1. Governing Equations

Size: px
Start display at page:

Download "1. Governing Equations"

Transcription

1 1. Governng Equatons 1a. Governng Equatons for Mean Varables The governng equatons descrbe the varaton n space and tme of the zonal, merdonal and vertcal wnd components, densty, temperature, specfc humdty and other scalars transported n the PBL. These sets of equatons contan the tme and space dervatves that requre ntal and boundary condtons for ther soluton. As stated above, we don t forecast all eddy motons, nstead we pck a cut-off eddy sze and below ths we nclude only the statstcal effects of turbulence. For mesoscale and synoptc models the cut-off s on the order of 10 to 100km, whle for large eddy smulaton, the cut-off s on the order of 100m. The methodology we wll use s: Step 1. Identfy the basc governng equatons for boundary layer. Step 2. Expand dependent varables nto mean and turbulent parts. Step 3. Apply Reynolds averagng to get mean varables wthn turbulent flow. Step 4. Obtan equatons for turbulent departure from mean. A. Equaton of state The deal gas law for most ar, expressed n terms of vrtual temperature s, p = ρrt v (1) where p s pressure, ρ s the densty of most ar, T v s the vrtual temperature n K and R s the gas constant for dry ar [R = 287Jkg 1 K 1 ]. After Reynolds averagng (1) becomes: p R = ρt v + ρ T v ρt v (2) The last approxmaton s due to the fact that ρ T v << ρt v. Ths s the equaton of state for mean varables. 1

2 Notce that f we subtract the equaton for mean varables from the orgnal equaton expressed as the sum of the mean and turbulent parts of every varable, and neglect the small covarance terms we obtan the lnearzed perturbaton deal gas law. p p = T v + ρ T v ρ Wthn the PBL, we can neglect the pressure perturbaton over average pressure, so that: T v = θ v = ρ (4) T v θ v ρ Ths mples that warmer (colder) than average ar s less dense (more dense) than average. Ths also allows us to substtute temperature fluctuatons n place of densty fluctuatons. B. Conservaton of mass The conservaton of mass equaton s wrtten as: ρ + (ρu j) = ρ + U j ρ + ρ U j (3) = dρ dt + ρ U j = 0 (5) Wthn the boundary layer, dρ dt /ρ << U j, so we can assume ncompressblty: After Reynolds averagng, the equaton becomes: U j = 0 (6) U j = 0 (7) Ths s the conservaton of mass for mean varables, also called ncompressble contnuty equaton. The conservaton equaton for turbulent varables s obtaned by subtractng (7) from (6): u j = 0 (8) C. Conservaton of mosture 2

3 The conservaton of mosture s wrtten as: q + U q 2 q j = ν q x 2 j + S q ρ where q s the specfc humdty (mass of water per unt mass of most ar), ν q s the molecular dffusvty for water vapor n the ar, S q s mosture source term as, for example, a phase change and we assume t only affects the mean varables. We then Reynolds average and express the turbulent advecton term n flux form u q j = u j q usng (8) to obtan the conservaton equaton for mean total mosture: q I q 2 q + U j = ν q x }{{ j x } 2 j II III + S q ρ IV u j q V (9) (10) where Term I represents the storage of mean mosture, Term II the advecton of mean mosture by mean wnd, Term III mean molecular dfusson of water vapor (generally neglected because t s much smaller than the other terms), Term IV mean net body source term for addtonal mosture processes, and Term V represents the dvergence of turbulent total mosture flux. By subtractng (10) from (9) (whch ncludes both mean and turbulent components for each varable) and omttng the source term (S q ) for perturbatons we obtan the prognostc equaton for the perturbaton part (q ). q + U q j + u q j + u q 2 q j = ν q D. Conservaton of scalar quantty + u j q (11) Conservaton of a scalar quantty s expressed n a very smlar form as the conservaton of mosture. C + U C 2 C j = ν c + S c ρ (12) where C s the concentraton of a tracer (mass of scalar per unt mass of most ar), ν c s the molecular dffusvty for that scalar n the ar, S c s net source term for the mean varables. We perform Reynolds averagng on (12) and express the 3

4 turbulent advecton term n flux form u j c = u j c equaton for mean tracer C: C I C 2 C + U j = ν c x }{{ j x } 2 j II III + S c ρ IV to obtan the conservaton u j c V (13) where each of the terms s analogous to (10). By subtractng (13) from (12), we obtan the prognostc equaton for the perturbaton part (c ). E. Conservaton of heat c + U c j + u C j + u C 2 c j = ν c + u j c (14) Conservaton of enthalpy per unt mass (C p θ) s derved from the frst law of thermodynamcs. The equaton ncludes contrbutons from both sensble and latent heat as water vapor has the potental to release or absorb latent heat durng phase change. θ + U θ 2 θ j = ν θ 1 ρc p Q j L pe ρc p (15) where ν θ s the thermal dffusvty, L p s the latent heat assocated wth the phase change of E. Q j s the component of net radaton n the j th drecton, and C p s the specfc heat of most ar, related to the specfc heat of dry ar C pd = 1005Jkg 1 K 1 by C p = C pd ( q). We perform Reynolds averagng and, wth the ad of the contnuty equaton, express the turbulent advecton term n flux form u j θ = u j θ prognostc equaton for the mean potental temperature (θ). θ I + U j θ II = ν θ 2 θ III 1 Q j ρc p x }{{ j } IV L ve ρc p V u j θ V I to obtan the (16) where Term I represents storage of heat, Term II advecton of heat by mean wnd, Term III mean molecular conducton of heat (generally neglected because t s much smaller than the other terms), Term IV mean net body source assocated 4

5 wth radaton dvergence, Term V mean net body source assocated wth latent heat release, and Term VI represents the dvergence of turbulent heat flux. By subtractng (16) from the orgnal equaton (15) we can obtan the prognostc equaton for the perturbaton part (θ ). θ + U θ j + u θ j + u θ 2 θ j = ν c + u j θ 1 ρc p Q j (17) Fgure 1: From Stull F. Conservaton of momentum Newton s second law of moton can be wrtten as: 5

6 Fgure 2: From Stull U I + U j U II = gδ }{{ 3 + f } c ɛ j3 U j 1 p ρ x III IV V + ν 2 U V I (18) where Term I represents storage of momentum (nerta), Term II represents advecton, Term III the vertcal effect of gravty, Term IV s the Corols effect where f c = 2ω snφ (wth φ beng lattude and ω beng the angular velocty of the earth), Term V pressure gradent forces and Term VI represents vscous stress (generally neglected because t s much smaller than the other terms n the equaton of mean moton, but not n the perturbaton equatons). Densty varatons are essentally what drve buoyancy n the vertcal drecton so that warmer (than average) ar rses and cooler ar snks. Wth ths fact and the ncompressblty assumpton (6), we can neglect densty varatons except n the 6

7 Fgure 3: From Stull buoyancy term assocated wth gravty. Ths s called Boussnesq approxmaton. To show ths clearly we can multply the the vertcal component of the momentum equaton by (ρ/ρ) and separate varables nto mean and perturbaton components. Applyng Boussnesq approxmaton, we can neglect all terms ρ /ρ, except n the gravty term [so (1 + ρ /ρ) 1 n all but gravty terms]. W + w + (U j + u j) (W + w ) = ) (1 + ρ g 1 (p + p ) + ν 2 (W + w ) ρ ρ z (19) We can use (4) to express the equaton n terms of vrtual potental temperature fluctuatons, and generalze for the three components: 7

8 U + u + (U j + u j) (U + u ) ( ) = g 1 + θ v δ 3 +f c ɛ j3 (U j + u j) 1 (p + p ) + ν 2 (U + u ) ρ x θ v (20) Fnally, we can do Reynolds averagng and express the turbulent advecton term n flux form u u j mean varables: U I + U j U II = u j u to obtan the conservaton of momentum for = gδ }{{ 3 + f } c ɛ j3 U j 1 p ρ x III IV V + ν 2 U V I u j u } {{ } V II (21) where the frst sx terms represent the same physcal mechansms as (18), and the new Term VII represents the nfluence of Reynold s stress on mean motons. Ths last term s also descrbed as dvergence of turbulent momentum flux. If we subtract (21) from (20), we get the equaton of conservaton of momentum for perturbatons: + U j + u U j + u u j = gθ v δ 3 + f c ɛ j3 u j 1 p + ν 2 u θ v ρ x u u We wll re-vst ths equaton when dscussng turbulent knetc energy. + u j u (22) It s sometmes useful to substtute the horzontal pressure gradent terms usng the defnton of geostrophc wnd: f c U g = 1 p and f ρ y cv g = + 1 p. In ths way, ρ x we can express the zonal and merdonal components of the momentum equaton n smplfed form as: U + U U j = f c (V g V ) (u j u ) (23) V + U V j = +f c (U g U) (u j v ) (24) In these equatons we have neglected the molecular dffuson/vscosty terms because they are much smaller than the other terms n the equaton. In addton, 8

9 notce that n the momentum equaton for far-weather condtons we can usually neglect subsdence, so the prognostc equaton for mean vertcal wnd s not presented. Notably, PBL numercal models generally use ths notaton for the horzontal components of the momentum equaton. 1b. Prognostc Equatons for Turbulent Fluxes and Varances A. Prognostc equatons for turbulent fluxes Equatons for the mean varables n turbulent flow (10), (13), (16) and (21) contan dvergence terms of turbulent fluxes q u j, c u j, θ u j and u u j. These terms arse drectly because of the nonlnearty of the advecton terms n the orgnal equatons. They act as source/snk terms that change the mean varables due to the transport of momentum, mosture, heat and/or scalars by perturbatons of wnd, mosture, heat and/or scalars. We can fnd prognostc equatons for these fluxes usng the followng methodology descrbed for any varable ζ, whch can denote wnd, humdty, potental temperature or a scalar. 1. Multply perturbaton equaton for ζ by u and Reynolds average. 2. Multply the momentum perturbaton equaton (u ) by ζ 3. Add the two resultng equatons 4. Use the contnuty equaton to get the turbulent transport terms nto flux form and merge any other terms Example: mosture flux Start wth the momentum perturbaton equaton and multply by mosture perturbaton, then Reynolds average. q u +U jq u +q x u j j U +q x u j j u = g q θ v δ 3 +f c ɛ j3 q x u j j θ q v ρ p x +νq 2 u (25) Smlarly, we start wth the mosture perturbaton equaton and multply by u and Reynolds average. u q + U ju q + u x u j j q + u q x u j = ν q u j 2 q (26) 9

10 Now we add (25) and (26), assume ν = ν q and use these smplfyng expressons: q 2 u q p = 1 (p q ) p q (27) ρ x ρ x ρ x + u 2 q = 2 (q u ) ( ) ( ) u 2 q (28) The boxed terms can be neglected based on scalng arguments (Stull, 1988), and we can denote the last term n (28) as 2ɛ u q. Other terms (e.g., ɛ u u j and ɛ) used n equatons below can be smlarly defned. We then express the turbulent flux dvergence terms nto flux form, neglect the Corols term and express the smplfed expresson as: u q I u + U q j + u q x u j + q }{{ j x u U j }}{{ j x }}{{ j } II III IV g q θ v δ ( ) p ρ q 2ɛ u q x θ v } {{ } V I } {{ } V II V III + (q u u j ) = x }{{ j } V (29) Term I s the storage term, Term II s the advecton term, III, IV and VI are producton/consumpton terms, V s a turbulent transport term, VII represents redstrbuton, and Term VIII s a molecular destructon (dsspaton of turbulent mosture flux). Wthout formal dervaton, we present the momentum flux budget equaton [See Stull (1988) for a formal dervaton]. Ths equaton s derved n a smlar fashon as the turbulent mosture flux, and wll be re-vsted later when dscussng turbulence closure: 10

11 u u k u + U u k j = u U k x u j u k j x u j j B. Prognostc equatons for varance terms U u j u u k + g ( ) [δ k3 u θ θ v + δ 3 u k θ v] + p u + u k v ρ x k x 2ɛ u u k (30) Prognostc equatons for varances are also useful for solvng the equatons for mean flow. In addton, the varance equatons provde a physcal descrpton for the evoluton of the boundary layer as wll be seen later when turbulent knetc energy s dscussed. The procedure for obtanng the equatons for the varance terms s smlar, although not dentcal, to that for the fluxes. 1. Begn wth the prognostc equaton for the perturbaton of the varable ζ. 2. Multply by 2ζ and convert the terms 2ζ ζ nto (ζ ) 2 3. Reynolds average 4. The terms that look lke u ζ 2 j can be turned nto flux form by usng the contnuty equaton multpled by ζ 2 (whch s equal to zero). Example: momentum varance Applyng the frst two steps to (22), we obtan: u ζ 2 j + ζ 2 u j = ζ 2 u j (31) u 2 u 2 + U j + 2u u U j + u u 2 j = u 2δ θ v 3 g + 2f c ɛ j3 u u j 2 u p + 2νu 2 u u + 2u j u θ v ρ x x 2 (32) j We can smplfy the dsspaton term usng the followng expresson: 11

12 2νu 2 u = ν 2 u 2 2ν ( ) u 2 (33) x We can neglect the boxed term based on scalng arguments (Stull, 1988) and express the last term n (33) as 2ɛ, transform the pressure perturbaton term n flux (u p ) form 2 ρ x usng the fact that the turbulence contnuty equaton s zero, and neglect Corols for velocty varances: u 2 u 2 + U j = 2δ 3 u θ v θ v g 2u U u j + u j u 2 ( ) 2 (u p ) 2ɛ (34) ρ x We can do the same for the prognostc equatons for mosture varance q 2, potental temperature varance θ 2, and varance of a scalar quantty c 2. The smplfed equatons are lsted below wthout formal dervaton: q 2 + U q 2 j = 2q x u j j θ 2 + U θ 2 j = 2θ x u j j c 2 + U c 2 j = 2c x u j j q (u j q 2 ) 2ɛ q (35) θ (u j θ 2 ) 2ɛ θ 2 θ ρc Q j (36) p c (u j c 2 ) 2ɛ c (37) where the defntoon of ɛ q, ɛ θ, and ɛ c s smlar to that of ɛ n (34). These three equatons are presented n smlar form where the frst term s the local storage, the second term s the advecton term, the thrd s a producton term assocated wth turbulent motons wthn a mean gradent, term four s the turbulent transport term, term fve denotes the molecular dsspaton, and the potental temperature varance has an addtonal term assocated wth radaton destructon. 1c. Turbulent Knetc Energy The prognostc equaton for turbulent knetc energy (TKE) s one of the most useful equatons for turbulence studes. The TKE per unt mass s defned as: T KE/m = e = 1 2 (u 2 + v 2 + w 2 ) = 1 2 u 2 (38) 12

13 Smlarly, we can defned e = u 2 /2. TKE ndcates whether the BL wll become more turbulent or f turbulence wll decay. Turbulence producton s due to buoyant thermals and mechancal eddes whle turbulence suppresson s drven by statcally stable lapse rate, and dsspated nto heat by molecular vscosty. To obtan a prognostc equaton for TKE, we can multply (34) by 0.5: e I + U j e II u = δ θ v 3 g θ }{{ v } III u U u j } {{ } IV u j e V 1 ρ (u p ) x } {{ } V I ɛ V II (39) where Term I represents local storage of TKE whch ncreases from early mornng wth a peak n the early afternoon. Over oceans, the storage term can be neglected (due to the small durnal cycle), whch means that the ntensty of turbulence doesn t change sgnfcantly wth tme. Term II represents advecton of TKE by mean wnd. Many tmes t s neglected assumng horzontal homogenety, however, ths mght not be vald for heterogeneous terran. Term III s a buoyant producton or consumpton term actng only n the vertcal drecton. It can be a producton term f the flux of vrtual potental temperature w θ v s postve (assocated to rsng thermals over land durng day) or a loss term when ths flux s negatve (as over land at nght, when statc stablty tends to suppress TKE). Ths term s very mportant for days of free convecton and can be used to normalze the TKE equaton. Term IV s a mechancal producton/loss term assocated wth mean wnd shear. Ths term s prmarly contrbuted by the vertcal gradent of horzontal wnd. Because mean horzontal wnd s zero at surface, t always ncreases wth heght near surface. Ths also mples that rsng parcels (wth w > 0) would have u < 0. Therefore term IV s generally postve and represents the mechancal producton of TKE. Term IV s largest near the surface, because of the large wnd shear, however, large wnd shear can exst at the top of the mxed layer wth geostrophc wnds above. Ths term s largest on wndy days, durng synoptc cyclones. Term V s the turbulent transport of TKE. It s a flux dvergence term - f ntegrated throughout the BL, t s zero- so t only redstrbutes turbulence and s not a producton/loss term. The maxmum vertcal transport occurs at z/z = 0.3 (wth z beng the PBL heght). Term VI descrbes how TKE s redstrbuted by pressure perturbatons, often assocated to oscllatons (buoyancy or gravty waves). Pressure perturbatons are usually small and s dffcult to measure, so ths term s usually calculated as a resdual. In very unstable condtons, ths term 13

14 can be a sgnfcant source of TKE near the top of the mxed layer (Hogstrom, 1990). Term VII s the vscous dsspaton of TKE representng the converson of TKE nto heat. Molecular destructon s greatest for the smallest eddy szes, so ntense small-scale turbulence nduces larger dsspaton. Ths term s largest near the surface, and then becomes constant, rapdly decreasng to zero above the PBL. Fgure 5 presents the terms of the TKE equaton as a functon of heght for steady-state daytme condtons. If we assume horzontal homogenety and neglect subsdence, the TKE equaton becomes: e = w θ v g (w u U θ v z + w v V z ) w e 1 (w p ) ɛ (40) z ρ z Shear producton and buoyant producton terms are large and postve for large eddy szes. However, there s a cascade of energy away from the large eddes towards the small eddes. At small eddy szes, the producton s close to zero and the dsspaton s very large. Ths can be thought of as an nertal process where large eddes bump nto smaller ones and transfer ther nerta, and the mddle porton of the spectrum s the nertal subrange. It can be shown from (21) that the prognostc equaton for the mean knetc energy contans the same mechancal producton/loss term as n the TKE equaton but they have opposte sgns. Therefore, the energy that s mechancally produced as turbulence s lost from the mean flow. 1d. Scalng and Stablty Crtera As we have shown, turbulence s generated by buoyant convecton (thermals) and by mechancal processes (wnd shear). Free convecton s the lmt when buoyant processes domnate, whle durng forced convecton, mechancal processes domnate. Here some useful scalng varables are defned for each of these two cases. They are used extensvely n scalng analyss and for presentaton of the data. A. Forced convecton scalng We defne a velocty scale called the frcton velocty u : u 2 = τ / ρ = [(u w ) 2 s + (v w ) 2 s] 1/2 (41) where τ refers to the total Reynolds stress, and subscrpt s refers to surface. 14

15 Fgure 4: From Garrat We can ntroduce the surface layer temperature scale θ = (w θ ) s u (42) 15

16 Fgure 5: From Garrat and the surface layer humdty scale B. Free convecton scalng q = (w q ) s u (43) 16

17 To defne the free convecton velocty scale, we frst defne the buoyance flux as: (g/θ v )w θ v. To generate the velocty scale we multply by the typcal length scale whch s z (the top of the mxed layer). Ths velocty scale s on the same order of magntude as observed vertcal velocty fluctuatons. w = [ ] 1/3 gz (w θ v) s (44) θ v The characterstc temperature s on the order of how much warmer thermals are than ther envronment. θ ML = (w θ ) s w (45) The characterstc humdty scale s on the order of how much moster thermals are than ther envronment. C. Flux Rchardson number q ML = (w q ) s w (46) The rato of the buoyant producton term and the mechancal producton term n the TKE equaton s called the flux Rchardson number (R f ). Ths number characterzes the thermal stablty of the flow. R f = g (w θ θ v v) (u u j ) (47) U The denomnator conssts of 9 terms. We assume horzontal homogenety and neglect subsdence: g (w θ θ R f = v v) (u w ) U + z (v w ) V z Because the denomnator s usually negatve. (48) R f > 0 for statcally stable flows R f < 0 for statcally unstable flows R f = 0 for statcally neutral flows 17

18 At the crtcal value of R f = +1, the mechancal producton rate balances the buoyant consumpton. Because dsspaton s always negatve n the TKE equaton, even before the buoyant consumpton balances the mechancal producton, turbulence would cease to exst. Therefore, the crtcal R f separatng turbulent and lamnar flows s generally less than 1 (and s about 0.25). D. Gradent Rchardson number The value of the turbulent correlatons could be expressed as beng proportonal to the lapse rate, and the turbulent momentum flux can be proportonal to the wnd gradent: w θ v θv, z w u U and z w v V. Ths s the bass z of K-theory that we wll dscuss later. When substtutng nto (48), we get the gradent Rchardson number: R = ( U z g θ v θ v z ) 2 + ( V z ) 2 (49) where t s assumed that turbulent exchange coeffcents for temperature and wnd are the same. The advantage of R over R f s that the former can be computed from temperature and wnd gradents drectly. E. Bulk Rchardson number When measurng wnd shear and temperature gradents, the gradents are usually approxmated by measurements at dscrete heghts: R B = ( U z g θ v θ v z ) 2 + ( V z ) 2 = g θ v z θ v (( U) 2 + ( V ) 2 (50) Ths s the form most frequently used. The values of the crtcal Rchardson number separatng turbulent and lamnar flows don t apply to these fnte dfferences across thck layers. The thnner the layer, the closer the value to the theory. F. Monn-Obukhov length The Monn-Obukhov Length s a very mportant parameter n the surface layer n whch turbulent fluxes and wnd drecton don t vary much wth heght. Takng 18

19 Table 1: Stablty Crtera Free Convecton Unstable Neutral Stable Lamnar (u w ) U / z 0 R < 0, ζ < 0 R = ζ = 0 R > 0, ζ > 0 R > R c U / z = (u /kz)φ m wth k beng the Von Karman constant (0.4) and φ m beng the stablty functon to be dscussed later, R f can be rewrtten as: R f = ζ/φ m (51) where ζ = z/l s the dmensonless heght and the Monn-Obukhov length L s L = θ vu 3 kg(w θ v) s (52) At a heght of z = φ m L, R f = 1 and the buoyancy and shear producton terms are equal. Consequently, we can nterpret the Monn-Obukhov Length as the heght at whch the buoyancy producton s equal to the mechancal producton under neutral condton (wth φ m = 1). ζ s a prmary parameter of the Monn- Obukhov smlarty of the atmospherc surface layer. We summarze the stablty condton n Table 1. Notce that when the gradent Rchardson number reaches a crtcal value of R c.2.25 the transton from turbulent to lamnar flow occurs. Theoretcally the transton from turbulent to lamnar flow s better represented by R f (rather than R ). Furthermore R B s computed n modelng and data analyss to represent R. In the atmosphere, even when turbulence ceases, turbulent ntermttency stll exsts and nternal gravty waves can stll generate mxng. For these reasons, even when R > R c, some turbulent mxng s stll consdered n numercal modelng. Ths s stll an area of actve research (Fernando and Wel, 2010). 19

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

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

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

FEATURES OF TURBULENT TRANSPORT OF MOMENTUM AND HEAT IN STABLY STRATIFIED BOUNDARY LAYERS AND THEIR REPRODUCTION IN ATMOSPHERIC MESOSCALE MODELS

FEATURES OF TURBULENT TRANSPORT OF MOMENTUM AND HEAT IN STABLY STRATIFIED BOUNDARY LAYERS AND THEIR REPRODUCTION IN ATMOSPHERIC MESOSCALE MODELS C I T E S 009_ Krasnoyarsk 009 FEATURES OF TURBULENT TRANSPORT OF MOMENTUM AND HEAT IN STABLY STRATIFIED BOUNDARY LAYERS AND THEIR REPRODUCTION IN ATMOSPHERIC MESOSCALE MODELS A. F. Kurbatsky Insttute

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

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

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

Thermodynamics General

Thermodynamics General Thermodynamcs General Lecture 1 Lecture 1 s devoted to establshng buldng blocks for dscussng thermodynamcs. In addton, the equaton of state wll be establshed. I. Buldng blocks for thermodynamcs A. Dmensons,

More information

1 Introduction to Governing Equations 2 1a Methodology... 2

1 Introduction to Governing Equations 2 1a Methodology... 2 Contents 1 Introduction to Governing Equations 2 1a Methodology............................ 2 2 Equation of State 2 2a Mean and Turbulent Parts...................... 3 2b Reynolds Averaging.........................

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

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

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

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

ESCI Cloud Physics and Precipitation Processes Lesson 4 - Convection Dr. DeCaria

ESCI Cloud Physics and Precipitation Processes Lesson 4 - Convection Dr. DeCaria References: ESCI 340 - Cloud Physcs and Precptaton Processes Lesson 4 - Convecton Dr. DeCara Glossary of Meteorology, 2nd ed., Amercan Meteorologcal Socety A Short Course n Cloud Physcs, 3rd ed., Rogers

More information

Modeling of Dynamic Systems

Modeling of Dynamic Systems Modelng of Dynamc Systems Ref: Control System Engneerng Norman Nse : Chapters & 3 Chapter objectves : Revew the Laplace transform Learn how to fnd a mathematcal model, called a transfer functon Learn how

More information

Turbulence and its Modelling

Turbulence and its Modelling School of Mechancal Aerospace and Cvl Engneerng 3rd Year Flud Mechancs Introducton In earler lectures we have consdered how flow nstabltes develop, and noted that above some crtcal Reynolds number flows

More information

2) For a two-dimensional steady turbulent flow in Cartesian coordinates (x,y), with mean velocity components (U,V), write

2) For a two-dimensional steady turbulent flow in Cartesian coordinates (x,y), with mean velocity components (U,V), write 058:68 Turbulent Flows 004 G. Constantnescu HOMEWORKS: Assgnment I - 01/6/04, Due 0/04/04 1) A cubcal box of volume L 3 s flled wth flud n turbulent moton. No source of energy s present, so that the turbulence

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

Physics 181. Particle Systems

Physics 181. Particle Systems Physcs 181 Partcle Systems Overvew In these notes we dscuss the varables approprate to the descrpton of systems of partcles, ther defntons, ther relatons, and ther conservatons laws. We consder a system

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

Structure and Drive Paul A. Jensen Copyright July 20, 2003

Structure and Drive Paul A. Jensen Copyright July 20, 2003 Structure and Drve Paul A. Jensen Copyrght July 20, 2003 A system s made up of several operatons wth flow passng between them. The structure of the system descrbes the flow paths from nputs to outputs.

More information

The classical spin-rotation coupling

The classical spin-rotation coupling LOUAI H. ELZEIN 2018 All Rghts Reserved The classcal spn-rotaton couplng Loua Hassan Elzen Basher Khartoum, Sudan. Postal code:11123 louaelzen@gmal.com Abstract Ths paper s prepared to show that a rgd

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

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

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

2 Finite difference basics

2 Finite difference basics Numersche Methoden 1, WS 11/12 B.J.P. Kaus 2 Fnte dfference bascs Consder the one- The bascs of the fnte dfference method are best understood wth an example. dmensonal transent heat conducton equaton T

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

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

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

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

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

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

CHAPTER 7 ENERGY BALANCES SYSTEM SYSTEM. * What is energy? * Forms of Energy. - Kinetic energy (KE) - Potential energy (PE) PE = mgz

CHAPTER 7 ENERGY BALANCES SYSTEM SYSTEM. * What is energy? * Forms of Energy. - Kinetic energy (KE) - Potential energy (PE) PE = mgz SYSTM CHAPTR 7 NRGY BALANCS 1 7.1-7. SYSTM nergy & 1st Law of Thermodynamcs * What s energy? * Forms of nergy - Knetc energy (K) K 1 mv - Potental energy (P) P mgz - Internal energy (U) * Total nergy,

More information

ENGN 40 Dynamics and Vibrations Homework # 7 Due: Friday, April 15

ENGN 40 Dynamics and Vibrations Homework # 7 Due: Friday, April 15 NGN 40 ynamcs and Vbratons Homework # 7 ue: Frday, Aprl 15 1. Consder a concal hostng drum used n the mnng ndustry to host a mass up/down. A cable of dameter d has the mass connected at one end and s wound/unwound

More information

2016 Wiley. Study Session 2: Ethical and Professional Standards Application

2016 Wiley. Study Session 2: Ethical and Professional Standards Application 6 Wley Study Sesson : Ethcal and Professonal Standards Applcaton LESSON : CORRECTION ANALYSIS Readng 9: Correlaton and Regresson LOS 9a: Calculate and nterpret a sample covarance and a sample correlaton

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

4.2 Chemical Driving Force

4.2 Chemical Driving Force 4.2. CHEMICL DRIVING FORCE 103 4.2 Chemcal Drvng Force second effect of a chemcal concentraton gradent on dffuson s to change the nature of the drvng force. Ths s because dffuson changes the bondng n a

More information

Lecture 12. Modeling of Turbulent Combustion

Lecture 12. Modeling of Turbulent Combustion Lecture 12. Modelng of Turbulent Combuston X.S. Ba Modelng of TC Content drect numercal smulaton (DNS) Statstcal approach (RANS) Modelng of turbulent non-premxed flames Modelng of turbulent premxed flames

More information

Process Modeling. Improving or understanding chemical process operation is a major objective for developing a dynamic process model

Process Modeling. Improving or understanding chemical process operation is a major objective for developing a dynamic process model Process Modelng Improvng or understandng chemcal process operaton s a major objectve for developng a dynamc process model Balance equatons Steady-state balance equatons mass or energy mass or energy enterng

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

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity

LINEAR REGRESSION ANALYSIS. MODULE IX Lecture Multicollinearity LINEAR REGRESSION ANALYSIS MODULE IX Lecture - 30 Multcollnearty Dr. Shalabh Department of Mathematcs and Statstcs Indan Insttute of Technology Kanpur 2 Remedes for multcollnearty Varous technques have

More information

11. Dynamics in Rotating Frames of Reference

11. Dynamics in Rotating Frames of Reference Unversty of Rhode Island DgtalCommons@URI Classcal Dynamcs Physcs Course Materals 2015 11. Dynamcs n Rotatng Frames of Reference Gerhard Müller Unversty of Rhode Island, gmuller@ur.edu Creatve Commons

More information

A particle in a state of uniform motion remain in that state of motion unless acted upon by external force.

A particle in a state of uniform motion remain in that state of motion unless acted upon by external force. The fundamental prncples of classcal mechancs were lad down by Galleo and Newton n the 16th and 17th centures. In 1686, Newton wrote the Prncpa where he gave us three laws of moton, one law of gravty,

More information

Uncertainty in measurements of power and energy on power networks

Uncertainty in measurements of power and energy on power networks Uncertanty n measurements of power and energy on power networks E. Manov, N. Kolev Department of Measurement and Instrumentaton, Techncal Unversty Sofa, bul. Klment Ohrdsk No8, bl., 000 Sofa, Bulgara Tel./fax:

More information

Basic concept of reactive flows. Basic concept of reactive flows Combustion Mixing and reaction in high viscous fluid Application of Chaos

Basic concept of reactive flows. Basic concept of reactive flows Combustion Mixing and reaction in high viscous fluid Application of Chaos Introducton to Toshhsa Ueda School of Scence for Open and Envronmental Systems Keo Unversty, Japan Combuston Mxng and reacton n hgh vscous flud Applcaton of Chaos Keo Unversty 1 Keo Unversty 2 What s reactve

More information

DUE: WEDS FEB 21ST 2018

DUE: WEDS FEB 21ST 2018 HOMEWORK # 1: FINITE DIFFERENCES IN ONE DIMENSION DUE: WEDS FEB 21ST 2018 1. Theory Beam bendng s a classcal engneerng analyss. The tradtonal soluton technque makes smplfyng assumptons such as a constant

More information

The Feynman path integral

The Feynman path integral The Feynman path ntegral Aprl 3, 205 Hesenberg and Schrödnger pctures The Schrödnger wave functon places the tme dependence of a physcal system n the state, ψ, t, where the state s a vector n Hlbert space

More information

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction ECONOMICS 5* -- NOTE (Summary) ECON 5* -- NOTE The Multple Classcal Lnear Regresson Model (CLRM): Specfcaton and Assumptons. Introducton CLRM stands for the Classcal Lnear Regresson Model. The CLRM s also

More information

Normally, in one phase reservoir simulation we would deal with one of the following fluid systems:

Normally, in one phase reservoir simulation we would deal with one of the following fluid systems: TPG4160 Reservor Smulaton 2017 page 1 of 9 ONE-DIMENSIONAL, ONE-PHASE RESERVOIR SIMULATION Flud systems The term sngle phase apples to any system wth only one phase present n the reservor In some cases

More information

Thermal-Fluids I. Chapter 18 Transient heat conduction. Dr. Primal Fernando Ph: (850)

Thermal-Fluids I. Chapter 18 Transient heat conduction. Dr. Primal Fernando Ph: (850) hermal-fluds I Chapter 18 ransent heat conducton Dr. Prmal Fernando prmal@eng.fsu.edu Ph: (850) 410-6323 1 ransent heat conducton In general, he temperature of a body vares wth tme as well as poston. In

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

First Law: A body at rest remains at rest, a body in motion continues to move at constant velocity, unless acted upon by an external force.

First Law: A body at rest remains at rest, a body in motion continues to move at constant velocity, unless acted upon by an external force. Secton 1. Dynamcs (Newton s Laws of Moton) Two approaches: 1) Gven all the forces actng on a body, predct the subsequent (changes n) moton. 2) Gven the (changes n) moton of a body, nfer what forces act

More information

SIO 224. m(r) =(ρ(r),k s (r),µ(r))

SIO 224. m(r) =(ρ(r),k s (r),µ(r)) SIO 224 1. A bref look at resoluton analyss Here s some background for the Masters and Gubbns resoluton paper. Global Earth models are usually found teratvely by assumng a startng model and fndng small

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

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

Physics 53. Rotational Motion 3. Sir, I have found you an argument, but I am not obliged to find you an understanding.

Physics 53. Rotational Motion 3. Sir, I have found you an argument, but I am not obliged to find you an understanding. Physcs 53 Rotatonal Moton 3 Sr, I have found you an argument, but I am not oblged to fnd you an understandng. Samuel Johnson Angular momentum Wth respect to rotatonal moton of a body, moment of nerta plays

More information

j) = 1 (note sigma notation) ii. Continuous random variable (e.g. Normal distribution) 1. density function: f ( x) 0 and f ( x) dx = 1

j) = 1 (note sigma notation) ii. Continuous random variable (e.g. Normal distribution) 1. density function: f ( x) 0 and f ( x) dx = 1 Random varables Measure of central tendences and varablty (means and varances) Jont densty functons and ndependence Measures of assocaton (covarance and correlaton) Interestng result Condtonal dstrbutons

More information

Airflow and Contaminant Simulation with CONTAM

Airflow and Contaminant Simulation with CONTAM Arflow and Contamnant Smulaton wth CONTAM George Walton, NIST CHAMPS Developers Workshop Syracuse Unversty June 19, 2006 Network Analogy Electrc Ppe, Duct & Ar Wre Ppe, Duct, or Openng Juncton Juncton

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

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

Temperature. Chapter Heat Engine

Temperature. Chapter Heat Engine Chapter 3 Temperature In prevous chapters of these notes we ntroduced the Prncple of Maxmum ntropy as a technque for estmatng probablty dstrbutons consstent wth constrants. In Chapter 9 we dscussed the

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

Chapter 6 Electrical Systems and Electromechanical Systems

Chapter 6 Electrical Systems and Electromechanical Systems ME 43 Systems Dynamcs & Control Chapter 6: Electrcal Systems and Electromechancal Systems Chapter 6 Electrcal Systems and Electromechancal Systems 6. INTODUCTION A. Bazoune The majorty of engneerng systems

More information

Iterative General Dynamic Model for Serial-Link Manipulators

Iterative General Dynamic Model for Serial-Link Manipulators EEL6667: Knematcs, Dynamcs and Control of Robot Manpulators 1. Introducton Iteratve General Dynamc Model for Seral-Lnk Manpulators In ths set of notes, we are gong to develop a method for computng a general

More information

Chapter 3. Estimation of Earthquake Load Effects

Chapter 3. Estimation of Earthquake Load Effects Chapter 3. Estmaton of Earthquake Load Effects 3.1 Introducton Sesmc acton on chmneys forms an addtonal source of natural loads on the chmney. Sesmc acton or the earthquake s a short and strong upheaval

More information

Supplementary Notes for Chapter 9 Mixture Thermodynamics

Supplementary Notes for Chapter 9 Mixture Thermodynamics Supplementary Notes for Chapter 9 Mxture Thermodynamcs Key ponts Nne major topcs of Chapter 9 are revewed below: 1. Notaton and operatonal equatons for mxtures 2. PVTN EOSs for mxtures 3. General effects

More information

Adiabatic Sorption of Ammonia-Water System and Depicting in p-t-x Diagram

Adiabatic Sorption of Ammonia-Water System and Depicting in p-t-x Diagram Adabatc Sorpton of Ammona-Water System and Depctng n p-t-x Dagram J. POSPISIL, Z. SKALA Faculty of Mechancal Engneerng Brno Unversty of Technology Techncka 2, Brno 61669 CZECH REPUBLIC Abstract: - Absorpton

More information

Frequency dependence of the permittivity

Frequency dependence of the permittivity Frequency dependence of the permttvty February 7, 016 In materals, the delectrc constant and permeablty are actually frequency dependent. Ths does not affect our results for sngle frequency modes, but

More information

Irregular vibrations in multi-mass discrete-continuous systems torsionally deformed

Irregular vibrations in multi-mass discrete-continuous systems torsionally deformed (2) 4 48 Irregular vbratons n mult-mass dscrete-contnuous systems torsonally deformed Abstract In the paper rregular vbratons of dscrete-contnuous systems consstng of an arbtrary number rgd bodes connected

More information

Physics 2A Chapters 6 - Work & Energy Fall 2017

Physics 2A Chapters 6 - Work & Energy Fall 2017 Physcs A Chapters 6 - Work & Energy Fall 017 These notes are eght pages. A quck summary: The work-energy theorem s a combnaton o Chap and Chap 4 equatons. Work s dened as the product o the orce actng on

More information

Spin-rotation coupling of the angularly accelerated rigid body

Spin-rotation coupling of the angularly accelerated rigid body Spn-rotaton couplng of the angularly accelerated rgd body Loua Hassan Elzen Basher Khartoum, Sudan. Postal code:11123 E-mal: louaelzen@gmal.com November 1, 2017 All Rghts Reserved. Abstract Ths paper s

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

Lagrange Multipliers. A Somewhat Silly Example. Monday, 25 September 2013

Lagrange Multipliers. A Somewhat Silly Example. Monday, 25 September 2013 Lagrange Multplers Monday, 5 September 013 Sometmes t s convenent to use redundant coordnates, and to effect the varaton of the acton consstent wth the constrants va the method of Lagrange undetermned

More information

4 Analysis of Variance (ANOVA) 5 ANOVA. 5.1 Introduction. 5.2 Fixed Effects ANOVA

4 Analysis of Variance (ANOVA) 5 ANOVA. 5.1 Introduction. 5.2 Fixed Effects ANOVA 4 Analyss of Varance (ANOVA) 5 ANOVA 51 Introducton ANOVA ANOVA s a way to estmate and test the means of multple populatons We wll start wth one-way ANOVA If the populatons ncluded n the study are selected

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

Finite Element Modelling of truss/cable structures

Finite Element Modelling of truss/cable structures Pet Schreurs Endhoven Unversty of echnology Department of Mechancal Engneerng Materals echnology November 3, 214 Fnte Element Modellng of truss/cable structures 1 Fnte Element Analyss of prestressed structures

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

STUDY ON TWO PHASE FLOW IN MICRO CHANNEL BASED ON EXPERI- MENTS AND NUMERICAL EXAMINATIONS

STUDY ON TWO PHASE FLOW IN MICRO CHANNEL BASED ON EXPERI- MENTS AND NUMERICAL EXAMINATIONS Blucher Mechancal Engneerng Proceedngs May 0, vol., num. www.proceedngs.blucher.com.br/evento/0wccm STUDY ON TWO PHASE FLOW IN MICRO CHANNEL BASED ON EXPERI- MENTS AND NUMERICAL EXAMINATIONS Takahko Kurahash,

More information

Lectures in Micro Meteorology

Lectures in Micro Meteorology Downloaded from orbt.dtu.dk on: Sep, 018 Lectures n Mcro Meteorology Larsen, Søren Ejlng Publcaton date: 015 Document Verson Publsher's PDF, also known as Verson of record Lnk back to DTU Orbt Ctaton (APA):

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

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

Introduction to Turbulence Modeling

Introduction to Turbulence Modeling Introducton to Turbulence Modelng Professor Ismal B. Celk West Vrgna nversty Ismal.Celk@mal.wvu.edu CFD Lab. - West Vrgna nversty I-1 Introducton to Turbulence CFD Lab. - West Vrgna nversty I-2 Introducton

More information

Week 11: Chapter 11. The Vector Product. The Vector Product Defined. The Vector Product and Torque. More About the Vector Product

Week 11: Chapter 11. The Vector Product. The Vector Product Defined. The Vector Product and Torque. More About the Vector Product The Vector Product Week 11: Chapter 11 Angular Momentum There are nstances where the product of two vectors s another vector Earler we saw where the product of two vectors was a scalar Ths was called the

More information

IC Engine Flow Simulation using KIVA code and A Modified Reynolds Stress Turbulence Model

IC Engine Flow Simulation using KIVA code and A Modified Reynolds Stress Turbulence Model IC Engne Flow Smulaton usng KIVA code and A Modfed Reynolds Stress Turbulence Model Satpreet Nanda and S.L. Yang Mechancal Engneerng-Engneerng Mechancs Department Mchgan Technologcal Unversty Houghton,

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

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

EVALUATION OF THE VISCO-ELASTIC PROPERTIES IN ASPHALT RUBBER AND CONVENTIONAL MIXES

EVALUATION OF THE VISCO-ELASTIC PROPERTIES IN ASPHALT RUBBER AND CONVENTIONAL MIXES EVALUATION OF THE VISCO-ELASTIC PROPERTIES IN ASPHALT RUBBER AND CONVENTIONAL MIXES Manuel J. C. Mnhoto Polytechnc Insttute of Bragança, Bragança, Portugal E-mal: mnhoto@pb.pt Paulo A. A. Perera and Jorge

More information

Physics 207: Lecture 20. Today s Agenda Homework for Monday

Physics 207: Lecture 20. Today s Agenda Homework for Monday Physcs 207: Lecture 20 Today s Agenda Homework for Monday Recap: Systems of Partcles Center of mass Velocty and acceleraton of the center of mass Dynamcs of the center of mass Lnear Momentum Example problems

More information

PHYSICS - CLUTCH CH 28: INDUCTION AND INDUCTANCE.

PHYSICS - CLUTCH CH 28: INDUCTION AND INDUCTANCE. !! www.clutchprep.com CONCEPT: ELECTROMAGNETIC INDUCTION A col of wre wth a VOLTAGE across each end wll have a current n t - Wre doesn t HAVE to have voltage source, voltage can be INDUCED V Common ways

More information

Nomenclature. I. Introduction

Nomenclature. I. Introduction Effect of Intal Condton and Influence of Aspect Rato Change on Raylegh-Benard Convecton Samk Bhattacharya 1 Aerospace Engneerng Department, Auburn Unversty, Auburn, AL, 36849 Raylegh Benard convecton s

More information

Spring 2002 Lecture #13

Spring 2002 Lecture #13 44-50 Sprng 00 ecture # Dr. Jaehoon Yu. Rotatonal Energy. Computaton of oments of nerta. Parallel-as Theorem 4. Torque & Angular Acceleraton 5. Work, Power, & Energy of Rotatonal otons Remember the md-term

More information

STAT 511 FINAL EXAM NAME Spring 2001

STAT 511 FINAL EXAM NAME Spring 2001 STAT 5 FINAL EXAM NAME Sprng Instructons: Ths s a closed book exam. No notes or books are allowed. ou may use a calculator but you are not allowed to store notes or formulas n the calculator. Please wrte

More information

Research & Reviews: Journal of Engineering and Technology

Research & Reviews: Journal of Engineering and Technology Research & Revews: Journal of Engneerng and Technology Case Study to Smulate Convectve Flows and Heat Transfer n Arcondtoned Spaces Hussen JA 1 *, Mazlan AW 1 and Hasanen MH 2 1 Department of Mechancal

More information

The Governing Equations

The Governing Equations The Governng Equatons L. Goodman General Physcal Oceanography MAR 555 School for Marne Scences and Technology Umass-Dartmouth Dynamcs of Oceanography The Governng Equatons- (IPO-7) Mass Conservaton and

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

DETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM

DETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM Ganj, Z. Z., et al.: Determnaton of Temperature Dstrbuton for S111 DETERMINATION OF TEMPERATURE DISTRIBUTION FOR ANNULAR FINS WITH TEMPERATURE DEPENDENT THERMAL CONDUCTIVITY BY HPM by Davood Domr GANJI

More information

Second Order Analysis

Second Order Analysis Second Order Analyss In the prevous classes we looked at a method that determnes the load correspondng to a state of bfurcaton equlbrum of a perfect frame by egenvalye analyss The system was assumed to

More information

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

Turbulence classification of load data by the frequency and severity of wind gusts. Oscar Moñux, DEWI GmbH Kevin Bleibler, DEWI GmbH

Turbulence classification of load data by the frequency and severity of wind gusts. Oscar Moñux, DEWI GmbH Kevin Bleibler, DEWI GmbH Turbulence classfcaton of load data by the frequency and severty of wnd gusts Introducton Oscar Moñux, DEWI GmbH Kevn Blebler, DEWI GmbH Durng the wnd turbne developng process, one of the most mportant

More information

Flow equations To simulate the flow, the Navier-Stokes system that includes continuity and momentum equations is solved

Flow equations To simulate the flow, the Navier-Stokes system that includes continuity and momentum equations is solved Smulaton of nose generaton and propagaton caused by the turbulent flow around bluff bodes Zamotn Krll e-mal: krart@gmal.com, cq: 958886 Summary Accurate predctons of nose generaton and spread n turbulent

More information