Analysis of the two-point velocity correlations. in turbulent boundary layer ows. By M. Oberlack

Size: px
Start display at page:

Download "Analysis of the two-point velocity correlations. in turbulent boundary layer ows. By M. Oberlack"

Transcription

1 Center for Turbulence Research Annual Research Brefs Analyss of the two-pont velocty correlatons n turbulent boundary layer ows By M. Oberlack. Motvaton obectves Two-pont Rapd Dstorton Theory (RDT) has become an mportant tool n the theory of homogeneous turbulence. Modelers try to mplement approprate results from RDT n ther statstcal turbulence models, for example n the structure based model developed by Kassnos Reynolds (994). On the other h, n non-homogeneous equlbrum ows the logarthmc law s one of the cornerstones n statstcal turbulence theory. Expermentalsts have found the log-law n a broad varety of derent turbulent wall shear ows, statstcal models have been made to be consstent wth the log-law. The logarthmc law was rst derved by von Karman (930a, 930b) usng dmensonal arguments. Later Mllkan (939) derved the law-of-the-wall more formally usng the so called \velocty defect law", also rst ntroduced by von Karman (930b). Even though the dervaton was much more comprehensve from a physcal pont of vew, the velocty defect law s essentally an emprcal observaton. A rst dervaton of the law-of-the-wall usng asymptotc methods n the Naver- Stokes equatons was gven by Mellor (972). Mellor needed the vscous sub-layer to obtan the log-regon, hs scalng of the nertal range n the log-regon s n error because t does not gve the one-pont lmt of producton equals dsspaton. The general obectve of the present work s to explore the use of RDT n analyss of the two-pont statstcs of the log-layer. RDT s applcable only to unsteady ows where the non-lnear turbulence-turbulence nteracton can be neglected n comparson to lnear turbulence-mean nteractons. Here we propose to use RDT to examne the structure of the large energy-contanng scales ther nteracton wth the mean ow n the log-regon. The contents of the work are twofold: Frst, two-pont analyss methods wll be used to derve the law-of-the-wall for the specal case of zero mean pressure gradent. The basc assumptons needed are one-dmensonalty n the mean ow homogenety of the uctuatons. It wll be shown that a formal soluton of the two-pont correlaton equaton can be obtaned as a power seres n the von Karman constant, known to be on the order of 0:4. In the second part, a detaled analyss of the two-pont correlaton functon n the log-layer wll be gven. The fundamental set of equatons a functonal relaton for the two-pont correlaton functon wll be derved. An asymptotc expanson procedure wll be used n the log-layer to match Kolmogorov's unversal range the one-pont correlatons to the nvscd outer regon vald for large correlaton dstances.

2 20 M. Oberlack 2. Governng equatons of the two-pont velocty correlaton functon Usng the stard Reynolds decomposton U =u + u P =p + p, the Reynolds averaged Naver Stokes (RANS) k = p u u k k 2 k the uctuaton equaton, later on referred to as N -equaton, s N @u k + u k u k The correspondng contnuty equatons are u 2 k =0 : k k =0 : (3) The ve two-pont correlaton tensor functons that appear n the two-pont correlaton equaton (5), further below, are dened as R (x r t) =u (x t) u (x () t) pu (x r t) =p(x t) u (x () t) u p(x r t) =u (x t) p(x () t) R (k) (x r t) =u (x t) u k (x t) u (x () t) R (k) (x r t) =u (x t) u (x () t) u k (x () t) : (4) All tensors n (4) are functons of the physcal the correlaton space coordnates x r = x () ; x respectvely. The double two-pont correlaton R, later on smply referred to as two-pont correlaton, converges to the Reynolds stress tensor u u n the lmt of zero separaton r. The well known two-pont correlaton equaton (Rotta (972)) can be wrtten as DR (x (x t) = ;R k ; R k (k) R(k) ; R k x+r ; [u k (x + r t) ; u k k 2 k ; k R (5) For both two-pont velocty-pressure correlatons, u p pu aposson equaton can be derved. The of equaton (5) leads to a Posson equaton for pu,

3 Two-pont velocty correlatons n turbulent boundary layers 2 x 2 ū (x 2 ) x x 3 Fgure. Sketch of the coordnate system the mean velocty pu ; pu k 2 R l ; R l R l = k k (6) the leads to the correspondng Posson equaton for u 2 u p = k(x l k R l (7) where the vertcal lne means that the dervatve s taken wth respect to x but wll be evaluated at x + r. All of the dependent varables n (5){(7) have to satsfy the =0 p p =0 @r For the analyss of the self-smlar, two-pont correlaton equaton further below, two denttes are mportant. They can easly be derved from a geometrcal consderaton by nterchangng the two ponts x x () = x + r R (x r) =R (x + r ;r) u p(x r) =pu (x + r ;r) : (0) The latter denttes are the key elements for the dervaton of some boundary condtons for the deeper understng of the self-smlar two-pont correlatons. There exsts a smlar dentty for the trple correlaton whch wll not be used here.

4 22 M. Oberlack 3. The log-law { a self-smlar form of the two-pont correlaton equaton Asketch of the coordnate system the mean velocty eld adopted n the proceedng paper s gven n Fg.. Wthn ths subsecton t wll be shown that the logarthmc part of the law-of-the-wall mean velocty prole can be derved from the two-pont correlaton equaton hence from the Naver-Stokes equaton f there exsts a regme where the followng assumptons hold: the mean velocty s parallel to the wall the statstcs n that doman are ndependent of vscosty tme the Reynolds number s hgh no mean pressure acts on the ow eld. The last assumpton can be elmnated, but n ths approach t wll be focused on the zero pressure gradent case. Besde the above assumptons no other condtons are needed n order to determne the log-law mean velocty prole the selfsmlarty of the correlaton functons. Inferrng the above assumpton n the Reynolds averaged Naver-Stokes equatons (), t s easy to conrm that the gradent of the Reynolds stress tensor on the rght h sde s the only remanng term. Integrated one tme we obtan that u u s ndependent ofx. However, ths s not necessarly true for the two-pont correlaton tensor R. It could depend on x f the dependence vanshes n the zero separaton lmt. Ths can only be acheved by havng the followng dependence on a new varable ~r = rg(x) () where g(x) has to be determned later no other hdden dependence on x can be n the correlaton functons. Of course, the latter denton of ~r can be generalzed to derent unknown scalng functons for every component of r, but from equaton (5) t can be vered that only a sngle scalng functon exsts. Wth the above gven assumptons, denng x = ~x usng the @~x + g the R -equaton (5) = k 0=;R 2 du (x 2 ) dx 2 ; R 2 du (x 2 ) dx 2 x2 +r 2 ; [u (x 2 + r 2 ) ; u (x 2 @pu ~r k ; + @~r k ~r l k R(k) ; R (k) : (3)

5 Two-pont velocty correlatons n turbulent boundary layers 23 As mentoned above, there s no hdden x dependence n the correlaton functon therefore all ~x dervatves comng from (2a) have been omtted. Obvously, equaton (3) can only have a non-trval soluton, thus be ndependent of x, f all the coecents have the same functonal dependence on x. Hence, the followng set of derental equatons determne the u g dependence on g for = 2 3 du (x 2 ) dx 2 g (4) g du (x 2 ) = f (~r) 6= f 2 (x) u (x 2 + r 2 ) ; u (x 2 )=f 3 (~r) 6= f 4 (x) : (5) dx 2 x+r are addtonal consstency condtons for u g. The last equaton n (4) determnes g to depend only on x 2. Hence, the equatons (4) have two ndependent sets of solutons gven by g(x 2 )= c () 2 (x 2 ; c () ) u (x 2 )= c () 3 c () 2 ln(x 2 ; c () )+c() 4 (6) g(x 2 )=c (2) u (x 2 )=c (2) 2 c(2) x 2 + c (2) 3 (7) where the c (p) q 's are ntegraton constants or proportonalty factors. Obvously, only the rst set of equatons correspond to a boundary layer ow because the solutons (7) dene homogeneous shear turbulence whch contradcts the assumpton to be ndependent of tme. Both equatons (5) requre c () = 0 c () 2 can be absorbed n the correlaton functons. In common notaton we nally obtan u = u ln(x 2)+C (8) ~r = r x 2 (9) where u s dened as u = s du dx 2 x2 =0 : (20) Insertng (8) (9) nto equaton (3) multplyng by the von Karman constant the nal form of the R -equaton results:

6 24 M. Oberlack 0=;R 2 ; R 2 ; ln( + ~r 2 +~r 2 ~r k (2) + ~r l R ; R (k) k (2) where R = R u 2 R (k) = R (k) u 3 R (k) = R (k) u 3 pu = pu u 3 u p = u p (22) The procedure descrbed above can be extended to the three-pont trple-correlaton equaton any hgher order correlaton equaton f an addtonal spatal pont sntroduced for each addtonal tensor order. As a result t s easy to verfy that the whole set of equatons dene an nnte set of lnear tensor equatons but whch are far too complex to be solved n general. Nevertheless, t s worthwhle to analyze some features of the soluton. In prncple ths nnte set of equatons could be solved by the followng procedure. Begnnng wth the two-pont correlaton equaton, the trple correlaton can be consdered as an nhomogeneous part of the R equaton. Once the homogeneous soluton s obtaned, the nhomogeneous soluton can be computed by stard methods. In the next step, the trple-correlaton equaton has to be tackled ts soluton wll be substtuted n the soluton for R, so forth for hgher correlatons. In each equaton the von Karman constant only appears as a factor of the hghest order tensor hence the nal soluton for R s a power seres n a (0) R = X m=0 u 3 a (m) m : (23) represents the soluton of the two-pont correlaton equaton after neglectng the trple-correlatons all hgher order terms. The structure of the formal soluton n equaton (23) admts the hope that a truncated seres may provde some nsght n the log-law statstcs. Hence, n the followng the trple-correlatons wll be neglected. Usng the smlarty varable n the posson the contnuty equatons, the pu equaton (6) becomes : ~r k ~r 2 k ~r l k ~r 2 pu +2~r k ~r +2~r 2 = (24) the u p equaton (7) becomes

7 Two-pont velocty correlatons n turbulent boundary layers 2 u k ~r k = ; 2 the contnuty equatons (8) (9) yeld ~r @u 2 p =0 k +~r @~r =0 (26) =0 : (27) The denttes (0) can also be transformed n a smlar manner. Introducng the transformaton (9) nto the equaton (0a), we obtan the relaton R (x 2 x 2 ~r) = R (x 2 ( + ~r 2 ) ;x 2 ~r). Because t was prevously assumed that all two-pont correlaton functons are solely functons of ~r, only the rato of the rst the second parameter can appear n R. Ths argumentaton can be extended to the pressure velocty correlaton. Thus, we nally obtan R (~r) ;~r =R (28) +~r 2 u p (~r) =pu ;~r +~r 2 : (29) The latter dentty also holds f u p pu are nterchanged. These two relatons gve valuable nsght nto the structure of the soluton. Relaton (28) connects derent ~r domans to each other provdes boundary condtons n the ~r 2 drecton. One nterestng feature of (28) s that t can be consdered as a functonal equaton for each trace element. It s easy to verfy that one soluton, but probably not the most general soluton to equaton (28), s gven by the followng form R [] (~r) =F ln( + ~r 2 ) 2 ~r ~r 2 ~r 3 ~r 2 where R s one of the three trace elements of [] R. In addton f the soluton for any o-dagonal R element ( 6= ) sknown, (28) provdes the soluton for the R. A smlar feature for u p pu s gven by relaton (29). If boundary condtons have to be satsed n nnty, all correlaton functons decay to zero. Therefore, any soluton of equatons (2) (24){(27) have toobey the boundary condtons (30) R (~r k!)=pu (~r k!)=u p (~r k!)=0 for k = 3 (3)

8 26 M. Oberlack x 2 = r 2 x 2 r 2 x 2 =0 r 2 Fgure 2. Sketch of the boundary condton n the x 2 -r 2 plane. R (~r 2!)=pu (~r 2!)=u p (~r 2!)=0 : (32) To better underst the boundary condtons n the wall-normal drecton, a sketch ofthex 2 -r 2 plane s gven n Fg. 2. Pckng any value for x 2, the negatve part of r 2 can not be smaller than x 2 hence one bound s on the lne x 2 = ;r 2. The bound for the physcal coordnate s at x 2 =0. Usng the denton of the scaled non-dmensonal coordnate (9), t s clear from Fg. 2 that ~r 2 represents the nverse of the slope gven by any straght lne through the orgn rangng between the two latter bounds. Hence, the doman for ~r 2 s restrcted to ; ~r 2 <. Usng (28) (29) together wth (32) one obtans R (~r 2 = ;) = 0 (33) pu (~r 2 = ;) = u p (~r 2 = ;) = 0 : (34) Obvously, the boundary condtons are all homogeneous one may expect the soluton to be zero. In secton (5) t wll be dscussed why the equatons mght have a non-trval soluton, but a rgorous proof s stll outstng. In the next secton an ntegral relaton comng from the one-pont equatons wll be derved, whch closes the mssng nformaton regardng the scalng of the two-pont correlatons. 4. Kolmogorov's unversal range one-pont correlatons The self-smlarty of the correlaton functons ntroduced n secton 3 s only vald n the lmt of large Reynolds number, based on the wall dstance the frcton velocty Re = u x 2 (35)

9 Two-pont velocty correlatons n turbulent boundary layers 27 Ths s also the denton of y +.From experments t s known that the log regon starts at about y + = 40 extends to y + =0:2U=. The analyss n the prevous chapters s nvscd, hence s not a regular expanson n Re. It s not applcable for small correlaton dstances, as wll be explaned n some detal now. An nner vscous layer n correlaton space has to be ntroduced n order to meet the requrement that vscosty s mportant for the dsspaton tensor " n the one-pont lmt. Comparng the two-pont correlaton equaton (5) n ts most general form to the nvscd verson n the log-layer (2), no vscous term has been retaned. In contrast to that, the Reynolds stress transport equaton n the log-layer ; [u u 2 + u 2 u ] u x 2 + ; " =0 (36) contans the vscosty n the dsspaton tensor, dened by @2 R =2 lm k k the pressure-stran tensor s dened by = + (37) : (38) The contracton of equaton (36) together wth u u 2 = ;u 2 determnes the scalar dsspaton " = " kk 2 = u3 x 2 : (39) As mentoned above we nd from equaton (36) that the asymptotc arguments we have used so far are not vald for correlaton dstances on the order of the Kolmogorov length scale l. The Kolmogorov length velocty scale are gven by 3 4 l = = x2 Re ; u =(") 4 = u Re ; 4 ; 4 : (40) " The only scalng of the ndependent varables wth whch the correct balance can be acheved n the two-pont correlaton equaton s gven by = r l = Re 3 4 ; 4 r x 2 : (4) In lne of Kolmogorov's arguments, the scalng of the dependent varables must be R = u 2 u u ; u 2 R (k) = u 3 h B (0) h D (0) (k) ()+O ()+O Re ; 4 Re ; 4

10 28 M. Oberlack h R (k) = u 3 D (0) ()+O Re ; 4 (k) pu = u 3 u p = u 3 h h M (0) N (0) ()+O ()+O Re ; 4 Re ; 4 : (42) Puttng (4) (42) nto (5), (6) (7) the leadng order terms n each equaton are gven by ; u 2 u ; u u @ ; (0) B (0) k (0) (k) 2 M k = (0) D(kl) 2 N (0) = k (0) l : (45) In order to obtan a unform soluton there must an overlappng regon that matches the nner the outer soluton together. From (42a) we see that the lmt!n the nner layer of the two-pont correlaton converges to the Reynolds stress tensor the same must be vald for a soluton of the equatons (2) (24){(29) n the outer layer for the lmt ~r! 0. Usng the same lmts for both regons n the trple- the pressure-velocty correlatons, they both drop to zero as they should do. As a result, the matchng between the nertal subrange obvously speces the outer soluton R at r = 0 to be u u, but the actual numercal value of Reynolds stress tensor s stll unknown. Note, that the equaton correspondng to (43) n Mellor's paper (972) (hs equaton (59)) has a serous error. It does not have the producton terms whch, of course, are responsble for the energy transfer rate. As mentoned above the nner layer does not determne the absolute value of the Reynolds stress tensor because the trple correlatons can not be neglected n (43){(45). Thus an addtonal assumpton s needed to determne the values of u u. In Kolmogorov's orgnal hypotheses t was suggested that n the lmt of large Reynolds number the dsspaton wll be sotropc. Saddough's (994) very hgh Reynolds number experment of a turbulent boundary layer n a wnd tunnel supports ths dea of sotropy. Hence, we take " = 2 3 " : (46) Usng ths, the three trace elements of can be obtaned from the Reynolds Stress tensor equaton whch n non-dmensonal form can be wrtten as

11 Two-pont velocty correlatons n turbulent boundary layers 29 ; [u u 2 + u 2 u ]+ ; 2 3 =0 wth = x 2 u 3 or n component notaton (47) = ; = = 2 3 : (48) Note, that the latter result for the pressure-stran correlaton holds no matter what s assumed for the trple-correlatons. As a result, all hgh Reynolds number secondmoment closure models should be consstent wth ths result. In most second moment models ths could only be ensured by addng wall reecton terms to the pressure-stran model. Because the system (2) (24){(29) has homogeneous boundary condtons on all boundares, there s nothng that speces the ampltude of R or the value of u u as mentoned above. In fact, ths would also be true f hgher correlaton functons would have been taken nto account. The denton (38) together wth the result (48) can be used to calculate the values for the Reynolds stress tensor. The term on the rght-h sde of (38) can be rewrtten as an ntegral of the two-pont correlaton some boundary ntegrals. Ths was necessary because the lmt r! 0 has to be evaluated wthn the dsspaton range where not enough s known about the two-pont velocty-pressure correlaton. It can be found that the dsspaton range, whch s of the order of l,makes a hgher order contrbuton to the above mentoned ntegral n the lmt of large Reynolds number thus can be neglected. After neglectng the trple-correlatons we nd Z = ; R l +~r l R 2 dv (~r) +( $ ) ~r where ( $ ) abbrevates the addton of the prevous term wth ndces nterchanged. No boundary ntegral has to be kept due to the homogeneous boundary condtons for all varables. Once a soluton to the equatons (2) (24){(27) are computed the scalng of the two-pont correlatons can be calculated by equatng (48) (49). Usng ths, the value for u u can be taken from R at r =0as has been proven by the matchng between the Kolmogorov unversal range the outer nvscd soluton. 5. Future plans There are bascally two outstng problems wthn the whole approach of RDT n the log-layer. The rst one s the fact that t has to be proven that the system (2), (24){(29) has a non-zero soluton even though all boundary condtons are homogeneous. A strong hnt towards ths character of the equaton s ganed by the analyss of the dscretsed set of equatons whch, of course, s lnear. To see why the equatons may have a non-zero soluton, a result from lnear algebra may

12 220 M. Oberlack be recalled. If n a lnear system of the form Ax = 0 the matrx A has the rank <nwhere n s the number of equatons, then the system has nontrval solutons. In ths partcular case consderng the dscretsed equatons (2), (24){ (27), A s a quadratc matrx ts rank can only be smaller than n f there s some redundancy n the equatons. In fact, ths redundancy s due to the denttes (28) (29). Even though the structure of the dscretsed system provdes some nformaton, the proof of a correspondng feature n the derental equatons s stll outstng. Once the prevous problem s solved, a numercal algorthm has to be coded to solve the dscretsed equatons (2) (24){(29) because t s very unlkely that an analytcal soluton can be found. In the next step of post-processng the numercal results, the ablty of the asymptotc lmts used n the RDT of the loglayer has to be revsed f necessary enhanced by ncludng hgher correlatons n the analyss. Fnally, the results of the theory wll be compared wth DNS data from the turbulent channel ow (Km et al. 987). Acknowledgment The author s sncerely grateful to Wllam C. Reynolds Paul A. Durbn for many valuable dscussons crtcal comments durng the development of the work. The work was n part supported by the Deutsche Forschungsgemenschaft. REFERENCES von Karman, Th. 930 Mechansche Ahnlchket und Turbulenz. Nachr. Ges. Wss. Goettngen. 68. von Karman, Th. 930 Mechansche Ahnlchket und Turbulenz. Proc. 3rd Int. Congr. Appl. Mech., Stockholm.. Kassnos, S. C. & Reynolds, W. C. 994 A structure-based model for rapd dstorton of homogeneous turbulence. Thermoscences Report No. TF-6. Km, J., Mon, P. & Moser, R. D. 987 Turbulence statstcs n fully developed channel ow at low Reynolds number. J. Flud Mech. 77, Mellor, G. L. 972 The large Reynolds number asymptotc theory of turbulent boundary layers. Int. J. Engng Sc. 0, Mllkan, C. B. 939 A crtcal dscusson of turbulent ows n channels crcular tubes. Proc. 5rd Int. Congr. Appl. Mech., Cambrdge. Rotta, J. C. 972 Turbulente Stromungen. Teubner Verlag Stuttgart. Saddough, S. G. & Veeravall, S. V. 994 Local sotropy n turbulent boundary layers at hgh Reynolds number. J. Flud Mech. 268,

ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM

ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM ELASTIC WAVE PROPAGATION IN A CONTINUOUS MEDIUM An elastc wave s a deformaton of the body that travels throughout the body n all drectons. We can examne the deformaton over a perod of tme by fxng our look

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

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

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

Mathematical Preparations

Mathematical Preparations 1 Introducton Mathematcal Preparatons The theory of relatvty was developed to explan experments whch studed the propagaton of electromagnetc radaton n movng coordnate systems. Wthn expermental error the

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

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

In this section is given an overview of the common elasticity models.

In this section is given an overview of the common elasticity models. Secton 4.1 4.1 Elastc Solds In ths secton s gven an overvew of the common elastcty models. 4.1.1 The Lnear Elastc Sold The classcal Lnear Elastc model, or Hooean model, has the followng lnear relatonshp

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

Convective Heat Transfer Past. Small Cylindrical Bodies. By Michele S. Titcombe and Michael J. Ward 1. Abstract

Convective Heat Transfer Past. Small Cylindrical Bodies. By Michele S. Titcombe and Michael J. Ward 1. Abstract Convectve Heat Transfer Past Small Cylndrcal Bodes By Mchele S. Ttcombe and Mchael J. Ward 1 Abstract Convectve heat transfer from an array of small, cylndrcal bodes of arbtrary shape n an unbounded, two-dmensonal

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

EPR Paradox and the Physical Meaning of an Experiment in Quantum Mechanics. Vesselin C. Noninski

EPR Paradox and the Physical Meaning of an Experiment in Quantum Mechanics. Vesselin C. Noninski EPR Paradox and the Physcal Meanng of an Experment n Quantum Mechancs Vesseln C Nonnsk vesselnnonnsk@verzonnet Abstract It s shown that there s one purely determnstc outcome when measurement s made on

More information

Turbulence. Lecture 21. Non-linear Dynamics. 30 s & 40 s Taylor s work on homogeneous turbulence Kolmogorov.

Turbulence. Lecture 21. Non-linear Dynamics. 30 s & 40 s Taylor s work on homogeneous turbulence Kolmogorov. Turbulence Lecture 1 Non-lnear Dynamcs Strong non-lnearty s a key feature of turbulence. 1. Unstable, chaotc behavor.. Strongly vortcal (vortex stretchng) 3 s & 4 s Taylor s work on homogeneous turbulence

More information

Lecture Note 3. Eshelby s Inclusion II

Lecture Note 3. Eshelby s Inclusion II ME340B Elastcty of Mcroscopc Structures Stanford Unversty Wnter 004 Lecture Note 3. Eshelby s Incluson II Chrs Wenberger and We Ca c All rghts reserved January 6, 004 Contents 1 Incluson energy n an nfnte

More information

Publication 2006/01. Transport Equations in Incompressible. Lars Davidson

Publication 2006/01. Transport Equations in Incompressible. Lars Davidson Publcaton 2006/01 Transport Equatons n Incompressble URANS and LES Lars Davdson Dvson of Flud Dynamcs Department of Appled Mechancs Chalmers Unversty of Technology Göteborg, Sweden, May 2006 Transport

More information

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4)

Econ107 Applied Econometrics Topic 3: Classical Model (Studenmund, Chapter 4) I. Classcal Assumptons Econ7 Appled Econometrcs Topc 3: Classcal Model (Studenmund, Chapter 4) We have defned OLS and studed some algebrac propertes of OLS. In ths topc we wll study statstcal propertes

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

Chapter 11: Simple Linear Regression and Correlation

Chapter 11: Simple Linear Regression and Correlation Chapter 11: Smple Lnear Regresson and Correlaton 11-1 Emprcal Models 11-2 Smple Lnear Regresson 11-3 Propertes of the Least Squares Estmators 11-4 Hypothess Test n Smple Lnear Regresson 11-4.1 Use of t-tests

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

COMPLEX NUMBERS AND QUADRATIC EQUATIONS

COMPLEX NUMBERS AND QUADRATIC EQUATIONS COMPLEX NUMBERS AND QUADRATIC EQUATIONS INTRODUCTION We know that x 0 for all x R e the square of a real number (whether postve, negatve or ero) s non-negatve Hence the equatons x, x, x + 7 0 etc are not

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

Chat eld, C. and A.J.Collins, Introduction to multivariate analysis. Chapman & Hall, 1980

Chat eld, C. and A.J.Collins, Introduction to multivariate analysis. Chapman & Hall, 1980 MT07: Multvarate Statstcal Methods Mke Tso: emal mke.tso@manchester.ac.uk Webpage for notes: http://www.maths.manchester.ac.uk/~mkt/new_teachng.htm. Introducton to multvarate data. Books Chat eld, C. and

More information

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system

Transfer Functions. Convenient representation of a linear, dynamic model. A transfer function (TF) relates one input and one output: ( ) system Transfer Functons Convenent representaton of a lnear, dynamc model. A transfer functon (TF) relates one nput and one output: x t X s y t system Y s The followng termnology s used: x y nput output forcng

More information

A Numerical Study of Heat Transfer and Fluid Flow past Single Tube

A Numerical Study of Heat Transfer and Fluid Flow past Single Tube A Numercal Study of Heat ransfer and Flud Flow past Sngle ube ZEINAB SAYED ABDEL-REHIM Mechancal Engneerng Natonal Research Center El-Bohos Street, Dokk, Gza EGYP abdelrehmz@yahoo.com Abstract: - A numercal

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

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

Lecture 6/7 (February 10/12, 2014) DIRAC EQUATION. The non-relativistic Schrödinger equation was obtained by noting that the Hamiltonian 2

Lecture 6/7 (February 10/12, 2014) DIRAC EQUATION. The non-relativistic Schrödinger equation was obtained by noting that the Hamiltonian 2 P470 Lecture 6/7 (February 10/1, 014) DIRAC EQUATION The non-relatvstc Schrödnger equaton was obtaned by notng that the Hamltonan H = P (1) m can be transformed nto an operator form wth the substtutons

More information

APPENDIX A Some Linear Algebra

APPENDIX A Some Linear Algebra APPENDIX A Some Lnear Algebra The collecton of m, n matrces A.1 Matrces a 1,1,..., a 1,n A = a m,1,..., a m,n wth real elements a,j s denoted by R m,n. If n = 1 then A s called a column vector. Smlarly,

More information

Exercise Solutions to Real Analysis

Exercise Solutions to Real Analysis xercse Solutons to Real Analyss Note: References refer to H. L. Royden, Real Analyss xersze 1. Gven any set A any ɛ > 0, there s an open set O such that A O m O m A + ɛ. Soluton 1. If m A =, then there

More information

Turbulent Flow. Turbulent Flow

Turbulent Flow. Turbulent Flow http://www.youtube.com/watch?v=xoll2kedog&feature=related http://br.youtube.com/watch?v=7kkftgx2any http://br.youtube.com/watch?v=vqhxihpvcvu 1. Caothc fluctuatons wth a wde range of frequences and

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

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

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

Solutions to Problem Set 6

Solutions to Problem Set 6 Solutons to Problem Set 6 Problem 6. (Resdue theory) a) Problem 4.7.7 Boas. n ths problem we wll solve ths ntegral: x sn x x + 4x + 5 dx: To solve ths usng the resdue theorem, we study ths complex ntegral:

More information

Tensor Analysis. For orthogonal curvilinear coordinates, ˆ ˆ (98) Expanding the derivative, we have, ˆ. h q. . h q h q

Tensor Analysis. For orthogonal curvilinear coordinates, ˆ ˆ (98) Expanding the derivative, we have, ˆ. h q. . h q h q For orthogonal curvlnear coordnates, eˆ grad a a= ( aˆ ˆ e). h q (98) Expandng the dervatve, we have, eˆ aˆ ˆ e a= ˆ ˆ a h e + q q 1 aˆ ˆ ˆ a e = ee ˆˆ ˆ + e. h q h q Now expandng eˆ / q (some of the detals

More information

8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS

8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS SECTION 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS 493 8.4 COMPLEX VECTOR SPACES AND INNER PRODUCTS All the vector spaces you have studed thus far n the text are real vector spaces because the scalars

More information

where the sums are over the partcle labels. In general H = p2 2m + V s(r ) V j = V nt (jr, r j j) (5) where V s s the sngle-partcle potental and V nt

where the sums are over the partcle labels. In general H = p2 2m + V s(r ) V j = V nt (jr, r j j) (5) where V s s the sngle-partcle potental and V nt Physcs 543 Quantum Mechancs II Fall 998 Hartree-Fock and the Self-consstent Feld Varatonal Methods In the dscusson of statonary perturbaton theory, I mentoned brey the dea of varatonal approxmaton schemes.

More information

Asymptotics of the Solution of a Boundary Value. Problem for One-Characteristic Differential. Equation Degenerating into a Parabolic Equation

Asymptotics of the Solution of a Boundary Value. Problem for One-Characteristic Differential. Equation Degenerating into a Parabolic Equation Nonl. Analyss and Dfferental Equatons, ol., 4, no., 5 - HIKARI Ltd, www.m-har.com http://dx.do.org/.988/nade.4.456 Asymptotcs of the Soluton of a Boundary alue Problem for One-Characterstc Dfferental Equaton

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

Moments of Inertia. and reminds us of the analogous equation for linear momentum p= mv, which is of the form. The kinetic energy of the body is.

Moments of Inertia. and reminds us of the analogous equation for linear momentum p= mv, which is of the form. The kinetic energy of the body is. Moments of Inerta Suppose a body s movng on a crcular path wth constant speed Let s consder two quanttes: the body s angular momentum L about the center of the crcle, and ts knetc energy T How are these

More information

Indeterminate pin-jointed frames (trusses)

Indeterminate pin-jointed frames (trusses) Indetermnate pn-jonted frames (trusses) Calculaton of member forces usng force method I. Statcal determnacy. The degree of freedom of any truss can be derved as: w= k d a =, where k s the number of all

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

PHYS 705: Classical Mechanics. Canonical Transformation II

PHYS 705: Classical Mechanics. Canonical Transformation II 1 PHYS 705: Classcal Mechancs Canoncal Transformaton II Example: Harmonc Oscllator f ( x) x m 0 x U( x) x mx x LT U m Defne or L p p mx x x m mx x H px L px p m p x m m H p 1 x m p m 1 m H x p m x m m

More information

Module 9. Lecture 6. Duality in Assignment Problems

Module 9. Lecture 6. Duality in Assignment Problems Module 9 1 Lecture 6 Dualty n Assgnment Problems In ths lecture we attempt to answer few other mportant questons posed n earler lecture for (AP) and see how some of them can be explaned through the concept

More information

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U)

ANSWERS. Problem 1. and the moment generating function (mgf) by. defined for any real t. Use this to show that E( U) var( U) Econ 413 Exam 13 H ANSWERS Settet er nndelt 9 deloppgaver, A,B,C, som alle anbefales å telle lkt for å gøre det ltt lettere å stå. Svar er gtt . Unfortunately, there s a prntng error n the hnt of

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

Joint Statistical Meetings - Biopharmaceutical Section

Joint Statistical Meetings - Biopharmaceutical Section Iteratve Ch-Square Test for Equvalence of Multple Treatment Groups Te-Hua Ng*, U.S. Food and Drug Admnstraton 1401 Rockvlle Pke, #200S, HFM-217, Rockvlle, MD 20852-1448 Key Words: Equvalence Testng; Actve

More information

2.3 Nilpotent endomorphisms

2.3 Nilpotent endomorphisms s a block dagonal matrx, wth A Mat dm U (C) In fact, we can assume that B = B 1 B k, wth B an ordered bass of U, and that A = [f U ] B, where f U : U U s the restrcton of f to U 40 23 Nlpotent endomorphsms

More information

Introduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law:

Introduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law: CE304, Sprng 2004 Lecture 4 Introducton to Vapor/Lqud Equlbrum, part 2 Raoult s Law: The smplest model that allows us do VLE calculatons s obtaned when we assume that the vapor phase s an deal gas, and

More information

12. The Hamilton-Jacobi Equation Michael Fowler

12. The Hamilton-Jacobi Equation Michael Fowler 1. The Hamlton-Jacob Equaton Mchael Fowler Back to Confguraton Space We ve establshed that the acton, regarded as a functon of ts coordnate endponts and tme, satsfes ( ) ( ) S q, t / t+ H qpt,, = 0, and

More information

Turbulent Transport in Single-Phase Flow. Peter Bernard, University of Maryland

Turbulent Transport in Single-Phase Flow. Peter Bernard, University of Maryland Turbulent Transport n Sngle-Phase Flow Peter Bernard, Unversty of Maryland Assume that our goal s to compute mean flow statstcs such as U and One can ether: 1 u where U Pursue DNS (.e. the "honest" approach)

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

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

Workshop: Approximating energies and wave functions Quantum aspects of physical chemistry

Workshop: Approximating energies and wave functions Quantum aspects of physical chemistry Workshop: Approxmatng energes and wave functons Quantum aspects of physcal chemstry http://quantum.bu.edu/pltl/6/6.pdf Last updated Thursday, November 7, 25 7:9:5-5: Copyrght 25 Dan Dll (dan@bu.edu) Department

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

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

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

Formal solvers of the RT equation

Formal solvers of the RT equation Formal solvers of the RT equaton Formal RT solvers Runge- Kutta (reference solver) Pskunov N.: 979, Master Thess Long characterstcs (Feautrer scheme) Cannon C.J.: 970, ApJ 6, 55 Short characterstcs (Hermtan

More information

9 Derivation of Rate Equations from Single-Cell Conductance (Hodgkin-Huxley-like) Equations

9 Derivation of Rate Equations from Single-Cell Conductance (Hodgkin-Huxley-like) Equations Physcs 171/271 - Chapter 9R -Davd Klenfeld - Fall 2005 9 Dervaton of Rate Equatons from Sngle-Cell Conductance (Hodgkn-Huxley-lke) Equatons We consder a network of many neurons, each of whch obeys a set

More information

The Geometry of Logit and Probit

The Geometry of Logit and Probit The Geometry of Logt and Probt Ths short note s meant as a supplement to Chapters and 3 of Spatal Models of Parlamentary Votng and the notaton and reference to fgures n the text below s to those two chapters.

More information

Comparison of Regression Lines

Comparison of Regression Lines STATGRAPHICS Rev. 9/13/2013 Comparson of Regresson Lnes Summary... 1 Data Input... 3 Analyss Summary... 4 Plot of Ftted Model... 6 Condtonal Sums of Squares... 6 Analyss Optons... 7 Forecasts... 8 Confdence

More information

Chapter 13: Multiple Regression

Chapter 13: Multiple Regression Chapter 13: Multple Regresson 13.1 Developng the multple-regresson Model The general model can be descrbed as: It smplfes for two ndependent varables: The sample ft parameter b 0, b 1, and b are used to

More information

PHYS 705: Classical Mechanics. Newtonian Mechanics

PHYS 705: Classical Mechanics. Newtonian Mechanics 1 PHYS 705: Classcal Mechancs Newtonan Mechancs Quck Revew of Newtonan Mechancs Basc Descrpton: -An dealzed pont partcle or a system of pont partcles n an nertal reference frame [Rgd bodes (ch. 5 later)]

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

Feb 14: Spatial analysis of data fields

Feb 14: Spatial analysis of data fields Feb 4: Spatal analyss of data felds Mappng rregularly sampled data onto a regular grd Many analyss technques for geophyscal data requre the data be located at regular ntervals n space and/or tme. hs s

More information

C/CS/Phy191 Problem Set 3 Solutions Out: Oct 1, 2008., where ( 00. ), so the overall state of the system is ) ( ( ( ( 00 ± 11 ), Φ ± = 1

C/CS/Phy191 Problem Set 3 Solutions Out: Oct 1, 2008., where ( 00. ), so the overall state of the system is ) ( ( ( ( 00 ± 11 ), Φ ± = 1 C/CS/Phy9 Problem Set 3 Solutons Out: Oct, 8 Suppose you have two qubts n some arbtrary entangled state ψ You apply the teleportaton protocol to each of the qubts separately What s the resultng state obtaned

More information

Chapter 12. Ordinary Differential Equation Boundary Value (BV) Problems

Chapter 12. Ordinary Differential Equation Boundary Value (BV) Problems Chapter. Ordnar Dfferental Equaton Boundar Value (BV) Problems In ths chapter we wll learn how to solve ODE boundar value problem. BV ODE s usuall gven wth x beng the ndependent space varable. p( x) q(

More information

Group Analysis of Ordinary Differential Equations of the Order n>2

Group Analysis of Ordinary Differential Equations of the Order n>2 Symmetry n Nonlnear Mathematcal Physcs 997, V., 64 7. Group Analyss of Ordnary Dfferental Equatons of the Order n> L.M. BERKOVICH and S.Y. POPOV Samara State Unversty, 4430, Samara, Russa E-mal: berk@nfo.ssu.samara.ru

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

MEM 255 Introduction to Control Systems Review: Basics of Linear Algebra

MEM 255 Introduction to Control Systems Review: Basics of Linear Algebra MEM 255 Introducton to Control Systems Revew: Bascs of Lnear Algebra Harry G. Kwatny Department of Mechancal Engneerng & Mechancs Drexel Unversty Outlne Vectors Matrces MATLAB Advanced Topcs Vectors A

More information

Lecture 10: Euler s Equations for Multivariable

Lecture 10: Euler s Equations for Multivariable Lecture 0: Euler s Equatons for Multvarable Problems Let s say we re tryng to mnmze an ntegral of the form: {,,,,,, ; } J f y y y y y y d We can start by wrtng each of the y s as we dd before: y (, ) (

More information

OPTIMISATION. Introduction Single Variable Unconstrained Optimisation Multivariable Unconstrained Optimisation Linear Programming

OPTIMISATION. Introduction Single Variable Unconstrained Optimisation Multivariable Unconstrained Optimisation Linear Programming OPTIMIATION Introducton ngle Varable Unconstraned Optmsaton Multvarable Unconstraned Optmsaton Lnear Programmng Chapter Optmsaton /. Introducton In an engneerng analss, sometmes etremtes, ether mnmum or

More information

Section 8.3 Polar Form of Complex Numbers

Section 8.3 Polar Form of Complex Numbers 80 Chapter 8 Secton 8 Polar Form of Complex Numbers From prevous classes, you may have encountered magnary numbers the square roots of negatve numbers and, more generally, complex numbers whch are the

More information

Handout: Large Eddy Simulation I. Introduction to Subgrid-Scale (SGS) Models

Handout: Large Eddy Simulation I. Introduction to Subgrid-Scale (SGS) Models Handout: Large Eddy mulaton I 058:68 Turbulent flows G. Constantnescu Introducton to ubgrd-cale (G) Models G tresses should depend on: Local large-scale feld or Past hstory of local flud (va PDE) Not all

More information

Week 9 Chapter 10 Section 1-5

Week 9 Chapter 10 Section 1-5 Week 9 Chapter 10 Secton 1-5 Rotaton Rgd Object A rgd object s one that s nondeformable The relatve locatons of all partcles makng up the object reman constant All real objects are deformable to some extent,

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

8.1 Arc Length. What is the length of a curve? How can we approximate it? We could do it following the pattern we ve used before

8.1 Arc Length. What is the length of a curve? How can we approximate it? We could do it following the pattern we ve used before .1 Arc Length hat s the length of a curve? How can we approxmate t? e could do t followng the pattern we ve used before Use a sequence of ncreasngly short segments to approxmate the curve: As the segments

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

Fundamental loop-current method using virtual voltage sources technique for special cases

Fundamental loop-current method using virtual voltage sources technique for special cases Fundamental loop-current method usng vrtual voltage sources technque for specal cases George E. Chatzaraks, 1 Marna D. Tortorel 1 and Anastasos D. Tzolas 1 Electrcal and Electroncs Engneerng Departments,

More information

1 Derivation of Rate Equations from Single-Cell Conductance (Hodgkin-Huxley-like) Equations

1 Derivation of Rate Equations from Single-Cell Conductance (Hodgkin-Huxley-like) Equations Physcs 171/271 -Davd Klenfeld - Fall 2005 (revsed Wnter 2011) 1 Dervaton of Rate Equatons from Sngle-Cell Conductance (Hodgkn-Huxley-lke) Equatons We consder a network of many neurons, each of whch obeys

More information

= = = (a) Use the MATLAB command rref to solve the system. (b) Let A be the coefficient matrix and B be the right-hand side of the system.

= = = (a) Use the MATLAB command rref to solve the system. (b) Let A be the coefficient matrix and B be the right-hand side of the system. Chapter Matlab Exercses Chapter Matlab Exercses. Consder the lnear system of Example n Secton.. x x x y z y y z (a) Use the MATLAB command rref to solve the system. (b) Let A be the coeffcent matrx and

More information

Composite Hypotheses testing

Composite Hypotheses testing Composte ypotheses testng In many hypothess testng problems there are many possble dstrbutons that can occur under each of the hypotheses. The output of the source s a set of parameters (ponts n a parameter

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

CHAPTER 14 GENERAL PERTURBATION THEORY

CHAPTER 14 GENERAL PERTURBATION THEORY CHAPTER 4 GENERAL PERTURBATION THEORY 4 Introducton A partcle n orbt around a pont mass or a sphercally symmetrc mass dstrbuton s movng n a gravtatonal potental of the form GM / r In ths potental t moves

More information

Implicit Integration Henyey Method

Implicit Integration Henyey Method Implct Integraton Henyey Method In realstc stellar evoluton codes nstead of a drect ntegraton usng for example the Runge-Kutta method one employs an teratve mplct technque. Ths s because the structure

More information

[7] R.S. Varga, Matrix Iterative Analysis, Prentice-Hall, Englewood Clis, New Jersey, (1962).

[7] R.S. Varga, Matrix Iterative Analysis, Prentice-Hall, Englewood Clis, New Jersey, (1962). [7] R.S. Varga, Matrx Iteratve Analyss, Prentce-Hall, Englewood ls, New Jersey, (962). [8] J. Zhang, Multgrd soluton of the convecton-duson equaton wth large Reynolds number, n Prelmnary Proceedngs of

More information

Department of Statistics University of Toronto STA305H1S / 1004 HS Design and Analysis of Experiments Term Test - Winter Solution

Department of Statistics University of Toronto STA305H1S / 1004 HS Design and Analysis of Experiments Term Test - Winter Solution Department of Statstcs Unversty of Toronto STA35HS / HS Desgn and Analyss of Experments Term Test - Wnter - Soluton February, Last Name: Frst Name: Student Number: Instructons: Tme: hours. Ads: a non-programmable

More information

Change. Flamenco Chuck Keyser. Updates 11/26/2017, 11/28/2017, 11/29/2017, 12/05/2017. Most Recent Update 12/22/2017

Change. Flamenco Chuck Keyser. Updates 11/26/2017, 11/28/2017, 11/29/2017, 12/05/2017. Most Recent Update 12/22/2017 Change Flamenco Chuck Keyser Updates /6/7, /8/7, /9/7, /5/7 Most Recent Update //7 The Relatvstc Unt Crcle (ncludng proof of Fermat s Theorem) Relatvty Page (n progress, much more to be sad, and revsons

More information

TURBULENT FLOW A BEGINNER S APPROACH. Tony Saad March

TURBULENT FLOW A BEGINNER S APPROACH. Tony Saad March TURBULENT FLOW A BEGINNER S APPROACH Tony Saad March 2004 http://tsaad.uts.edu - tsaad@uts.edu CONTENTS Introducton Random processes The energy cascade mechansm The Kolmogorov hypotheses The closure problem

More information

THE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructions

THE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructions THE VIBRATIONS OF MOLECULES II THE CARBON DIOXIDE MOLECULE Student Instructons by George Hardgrove Chemstry Department St. Olaf College Northfeld, MN 55057 hardgrov@lars.acc.stolaf.edu Copyrght George

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

Supporting Information

Supporting Information Supportng Informaton The neural network f n Eq. 1 s gven by: f x l = ReLU W atom x l + b atom, 2 where ReLU s the element-wse rectfed lnear unt, 21.e., ReLUx = max0, x, W atom R d d s the weght matrx to

More information

Open Systems: Chemical Potential and Partial Molar Quantities Chemical Potential

Open Systems: Chemical Potential and Partial Molar Quantities Chemical Potential Open Systems: Chemcal Potental and Partal Molar Quanttes Chemcal Potental For closed systems, we have derved the followng relatonshps: du = TdS pdv dh = TdS + Vdp da = SdT pdv dg = VdP SdT For open systems,

More information

(A and B must have the same dmensons to be able to add them together.) Addton s commutatve and assocatve, just lke regular addton. A matrx A multpled

(A and B must have the same dmensons to be able to add them together.) Addton s commutatve and assocatve, just lke regular addton. A matrx A multpled CNS 185: A Bref Revew of Lnear Algebra An understandng of lnear algebra s crtcal as a steppng-o pont for understandng neural networks. Ths handout ncludes basc dentons, then quckly progresses to elementary

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

Time-Varying Systems and Computations Lecture 6

Time-Varying Systems and Computations Lecture 6 Tme-Varyng Systems and Computatons Lecture 6 Klaus Depold 14. Januar 2014 The Kalman Flter The Kalman estmaton flter attempts to estmate the actual state of an unknown dscrete dynamcal system, gven nosy

More information

Principles of Food and Bioprocess Engineering (FS 231) Solutions to Example Problems on Heat Transfer

Principles of Food and Bioprocess Engineering (FS 231) Solutions to Example Problems on Heat Transfer Prncples of Food and Boprocess Engneerng (FS 31) Solutons to Example Problems on Heat Transfer 1. We start wth Fourer s law of heat conducton: Q = k A ( T/ x) Rearrangng, we get: Q/A = k ( T/ x) Here,

More information

On the symmetric character of the thermal conductivity tensor

On the symmetric character of the thermal conductivity tensor On the symmetrc character of the thermal conductvty tensor Al R. Hadjesfandar Department of Mechancal and Aerospace Engneerng Unversty at Buffalo, State Unversty of New York Buffalo, NY 146 USA ah@buffalo.edu

More information

Negative Binomial Regression

Negative Binomial Regression STATGRAPHICS Rev. 9/16/2013 Negatve Bnomal Regresson Summary... 1 Data Input... 3 Statstcal Model... 3 Analyss Summary... 4 Analyss Optons... 7 Plot of Ftted Model... 8 Observed Versus Predcted... 10 Predctons...

More information

Numerical Solution of Ordinary Differential Equations

Numerical Solution of Ordinary Differential Equations Numercal Methods (CENG 00) CHAPTER-VI Numercal Soluton of Ordnar Dfferental Equatons 6 Introducton Dfferental equatons are equatons composed of an unknown functon and ts dervatves The followng are examples

More information