ME617 - Handout 7 (Undamped) Modal Analysis of MDOF Systems

Size: px
Start display at page:

Download "ME617 - Handout 7 (Undamped) Modal Analysis of MDOF Systems"

Transcription

1 ME67 - Hadout 7 (Udamped) Modal Aalysis of MDOF Systems he goverig equatios of motio for a -DOF liear mechaical system with viscous dampig are: MU+DU+KU F () () t () t where U,U, ad U are the vectors of geeralized displacemet, velocity ad acceleratio, respectively; ad F () t is the vector of geeralized (exteral forces) actig o the system. M,D,K represet the matrices of iertia, viscous dampig ad stiffess coefficiets, respectively. he solutio of Eq. () is uiquely determied oce iitial coditios are specified. hat is, at t U U, U U () () o () o I most cases, i.e. coservative systems, the iertia ad stiffess matrices are SYMMERIC, i.e., eergy () ad potetial eergy (V) i a coservative system are M M K K. he kietic U MU, V U KU (3) he matrices are square with -rows colums, while the vectors are - rows. MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8

2 I additio, sice >, the M is a positive defiite matrix. If V >, the K is a positive defiite matrix. V deotes the existece of a rigid body mode, ad makes K a semi-positive matrix. I MDOF systems, a atural state implies a certai cofiguratio of shape take by the system durig motio. Moreover a MDOF system does ot possess oly ONE atural state but a fiite umber of states kow as atural modes of vibratio. Depedig o the iitial coditios or exteral forcig excitatio, the system ca vibrate i ay of these modes or a combiatio of them. o each mode correspods a uique frequecy kows as a atural frequecy. here are as may atural frequecies as atural modes. he modelig of a -DOF mechaical system leads to a set of - coupled d order ODEs, Hece the motio i the directio of oe DOF, say k, depeds o or it is coupled to the motio i the other degrees of freedom,,. I the aalysis below, for a proper choice of geeralized coordiates, kow as pricipal or atural coordiates, the system of -ODE describig the system motio is idepedet of each other, i.e. ucoupled. he atural coordiates are liear combiatios of the (actual) physical coordiates, ad coversely. Hece, the motio i physical coordiates ca be costrued or iterpreted as the superpositio or combiatio of the motios i each atural coordiate. Positive defiite meas that the determiat of the matrix is greater tha zero. More importatly, it also meas that all the matrix eigevalues will be positive. A semi-positive matrix has a zero determiat, with at least a eigevalues equalig zero. MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8

3 For simplicity, begi the aalysis of the system by eglectig dampig, D. Hece, Eq.() reduces to MU+KU () t F() t (4) at t U U, U U ad () o () Presetly, set the exteral force F, ad let s fid the free vibratios respose of the system. o MU+KU (5) he solutio to the homogeous Eq. (5) is simply U φ cos( t θ ) (6) which deotes a periodic respose with a typical frequecy. From Eq. (6), U φ cos( t θ) (7) Note that Eq. (6) is a simplificatio of the more geeral solutio st U φ e with s i ad where i (8) Substitutio of Eqs. (6) ad (7) ito the EOM (5) gives: MU+KU Mφ cos( t θ) +Kφ cos( t θ) cos( t ) M +K φ θ ad sice cos( t θ ) for most times, the MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 3

4 or M +K φ (9) Mφ K φ () Eq. () is usually referred as the stadard eigevalue problem (mathematical argo): Aφ λ φ where Α M K adλ () Eq.(9) is a set of -homogeous algebraic equatios. A otrivial solutio, φ exists if ad oly if the determiat Δ of the system of equatios is zero, i.e. Δ M +K () Eq. () is kow as the characteristic equatio of the system. It is a polyomial i λ, i.e. 4 6 Δ a+ a + a + a a (3) i Δ a + ( ai λ ) i his polyomial or characteristic equatios has -roots, i.e. the λ k k set { },,... ± sice ± λ. k k or { },,... he s are kow as the atural frequecies of the system. I the MAH argo, the λ s are kow as the eigevalues (of matrix A) MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 4

5 Kowledge summary a) A -DOF system has -atural frequecies. b) If M ad K are positive defiite, the <.... c) If K is semi-positive defiite, the..., i.e. at least oe atural frequecy is zero, i.e. motio with ifiite period. his is kow as rigid body mode. Note that each of the atural frequecies satisfies Eq. (9). Hece, associated to each atural frequecy (or eigevalues) there is a correspodig atural mode vector (eigevector) such that [ ] (),,... M +K φ (4) λ i i i he -elemets of a eigevector are real umbers (for udamped system), with all etries defied except for a costat. he eigevectors are uique i the sese that the ratio betwee two elemets is costat, i.e. ϕ( k ) costat for ay i,,... ϕ ( k ) i he actual value of the elemets i the vector is etirely arbitrary. Sice Eq. (4) is homogeous, if φ is a solutio, so it is αφ for ay arbitrary costat α. Hece, oe ca say that the SHAPE of a atural mode is UNIQUE but ot its amplitude. For MDOF systems with a large umber of degrees of freedom, >>3, the eigevalue problem, Eq. (), is solved umerically. MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 5

6 Nowadays, PCs ad mathematical computatio software allow, with a sigle (simple) commad, the evaluatio of all (or some) eigevalues ad its correspodig eigevectors i real time, eve for systems with thousads of DOFs. Log goe are the days whe the graduate studet or practicig egieer had to develop his/her ow efficiet computatioal routies to calculate eigevalues. Hadout # 9 discusses briefly some of the most popular umerical methods to solve the eigevalue problem. A this time, however, let s assume the set of eigepairs, φ is kow. { i () i } i,... Properties of atural modes he atural modes (or eigevectors) satisfy importat orthogoality properties. Recall that each eigepair, φ satisfies the equatio { i () i } i,... M i +K φ () i, i,.... (5) Cosider two differet modes, say mode- ad mode-k, each satisfyig Mφ K φ ad Mφ K φ (6) k ( k) ( k) Pre-multiply the equatios above by φ( k ) ad φ to obtai MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 6

7 ad φ Mφ φ K φ ( k) ( k) φ Mφ φ K φ k ( k) ( k) (7) Now, perform some matrix maipulatios. he products φ Mφ ad φ Kφ are scalars, i.e. ot a matrix or a vector. he traspose of a scalar is the umber itself. Hece, ( φ K φ( k) ) ( K φ( k) ) ( φ ) ad φ ( k) φ K φ sice KK k K φ ( k) ( k) sice φ Mφ φ Mφ MM for symmetric systems. hus, Eqs. (7) are rewritte as ad φ Mφ φ K φ ( k) ( k) ( a) (8) φ Mφ φ K φ k ( k) ( k) ( b) Subtract (b) from (a) above to obtai if k follows that ( ) k ( k) φ Mφ (9), i.e. for WO differet atural frequecies; the it MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 7

8 for k φ Mφ ad φ K φ () k k for k φ Mφ M ad φ K φ K M () where K ad M are kow as the -modal stiffess ad -modal mass, respectively. Defie a modal matrix Φ has as its colums each of the eigevectors, i.e. [ ] Φ φ φ φ ().. ad the modal properties are writte as [ M ]; [ K ] Φ MΦ Φ K Φ () where [M] ad [K] are diagoal matrices cotaiig the modal mass ad stiffesses, respectively. he eigevector set φ k, is liearly idepedet. Hece, ay vector (v) i -dimesioal space ca be described as a liear combiatio of the atural modes, i.e. v a φ Φa (3) a a v φa+ φa φa [ φ φ.. φ] Φa.. a MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 8

9 System Respose i Modal Coordiates he orthogoality property of the atural modes (eigevectors) permits the simplificatio of the aalysis for predictio of system respose. Recall that the equatios of motio for the udamped system are MU+KU () t F() t (4) at t U U, U U ad () () U Φ q (4) 3 Cosider the modal trasformatio () t () t Ad with U () t Φ q () t, the EOM (4) becomes: M Φq+KΦqF () t which offers o advatage i the aalysis. However, premultiply the equatio above by Φ to obtai ( Φ MΦ ) q+ ( Φ K Φ ) qφ F () t (5) ad usig the properties of the atural modes, Φ M Φ M ; Φ K Φ K, the Eq. (5) becomes [ ] [ ] [ M] q+ [ K ] qq Φ F() t (6) 3 Eq. (4) sets the physical displacemets U as a fuctio of the modal coordiates q. his trasformatio merely uses the property of liear idepedece of the atural modes. MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 9

10 Ad sice [M] ad [K] are diagoal matrices. Eq. (6) is ust a set of -ucoupled ODEs. hat is, Mq+ Kq Q M q + K q Q... M q + K q Q (7) (8) M q + K q Q with, K Or M,... he set of q s are kow as modal or atural coordiates (caoical or pricipal, too). he vector Q Φ F() t is kow as the modal force vector. hus, the maor advatage of the modal trasformatio (4) is that i modal space the EOMS are ucoupled. Each equatio describes a mode as a SDOF system. he uique solutio of Eqs. (8) eeds of iitial coditios qo, q o. U Φq U Φq specified i modal space, i.e. { } Usig the modal trasformatio, o o; o o, it follows q Φ U ; q Φ U (8) o o o o However, Eq. (8) requires of the iverse of modal matrix Φ, i.e. Φ Φ I. For systems with a large umber of DOF, >>, fidig the matrix Φ is computatioally expesive. MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8

11 A more efficiet to determie the iitial state { q, q } o o i modal coordiates follows. Start with the fudametal trasformatio, Uo Φq o, ad premultiply this relatioship by Φ M to obtai, Φ MUo Φ MΦqo [ M ] q, o sice [ M ] Φ MΦ, hece or q q q o o [ M ] [ M ] Φ MUo Φ MU o φ MU φ MU, q ok ( k) o ok ( k) o Mk Mk, (9a) (9b) Eqs. (9) are much easier to calculate efficietly whe -DOF is large. Note that fidig the iverse of the modal mass matrix [M] - is trivial, sice this matrix is diagoal. Comparig eqs. (8) ad (9a) it follows that [ M ] Φ Φ M (3) he solutio of ODEs M q + K q Q with iitial coditios { o, } o q q follows a idetical procedure as i the solutio of the SDOF respose. hat is, each modal respose adds the homogeeous solutio ad the particular solutio. he particular solutio clearly depeds o the time form of the modal MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8

12 force Q(t), i.e step-load, ramp-load, pulse-load, periodic load, or arbitrary time form. Free respose i modal coordiates Without modal forces, Q, the modal equatios are (3a) M q + K q Q H H with solutios, for a elastic mode qo qh qo cos( ) si t + t if (3b) ; ad for a rigid body mode qh qo + q o t if (3c),,. Forced respose i modal coordiates For step-loads, Q S, the modal equatios are (3a) M q + K q Q S ad; for a elastic mode,, q Q q qo cos si cos t + t + t K o S ( ) ( ) ( ) (3a) MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8

13 ; ad for a rigid body mode,, QS q qo + q o t+ t M (3c) For periodic loads,, the modal equatios are with solutios M q + K q Q cos( Ωt) P for a elastic mode,, ad,,. (33a) Ω QP q Ccos( t) + S si cos t + Ωt K ( Ω ) (33b) Note that if destructio. Ω, a resoace appears that will lead to system For a rigid body mode,, Q P q cos qo + q o t Ωt (33c) M Ω For arbitrary-loads Q, the modal respose is q q q cos( t) + si( t) + Q si ( t τ) dτ o t o ( τ ) M (34) for a elastic mode,. MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 3

14 System Respose i Physical Coordiates Oce the respose i modal coordiates is fully determied, the system respose i physical coordiates follows usig the modal trasformatio U Φ q () t () t q t q U [ φ φ.. φ ] φ q + φ q φ q.. q () t () t q U φ (35) ( t ) Oe importat questio follows: are all the modal resposes importat ad eed be accouted for to obtai the respose i physical coordiates? If ot, savigs i computatio time are evidet. Hece, the physical respose becomes m U φ q, m< (36) () t ( t ) If m<, the how may modes are to be icluded to esure the physical respose is accurate? hat is, which modes are importat ad which others are ot? MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 4

15 Example: Cosider the case of force excitatio with frequecy Ω ad actig for very log times. he EOMs i physical space are MU+KUF P cos ( Ωt) Let s assume there is a little dampig; hece, the steady state periodic respose i modal coordiates is (see eq. (33b)): Ad thus, q Q K P Ω ( ) cos ( Ωt) (37a) Q P U U cos( t) P Ω Φq φ cos Ω K ( Ω ) (38) he physical respose is also periodic with same frequecy as the force excitatio. ( t) Recall that K M φ K φ ad Q P φ F P However, owadays the egieer i a hurry prefers to dump the problem ito a super computer; ad for UU P cos( Ωt), fids the solutio U P K Ω M F (39) P at a fixed excitatio frequecy Ω. Brute force substitutes beauty ad elegace, time savigs i lieu of uderstadig! MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 5

16 Example: Fid atural frequecies ad atural mode shapes of UNDAMPED system. Give EOMs for a DOF - udamped- system: ORIGIN : M M d dt X X + K K K K + K X X () K Z where Mmo, M5 mo, Kko; K5 ko m o 5 m o d dt X X + k o k o k o k o + 5 k o X X K Z (a) PROCEDURE O FIND NAURAL FREQUENCIES AND NAURAL MODES: Assume the motios are periodic with frequecy, ie X a cos t X a cos t () Set the RHS of Eq. () equal to. Substitutio of () ito () gives k o m o k o 7 k o k o 5 m o he homogeeous system of eqs a a cos t cacel cos(t) sice it is NO zero for all times has a o-trivial solutio if the determiat of the system of equatios equals zero, i.e. if Δ ( 7 k o 5 m o ) ( k o m o ) 4 k o Let λ k o m o k o 7 k o, ad expadig the products i the determiat k o 5 m o λ 5m o λ 7 k o m o + k o m o + 4 k o 4 k o a a (3) Let m o λ λ k o Leads to: with: a λ a : 5 + b λ + c b : 7 (4) c : he roots (eigevalues) of the characteristic equatio are

17 λ.5.5 b b 4 a c b + b 4 a c : λ a : a λ k o m o ad the atural frequecies are: (b) Explaatio: DOF (X) ad DOF (X) move i phase, with X>X for φ : k o m o ( k o.643 k o ) φ (.643) k o k φ o : : φ φ is the d eigevector (atural mode).3 φ ( λ ).5 Fid the eigevectors: : : λ (b) Explaatio:DOF (X) ad DOF (X) move 8 deg OU of phase, with X > X (c) fid the umerical value for each atural frequecy: lb.5 m o : Sice.87 k o g :.66 m o rad sec f : π 7.7 f Hz m o he two equatios i (3) are liearly depedet. hus, oe caot solve for a ad a. Set φ : arbitrarily; ad from the first equatio for φ ( k o m o ) k o φ : φ φ.6 k o.757 k o k o φ : k o m o φ.6 is the first eigevector (atural mode) k o : 5 lb i Note that mass must be expressed i physical uits cosistet with the problem, i.e. lb sec i.5 (.757)

18 Perform same work usig a calculator M : 5 m o K : 7 k o Use BUIL IN fuctios - Not much learig Let Z : M K λ : sort( eigevals( Z) ) : ( λ ).5 : ( λ ).5 λ rad sec sec π Hz atural modes: φ : eigevec Z, λ φ : eigevec Z, λ.849 φ φ.36 ( φ ).6 φ ( φ ).3 φ which are the same ratios as for the vectors foud earlier

19 Example: Udamped Modal Aalysis m o Mode K m : lb sec K lb M m m 3.95 i i (b) Fid iitial moddal displacemets ad velocities ad modal force vector (Q) At time ts, the system is at RES at its static equilibrium positio, hece the iitial coditios are ull displacemets ad ull velocities. Of course, the same applies to modal space, i.e. ull iitial displacemets ad velocities X for geerality, defie: X o : X ft V ft o : Calculate iverse of A matrix sec ad i modal coordiates q o : Φ iv X o q o_dot : Φ iv V o velocity (disp & velocities) Defie modal force he EOMs i modal space are ucoupled ad equal to where q () t : δ m cos t.8 3 δ m ft (c) Modal EOMs ad modal resposes q o q o_dot Q : Usig the cheat sheet, ad sice the Iitial coditios are ull, the respose i modal coordiates are Φ F i lb : k g o : 5 lb g 3.74 ft i sec ORIGIN : Equatios of motio: atural frequecies, modal matrix (eigevectors) m o 5m o d dt Defie matrices: M M X X + M : k o k o m o k o 7k o X X (a) FIND modal masses ad stiffesses modal masses ad stiffesses: 5m o lb sec i K : k o k o k o Z k o 7k o Mode Q 6 3 d M mi q i d t lb Q δ m : K m 7.95 : Φ : 39.5 sec ft sec q () t : δ m cos t rad + K mi q Q i i Q δ m : K m Φ iv : Φ No eed for actual calculatio - a kowledge statemet suffices Both atural modes will be excited i,.6 where: are the "static" deflectios i modal space. δ << δ, thus first modal respose is MORE importat.3 give: Z o :. i provides a F o : k o Z o costat force M M : Φ M Φ F : M m : M m : lb F o K M : Φ K Φ M M, M M, at ts, Iitial coditios: system is at RES o-diagoal elemets are very small o zero b/c of roudoff i umerical calculator K m : MM, MM, rad sec

20 (d) he respose i physical coordiates, X ad X, equals (from trasformatio xaq) with X () t : q () t + q () t Φ X () t δ m cos t + δ m cos t Ad equatios of motio reduce to: k o k o X d dt X ; hece > K k o 7k o X ed X ed F o X ed X ed F F o 3 lb.6 X ( t) :.6 q () t.3 q () t for graph below: X () t δ m.6 cos t + δ m (.3) cos t large : δ m i δ m (.3).57 4 i.3 Explaatio: Sice q ad q are o-zero, the physical motio, X &X, shows excitatio of the WO fudametal modes of vibratio - BU respose for secod mode is much less GRAPHs ot eeded for exam: displacemets (ich) time (sec) X X termial value Note that there is o dampig or atteuatio of motios. π Not too complicated physical respose. It shows domiace of first mode (lowest atural freq or largest period) π π.37 sec. sec ermial coditio: If dampig is preset ad sice the applied force is a costat, the system will achieve a ew steady state coditio. I the limit as t approaches very, very large values Ad solvig this system of equatios usig Cramer's rule F o k o k o F o X ed : X ed : Δ Δ Δ : 4 k o 4k o determiat of system of eqs. X ed 3 i X ed 3 i Note that the graph of udamped periodic motios Z(t) ad X(t) shows oscillatory motios abut these termial or ed values. OR K F 3 3 i recall Z o. i Z o 5 X ed

21 COMPARE actual respose with a respose eglectig q. Ideed mode does ot afffect the physical respose, except for motio X sligthly displacemets (ich) X X termial time (sec)

22 Normalizatio of eigevectors (atural modes) Recall that the compoets of a eigevector φ are ARBIRARY but for a multiplicative costat. If oe of the elemets of the eigevector is assiged a certai value, the this vector becomes uique, sice the - remaiig elemets are automatically adusted to keep costat the ratio betwee ay two elemets i the vector. I practice, the eigevectors are ormalized. he resultig vectors are called NORMAL MODES. Some typical NORMS are L orm: max( q ) q (39a) k L orm: q q q q (39b) Or makig the mass modal matrix equal to the idetity matrix, [M]I, i.e. hece φ Mφ (39c) M φ K φ K M (39d) his ormalizatio has obvious advatages sice it will reduce the umber of operatios whe coductig the modal aalysis. However, the physical sigificace of the modal equatios is lost. Note that the modal Eqs. (6) become: MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 6

23 q + q Q Your lecturer recommeds this ormalizatio procedure be coducted oly for systems with large umber of degrees of freedom, >>>. Note that the ormalizatio process is a mere coveiece, devoid of ay physical sigificace. Rayleigh s Eergy Method he method is a procedure to determie a approximate value (from above) for the fudametal atural frequecy of a MDOF system. At times, the full solutio of the eigevalue problem is of NO particular iterest ad a estimate of the system lowest atural frequecy suffices. Recall that the pairs { i, () i } φ satisfy Kφ M φ i,... with properties Φ M Φ [ M ]; Φ K Φ [ K ] () i i () i i.e. with modal stiffess ad masses calculated from: K K () (); () (), ad i i φ i Kφ i Mi φ i Mφ i i (4) M i hat is, K () i () i i i φ Kφ M i φ() i Mφ() i (4) Above, the umerator relates to the potetial or strai eergy of the system for the i-mode, ad the deomiator to the kietic eergy for the same mode. MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 7

24 Cosider a arbitrary vector u ad defie Rayleigh s quotiet R(u) as R ( u) uku umu (43) R( u ) is a scalar whose value depeds ot oly o the matrices M & K, but also o the choice of the vector u. Clearly, if the arbitrary vector u coicides with (or is a multiple of) oe of the atural mode vectors, the Rayleigh s quotiet will deliver the exact atural frequecy for that particular mode. It ca also be show that the quotiet has a statioary value, i.e. a miimum, i the eighborhood of the system atural modes (eigevectors). o show this, sice u is a arbitrary vector ad the atural modes are a set of liearly idepedet vectors, the oe ca represet Where { } u φc Φc (44) c c c.. c is the vector of coefficiets i the expasio. Substitutio of the expressio above ito Rayleigh s quotiet gives ( Φc) K( Φc) ( Φc) M( Φc) R ( u) c Φ KΦ c c Φ MΦ c [ K ] [ M ] R( u) c c c c (45) MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 8

25 Assume the modes have bee ormalized with respect to the mass matrix, i.e. ci i c i cic ci i c R( u) (46a) Next, cosider that the arbitrary vector u (which at this time ca be regarded as a assumed mode vector) differs very little from the atural mode (eigevector) φ ( r). his meas that i the expasio of vector u, the coefficiets c << c ; for i,,... adi r Or c ς c ; ς << for i,,... adi r i i r i he, Rayleigh s quotiet is expressed as i r R( u ) c r + c r r ς i i i, i r cr + cr ς i i, i r ς i i + ςi + i, i r i, i r r + ςi + ςi i, i r i, i r r i r R( u ) (46b) he quatities { ς i } are small, of secod order, hece R(u) differs from the atural frequecy by a small quatity of secod order. MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 9

26 his implies that R(u)has a statioary value i the viciity of the modal vector φ ( r). he most importat property of Rayleigh s quotiet is that it shows a miimum value i the eighborhood of the fudametal mode, i.e. whe r. R ς i + i u (47) i, sice i > + ς i i he each term i the umerator is greater tha the correspodig oe i the deomiator. Hece, it follows that R u (48) i.e., Rayleigh s quotiet provides a upper boud to the first (lowest) atural frequecy of the udamped MDOF system. Clearly, the equality holds above if oe selects u c φ (); c. Closure Rayleigh s eergy method is geerally used whe oe is iterested i a quick (but particularly accurate) estimate of the fudametal atural frequecy of a cotiuous system, ad for which a solutio to the whole eigevalue problem caot be readily obtaied. he method is based o the fact that the atural frequecies have statioary values i the eighborhood of the atural modes. I additio, Rayleigh s quotiet provides a upper boud to the first (lowest) atural frequecy. he egieerig value of this approximatio ca hardly be overstated. Rayleigh s eergy method is the basis for the umerical computig of eigevectors ad eigevalues as will be see later. MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8

27 N 5 umber of DOFS mass stiff 3 M idetity( N) mass Example for estimatio of first atural frequecy ORIGIN d M U d t KU K stiff K U M K U M K U3 M K U4 M K U5 M K

28 Estimate for first atural frequecy - Use Rayleigh-Ritz method: ASSUME u ( ) calculate Rayleigh's quotiet Ru u Ku u Mu _ap Ru _ap 6.93 Estimate Actual rad/s % differece _ap M u (approx)

29 Estimate for secod atural frequecy - Use Rayleigh-Ritz method: ASSUME u ( ) calculate Rayleigh's quotiet Ru u Ku u Mu _ap Ru _ap 3.63 Estimate Actual 3.63 rad/s % differece _ap M u (approx)

30 N 5 umber of DOFS mass stiff 3 M idetity( N) mass Example for estimatio of first atural frequecy ORIGIN d M U d t KU K stiff K U M K U M K U3 M K U4 M K U5 M

31 Estimate for first atural frequecy - Use Rayleigh-Ritz method: ASSUME u ( ) calculate Rayleigh's quotiet Ru u Ku u Mu _ap Ru _ap.935 Estimate Actual 9. rad/s % differece _ap M u (approx)

32 Mode Acceleratio Method Recall that the respose i physical coordiates is m U φ q, m< (36) () t ( t ) where m<. he procedure is kow as the mode displacemet method. his method, however, fails to give a accurate solutio eve whe a static load is applied (See Structural Dyamics, by R. Craig, J. Wiley Pubs, NY, 98.). he difficulty is overcome by usig the procedure detailed below. Recall that the system motio is govered by the set of equatios (4) MU+KU F () t () t Ad, if there are o rigid body modes, i.e. all atural frequecies are greater tha zero, the U K F MU (5) () t () t where K is a flexibility matrix. From Eq. (36), m U φ q, m< (5) ( t ) Hece, Eq, (5) ca be writte as MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8

33 m () t () t q U K F K M φ (53) ( t ) Usig the fudametal idetity, Kφ Mφ φ K Mφ Write Eq. (53) as () i i () i () i () i i m U() t K F() t φ q ( t ) (54) Note that US K F () t (55) is the displacemet respose vector due to a pseudo-static force F(t), i.e. without the system iertia accouted for. Hece write Eq. (54), as m () t s() t φ q U U ( t ) ; m< (56) he secod term above ca be thought as the iertia iduced respose. Example: Cosider the case of force excitatio with frequecy Ω ad actig for very log times. he EOMs i physical space are: MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8

34 MU+KUF P cos ( Ωt) With a little dampig, the steady state periodic respose i modal coordiates is q Q K P Ω ( ) cos ( Ωt) Recall that, usig the mode displacemet method, the respose i physical coordiates is: (37a) m QP U φ cos ( Ωt ) K (38) ( Ω ) From each of the modal resposes, Q P q ( Ω ) cos ( Ωt) ; K ( Ω ) q QP Ω cos K ( Ω ) ( Ωt) (57) Sice K respose is M ; the usig the mode acceleratio method, the m Q P Ω U U SP + φ cos ( Ωt) K (58 ( Ω ) ) MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 3

35 U K F. Now, i the where the pseudo-static respose is SP P limit, as the excitatio frequecy decreases, i.e., as Ω, the secod term i Eq. (58) above disappears, ad hece the physical respose becomes: U USP K F P (59) which is the exact respose, regardless of the umber of modes chose. Hece, the mode acceleratio method is more accurate tha the mode displacemet method. Kow disadvatages iclude more operatios. Fidig the flexibility matrix is, i actuality, desirable. I particular, if derived from measuremets, the flexibility matrix is easier to determie tha the stiffess matrix. MEEN 67 HD#7 Udamped Modal Aalysis of MDOF systems. L. Sa Adrés 8 4

36 SEP FORCED RESPONSE of Udamped -DOF mechaical system ORIGIN : Dr. Luis Sa Adres (c) MEEN 363, 67 February 8 he udamped equatios of motio are: d M dt X + KX F o () where M,K are matrices of iertia ad stiffess coefficiets, ad X, VdX/dt, d X/dt are the vectors of physical displacemet, velocity ad acceleratio, respectively. he FORCED udamped respose to the iitial coditios, at t, Xo,VodX/dt, follows: he equatios of motio are: M M M M d dt x x + K K K K x x F o F o (). Set elemets of iertia ad stiffess matrices DAA FOR problem M : K : 5 Note M ad K kg 6 6 are symmetric matrices 6 6 N m : # of DOF iitial coditios Applied force vector: m. X o : V o : F o : 5 N m sec. Fid eigevalues (udamped atural frequecies) ad eigevectors Set determiat of system of eqs ( K M ) ( K M ) Δ K M K M (a) Δ a 4 + b + c a λ + b λ + c with λ (b) where the coefficiets are: a : M, M, M, M, b : K, M, K, M, K, M, + K, M, c : K, K, K, K, (c)

37 he roots of equatio (b) are: λ :.5 b b 4 a c a λ :.5 b + b 4 a c a (3) also kow as eigevalues. he atural frequecies follow as: Note that: :.. Δ( ) Δ : ( λ ).5 f : π f rad sec Hz (4) For each eigevalue, the eigevectors (atural modes) are :.. a : MODAL matrix A : a K, M, λ ( K ), M, λ Set arbitrarily first elemet of vector a.73 a.73 A is the matrix of eigevectors (udamped modal matrix): each colum correspods to a eigevector A.73 (5).73 Plot the mode shapes: A, A, DOF mode mode

38 3. Modal trasformatio of physical equatios to (atural) modal coordiates Usig trasformatio: X A q EOMs () become ucoupled i modal space: d M m q dt + K m q Q m (6) (7) with modal force vector: Q m A F o (8) ad iitial coditios (modal displacemetq ad modal velocity dq/dts) q o M m A M X o s o M m A M V o (9) he modal resposes are of the form: k... OR q k q ok cos k t + q k q ok + s ok t + s ok k si ( k t) Q mk t M mk, k + Q mk ( cos ( K k t) ) mk, k for a elastic mode k for k for a rigid body mode (a) (b) Ad, the respose i the physical coordiates is give by the superpositio of the modal resposes, i.e. X() t Aqt () CHECK Verify the orthogoality properties of the atural mode shapes M m A 6.79 : M A M m.58 4 K m : A K A.6 6 K m (5) N m kg s -

39 4. Fid Modal ad Physical Respose for give iitial coditio ad Costat Force vector Recall the vectors of iitial coditios X o m V o m s ad Costat forces: 4.a Fid iitial coditios i modal coordiates (displacemet q, velocity s) Set iverse of modal mass matrix 4 F o 5 3 m N m A iv : M m DAA FOR problem beig aalyzed: ( A M) q o : A iv X o s o : A iv V o q o 4.b Fid Modal forces: m s o ms- Q m : A F o Q m.37 4 N 4.c Build Modal resposes: q () t : q o cos t + s o si ( t) + Q m K m ( ) cos t, q () t : q o cos t + s o si ( t) + Q m K m ( ) cos t, 4.d Build Physical resposes: X() t : a q () t + a q () t for plots: 6 plot : f 4.e Graphs of Modal ad Physical resposes:. Respose i modal coordiates

40 q q time (s). Respose i physical coordiates x x time (s) 5. Iterpret respose: aalyze results, provide recommedatios Recall atural frequecies & periods S-S displacemet K F o 5 3 m f Hz f s s A.73.73

41 SEP FORCED RESPONSE of Udamped -DOF mechaical system ORIGIN : Dr. Luis Sa Adres (c) MEEN 363, 67 February 8 he udamped equatios of motio are: d M dt X + KX F o () where M,K are matrices of iertia ad stiffess coefficiets, ad X, VdX/dt, d X/dt are the vectors of physical displacemet, velocity ad acceleratio, respectively. he FORCED udamped respose to the iitial coditios, at t, Xo,VodX/dt, follows: he equatios of motio are: M M M M d dt x x + K K K K x x F o F o WIH RIGID BODY MODE (). Set elemets of iertia ad stiffess matrices DAA FOR problem Note M : K : 5 M ad K kg 6 6 are symmetric matrices 6 6 N m : # of DOF iitial coditios Applied force vector: m. X o : V o : F o : 98 N m sec. Fid eigevalues (udamped atural frequecies) ad eigevectors Set determiat of system of eqs ( K M ) ( K M ) Δ K M K M (a) Δ a 4 + b + c a λ + b λ + c with λ (b) where the coefficiets are: a : M, M, M, M, b : K, M, K, M, K, M, + K, M, c : K, K, K, K, (c)

42 ,,,, he roots of equatio (b) are: λ :.5 b b 4 a c a λ :.5 b + b 4 a c a (3) also kow as eigevalues. he atural frequecies follow as: Note that: :.. Δ( ) Δ : ( λ ).5 f : π f rad sec Hz (4) For each eigevalue, the eigevectors (atural modes) are :.. a : MODAL matrix A : a K, M, λ ( K ), M, λ Set arbitrarily first elemet of vector a a A is the matrix of eigevectors (udamped modal matrix): each colum correspods to a eigevector A (5) Plot the mode shapes: A, A, DOF mode mode 3. Modal trasformatio of physical equatios to (atural) modal coordiates Usig trasformatio: X A (6)

43 Usig trasformatio: X A q EOMs () become ucoupled i modal space: d M m q dt + K m q Q m (6) (7) with modal force vector: Q m A F o (8) ad iitial coditios (modal displacemetq ad modal velocity dq/dts) q o M m A M X o s o M m A M V o (9) he modal resposes are of the form: k... OR q k q ok cos k t + q k q ok + s ok t + s ok k si ( k t) Q mk t M mk, k + Q mk ( cos ( k t) ) K mk, k for a elastic mode for k k for a rigid body mode (a) (b) Ad, the respose i the physical coordiates is give by the superpositio of the modal resposes, i.e. X() t Aqt () CHECK Verify the orthogoality properties of the atural mode shapes (5) M m A 5 : M A M m 3 kg K m : A K A N m K m s- 4. Fid Modal ad Physical Respose for give iitial coditio ad Costat Force vector Recall the vectors of iitial coditios X o m Vo m s d C t t f

44 q o : ad Costat forces: 4.a Fid iitial coditios i modal coordiates (displacemet q, velocity s) Set iverse of modal mass matrix A iv X o s o : 3 F o 98 A iv V o m N m A iv : M m DAA FOR problem beig aalyzed: ( A M).67 A iv b Fid Modal forces: q o m s o ms- Q m : A F o Q m.96 3 N 4.c Build Modal resposes: q () t : q o + s o t + Q m t respose for rigid body mode M m, q () t : q o cos t + s o si ( t) + Q m K m ( ) cos t, 4.d Build Physical resposes: X() t : a q () t + a q () t for plots: 6 plot : f 4.e Graphs of Modal ad Physical resposes:.4 Respose i modal coordiates time (s)

45 q q time (s) Respose i physical coordiates x x time (s) 5. Iterpret respose: aalyze results, provide recommedatios S-S displacemet - NONE Recall atural frequecies & periods f Hz A s -

Problem 1. Problem Engineering Dynamics Problem Set 9--Solution. Find the equation of motion for the system shown with respect to:

Problem 1. Problem Engineering Dynamics Problem Set 9--Solution. Find the equation of motion for the system shown with respect to: 2.003 Egieerig Dyamics Problem Set 9--Solutio Problem 1 Fid the equatio of motio for the system show with respect to: a) Zero sprig force positio. Draw the appropriate free body diagram. b) Static equilibrium

More information

CHAPTER 5. Theory and Solution Using Matrix Techniques

CHAPTER 5. Theory and Solution Using Matrix Techniques A SERIES OF CLASS NOTES FOR 2005-2006 TO INTRODUCE LINEAR AND NONLINEAR PROBLEMS TO ENGINEERS, SCIENTISTS, AND APPLIED MATHEMATICIANS DE CLASS NOTES 3 A COLLECTION OF HANDOUTS ON SYSTEMS OF ORDINARY DIFFERENTIAL

More information

Principle Of Superposition

Principle Of Superposition ecture 5: PREIMINRY CONCEP O RUCUR NYI Priciple Of uperpositio Mathematically, the priciple of superpositio is stated as ( a ) G( a ) G( ) G a a or for a liear structural system, the respose at a give

More information

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j.

Apply change-of-basis formula to rewrite x as a linear combination of eigenvectors v j. Eigevalue-Eigevector Istructor: Nam Su Wag eigemcd Ay vector i real Euclidea space of dimesio ca be uiquely epressed as a liear combiatio of liearly idepedet vectors (ie, basis) g j, j,,, α g α g α g α

More information

2C09 Design for seismic and climate changes

2C09 Design for seismic and climate changes 2C09 Desig for seismic ad climate chages Lecture 02: Dyamic respose of sigle-degree-of-freedom systems I Daiel Grecea, Politehica Uiversity of Timisoara 10/03/2014 Europea Erasmus Mudus Master Course Sustaiable

More information

Dynamic Response of Second Order Mechanical Systems with Viscous Dissipation forces

Dynamic Response of Second Order Mechanical Systems with Viscous Dissipation forces Hadout #b (pp. 4-55) Dyamic Respose o Secod Order Mechaical Systems with Viscous Dissipatio orces M X + DX + K X = F t () Periodic Forced Respose to F (t) = F o si( t) ad F (t) = M u si(t) Frequecy Respose

More information

CALCULATION OF STIFFNESS AND MASS ORTHOGONAL VECTORS

CALCULATION OF STIFFNESS AND MASS ORTHOGONAL VECTORS 14. CALCULATION OF STIFFNESS AND MASS ORTHOGONAL VECTORS LDR Vectors are Always More Accurate tha Usig the Exact Eigevectors i a Mode Superpositio Aalysis 14.1 INTRODUCTION The major reaso to calculate

More information

Chapter Vectors

Chapter Vectors Chapter 4. Vectors fter readig this chapter you should be able to:. defie a vector. add ad subtract vectors. fid liear combiatios of vectors ad their relatioship to a set of equatios 4. explai what it

More information

Physics 324, Fall Dirac Notation. These notes were produced by David Kaplan for Phys. 324 in Autumn 2001.

Physics 324, Fall Dirac Notation. These notes were produced by David Kaplan for Phys. 324 in Autumn 2001. Physics 324, Fall 2002 Dirac Notatio These otes were produced by David Kapla for Phys. 324 i Autum 2001. 1 Vectors 1.1 Ier product Recall from liear algebra: we ca represet a vector V as a colum vector;

More information

Stochastic Matrices in a Finite Field

Stochastic Matrices in a Finite Field Stochastic Matrices i a Fiite Field Abstract: I this project we will explore the properties of stochastic matrices i both the real ad the fiite fields. We first explore what properties 2 2 stochastic matrices

More information

3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense,

3. Z Transform. Recall that the Fourier transform (FT) of a DT signal xn [ ] is ( ) [ ] = In order for the FT to exist in the finite magnitude sense, 3. Z Trasform Referece: Etire Chapter 3 of text. Recall that the Fourier trasform (FT) of a DT sigal x [ ] is ω ( ) [ ] X e = j jω k = xe I order for the FT to exist i the fiite magitude sese, S = x [

More information

Inverse Matrix. A meaning that matrix B is an inverse of matrix A.

Inverse Matrix. A meaning that matrix B is an inverse of matrix A. Iverse Matrix Two square matrices A ad B of dimesios are called iverses to oe aother if the followig holds, AB BA I (11) The otio is dual but we ofte write 1 B A meaig that matrix B is a iverse of matrix

More information

Signal Processing in Mechatronics

Signal Processing in Mechatronics Sigal Processig i Mechatroics Zhu K.P. AIS, UM. Lecture, Brief itroductio to Sigals ad Systems, Review of Liear Algebra ad Sigal Processig Related Mathematics . Brief Itroductio to Sigals What is sigal

More information

1 1 2 = show that: over variables x and y. [2 marks] Write down necessary conditions involving first and second-order partial derivatives for ( x0, y

1 1 2 = show that: over variables x and y. [2 marks] Write down necessary conditions involving first and second-order partial derivatives for ( x0, y Questio (a) A square matrix A= A is called positive defiite if the quadratic form waw > 0 for every o-zero vector w [Note: Here (.) deotes the traspose of a matrix or a vector]. Let 0 A = 0 = show that:

More information

Load Dependent Ritz Vector Algorithm and Error Analysis

Load Dependent Ritz Vector Algorithm and Error Analysis Load Depedet Ritz Vector Algorithm ad Error Aalysis Writte by Ed Wilso i 006. he Complete eigealue subspace I the aalysis of structures subected to three base acceleratios there is a requiremet that oe

More information

SNAP Centre Workshop. Basic Algebraic Manipulation

SNAP Centre Workshop. Basic Algebraic Manipulation SNAP Cetre Workshop Basic Algebraic Maipulatio 8 Simplifyig Algebraic Expressios Whe a expressio is writte i the most compact maer possible, it is cosidered to be simplified. Not Simplified: x(x + 4x)

More information

mx bx kx F t. dt IR I LI V t, Q LQ RQ V t,

mx bx kx F t. dt IR I LI V t, Q LQ RQ V t, Lecture 5 omplex Variables II (Applicatios i Physics) (See hapter i Boas) To see why complex variables are so useful cosider first the (liear) mechaics of a sigle particle described by Newto s equatio

More information

5.1. The Rayleigh s quotient. Definition 49. Let A = A be a self-adjoint matrix. quotient is the function. R(x) = x,ax, for x = 0.

5.1. The Rayleigh s quotient. Definition 49. Let A = A be a self-adjoint matrix. quotient is the function. R(x) = x,ax, for x = 0. 40 RODICA D. COSTIN 5. The Rayleigh s priciple ad the i priciple for the eigevalues of a self-adjoit matrix Eigevalues of self-adjoit matrices are easy to calculate. This sectio shows how this is doe usig

More information

, then cv V. Differential Equations Elements of Lineaer Algebra Name: Consider the differential equation. and y2 cos( kx)

, then cv V. Differential Equations Elements of Lineaer Algebra Name: Consider the differential equation. and y2 cos( kx) Cosider the differetial equatio y '' k y 0 has particular solutios y1 si( kx) ad y cos( kx) I geeral, ay liear combiatio of y1 ad y, cy 1 1 cy where c1, c is also a solutio to the equatio above The reaso

More information

MATH10212 Linear Algebra B Proof Problems

MATH10212 Linear Algebra B Proof Problems MATH22 Liear Algebra Proof Problems 5 Jue 26 Each problem requests a proof of a simple statemet Problems placed lower i the list may use the results of previous oes Matrices ermiats If a b R the matrix

More information

EXPERIMENT OF SIMPLE VIBRATION

EXPERIMENT OF SIMPLE VIBRATION EXPERIMENT OF SIMPLE VIBRATION. PURPOSE The purpose of the experimet is to show free vibratio ad damped vibratio o a system havig oe degree of freedom ad to ivestigate the relatioship betwee the basic

More information

U8L1: Sec Equations of Lines in R 2

U8L1: Sec Equations of Lines in R 2 MCVU U8L: Sec. 8.9. Equatios of Lies i R Review of Equatios of a Straight Lie (-D) Cosider the lie passig through A (-,) with slope, as show i the diagram below. I poit slope form, the equatio of the lie

More information

Chimica Inorganica 3

Chimica Inorganica 3 himica Iorgaica Irreducible Represetatios ad haracter Tables Rather tha usig geometrical operatios, it is ofte much more coveiet to employ a ew set of group elemets which are matrices ad to make the rule

More information

5.74 TIME-DEPENDENT QUANTUM MECHANICS

5.74 TIME-DEPENDENT QUANTUM MECHANICS p. 1 5.74 TIME-DEPENDENT QUANTUM MECHANICS The time evolutio of the state of a system is described by the time-depedet Schrödiger equatio (TDSE): i t ψ( r, t)= H ˆ ψ( r, t) Most of what you have previously

More information

Time-Domain Representations of LTI Systems

Time-Domain Representations of LTI Systems 2.1 Itroductio Objectives: 1. Impulse resposes of LTI systems 2. Liear costat-coefficiets differetial or differece equatios of LTI systems 3. Bloc diagram represetatios of LTI systems 4. State-variable

More information

1 Last time: similar and diagonalizable matrices

1 Last time: similar and diagonalizable matrices Last time: similar ad diagoalizable matrices Let be a positive iteger Suppose A is a matrix, v R, ad λ R Recall that v a eigevector for A with eigevalue λ if v ad Av λv, or equivaletly if v is a ozero

More information

Assignment 2 Solutions SOLUTION. ϕ 1 Â = 3 ϕ 1 4i ϕ 2. The other case can be dealt with in a similar way. { ϕ 2 Â} χ = { 4i ϕ 1 3 ϕ 2 } χ.

Assignment 2 Solutions SOLUTION. ϕ 1  = 3 ϕ 1 4i ϕ 2. The other case can be dealt with in a similar way. { ϕ 2 Â} χ = { 4i ϕ 1 3 ϕ 2 } χ. PHYSICS 34 QUANTUM PHYSICS II (25) Assigmet 2 Solutios 1. With respect to a pair of orthoormal vectors ϕ 1 ad ϕ 2 that spa the Hilbert space H of a certai system, the operator  is defied by its actio

More information

Matrix Algebra from a Statistician s Perspective BIOS 524/ Scalar multiple: ka

Matrix Algebra from a Statistician s Perspective BIOS 524/ Scalar multiple: ka Matrix Algebra from a Statisticia s Perspective BIOS 524/546. Matrices... Basic Termiology a a A = ( aij ) deotes a m matrix of values. Whe =, this is a am a m colum vector. Whe m= this is a row vector..2.

More information

(3) If you replace row i of A by its sum with a multiple of another row, then the determinant is unchanged! Expand across the i th row:

(3) If you replace row i of A by its sum with a multiple of another row, then the determinant is unchanged! Expand across the i th row: Math 5-4 Tue Feb 4 Cotiue with sectio 36 Determiats The effective way to compute determiats for larger-sized matrices without lots of zeroes is to ot use the defiitio, but rather to use the followig facts,

More information

Polynomials with Rational Roots that Differ by a Non-zero Constant. Generalities

Polynomials with Rational Roots that Differ by a Non-zero Constant. Generalities Polyomials with Ratioal Roots that Differ by a No-zero Costat Philip Gibbs The problem of fidig two polyomials P(x) ad Q(x) of a give degree i a sigle variable x that have all ratioal roots ad differ by

More information

Appendix: The Laplace Transform

Appendix: The Laplace Transform Appedix: The Laplace Trasform The Laplace trasform is a powerful method that ca be used to solve differetial equatio, ad other mathematical problems. Its stregth lies i the fact that it allows the trasformatio

More information

Math 5311 Problem Set #5 Solutions

Math 5311 Problem Set #5 Solutions Math 5311 Problem Set #5 Solutios March 9, 009 Problem 1 O&S 11.1.3 Part (a) Solve with boudary coditios u = 1 0 x < L/ 1 L/ < x L u (0) = u (L) = 0. Let s refer to [0, L/) as regio 1 ad (L/, L] as regio.

More information

Notes The Incremental Motion Model:

Notes The Incremental Motion Model: The Icremetal Motio Model: The Jacobia Matrix I the forward kiematics model, we saw that it was possible to relate joit agles θ, to the cofiguratio of the robot ed effector T I this sectio, we will see

More information

Lesson 10: Limits and Continuity

Lesson 10: Limits and Continuity www.scimsacademy.com Lesso 10: Limits ad Cotiuity SCIMS Academy 1 Limit of a fuctio The cocept of limit of a fuctio is cetral to all other cocepts i calculus (like cotiuity, derivative, defiite itegrals

More information

Determinants of order 2 and 3 were defined in Chapter 2 by the formulae (5.1)

Determinants of order 2 and 3 were defined in Chapter 2 by the formulae (5.1) 5. Determiats 5.. Itroductio 5.2. Motivatio for the Choice of Axioms for a Determiat Fuctios 5.3. A Set of Axioms for a Determiat Fuctio 5.4. The Determiat of a Diagoal Matrix 5.5. The Determiat of a Upper

More information

Linear regression. Daniel Hsu (COMS 4771) (y i x T i β)2 2πσ. 2 2σ 2. 1 n. (x T i β y i ) 2. 1 ˆβ arg min. β R n d

Linear regression. Daniel Hsu (COMS 4771) (y i x T i β)2 2πσ. 2 2σ 2. 1 n. (x T i β y i ) 2. 1 ˆβ arg min. β R n d Liear regressio Daiel Hsu (COMS 477) Maximum likelihood estimatio Oe of the simplest liear regressio models is the followig: (X, Y ),..., (X, Y ), (X, Y ) are iid radom pairs takig values i R d R, ad Y

More information

State Space Representation

State Space Representation Optimal Cotrol, Guidace ad Estimatio Lecture 2 Overview of SS Approach ad Matrix heory Prof. Radhakat Padhi Dept. of Aerospace Egieerig Idia Istitute of Sciece - Bagalore State Space Represetatio Prof.

More information

The time evolution of the state of a quantum system is described by the time-dependent Schrödinger equation (TDSE): ( ) ( ) 2m "2 + V ( r,t) (1.

The time evolution of the state of a quantum system is described by the time-dependent Schrödinger equation (TDSE): ( ) ( ) 2m 2 + V ( r,t) (1. Adrei Tokmakoff, MIT Departmet of Chemistry, 2/13/2007 1-1 574 TIME-DEPENDENT QUANTUM MECHANICS 1 INTRODUCTION 11 Time-evolutio for time-idepedet Hamiltoias The time evolutio of the state of a quatum system

More information

Machine Learning for Data Science (CS 4786)

Machine Learning for Data Science (CS 4786) Machie Learig for Data Sciece CS 4786) Lecture & 3: Pricipal Compoet Aalysis The text i black outlies high level ideas. The text i blue provides simple mathematical details to derive or get to the algorithm

More information

Chapter 7: The z-transform. Chih-Wei Liu

Chapter 7: The z-transform. Chih-Wei Liu Chapter 7: The -Trasform Chih-Wei Liu Outlie Itroductio The -Trasform Properties of the Regio of Covergece Properties of the -Trasform Iversio of the -Trasform The Trasfer Fuctio Causality ad Stability

More information

6.3 Testing Series With Positive Terms

6.3 Testing Series With Positive Terms 6.3. TESTING SERIES WITH POSITIVE TERMS 307 6.3 Testig Series With Positive Terms 6.3. Review of what is kow up to ow I theory, testig a series a i for covergece amouts to fidig the i= sequece of partial

More information

1. Linearization of a nonlinear system given in the form of a system of ordinary differential equations

1. Linearization of a nonlinear system given in the form of a system of ordinary differential equations . Liearizatio of a oliear system give i the form of a system of ordiary differetial equatios We ow show how to determie a liear model which approximates the behavior of a time-ivariat oliear system i a

More information

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j

The z-transform. 7.1 Introduction. 7.2 The z-transform Derivation of the z-transform: x[n] = z n LTI system, h[n] z = re j The -Trasform 7. Itroductio Geeralie the complex siusoidal represetatio offered by DTFT to a represetatio of complex expoetial sigals. Obtai more geeral characteristics for discrete-time LTI systems. 7.

More information

Linear Differential Equations of Higher Order Basic Theory: Initial-Value Problems d y d y dy

Linear Differential Equations of Higher Order Basic Theory: Initial-Value Problems d y d y dy Liear Differetial Equatios of Higher Order Basic Theory: Iitial-Value Problems d y d y dy Solve: a( ) + a ( )... a ( ) a0( ) y g( ) + + + = d d d ( ) Subject to: y( 0) = y0, y ( 0) = y,..., y ( 0) = y

More information

TMA4205 Numerical Linear Algebra. The Poisson problem in R 2 : diagonalization methods

TMA4205 Numerical Linear Algebra. The Poisson problem in R 2 : diagonalization methods TMA4205 Numerical Liear Algebra The Poisso problem i R 2 : diagoalizatio methods September 3, 2007 c Eiar M Røquist Departmet of Mathematical Scieces NTNU, N-749 Trodheim, Norway All rights reserved A

More information

Kinetics of Complex Reactions

Kinetics of Complex Reactions Kietics of Complex Reactios by Flick Colema Departmet of Chemistry Wellesley College Wellesley MA 28 wcolema@wellesley.edu Copyright Flick Colema 996. All rights reserved. You are welcome to use this documet

More information

10-701/ Machine Learning Mid-term Exam Solution

10-701/ Machine Learning Mid-term Exam Solution 0-70/5-78 Machie Learig Mid-term Exam Solutio Your Name: Your Adrew ID: True or False (Give oe setece explaatio) (20%). (F) For a cotiuous radom variable x ad its probability distributio fuctio p(x), it

More information

DETERMINATION OF MECHANICAL PROPERTIES OF A NON- UNIFORM BEAM USING THE MEASUREMENT OF THE EXCITED LONGITUDINAL ELASTIC VIBRATIONS.

DETERMINATION OF MECHANICAL PROPERTIES OF A NON- UNIFORM BEAM USING THE MEASUREMENT OF THE EXCITED LONGITUDINAL ELASTIC VIBRATIONS. ICSV4 Cairs Australia 9- July 7 DTRMINATION OF MCHANICAL PROPRTIS OF A NON- UNIFORM BAM USING TH MASURMNT OF TH XCITD LONGITUDINAL LASTIC VIBRATIONS Pavel Aokhi ad Vladimir Gordo Departmet of the mathematics

More information

Numerical Methods in Fourier Series Applications

Numerical Methods in Fourier Series Applications Numerical Methods i Fourier Series Applicatios Recall that the basic relatios i usig the Trigoometric Fourier Series represetatio were give by f ( x) a o ( a x cos b x si ) () where the Fourier coefficiets

More information

September 2012 C1 Note. C1 Notes (Edexcel) Copyright - For AS, A2 notes and IGCSE / GCSE worksheets 1

September 2012 C1 Note. C1 Notes (Edexcel) Copyright   - For AS, A2 notes and IGCSE / GCSE worksheets 1 September 0 s (Edecel) Copyright www.pgmaths.co.uk - For AS, A otes ad IGCSE / GCSE worksheets September 0 Copyright www.pgmaths.co.uk - For AS, A otes ad IGCSE / GCSE worksheets September 0 Copyright

More information

Matrices and vectors

Matrices and vectors Oe Matrices ad vectors This book takes for grated that readers have some previous kowledge of the calculus of real fuctios of oe real variable It would be helpful to also have some kowledge of liear algebra

More information

Mechatronics. Time Response & Frequency Response 2 nd -Order Dynamic System 2-Pole, Low-Pass, Active Filter

Mechatronics. Time Response & Frequency Response 2 nd -Order Dynamic System 2-Pole, Low-Pass, Active Filter Time Respose & Frequecy Respose d -Order Dyamic System -Pole, Low-Pass, Active Filter R 4 R 7 C 5 e i R 1 C R 3 - + R 6 - + e out Assigmet: Perform a Complete Dyamic System Ivestigatio of the Two-Pole,

More information

PAPER : IIT-JAM 2010

PAPER : IIT-JAM 2010 MATHEMATICS-MA (CODE A) Q.-Q.5: Oly oe optio is correct for each questio. Each questio carries (+6) marks for correct aswer ad ( ) marks for icorrect aswer.. Which of the followig coditios does NOT esure

More information

Chapter 4. Fourier Series

Chapter 4. Fourier Series Chapter 4. Fourier Series At this poit we are ready to ow cosider the caoical equatios. Cosider, for eample the heat equatio u t = u, < (4.) subject to u(, ) = si, u(, t) = u(, t) =. (4.) Here,

More information

Matrix Algebra 2.2 THE INVERSE OF A MATRIX Pearson Education, Inc.

Matrix Algebra 2.2 THE INVERSE OF A MATRIX Pearson Education, Inc. 2 Matrix Algebra 2.2 THE INVERSE OF A MATRIX MATRIX OPERATIONS A matrix A is said to be ivertible if there is a matrix C such that CA = I ad AC = I where, the idetity matrix. I = I I this case, C is a

More information

Zeros of Polynomials

Zeros of Polynomials Math 160 www.timetodare.com 4.5 4.6 Zeros of Polyomials I these sectios we will study polyomials algebraically. Most of our work will be cocered with fidig the solutios of polyomial equatios of ay degree

More information

Chapter 9 - CD companion 1. A Generic Implementation; The Common-Merge Amplifier. 1 τ is. ω ch. τ io

Chapter 9 - CD companion 1. A Generic Implementation; The Common-Merge Amplifier. 1 τ is. ω ch. τ io Chapter 9 - CD compaio CHAPTER NINE CD-9.2 CD-9.2. Stages With Voltage ad Curret Gai A Geeric Implemetatio; The Commo-Merge Amplifier The advaced method preseted i the text for approximatig cutoff frequecies

More information

FREE VIBRATION RESPONSE OF A SYSTEM WITH COULOMB DAMPING

FREE VIBRATION RESPONSE OF A SYSTEM WITH COULOMB DAMPING Mechaical Vibratios FREE VIBRATION RESPONSE OF A SYSTEM WITH COULOMB DAMPING A commo dampig mechaism occurrig i machies is caused by slidig frictio or dry frictio ad is called Coulomb dampig. Coulomb dampig

More information

ECE-S352 Introduction to Digital Signal Processing Lecture 3A Direct Solution of Difference Equations

ECE-S352 Introduction to Digital Signal Processing Lecture 3A Direct Solution of Difference Equations ECE-S352 Itroductio to Digital Sigal Processig Lecture 3A Direct Solutio of Differece Equatios Discrete Time Systems Described by Differece Equatios Uit impulse (sample) respose h() of a DT system allows

More information

Chapter 5 Vibrational Motion

Chapter 5 Vibrational Motion Fall 4 Chapter 5 Vibratioal Motio... 65 Potetial Eergy Surfaces, Rotatios ad Vibratios... 65 Harmoic Oscillator... 67 Geeral Solutio for H.O.: Operator Techique... 68 Vibratioal Selectio Rules... 7 Polyatomic

More information

In algebra one spends much time finding common denominators and thus simplifying rational expressions. For example:

In algebra one spends much time finding common denominators and thus simplifying rational expressions. For example: 74 The Method of Partial Fractios I algebra oe speds much time fidig commo deomiators ad thus simplifyig ratioal epressios For eample: + + + 6 5 + = + = = + + + + + ( )( ) 5 It may the seem odd to be watig

More information

Basic Iterative Methods. Basic Iterative Methods

Basic Iterative Methods. Basic Iterative Methods Abel s heorem: he roots of a polyomial with degree greater tha or equal to 5 ad arbitrary coefficiets caot be foud with a fiite umber of operatios usig additio, subtractio, multiplicatio, divisio, ad extractio

More information

(3) If you replace row i of A by its sum with a multiple of another row, then the determinant is unchanged! Expand across the i th row:

(3) If you replace row i of A by its sum with a multiple of another row, then the determinant is unchanged! Expand across the i th row: Math 50-004 Tue Feb 4 Cotiue with sectio 36 Determiats The effective way to compute determiats for larger-sized matrices without lots of zeroes is to ot use the defiitio, but rather to use the followig

More information

The Jordan Normal Form: A General Approach to Solving Homogeneous Linear Systems. Mike Raugh. March 20, 2005

The Jordan Normal Form: A General Approach to Solving Homogeneous Linear Systems. Mike Raugh. March 20, 2005 The Jorda Normal Form: A Geeral Approach to Solvig Homogeeous Liear Sstems Mike Raugh March 2, 25 What are we doig here? I this ote, we describe the Jorda ormal form of a matrix ad show how it ma be used

More information

Damped Vibration of a Non-prismatic Beam with a Rotational Spring

Damped Vibration of a Non-prismatic Beam with a Rotational Spring Vibratios i Physical Systems Vol.6 (0) Damped Vibratio of a No-prismatic Beam with a Rotatioal Sprig Wojciech SOCHACK stitute of Mechaics ad Fudametals of Machiery Desig Uiversity of Techology, Czestochowa,

More information

The Growth of Functions. Theoretical Supplement

The Growth of Functions. Theoretical Supplement The Growth of Fuctios Theoretical Supplemet The Triagle Iequality The triagle iequality is a algebraic tool that is ofte useful i maipulatig absolute values of fuctios. The triagle iequality says that

More information

Math 475, Problem Set #12: Answers

Math 475, Problem Set #12: Answers Math 475, Problem Set #12: Aswers A. Chapter 8, problem 12, parts (b) ad (d). (b) S # (, 2) = 2 2, sice, from amog the 2 ways of puttig elemets ito 2 distiguishable boxes, exactly 2 of them result i oe

More information

Notes on iteration and Newton s method. Iteration

Notes on iteration and Newton s method. Iteration Notes o iteratio ad Newto s method Iteratio Iteratio meas doig somethig over ad over. I our cotet, a iteratio is a sequece of umbers, vectors, fuctios, etc. geerated by a iteratio rule of the type 1 f

More information

Math 61CM - Solutions to homework 3

Math 61CM - Solutions to homework 3 Math 6CM - Solutios to homework 3 Cédric De Groote October 2 th, 208 Problem : Let F be a field, m 0 a fixed oegative iteger ad let V = {a 0 + a x + + a m x m a 0,, a m F} be the vector space cosistig

More information

Eigenvalues and Eigenvectors

Eigenvalues and Eigenvectors 5 Eigevalues ad Eigevectors 5.3 DIAGONALIZATION DIAGONALIZATION Example 1: Let. Fid a formula for A k, give that P 1 1 = 1 2 ad, where Solutio: The stadard formula for the iverse of a 2 2 matrix yields

More information

Castiel, Supernatural, Season 6, Episode 18

Castiel, Supernatural, Season 6, Episode 18 13 Differetial Equatios the aswer to your questio ca best be epressed as a series of partial differetial equatios... Castiel, Superatural, Seaso 6, Episode 18 A differetial equatio is a mathematical equatio

More information

Chapter 9: Numerical Differentiation

Chapter 9: Numerical Differentiation 178 Chapter 9: Numerical Differetiatio Numerical Differetiatio Formulatio of equatios for physical problems ofte ivolve derivatives (rate-of-chage quatities, such as velocity ad acceleratio). Numerical

More information

CHAPTER I: Vector Spaces

CHAPTER I: Vector Spaces CHAPTER I: Vector Spaces Sectio 1: Itroductio ad Examples This first chapter is largely a review of topics you probably saw i your liear algebra course. So why cover it? (1) Not everyoe remembers everythig

More information

Sequences A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence

Sequences A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence Sequeces A sequece of umbers is a fuctio whose domai is the positive itegers. We ca see that the sequece 1, 1, 2, 2, 3, 3,... is a fuctio from the positive itegers whe we write the first sequece elemet

More information

Definition 4.2. (a) A sequence {x n } in a Banach space X is a basis for X if. unique scalars a n (x) such that x = n. a n (x) x n. (4.

Definition 4.2. (a) A sequence {x n } in a Banach space X is a basis for X if. unique scalars a n (x) such that x = n. a n (x) x n. (4. 4. BASES I BAACH SPACES 39 4. BASES I BAACH SPACES Sice a Baach space X is a vector space, it must possess a Hamel, or vector space, basis, i.e., a subset {x γ } γ Γ whose fiite liear spa is all of X ad

More information

t distribution [34] : used to test a mean against an hypothesized value (H 0 : µ = µ 0 ) or the difference

t distribution [34] : used to test a mean against an hypothesized value (H 0 : µ = µ 0 ) or the difference EXST30 Backgroud material Page From the textbook The Statistical Sleuth Mea [0]: I your text the word mea deotes a populatio mea (µ) while the work average deotes a sample average ( ). Variace [0]: The

More information

Lecture 6 Chi Square Distribution (χ 2 ) and Least Squares Fitting

Lecture 6 Chi Square Distribution (χ 2 ) and Least Squares Fitting Lecture 6 Chi Square Distributio (χ ) ad Least Squares Fittig Chi Square Distributio (χ ) Suppose: We have a set of measuremets {x 1, x, x }. We kow the true value of each x i (x t1, x t, x t ). We would

More information

1 Adiabatic and diabatic representations

1 Adiabatic and diabatic representations 1 Adiabatic ad diabatic represetatios 1.1 Bor-Oppeheimer approximatio The time-idepedet Schrödiger equatio for both electroic ad uclear degrees of freedom is Ĥ Ψ(r, R) = E Ψ(r, R), (1) where the full molecular

More information

First, note that the LS residuals are orthogonal to the regressors. X Xb X y = 0 ( normal equations ; (k 1) ) So,

First, note that the LS residuals are orthogonal to the regressors. X Xb X y = 0 ( normal equations ; (k 1) ) So, 0 2. OLS Part II The OLS residuals are orthogoal to the regressors. If the model icludes a itercept, the orthogoality of the residuals ad regressors gives rise to three results, which have limited practical

More information

Session 5. (1) Principal component analysis and Karhunen-Loève transformation

Session 5. (1) Principal component analysis and Karhunen-Loève transformation 200 Autum semester Patter Iformatio Processig Topic 2 Image compressio by orthogoal trasformatio Sessio 5 () Pricipal compoet aalysis ad Karhue-Loève trasformatio Topic 2 of this course explais the image

More information

THE ASYMPTOTIC COMPLEXITY OF MATRIX REDUCTION OVER FINITE FIELDS

THE ASYMPTOTIC COMPLEXITY OF MATRIX REDUCTION OVER FINITE FIELDS THE ASYMPTOTIC COMPLEXITY OF MATRIX REDUCTION OVER FINITE FIELDS DEMETRES CHRISTOFIDES Abstract. Cosider a ivertible matrix over some field. The Gauss-Jorda elimiatio reduces this matrix to the idetity

More information

Basics of Dynamics. Amit Prashant. Indian Institute of Technology Gandhinagar. Short Course on. Geotechnical Aspects of Earthquake Engineering

Basics of Dynamics. Amit Prashant. Indian Institute of Technology Gandhinagar. Short Course on. Geotechnical Aspects of Earthquake Engineering Basics of yamics Amit Prashat Idia Istitute of Techology Gadhiagar Short Course o Geotechical Aspects of Earthquake Egieerig 4 8 March, 213 Our ear Pedulum Revisited g.si g l s Force Equilibrium: Cord

More information

Theorem: Let A n n. In this case that A does reduce to I, we search for A 1 as the solution matrix X to the matrix equation A X = I i.e.

Theorem: Let A n n. In this case that A does reduce to I, we search for A 1 as the solution matrix X to the matrix equation A X = I i.e. Theorem: Let A be a square matrix The A has a iverse matrix if ad oly if its reduced row echelo form is the idetity I this case the algorithm illustrated o the previous page will always yield the iverse

More information

a for a 1 1 matrix. a b a b 2 2 matrix: We define det ad bc 3 3 matrix: We define a a a a a a a a a a a a a a a a a a

a for a 1 1 matrix. a b a b 2 2 matrix: We define det ad bc 3 3 matrix: We define a a a a a a a a a a a a a a a a a a Math S-b Lecture # Notes This wee is all about determiats We ll discuss how to defie them, how to calculate them, lear the allimportat property ow as multiliearity, ad show that a square matrix A is ivertible

More information

A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence

A sequence of numbers is a function whose domain is the positive integers. We can see that the sequence Sequeces A sequece of umbers is a fuctio whose domai is the positive itegers. We ca see that the sequece,, 2, 2, 3, 3,... is a fuctio from the positive itegers whe we write the first sequece elemet as

More information

( ) ( ) ( ) notation: [ ]

( ) ( ) ( ) notation: [ ] Liear Algebra Vectors ad Matrices Fudametal Operatios with Vectors Vector: a directed lie segmets that has both magitude ad directio =,,,..., =,,,..., = where 1, 2,, are the otatio: [ ] 1 2 3 1 2 3 compoets

More information

Discrete-Time Systems, LTI Systems, and Discrete-Time Convolution

Discrete-Time Systems, LTI Systems, and Discrete-Time Convolution EEL5: Discrete-Time Sigals ad Systems. Itroductio I this set of otes, we begi our mathematical treatmet of discrete-time s. As show i Figure, a discrete-time operates or trasforms some iput sequece x [

More information

Symmetric Matrices and Quadratic Forms

Symmetric Matrices and Quadratic Forms 7 Symmetric Matrices ad Quadratic Forms 7.1 DIAGONALIZAION OF SYMMERIC MARICES SYMMERIC MARIX A symmetric matrix is a matrix A such that. A = A Such a matrix is ecessarily square. Its mai diagoal etries

More information

Infinite Sequences and Series

Infinite Sequences and Series Chapter 6 Ifiite Sequeces ad Series 6.1 Ifiite Sequeces 6.1.1 Elemetary Cocepts Simply speakig, a sequece is a ordered list of umbers writte: {a 1, a 2, a 3,...a, a +1,...} where the elemets a i represet

More information

Microscopic Theory of Transport (Fall 2003) Lecture 6 (9/19/03) Static and Short Time Properties of Time Correlation Functions

Microscopic Theory of Transport (Fall 2003) Lecture 6 (9/19/03) Static and Short Time Properties of Time Correlation Functions .03 Microscopic Theory of Trasport (Fall 003) Lecture 6 (9/9/03) Static ad Short Time Properties of Time Correlatio Fuctios Refereces -- Boo ad Yip, Chap There are a umber of properties of time correlatio

More information

CS284A: Representations and Algorithms in Molecular Biology

CS284A: Representations and Algorithms in Molecular Biology CS284A: Represetatios ad Algorithms i Molecular Biology Scribe Notes o Lectures 3 & 4: Motif Discovery via Eumeratio & Motif Represetatio Usig Positio Weight Matrix Joshua Gervi Based o presetatios by

More information

Chapter 6 Principles of Data Reduction

Chapter 6 Principles of Data Reduction Chapter 6 for BST 695: Special Topics i Statistical Theory. Kui Zhag, 0 Chapter 6 Priciples of Data Reductio Sectio 6. Itroductio Goal: To summarize or reduce the data X, X,, X to get iformatio about a

More information

Finite Element Modeling of Seismic Response of Field Fabricated Liquefied Natural Gas (LNG) Spherical Storage Vessels

Finite Element Modeling of Seismic Response of Field Fabricated Liquefied Natural Gas (LNG) Spherical Storage Vessels Egieerig, 013, 5, 543-550 doi:10.436/eg.013.56065 Published Olie Jue 013 (http://www.scirp.org/joural/eg) Fiite Elemet Modelig of Seismic Respose of Field Fabricated Liquefied Natural Gas (LNG) Spherical

More information

REVISION SHEET FP1 (MEI) ALGEBRA. Identities In mathematics, an identity is a statement which is true for all values of the variables it contains.

REVISION SHEET FP1 (MEI) ALGEBRA. Identities In mathematics, an identity is a statement which is true for all values of the variables it contains. The mai ideas are: Idetities REVISION SHEET FP (MEI) ALGEBRA Before the exam you should kow: If a expressio is a idetity the it is true for all values of the variable it cotais The relatioships betwee

More information

Recursive Algorithms. Recurrences. Recursive Algorithms Analysis

Recursive Algorithms. Recurrences. Recursive Algorithms Analysis Recursive Algorithms Recurreces Computer Sciece & Egieerig 35: Discrete Mathematics Christopher M Bourke cbourke@cseuledu A recursive algorithm is oe i which objects are defied i terms of other objects

More information

THE KALMAN FILTER RAUL ROJAS

THE KALMAN FILTER RAUL ROJAS THE KALMAN FILTER RAUL ROJAS Abstract. This paper provides a getle itroductio to the Kalma filter, a umerical method that ca be used for sesor fusio or for calculatio of trajectories. First, we cosider

More information

8. Applications To Linear Differential Equations

8. Applications To Linear Differential Equations 8. Applicatios To Liear Differetial Equatios 8.. Itroductio 8.. Review Of Results Cocerig Liear Differetial Equatios Of First Ad Secod Orders 8.3. Eercises 8.4. Liear Differetial Equatios Of Order N 8.5.

More information

1. Hydrogen Atom: 3p State

1. Hydrogen Atom: 3p State 7633A QUANTUM MECHANICS I - solutio set - autum. Hydroge Atom: 3p State Let us assume that a hydroge atom is i a 3p state. Show that the radial part of its wave fuctio is r u 3(r) = 4 8 6 e r 3 r(6 r).

More information

EXAM-3 MATH 261: Elementary Differential Equations MATH 261 FALL 2006 EXAMINATION COVER PAGE Professor Moseley

EXAM-3 MATH 261: Elementary Differential Equations MATH 261 FALL 2006 EXAMINATION COVER PAGE Professor Moseley EXAM-3 MATH 261: Elemetary Differetial Equatios MATH 261 FALL 2006 EXAMINATION COVER PAGE Professor Moseley PRINT NAME ( ) Last Name, First Name MI (What you wish to be called) ID # EXAM DATE Friday Ocober

More information

PAijpam.eu ON TENSOR PRODUCT DECOMPOSITION

PAijpam.eu ON TENSOR PRODUCT DECOMPOSITION Iteratioal Joural of Pure ad Applied Mathematics Volume 103 No 3 2015, 537-545 ISSN: 1311-8080 (prited versio); ISSN: 1314-3395 (o-lie versio) url: http://wwwijpameu doi: http://dxdoiorg/1012732/ijpamv103i314

More information