Mechanics and strength of materials

Size: px
Start display at page:

Download "Mechanics and strength of materials"

Transcription

1 Lecue pogam D ż. Po Szulc Wocław Uves of Techlog Facul of Mechacal ad Powe Egeeg 00 Mechacs ad segh of maeals. Kemacs of a po.. Moo of a gd bod 3. Damcs of fee ad cosaed moo of a po 4. Damcs of a gd bod 5. Cosevao laws. 6. Wok, powe ad kec eeg 7. Mass geome ad mpac heo 8. Teso ad compesso. Hooke s law. 9. Bedg. 0. Bedg le of beam.. Shea, oso ad bucklg.. Hpohess of exeo. Combed sess. 3. Eeg mehods Leaue Ioduco. TYLOR J., Classcal mechacs, Uves Scece Books, 005. SCHECK F., Mechacs- Fom Newo s Laws o Deemsc Chaos, Spge, SINGH U.K., DWIVEDI M., Poblems ad soluos mechacal egeeg, New ge Ieaoal, Mo R., ppledseghofmaeals, UppeSaddleRve, Peaso/PeceHall, SIUT W., Mechaka Techcza, Wdawcwa Szkole Pedagogcze, Waszawa MISIK J., Mechaka Ogóla, WNT, Waszawa ŻUCHOWSKI R., Wzmałośćmaeałów, Ofca Wdawcza PW., Wocław 998. KINEMTICS seco descbg he mechacs of moo of a po o block, whou akg o accou he wegh ad causes of chage moo - The geome of moo MOTION descbed as chagg bod poso elave o he efeece bod whch emas a es

2 Tack ofa po Ths s a sold le lfomed b he subseque locao of a movg po. Po pah ma be a sagh le o a cuve Kemac equaos of moo of a maeal po Recagula coodaes x f (), f (), z f 3 () z Radus veco () x z O z x x(), (), z z() x x Veloc of a po cceleao of a po v v + B v v v v O veage veloc v s Isaaeous veloc d v lm & 0 Medum v cceleao - v v a s - Isaaeous cceleao v dv a lm v & && 0

3 The equaos of ufom lea moo Equaos of lea moo vaable ufoml v v acceleao dv a cos s v veloc v vo + a veloc dsace ds v cos s so + v s g α g αv dsace a s so + vo + a > 0 ufoml acceleaed moo a < 0 ufoml eaded moo Lea moo vaable ufoml dv a cos v vo + a a s so + vo + Cuvlea moo a a s a v Tageal acceleao a a dv v& Nomal cceleao v ρ a a + a value a a +a

4 Ufom moo a ccle dsace s lea veloc agula veloc α ( ) ds d α v ω ω dα ω π 60 gula acceleao Tageal acceleao Nomal cceleao ε a dω ( ω) dv d dω as ε v ω ( ) ( ) a a + a ω + ε ω + ε 4 s Moo of a gd bod Moo of a gd bod z O B C C B B C B C Rgd bod dsaces bewee pos ae uchaged Moo of a gd bod ca be deemed b veco equaos of hee pos, B, C z O C B C B u() u() u() C B C () ( ) + u(), o () ( ) + u(), B B o () ( ) + u(), C C o x () () B B () C C x u() -Shf s equal fo all pos of he bod

5 Moo of a gd bod Dffeeag he above equaos of moo vecos wh espec o me we ge veloc ad acceleao of pos,b,c du() v vb vc d u() a ab ac Vecos of veloc ad acceleao of all pos of a gd bod, movg wh a advacg moo aehesamea he same me The oa moo of he sold aoud a fxed axs lump ca be oaed aoud he axs ol (passg hough wo pos), called he axs of oao ϕ ϕ() ω ϕ& ε ω & ϕ&& v ω v ω cceleao oao Newo's Secod Rule cceleao of ageal ad omal acceleao of a po of a gd bod lg a a dsace fom he axs of oao wh espec o me we ge b dffeeag he fomula fo lea veloc eldg: dω a v& ε a v ω ω a a + a ε + ω 4 The chage of moo s popooal o he appled foce ad akes place he deco of he sagh le alog whch ha foce acs m cos d F (mv) dv m ma F

6 Iea a F ma Ca acceleaes wh he acceleao. We mus heefoe wok foce. ccodg o he pcple of aco ad eaco ou hads, wok he same foce fom he ca, bu eued o he coa. D ma Ths s he foce of ea (D'lembe) D F The damcs of fee ad cosaed moo of a po. D'lembe's Pcple I he case of fee moo of a po ssem of acve foces balaces he foce of ea F + ( ma) 0 I he case of moo cosaed po foce espose of acvead balaced es wh he foce of ea F + R + ( ma) 0 The momeum of he maeal po We henewo's secod law he fom of: d (mv) dp The veco s called he momeum o qua of moo of a po. mv p F The pcple of cosevao of momeum of a po I he eve ha a maeal po does o wok foce o foces balace, he momeum of he maeal po s cosa. d dp (mv) p cos. 0

7 The pcple of mass momeum ad mpulse foces The Newo s secod law: F d(mv) F o dπ Elemea mpulse foce acg o a maeal po s equal o he ga momeum of he elemea po. Π The pcple of mass momeum ad mpulse foces Iegag boh sdes of pevous equao, we oba F d m v m v ( ) F -mpulse s he oal foce F he me eval -, We oba v Π p p The gowh momeum of a movg mass po s equal o he oal mpulse foces gula momeum of maeal po Ko mv Thsshemome of momeumb he chose pole K& o Mo o o M 0 K cos Damc equaos of moo of a maeal po Damc equao of moo veco fom ca be eplaced b hee aalcal equaos: Fx F ma mx &&, F m &&, Fz mz &&. The fs ask (smple) -hese ae he paamec equaos of he ack, whch moves he maeal po, fd he foce acg o po. The secod ask (evese) - o deeme he equao of moo, wh a pacula segh

8 Relave mooof a maeal po Moo elave o he fxed po s defed b he equao m ab ad I whch Du mau called he lfg foce of ea. I s equal o mass mulpled b acceleao of floag po ad s oppose ha a u F a a + a b w u I a movg ssem he equao of moo s deemed ma F ma w u Wok ofa cosa foce Pemae wok ofa foce o a sagh moveme he deco of foce s called he poduc of hs foce b he legh of shfs Fs The u of wok he SI ssem sj (dżul): kgm J Nm m s Wok ofa cosa foce F If he veco of foce s cled o he deco ems of a shf, he wok s calculaed fom he fomula: Fs Fs cos α The wok makes ol a ageal foce compoe o he ajeco of F. Jobs omal compoe o he ajeco of F s equal o zeo F F Wok ofa cosa foce α 0 Fs > 0 0 < α < 90 Fs cos α > 0 α < α < 80 Fs cos α < 0 α 80 Fs < 0 I geeal: a)wok s a scala, b)wok ma ake posve oegavevalues ad zeo, c)wok s doe ol b compoe of foce ageal o he pah.

9 Wokofa vaable foce The elemea wok of he vaable foce o a shf he do poduc of foce F b a elemea shf δ F ds because F ds Fds cos F, ds Fds so δ F ds ( ) ds s called Wokofa foceo a shf s equal o he oal wok foces he especve cosue compoes of dsplacemes Wokofa vaable foce Toal wok of he poso o poso o he ack ae obaed b egag he expesso of a elemea wok. F X + jy + kz s δ s ds dx + jd + kdz x z Xdx + Yd + Zdz x z Wok o ccula pah Whe he foce F acg o a po movg alog a ccula pah (bel eso bel dve), we oba Wok o ccula pah Expesso F deemes he mome of foce F elave measue O (eg, cee of he dsc). We call oque ds F d F O δ F ds Fds ds dϕ δ F dϕ M o F The fomula fo he elemea wok akes he fom: δ M dϕ o

10 Wok o ccula pah ϕ Toal wok o he oad o ϕ deeme he agula egal ϕ o ϕ M dϕ Powe I pacce, we ae ofe eesed he volume of wok he moo o he mache ca pefom pe u me. The wok s elaed ohe u of me s called powe. I pacula, he saaeous powe of he emplome elaoshp s called he elemea o he me a whch hs wok was pefomed δ P expesso fo he saaeous powe s peseed he followg fom: Fds P o P F v Powe oao Powe P Powe Modϕ Powe oao P M o ω gula veloc dϕ ω Whe he oao velocsepo s usg he ege speed, pm -he he agula veloc s calculaed fom he fomula: ω π 60 Powe π P Mo 30 The fudameal u of powe s W J/s Nm/s Ths echcal us : kw MW

11 Effcec Pcple ofwok ad kec eeg Effcecs he ao of eceved wok(powe)o opeae he pu wok(powe) dv F ma m δ F ds Mechacal effcec ao deemed b: u η P P u 0 0 The effcec s a dmesoless umbe ad ca be egaded as a chaacesc measue of compaso eges ad maches, as fa as he ecoomcal wa o wok ulzao s o loaded dv δ m ds mvdv The gh sde of hs equao s a fuco of he oal dffeeal called he kec eeg of a movg maeal po. E k mv ds v Pcple ofwok ad kec eeg Based o he above depedece we oba δ de Ths equao shows he pcple of wok ad kec eeg, expessed he fom of dffeeal equao. fe egao we oba E E The kec eeg of a movg maeal po ceases o deceases he volume of wok doe b foces acg o he maeal po. Fuco of feld foces Toal dffeeal feld fuco s equal: Φ Φ Φ dφ dx + d + dz x z So he dffeeal was equal o he elemea wok X δ Xdx + Yd + Zdz mus be me depedg o Φ Y x Φ Z Φ z

12 Poeal of feld foces Veco offeldfoce ca be we he fom Φ Φ Φ F + j + k x z The gh sde s he gade of he fuco, Φ so F gad Φ ma Pogessve moo of a gd bod c F whee: m mass of a gd bod a C - acceleao of cee of mass mx && c Fx x m && z O c F c F C F C zc a C xc mz && F F c Fz The heoem o he devave of agula momeum The devave of agula momeum of he bod elave o s cee of mass s equal o he geomec momes of all foces exeal o hs measue d Kc M c Pogessve moo of a gd bod The pogessve moo of all pos of a gd bod have he same veloc, such as he cee of mass of he bod. Thus, gula momeum of a gd bod elave o he cee of mass s equal o zeo K 0 The equao shows ha whe he bod moves wh a advacg moo s he sum of he geomec momes of exeal foces o he cee ofbod mass mus be zeo M c 0 The exeal foces mus ceae a laou ha hashe esul W of a le of aco passg hough he cee of mass C. c

13 Plae moo of gd bod Show he dawg seco of he bod obaed b eseco of he plae paallel o he plae of he decg ad passg hough he cee of mass C xc F F C c F F x Damc equaos of moo of a gd bod To oba he damc equaos of moo of a gd bod we use a fla: damc equaos of Pogessvemoo he pcple of agula momeum a oag moo I z ε M z O x Damc equaos of moo of a gd bod The equao of pogessvemoo he x deco The equao of pogessvemoo he deco The pcple of cosevao of agula momeum a oag moo && x,&& hadwae acceleao of he cee of mass C c Iz ε c mx && z c m && c I ε mome of ea wh espec o he axs z of he bod agula acceleao of he axs z of oao of he bod F F M x z Mome of ea Mome of ea of a maeal po elave o he plae, a axs o polespoduc of he mass b he squae of he dsace of hs po fom he plae, a axs o pole: I m U s [ I ] kg m

14 Mome of ea of maeal pos ssem Mome of eaofmaealposssemhe plae, a axs o polescallehe sum of he momes of ea of all he maeal pos of hs plae, axs o pole. Mome of ea of he cosa Mome of ea of he cosa (les, sufaces o sold maeal) of vew of he plae, called he axs o pole of he egal I dm I m seched o he whole mass of he ssem Mome of ea of he plae Momes of ea wh espec o he coodae plaes defe he fomulas: I I I x z zx m z, mx, m I Mome of ea axs ad pole I I I x ( ) ( ) ( ) m + z, m x + z, m x + z Mome of ea axs Mome of ea pole ( ) m x + + z o

15 Mome of devao Mome of devao The mome of devao of a po muuall pepedcula plaes, called he poduc of he mass b he dsace fom he po of plaes D m ρ αβ Momes of devao ca be posve, egave ad, pacula, equal o zeo Mome ofdevaoof maeal pos elave o he wo muuall pepedcula plaes, s he sum of he momes of devao of dvdual pos of he maeal ems of hese plaes. D D αβ Fo he cosa αβ m ρ ρ dm exeded o he whole mass. m m Mome of devao The spaal coodaes of he ssem of maeal pos s hee momes of devao D D D m x, x m z x, zx m z z I fla coodaes he maeal ssem has oe mome of devao Paallel asfomao of he momes of ea Mome of ea wh espec o a axs s equal o he momeum paallel o he axs passg hough he cee of gav plus he poduc of he oal wegh b he squae of he dsace of he wo axes. I l I + md c D D m x x

16 Ceal smple collso Ceal smple collso v v w w mv + mv mw + mw he same me w adw showshe velocof boh masses afehe collso. The appome also use he equao esulg fom eeg cosdeaos. Veloc w ad w wll deped o whehe he loss of kec eeg a) eeg eued 00% (pefecl elasc collso of bodes) b) eeg absobed a 00% (pefecl plasc bod collso), c) eeg absobed pa (he acual collso of bodes.) Fo he deemao of hese losses wll oduce he so-called eeg. collso ae, callg hm a model k w w 0 k v v The lm values coespod o he ao k k k 0 fo he bod pefecl elasc fo pefecl plasc bod Ceal smple collso Dagoal ceal collso The acual loss of kec eeg s E mv mv mw mw + Spead he veloc vecos v ad v o compoes omal ad ageal o he plae of coac v v v cos α v s α v v v cos α v s α v w v w ad fe subsuo of equaos fo w ad w eceve m m E v v k m + m ( ) ( ) v v v v v v Fall, afe collso w w w w + w + w w w + v, + v

17 Sess Le's cosde he foce F pe eleme of aea Sess pa a po whee s called a sold bouda, whch seeks he ao of eal foce F b elemea feld of hs seco, whee he feld eds o zeo. F df N p lm, d m 0 T F N Tageal ad omal sess fe speadg he foce Fo he omal compoe N ad ageal T wll eceve he omal ad ageal τ sesses: N dn N lm, d m 0 τ T dt N lm, d m 0 Lea Defomao Smple sechg SegmeB l -chaged afe loadg: B l+ l. The aveage elogao of he segme B wll be : ε s l l Local exeso: ε lm l 0 l l Smple sechg occus whe he esul of educo of he eal foces fom he cee of he coss seco of he bodwll eceve ol he pcpal veco, omal o hs seco N N axal foce, coss-secoal aea of ba omal sess

18 Smple sechg The codo of balace -he sum of he pojecos of all foces he deco of he axs of he od Fx d N 0 () N d () Whe he sesses ae he same fo he ee coss-seco: Ths meas ha he ma veco s equal o he segh of he aggavag ad he absece of ohe sesses o he coss-secoal aea. N Smple sechg Effo of he maeal degee of appoxmao of he load maeal o a ccal sae The codo of he ba segh: llowable sess dop safe faco( ), eb Dageous Sess N dop eb dop Hoocke slaw Laeal defomao F ε l l F l l E F Hooke s law akes he fom: ε E The dffeece of al ad fal hckess s called oal seoss, h h h. Rao of scue of he oal hckess of he al call o he aowg of he u ε ε h h

19 Posso sumbe Gaph dawg low cabo seel The absolue value of he ao of seoss (swellg) of he u ε o u ε elogao (shoeg), s called he coeffce of asvese sa ad Posso's umbe ν ε ν ε d sp p Rm Posso s umbe assumes values wh he 0 0,5 Gaph dawg low cabo seel Idvdual pos o he gaph meas: lm of popooal (he lm of applcabl of Hooke's law) B elasc lm - pacce s assumed ha le ea each ohe, pos ad B ae of equal value: p C, D - eld Re, - cleal vsble o he gaph dawg ad eas o se ol fo cea maeals, such as low cabo seel. R e Fe sp 0 Gaph dawg low cabo seel K -eld esle segh R m (Emegec segh of he maeal). Tesle segh R m s he ao of he maxmum esle segh F max obaed he pocess of dawg he sample hough he box seco of he al sample 0 : R m F fe eachg he sess o he sample ases R m local cosco (he eck). I place of he sample upues - segme KL sechg fom he cha. max 0

20 Dawg gaphs of dffee maeals low cabo seel, coppe cas alumum allos Beam subjeced o pue bedg Pue bedgca be obseved he case of bedg of a psmac beam loaded as show R R x F F R B The codo of bedg segh The sesses he bedgod ae he lages he fbes, hus M g max dop W Beams of equal segh The codo of cosa-segh beam bedg segh alog he ee legh has he fom: M g (x) W (x) dop s we appoach he fbe axs of he beam load deceases

21 Defleco of he beam le The equao fo beam defleco agle Iegag he pevous equao, we oba he depedece of he vaable x s used o desgae he agle of defleco j he fom: Dffeeal equao of defleco of he beam le d dx M g (x) E I ϕ d(x) M (x) ( ) dx E I + g x dx C The equao fo defleco of he beam le fe e-egao wh espec o he vaable x we oba: ϕ (x) dx + D Cosas of egao C ad D we deeme he bouda codos. We have wo pes of hese codos ad he esul fom: sffess of he suppos (bouda codos), cou of he beam (cou codos). Shea sess I coss-seco of a esle od, led a a agle s addo o omal sesses ae also shea sess o shea : τ α s α

22 Pue shea Techcal Shea Sae of sess hese secos, whch hee ae ol a shea sess s called he pue shea Sae of pue shea s dffcul o be pepaed b dec ode of he bod hemselves shea sess, wheeas such a effec ca be obaed b callg eg, esle ad compessve same, absolue value sess, acg wo muuall pepedcula decos whee: τ dop allowable shea sess, T sheafoce, codo of shea segh: τ T τ dop coss-seco subjeced o shea. Cases of he echcal shea Toque Elemea oque eso od axs s: ves weld dm τ dρ ρ

23 gle oso ba Toso agle oud ba of dmesos d, ladm s s he: Codo of he osoal segh Sess he scew od ca o exceed he allowable osoal sessk s ϕ M s G I l 0 M s τ max W0 k s Sesses he maeal Maeal effo dτ zx τ zx + dz dz τ x τ z d x x + dx dx τ x dτ xz τ xz + dx dx τ xz dτ x τ + dτ x x dx dx τ x + d d τ z d z z + dz dz dτ z τ z + dz dz x τ zx dτ z τ z + d d d + d d Maeal effo degee of appoxmao of he load maeal o he bouda codo. Hpoheses ofmaeal effo desgs fo he coveso of he load o he load-dmesoal spaal. z

24 Hpoheses effo Basc coceps Hpoheses effo depedg o he adoped measue of effo ca be dvded o: Sess Defomao Eeg Mxed The pupose of effo hpohess s o deeme he coelaobewee he compoes of he effo a sae of sess: ( x z x z zx ) W F,,, τ, τ, τ, C Ccal values of effo ca be deemed b cag ou he expeece fo oe specfc sae of sess 0, s bes fo he uaxal eso ( ) W F,0,0,0,0,0, C 0 The hpohess of he lages esle sess The auhos of hs hpohess ae Galleusz (63) ad Lebz(864) ccodg o hs hpohess, a measue of he effo s he lages esle sess Ths s he hpohess of sess ad s occasoall used facue mechacs The hpohess of he geaes elogao The auhos of hs hpohess ae E. Maoe, B. S Vea ad J.V. Pocele. The measue of effo accodg o hs hpohess s he geaes elogao. ε εk ε εk ε3 εk Fo ε k adoped elogao ε Z coespodg esle segh Rm

25 The hpohess of he geaes elogao Whe he plae sae of sess s expessed b meas of sa x,, τ x he ma sess s deemed b he fomula: + ± + τ ( ) ( ) 4, x x x ad he educed sess s deemed fom oe of he hee equaos ν k k ν ν ( + ) k Wh educed sess should be he lef sde of he equao, whch s hghe ha he lef sde of each of he ohe wo equaos The hpohess of he lages shea sess Is auhos aec.. Culomb, H. Tesca J.J. Gues. The measue of effo hs hpohess s he geaes ageal sess τ max max m I he case of a smple esle sess s educed equao has he fom: ed max m k ed 0 The hpohess of he lages shea sess Whee max ad m 3, ha: ed 3 k I he case of plae sae of sess, whe: x, 0, τ x τ, educed sess ca be deemed: ed + 4τ The hpohess of eal eeg shea (Hube s hpohess) s a measue of effo b hs hpohessshe specfc eeg shea, whch a sae of sess s spaall: φ + ν ( x ) + ( z ) + ( z x ) + 6( τ x + τ z + τzx ) 6E I he uaxal sae of sess esposble shea eeg wll be: + ν φ 6E 0

26 The hpohess of eal eeg shea (Hube s hpohess) Reduced sess : τ + τ + τ ( ) ( ) ( ) 6( ) ed x z z x x z zx Reduced sess he ssem of pcpal sesses ca be deemed fom he equao: + + ( ) ( ) ( ) ed 3 3 The hpohess of eal eeg shea (Hube s hpohess) Fo a plae sae of sess x,, x educed sess expessed he equao: ( ) ed x + 3τ If x, 0, τ x τ hs equaoof educed sess ake he followg fom: ed + 3τ Eeg mehods Casglao s Theoem geealzed coodaes f coespodg o he foce F s equal o he paal devave of elasc eeg V f δv δ F Meabe s Theoem paal devave of he elasc eegvof he ssem wh espec o sacall deemae eaco X s equal o zeo δv 0 δx

EMA5001 Lecture 3 Steady State & Nonsteady State Diffusion - Fick s 2 nd Law & Solutions

EMA5001 Lecture 3 Steady State & Nonsteady State Diffusion - Fick s 2 nd Law & Solutions EMA5 Lecue 3 Seady Sae & Noseady Sae ffuso - Fck s d Law & Soluos EMA 5 Physcal Popees of Maeals Zhe heg (6) 3 Noseady Sae ff Fck s d Law Seady-Sae ffuso Seady Sae Seady Sae = Equlbum? No! Smlay: Sae fuco

More information

Lagrangian & Hamiltonian Mechanics:

Lagrangian & Hamiltonian Mechanics: XII AGRANGIAN & HAMITONIAN DYNAMICS Iouco Hamlo aaoal Pcple Geealze Cooaes Geealze Foces agaga s Euao Geealze Momea Foces of Cosa, agage Mulples Hamloa Fucos, Cosevao aws Hamloa Dyamcs: Hamlo s Euaos agaga

More information

EGN 3321 Final Exam Review Spring 2017

EGN 3321 Final Exam Review Spring 2017 EN 33 l Em Reew Spg 7 *T fshg ech poblem 5 mues o less o pcce es-lke me coss. The opcs o he pcce em e wh feel he bee sessed clss, bu hee m be poblems o he es o lke oes hs pcce es. Use ohe esouces lke he

More information

Suppose we have observed values t 1, t 2, t n of a random variable T.

Suppose we have observed values t 1, t 2, t n of a random variable T. Sppose we have obseved vales, 2, of a adom vaable T. The dsbo of T s ow o belog o a cea ype (e.g., expoeal, omal, ec.) b he veco θ ( θ, θ2, θp ) of ow paamees assocaed wh s ow (whee p s he mbe of ow paamees).

More information

For the plane motion of a rigid body, an additional equation is needed to specify the state of rotation of the body.

For the plane motion of a rigid body, an additional equation is needed to specify the state of rotation of the body. The kecs of rgd bodes reas he relaoshps bewee he exeral forces acg o a body ad he correspodg raslaoal ad roaoal moos of he body. he kecs of he parcle, we foud ha wo force equaos of moo were requred o defe

More information

ANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER 2

ANSWERS TO ODD NUMBERED EXERCISES IN CHAPTER 2 Joh Rley Novembe ANSWERS O ODD NUMBERED EXERCISES IN CHAPER Seo Eese -: asvy (a) Se y ad y z follows fom asvy ha z Ehe z o z We suppose he lae ad seek a oado he z Se y follows by asvy ha z y Bu hs oads

More information

( ) ( ) Weibull Distribution: k ti. u u. Suppose t 1, t 2, t n are times to failure of a group of n mechanisms. The likelihood function is

( ) ( ) Weibull Distribution: k ti. u u. Suppose t 1, t 2, t n are times to failure of a group of n mechanisms. The likelihood function is Webll Dsbo: Des Bce Dep of Mechacal & Idsal Egeeg The Uvesy of Iowa pdf: f () exp Sppose, 2, ae mes o fale of a gop of mechasms. The lelhood fco s L ( ;, ) exp exp MLE: Webll 3//2002 page MLE: Webll 3//2002

More information

SIMULATIUON OF SEISMIC ACTION FOR TBILISI CITY WITH LOCAL SEISMOLOGICAL PARTICULARITIES AND SITE EFFECTS

SIMULATIUON OF SEISMIC ACTION FOR TBILISI CITY WITH LOCAL SEISMOLOGICAL PARTICULARITIES AND SITE EFFECTS SIMULTIUON OF SEISMIC CTION FOR TBILISI CITY WITH LOCL SEISMOLOGICL PRTICULRITIES ND SITE EFFECTS Paaa REKVV ad Keeva MDIVNI Geoga Naoal ssocao fo Egeeg Sesmology ad Eahquake Egeeg Tbls Geoga ekvavapaaa@yahoo.com

More information

Lecture 3 summary. C4 Lecture 3 - Jim Libby 1

Lecture 3 summary. C4 Lecture 3 - Jim Libby 1 Lecue su Fes of efeece Ivce ude sfoos oo of H wve fuco: d-fucos Eple: e e - µ µ - Agul oeu s oo geeo Eule gles Geec slos cosevo lws d Noehe s heoe C4 Lecue - Lbb Fes of efeece Cosde fe of efeece O whch

More information

MATHEMATICAL DERIVATION OF THE FARADAY INDUCTION LAW AND EXPLANATION OF ITS LORENTZ NON-INVARIANCE

MATHEMATICAL DERIVATION OF THE FARADAY INDUCTION LAW AND EXPLANATION OF ITS LORENTZ NON-INVARIANCE MTHEMTICL DERIVTION OF THE FRDY INDUCTION LW ND EXPLNTION OF ITS LORENTZ NON-INVRINCE.L. Kholmesk Depame of Phscs Belausa Sae Ues 4 F. Skoa eue 0080 Msk Belaus E-mal: kholm@bsu.b The pese pape ees he Faaa

More information

Least Squares Fitting (LSQF) with a complicated function Theexampleswehavelookedatsofarhavebeenlinearintheparameters

Least Squares Fitting (LSQF) with a complicated function Theexampleswehavelookedatsofarhavebeenlinearintheparameters Leas Squares Fg LSQF wh a complcaed fuco Theeampleswehavelookedasofarhavebeelearheparameers ha we have bee rg o deerme e.g. slope, ercep. For he case where he fuco s lear he parameers we ca fd a aalc soluo

More information

WORK POWER AND ENERGY Consevaive foce a) A foce is said o be consevaive if he wok done by i is independen of pah followed by he body b) Wok done by a consevaive foce fo a closed pah is zeo c) Wok done

More information

Field due to a collection of N discrete point charges: r is in the direction from

Field due to a collection of N discrete point charges: r is in the direction from Physcs 46 Fomula Shee Exam Coulomb s Law qq Felec = k ˆ (Fo example, f F s he elecc foce ha q exes on q, hen ˆ s a un veco n he decon fom q o q.) Elecc Feld elaed o he elecc foce by: Felec = qe (elecc

More information

Exponential Synchronization of the Hopfield Neural Networks with New Chaotic Strange Attractor

Exponential Synchronization of the Hopfield Neural Networks with New Chaotic Strange Attractor ITM Web of Cofeeces, 0509 (07) DOI: 0.05/ mcof/070509 ITA 07 Expoeal Sychozao of he Hopfeld Neual Newos wh New Chaoc Sage Aaco Zha-J GUI, Ka-Hua WANG* Depame of Sofwae Egeeg, Haa College of Sofwae Techology,qogha,

More information

Partial Molar Properties of solutions

Partial Molar Properties of solutions Paral Molar Properes of soluos A soluo s a homogeeous mxure; ha s, a soluo s a oephase sysem wh more ha oe compoe. A homogeeous mxures of wo or more compoes he gas, lqud or sold phase The properes of a

More information

MULTI-OBJECTIVE GEOMETRIC PROGRAMMING PROBLEM AND ITS APPLICATIONS

MULTI-OBJECTIVE GEOMETRIC PROGRAMMING PROBLEM AND ITS APPLICATIONS Yugoslav Joual of Opeaos Reseach Volume (), Numbe, -7 DOI:.98/YJORI MULTI-OBJECTIVE GEOMETRIC PROGRAMMING PROBLEM AND ITS APPLICATIONS Sahdul ISLAM Depame of Mahemacs, Guskaa Mahavdyalaya, Guskaa, Budwa

More information

5-1. We apply Newton s second law (specifically, Eq. 5-2). F = ma = ma sin 20.0 = 1.0 kg 2.00 m/s sin 20.0 = 0.684N. ( ) ( )

5-1. We apply Newton s second law (specifically, Eq. 5-2). F = ma = ma sin 20.0 = 1.0 kg 2.00 m/s sin 20.0 = 0.684N. ( ) ( ) 5-1. We apply Newon s second law (specfcally, Eq. 5-). (a) We fnd he componen of he foce s ( ) ( ) F = ma = ma cos 0.0 = 1.00kg.00m/s cos 0.0 = 1.88N. (b) The y componen of he foce s ( ) ( ) F = ma = ma

More information

Professor Wei Zhu. 1. Sampling from the Normal Population

Professor Wei Zhu. 1. Sampling from the Normal Population AMS570 Pofesso We Zhu. Samplg fom the Nomal Populato *Example: We wsh to estmate the dstbuto of heghts of adult US male. It s beleved that the heght of adult US male follows a omal dstbuto N(, ) Def. Smple

More information

2 shear strain / L for small angle

2 shear strain / L for small angle Sac quaons F F M al Sess omal sess foce coss-seconal aea eage Shea Sess shea sess shea foce coss-seconal aea llowable Sess Faco of Safe F. S San falue Shea San falue san change n lengh ognal lengh Hooke

More information

VECTOR MECHANICS FOR ENGINEERS: Vector Mechanics for Engineers: Dynamics. In the current chapter, you will study the motion of systems of particles.

VECTOR MECHANICS FOR ENGINEERS: Vector Mechanics for Engineers: Dynamics. In the current chapter, you will study the motion of systems of particles. Seeth Edto CHPTER 4 VECTOR MECHNICS FOR ENINEERS: DYNMICS Fedad P. ee E. Russell Johsto, J. Systems of Patcles Lectue Notes: J. Walt Ole Texas Tech Uesty 003 The Mcaw-Hll Compaes, Ic. ll ghts eseed. Seeth

More information

Capítulo. of Particles: Energy and Momentum Methods

Capítulo. of Particles: Energy and Momentum Methods Capíulo 5 Kieics of Paicles: Eegy ad Momeum Mehods Mecáica II Coes Ioducio Wok of a Foce Piciple of Wok & Eegy pplicaios of he Piciple of Wok & Eegy Powe ad Efficiecy Sample Poblem 3. Sample Poblem 3.

More information

Solution set Stat 471/Spring 06. Homework 2

Solution set Stat 471/Spring 06. Homework 2 oluo se a 47/prg 06 Homework a Whe he upper ragular elemes are suppressed due o smmer b Le Y Y Y Y A weep o he frs colum o oba: A ˆ b chagg he oao eg ad ec YY weep o he secod colum o oba: Aˆ YY weep o

More information

Continuous Time Markov Chains

Continuous Time Markov Chains Couous me Markov chas have seay sae probably soluos f a oly f hey are ergoc, us lke scree me Markov chas. Fg he seay sae probably vecor for a couous me Markov cha s o more ffcul ha s he scree me case,

More information

Lecture 5. Chapter 3. Electromagnetic Theory, Photons, and Light

Lecture 5. Chapter 3. Electromagnetic Theory, Photons, and Light Lecue 5 Chape 3 lecomagneic Theo, Phoons, and Ligh Gauss s Gauss s Faada s Ampèe- Mawell s + Loen foce: S C ds ds S C F dl dl q Mawell equaions d d qv A q A J ds ds In mae fields ae defined hough ineacion

More information

Technical Appendix for Inventory Management for an Assembly System with Product or Component Returns, DeCroix and Zipkin, Management Science 2005.

Technical Appendix for Inventory Management for an Assembly System with Product or Component Returns, DeCroix and Zipkin, Management Science 2005. Techc Appedx fo Iveoy geme fo Assemy Sysem wh Poduc o Compoe eus ecox d Zp geme Scece 2005 Lemm µ µ s c Poof If J d µ > µ he ˆ 0 µ µ µ µ µ µ µ µ Sm gumes essh he esu f µ ˆ > µ > µ > µ o K ˆ If J he so

More information

QR factorization. Let P 1, P 2, P n-1, be matrices such that Pn 1Pn 2... PPA

QR factorization. Let P 1, P 2, P n-1, be matrices such that Pn 1Pn 2... PPA QR facorzao Ay x real marx ca be wre as AQR, where Q s orhogoal ad R s upper ragular. To oba Q ad R, we use he Householder rasformao as follows: Le P, P, P -, be marces such ha P P... PPA ( R s upper ragular.

More information

k of the incident wave) will be greater t is too small to satisfy the required kinematics boundary condition, (19)

k of the incident wave) will be greater t is too small to satisfy the required kinematics boundary condition, (19) TOTAL INTRNAL RFLTION Kmacs pops Sc h vcos a coplaa, l s cosd h cd pla cocds wh h X pla; hc 0. y y y osd h cas whch h lgh s cd fom h mdum of hgh dx of faco >. Fo cd agls ga ha h ccal agl s 1 ( /, h hooal

More information

Phys Nov. 3, 2017 Today s Topics. Continue Chapter 2: Electromagnetic Theory, Photons, and Light Reading for Next Time

Phys Nov. 3, 2017 Today s Topics. Continue Chapter 2: Electromagnetic Theory, Photons, and Light Reading for Next Time Phys 31. No. 3, 17 Today s Topcs Cou Chap : lcomagc Thoy, Phoos, ad Lgh Radg fo Nx Tm 1 By Wdsday: Radg hs Wk Fsh Fowls Ch. (.3.11 Polazao Thoy, Jos Macs, Fsl uaos ad Bws s Agl Homwok hs Wk Chap Homwok

More information

The Linear Regression Of Weighted Segments

The Linear Regression Of Weighted Segments The Lear Regresso Of Weghed Segmes George Dael Maeescu Absrac. We proposed a regresso model where he depede varable s made o up of pos bu segmes. Ths suao correspods o he markes hroughou he da are observed

More information

Increasing the Image Quality of Atomic Force Microscope by Using Improved Double Tapered Micro Cantilever

Increasing the Image Quality of Atomic Force Microscope by Using Improved Double Tapered Micro Cantilever Rece Reseaces Teecocaos foacs Eecocs a Sga Pocessg ceasg e age Qa of oc Foce Mcope Usg pove oe Tapee Mco aeve Saeg epae of Mecaca Egeeg aava Bac sac za Uves aava Tea a a_saeg@aavaa.ac. sac: Te esoa feqec

More information

Chapter 5. Long Waves

Chapter 5. Long Waves ape 5. Lo Waes Wae e s o compaed ae dep: < < L π Fom ea ae eo o s s ; amos ozoa moo z p s ; dosac pesse Dep-aeaed coseao o mass

More information

FORCED VIBRATION of MDOF SYSTEMS

FORCED VIBRATION of MDOF SYSTEMS FORCED VIBRAION of DOF SSES he respose of a N DOF sysem s govered by he marx equao of moo: ] u C] u K] u 1 h al codos u u0 ad u u 0. hs marx equao of moo represes a sysem of N smulaeous equaos u ad s me

More information

Applying Eyring s Model to Times to Breakdown of Insulating Fluid

Applying Eyring s Model to Times to Breakdown of Insulating Fluid Ieaoal Joual of Pefomably Egeeg, Vol. 8, No. 3, May 22, pp. 279-288. RAMS Cosulas Ped Ida Applyg Eyg s Model o Tmes o Beakdow of Isulag Flud DANIEL I. DE SOUZA JR. ad R. ROCHA Flumese Fed. Uvesy, Cvl Egeeg

More information

Comparing Different Estimators for Parameters of Kumaraswamy Distribution

Comparing Different Estimators for Parameters of Kumaraswamy Distribution Compaig Diffee Esimaos fo Paamees of Kumaaswamy Disibuio ا.م.د نذير عباس ابراهيم الشمري جامعة النهرين/بغداد-العراق أ.م.د نشات جاسم محمد الجامعة التقنية الوسطى/بغداد- العراق Absac: This pape deals wih compaig

More information

s = rθ Chapter 10: Rotation 10.1: What is physics?

s = rθ Chapter 10: Rotation 10.1: What is physics? Chape : oaon Angula poson, velocy, acceleaon Consan angula acceleaon Angula and lnea quanes oaonal knec enegy oaonal nea Toque Newon s nd law o oaon Wok and oaonal knec enegy.: Wha s physcs? In pevous

More information

Today - Lecture 13. Today s lecture continue with rotations, torque, Note that chapters 11, 12, 13 all involve rotations

Today - Lecture 13. Today s lecture continue with rotations, torque, Note that chapters 11, 12, 13 all involve rotations Today - Lecue 13 Today s lecue coninue wih oaions, oque, Noe ha chapes 11, 1, 13 all inole oaions slide 1 eiew Roaions Chapes 11 & 1 Viewed fom aboe (+z) Roaional, o angula elociy, gies angenial elociy

More information

Single-Plane Auto-Balancing of Rigid Rotors

Single-Plane Auto-Balancing of Rigid Rotors TECHNISCHE MECHANIK Bad 4 Hef (4) -4 Mauspegag: 4. Novebe 3 Sgle-Plae Auo-Balacg of gd oos L. Spelg B. h H. Ducse Ths pape peses a aalcal sud of sgle-plae auoac balacg of sacall ad dacall ubalaced gd oos

More information

PULSATILE BLOOD FLOW IN CONSTRICTED TAPERED ARTERY USING A VARIABLE-ORDER FRACTIONAL OLDROYD-B MODEL

PULSATILE BLOOD FLOW IN CONSTRICTED TAPERED ARTERY USING A VARIABLE-ORDER FRACTIONAL OLDROYD-B MODEL Bakh, H., e al.: Pulsale Blood Flo Cosced Tapeed Aey Usg... THERMAL SCIENCE: Yea 7, Vol., No. A, pp. 9-4 9 PULSATILE BLOOD FLOW IN CONSTRICTED TAPERED ARTERY USING A VARIABLE-ORDER FRACTIONAL OLDROYD-B

More information

On Probability Density Function of the Quotient of Generalized Order Statistics from the Weibull Distribution

On Probability Density Function of the Quotient of Generalized Order Statistics from the Weibull Distribution ISSN 684-843 Joua of Sac Voue 5 8 pp. 7-5 O Pobaby Dey Fuco of he Quoe of Geeaed Ode Sac fo he Webu Dbuo Abac The pobaby dey fuco of Muhaad Aee X k Y k Z whee k X ad Y k ae h ad h geeaed ode ac fo Webu

More information

DUALITY IN MULTIPLE CRITERIA AND MULTIPLE CONSTRAINT LEVELS LINEAR PROGRAMMING WITH FUZZY PARAMETERS

DUALITY IN MULTIPLE CRITERIA AND MULTIPLE CONSTRAINT LEVELS LINEAR PROGRAMMING WITH FUZZY PARAMETERS Ida Joual of Fudameal ad ppled Lfe Sceces ISSN: 223 6345 (Ole) Ope ccess, Ole Ieaoal Joual valable a www.cbech.o/sp.ed/ls/205/0/ls.hm 205 Vol.5 (S), pp. 447-454/Noua e al. Reseach cle DULITY IN MULTIPLE

More information

Chapter 4. The Properties of Light 4.1 Introduction Scattering Transmission, reflection, and refraction

Chapter 4. The Properties of Light 4.1 Introduction Scattering Transmission, reflection, and refraction Chape 4. The Popees of Lgh 4.1 Ioduco Scaeg Tasmsso, efleco, ad efaco (mcoscopc) (macoscopc) Hech by YHLEE;100510; 4-1 4. Raylegh Scaeg Scaeg of sulgh Sulgh he a Goud-sae vbao of Re-emsso of lgh. oge,

More information

Midterm Exam. Tuesday, September hour, 15 minutes

Midterm Exam. Tuesday, September hour, 15 minutes Ecoomcs of Growh, ECON560 Sa Fracsco Sae Uvers Mchael Bar Fall 203 Mderm Exam Tuesda, Sepember 24 hour, 5 mues Name: Isrucos. Ths s closed boo, closed oes exam. 2. No calculaors of a d are allowed. 3.

More information

A Generalized Recursive Coordinate Reduction Method for Multibody System Dynamics

A Generalized Recursive Coordinate Reduction Method for Multibody System Dynamics eaoal Joual fo Mulscale Compuaoal Egeeg, 1(2&3181 199 (23 A Geealzed Recusve Coodae Reduco Mehod fo Mulbody Sysem Dyamcs J. H. Cchley & K. S. Adeso Depame of Mechacal, Aeoaucal, ad Nuclea Egeeg, Resselae

More information

A New Approach to Probabilistic Load Flow

A New Approach to Probabilistic Load Flow INDIAN INSTITUTE OF TECHNOLOGY, KHARAGPUR 73, DECEMBER 79, 837 A New Appoach o Pobablsc Load Flow T K Basu, R B Msa ad Puob Paoway Absac: Ths pape descbes a ew appoach o modellg of asmsso le uceaes usg

More information

( m is the length of columns of A ) spanned by the columns of A : . Select those columns of B that contain a pivot; say those are Bi

( m is the length of columns of A ) spanned by the columns of A : . Select those columns of B that contain a pivot; say those are Bi Assgmet /MATH 47/Wte Due: Thusday Jauay The poblems to solve ae umbeed [] to [] below Fst some explaatoy otes Fdg a bass of the colum-space of a max ad povg that the colum ak (dmeso of the colum space)

More information

Chapter 3: Vectors and Two-Dimensional Motion

Chapter 3: Vectors and Two-Dimensional Motion Chape 3: Vecos and Two-Dmensonal Moon Vecos: magnude and decon Negae o a eco: eese s decon Mulplng o ddng a eco b a scala Vecos n he same decon (eaed lke numbes) Geneal Veco Addon: Tangle mehod o addon

More information

dm dt = 1 V The number of moles in any volume is M = CV, where C = concentration in M/L V = liters. dcv v

dm dt = 1 V The number of moles in any volume is M = CV, where C = concentration in M/L V = liters. dcv v Mg: Pcess Aalyss: Reac ae s defed as whee eac ae elcy lue M les ( ccea) e. dm he ube f les ay lue s M, whee ccea M/L les. he he eac ae beces f a hgeeus eac, ( ) d Usually s csa aqueus eeal pcesses eac,

More information

ON TOTAL TIME ON TEST TRANSFORM ORDER ABSTRACT

ON TOTAL TIME ON TEST TRANSFORM ORDER ABSTRACT V M Chacko E CONVE AND INCREASIN CONVE OAL IME ON ES RANSORM ORDER R&A # 4 9 Vol. Decembe ON OAL IME ON ES RANSORM ORDER V. M. Chacko Depame of Sascs S. homas Collee hss eala-68 Emal: chackovm@mal.com

More information

APPLICATION OF A Z-TRANSFORMS METHOD FOR INVESTIGATION OF MARKOV G-NETWORKS

APPLICATION OF A Z-TRANSFORMS METHOD FOR INVESTIGATION OF MARKOV G-NETWORKS Joa of Aed Mahema ad Comaoa Meha 4 3( 6-73 APPLCATON OF A Z-TRANSFORMS METHOD FOR NVESTGATON OF MARKOV G-NETWORKS Mha Maay Vo Nameo e of Mahema Ceohowa Uey of Tehoogy Cęohowa Poad Fay of Mahema ad Come

More information

(1) Cov(, ) E[( E( ))( E( ))]

(1) Cov(, ) E[( E( ))( E( ))] Impac of Auocorrelao o OLS Esmaes ECON 3033/Evas Cosder a smple bvarae me-seres model of he form: y 0 x The four key assumpos abou ε hs model are ) E(ε ) = E[ε x ]=0 ) Var(ε ) =Var(ε x ) = ) Cov(ε, ε )

More information

1. INTRODUCTION In this paper, we consider a general ninth order linear boundary value problem (1) subject to boundary conditions

1. INTRODUCTION In this paper, we consider a general ninth order linear boundary value problem (1) subject to boundary conditions NUMERICAL SOLUTION OF NINTH ORDER BOUNDARY VALUE PROBLEMS BY PETROV-GALERKIN METHOD WITH QUINTIC B-SPLINES AS BASIS FUNCTIONS AND SEXTIC B-SPLINES AS WEIGHT FUNCTIONS K. N. S. Kas Vswaaham a S. V. Kamay

More information

General Non-Arbitrage Model. I. Partial Differential Equation for Pricing A. Traded Underlying Security

General Non-Arbitrage Model. I. Partial Differential Equation for Pricing A. Traded Underlying Security 1 Geneal Non-Abiage Model I. Paial Diffeenial Equaion fo Picing A. aded Undelying Secuiy 1. Dynamics of he Asse Given by: a. ds = µ (S, )d + σ (S, )dz b. he asse can be eihe a sock, o a cuency, an index,

More information

Shrinkage Estimators for Reliability Function. Mohammad Qabaha

Shrinkage Estimators for Reliability Function. Mohammad Qabaha A - Najah Uv. J. es. (N. Sc.) Vol. 7 3 Shkage Esmaos fo elably Fuco مقدرات التقلص لدالة الفاعلية ohammad Qabaha محمد قبها Depame of ahemacs Faculy of Scece A-Najah Naoal Uvesy alese E-mal: mohqabha@mal.ajah.edu

More information

EN221 - Fall HW # 7 Solutions

EN221 - Fall HW # 7 Solutions EN221 - Fall2008 - HW # 7 Soluions Pof. Vivek Shenoy 1.) Show ha he fomulae φ v ( φ + φ L)v (1) u v ( u + u L)v (2) can be pu ino he alenaive foms φ φ v v + φv na (3) u u v v + u(v n)a (4) (a) Using v

More information

PHYS 1114, Lecture 21, March 6 Contents:

PHYS 1114, Lecture 21, March 6 Contents: PHYS 1114, Lectue 21, Mach 6 Contents: 1 This class is o cially cancelled, being eplaced by the common exam Tuesday, Mach 7, 5:30 PM. A eview and Q&A session is scheduled instead duing class time. 2 Exam

More information

, on the power of the transmitter P t fed to it, and on the distance R between the antenna and the observation point as. r r t

, on the power of the transmitter P t fed to it, and on the distance R between the antenna and the observation point as. r r t Lecue 6: Fiis Tansmission Equaion and Rada Range Equaion (Fiis equaion. Maximum ange of a wieless link. Rada coss secion. Rada equaion. Maximum ange of a ada. 1. Fiis ansmission equaion Fiis ansmission

More information

The ray paths and travel times for multiple layers can be computed using ray-tracing, as demonstrated in Lab 3.

The ray paths and travel times for multiple layers can be computed using ray-tracing, as demonstrated in Lab 3. C. Trael me cures for mulple reflecors The ray pahs ad rael mes for mulple layers ca be compued usg ray-racg, as demosraed Lab. MATLAB scrp reflec_layers_.m performs smple ray racg. (m) ref(ms) ref(ms)

More information

An Exact Solution for the Differential Equation. Governing the Lateral Motion of Thin Plates. Subjected to Lateral and In-Plane Loadings

An Exact Solution for the Differential Equation. Governing the Lateral Motion of Thin Plates. Subjected to Lateral and In-Plane Loadings Appled Mahemacal Sceces, Vol., 8, o. 34, 665-678 A Eac Soluo for he Dffereal Equao Goverg he Laeral Moo of Th Plaes Subjeced o Laeral ad I-Plae Loadgs A. Karmpour ad D.D. Gaj Mazadara Uvers Deparme of

More information

The Poisson Process Properties of the Poisson Process

The Poisson Process Properties of the Poisson Process Posso Processes Summary The Posso Process Properes of he Posso Process Ierarrval mes Memoryless propery ad he resdual lfeme paradox Superposo of Posso processes Radom seleco of Posso Pos Bulk Arrvals ad

More information

Minimizing spherical aberrations Exploiting the existence of conjugate points in spherical lenses

Minimizing spherical aberrations Exploiting the existence of conjugate points in spherical lenses Mmzg sphecal abeatos Explotg the exstece of cojugate pots sphecal leses Let s ecall that whe usg asphecal leses, abeato fee magg occus oly fo a couple of, so called, cojugate pots ( ad the fgue below)

More information

Anouncements. Conjugate Gradients. Steepest Descent. Outline. Steepest Descent. Steepest Descent

Anouncements. Conjugate Gradients. Steepest Descent. Outline. Steepest Descent. Steepest Descent oucms Couga Gas Mchal Kazha (6.657) Ifomao abou h Sma (6.757) hav b pos ol: hp://www.cs.hu.u/~msha Tch Spcs: o M o Tusay afoo. o Two paps scuss ach w. o Vos fo w s caa paps u by Thusay vg. Oul Rvw of Sps

More information

Cyclone. Anti-cyclone

Cyclone. Anti-cyclone Adveco Cycloe A-cycloe Lorez (963) Low dmesoal aracors. Uclear f hey are a good aalogy o he rue clmae sysem, bu hey have some appealg characerscs. Dscusso Is he al codo balaced? Is here a al adjusme

More information

Non-axial symmetric loading on axial symmetric. Final Report of AFEM

Non-axial symmetric loading on axial symmetric. Final Report of AFEM No-axal symmetc loadg o axal symmetc body Fal Repot of AFEM Ths poject does hamoc aalyss of o-axal symmetc loadg o axal symmetc body. Shuagxg Da, Musket Kamtokat 5//009 No-axal symmetc loadg o axal symmetc

More information

Final Exam Applied Econometrics

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

More information

A Survey on Model Reduction Methods to Reduce Degrees of Freedom of Linear Damped Vibrating Systems

A Survey on Model Reduction Methods to Reduce Degrees of Freedom of Linear Damped Vibrating Systems opdaa Aavakom 460767 Mah, pg 003 A uvey o Model Reduco Mehods o Reduce Degees o Feedom o Lea Damped Vbag ysems ABRAC hs epo descbes he deals o he model educo mehods o educe degees o eedom o he dyamc aalyss

More information

ENGI 4430 Advanced Calculus for Engineering Faculty of Engineering and Applied Science Problem Set 9 Solutions [Theorems of Gauss and Stokes]

ENGI 4430 Advanced Calculus for Engineering Faculty of Engineering and Applied Science Problem Set 9 Solutions [Theorems of Gauss and Stokes] ENGI 44 Avance alculus fo Engineeing Faculy of Engineeing an Applie cience Poblem e 9 oluions [Theoems of Gauss an okes]. A fla aea A is boune by he iangle whose veices ae he poins P(,, ), Q(,, ) an R(,,

More information

Fairing of Parametric Quintic Splines

Fairing of Parametric Quintic Splines ISSN 46-69 Eglad UK Joual of Ifomato ad omputg Scece Vol No 6 pp -8 Fag of Paametc Qutc Sples Yuau Wag Shagha Isttute of Spots Shagha 48 ha School of Mathematcal Scece Fuda Uvesty Shagha 4 ha { P t )}

More information

CHAPTER 10: LINEAR DISCRIMINATION

CHAPTER 10: LINEAR DISCRIMINATION HAPER : LINEAR DISRIMINAION Dscmnan-based lassfcaon 3 In classfcaon h K classes ( k ) We defned dsmnan funcon g () = K hen gven an es eample e chose (pedced) s class label as f g () as he mamum among g

More information

The shortest path between two truths in the real domain passes through the complex domain. J. Hadamard

The shortest path between two truths in the real domain passes through the complex domain. J. Hadamard Complex Analysis R.G. Halbud R.Halbud@ucl.ac.uk Depamen of Mahemaics Univesiy College London 202 The shoes pah beween wo uhs in he eal domain passes hough he complex domain. J. Hadamad Chape The fis fundamenal

More information

Lecture 5. Plane Wave Reflection and Transmission

Lecture 5. Plane Wave Reflection and Transmission Lecue 5 Plane Wave Reflecon and Tansmsson Incden wave: 1z E ( z) xˆ E (0) e 1 H ( z) yˆ E (0) e 1 Nomal Incdence (Revew) z 1 (,, ) E H S y (,, ) 1 1 1 Refleced wave: 1z E ( z) xˆ E E (0) e S H 1 1z H (

More information

Trajectory Planning and Tracking Control of a Differential-Drive Mobile Robot in a Picture Drawing Application

Trajectory Planning and Tracking Control of a Differential-Drive Mobile Robot in a Picture Drawing Application Acle ajecoy Plag ad ackg Cool of a Dffeeal-Dve Mole Roo a Pcue Dawg Applcao Chg-Log Shh * ad L-Che L Depame of Eleccal Egeeg, aoal awa Uvesy of Scece ad echology, ape 67, awa; M4743@mal.us.edu.w * Coespodece:

More information

VIII Dynamics of Systems of Particles

VIII Dynamics of Systems of Particles VIII Dyacs of Systes of Patcles Cete of ass: Cete of ass Lea oetu of a Syste Agula oetu of a syste Ketc & Potetal Eegy of a Syste oto of Two Iteactg Bodes: The Reduced ass Collsos: o Elastc Collsos R whee:

More information

Circular Motion. Radians. One revolution is equivalent to which is also equivalent to 2π radians. Therefore we can.

Circular Motion. Radians. One revolution is equivalent to which is also equivalent to 2π radians. Therefore we can. 1 Cicula Moion Radians One evoluion is equivalen o 360 0 which is also equivalen o 2π adians. Theefoe we can say ha 360 = 2π adians, 180 = π adians, 90 = π 2 adians. Hence 1 adian = 360 2π Convesions Rule

More information

AP-C WEP. h. Students should be able to recognize and solve problems that call for application both of conservation of energy and Newton s Laws.

AP-C WEP. h. Students should be able to recognize and solve problems that call for application both of conservation of energy and Newton s Laws. AP-C WEP 1. Wok a. Calculate the wok done by a specified constant foce on an object that undegoes a specified displacement. b. Relate the wok done by a foce to the aea unde a gaph of foce as a function

More information

MAT 516 Curve and Surface Methods for CAGD [Kaedah Lengkung dan Permukaan untuk RGBK]

MAT 516 Curve and Surface Methods for CAGD [Kaedah Lengkung dan Permukaan untuk RGBK] UNIVERSITI SAINS MALAYSIA Secod Semese Examao / Academc Sesso Jue MAT 56 Cuve ad Suface Mehods fo CAGD [Kaedah Legkug da Pemukaa uuk RGBK] Duao : hous [Masa : am] Please check ha hs examao ae cosss of

More information

2. Electrostatics. Dr. Rakhesh Singh Kshetrimayum 8/11/ Electromagnetic Field Theory by R. S. Kshetrimayum

2. Electrostatics. Dr. Rakhesh Singh Kshetrimayum 8/11/ Electromagnetic Field Theory by R. S. Kshetrimayum 2. Electostatics D. Rakhesh Singh Kshetimayum 1 2.1 Intoduction In this chapte, we will study how to find the electostatic fields fo vaious cases? fo symmetic known chage distibution fo un-symmetic known

More information

= y and Normed Linear Spaces

= y and Normed Linear Spaces 304-50 LINER SYSTEMS Lectue 8: Solutos to = ad Nomed Lea Spaces 73 Fdg N To fd N, we eed to chaacteze all solutos to = 0 Recall that ow opeatos peseve N, so that = 0 = 0 We ca solve = 0 ecusvel backwads

More information

φ (x,y,z) in the direction of a is given by

φ (x,y,z) in the direction of a is given by UNIT-II VECTOR CALCULUS Dectoal devatve The devatve o a pot ucto (scala o vecto) a patcula decto s called ts dectoal devatve alo the decto. The dectoal devatve o a scala pot ucto a ve decto s the ate o

More information

Qualifying Examination Electricity and Magnetism Solutions January 12, 2006

Qualifying Examination Electricity and Magnetism Solutions January 12, 2006 1 Qualifying Examination Electicity and Magnetism Solutions Januay 12, 2006 PROBLEM EA. a. Fist, we conside a unit length of cylinde to find the elationship between the total chage pe unit length λ and

More information

Real-Time Systems. Example: scheduling using EDF. Feasibility analysis for EDF. Example: scheduling using EDF

Real-Time Systems. Example: scheduling using EDF. Feasibility analysis for EDF. Example: scheduling using EDF EDA/DIT6 Real-Tme Sysems, Chalmers/GU, 0/0 ecure # Updaed February, 0 Real-Tme Sysems Specfcao Problem: Assume a sysem wh asks accordg o he fgure below The mg properes of he asks are gve he able Ivesgae

More information

Physics 201 Lecture 15

Physics 201 Lecture 15 Phscs 0 Lecue 5 l Goals Lecue 5 v Elo consevaon of oenu n D & D v Inouce oenu an Iulse Coens on oenu Consevaon l oe geneal han consevaon of echancal eneg l oenu Consevaon occus n sses wh no ne eenal foces

More information

Mixed Integral Equation of Contact Problem in Position and Time

Mixed Integral Equation of Contact Problem in Position and Time Ieraoal Joural of Basc & Appled Sceces IJBAS-IJENS Vol: No: 3 ed Iegral Equao of Coac Problem Poso ad me. A. Abdou S. J. oaquel Deparme of ahemacs Faculy of Educao Aleadra Uversy Egyp Deparme of ahemacs

More information

Name of the Student:

Name of the Student: Engneeng Mahemacs 05 SUBJEC NAME : Pobably & Random Pocess SUBJEC CODE : MA645 MAERIAL NAME : Fomula Maeal MAERIAL CODE : JM08AM007 REGULAION : R03 UPDAED ON : Febuay 05 (Scan he above QR code fo he dec

More information

A Modeling Method of SISO Discrete-Event Systems in Max Algebra

A Modeling Method of SISO Discrete-Event Systems in Max Algebra A Modelg Mehod of SISO Dscee-Eve Syses Max Algeba Jea-Lous Bood, Laue Hadou, P. Cho To ce hs veso: Jea-Lous Bood, Laue Hadou, P. Cho. A Modelg Mehod of SISO Dscee-Eve Syses Max Algeba. Euopea Cool Cofeece

More information

Eurasian International Center of Theoretical Physics, Eurasian National University, Astana , Kazakhstan

Eurasian International Center of Theoretical Physics, Eurasian National University, Astana , Kazakhstan Joul o Mhems d sem ee 8 8 87-95 do: 765/59-59/8 D DAVID PUBLIHIG E Loled oluos o he Geeled +-Dmesol Ldu-Lsh Equo Gulgssl ugmov Ao Mul d Zh gdullev Eus Ieol Cee o Theoel Phss Eus ol Uves As 8 Khs As: I

More information

Chapter Fifiteen. Surfaces Revisited

Chapter Fifiteen. Surfaces Revisited Chapte Ffteen ufaces Revsted 15.1 Vecto Descpton of ufaces We look now at the vey specal case of functons : D R 3, whee D R s a nce subset of the plane. We suppose s a nce functon. As the pont ( s, t)

More information

On the Quasi-Hyperbolic Kac-Moody Algebra QHA7 (2)

On the Quasi-Hyperbolic Kac-Moody Algebra QHA7 (2) Ieaoal Reeach Joual of Egeeg ad Techology (IRJET) e-issn: 9 - Volume: Iue: May- www.e.e -ISSN: 9-7 O he Qua-Hyebolc Kac-Moody lgeba QH7 () Uma Mahewa., Khave. S Deame of Mahemac Quad-E-Mllah Goveme College

More information

Two-dimensional Effects on the CSR Interaction Forces for an Energy-Chirped Bunch. Rui Li, J. Bisognano, R. Legg, and R. Bosch

Two-dimensional Effects on the CSR Interaction Forces for an Energy-Chirped Bunch. Rui Li, J. Bisognano, R. Legg, and R. Bosch Two-dimensional Effecs on he CS Ineacion Foces fo an Enegy-Chiped Bunch ui Li, J. Bisognano,. Legg, and. Bosch Ouline 1. Inoducion 2. Pevious 1D and 2D esuls fo Effecive CS Foce 3. Bunch Disibuion Vaiaion

More information

Review: Electrostatics and Magnetostatics

Review: Electrostatics and Magnetostatics Review: Electostatics and Magnetostatics In the static egime, electomagnetic quantities do not vay as a function of time. We have two main cases: ELECTROSTATICS The electic chages do not change postion

More information

Lecture Y4: Computational Optics I

Lecture Y4: Computational Optics I Phooc ad opolcoc chologs DPMS: Advacd Maals Udsadg lgh ma acos s cucal fo w applcaos Lcu Y4: Compuaoal Opcs I lfos Ldoks Room Π, 65 746 ldok@cc.uo.g hp://cmsl.maals.uo.g/ldoks Rflco ad faco Toal al flco

More information

L4:4. motion from the accelerometer. to recover the simple flutter. Later, we will work out how. readings L4:3

L4:4. motion from the accelerometer. to recover the simple flutter. Later, we will work out how. readings L4:3 elave moon L4:1 To appl Newon's laws we need measuemens made fom a 'fed,' neal efeence fame (unacceleaed, non-oang) n man applcaons, measuemens ae made moe smpl fom movng efeence fames We hen need a wa

More information

Competitive Facility Location Problem with Demands Depending on the Facilities

Competitive Facility Location Problem with Demands Depending on the Facilities Aa Pacc Maageme Revew 4) 009) 5-5 Compeve Facl Locao Problem wh Demad Depedg o he Facle Shogo Shode a* Kuag-Yh Yeh b Hao-Chg Ha c a Facul of Bue Admrao Kobe Gau Uver Japa bc Urba Plag Deparme Naoal Cheg

More information

JURONG JUNIOR COLLEGE Physics Department Tutorial: Electric Fields (solutions)

JURONG JUNIOR COLLEGE Physics Department Tutorial: Electric Fields (solutions) JJ 5 H Physics (646) Electic Fields_tutsoln JURONG JUNIOR COLLEGE Physics Depatment Tutoial: Electic Fields (solutions) No Solution LO Electic field stength at a point in an electic field is defined as

More information

Computation of an Over-Approximation of the Backward Reachable Set using Subsystem Level Set Functions

Computation of an Over-Approximation of the Backward Reachable Set using Subsystem Level Set Functions Compuao o a Ove-Appomao o he Backwad Reachable Se usg Subsysem Level Se Fucos Duša M Spaov, Iseok Hwag, ad Clae J oml Depame o Aeoaucs ad Asoaucs Saod Uvesy Saod, CA 94305-4035, USA E-mal: {dusko, shwag,

More information

Motion and Flow II. Structure from Motion. Passive Navigation and Structure from Motion. rot

Motion and Flow II. Structure from Motion. Passive Navigation and Structure from Motion. rot Moto ad Flow II Sce fom Moto Passve Navgato ad Sce fom Moto = + t, w F = zˆ t ( zˆ ( ([ ] =? hesystemmoveswth a gd moto wth aslat oal velocty t = ( U, V, W ad atoalvelocty w = ( α, β, γ. Scee pots R =

More information

Lecture 11: Introduction to nonlinear optics I.

Lecture 11: Introduction to nonlinear optics I. Lectue : Itoducto to olea optcs I. Pet Kužel Fomulato of the olea optcs: olea polazato Classfcato of the olea pheomea Popagato of wea optc sgals stog quas-statc felds (descpto usg eomalzed lea paametes)!

More information

Key words: Fractional difference equation, oscillatory solutions,

Key words: Fractional difference equation, oscillatory solutions, OSCILLATION PROPERTIES OF SOLUTIONS OF FRACTIONAL DIFFERENCE EQUATIONS Musafa BAYRAM * ad Ayd SECER * Deparme of Compuer Egeerg, Isabul Gelsm Uversy Deparme of Mahemacal Egeerg, Yldz Techcal Uversy * Correspodg

More information

BENDING OF BEAM. Compressed layer. Elongated. layer. Un-strained. layer. NA= Neutral Axis. Compression. Unchanged. Elongation. Two Dimensional View

BENDING OF BEAM. Compressed layer. Elongated. layer. Un-strained. layer. NA= Neutral Axis. Compression. Unchanged. Elongation. Two Dimensional View BNDING OF BA Compessed laye N Compession longation Un-stained laye Unchanged longated laye NA Neutal Axis Two Dimensional View A When a beam is loaded unde pue moment, it can be shown that the beam will

More information

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

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

More information

Fakultas Matematika dan Ilmu Pengetahuan Alam, Institut Teknologi Bandung, Bandung, 40132, Indonesia *

Fakultas Matematika dan Ilmu Pengetahuan Alam, Institut Teknologi Bandung, Bandung, 40132, Indonesia * MacWllams Equvalece Theoem fo he Lee Wegh ove Z 4 leams Baa * Fakulas Maemaka da Ilmu Pegeahua lam, Isu Tekolog Badug, Badug, 403, Idoesa * oesodg uho: baa@mahbacd BSTRT Fo codes ove felds, he MacWllams

More information