght. The ntal condtons are gven by: hx, y, = max, bx, y, hux, y, = 2, hvx, y, =. We mpose the reflectng boundary condton on the upper and lower boundares n y-drecton. The left x-boundary s set as an nflow boundary wth u = 2 and the rght x-boundary s a zeroth-order outflow boundary.

20 38 J Sc Comput 23 57: Fg. 8 Intal setup of the convergng dvergng channels problem n Sect Left the computatonal doman wth d =.6 and the unstructured trangular meshes wth τ =.25; rght the contours of the bottom topography 4.9 wth B = and d = Fg. 9 The contours of the water surface level of the convergng dvergng channels problem n Sect. 4.7 wth the parameters d =.9 andb =. Results are based on the trangulaton wth mesh szes τ =.25 left and 6.25E 3 rght, respectvely We frst generate the trangular meshes on the rectangle doman [, 3] [.5,.5]. Followng the dea n [8], the trangulaton on the convergng dvergng channel s obtaned through the mappng { x, y d cos 2 πx.5y, f x.5.5, x, y x, y, otherwse. The resultng unstructured trangular mesh wth τ =.25sshownnFg.8, left. Our well-balanced postvty-preservng methods are tested on ths problem. In all tests, the smulatons are carred out on two trangulaton wth mesh szes τ =.25 and 6.25E 3 respectvely. The stoppng tme s set as t = 2. We start wth the parameters d =.9 and B =,.e., a flat bottom. The numercal results are shown n Fg. 9, whch agree well wth the solutons n [9,8]. Next, we keep the computatonal doman d =.9 and set the bottom topography as B = n9. The two mounds are set to reach the water surface. We repeat our smulatons and show the results n Fg.. They are n good agreement wth the results shown n [8], and we can conclude that our well-balanced methods capture the complcated soluton well. We also modfy the wdth of the channel by settng d =.6. The bottom topography s kept as B =. The numercal results are shown n Fg., whch also agree well wth the results n [8]. At the end, we ncrease the heght of the mound to B = 2, to smulate the flows through two slands. Our postvty-preservng methods demonstrate to be robust and provde nce results, presented n Fg. 2.

21 J Sc Comput 23 57: Fg. The contours of the water surface level of the convergng dvergng channels problem n Sect. 4.7 wth the parameters d =.9 andb =. Results are based on the trangulaton wth mesh szes τ =.25 left and 6.25E 3 rght, respectvely Fg. The contours of the water surface level of the convergng dvergng channels problem n Sect. 4.7 wth the parameters d =.6 andb =. Results are based on the trangulaton wth mesh szes τ =.25 left and 6.25E 3 rght, respectvely Fg. 2 The contours of the water surface level of the convergng dvergng channels problem n Sect. 4.7 wth the parameters d =.9 andb = 2. Results are based on the trangulaton wth mesh szes τ =.25 left and 6.25E 3 rght, respectvely 5 Concludng Remarks Postvty-preservng well-balanced dscontnuous Galerkn methods have been presented n [36] for the shallow water equatons on one-dmensonal and two-dmensonal problems wth rectangular meshes. In ths paper, we showed that such methods can be naturally extended to unstructured trangular meshes, wth the ntroducton of a specal quadrature rule from [39]. We have demonstrated that ths postvty-preservng lmter can keep the water heght non-negatve under sutable CFL condton, can preserve the mass conservaton, s easy to mplement, and at the same tme does not affect the hgh order accuracy for the general solutons. Extensve numercal examples are provded at the end to demonstrate the well-balanced property, accuracy, postvty-preservng property, and non-oscllatory shock resoluton of the proposed numercal methods. The proposed methods are hghly parallelzable and our ongong work s to nvestgate ther performance on hgh performance computers.

22 4 J Sc Comput 23 57:9 4 Acknowledgments Research of the frst author s sponsored by the Natonal Scence Foundaton grant DMS-26454, ORNL s Laboratory Drected Research and Development funds, and the U. S. Department of Energy, Offce of Advanced Scentfc Computng Research. The work was partally performed at ORNL, whch s managed by UT-Battelle, LLC, under Contract No. DE-AC5-OR References. Audusse, E., Bouchut, F., Brsteau, M.-O., len, R., Perthame, B.: A fast and stable well-balanced scheme wth hydrostatc reconstructon for shallow water flows. SIAM J. Sc. Comput. 25, Bale, D.S., LeVeque, R.J., Mtran, S., Rossmanth, J.A.: A wave propagaton method for conservaton laws and balance laws wth spatally varyng flux functons. SIAM J. Sc. Comput. 24, Bermudez, A., Vazquez, M.E.: Upwnd methods for hyperbolc conservaton laws wth source terms. Comput. Fluds 23, Berthon, C., Marche, F.: A postve preservng hgh order VFRoe scheme for shallow water equatons: a class of relaxaton schemes. SIAM J. Sc. Comput. 3, Bokhove, O.: Floodng and dryng n dscontnuous Galerkn fnte-element dscretzatons of shallowwater equatons. Part : one dmenson. J. Sc. Comput. 22, Bollermann, A., Noelle, S., Lukácová-Medvová, M.: Fnte volume evoluton Galerkn methods for the shallow water equatons wth dry beds. Commun. Comput. Phys., Brufau, P., Vázquez-Cendón, M.E., García-Navarro, P.: A numercal model for the floodng and dryng of rregular domans. Int. J. Numer. Methods Fluds 39, Bryson, S., Epshteyn, Y., urganov, A., Petrova, G.: Well-balanced postvty preservng central-upwnd shceme on trangular grds for the Sant-Venant system. ESAIM. Math. Modell. Numer. Anal. 45, Bunya, S., ubatko, E.J., Westernk, J.J., Dawson, C.: A wettng and dryng treatment for the Runge-utta dscontnuous Galerkn soluton to the shallow water equatons. Comput. Methods Appl. Mech. Eng. 98, Cockburn, B., arnadaks, G., Shu, C.-W.: The development of dscontnuous galerkn methods. In: B. Cockburn, G. arnadaks, C.-W. Shu eds. Dscontnuous Galerkn Methods: Theory, Computaton and Applcatons. Lecture Notes n Computatonal Scence and Engneerng, Part I: Overvew, vol., pp Sprnger, Berln 2. Cockburn, B., Shu, C.-W.: TVB Runge-utta local projecton dscontnuous Galerkn fnte element method for conservaton laws II: general framework. Math. Comput. 52, Cockburn, B., Shu, C.-W.: The Runge-utta dscontnuous Galerkn method for conservaton laws V: multdmensonal systems. J. Comput. Phys. 4, Dawson, C., Proft, J.: Dscontnuous and coupled contnuous/dscontnuous Galerkn methods for the shallow water equatons. Comput. Methods Appl. Mech. Eng. 9, Ern, A., Pperno, S., Djadel,.: A well-balanced Runge-utta dscontnuous Galerkn method for the shallow-water equatons wth floodng and dryng. Int. J. Numer. Methods Fluds 58, Esklsson, C., Sherwn, S.J.: A trangular spectral/hp dscontnuous Galerkn method for modellng 2D shallow water equatons. Int. J. Numer. Methods Fluds 45, Feng, J.-H., Ca, L., Xe, W.-X.: CWENO-type central-upwnd schemes for multdmensonal Sant- Venant system of shallow water equatons. Appl. Numer. Math. 56, Gallardo, J.M., Parés, C., Castro, M.: On a well-balanced hgh-order fnte volume scheme for shallow water equatons wth topography and dry areas. J. Comput. Phys. 227, Graldo, F.X., Hesthaven, J.S., Warburton, T.: Nodal hgh-order dscontnuous Galerkn methods for the sphercal shallow water equatons. J. Comput. Phys. 8, Hubbard, M.E.: On the accuracy of one-dmensonal models of steady convergng/dvergng open channel flows. Int. J. Numer. Methods Fluds 35, esserwan, G., Lang, Q.: Well-balanced RDG2 solutons to the shallow water equatons over rregular domans wth wettng and dryng. Comput. Fluds 39, urganov, A., Levy, D.: Central-upwnd schemes for the Sant-Venant system. Math. Modell. Numer. Anal. 36, LeVeque, R.J.: Balancng source terms and flux gradents on hgh-resoluton Godunov methods: the quas-steady wave-propagaton algorthm. J. Comput. Phys. 46, Nar, R.D., Thomas, S.J., Loft, R.D.: A dscontnuous Galerkn global shallow water model. Mon. Weather Rev. 33,

23 J Sc Comput 23 57: Nceno, B.: EasyMesh Verson.4: A Two-Dmensonal Qualty Mesh Generator. unv.treste.t/nrftc/research/easymesh/ Noelle, S., Xng, Y., Shu, C.-W.: Hgh-order well-balanced schemes. In: Russo, G., Puppo, G. eds. Numercal Methods for Relaxaton Systems and Balance Equatons. Seconda Unversta d Napol, Quadern d Matematca, Italy, Dpartmento d Matematca Perthame, B., Smeon, C.: A knetc scheme for the Sant-Venant system wth a source term. Calcolo 38, Rhebergen, S., Bokhove, O., van der Vegt, J.J.W.: Dscontnuous galerkn fnte element methods for hyperbolc nonconservatve partal dfferental equatons. J. Comput. Phys. 227, San, O., ara,.: Hgh-order acurate spectral dfference method for shallow water equatons. Int. J. Res. Rev. Appl. Sc. 6, Schwanenberg, D., öngeter, J.: A dscontnuous Galerkn method for the shallow water equatons wth source terms. In: B. Cockburn, G. arnadaks, C.-W. Shu eds. Dscontnuous Galerkn Methods: Theory, Computaton and Applcatons. Lecture Notes n Computatonal Scence and Engneerng, Part I: Overvew, vol., pp Sprnger, Berln 2 3. Shu, C.-W.: Tvb unformly hgh-order schemes for conservaton laws. Math. Comput. 49, Shu, C.-W., Osher, S.: Effcent mplementaton of essentally non-oscllatory shock-capturng schemes. J. Comput. Phys. 77, Xng, Y., Shu, C.-W.: Hgh order fnte dfference WENO schemes wth the exact conservaton property for the shallow water equatons. J. Comput. Phys. 28, Xng, Y., Shu, C.-W.: Hgh order well-balanced fnte volume WENO schemes and dscontnuous Galerkn methods for a class of hyperbolc systems wth source terms. J. Comput. Phys. 24, Xng, Y., Shu, C.-W.: A new approach of hgh order well-balanced fnte volume WENO schemes and dscontnuous Galerkn methods for a class of hyperbolc systems wth source terms. Commun. Comput. Phys., Xng, Y., Shu, C.-W.: Hgh-order fnte volume WENO schemes for the shallow water equatons wth dry states. Adv. Water Resourc. 34, Xng, Y., Zhang, X., Shu, C.-W.: Postvty-preservng hgh order well-balanced dscontnuous Galerkn methods for the shallow water equatons. Adv. Water Resourc. 33, Zhang, X., Shu, C.-W.: On maxmum-prncple-satsfyng hgh order schemes for scalar conservaton laws. J. Comput. Phys. 229, Zhang, X., Shu, C.-W.: Maxmum-prncple-satsfyng and postvty-preservng hgh order schemes for conservaton laws: survey and new developments. Proc. R. Soc. A 467, Zhang, X., Xa, Y., Shu, C.-W.: Maxmum-prncple-satsfyng and postvty-preservng hgh order dscontnuous galerkn schemes for conservaton laws on trangular meshes. J. Sc. Comput. 5,

High resolution entropy stable scheme for shallow water equations

High resolution entropy stable scheme for shallow water equations Internatonal Symposum on Computers & Informatcs (ISCI 05) Hgh resoluton entropy stable scheme for shallow water equatons Xaohan Cheng,a, Yufeng Ne,b, Department of Appled Mathematcs, Northwestern Polytechncal

More information

Lecture 12: Discrete Laplacian

Lecture 12: Discrete Laplacian Lecture 12: Dscrete Laplacan Scrbe: Tanye Lu Our goal s to come up wth a dscrete verson of Laplacan operator for trangulated surfaces, so that we can use t n practce to solve related problems We are mostly

More information

Numerical Heat and Mass Transfer

Numerical Heat and Mass Transfer Master degree n Mechancal Engneerng Numercal Heat and Mass Transfer 06-Fnte-Dfference Method (One-dmensonal, steady state heat conducton) Fausto Arpno f.arpno@uncas.t Introducton Why we use models and

More information

Appendix B. The Finite Difference Scheme

Appendix B. The Finite Difference Scheme 140 APPENDIXES Appendx B. The Fnte Dfference Scheme In ths appendx we present numercal technques whch are used to approxmate solutons of system 3.1 3.3. A comprehensve treatment of theoretcal and mplementaton

More information

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE Analytcal soluton s usually not possble when exctaton vares arbtrarly wth tme or f the system s nonlnear. Such problems can be solved by numercal tmesteppng

More information

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems Numercal Analyss by Dr. Anta Pal Assstant Professor Department of Mathematcs Natonal Insttute of Technology Durgapur Durgapur-713209 emal: anta.bue@gmal.com 1 . Chapter 5 Soluton of System of Lnear Equatons

More information

NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS

NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS IJRRAS 8 (3 September 011 www.arpapress.com/volumes/vol8issue3/ijrras_8_3_08.pdf NON-CENTRAL 7-POINT FORMULA IN THE METHOD OF LINES FOR PARABOLIC AND BURGERS' EQUATIONS H.O. Bakodah Dept. of Mathematc

More information

Lecture 5.8 Flux Vector Splitting

Lecture 5.8 Flux Vector Splitting Lecture 5.8 Flux Vector Splttng 1 Flux Vector Splttng The vector E n (5.7.) can be rewrtten as E = AU (5.8.1) (wth A as gven n (5.7.4) or (5.7.6) ) whenever, the equaton of state s of the separable form

More information

More metrics on cartesian products

More metrics on cartesian products More metrcs on cartesan products If (X, d ) are metrc spaces for 1 n, then n Secton II4 of the lecture notes we defned three metrcs on X whose underlyng topologes are the product topology The purpose of

More information

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur Module 3 LOSSY IMAGE COMPRESSION SYSTEMS Verson ECE IIT, Kharagpur Lesson 6 Theory of Quantzaton Verson ECE IIT, Kharagpur Instructonal Objectves At the end of ths lesson, the students should be able to:

More information

Modified Mass Matrices and Positivity Preservation for Hyperbolic and Parabolic PDEs

Modified Mass Matrices and Positivity Preservation for Hyperbolic and Parabolic PDEs COMMUNICATIONS IN NUMERICAL METHODS IN ENGINEERING Commun. Numer. Meth. Engng 2000; 00:6 Prepared usng cnmauth.cls [Verson: 2000/03/22 v.0] Modfed Mass Matrces and Postvty Preservaton for Hyperbolc and

More information

The Finite Element Method

The Finite Element Method The Fnte Element Method GENERAL INTRODUCTION Read: Chapters 1 and 2 CONTENTS Engneerng and analyss Smulaton of a physcal process Examples mathematcal model development Approxmate solutons and methods of

More information

Lab session: numerical simulations of sponateous polarization

Lab session: numerical simulations of sponateous polarization Lab sesson: numercal smulatons of sponateous polarzaton Emerc Boun & Vncent Calvez CNRS, ENS Lyon, France CIMPA, Hammamet, March 2012 Spontaneous cell polarzaton: the 1D case The Hawkns-Voturez model for

More information

page 2 2 dscretzaton mantans ths stablty under a sutable restrcton on the tme step. SSP tme dscretzaton methods were frst developed by Shu n [20] and

page 2 2 dscretzaton mantans ths stablty under a sutable restrcton on the tme step. SSP tme dscretzaton methods were frst developed by Shu n [20] and page 1 A Survey of Strong Stablty Preservng Hgh Order Tme Dscretzatons Ch-Wang Shu Λ 1 Introducton Numercal soluton for ordnary dfferental equatons (ODEs) s an establshed research area. There are many

More information

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS Avalable onlne at http://sck.org J. Math. Comput. Sc. 3 (3), No., 6-3 ISSN: 97-537 COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

More information

4DVAR, according to the name, is a four-dimensional variational method.

4DVAR, according to the name, is a four-dimensional variational method. 4D-Varatonal Data Assmlaton (4D-Var) 4DVAR, accordng to the name, s a four-dmensonal varatonal method. 4D-Var s actually a drect generalzaton of 3D-Var to handle observatons that are dstrbuted n tme. The

More information

NUMERICAL DIFFERENTIATION

NUMERICAL DIFFERENTIATION NUMERICAL DIFFERENTIATION 1 Introducton Dfferentaton s a method to compute the rate at whch a dependent output y changes wth respect to the change n the ndependent nput x. Ths rate of change s called the

More information

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1

Physics 5153 Classical Mechanics. D Alembert s Principle and The Lagrangian-1 P. Guterrez Physcs 5153 Classcal Mechancs D Alembert s Prncple and The Lagrangan 1 Introducton The prncple of vrtual work provdes a method of solvng problems of statc equlbrum wthout havng to consder the

More information

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity Week3, Chapter 4 Moton n Two Dmensons Lecture Quz A partcle confned to moton along the x axs moves wth constant acceleraton from x =.0 m to x = 8.0 m durng a 1-s tme nterval. The velocty of the partcle

More information

A hybrid kinetic WENO scheme for compressible flow simulations

A hybrid kinetic WENO scheme for compressible flow simulations Tenth Internatonal onference on omputatonal Flud Dynamcs (IFD10), Barcelona, Span, July 9-13, 2018 IFD10-389 A hybrd knetc WENO scheme for compressble flow smulatons Hongwe Lu *, hangpng Yu, Xnlang L *orrespondng

More information

Application of B-Spline to Numerical Solution of a System of Singularly Perturbed Problems

Application of B-Spline to Numerical Solution of a System of Singularly Perturbed Problems Mathematca Aeterna, Vol. 1, 011, no. 06, 405 415 Applcaton of B-Splne to Numercal Soluton of a System of Sngularly Perturbed Problems Yogesh Gupta Department of Mathematcs Unted College of Engneerng &

More information

1. Introduction. The present work is devoted to the numerical approximations of weak solutions of the Euler equations: (1.1)

1. Introduction. The present work is devoted to the numerical approximations of weak solutions of the Euler equations: (1.1) STABILITY OF THE MUSCL SCHEMES FOR THE EULER EQUATIONS CHRISTOPHE BERTHON Abstract. The second-order Van-Leer MUSCL schemes are actually one of the most popular hgh order scheme for flud dynamc computatons.

More information

Tensor Smooth Length for SPH Modelling of High Speed Impact

Tensor Smooth Length for SPH Modelling of High Speed Impact Tensor Smooth Length for SPH Modellng of Hgh Speed Impact Roman Cherepanov and Alexander Gerasmov Insttute of Appled mathematcs and mechancs, Tomsk State Unversty 634050, Lenna av. 36, Tomsk, Russa RCherepanov82@gmal.com,Ger@npmm.tsu.ru

More information

One-sided finite-difference approximations suitable for use with Richardson extrapolation

One-sided finite-difference approximations suitable for use with Richardson extrapolation Journal of Computatonal Physcs 219 (2006) 13 20 Short note One-sded fnte-dfference approxmatons sutable for use wth Rchardson extrapolaton Kumar Rahul, S.N. Bhattacharyya * Department of Mechancal Engneerng,

More information

(Online First)A Lattice Boltzmann Scheme for Diffusion Equation in Spherical Coordinate

(Online First)A Lattice Boltzmann Scheme for Diffusion Equation in Spherical Coordinate Internatonal Journal of Mathematcs and Systems Scence (018) Volume 1 do:10.494/jmss.v1.815 (Onlne Frst)A Lattce Boltzmann Scheme for Dffuson Equaton n Sphercal Coordnate Debabrata Datta 1 *, T K Pal 1

More information

Convexity preserving interpolation by splines of arbitrary degree

Convexity preserving interpolation by splines of arbitrary degree Computer Scence Journal of Moldova, vol.18, no.1(52), 2010 Convexty preservng nterpolaton by splnes of arbtrary degree Igor Verlan Abstract In the present paper an algorthm of C 2 nterpolaton of dscrete

More information

A Hybrid Variational Iteration Method for Blasius Equation

A Hybrid Variational Iteration Method for Blasius Equation Avalable at http://pvamu.edu/aam Appl. Appl. Math. ISSN: 1932-9466 Vol. 10, Issue 1 (June 2015), pp. 223-229 Applcatons and Appled Mathematcs: An Internatonal Journal (AAM) A Hybrd Varatonal Iteraton Method

More information

Relaxation Methods for Iterative Solution to Linear Systems of Equations

Relaxation Methods for Iterative Solution to Linear Systems of Equations Relaxaton Methods for Iteratve Soluton to Lnear Systems of Equatons Gerald Recktenwald Portland State Unversty Mechancal Engneerng Department gerry@pdx.edu Overvew Techncal topcs Basc Concepts Statonary

More information

Module 3: Element Properties Lecture 1: Natural Coordinates

Module 3: Element Properties Lecture 1: Natural Coordinates Module 3: Element Propertes Lecture : Natural Coordnates Natural coordnate system s bascally a local coordnate system whch allows the specfcaton of a pont wthn the element by a set of dmensonless numbers

More information

ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION

ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EQUATION Advanced Mathematcal Models & Applcatons Vol.3, No.3, 2018, pp.215-222 ON A DETERMINATION OF THE INITIAL FUNCTIONS FROM THE OBSERVED VALUES OF THE BOUNDARY FUNCTIONS FOR THE SECOND-ORDER HYPERBOLIC EUATION

More information

Difference Equations

Difference Equations Dfference Equatons c Jan Vrbk 1 Bascs Suppose a sequence of numbers, say a 0,a 1,a,a 3,... s defned by a certan general relatonshp between, say, three consecutve values of the sequence, e.g. a + +3a +1

More information

New Method for Solving Poisson Equation. on Irregular Domains

New Method for Solving Poisson Equation. on Irregular Domains Appled Mathematcal Scences Vol. 6 01 no. 8 369 380 New Method for Solvng Posson Equaton on Irregular Domans J. Izadan and N. Karamooz Department of Mathematcs Facult of Scences Mashhad BranchIslamc Azad

More information

Lecture 10 Support Vector Machines II

Lecture 10 Support Vector Machines II Lecture 10 Support Vector Machnes II 22 February 2016 Taylor B. Arnold Yale Statstcs STAT 365/665 1/28 Notes: Problem 3 s posted and due ths upcomng Frday There was an early bug n the fake-test data; fxed

More information

Additional Codes using Finite Difference Method. 1 HJB Equation for Consumption-Saving Problem Without Uncertainty

Additional Codes using Finite Difference Method. 1 HJB Equation for Consumption-Saving Problem Without Uncertainty Addtonal Codes usng Fnte Dfference Method Benamn Moll 1 HJB Equaton for Consumpton-Savng Problem Wthout Uncertanty Before consderng the case wth stochastc ncome n http://www.prnceton.edu/~moll/ HACTproect/HACT_Numercal_Appendx.pdf,

More information

2.29 Numerical Fluid Mechanics

2.29 Numerical Fluid Mechanics REVIEW Lecture 10: Sprng 2015 Lecture 11 Classfcaton of Partal Dfferental Equatons PDEs) and eamples wth fnte dfference dscretzatons Parabolc PDEs Ellptc PDEs Hyperbolc PDEs Error Types and Dscretzaton

More information

On a direct solver for linear least squares problems

On a direct solver for linear least squares problems ISSN 2066-6594 Ann. Acad. Rom. Sc. Ser. Math. Appl. Vol. 8, No. 2/2016 On a drect solver for lnear least squares problems Constantn Popa Abstract The Null Space (NS) algorthm s a drect solver for lnear

More information

Lecture 21: Numerical methods for pricing American type derivatives

Lecture 21: Numerical methods for pricing American type derivatives Lecture 21: Numercal methods for prcng Amercan type dervatves Xaoguang Wang STAT 598W Aprl 10th, 2014 (STAT 598W) Lecture 21 1 / 26 Outlne 1 Fnte Dfference Method Explct Method Penalty Method (STAT 598W)

More information

MMA and GCMMA two methods for nonlinear optimization

MMA and GCMMA two methods for nonlinear optimization MMA and GCMMA two methods for nonlnear optmzaton Krster Svanberg Optmzaton and Systems Theory, KTH, Stockholm, Sweden. krlle@math.kth.se Ths note descrbes the algorthms used n the author s 2007 mplementatons

More information

Linear Approximation with Regularization and Moving Least Squares

Linear Approximation with Regularization and Moving Least Squares Lnear Approxmaton wth Regularzaton and Movng Least Squares Igor Grešovn May 007 Revson 4.6 (Revson : March 004). 5 4 3 0.5 3 3.5 4 Contents: Lnear Fttng...4. Weghted Least Squares n Functon Approxmaton...

More information

NP-Completeness : Proofs

NP-Completeness : Proofs NP-Completeness : Proofs Proof Methods A method to show a decson problem Π NP-complete s as follows. (1) Show Π NP. (2) Choose an NP-complete problem Π. (3) Show Π Π. A method to show an optmzaton problem

More information

Feature Selection: Part 1

Feature Selection: Part 1 CSE 546: Machne Learnng Lecture 5 Feature Selecton: Part 1 Instructor: Sham Kakade 1 Regresson n the hgh dmensonal settng How do we learn when the number of features d s greater than the sample sze n?

More information

Physics 5153 Classical Mechanics. Principle of Virtual Work-1

Physics 5153 Classical Mechanics. Principle of Virtual Work-1 P. Guterrez 1 Introducton Physcs 5153 Classcal Mechancs Prncple of Vrtual Work The frst varatonal prncple we encounter n mechancs s the prncple of vrtual work. It establshes the equlbrum condton of a mechancal

More information

Report on Image warping

Report on Image warping Report on Image warpng Xuan Ne, Dec. 20, 2004 Ths document summarzed the algorthms of our mage warpng soluton for further study, and there s a detaled descrpton about the mplementaton of these algorthms.

More information

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix

Lectures - Week 4 Matrix norms, Conditioning, Vector Spaces, Linear Independence, Spanning sets and Basis, Null space and Range of a Matrix Lectures - Week 4 Matrx norms, Condtonng, Vector Spaces, Lnear Independence, Spannng sets and Bass, Null space and Range of a Matrx Matrx Norms Now we turn to assocatng a number to each matrx. We could

More information

A PROCEDURE FOR SIMULATING THE NONLINEAR CONDUCTION HEAT TRANSFER IN A BODY WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY.

A PROCEDURE FOR SIMULATING THE NONLINEAR CONDUCTION HEAT TRANSFER IN A BODY WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY. Proceedngs of the th Brazlan Congress of Thermal Scences and Engneerng -- ENCIT 006 Braz. Soc. of Mechancal Scences and Engneerng -- ABCM, Curtba, Brazl,- Dec. 5-8, 006 A PROCEDURE FOR SIMULATING THE NONLINEAR

More information

College of Computer & Information Science Fall 2009 Northeastern University 20 October 2009

College of Computer & Information Science Fall 2009 Northeastern University 20 October 2009 College of Computer & Informaton Scence Fall 2009 Northeastern Unversty 20 October 2009 CS7880: Algorthmc Power Tools Scrbe: Jan Wen and Laura Poplawsk Lecture Outlne: Prmal-dual schema Network Desgn:

More information

The Two-scale Finite Element Errors Analysis for One Class of Thermoelastic Problem in Periodic Composites

The Two-scale Finite Element Errors Analysis for One Class of Thermoelastic Problem in Periodic Composites 7 Asa-Pacfc Engneerng Technology Conference (APETC 7) ISBN: 978--6595-443- The Two-scale Fnte Element Errors Analyss for One Class of Thermoelastc Problem n Perodc Compostes Xaoun Deng Mngxang Deng ABSTRACT

More information

A New Refinement of Jacobi Method for Solution of Linear System Equations AX=b

A New Refinement of Jacobi Method for Solution of Linear System Equations AX=b Int J Contemp Math Scences, Vol 3, 28, no 17, 819-827 A New Refnement of Jacob Method for Soluton of Lnear System Equatons AX=b F Naem Dafchah Department of Mathematcs, Faculty of Scences Unversty of Gulan,

More information

CSci 6974 and ECSE 6966 Math. Tech. for Vision, Graphics and Robotics Lecture 21, April 17, 2006 Estimating A Plane Homography

CSci 6974 and ECSE 6966 Math. Tech. for Vision, Graphics and Robotics Lecture 21, April 17, 2006 Estimating A Plane Homography CSc 6974 and ECSE 6966 Math. Tech. for Vson, Graphcs and Robotcs Lecture 21, Aprl 17, 2006 Estmatng A Plane Homography Overvew We contnue wth a dscusson of the major ssues, usng estmaton of plane projectve

More information

Hongyi Miao, College of Science, Nanjing Forestry University, Nanjing ,China. (Received 20 June 2013, accepted 11 March 2014) I)ϕ (k)

Hongyi Miao, College of Science, Nanjing Forestry University, Nanjing ,China. (Received 20 June 2013, accepted 11 March 2014) I)ϕ (k) ISSN 1749-3889 (prnt), 1749-3897 (onlne) Internatonal Journal of Nonlnear Scence Vol.17(2014) No.2,pp.188-192 Modfed Block Jacob-Davdson Method for Solvng Large Sparse Egenproblems Hongy Mao, College of

More information

Chapter 4 The Wave Equation

Chapter 4 The Wave Equation Chapter 4 The Wave Equaton Another classcal example of a hyperbolc PDE s a wave equaton. The wave equaton s a second-order lnear hyperbolc PDE that descrbes the propagaton of a varety of waves, such as

More information

PHYS 705: Classical Mechanics. Calculus of Variations II

PHYS 705: Classical Mechanics. Calculus of Variations II 1 PHYS 705: Classcal Mechancs Calculus of Varatons II 2 Calculus of Varatons: Generalzaton (no constrant yet) Suppose now that F depends on several dependent varables : We need to fnd such that has a statonary

More information

The equation of motion of a dynamical system is given by a set of differential equations. That is (1)

The equation of motion of a dynamical system is given by a set of differential equations. That is (1) Dynamcal Systems Many engneerng and natural systems are dynamcal systems. For example a pendulum s a dynamcal system. State l The state of the dynamcal system specfes t condtons. For a pendulum n the absence

More information

2.29 Numerical Fluid Mechanics Fall 2011 Lecture 12

2.29 Numerical Fluid Mechanics Fall 2011 Lecture 12 REVIEW Lecture 11: 2.29 Numercal Flud Mechancs Fall 2011 Lecture 12 End of (Lnear) Algebrac Systems Gradent Methods Krylov Subspace Methods Precondtonng of Ax=b FINITE DIFFERENCES Classfcaton of Partal

More information

A MODIFIED METHOD FOR SOLVING SYSTEM OF NONLINEAR EQUATIONS

A MODIFIED METHOD FOR SOLVING SYSTEM OF NONLINEAR EQUATIONS Journal of Mathematcs and Statstcs 9 (1): 4-8, 1 ISSN 1549-644 1 Scence Publcatons do:1.844/jmssp.1.4.8 Publshed Onlne 9 (1) 1 (http://www.thescpub.com/jmss.toc) A MODIFIED METHOD FOR SOLVING SYSTEM OF

More information

PARTICIPATION FACTOR IN MODAL ANALYSIS OF POWER SYSTEMS STABILITY

PARTICIPATION FACTOR IN MODAL ANALYSIS OF POWER SYSTEMS STABILITY POZNAN UNIVE RSITY OF TE CHNOLOGY ACADE MIC JOURNALS No 86 Electrcal Engneerng 6 Volodymyr KONOVAL* Roman PRYTULA** PARTICIPATION FACTOR IN MODAL ANALYSIS OF POWER SYSTEMS STABILITY Ths paper provdes a

More information

Some Comments on Accelerating Convergence of Iterative Sequences Using Direct Inversion of the Iterative Subspace (DIIS)

Some Comments on Accelerating Convergence of Iterative Sequences Using Direct Inversion of the Iterative Subspace (DIIS) Some Comments on Acceleratng Convergence of Iteratve Sequences Usng Drect Inverson of the Iteratve Subspace (DIIS) C. Davd Sherrll School of Chemstry and Bochemstry Georga Insttute of Technology May 1998

More information

Positivity-preserving time discretizations for production-destruction equations. with applications to non-equilibrium flows.

Positivity-preserving time discretizations for production-destruction equations. with applications to non-equilibrium flows. Postvty-preservng tme dscretzatons for producton-destructon equatons wth applcatons to non-equlbrum flows Juntao Huang and Ch-Wang Shu Abstract In ths paper, we construct a famly of modfed Patankar Runge-Kutta

More information

Inductance Calculation for Conductors of Arbitrary Shape

Inductance Calculation for Conductors of Arbitrary Shape CRYO/02/028 Aprl 5, 2002 Inductance Calculaton for Conductors of Arbtrary Shape L. Bottura Dstrbuton: Internal Summary In ths note we descrbe a method for the numercal calculaton of nductances among conductors

More information

Affine transformations and convexity

Affine transformations and convexity Affne transformatons and convexty The purpose of ths document s to prove some basc propertes of affne transformatons nvolvng convex sets. Here are a few onlne references for background nformaton: http://math.ucr.edu/

More information

Module 1 : The equation of continuity. Lecture 1: Equation of Continuity

Module 1 : The equation of continuity. Lecture 1: Equation of Continuity 1 Module 1 : The equaton of contnuty Lecture 1: Equaton of Contnuty 2 Advanced Heat and Mass Transfer: Modules 1. THE EQUATION OF CONTINUITY : Lectures 1-6 () () () (v) (v) Overall Mass Balance Momentum

More information

Note 10. Modeling and Simulation of Dynamic Systems

Note 10. Modeling and Simulation of Dynamic Systems Lecture Notes of ME 475: Introducton to Mechatroncs Note 0 Modelng and Smulaton of Dynamc Systems Department of Mechancal Engneerng, Unversty Of Saskatchewan, 57 Campus Drve, Saskatoon, SK S7N 5A9, Canada

More information

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal

Inner Product. Euclidean Space. Orthonormal Basis. Orthogonal Inner Product Defnton 1 () A Eucldean space s a fnte-dmensonal vector space over the reals R, wth an nner product,. Defnton 2 (Inner Product) An nner product, on a real vector space X s a symmetrc, blnear,

More information

FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP

FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP C O L L O Q U I U M M A T H E M A T I C U M VOL. 80 1999 NO. 1 FACTORIZATION IN KRULL MONOIDS WITH INFINITE CLASS GROUP BY FLORIAN K A I N R A T H (GRAZ) Abstract. Let H be a Krull monod wth nfnte class

More information

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0

n α j x j = 0 j=1 has a nontrivial solution. Here A is the n k matrix whose jth column is the vector for all t j=0 MODULE 2 Topcs: Lnear ndependence, bass and dmenson We have seen that f n a set of vectors one vector s a lnear combnaton of the remanng vectors n the set then the span of the set s unchanged f that vector

More information

Weighted Fifth Degree Polynomial Spline

Weighted Fifth Degree Polynomial Spline Pure and Appled Mathematcs Journal 5; 4(6): 69-74 Publshed onlne December, 5 (http://www.scencepublshnggroup.com/j/pamj) do:.648/j.pamj.546.8 ISSN: 36-979 (Prnt); ISSN: 36-98 (Onlne) Weghted Ffth Degree

More information

Salmon: Lectures on partial differential equations. Consider the general linear, second-order PDE in the form. ,x 2

Salmon: Lectures on partial differential equations. Consider the general linear, second-order PDE in the form. ,x 2 Salmon: Lectures on partal dfferental equatons 5. Classfcaton of second-order equatons There are general methods for classfyng hgher-order partal dfferental equatons. One s very general (applyng even to

More information

Snce h( q^; q) = hq ~ and h( p^ ; p) = hp, one can wrte ~ h hq hp = hq ~hp ~ (7) the uncertanty relaton for an arbtrary state. The states that mnmze t

Snce h( q^; q) = hq ~ and h( p^ ; p) = hp, one can wrte ~ h hq hp = hq ~hp ~ (7) the uncertanty relaton for an arbtrary state. The states that mnmze t 8.5: Many-body phenomena n condensed matter and atomc physcs Last moded: September, 003 Lecture. Squeezed States In ths lecture we shall contnue the dscusson of coherent states, focusng on ther propertes

More information

A new construction of 3-separable matrices via an improved decoding of Macula s construction

A new construction of 3-separable matrices via an improved decoding of Macula s construction Dscrete Optmzaton 5 008 700 704 Contents lsts avalable at ScenceDrect Dscrete Optmzaton journal homepage: wwwelsevercom/locate/dsopt A new constructon of 3-separable matrces va an mproved decodng of Macula

More information

Global Sensitivity. Tuesday 20 th February, 2018

Global Sensitivity. Tuesday 20 th February, 2018 Global Senstvty Tuesday 2 th February, 28 ) Local Senstvty Most senstvty analyses [] are based on local estmates of senstvty, typcally by expandng the response n a Taylor seres about some specfc values

More information

Uniqueness of Weak Solutions to the 3D Ginzburg- Landau Model for Superconductivity

Uniqueness of Weak Solutions to the 3D Ginzburg- Landau Model for Superconductivity Int. Journal of Math. Analyss, Vol. 6, 212, no. 22, 195-114 Unqueness of Weak Solutons to the 3D Gnzburg- Landau Model for Superconductvty Jshan Fan Department of Appled Mathematcs Nanjng Forestry Unversty

More information

Errors for Linear Systems

Errors for Linear Systems Errors for Lnear Systems When we solve a lnear system Ax b we often do not know A and b exactly, but have only approxmatons  and ˆb avalable. Then the best thng we can do s to solve ˆx ˆb exactly whch

More information

The Exact Formulation of the Inverse of the Tridiagonal Matrix for Solving the 1D Poisson Equation with the Finite Difference Method

The Exact Formulation of the Inverse of the Tridiagonal Matrix for Solving the 1D Poisson Equation with the Finite Difference Method Journal of Electromagnetc Analyss and Applcatons, 04, 6, 0-08 Publshed Onlne September 04 n ScRes. http://www.scrp.org/journal/jemaa http://dx.do.org/0.46/jemaa.04.6000 The Exact Formulaton of the Inverse

More information

U.C. Berkeley CS294: Beyond Worst-Case Analysis Luca Trevisan September 5, 2017

U.C. Berkeley CS294: Beyond Worst-Case Analysis Luca Trevisan September 5, 2017 U.C. Berkeley CS94: Beyond Worst-Case Analyss Handout 4s Luca Trevsan September 5, 07 Summary of Lecture 4 In whch we ntroduce semdefnte programmng and apply t to Max Cut. Semdefnte Programmng Recall that

More information

The Order Relation and Trace Inequalities for. Hermitian Operators

The Order Relation and Trace Inequalities for. Hermitian Operators Internatonal Mathematcal Forum, Vol 3, 08, no, 507-57 HIKARI Ltd, wwwm-hkarcom https://doorg/0988/mf088055 The Order Relaton and Trace Inequaltes for Hermtan Operators Y Huang School of Informaton Scence

More information

ALGORITHM FOR THE CALCULATION OF THE TWO VARIABLES CUBIC SPLINE FUNCTION

ALGORITHM FOR THE CALCULATION OF THE TWO VARIABLES CUBIC SPLINE FUNCTION ANALELE ŞTIINŢIFICE ALE UNIVERSITĂŢII AL.I. CUZA DIN IAŞI (S.N.) MATEMATICĂ, Tomul LIX, 013, f.1 DOI: 10.478/v10157-01-00-y ALGORITHM FOR THE CALCULATION OF THE TWO VARIABLES CUBIC SPLINE FUNCTION BY ION

More information

THE EFFECT OF TORSIONAL RIGIDITY BETWEEN ELEMENTS ON FREE VIBRATIONS OF A TELESCOPIC HYDRAULIC CYLINDER SUBJECTED TO EULER S LOAD

THE EFFECT OF TORSIONAL RIGIDITY BETWEEN ELEMENTS ON FREE VIBRATIONS OF A TELESCOPIC HYDRAULIC CYLINDER SUBJECTED TO EULER S LOAD Journal of Appled Mathematcs and Computatonal Mechancs 7, 6(3), 7- www.amcm.pcz.pl p-issn 99-9965 DOI:.75/jamcm.7.3. e-issn 353-588 THE EFFECT OF TORSIONAL RIGIDITY BETWEEN ELEMENTS ON FREE VIBRATIONS

More information

1-Dimensional Advection-Diffusion Finite Difference Model Due to a Flow under Propagating Solitary Wave

1-Dimensional Advection-Diffusion Finite Difference Model Due to a Flow under Propagating Solitary Wave 014 4th Internatonal Conference on Future nvronment and nergy IPCB vol.61 (014) (014) IACSIT Press, Sngapore I: 10.776/IPCB. 014. V61. 6 1-mensonal Advecton-ffuson Fnte fference Model ue to a Flow under

More information

On the Interval Zoro Symmetric Single-step Procedure for Simultaneous Finding of Polynomial Zeros

On the Interval Zoro Symmetric Single-step Procedure for Simultaneous Finding of Polynomial Zeros Appled Mathematcal Scences, Vol. 5, 2011, no. 75, 3693-3706 On the Interval Zoro Symmetrc Sngle-step Procedure for Smultaneous Fndng of Polynomal Zeros S. F. M. Rusl, M. Mons, M. A. Hassan and W. J. Leong

More information

SIMULATION OF WAVE PROPAGATION IN AN HETEROGENEOUS ELASTIC ROD

SIMULATION OF WAVE PROPAGATION IN AN HETEROGENEOUS ELASTIC ROD SIMUATION OF WAVE POPAGATION IN AN HETEOGENEOUS EASTIC OD ogéro M Saldanha da Gama Unversdade do Estado do o de Janero ua Sào Francsco Xaver 54, sala 5 A 559-9, o de Janero, Brasl e-mal: rsgama@domancombr

More information

Generalized Linear Methods

Generalized Linear Methods Generalzed Lnear Methods 1 Introducton In the Ensemble Methods the general dea s that usng a combnaton of several weak learner one could make a better learner. More formally, assume that we have a set

More information

General viscosity iterative method for a sequence of quasi-nonexpansive mappings

General viscosity iterative method for a sequence of quasi-nonexpansive mappings Avalable onlne at www.tjnsa.com J. Nonlnear Sc. Appl. 9 (2016), 5672 5682 Research Artcle General vscosty teratve method for a sequence of quas-nonexpansve mappngs Cuje Zhang, Ynan Wang College of Scence,

More information

The Minimum Universal Cost Flow in an Infeasible Flow Network

The Minimum Universal Cost Flow in an Infeasible Flow Network Journal of Scences, Islamc Republc of Iran 17(2): 175-180 (2006) Unversty of Tehran, ISSN 1016-1104 http://jscencesutacr The Mnmum Unversal Cost Flow n an Infeasble Flow Network H Saleh Fathabad * M Bagheran

More information

U.C. Berkeley CS294: Spectral Methods and Expanders Handout 8 Luca Trevisan February 17, 2016

U.C. Berkeley CS294: Spectral Methods and Expanders Handout 8 Luca Trevisan February 17, 2016 U.C. Berkeley CS94: Spectral Methods and Expanders Handout 8 Luca Trevsan February 7, 06 Lecture 8: Spectral Algorthms Wrap-up In whch we talk about even more generalzatons of Cheeger s nequaltes, and

More information

EEE 241: Linear Systems

EEE 241: Linear Systems EEE : Lnear Systems Summary #: Backpropagaton BACKPROPAGATION The perceptron rule as well as the Wdrow Hoff learnng were desgned to tran sngle layer networks. They suffer from the same dsadvantage: they

More information

Lecture Notes on Linear Regression

Lecture Notes on Linear Regression Lecture Notes on Lnear Regresson Feng L fl@sdueducn Shandong Unversty, Chna Lnear Regresson Problem In regresson problem, we am at predct a contnuous target value gven an nput feature vector We assume

More information

Kernel Methods and SVMs Extension

Kernel Methods and SVMs Extension Kernel Methods and SVMs Extenson The purpose of ths document s to revew materal covered n Machne Learnng 1 Supervsed Learnng regardng support vector machnes (SVMs). Ths document also provdes a general

More information

Additive Schwarz Method for DG Discretization of Anisotropic Elliptic Problems

Additive Schwarz Method for DG Discretization of Anisotropic Elliptic Problems Addtve Schwarz Method for DG Dscretzaton of Ansotropc Ellptc Problems Maksymlan Dryja 1, Potr Krzyżanowsk 1, and Marcus Sarks 2 1 Introducton In the paper we consder a second order ellptc problem wth dscontnuous

More information

An efficient algorithm for multivariate Maclaurin Newton transformation

An efficient algorithm for multivariate Maclaurin Newton transformation Annales UMCS Informatca AI VIII, 2 2008) 5 14 DOI: 10.2478/v10065-008-0020-6 An effcent algorthm for multvarate Maclaurn Newton transformaton Joanna Kapusta Insttute of Mathematcs and Computer Scence,

More information

Maejo International Journal of Science and Technology

Maejo International Journal of Science and Technology Maejo Int. J. Sc. Technol. () - Full Paper Maejo Internatonal Journal of Scence and Technology ISSN - Avalable onlne at www.mjst.mju.ac.th Fourth-order method for sngularly perturbed sngular boundary value

More information

A constant recursive convolution technique for frequency dependent scalar wave equation based FDTD algorithm

A constant recursive convolution technique for frequency dependent scalar wave equation based FDTD algorithm J Comput Electron (213) 12:752 756 DOI 1.17/s1825-13-479-2 A constant recursve convoluton technque for frequency dependent scalar wave equaton bed FDTD algorthm M. Burak Özakın Serkan Aksoy Publshed onlne:

More information

Problem Set 9 Solutions

Problem Set 9 Solutions Desgn and Analyss of Algorthms May 4, 2015 Massachusetts Insttute of Technology 6.046J/18.410J Profs. Erk Demane, Srn Devadas, and Nancy Lynch Problem Set 9 Solutons Problem Set 9 Solutons Ths problem

More information

A CHARACTERIZATION OF ADDITIVE DERIVATIONS ON VON NEUMANN ALGEBRAS

A CHARACTERIZATION OF ADDITIVE DERIVATIONS ON VON NEUMANN ALGEBRAS Journal of Mathematcal Scences: Advances and Applcatons Volume 25, 2014, Pages 1-12 A CHARACTERIZATION OF ADDITIVE DERIVATIONS ON VON NEUMANN ALGEBRAS JIA JI, WEN ZHANG and XIAOFEI QI Department of Mathematcs

More information

Georgia Tech PHYS 6124 Mathematical Methods of Physics I

Georgia Tech PHYS 6124 Mathematical Methods of Physics I Georga Tech PHYS 624 Mathematcal Methods of Physcs I Instructor: Predrag Cvtanovć Fall semester 202 Homework Set #7 due October 30 202 == show all your work for maxmum credt == put labels ttle legends

More information

COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD

COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD COMPOSITE BEAM WITH WEAK SHEAR CONNECTION SUBJECTED TO THERMAL LOAD Ákos Jósef Lengyel, István Ecsed Assstant Lecturer, Professor of Mechancs, Insttute of Appled Mechancs, Unversty of Mskolc, Mskolc-Egyetemváros,

More information

Lecture 20: Lift and Project, SDP Duality. Today we will study the Lift and Project method. Then we will prove the SDP duality theorem.

Lecture 20: Lift and Project, SDP Duality. Today we will study the Lift and Project method. Then we will prove the SDP duality theorem. prnceton u. sp 02 cos 598B: algorthms and complexty Lecture 20: Lft and Project, SDP Dualty Lecturer: Sanjeev Arora Scrbe:Yury Makarychev Today we wll study the Lft and Project method. Then we wll prove

More information

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X

3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number

More information

Canonical transformations

Canonical transformations Canoncal transformatons November 23, 2014 Recall that we have defned a symplectc transformaton to be any lnear transformaton M A B leavng the symplectc form nvarant, Ω AB M A CM B DΩ CD Coordnate transformatons,

More information

A new Approach for Solving Linear Ordinary Differential Equations

A new Approach for Solving Linear Ordinary Differential Equations , ISSN 974-57X (Onlne), ISSN 974-5718 (Prnt), Vol. ; Issue No. 1; Year 14, Copyrght 13-14 by CESER PUBLICATIONS A new Approach for Solvng Lnear Ordnary Dfferental Equatons Fawz Abdelwahd Department of

More information

Yong Joon Ryang. 1. Introduction Consider the multicommodity transportation problem with convex quadratic cost function. 1 2 (x x0 ) T Q(x x 0 )

Yong Joon Ryang. 1. Introduction Consider the multicommodity transportation problem with convex quadratic cost function. 1 2 (x x0 ) T Q(x x 0 ) Kangweon-Kyungk Math. Jour. 4 1996), No. 1, pp. 7 16 AN ITERATIVE ROW-ACTION METHOD FOR MULTICOMMODITY TRANSPORTATION PROBLEMS Yong Joon Ryang Abstract. The optmzaton problems wth quadratc constrants often

More information