Übung zur Meteorologischen Modellierung (Numerik): Das barotrope Modell

Size: px
Start display at page:

Download "Übung zur Meteorologischen Modellierung (Numerik): Das barotrope Modell"

Transcription

1 Ün zr Meeoroloischen Modelliern Nmerik: Ds rorope Modell Beside is impornce for concepl nd nlicl sdies of he lre- nd snopic-scle circlion, he roropic model is of hisoricl ineres. I ws he firs workin nmericl weher predicion model in is qsi-eosrophic non-dieren ersion; Chrne, J. G., Fjorof, R. nd on Nemnn, J. 95: Nmericl inerion of he roropic orici eqion. Tells,, 7 5. The followin ies he sics on deelopin nd prormmin sch model spplemenin he lecre. The im is o prorm, o es nd o rn or own roopic model.. Eqions The roropic model represens he dnmic of homoeneos incompressile flid which is in hdrosic lnce. This m e epressed sin he horizonl eqions of moion for, nd he conini eqion. Assmin roropic condiions no chne of elociies wih heih, i.e. no herml wind, no ericl decion, no fricion, nd sin cresin z- coordines, he eqion of moions red P ρ f P ρ f Wih Coriolis prmeer f, pressre p, nd consn densi. The conini eqion wih consn reds z w Wih ericl eloci w. B inerin he hdrosic eqion z P P/ in he eqions of moions cn e replced he eopoenil h: h f h f Inerin he conini eqion from z= wih w= o h nd sin h h h d dh w h pronosic eqion for he eopoenil h is opined needed in he eqions of moion:

2 h h h h These eqions form closed ssem wih hree nknows: he so clled 'primiie eqions' of he dieren roropic model or 'shllow wer model' Alhoh his model m lred e soled nmericll, we will ppl some simplificions pproimions o mke he nmericl remen mch esier e.., we he lred sed he hdrosic lnce o oin dinosic relion eween pressre nd eopoenil. Firs, he Coriolis prmeer f is linerized o reference lide wih f =f : f d df f f Which is commonl clled 'e plne pproimion'. A second pproimion, lid for he lre snopic scle circlion in he mid-lides is he qsi-eosrophic pproimion: Usin scle nlsis see lecre Theoreicl Meeorolo i cn een shown h eosrophic eqilirim is firs order pproimion for smll Ross nmers Ro=U/Lf <<. i spliin he flow, nd he diiion of he eopoenil from men le h ino eosrophic,,,h nd smll; ORo eosrophic,,h pr = +,= +,h=h +h +h, ii inserin his ino he shllow wer eqions, iii pplin scle nlsis, i eliminin eosroph, sin he non-dierence of he eosrophic pr, nd i nelecin ll erms smller hn ORo, we derie ssem for he emporl chne of he eosrophic flow: h f h f h h h h Inrodcin he eosrophic orici, he firs wo eqions cn e comined o he qsi-eosrophic roropic orici eqion, nd he ssem redces o f h h h h Usin eosrophic lnce, eosrophic sremfncin cn e inrodced, =h /f, wih

3 Eliminin he dierence of he eosrophic flow nd sin he eosrophic sremfncion we derie he qsi-eosrophic dieren roropic model qsi-eosrophic shllow wer model: J, Wih onl one pronosic rile, he sremfncion, his model compleel descries he flow wihin he scope of he pplied pproimions. Here is he Ross rdis of deformion =h / /f, nd J,=/ / - / / he Jcoi operor. Noe h he erm - in he Jcoi operor i.e. he decion of hickness he eosrophic flow is onl formll kep in he eqion, since J,- - =. An een more drsic pproimion is o oll disrerd he dierence. Then, he dnmic is redced o he non-dieren roropic model he non-dieren roropic orici eqion, which, s wrien oe, ws ilized for he firs workin nmericl weher predicion: or J, A hird ersion of he roropic model is he so clled eqilen roropic model, which hs een ofen sed in he einnin of nmericl weher predicion nd for heoreicl sdies. To rel he roropic condiion no herml wind, keepin simple ssem, i is ssmed h srenh no he direcion of he wind m chne wih heih. The ericl profile of he flow Ap is ssmed o e independen in spce, nd ime. Then, he horizonl flow, cn e wrien s Ap<>,,,<>,,, wih ericl ere <.> nd <A> =. Here common in meeoroloicl pplicions, p-coordines re sed in he ericl. Inrodcin he rle *=<A > we oin: * A p s * * J, * This model is lid for leel p* wih Ap*=<A >, he so clled eqilen-roropic leel. Tpicl wind profiles ie p* of o 6-5hP. This leel is in prcice idenicl wih he leel of minimm dierence.

4 Forml, he difference eween he hree qsi-eosrophic ersions lies in he fcor Ap s, in he erm represenin he emporl chne of he eopoenil enerion of orici srechin: Ap s = resls in he non-dieren model where orici is chned decion of sol orici onl. Ap s = resls in he shllow wer eqions. Here, decion of sol orici nd chne of hickness de o dierence/conerence conrie o he orici endenc. Ap s deermines he effec of dierence on he orici prodcion wihin he eqilen roropic ler. In prcice, he choise of Ap s conrols he phse speed of Ross wes which hs conseqences for he qli of he weher predicion. Ths, Ap s m e sed s nin prmeer o improe he forecs scill empiricll.. Nmericl Solion To sole he roropc modell nmericll, differen mehods m e pplied. rid-poin, semi-lrne, specrl, finie elemens. Here, we will se 'clssicl' rid-poin mehod. We focs on he simples roropic model: The non-dieren ersion. As mih e seen from he eqions, oin o he qsi-eosrophic shllow wer model or o he qsieosrophic eqilen roropic model is es, while solin he primiie eqion ersion needs some more effor. From he respecie eqion J, We see h we need o compe he emporl eolion of he sremfncion, which onl depends on he sremfncion iself. From sremfncion we re le o dinose ll rile needed, like wind, orici, nd eopoenil. Ths, he nmericl im is o compe new sremfncion field on discree ime is from ien one pls pproprie ondr condiions, nlo o he nmericl solion of he nonliner decion prolem see Meeoroloische Modelliern/Nmerik pr one. In principle we he o do he followin: Srin from iniil condiion for he sremfncion or he eopoenil nd sin sile ondr condiions in, we he o sole / =. To o his we he i o compe he rih hnd side forcin from ien. This is done nmericl pproimions/discreizions for he deriies in spce or he Jcoi operor. ii Then we he o sole he Poisson- or Helmholz- eqion G, o e / =. iii Finll we he o do he emporl erpolion ime sep o oin =. These hree seps i-iii re repeed nil we he he finl he end of he predicion =T. Before solin he model nmericll sin rid poin scheme, we need o define he model domin nd sile rid. in ddiion we need o choose deqe les for he free prmeers f,,, ec.. Since he eqions re formled in cresin coordines on - plne, cnl in zonl direcion for meeoroloicl pplicion or sqred sin ocen m e chosen s he domin. proper rid m e cresin rid wih NM rid poins. The ridsize resolion in - nd -direcion needs o e deermined from he processes

5 5 nder considerion nd he ille comper power. The resolion nd he processes lso se he mimm ime sep since we he o flfill he Corn-Friedrich-Le crierion. In he non-dieren qsi-eosrophic model, he ime sep is in enerl deermined he phse speed of he reliel slow Ross-wes. Dependin on he men flow nd he scle of he lres Ross we, ime sep of o hor is possile sin rid size of c. km sin primiie eqions, mch fser e.. ri wes wold reqire mch shorer ime sep. As he domin is limied, we need o inrodce pproprie ondr condiions o compe, e.., he deriies. For cnl, cclic ondr condiions cn e sed in -direcion i.e., = N, nd N+, =,, wih nd N indicin he firs nd ls rid poin in. A he meridionl ondries i is commonl ssmed h he norml componen of he flow nishes no rnspor cross he ondr. This is oined sein consn in i.e.,=c,,m+=c. To implemen he model procedre we finll need o deermine he nmericl pproimions for he indiidl prs, i.e. compin he Jcoi-operor, he Lplceoperor, he horizonl deriies, solin he Poisson- Helmholz- eqion, nd erpolin in ime. Jcoi-Operor There re rios mehods o pproime he Jcoi-operor finie differences, which follow from he nlicl epression:, J For he discreizion we will se he respecie rid poin iself, =i,j, nd he srrondin 8 poins -8, which re loced s follows: 6 = i-,j+ = i,j+ 5 = i+,j+ = i-,j = i,j = i+,j 7 = i-,j- = i,j- 8 = i+,j- For he oe hree epressions of he Jcopi-operor we oin he followin pproimions: } { } { } { J J J

6 The cl pproimion J resls from liner cominion of hese J, J nd J : J = J + J + J. Arkw 966 shows h ===/ is he es cominion s i wrrns he imporn conserions of ener nd ensroph of he ssem. Lplce-Operor The Lplce-operor,, cn e pproimed cenered differences: i, j sin he sme indices s for he Jcoi-operor. Horizonl Deriies Also for he deriies in - nd -direcion, we cn se cenrl differences: Poisson- Helmholz- Eqions An essenil pr of he roropic qsi-eosrophic model is o sole he Poisson- G, or Helmholz- G, eqion o compe from known G, ech ime sep. A poenil procedre is he Gß-Seidel mehod or i improemen, he Sccessie Oer-Relion SOR, which in he followin will e eplined sin he Poisson-eqion: Srin poin is he discree represenion of he Lplce-operor see oe. Inserin i we oin for he discree Poisson-eqion G G from his we m formll compe for eer rid poin. Howeer, depends on he lso nknown rid poins,, nd. Ths, direc solion is no possile, n pproimie solion cn e fond ierion: Firs we compe he error = G for prescried iniil field e.. ll poins or, perhps eer, he preios ime sep. is comped followin he eqion oe. Ne we correc wih o oin new improed = ' : 6

7 ' ε / G / Afer compin new for eer rid poin he procedre compin nd correcin is repeed nil mesre of he ol error e.. he sm of ll errors sqred is elow predefined limi, or if ien nmer of ierions hs een mde. Noe: s cn e seen, we cn compe new wiho eplicil compin. Howeer, his procedre is no e he Gß-Seidel mehod he Jcoi mehod. Thoh he Jcoi mehod looks nice, i cn, in enerl, no e sed in prcice, s i rns o o coner onl er slowl ins he rel nlic solion. The Gß-Seidel mehod ssnill improes he conerence re. The ide is no o se onl he 'old' o compe he new ' lso o ilize he new ' whereer i is possile. If, for emple, he domin pssed line--line from he pper lef o he lower rih, we cn lred se he new ' poin nd. Ths, he new ' is ien ' ' ' G / Tpicll we need N p/ ierionsn for NN rid o decrese he iniil error fcor -p which is n improemen of fcor compred o he Jcoi mehod. Sill his is reliel lre effor. A ssnil redcion cn e chieed sin he Sccessie Oer-Relion SOR mehod. Here we do no correc he old, oer-correc i, wih < < : ' ωε / ω ' ' G / Ain we se lso he ille new. The nmer of necessr ierions o redce he iniil error -p is diminished o N p/, sin n opiml, h is fcor of N in comprison o Gß-Seidel noe h N is picll er lre. Unfornel, he choice of is difficl, nd, for norml pplicions, onl possile sin ril-nd-error. The solion of Helmholz eqion follows he sme sre epndin he discree Lplce-operor he erm. Noe h here re rios oher mehods o sole he Poisson- Helmholz- prolem, incldin he se of Forier epnsion of mli-rid mehods. Deriie in Time To erpole ino he fre, i.e. o compe he les for he ne ime sep, we need o pproime he deriie in ime nmericll. As we he ssen for he dec or decion eqion see lecre he eis rios mehods. Here we m se n nmericll se 7

8 mehod. Implici echniqes, howeer, m no e plicle de o he complei of he prolem non-lineriies. In meeorolo he lepfro scheme hree leel scheme, see lecre oeher wih he Roer-Asselin filer o redce he compionl mode is commonl sed, nd m lso e sed here: * * F * Wih filer consn F picll F=.. As he lepfro scheme needs wo ime leels o compe he ne one, noher scheme like he eplici Eler needs o e sed he einnin of he inerion.. Implemenion The implemenion of he oe descried roropic model needs reliel lre mon of prormmin, which is nrll prone o errors heoreicl nd echnicl. Therefor i is preferle o srcre nd prorm he model in smller nis, which cn e esed seprel nd in cominion modlr srcre. Followin his w, we cree i i sroines of indiidl componens, which hen re comined wihin min prorm. These componens m e: - Inp nd op - Grid definiion - Horizonl deriies - Lplce-operors - Jcoi-operors - Temporl erpolion lep fro nd Eler - Poisson-eqion - Bondr condiions - Ohers Bildin he min prorm m e he sr of he sk. I defines he work flow of he model nd he inercion eween he differen componens. Ain, he srcrin cn e fcilied sin sroines nd/or fncions for indiidl prs. In ddiion, we he o decide nd o define he lol riles sclrs nd rrs nd o ie hem self eplinin nmes. These riles m e defined wihin forrn 'modl'. Clls o respecie sroines, nd 'dmm' sroines sroines which he momen do nohin m lso lred e inclded in he code. Ler hose dmmies re replced he cl roines. Afer codin he min prorm i needs o e esed compiled. In second sep we m code he inp nd op of he model. Prmeer conrollin he model rn, nd, perhps, iniil condiions for he sremfncions, ec., need o e red in. Op like he prediced sremfncion, winds, ec., need o wrien o for ien op inerl. Addiionll some conrol prmeer e.. nmer of ierions in he Poisson soler m e wrien. The choice of he op form is n imporn isse o mke he resls es o se. Afer complein he more echnicl work we cn sr wih he phsicl pr of he model. Firs we he o iniilize he model. Prmeer, which he no een se or which depend on he inp need o e comped/se. For emple, definin he rid lides, lonides, disnces, ec. is pr of he iniilizion, s well s he iniilizion of he pronosic field. 8

9 Finll, he so fr dmm roines for ll componens need o e replced. Here, inensie esin is indispensle. For compliced roines, e.. he Poisson-soler, his m e done independen from he res of he model. Afer complein he codin, he phsicl correcness of he model needs o e esed. Th is, he models nmericl solion for priclr cses needs o e compred wih oher resls. In he es cse wih nlic solion, or wih resls from oher models which he een plished. For he roropic model, he Ross -Hrwiz- we is ood es cse s. lecre 'Theoreische Meeoroloie' s i is n nlic solion. If he model rees wih wih known solions, we cn sr doin some eperimens.. The Code The lime im is o ild non-dieren roropic model s descried oe. Howeer, s lred noed, ssnil ime for prormin is needed, which m eceed he ille ime for he lecre. Ths, we m se he prepred prorm 'ro.f9' s srin poin, which lred conins some of he componens infos will e ien drin he lecre. To complee ro.f9 we need o replce he followin dmm sroines: sor: Solin he Poisson-eqion inerse Lplce wih 'Sccessie Oer-Relion' SOR mkdfd: Compe deriies in -direcion lplce: Appl he Lplce-operor o field jcoi: Appl he Jcoi-operor o wo fields eler: Do eplici Eler ime sep lepfro: Do he lepfro ime sep wih filer sor Solin he Poisson-eqion sin he SOR mehod is he mos comple pr of he model. We need he dimensions of he field, he ridpoin disnces in - nd -direcion, nd he inp filed he orici endencies. Oo is he inerse Lplce of he inp he sremfncion endencies. This is cconed for in he dmm sroine sor: sroine sorpdf,pf,pd,pd,k,k implici none sroine sor compe he inerse Lplcin from ien field sin he Sccessie OerRelion mehod SOR ineer :: k dimension ineer :: k dimension rel :: pd rid poin disnce rel :: pd rid poin disnce rel :: pdf:k+,:k+ inp: field rel :: pf:k+,:k+ op: inerse Lplcin of inp rern end Noe h dimensions of he fields rrs inclde he ondries,n+. To complee he sor sroine we m dd he followin prs:. Compe he iniil error = G, s. secion SOR oe. oer- correc he iniil solion. Compe he new error 9

10 . Repe nd nil he mesre of he error is 'smll enoh' or nil he errormesre is redced fcor I m e conenien o noe: Se he ondr condiions fer ech ierion. The comper precision limis he redcion of he error. Sr wih smll redcion, s fcor. c Se mimm of ierions no o prodce ded-loop heoreicll o need N p/ ierions for NN o redce he error p. mkdfd To compe -deriies sin cenrl differences we need he dimension of he field, he rid disnce in -direcion, nd he inp field. Op is he -deriie of he inp field. Therefore, he dmm sroine mkdfd is: sroine mkdfdpf,pdfd,pd,k,k implici none sroine mkdfd compes deriion from field sin cenrl differences ineer :: k -dimension ineer :: k -dimension rel :: pd rid disnce rel :: pf:k+,:k+ inp: field rel :: pdfd:k+,:k+ op: dfield/d rern end As we lred sed cenrl differences in he ls semeser decion, complein mkdfd m e no e oo dificl. lplce The Lplce-operor shold e pproimed cenrl differences. We need he dimension of he field, he rid disnce in - nd -direcion, nd he inp field. Op is he Lplce of he inp: sroine lplcepf,pdf,pd,pd,k,k implici none sroine lplce compes he lplcin from field ineer :: k -dimension ineer :: k -dimension rel :: pd rid disnce rel :: pd rid disnce rel :: pf:k+,:k+ inp: field rel :: pdf:k+,:k+ op: Lplcin rern end To complee lplce is srihforwrd. jcoi Codin he conserie Jcoi-operer fer Arkw, see oe needs i more work. In priclr we he o e crefl sin he correc indices. We need he dimensions, he rid disnce in - nd -direcion, nd he inp fields. Op is he Jcoi-operor pplied o he inp fields:

11 sroine jcoip,p,pj,pd,pd,k,k implici none sroine jcoi compes he jcoi operor ccordin o Arkw 966 jcoi,=j+j+j/. fer Arkw 966 ineer :: k -dimension ineer :: k -dimension rel :: p:k+,:k+ inp: field rel :: p:k+,:k+ inp: field rel :: pj:k+,:k+ op: jcoi, rel :: pd rid disnce rel :: pd rid disnce rern end We m se emporr rrs for he hree differen Jcois, which needs o e declred oo. eler Codin he eplici Eler is n es sk rememer he dec eqion. We need he dimension of he field, he ime sep, he endenc, nd he cl field ime=. Op is he filed he ne ime sep +: sroine elerpfm,pdfd,pf,pdel,k,k implici none sroine eler does n eplici Eler ime sep ineer :: k dimension ineer :: k dimension rel :: pdel ime sep [s] rel :: pfm:k+,:k+ inp f rel :: pdfd:k+,:k+ inp endenc rel :: pf:k+,:k+ op f+ rern end To complee eler, we onl need one ddiionl line of code. lepfro Compred o he eplici Eler implemenin he filered lepfro needs i more work hoh we lred did i for he decion eqion ls semeser. We need he dimension of he fields, he ime sep or wo imes he imesep, he endenc, cl field ime=, nd he filered field for -. Op is he filed he ne ime sep + nd he filered field for ime, which re se s nd filered -, especiel, drin he ne imesep. Here, i is ssmed h he old fields re replced he new ones: sroine lepfropf,pfm,pdfd,pdel,k,k implici none sroine lepfro does lepfro ime sep wih Roer Asselin filer ineer :: k dimension ineer :: k dimension

12 rel :: pdel.* imesep rel :: pf:k+,:k+ inp/op f rel :: pfm:k+,:k+ inp/op f- filered rel :: pdfd:k+,:k+ inp endenc rern end lepfro m e cmpleed ccordin o he eqions oe or from he lecre ls semeser. Rememer he replcemen -> - nd + -> he end of he roine. 5. Prolems 5.. Codin he model: Bild he non-dieren roropic model sin he oe nd, perhps, ien emples. Tes he model simlin he Ross-Hrwiz we. The code 'ro.f9' 'homepe' lred incldes lmos ll seins necessr: Modle romod conins he dimensions NX nd NY of he chnnel 6 nd, resp., he lonidinl nd meridionl een chnnel, chnnel; 6 nd, he cenrl lide rl; 5 N, nd he imesep del; s. Sroine iniil iniilizes he sremfncion wih we nmer in -direcion.5 in -direcion. Yo onl need o se he nmer of imeseps nrn. A he einnin nrn m se o o es he iniil condiion nd he firs predicion sep. If he resls look ok o m rn finl es wih nrn=. 5.. Broropic insili: I cn e shown e.. Holon h nder cerin condiions zonll smmeric flow cn e nsle, i.e. smll iniil disrnces erc kineic ener from he zonl flow nd row wih ime. On he oher hnd siions eis where disrnces ie kineic ener o he zonl flow roropic sili, which is dominn on he lre scle. A condiion for zonl je o e roropicll nsle is zero of he sole in enerl, he poenil orici wihin he domin, i.e. [ U ] somewhere he criicl lide c. Here [U] denoes he zonl ered zonl wind je. Broropic insili cn e nlicll or nmericll sdied inesiin he ehior of perrions in differen zonl men jes. I is reliel es o show h simple cosineprofile [U]=cosπ/B; wih B=widh of he chnnel is lws sle. Howeer, he profile U [ U] m cos B m e nsle U m is he wind speed in he cener of he je. Dependin on he srenh of he je nd he wenmer of he disrnce, we cn find sle, nerl or nsle siions i.e. he disrnce will decrese, s consn of increse. In enerl: srin from cerin minimm eloci of he je wes wih wenlenhs smller hn criicl le L c re sle ie ener o he zonl men flow, wes loner hn L c shorer h second criicl le L re nsle in ener from he zonl flow, nd er lon

13 wes L > L re nerl heir ener ss consn. For he hree clsses he followin pplies:. Sle: The phse eloci of he we is lrer hn he wind speed of he je he criicl lie. Unsle: The phse eloci of he we is posiie smller hn he windspeed of he je he criicl lide.. Nerl: The phse eloci of he we is neie. The eloci of he je he criicl lide, nd he phse eloci which sepres nd Cn, cn e comped from he insili condiion for he je: [ U m U] c Cn B Sd/erif sin or roropic model he sili properies of he oe je-profile. Vr he welenh of he perrion keepin U m consn. Anlse he emporl eolion of he kineic ener of he disrnce nd of he zonl men flow. Which re he les for he criicl welenhs? How des he meridionl srcre looks like for he sle nd he nsle cse? Yo m se he followin sep: - Chnnel s in he oriinl model U m =m/s - Meridionl wenmer of he disrnce =.5 s in 5. - d of inerion wih mines imesep Noes: To inclde he je-profile o need o chne he ondr condiions sroine ondr. So fr, he sremfncion is se o he meridionl ondries which does no llow for je. The new condiion in m e he zonl ere of he sremfncion poin = for nd =NY for NY+. In sroine iniil he je needs o e inclded in he iniil condiions. For sremfncion, he profile is U [ ] m B sin B c In sroine iniil o cn choose he -we nmer of he perrion prmeer zk. d I cn e sefl o inclde he ener dinosics in he model e.. in sroine roo, priioned in zonl men nd perrion. e De o he nmerics inecness of he mehod nd/or he nmericl precision of he comper o m no epec h nerl wes ecl pper 5.. Weher predicion: The non-dieren roropic model ws he firs workin weher predicion model. De o ll pproimions enerin he model i cn, of corse, no compee wih se-of-he-r predicion models. Howeer, o m r predicion sin or model. For his prpose file inp.d is proided he 'homepe'. I conins iniil nd erificion d for 6-horl predicion for eopoenil on he model rid 6; i.e. for

14 he complee chnnel incl. ondr for he ime..96 : o..96 : Hmr sorm sre In ddiion, file inp.cl proides rds-conrol file o plo he d. Noes: To red he d, o m se sroine iniil. The d re nformed nd m e red sin open,file='inp.d',form='nformed' red f:nx,:ny+ close Usin mliple reds o m skip ime seps o choose differen iniil imes. As i is eopoenil o need o diide f o e sremfncion. c Imporn: To keep he model nmericll sle o m keep he meridionl ondr condiion poins nd NY+ consn sin he iniil les. This cn e done remoin he sein of he ondr condiions for he respecie poins in sroine ondr.

Introduction to Numerical Modeling. 7. An Example: QG Barotropic Channel Model (Weather Prediction)

Introduction to Numerical Modeling. 7. An Example: QG Barotropic Channel Model (Weather Prediction) Inrodcion o Nmericl Modelin 7. An Emple: QG Broropic Chnnel Model Weher Predicion Frnk Lnkei The Broropic Model - Firs fncionin nmericl weher predicion model Chrne, J. G., Fjorof, R. nd on Nemnn, J. 95.

More information

15/03/1439. Lecture 4: Linear Time Invariant (LTI) systems

15/03/1439. Lecture 4: Linear Time Invariant (LTI) systems Lecre 4: Liner Time Invrin LTI sysems 2. Liner sysems, Convolion 3 lecres: Implse response, inp signls s coninm of implses. Convolion, discree-ime nd coninos-ime. LTI sysems nd convolion Specific objecives

More information

3 Motion with constant acceleration: Linear and projectile motion

3 Motion with constant acceleration: Linear and projectile motion 3 Moion wih consn ccelerion: Liner nd projecile moion cons, In he precedin Lecure we he considered moion wih consn ccelerion lon he is: Noe h,, cn be posiie nd neie h leds o rie of behiors. Clerl similr

More information

A Kalman filtering simulation

A Kalman filtering simulation A Klmn filering simulion The performnce of Klmn filering hs been esed on he bsis of wo differen dynmicl models, ssuming eiher moion wih consn elociy or wih consn ccelerion. The former is epeced o beer

More information

A 1.3 m 2.5 m 2.8 m. x = m m = 8400 m. y = 4900 m 3200 m = 1700 m

A 1.3 m 2.5 m 2.8 m. x = m m = 8400 m. y = 4900 m 3200 m = 1700 m PHYS : Soluions o Chper 3 Home Work. SSM REASONING The displcemen is ecor drwn from he iniil posiion o he finl posiion. The mgniude of he displcemen is he shores disnce beween he posiions. Noe h i is onl

More information

PHYSICS 1210 Exam 1 University of Wyoming 14 February points

PHYSICS 1210 Exam 1 University of Wyoming 14 February points PHYSICS 1210 Em 1 Uniersiy of Wyoming 14 Februry 2013 150 poins This es is open-noe nd closed-book. Clculors re permied bu compuers re no. No collborion, consulion, or communicion wih oher people (oher

More information

Physic 231 Lecture 4. Mi it ftd l t. Main points of today s lecture: Example: addition of velocities Trajectories of objects in 2 = =

Physic 231 Lecture 4. Mi it ftd l t. Main points of today s lecture: Example: addition of velocities Trajectories of objects in 2 = = Mi i fd l Phsic 3 Lecure 4 Min poins of od s lecure: Emple: ddiion of elociies Trjecories of objecs in dimensions: dimensions: g 9.8m/s downwrds ( ) g o g g Emple: A foobll pler runs he pern gien in he

More information

September 20 Homework Solutions

September 20 Homework Solutions College of Engineering nd Compuer Science Mechnicl Engineering Deprmen Mechnicl Engineering A Seminr in Engineering Anlysis Fll 7 Number 66 Insrucor: Lrry Creo Sepember Homework Soluions Find he specrum

More information

2D Motion WS. A horizontally launched projectile s initial vertical velocity is zero. Solve the following problems with this information.

2D Motion WS. A horizontally launched projectile s initial vertical velocity is zero. Solve the following problems with this information. Nme D Moion WS The equions of moion h rele o projeciles were discussed in he Projecile Moion Anlsis Acii. ou found h projecile moes wih consn eloci in he horizonl direcion nd consn ccelerion in he ericl

More information

2IV10/2IV60 Computer Graphics

2IV10/2IV60 Computer Graphics I0/I60 omper Grphics Eminion April 6 0 4:00 7:00 This eminion consis of for qesions wih in ol 6 sqesion. Ech sqesion weighs eqll. In ll cses: EXPLAIN YOUR ANSWER. Use skeches where needed o clrif or nswer.

More information

THE EXTENDED TANH METHOD FOR SOLVING THE -DIMENSION NONLINEAR DISPERSIVE LONG WAVE EQUATION

THE EXTENDED TANH METHOD FOR SOLVING THE -DIMENSION NONLINEAR DISPERSIVE LONG WAVE EQUATION Jornl of Mhemil Sienes: Adnes nd Appliions Volme Nmer 8 Pes 99- THE EXTENDED TANH METHOD FOR SOLVING THE ( ) -DIMENSION NONLINEAR DISPERSIVE LONG WAVE EQUATION SHENGQIANG TANG KELEI ZHANG nd JIHONG RONG

More information

MTH 146 Class 11 Notes

MTH 146 Class 11 Notes 8.- Are of Surfce of Revoluion MTH 6 Clss Noes Suppose we wish o revolve curve C round n is nd find he surfce re of he resuling solid. Suppose f( ) is nonnegive funcion wih coninuous firs derivive on he

More information

ENGR 1990 Engineering Mathematics The Integral of a Function as a Function

ENGR 1990 Engineering Mathematics The Integral of a Function as a Function ENGR 1990 Engineering Mhemics The Inegrl of Funcion s Funcion Previously, we lerned how o esime he inegrl of funcion f( ) over some inervl y dding he res of finie se of rpezoids h represen he re under

More information

1. Find a basis for the row space of each of the following matrices. Your basis should consist of rows of the original matrix.

1. Find a basis for the row space of each of the following matrices. Your basis should consist of rows of the original matrix. Mh 7 Exm - Prcice Prolem Solions. Find sis for he row spce of ech of he following mrices. Yor sis shold consis of rows of he originl mrix. 4 () 7 7 8 () Since we wn sis for he row spce consising of rows

More information

Minimum Squared Error

Minimum Squared Error Minimum Squred Error LDF: Minimum Squred-Error Procedures Ide: conver o esier nd eer undersood prolem Percepron y i > 0 for ll smples y i solve sysem of liner inequliies MSE procedure y i i for ll smples

More information

Minimum Squared Error

Minimum Squared Error Minimum Squred Error LDF: Minimum Squred-Error Procedures Ide: conver o esier nd eer undersood prolem Percepron y i > for ll smples y i solve sysem of liner inequliies MSE procedure y i = i for ll smples

More information

Motion. Part 2: Constant Acceleration. Acceleration. October Lab Physics. Ms. Levine 1. Acceleration. Acceleration. Units for Acceleration.

Motion. Part 2: Constant Acceleration. Acceleration. October Lab Physics. Ms. Levine 1. Acceleration. Acceleration. Units for Acceleration. Moion Accelerion Pr : Consn Accelerion Accelerion Accelerion Accelerion is he re of chnge of velociy. = v - vo = Δv Δ ccelerion = = v - vo chnge of velociy elpsed ime Accelerion is vecor, lhough in one-dimensionl

More information

Physics 101 Lecture 4 Motion in 2D and 3D

Physics 101 Lecture 4 Motion in 2D and 3D Phsics 11 Lecure 4 Moion in D nd 3D Dr. Ali ÖVGÜN EMU Phsics Deprmen www.ogun.com Vecor nd is componens The componens re he legs of he righ ringle whose hpoenuse is A A A A A n ( θ ) A Acos( θ) A A A nd

More information

1. Consider a PSA initially at rest in the beginning of the left-hand end of a long ISS corridor. Assume xo = 0 on the left end of the ISS corridor.

1. Consider a PSA initially at rest in the beginning of the left-hand end of a long ISS corridor. Assume xo = 0 on the left end of the ISS corridor. In Eercise 1, use sndrd recngulr Cresin coordine sysem. Le ime be represened long he horizonl is. Assume ll ccelerions nd decelerions re consn. 1. Consider PSA iniilly res in he beginning of he lef-hnd

More information

(b) 10 yr. (b) 13 m. 1.6 m s, m s m s (c) 13.1 s. 32. (a) 20.0 s (b) No, the minimum distance to stop = 1.00 km. 1.

(b) 10 yr. (b) 13 m. 1.6 m s, m s m s (c) 13.1 s. 32. (a) 20.0 s (b) No, the minimum distance to stop = 1.00 km. 1. Answers o Een Numbered Problems Chper. () 7 m s, 6 m s (b) 8 5 yr 4.. m ih 6. () 5. m s (b).5 m s (c).5 m s (d) 3.33 m s (e) 8. ().3 min (b) 64 mi..3 h. ().3 s (b) 3 m 4..8 mi wes of he flgpole 6. (b)

More information

4.8 Improper Integrals

4.8 Improper Integrals 4.8 Improper Inegrls Well you ve mde i hrough ll he inegrion echniques. Congrs! Unforunely for us, we sill need o cover one more inegrl. They re clled Improper Inegrls. A his poin, we ve only del wih inegrls

More information

Contraction Mapping Principle Approach to Differential Equations

Contraction Mapping Principle Approach to Differential Equations epl Journl of Science echnology 0 (009) 49-53 Conrcion pping Principle pproch o Differenil Equions Bishnu P. Dhungn Deprmen of hemics, hendr Rn Cmpus ribhuvn Universiy, Khmu epl bsrc Using n eension of

More information

CSE 5365 Computer Graphics. Take Home Test #1

CSE 5365 Computer Graphics. Take Home Test #1 CSE 5365 Comper Graphics Take Home Tes #1 Fall/1996 Tae-Hoon Kim roblem #1) A bi-cbic parameric srface is defined by Hermie geomery in he direcion of parameer. In he direcion, he geomery ecor is defined

More information

Physics 2A HW #3 Solutions

Physics 2A HW #3 Solutions Chper 3 Focus on Conceps: 3, 4, 6, 9 Problems: 9, 9, 3, 41, 66, 7, 75, 77 Phsics A HW #3 Soluions Focus On Conceps 3-3 (c) The ccelerion due o grvi is he sme for boh blls, despie he fc h he hve differen

More information

Chapter Direct Method of Interpolation

Chapter Direct Method of Interpolation Chper 5. Direc Mehod of Inerpolion Afer reding his chper, you should be ble o:. pply he direc mehod of inerpolion,. sole problems using he direc mehod of inerpolion, nd. use he direc mehod inerpolns o

More information

Flow Networks Alon Efrat Slides courtesy of Charles Leiserson with small changes by Carola Wenk. Flow networks. Flow networks CS 445

Flow Networks Alon Efrat Slides courtesy of Charles Leiserson with small changes by Carola Wenk. Flow networks. Flow networks CS 445 CS 445 Flow Nework lon Efr Slide corey of Chrle Leieron wih mll chnge by Crol Wenk Flow nework Definiion. flow nework i direced grph G = (V, E) wih wo diingihed erice: orce nd ink. Ech edge (, ) E h nonnegie

More information

Properties of Logarithms. Solving Exponential and Logarithmic Equations. Properties of Logarithms. Properties of Logarithms. ( x)

Properties of Logarithms. Solving Exponential and Logarithmic Equations. Properties of Logarithms. Properties of Logarithms. ( x) Properies of Logrihms Solving Eponenil nd Logrihmic Equions Properies of Logrihms Produc Rule ( ) log mn = log m + log n ( ) log = log + log Properies of Logrihms Quoien Rule log m = logm logn n log7 =

More information

ME 425: Aerodynamics

ME 425: Aerodynamics ME 45: Aerodnamics Dr. A.B.M. Toiqe Hasan Proessor Deparmen o Mechanical Engineering Bangladesh Uniersi o Engineering & Technolog BUET, Dhaka Lecre-7 Fndamenals so Aerodnamics oiqehasan.be.ac.bd oiqehasan@me.be.ac.bd

More information

An object moving with speed v around a point at distance r, has an angular velocity. m/s m

An object moving with speed v around a point at distance r, has an angular velocity. m/s m Roion The mosphere roes wih he erh n moions wihin he mosphere clerly follow cure phs (cyclones, nicyclones, hurricnes, ornoes ec.) We nee o epress roion quniiely. For soli objec or ny mss h oes no isor

More information

Average & instantaneous velocity and acceleration Motion with constant acceleration

Average & instantaneous velocity and acceleration Motion with constant acceleration Physics 7: Lecure Reminders Discussion nd Lb secions sr meeing ne week Fill ou Pink dd/drop form if you need o swich o differen secion h is FULL. Do i TODAY. Homework Ch. : 5, 7,, 3,, nd 6 Ch.: 6,, 3 Submission

More information

CSE-4303/CSE-5365 Computer Graphics Fall 1996 Take home Test

CSE-4303/CSE-5365 Computer Graphics Fall 1996 Take home Test Comper Graphics roblem #1) A bi-cbic parameric srface is defined by Hermie geomery in he direcion of parameer. In he direcion, he geomery ecor is defined by a poin @0, a poin @0.5, a angen ecor @1 and

More information

Motion in a Straight Line

Motion in a Straight Line Moion in Srigh Line. Preei reched he mero sion nd found h he esclor ws no working. She wlked up he sionry esclor in ime. On oher dys, if she remins sionry on he moing esclor, hen he esclor kes her up in

More information

An Integral Two Space-Variables Condition for Parabolic Equations

An Integral Two Space-Variables Condition for Parabolic Equations Jornl of Mhemics nd Sisics 8 (): 85-9, ISSN 549-3644 Science Pblicions An Inegrl Two Spce-Vribles Condiion for Prbolic Eqions Mrhone, A.L. nd F. Lkhl Deprmen of Mhemics, Lborory Eqions Differenielles,

More information

Chapter 2: Evaluative Feedback

Chapter 2: Evaluative Feedback Chper 2: Evluive Feedbck Evluing cions vs. insrucing by giving correc cions Pure evluive feedbck depends olly on he cion ken. Pure insrucive feedbck depends no ll on he cion ken. Supervised lerning is

More information

PH2130 Mathematical Methods Lab 3. z x

PH2130 Mathematical Methods Lab 3. z x PH130 Mahemaical Mehods Lab 3 This scrip shold keep yo bsy for he ne wo weeks. Yo shold aim o creae a idy and well-srcred Mahemaica Noebook. Do inclde plenifl annoaions o show ha yo know wha yo are doing,

More information

UNIT # 01 (PART II) JEE-Physics KINEMATICS EXERCISE I. 2h g. 8. t 1 = (4 1)i ˆ (2 2) ˆj (3 3)kˆ 1. ˆv = 2 2h g. t 2 = 2 3h g

UNIT # 01 (PART II) JEE-Physics KINEMATICS EXERCISE I. 2h g. 8. t 1 = (4 1)i ˆ (2 2) ˆj (3 3)kˆ 1. ˆv = 2 2h g. t 2 = 2 3h g J-Physics UNI # (PR II) KINMICS XRCIS I ( )i ˆ ( ) ˆj ( )kˆ i. ˆ ˆ ˆ j i ˆ ˆ j ˆ 6i ˆ 8ˆj 8. h h h C h h.. elociy m/s h D. ˆ i i cos6ˆi sin 6ˆj f ˆ i ˆj i ˆ ˆj i ˆ ˆj i ˆ ˆj f i ˆj ˆj m/s. For,, nd d d

More information

M r. d 2. R t a M. Structural Mechanics Section. Exam CT5141 Theory of Elasticity Friday 31 October 2003, 9:00 12:00 hours. Problem 1 (3 points)

M r. d 2. R t a M. Structural Mechanics Section. Exam CT5141 Theory of Elasticity Friday 31 October 2003, 9:00 12:00 hours. Problem 1 (3 points) Delf Universiy of Technology Fculy of Civil Engineering nd Geosciences Srucurl echnics Secion Wrie your nme nd sudy numer he op righ-hnd of your work. Exm CT5 Theory of Elsiciy Fridy Ocoer 00, 9:00 :00

More information

PHY2048 Exam 1 Formula Sheet Vectors. Motion. v ave (3 dim) ( (1 dim) dt. ( (3 dim) Equations of Motion (Constant Acceleration)

PHY2048 Exam 1 Formula Sheet Vectors. Motion. v ave (3 dim) ( (1 dim) dt. ( (3 dim) Equations of Motion (Constant Acceleration) Insrucors: Field/Mche PHYSICS DEPATMENT PHY 48 Em Ferur, 5 Nme prin, ls firs: Signure: On m honor, I he neiher gien nor receied unuhoried id on his eminion. YOU TEST NUMBE IS THE 5-DIGIT NUMBE AT THE TOP

More information

Phys 110. Answers to even numbered problems on Midterm Map

Phys 110. Answers to even numbered problems on Midterm Map Phys Answers o een numbered problems on Miderm Mp. REASONING The word per indices rio, so.35 mm per dy mens.35 mm/d, which is o be epressed s re in f/cenury. These unis differ from he gien unis in boh

More information

4.2 Continuous-Time Systems and Processes Problem Definition Let the state variable representation of a linear system be

4.2 Continuous-Time Systems and Processes Problem Definition Let the state variable representation of a linear system be 4 COVARIANCE ROAGAION 41 Inrodcion Now ha we have compleed or review of linear sysems and random processes, we wan o eamine he performance of linear sysems ecied by random processes he sandard approach

More information

Solutions to Problems from Chapter 2

Solutions to Problems from Chapter 2 Soluions o Problems rom Chper Problem. The signls u() :5sgn(), u () :5sgn(), nd u h () :5sgn() re ploed respecively in Figures.,b,c. Noe h u h () :5sgn() :5; 8 including, bu u () :5sgn() is undeined..5

More information

HYPOTHESIS TESTING. four steps. 1. State the hypothesis and the criterion. 2. Compute the test statistic. 3. Compute the p-value. 4.

HYPOTHESIS TESTING. four steps. 1. State the hypothesis and the criterion. 2. Compute the test statistic. 3. Compute the p-value. 4. Inrodcion o Saisics in Psychology PSY Professor Greg Francis Lecre 24 Hypohesis esing for correlaions Is here a correlaion beween homework and exam grades? for seps. Sae he hypohesis and he crierion 2.

More information

NMR Spectroscopy: Principles and Applications. Nagarajan Murali Advanced Tools Lecture 4

NMR Spectroscopy: Principles and Applications. Nagarajan Murali Advanced Tools Lecture 4 NMR Specroscop: Principles nd Applicions Ngrjn Murli Advnced Tools Lecure 4 Advnced Tools Qunum Approch We know now h NMR is rnch of Specroscop nd he MNR specrum is n oucome of nucler spin inercion wih

More information

3. Renewal Limit Theorems

3. Renewal Limit Theorems Virul Lborories > 14. Renewl Processes > 1 2 3 3. Renewl Limi Theorems In he inroducion o renewl processes, we noed h he rrivl ime process nd he couning process re inverses, in sens The rrivl ime process

More information

MATH 124 AND 125 FINAL EXAM REVIEW PACKET (Revised spring 2008)

MATH 124 AND 125 FINAL EXAM REVIEW PACKET (Revised spring 2008) MATH 14 AND 15 FINAL EXAM REVIEW PACKET (Revised spring 8) The following quesions cn be used s review for Mh 14/ 15 These quesions re no cul smples of quesions h will pper on he finl em, bu hey will provide

More information

0 for t < 0 1 for t > 0

0 for t < 0 1 for t > 0 8.0 Sep nd del funcions Auhor: Jeremy Orloff The uni Sep Funcion We define he uni sep funcion by u() = 0 for < 0 for > 0 I is clled he uni sep funcion becuse i kes uni sep = 0. I is someimes clled he Heviside

More information

Version 001 test-1 swinney (57010) 1. is constant at m/s.

Version 001 test-1 swinney (57010) 1. is constant at m/s. Version 001 es-1 swinne (57010) 1 This prin-ou should hve 20 quesions. Muliple-choice quesions m coninue on he nex column or pge find ll choices before nswering. CubeUniVec1x76 001 10.0 poins Acubeis1.4fee

More information

Kinematics in two Dimensions

Kinematics in two Dimensions Lecure 5 Chaper 4 Phsics I Kinemaics in wo Dimensions Course websie: hp://facul.uml.edu/andri_danlo/teachin/phsicsi PHYS.141 Lecure 5 Danlo Deparmen of Phsics and Applied Phsics Toda we are oin o discuss:

More information

3D Transformations. Computer Graphics COMP 770 (236) Spring Instructor: Brandon Lloyd 1/26/07 1

3D Transformations. Computer Graphics COMP 770 (236) Spring Instructor: Brandon Lloyd 1/26/07 1 D Trnsformions Compuer Grphics COMP 770 (6) Spring 007 Insrucor: Brndon Lloyd /6/07 Geomery Geomeric eniies, such s poins in spce, exis wihou numers. Coordines re nming scheme. The sme poin cn e descried

More information

e t dt e t dt = lim e t dt T (1 e T ) = 1

e t dt e t dt = lim e t dt T (1 e T ) = 1 Improper Inegrls There re wo ypes of improper inegrls - hose wih infinie limis of inegrion, nd hose wih inegrnds h pproch some poin wihin he limis of inegrion. Firs we will consider inegrls wih infinie

More information

Method of Moment Area Equations

Method of Moment Area Equations Noe proided b JRR Page-1 Noe proided b JRR Page- Inrodcion ehod of omen rea qaions Perform deformaion analsis of flere-dominaed srcres eams Frames asic ssmpions (on.) No aial deformaion (aiall rigid members)

More information

Introduction to LoggerPro

Introduction to LoggerPro Inroducion o LoggerPro Sr/Sop collecion Define zero Se d collecion prmeers Auoscle D Browser Open file Sensor seup window To sr d collecion, click he green Collec buon on he ool br. There is dely of second

More information

Name: Per: L o s A l t o s H i g h S c h o o l. Physics Unit 1 Workbook. 1D Kinematics. Mr. Randall Room 705

Name: Per: L o s A l t o s H i g h S c h o o l. Physics Unit 1 Workbook. 1D Kinematics. Mr. Randall Room 705 Nme: Per: L o s A l o s H i g h S c h o o l Physics Uni 1 Workbook 1D Kinemics Mr. Rndll Room 705 Adm.Rndll@ml.ne www.laphysics.com Uni 1 - Objecies Te: Physics 6 h Ediion Cunel & Johnson The objecies

More information

1.0 Electrical Systems

1.0 Electrical Systems . Elecricl Sysems The ypes of dynmicl sysems we will e sudying cn e modeled in erms of lgeric equions, differenil equions, or inegrl equions. We will egin y looking fmilir mhemicl models of idel resisors,

More information

LECTURE 5. is defined by the position vectors r, 1. and. The displacement vector (from P 1 to P 2 ) is defined through r and 1.

LECTURE 5. is defined by the position vectors r, 1. and. The displacement vector (from P 1 to P 2 ) is defined through r and 1. LECTURE 5 ] DESCRIPTION OF PARTICLE MOTION IN SPACE -The displcemen, veloci nd cceleion in -D moion evel hei veco nue (diecion) houh he cuion h one mus p o hei sin. Thei full veco menin ppes when he picle

More information

Scalar Conservation Laws

Scalar Conservation Laws MATH-459 Nmerical Mehods for Conservaion Laws by Prof. Jan S. Heshaven Solion se : Scalar Conservaion Laws Eercise. The inegral form of he scalar conservaion law + f ) = is given in Eq. below. ˆ 2, 2 )

More information

Lecture 8 Backlash and Quantization. Material. Linear and Angular Backlash. Example: Parallel Kinematic Robot. Backlash.

Lecture 8 Backlash and Quantization. Material. Linear and Angular Backlash. Example: Parallel Kinematic Robot. Backlash. Lecre 8 Backlash and Qanizaion Maerial Toda s Goal: To know models and compensaion mehods for backlash Lecre slides Be able o analze he effec of qanizaion errors Noe: We are sing analsis mehods from previos

More information

Global alignment in linear space

Global alignment in linear space Globl linmen in liner spe 1 2 Globl linmen in liner spe Gol: Find n opiml linmen of A[1..n] nd B[1..m] in liner spe, i.e. O(n) Exisin lorihm: Globl linmen wih bkrkin O(nm) ime nd spe, bu he opiml os n

More information

HYPOTHESIS TESTING. four steps. 1. State the hypothesis. 2. Set the criterion for rejecting. 3. Compute the test statistics. 4. Interpret the results.

HYPOTHESIS TESTING. four steps. 1. State the hypothesis. 2. Set the criterion for rejecting. 3. Compute the test statistics. 4. Interpret the results. Inrodcion o Saisics in Psychology PSY Professor Greg Francis Lecre 23 Hypohesis esing for correlaions Is here a correlaion beween homework and exam grades? for seps. Sae he hypohesis. 2. Se he crierion

More information

Probability, Estimators, and Stationarity

Probability, Estimators, and Stationarity Chper Probbiliy, Esimors, nd Sionriy Consider signl genered by dynmicl process, R, R. Considering s funcion of ime, we re opering in he ime domin. A fundmenl wy o chrcerize he dynmics using he ime domin

More information

T-Match: Matching Techniques For Driving Yagi-Uda Antennas: T-Match. 2a s. Z in. (Sections 9.5 & 9.7 of Balanis)

T-Match: Matching Techniques For Driving Yagi-Uda Antennas: T-Match. 2a s. Z in. (Sections 9.5 & 9.7 of Balanis) 3/0/018 _mch.doc Pge 1 of 6 T-Mch: Mching Techniques For Driving Ygi-Ud Anenns: T-Mch (Secions 9.5 & 9.7 of Blnis) l s l / l / in The T-Mch is shun-mching echnique h cn be used o feed he driven elemen

More information

DESIGN OF TENSION MEMBERS

DESIGN OF TENSION MEMBERS CHAPTER Srcral Seel Design LRFD Mehod DESIGN OF TENSION MEMBERS Third Ediion A. J. Clark School of Engineering Deparmen of Civil and Environmenal Engineering Par II Srcral Seel Design and Analysis 4 FALL

More information

Atmospheric Dynamics 11:670:324. Class Time: Tuesdays and Fridays 9:15-10:35

Atmospheric Dynamics 11:670:324. Class Time: Tuesdays and Fridays 9:15-10:35 Amospheric Dnamics 11:67:324 Class ime: esdas and Fridas 9:15-1:35 Insrcors: Dr. Anhon J. Broccoli (ENR 229 broccoli@ensci.rgers.ed 848-932-5749 Dr. Benjamin Linner (ENR 25 linner@ensci.rgers.ed 848-932-5731

More information

Chapter 2. Motion along a straight line. 9/9/2015 Physics 218

Chapter 2. Motion along a straight line. 9/9/2015 Physics 218 Chper Moion long srigh line 9/9/05 Physics 8 Gols for Chper How o describe srigh line moion in erms of displcemen nd erge elociy. The mening of insnneous elociy nd speed. Aerge elociy/insnneous elociy

More information

Physics 201, Lecture 5

Physics 201, Lecture 5 Phsics 1 Lecue 5 Tod s Topics n Moion in D (Chp 4.1-4.3): n D Kinemicl Quniies (sec. 4.1) n D Kinemics wih Consn Acceleion (sec. 4.) n D Pojecile (Sec 4.3) n Epeced fom Peiew: n Displcemen eloci cceleion

More information

CHAPTER 11 PARAMETRIC EQUATIONS AND POLAR COORDINATES

CHAPTER 11 PARAMETRIC EQUATIONS AND POLAR COORDINATES CHAPTER PARAMETRIC EQUATIONS AND POLAR COORDINATES. PARAMETRIZATIONS OF PLANE CURVES., 9, _ _ Ê.,, Ê or, Ÿ. 5, 7, _ _.,, Ÿ Ÿ Ê Ê 5 Ê ( 5) Ê ˆ Ê 6 Ê ( 5) 7 Ê Ê, Ÿ Ÿ $ 5. cos, sin, Ÿ Ÿ 6. cos ( ), sin (

More information

Three Dimensional Coordinate Geometry

Three Dimensional Coordinate Geometry HKCWCC dvned evel Pure Mhs. / -D Co-Geomer Three Dimensionl Coordine Geomer. Coordine of Poin in Spe Z XOX, YOY nd ZOZ re he oordine-es. P,, is poin on he oordine plne nd is lled ordered riple. P,, X Y

More information

Some basic notation and terminology. Deterministic Finite Automata. COMP218: Decision, Computation and Language Note 1

Some basic notation and terminology. Deterministic Finite Automata. COMP218: Decision, Computation and Language Note 1 COMP28: Decision, Compuion nd Lnguge Noe These noes re inended minly s supplemen o he lecures nd exooks; hey will e useful for reminders ou noion nd erminology. Some sic noion nd erminology An lphe is

More information

Magnetostatics Bar Magnet. Magnetostatics Oersted s Experiment

Magnetostatics Bar Magnet. Magnetostatics Oersted s Experiment Mgneosics Br Mgne As fr bck s 4500 yers go, he Chinese discovered h cerin ypes of iron ore could rc ech oher nd cerin mels. Iron filings "mp" of br mgne s field Crefully suspended slivers of his mel were

More information

Available online at Pelagia Research Library. Advances in Applied Science Research, 2011, 2 (3):

Available online at   Pelagia Research Library. Advances in Applied Science Research, 2011, 2 (3): Avilble online www.pelgireserchlibrry.com Pelgi Reserch Librry Advnces in Applied Science Reserch 0 (): 5-65 ISSN: 0976-860 CODEN (USA): AASRFC A Mhemicl Model of For Species Syn-Ecosymbiosis Comprising

More information

I = I = I for this case of symmetry about the x axis, we find from

I = I = I for this case of symmetry about the x axis, we find from 8-5. THE MOTON OF A TOP n his secion, we shll consider he moion of n xilly symmeric body, sch s op, which hs fixed poin on is xis of symmery nd is ced pon by niform force field. The op ws chosen becse

More information

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle

Physics 235 Chapter 2. Chapter 2 Newtonian Mechanics Single Particle Chaper 2 Newonian Mechanics Single Paricle In his Chaper we will review wha Newon s laws of mechanics ell us abou he moion of a single paricle. Newon s laws are only valid in suiable reference frames,

More information

t s (half of the total time in the air) d?

t s (half of the total time in the air) d? .. In Cl or Homework Eercie. An Olmpic long jumper i cpble of jumping 8.0 m. Auming hi horizonl peed i 9.0 m/ he lee he ground, how long w he in he ir nd how high did he go? horizonl? 8.0m 9.0 m / 8.0

More information

Chapter 12: Velocity, acceleration, and forces

Chapter 12: Velocity, acceleration, and forces To Feel a Force Chaper Spring, Chaper : A. Saes of moion For moion on or near he surface of he earh, i is naural o measure moion wih respec o objecs fixed o he earh. The 4 hr. roaion of he earh has a measurable

More information

graph of unit step function t

graph of unit step function t .5 Piecewie coninuou forcing funcion...e.g. urning he forcing on nd off. The following Lplce rnform meril i ueful in yem where we urn forcing funcion on nd off, nd when we hve righ hnd ide "forcing funcion"

More information

The solution is often represented as a vector: 2xI + 4X2 + 2X3 + 4X4 + 2X5 = 4 2xI + 4X2 + 3X3 + 3X4 + 3X5 = 4. 3xI + 6X2 + 6X3 + 3X4 + 6X5 = 6.

The solution is often represented as a vector: 2xI + 4X2 + 2X3 + 4X4 + 2X5 = 4 2xI + 4X2 + 3X3 + 3X4 + 3X5 = 4. 3xI + 6X2 + 6X3 + 3X4 + 6X5 = 6. [~ o o :- o o ill] i 1. Mrices, Vecors, nd Guss-Jordn Eliminion 1 x y = = - z= The soluion is ofen represened s vecor: n his exmple, he process of eliminion works very smoohly. We cn elimine ll enries

More information

Lecture 3: 1-D Kinematics. This Week s Announcements: Class Webpage: visit regularly

Lecture 3: 1-D Kinematics. This Week s Announcements: Class Webpage:   visit regularly Lecure 3: 1-D Kinemics This Week s Announcemens: Clss Webpge: hp://kesrel.nm.edu/~dmeier/phys121/phys121.hml isi regulrly Our TA is Lorrine Bowmn Week 2 Reding: Chper 2 - Gincoli Week 2 Assignmens: Due:

More information

ME 321: FLUID MECHANICS-I

ME 321: FLUID MECHANICS-I 8/7/18 ME 31: FLUID MECHANICS-I Dr. A.B.M. Toiqe Hasan Proessor Dearmen o Mechanical Engineering Bangladesh Uniersi o Engineering & Technolog BUET, Dhaka Lecre-13 8/7/18 Dierenial Analsis o Flid Moion

More information

Brock University Physics 1P21/1P91 Fall 2013 Dr. D Agostino. Solutions for Tutorial 3: Chapter 2, Motion in One Dimension

Brock University Physics 1P21/1P91 Fall 2013 Dr. D Agostino. Solutions for Tutorial 3: Chapter 2, Motion in One Dimension Brock Uniersiy Physics 1P21/1P91 Fall 2013 Dr. D Agosino Soluions for Tuorial 3: Chaper 2, Moion in One Dimension The goals of his uorial are: undersand posiion-ime graphs, elociy-ime graphs, and heir

More information

ECE Microwave Engineering. Fall Prof. David R. Jackson Dept. of ECE. Notes 10. Waveguides Part 7: Transverse Equivalent Network (TEN)

ECE Microwave Engineering. Fall Prof. David R. Jackson Dept. of ECE. Notes 10. Waveguides Part 7: Transverse Equivalent Network (TEN) EE 537-635 Microwve Engineering Fll 7 Prof. Dvid R. Jcson Dep. of EE Noes Wveguides Pr 7: Trnsverse Equivlen Newor (N) Wveguide Trnsmission Line Model Our gol is o come up wih rnsmission line model for

More information

22.615, MHD Theory of Fusion Systems Prof. Freidberg Lecture 9: The High Beta Tokamak

22.615, MHD Theory of Fusion Systems Prof. Freidberg Lecture 9: The High Beta Tokamak .65, MHD Theory of Fusion Sysems Prof. Freidberg Lecure 9: The High e Tokmk Summry of he Properies of n Ohmic Tokmk. Advnges:. good euilibrium (smll shif) b. good sbiliy ( ) c. good confinemen ( τ nr )

More information

5.1-The Initial-Value Problems For Ordinary Differential Equations

5.1-The Initial-Value Problems For Ordinary Differential Equations 5.-The Iniil-Vlue Problems For Ordinry Differenil Equions Consider solving iniil-vlue problems for ordinry differenil equions: (*) y f, y, b, y. If we know he generl soluion y of he ordinry differenil

More information

Introduction to Bayesian Estimation. McGill COMP 765 Sept 12 th, 2017

Introduction to Bayesian Estimation. McGill COMP 765 Sept 12 th, 2017 Inrodcion o Baesian Esimaion McGill COM 765 Sep 2 h 207 Where am I? or firs core problem Las class: We can model a robo s moions and he world as spaial qaniies These are no perfec and herefore i is p o

More information

What distance must an airliner travel down a runway before reaching

What distance must an airliner travel down a runway before reaching 2 LEARNING GALS By sudying his chper, you will lern: How o describe srigh-line moion in erms of erge elociy, insnneous elociy, erge ccelerion, nd insnneous ccelerion. How o inerpre grphs of posiion ersus

More information

Miscellanea Miscellanea

Miscellanea Miscellanea Miscellanea Miscellanea Miscellanea Miscellanea Miscellanea CENRAL EUROPEAN REVIEW OF ECONOMICS & FINANCE Vol., No. (4) pp. -6 bigniew Śleszński USING BORDERED MARICES FOR DURBIN WASON D SAISIC EVALUAION

More information

Numerical Dispersion

Numerical Dispersion eview of Linear Numerical Sabiliy Numerical Dispersion n he previous lecure, we considered he linear numerical sabiliy of boh advecion and diffusion erms when approimaed wih several spaial and emporal

More information

Mathematical Modeling

Mathematical Modeling ME pplie Engineering nlsis Chper Mhemicl Moeling Professor Ti-Rn Hsu, Ph.D. Deprmen of Mechnicl n erospce Engineering Sn Jose Se Universi Sn Jose, Cliforni, US Jnur Chper Lerning Ojecives Mhemicl moeling

More information

LAB # 2 - Equilibrium (static)

LAB # 2 - Equilibrium (static) AB # - Equilibrium (saic) Inroducion Isaac Newon's conribuion o physics was o recognize ha despie he seeming compleiy of he Unierse, he moion of is pars is guided by surprisingly simple aws. Newon's inspiraion

More information

Mat 267 Engineering Calculus III Updated on 04/30/ x 4y 4z 8x 16y / 4 0. x y z x y. 4x 4y 4z 24x 16y 8z.

Mat 267 Engineering Calculus III Updated on 04/30/ x 4y 4z 8x 16y / 4 0. x y z x y. 4x 4y 4z 24x 16y 8z. Ma 67 Engineering Calcls III Updaed on 04/0/0 r. Firoz Tes solion:. a) Find he cener and radis of he sphere 4 4 4z 8 6 0 z ( ) ( ) z / 4 The cener is a (, -, 0), and radis b) Find he cener and radis of

More information

A LOG IS AN EXPONENT.

A LOG IS AN EXPONENT. Ojeives: n nlze nd inerpre he ehvior of rihmi funions, inluding end ehvior nd smpoes. n solve rihmi equions nlill nd grphill. n grph rihmi funions. n deermine he domin nd rnge of rihmi funions. n deermine

More information

An integral having either an infinite limit of integration or an unbounded integrand is called improper. Here are two examples.

An integral having either an infinite limit of integration or an unbounded integrand is called improper. Here are two examples. Improper Inegrls To his poin we hve only considered inegrls f(x) wih he is of inegrion nd b finie nd he inegrnd f(x) bounded (nd in fc coninuous excep possibly for finiely mny jump disconinuiies) An inegrl

More information

Let us start with a two dimensional case. We consider a vector ( x,

Let us start with a two dimensional case. We consider a vector ( x, Roaion marices We consider now roaion marices in wo and hree dimensions. We sar wih wo dimensions since wo dimensions are easier han hree o undersand, and one dimension is a lile oo simple. However, our

More information

P441 Analytical Mechanics - I. Coupled Oscillators. c Alex R. Dzierba

P441 Analytical Mechanics - I. Coupled Oscillators. c Alex R. Dzierba Lecure 3 Mondy - Deceber 5, 005 Wrien or ls upded: Deceber 3, 005 P44 Anlyicl Mechnics - I oupled Oscillors c Alex R. Dzierb oupled oscillors - rix echnique In Figure we show n exple of wo coupled oscillors,

More information

Observability of flow dependent structure functions and their use in data assimilation

Observability of flow dependent structure functions and their use in data assimilation Oserviliy of flow dependen srucure funcions nd heir use in d ssimilion Pierre Guhier nd Crisin Lupu Collorion wih Séphne Lroche, Mrk Buehner nd Ahmed Mhidji (Env. Cnd) 3rd meeing of he HORPEX DAOS-WG Monrél

More information

Honours Introductory Maths Course 2011 Integration, Differential and Difference Equations

Honours Introductory Maths Course 2011 Integration, Differential and Difference Equations Honours Inroducory Mhs Course 0 Inegrion, Differenil nd Difference Equions Reding: Ching Chper 4 Noe: These noes do no fully cover he meril in Ching, u re men o supplemen your reding in Ching. Thus fr

More information

FM Applications of Integration 1.Centroid of Area

FM Applications of Integration 1.Centroid of Area FM Applicions of Inegrion.Cenroid of Are The cenroid of ody is is geomeric cenre. For n ojec mde of uniform meril, he cenroid coincides wih he poin which he ody cn e suppored in perfecly lnced se ie, is

More information

CORRELATION. two variables may be related. SAT scores, GPA hours in therapy, self-esteem grade on homeworks, grade on exams

CORRELATION. two variables may be related. SAT scores, GPA hours in therapy, self-esteem grade on homeworks, grade on exams Inrodcion o Saisics in sychology SY 1 rofessor Greg Francis Lecre 1 correlaion Did I damage my dagher s eyes? CORRELATION wo ariables may be relaed SAT scores, GA hors in herapy, self-eseem grade on homeworks,

More information

Chapter 2 PROBLEM SOLUTIONS

Chapter 2 PROBLEM SOLUTIONS Chper PROBLEM SOLUTIONS. We ssume h you re pproximely m ll nd h he nere impulse rels uniform speed. The elpsed ime is hen Δ x m Δ = m s s. s.3 Disnces reled beween pirs of ciies re ( ) Δx = Δ = 8. km h.5

More information

( ) ( ) ( ) ( ) ( ) ( y )

( ) ( ) ( ) ( ) ( ) ( y ) 8. Lengh of Plne Curve The mos fmous heorem in ll of mhemics is he Pyhgoren Theorem. I s formulion s he disnce formul is used o find he lenghs of line segmens in he coordine plne. In his secion you ll

More information

Integration of the equation of motion with respect to time rather than displacement leads to the equations of impulse and momentum.

Integration of the equation of motion with respect to time rather than displacement leads to the equations of impulse and momentum. Inegraion of he equaion of moion wih respec o ime raher han displacemen leads o he equaions of impulse and momenum. These equaions greal faciliae he soluion of man problems in which he applied forces ac

More information