Investigations on the Dynamical Characteristics of One Water Molecule Embedded in a Singlewalled Carbon Nanotube

Size: px
Start display at page:

Download "Investigations on the Dynamical Characteristics of One Water Molecule Embedded in a Singlewalled Carbon Nanotube"

Transcription

1 Ivesgaos o he Dyamcal Chaacescs of Oe Wae Molecule Embedded a Sglewalled Cabo Naoube Ja-Mg Lu * Tzu-Hua Wu 2 ad Su-Tog Cho 2 Naoal Cee fo Hgh-Pefomace Compug Naoal Appled Reseach Laboaoes 2 Depame of Aeoaucs ad Asoaucs Naoal Cheg Kug Uvesy * Coespodece: ockylu@chc.og.w

2 Oule INTRODUCTION MD SIMULATION METHODOLOGY RESULTS AND DISCUSSION CONCLUSIONS FUTURE DIRECTIONS ACKNOWLEDGMENTS

3 Ioduco I CNT Applcaos 24/4/ 3

4 Ioduco II - Applcaos Baees Bosesos fo hamful gases ad chemcal aalyses Capacos Cahodes fo mcowave ubes Chemcal facoy-o-a-chp applcaos Compues ad TVs wh ao ccus Coducg composes Coducos fo mco elecoc devces Coolled dug elease applcaos DNA chps Elecoc applcaos Elecoc ecfcao ballsc swchg ad logc fucos Elecoc aocompoes ad maeal poeco applcaos Feld effec assos Feld-emsso fla pael dsplays Fle applcaos Fuel cell membaes Hea ppe Hydoge soage LEDs Mcoscope pobes Molecula pumps Naomec es ubes Naoube efoced composes Nao-daa soage Quaum wes Sgle eleco assos Spog goods Wae desalaos Weless devces hp://

5 Movao Ieesg pheomea ad physcal popees may be foud he wae-aoube composes. Sce he dscovey of cabo aoubes eseaches vgoously vesgaed he faasc behavo of cabo aoubes wh o whou cluso aoms. povdg avalable fomao o esmae he effecve Youg s modulus of he wae-aoube compose.

6 Pape Suvey PublsheNaue Yea2 AuhoHumme G Rasaah JC Nowoya JP TleWae coduco hough he hydophobc chael of a cabo aoube Humme e al. ulzed he molecula dyamcs mehod ad foud ha wae aages oedmesoal ode sde a hydophobc cabo aoube by sog eaco of hydoge bods. He vesgaed wae a log cha ode ad s fludy a pulsed mode

7 Pape Suvey Publshe Nao Les Yea24 AuhoN. Nagub H. Ye Y. Gogos A. G. Yazcoglu C. M. Megads M. Yoshmua TleObsevao of wae cofed aomee chaels of closed cabo aoubes Nagub e al. suded wae passg o he defecs of a cabo aoube ad vesgaed he behavo of wae sde a cabo aoube. They foud ha he flow of wae s much less ha ha of macoscopc wae ageeme wh Lu s esuls. Also wae ca be soldfed by ceasg he pessue ad s foud ha hexagoal ad hepagoal cy colums chage o ecagula ad peagoal oes whe exeal pessue s ceased

8 Pape Suvey Publshe Phys. Rev. B Yea25 Auho Lu YC Wag Q TleTaspo behavo of wae cofed cabo aoubes Lu ad Wag foud ha wae sde a cabo aoube behaves as of asoopc aspoao by he molecula dyamcs mehod. They also vesgaed ha axal hea coduco ae dffusve ae ad vscosy ae much moe ha logude ha. The dffusve ae of wae deceases oceably wh he decease of a cabo aoube s damee. Howeve he axal hea coducve ae ad shea vscosy of wae ae much moe ha ha of macoscopc wae. Moeove he chal ode ad lama dsbuo of wae wee also vesgaed

9 Pape Suvey Publshe J. Phys.: Codes. Mae Yea 26 AuhoN R de Souza A I Koleskov C J Buham ad C-K Loog TleSucue ad dyamcs of wae cofed sgle-wall cabo aoubes Souza e al. used he euo dffaco ad he molecula dyamcs mehod o vesgae wae sde a cabo aoube ad foud ha wae s able o pass hough a SWNT a shell-cha sucue a lowe empeaue. They defed ha wae eaages ad chages o a cubc cy sucue whch coas cha-sucued wae molecules. The hydoge bods ae ceaed ad boke volely wh he empeaue ceasg. He foud ha he shell-cha sucue dsappeas whe he empeaue s beyod 2K

10 Pape Suvey Publshe Nao Les Yea27 AuhoWag Z. C L. Che L. Nayak S. Ajaya P.M. ad Koaka N. TlePolay-Depede Elecochemcally Coolled Taspo of Wae hough Cabo Naoube Membaes Wag e al. obseved wae egave chage by bgg posve volage o a waeembedded cabo aoube ad foud ha a cabo aoube s popees chage o hydophlc fom hydophobc. Moeove he flow ae ceases subsaally wh he elecc feld ceasg. They dcaed ha he echque ca be appled o pufy dkg wae ad gee eseach.

11 Oule INTRODUCTION MD SIMULATION METHODOLOGY RESULTS AND DISCUSSION CONCLUSIONS FUTURE DIRECTIONS ACKNOWLEDGMENTS

12 Huma ha ~ -5 mm wde Red blood cells wh whe cell ~ 2-5 mm Thgs Naual Dus me 2 mm ~ m damee The Scale of Thgs -- Naomees ad Moe A ~ 5 mm Fly ash ~ -2 mm ATP syhase The Mcowold The Naowold -2 m -3 m -4 m -5 m -6 m -7 m -8 m aomees = mllmee mm Ulavole Vsble Ifaed Mcowave cm mm. mm mm. mm mm aomees = mcomee mm. mm m. mm m MD Thgs Mamade McoElecoMechacal devces - mm wde Red blood cells Polle ga Zoe plae x-ay les Ouemos g spacg ~35 m Naoube elecode Head of a p -2 mm Naoube asso 2s Ceuy Challege O O S O O O O O O O O O O O S O S O S Combe aoscale buldg blocks o make ovel fucoal devces e.g. a phoosyhec eaco cee wh egal semcoduco soage O S P O O O O S O O S O S -9 m aomee m DNA ~2-/2 m damee Aoms of slco spacg ~ehs of m - m Sof x-ay. m Quaum coal of 48 o aoms o coppe suface posoed oe a a me wh a STM p Coal damee 4 m Cabo aoube ~2 m damee Offce of Basc Eegy Sceces Offce of Scece U.S. DOE Veso 3-5-2

13 Legh ad Tme Scales Numecal Modelg Tme Scale msec Naoechology sec psec fsec QC QMD MD Sascs Mechacs Couum Mechacs m m mm Space Scale

14 Molecula Dyamcs A compue smulao echque ha allows oe o pedc he me evoluo of a sysem of eacg pacles aoms molecules.. ec.

15 Two Seps o pefom MD smulao I Seg al codos e.q. al poso ad veloces of all pacles he sysem Selecg accuae eaco poeal fo descbg he foces amog all he pacles.

16 II Solvg a se of classcal equaos of moo j : eaomc poeal

17 Schemac dagam of a basc MD code Defe al posos ad veloces ad V Pa A 2 3 N a Calculae foces a cue me F V... Pa B Solve equaos of moo fo all pacles he sysem Ove a sho mesep V V Pa C Calculae desed physcal quaes we daa o ajecoy fle Pa D s max We o he dsk fal aomc cofguao & fsh 7

18 Pa A Seg Ial Codo s Pa A HPC-NMR Pa B V... Defe al posos ad veloces ad Calculae foces a cue me F 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep V V Calculae desed physcal quaes we daa o ajecoy fle Pa D s max V Pa C We o he dsk fal aomc cofguao & fsh esablshg al posos ad veloces of all aoms befoe MD smulao Two sklls o acheve he elaxao pocess usg values afe elaxao pocess Udegog a elaxao pocess Relaxao cycles Re-zeo smulao sums Poduco cycles 8 Schemac fom lecue of D. A. Kofke

19 s Pa A HPC-NMR Pa B F V... Defe al posos ad veloces ad Calculae foces a cue me 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V V Geeag a Ial Cofguao Calculae desed physcal quaes we daa o ajecoy fle s max We o he dsk fal aomc cofguao & fsh Pa D The aageme of he Ial cofguao s maly based o he maeal aue we wa o smulae fo example b.c.c f.c.c h.c.p amophous. H.C.P F.C.C

20 s Pa A HPC-NMR Pa B V... Defe al posos ad veloces ad Calculae foces a cue me F 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V V Ial Veloces Calculae desed physcal quaes we daa o ajecoy fle s max We o he dsk fal aomc cofguao & fsh Pa D Geeag veloces of aoms x y z decos ove a ufom adom umbes ove -. Scalg he kec eegy of he sysem o he coespodg empeaue we desed. shfg he cee-of-mass momeum o be zeo

21 Dmesos ad Us s Pa A HPC-NMR Pa B F V... Defe al posos ad veloces ad Calculae foces a cue me 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V Calculae desed physcal quaes we daa o ajecoy fle Pa D V s max We o he dsk fal aomc cofguao & fsh Scalg by model paamees sze s eegy e mass m Tables fom he lecue of D. A. Kofke

22 Themosas s Pa A HPC-NMR Pa B F V... Defe al posos ad veloces ad Calculae foces a cue me 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V Calculae desed physcal quaes we daa o ajecoy fle Pa D V s max We o he dsk fal aomc cofguao & fsh momeum empeaue s popooal o oal kec eegy kt N 2 2 p Nd m Nd K eegy flucuae bewee K ad U p N Q N

23 s Pa A HPC-NMR Pa B F V... Defe al posos ad veloces ad Calculae foces a cue me 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V V Calculae desed physcal quaes we daa o ajecoy fle Pa D s max Foce momeum empeaue o ema cosa. Isokec Themosag Themosag va Wall Collsos.Adese Themosa 2. Nosé Themosa 3. Nosé-Hoove Themosa We o he dsk fal aomc cofguao & fsh

24 Peodc Bouday Codo geomec bouday s Pa A HPC-NMR Pa B V... Defe al posos ad veloces ad Calculae foces a cue me F 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V Calculae desed physcal quaes we daa o ajecoy fle Pa D s max We o he dsk fal aomc cofguao & fsh V

25 Pa B Poeals used he MD smulao s Pa A HPC-NMR Pa B V... Defe al posos ad veloces ad Calculae foces a cue me F 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V Calculae desed physcal quaes we daa o ajecoy fle Pa D s max V Bodg Foce a bod segh V bod legh N b N b / 2 k b b b c bod oso We o he dsk fal aomc cofguao & fsh b bod bedg 2 V bedg N N We o he dsk fal aomc cofguao & fsh k 2 N V dhedal K -cos[ - ]

26 d Va de Wal V [ j j 2 2 j j 6 A ] vdw j SC j vdw j A S s Pa A HPC-NMR Pa B V... Defe al posos ad veloces ad Calculae foces a cue me F 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V Calculae desed physcal quaes we daa o ajecoy fle Pa D s max We o he dsk fal aomc cofguao & fsh V S A vdw j [ j j 2 j j 6 j j 2 j j 6 A SC j 2 j ] 2 c [ ASC j 2 j ] c No-bodg Foce e Coulomb foce V. j coul 332 [ q q j j ] q paal ch ag es j A S els j j c c q q 2 c f Hydoge foce q j S A els V HB M 2 N

27 Two ypes of eaomc poeal s Pa A HPC-NMR Pa B V... Defe al posos ad veloces ad Calculae foces a cue me F 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V Calculae desed physcal quaes we daa o ajecoy fle Pa D s max We o he dsk fal aomc cofguao & fsh V Pawse Poeal May body poeal

28 Lead-Joes poeal s Pa A HPC-NMR Pa B V... Defe al posos ad veloces ad Calculae foces a cue me F 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V V Two-body poeal U j 4 j j Mose poeal 2 6 exp 2 2*exp j D j o j o Calculae desed physcal quaes we daa o ajecoy fle s max We o he dsk fal aomc cofguao & fsh Pa D m

29 May body poeal Tgh-bdg poeal Co Cu T s Pa A HPC-NMR Pa B F V... Defe al posos ad veloces ad Calculae foces a cue me 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V Calculae desed physcal quaes we daa o ajecoy fle Pa D s max We o he dsk fal aomc cofguao & fsh V May-body Poeal exp 2 exp 2 j j E q A p j j May-body em-log age foce aacve foce Whee s a effecve hoppg egal j o /2 s he dsace bewee aom ad j s he fs-eghbo dsace Bo-Maye ype pawse em-sho age epulsve foce

30 May-body PoealNo-bodg Foce May body poeal V Tesoff poeal C S Ge A complcaed poeal o descbe he covale bodg bewee aoms V R V j f c E j Aj exp jj A j Bj exp jj f j R j Rj f c j cos f 2 2 Sj Rj f j Sj V j j [ V b V j R j j A j ] Pawse em-sho age epulsve foce Thee-body em-log age aacve foce bodg agle s also cosdeed j R j j S j s Pa A HPC-NMR Pa B F V... Defe al posos ad veloces ad Calculae foces a cue me 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep V V Calculae desed physcal quaes we daa o ajecoy fle Cuoff Fuco whch s used o smooh he eegy fuco o be zeo a he cuoff dsace bewee aoms. s max We o he dsk fal aomc cofguao & fsh V Pa D Pa C

31 Cuoff Mehod s Pa A HPC-NMR Pa B F V... Defe al posos ad veloces ad Calculae foces a cue me 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V Calculae desed physcal quaes we daa o ajecoy fle Pa D V s max We o he dsk fal aomc cofguao & fsh Vele ls Cell ls Vele combe cell ls

32 Vele combe Cell Ls s Pa A HPC-NMR Pa B V... Defe al posos ad veloces ad Calculae foces a cue me F 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V Calculae desed physcal quaes we daa o ajecoy fle Pa D V s max We o he dsk fal aomc cofguao & fsh 2 3 L L L

33 s Pa A HPC-NMR Pa B V... Defe al posos ad veloces ad Calculae foces a cue me F 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V V Calculae desed physcal quaes we daa o ajecoy fle Pa D s max We o he dsk fal aomc cofguao & fsh Algohm Compue Tme Sec./Tme sep Effce% Noe Vele Ls Cell lk Vele + Cell lk.66

34 Pa C Iegao Algohms s Pa A HPC-NMR Pa B V... Defe al posos ad veloces ad Calculae foces a cue me F 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V Calculae desed physcal quaes we daa o ajecoy fle Pa D V s max We o he dsk fal aomc cofguao & fsh. Vele Algohm 2. Leapfog Algohm 3. Velocy Vele Algohm 4. Gea Pedco-Coeco Algohm 34

35 Pa D Daa samplg Pa A Pa B F V... Defe al posos ad veloces ad Calculae foces a cue me 2 3 N a Solve equaos of moo fo all pacles he sysem Ove a sho mesep Pa C V V Calculae desed physcal quaes we daa o ajecoy fle Pa D V Pogess of smulao s max We o he dsk fal aomc cofguao & fsh MD me sep o MC cycle popey value m m m 3 m 5m6 m 7 m 9 m 2 m 4 m 8 Smulao block block aveage m. b m b m b- m b m3 m4 m5 Complee smulao smulao aveage m m k k. m 35 Schemac fom lecue of D. A. Kofke

36 Oule INTRODUCTION MD SIMULATION METHODOLOGY RESULTS AND DISCUSSION CONCLUSIONS FUTURE DIRECTIONS ACKNOWLEDGMENTS

37 MD SIMULATION The al codos: The boom ed of he cabo aoube s fxed. The me sep s chose o be =. fs fo he case of a cabo aoube whou wae; =.5 fs fo cabo aoubes wh wae. The empeaue s se o be 3 ad 2K. The NTV esemble s chose ad he cu-off dsace s 2 Å. Fo he wae-aoube compose o he cabo aoube hee ae execued fo al elaxao ad addoal 5 me seps fo eachg he lowes eegy cofguao.

38 MD SIMULATION The coolled paamees: The eval of me sep ad he cu-off dsace ae pe-chose. Tempeaue 3 ad 2K. The umbe of wae molecules ad 25. The ug me of a case 5 me seps. The vesgaed paamees: The vbao dsplacemes he amplude ad he vaace ad he mea value of he ampludes of he cabo aoube ae suded. Summay: The fee-vbao dsplaceme of he cabo aoube s p s vesgaed ad he dyamcal behavo of wae sde he cabo aoube s also ecoded. The elaoshp bewee he vaace ad mea value of vbag ampludes of he cabo aoube ad empeaue ae dscussed.

39 Mehodology TesoffCabo j j k E j V V f [ V bv ] j c j R j j A j V A exp R j j j j V B exp A j j j j j jk k f j Rj j R j f cos f R S 2 2 Sj R j f j Sj c j j j j b j j j 2

40 Mehodology Tesoff Cabo whee E s he oal eegy of all he covalely boded cabo aoms E he eegy fo aom V j he eaco eegy bewee aoms ad j j he dsace bewee hem jk s he bod agle bewee aoms j ad k ad f c s a cuoff fuco o esc he age of he poeal. I he pese wok he oal eegy calculaed fom he Tesoff poeal s assumed o be he oal sa eegy of he sysem. E j V V f [ V bv ] j c j R j j A j V A exp R j j j j V B exp A j j j j f j Rj j R j f cos f R S 2 2 Sj R j f j Sj c j j j j j b j j j 2

41 Mehodology Tesoff Cabo Paamees used he Tesoff poeal fo cabo-cabo bdg. Paamee A ev B ev Å - Å - c d H R Å S Å Value

42 Mehodology TIP3P wae Wae E whee ad ae cosa. They ae us of g-å 2 /fs 2 ad Å especvely.

43 Mehodology ME3Ogac Bodg Tems Wae-Cabo a Bod Sechg Poeal E 2 K R b Bod Agle Poeal 2 Hee K s a cosa us of kcal/mol/å 2. Å s he dsace bewee aom ad aom j. R Å s he equlbum bod sechg dsace. E C 2 2s C cos cos cos 2 8 Hee C s a cosa us of kcal/mol. deg s he equlbum bod agle.

44 Mehodology ME3Ogac Bodg Tems Wae-Cabo c Tosoal Agle Poeal V E [ cos{ }] 2 d Ou-of of-plae Poeal K cos cos 2 E 2s C cos Hee V s a cosa us of kcal/mol. deg s he equlbum osoal agle ad s a peodc paamee. Hee K s a cosa us of kcal/mol. deg s he equlbum ou-of of-plae agle. 2

45 Mehodology ME3Ogac No-bodg Tems Wae-Cabo e LJ oly UFF Poeal E D R R The above equao s he o-bodg em. D s a cosa whose u s kcal/mol. R Å s also a cosa.

46 Oule INTRODUCTION MD SIMULATION METHODOLOGY RESULTS AND DISCUSSION CONCLUSIONS FUTURE DIRECTIONS ACKNOWLEDGMENTS

47 RESULTS AND DISCUSSION Mea-SDA TempeaueK I shows ha loge ug me blue le 5 me seps pedcs less vaao ha shoe ug me whe le me seps bu o sgfcaly dcag ou esuls have eached umecal equlbum. Also by hs slgh dffeece ca be see ha he ase sae of a cabo aoube s vbao s moe vole ha he seady-sae oe. The vaace of he amplude of a capped cabo aoube s p deceases wh he execug me ceasg. The elaoshp bewee he mea value ad he vaace of a capped SWCNT ad empeaue whou wae 47

48 RESULTS AND DISCUSSION Mea-SDA TempeaueK I shows ha he amplude of a SWCNT s p ceases wh empeaue. Is ceasg ae s ealy lealy. Also s foud ha he vaace of a cabo aoube s he lages ea 3K. We obseve ha he sysem coag oe wae molecule dsubs he ube s vbao mos whe empeaue s ea he bolg po. I s suspeced ha wae s bolg s esposble fo hs obsevao. Whe he empeaue of wae s above he bolg po he volume of he wae vapo expads moe ha ha of he wae. Hece he collso bewee wae molecules ad he wall of a cabo aoube ceases ad esuls he vaace of he amplude of a cabo aoube. The elaoshp bewee he mea value ad he vaace of a capped SWCNT ad empeaue wh oly oe wae molecule 48

49 RESULTS AND DISCUSSION 4 Mea-SDA I shows ha he amplude of a SWCNT s p ceases wh empeaue. Is ceasg ae s ealy lealy whe he case has 25 wae molecules sde a SWNT TempeaueK The elaoshp bewee he mea value ad he vaace of a capped SWCNT ad empeaue wh 25 wae molecules. 49

50 RESULTS AND DISCUSSION a b c d The spaal poso of oe wae molecule he axal deco of a capped SWCNT whch s execued me seps a dffee empeaue a K; b 3K; c K; d 2K. The ed of dyamcal behavo of oe wae molecules lke walkg adomly a oe-dmesoal space as show Fg. Oe wae molecule behaves adomwalk fasho moe oceable wh empeaue ceasg. The kec eegy of wae ceases wh he cease of empeaue ad esuls he moveme of wae molecule. Howeve he ceasg he umbe of wae molecules deceases he adom-walk ed. The dffuso pahways ae dve by he mechasm of adom-walk ad he coceao of wae. Wh empeaue ad execug me ceasg wae molecules dsbue ufomly gadually alog he axal deco of he SWCNT. The beahg ad sechg-shoeg modes of he SWCNT ae cuely ude vesgao by ou goup 5

51 RESULTS AND DISCUSSION

52 RESULTS AND DISCUSSION a b 552 Å298Ka5Kb 52

53 RESULTS AND DISCUSSION a b a 9b 55 53

54 RESULTS AND DISCUSSION 55 54

55 Resuls Å Å Å

56 Oule INTRODUCTION MD SIMULATION METHODOLOGY RESULTS AND DISCUSSION CONCLUSIONS FUTURE DIRECTIONS ACKNOWLEDGMENTS

57 Coclusos The moe empeaue s he moe he vbag amplude of he SWNT ad he dyamcal behavo of wae moome sde s. 2 The opmal geomecal dsace s almos lealy elaed wh he damee of a SWNT o wh he chal veco of ha. 3 The wae moome emas he opmal geomecal dsace ad says close o he wall of a SWNT sead of o keep ealy he z-axal cee of a SWNT afe achevg he seady sae.

58 Oule INTRODUCTION MD SIMULATION METHODOLOGY RESULTS AND DISCUSSION CONCLUSIONS FUTURE DIRECTIONS ACKNOWLEDGMENTS

59 Ackowledgemes A ga fom he compuaoal suppos of Naoal Cee fo Hgh-Pefomace Compug Tawa. 2 A ga fom he Tawa Naoal Scece Coucl ude he coac NSC E MY3 s gaefully appecaed. 3 We ae also hakful he asssace of he Chu-Y Wu Q. Y. Kuo Cheg-Shu Hug ad S. S. Tu.

60

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

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

( ) ( ) 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

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

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

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

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

Hydrodynamic Modeling: Hydrodynamic Equations. Prepared by Dragica Vasileska Professor Arizona State University

Hydrodynamic Modeling: Hydrodynamic Equations. Prepared by Dragica Vasileska Professor Arizona State University Hyoyamc Moelg: Hyoyamc Equaos Peae by Dagca Vasleska Poesso Azoa Sae Uesy D-Duso Aoaches Val he use aso omaes Exeso o DD Aoaches Valy Iouco o he el-eee mobly Velocy Sauao Imlcaos Velocy Sauao Dece Scalg

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

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

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

Lecture 10: Condensed matter systems

Lecture 10: Condensed matter systems Lectue 0: Codesed matte systems Itoducg matte ts codesed state.! Ams: " Idstgushable patcles ad the quatum atue of matte: # Cosequeces # Revew of deal gas etopy # Femos ad Bosos " Quatum statstcs. # Occupato

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

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

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

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

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

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

XII. Addition of many identical spins

XII. Addition of many identical spins XII. Addto of may detcal sps XII.. ymmetc goup ymmetc goup s the goup of all possble pemutatos of obects. I total! elemets cludg detty opeato. Each pemutato s a poduct of a ceta fte umbe of pawse taspostos.

More information

Quantum Mechanics II Lecture 11 Time-dependent perturbation theory. Time-dependent perturbation theory (degenerate or non-degenerate starting state)

Quantum Mechanics II Lecture 11 Time-dependent perturbation theory. Time-dependent perturbation theory (degenerate or non-degenerate starting state) Pro. O. B. Wrgh, Auum Quaum Mechacs II Lecure Tme-depede perurbao heory Tme-depede perurbao heory (degeerae or o-degeerae sarg sae) Cosder a sgle parcle whch, s uperurbed codo wh Hamloa H, ca exs a superposo

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

c-field descriptions of nonequilibrium polariton fluids

c-field descriptions of nonequilibrium polariton fluids c-feld descrpos of oequlbrum polaro fluds Mchel Wouers Iacopo Carusoo, Vcezo Savoa polaro characerscs Dsperso D / 1D / 0D Ieracos g=0.01 1 ev 1 mm -1 1 mev homogeeous broadeg (bu log lfe me) 0.x mev Polaro

More information

FALL HOMEWORK NO. 6 - SOLUTION Problem 1.: Use the Storage-Indication Method to route the Input hydrograph tabulated below.

FALL HOMEWORK NO. 6 - SOLUTION Problem 1.: Use the Storage-Indication Method to route the Input hydrograph tabulated below. Jorge A. Ramírez HOMEWORK NO. 6 - SOLUTION Problem 1.: Use he Sorage-Idcao Mehod o roue he Ipu hydrograph abulaed below. Tme (h) Ipu Hydrograph (m 3 /s) Tme (h) Ipu Hydrograph (m 3 /s) 0 0 90 450 6 50

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

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

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

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

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

Modern Energy Functional for Nuclei and Nuclear Matter. By: Alberto Hinojosa, Texas A&M University REU Cyclotron 2008 Mentor: Dr.

Modern Energy Functional for Nuclei and Nuclear Matter. By: Alberto Hinojosa, Texas A&M University REU Cyclotron 2008 Mentor: Dr. Moden Enegy Funconal fo Nucle and Nuclea Mae By: lbeo noosa Teas &M Unvesy REU Cycloon 008 Meno: D. Shalom Shlomo Oulne. Inoducon.. The many-body poblem and he aee-fock mehod. 3. Skyme neacon. 4. aee-fock

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

Tle Model Aalyss of Plasma-Suface I Oxde Echg Fluoocabo Plasm Auho(s) Fukumoo, Hosh Cao Kyoo Uvesy ( 京都大学 ) Issue Dae 2012-05-23 URL hps://do.og/10.14989/doco.k17 Rgh Type Thess o Dsseao Texveso auho Kyoo

More information

Mechanics and strength of materials

Mechanics and strength of materials 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

More information

Determination of Antoine Equation Parameters. December 4, 2012 PreFEED Corporation Yoshio Kumagae. Introduction

Determination of Antoine Equation Parameters. December 4, 2012 PreFEED Corporation Yoshio Kumagae. Introduction refeed Soluos for R&D o Desg Deermao of oe Equao arameers Soluos for R&D o Desg December 4, 0 refeed orporao Yosho Kumagae refeed Iroduco hyscal propery daa s exremely mpora for performg process desg ad

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

Redundancy System Fault Sampling Under Imperfect Maintenance

Redundancy System Fault Sampling Under Imperfect Maintenance A publcao of CHEMICAL EGIEERIG TRASACTIOS VOL. 33, 03 Gues Edors: Erco Zo, Pero Barald Copyrgh 03, AIDIC Servz S.r.l., ISB 978-88-95608-4-; ISS 974-979 The Iala Assocao of Chemcal Egeerg Ole a: www.adc./ce

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

Multiphase Flow Simulation Based on Unstructured Grid

Multiphase Flow Simulation Based on Unstructured Grid 200 Tuoral School o Flud Dyamcs: Topcs Turbulece Uversy of Marylad, May 24-28, 200 Oule Bacgroud Mulphase Flow Smulao Based o Usrucured Grd Bubble Pacg Mehod mehod Based o he Usrucured Grd Remar B CHEN,

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

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

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

The algebraic immunity of a class of correlation immune H Boolean functions

The algebraic immunity of a class of correlation immune H Boolean functions Ieraoal Coferece o Advaced Elecroc Scece ad Techology (AEST 06) The algebrac mmuy of a class of correlao mmue H Boolea fucos a Jgla Huag ad Zhuo Wag School of Elecrcal Egeerg Norhwes Uversy for Naoales

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

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

14. Poisson Processes

14. Poisson Processes 4. Posso Processes I Lecure 4 we roduced Posso arrvals as he lmg behavor of Bomal radom varables. Refer o Posso approxmao of Bomal radom varables. From he dscusso here see 4-6-4-8 Lecure 4 " arrvals occur

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

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

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

RECAPITULATION & CONDITIONAL PROBABILITY. Number of favourable events n E Total number of elementary events n S

RECAPITULATION & CONDITIONAL PROBABILITY. Number of favourable events n E Total number of elementary events n S Fomulae Fo u Pobablty By OP Gupta [Ida Awad We, +91-9650 350 480] Impotat Tems, Deftos & Fomulae 01 Bascs Of Pobablty: Let S ad E be the sample space ad a evet a expemet espectvely Numbe of favouable evets

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

Minimum Hyper-Wiener Index of Molecular Graph and Some Results on Szeged Related Index

Minimum Hyper-Wiener Index of Molecular Graph and Some Results on Szeged Related Index Joual of Multdscplay Egeeg Scece ad Techology (JMEST) ISSN: 359-0040 Vol Issue, Febuay - 05 Mmum Hype-Wee Idex of Molecula Gaph ad Some Results o eged Related Idex We Gao School of Ifomato Scece ad Techology,

More information

The Solutions of Initial Value Problems for Nonlinear Fourth-Order Impulsive Integro-Differential Equations in Banach Spaces

The Solutions of Initial Value Problems for Nonlinear Fourth-Order Impulsive Integro-Differential Equations in Banach Spaces WSEAS TRANSACTIONS o MATHEMATICS Zhag Lglg Y Jgy Lu Juguo The Soluos of Ial Value Pobles fo Nolea Fouh-Ode Ipulsve Iego-Dffeeal Equaos Baach Spaces Zhag Lglg Y Jgy Lu Juguo Depae of aheacs of Ta Yua Uvesy

More information

Molecular dynamics modeling of thermal and mechanical properties

Molecular dynamics modeling of thermal and mechanical properties Molecula dynamcs modelng of hemal and mechancal popees Alejando Sachan School of Maeals Engneeng Pudue Unvesy sachan@pudue.edu Maeals a molecula scales Molecula maeals Ceamcs Meals Maeals popees chas Maeals

More information

T h e C S E T I P r o j e c t

T h e C S E T I P r o j e c t T h e P r o j e c t T H E P R O J E C T T A B L E O F C O N T E N T S A r t i c l e P a g e C o m p r e h e n s i v e A s s es s m e n t o f t h e U F O / E T I P h e n o m e n o n M a y 1 9 9 1 1 E T

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

Parameter Estimation and Hypothesis Testing of Two Negative Binomial Distribution Population with Missing Data

Parameter Estimation and Hypothesis Testing of Two Negative Binomial Distribution Population with Missing Data Avlble ole wwwsceceeccom Physcs Poce 0 475 480 0 Ieol Cofeece o Mecl Physcs Bomecl ee Pmee smo Hyohess es of wo Neve Boml Dsbuo Poulo wh Mss D Zhwe Zho Collee of MhemcsJl Noml UvesyS Ch zhozhwe@6com Absc

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

Queuing Theory: Memory Buffer Limits on Superscalar Processing

Queuing Theory: Memory Buffer Limits on Superscalar Processing Cle/ Model of I/O Queug Theory: Memory Buffer Lms o Superscalar Processg Cle reques respose Devce Fas CPU s cle for slower I/O servces Buffer sores cle requess ad s a slower server respose rae Laecy Tme

More information

Verification and Validation of LAD2D Hydrocodes for Multi-material Compressible Flows

Verification and Validation of LAD2D Hydrocodes for Multi-material Compressible Flows 8 Ieaoal Cofeece o Physcs Maheacs Sascs Modellg ad Sulao (PMSMS 8) ISBN: 978--6595-558- Vefcao ad Valdao of ADD Hydocodes fo Mul-aeal Copessle Flows Ru-l WANG * ad Xao IANG Isue of Appled Physcs ad Copuaoal

More information

The Stability of High Order Max-Type Difference Equation

The Stability of High Order Max-Type Difference Equation Aled ad Comuaoal Maemacs 6; 5(): 5-55 ://wwwsceceulsggoucom/j/acm do: 648/jacm653 ISSN: 38-565 (P); ISSN: 38-563 (Ole) Te Saly of g Ode Ma-Tye Dffeece Equao a Ca-og * L Lue Ta Xue Scool of Maemacs ad Sascs

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

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

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

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

AML710 CAD LECTURE 12 CUBIC SPLINE CURVES. Cubic Splines Matrix formulation Normalised cubic splines Alternate end conditions Parabolic blending

AML710 CAD LECTURE 12 CUBIC SPLINE CURVES. Cubic Splines Matrix formulation Normalised cubic splines Alternate end conditions Parabolic blending CUIC SLINE CURVES Cubc Sples Marx formulao Normalsed cubc sples Alerae ed codos arabolc bledg AML7 CAD LECTURE CUIC SLINE The ame sple comes from he physcal srume sple drafsme use o produce curves A geeral

More information

Supplementary Information

Supplementary Information Supplemeay Ifomaio No-ivasive, asie deemiaio of he coe empeaue of a hea-geeaig solid body Dea Ahoy, Daipaya Saka, Aku Jai * Mechaical ad Aeospace Egieeig Depame Uivesiy of Texas a Aligo, Aligo, TX, USA.

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

Bianchi Type II Stiff Fluid Tilted Cosmological Model in General Relativity

Bianchi Type II Stiff Fluid Tilted Cosmological Model in General Relativity Ieraoal Joural of Mahemacs esearch. IN 0976-50 Volume 6, Number (0), pp. 6-7 Ieraoal esearch Publcao House hp://www.rphouse.com Bach ype II ff Flud led Cosmologcal Model Geeral elay B. L. Meea Deparme

More information

NUMERICAL SIMULATION OF TSUNAMI CURRENTS AROUND MOVING STRUCTURES

NUMERICAL SIMULATION OF TSUNAMI CURRENTS AROUND MOVING STRUCTURES NUMERICAL SIMULATION OF TSUNAMI CURRENTS AROUND MOVING STRUCTURES Ezo Nakaza 1, Tsuakyo Ibe ad Muhammad Abdu Rouf 1 The pape ams to smulate Tsuam cuets aoud movg ad fxed stuctues usg the movg-patcle semmplct

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

An Open cycle and Closed cycle Gas Turbine Engines. Methods to improve the performance of simple gas turbine plants

An Open cycle and Closed cycle Gas Turbine Engines. Methods to improve the performance of simple gas turbine plants An Open cycle and losed cycle Gas ubine Engines Mehods o impove he pefomance of simple gas ubine plans I egeneaive Gas ubine ycle: he empeaue of he exhaus gases in a simple gas ubine is highe han he empeaue

More information

Reliability Analysis. Basic Reliability Measures

Reliability Analysis. Basic Reliability Measures elably /6/ elably Aaly Perae faul Πelably decay Teporary faul ΠOfe Seady ae characerzao Deg faul Πelably growh durg eg & debuggg A pace hule Challeger Lauch, 986 Ocober 6, Bac elably Meaure elably:

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

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse

Asymptotic Behavior of Solutions of Nonlinear Delay Differential Equations With Impulse P a g e Vol Issue7Ver,oveber Global Joural of Scece Froer Research Asypoc Behavor of Soluos of olear Delay Dffereal Equaos Wh Ipulse Zhag xog GJSFR Classfcao - F FOR 3 Absrac Ths paper sudes he asypoc

More information

Op Amp Noise in Dynamic Range Maximization of Integrated Active-RC Filters

Op Amp Noise in Dynamic Range Maximization of Integrated Active-RC Filters Op Amp Nose Dyamc Rage Maxmzao of Iegaed Acve-R Fles N MARAOS* AND M MLADENO** * Naoal echcal Uvesy of Ahes Dep of Eleccal ad ompue Egeeg 9 Ioo Polyechou S ogafou 577 Ahes eece ** Depame of heoecal Elecoechcs

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

ESTIMATION OF PARAMETERS AND VERIFICATION OF STATISTICAL HYPOTHESES FOR GAUSSIAN MODELS OF STOCK PRICE

ESTIMATION OF PARAMETERS AND VERIFICATION OF STATISTICAL HYPOTHESES FOR GAUSSIAN MODELS OF STOCK PRICE Lhuaa Joual of Sascs Leuvos sasos daba 06, vol 55, o, pp 9 0 06, 55,, 9 0 p wwwsascsjouall ESTIMATIO OF PARAMETERS AD VERIFICATIO OF STATISTICAL YPOTESES FOR GAUSSIA MODELS OF STOCK PRICE Dmyo Maushevych,

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

The Mean Residual Lifetime of (n k + 1)-out-of-n Systems in Discrete Setting

The Mean Residual Lifetime of (n k + 1)-out-of-n Systems in Discrete Setting Appled Mahemacs 4 5 466-477 Publshed Ole February 4 (hp//wwwscrporg/oural/am hp//dxdoorg/436/am45346 The Mea Resdual Lfeme of ( + -ou-of- Sysems Dscree Seg Maryam Torab Sahboom Deparme of Sascs Scece ad

More information

VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS. Hunan , China,

VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS. Hunan , China, Mahemacal ad Compuaoal Applcaos Vol. 5 No. 5 pp. 834-839. Assocao for Scefc Research VARIATIONAL ITERATION METHOD FOR DELAY DIFFERENTIAL-ALGEBRAIC EQUATIONS Hoglag Lu Aguo Xao Yogxag Zhao School of Mahemacs

More information

Maximum likelihood estimate of phylogeny. BIOL 495S/ CS 490B/ MATH 490B/ STAT 490B Introduction to Bioinformatics April 24, 2002

Maximum likelihood estimate of phylogeny. BIOL 495S/ CS 490B/ MATH 490B/ STAT 490B Introduction to Bioinformatics April 24, 2002 Mmm lkelhood eme of phylogey BIO 9S/ S 90B/ MH 90B/ S 90B Iodco o Bofomc pl 00 Ovevew of he pobblc ppoch o phylogey o k ee ccodg o he lkelhood d ee whee d e e of eqece d ee by ee wh leve fo he eqece. he

More information

ESS 265 Spring Quarter 2005 Kinetic Simulations

ESS 265 Spring Quarter 2005 Kinetic Simulations SS 65 Spng Quae 5 Knec Sulaon Lecue une 9 5 An aple of an lecoagnec Pacle Code A an eaple of a knec ulaon we wll ue a one denonal elecoagnec ulaon code called KMPO deeloped b Yohhau Oua and Hoh Mauoo.

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

IMPROVED PORTFOLIO OPTIMIZATION MODEL WITH TRANSACTION COST AND MINIMAL TRANSACTION LOTS

IMPROVED PORTFOLIO OPTIMIZATION MODEL WITH TRANSACTION COST AND MINIMAL TRANSACTION LOTS Vol.7 No.4 (200) p73-78 Joural of Maageme Scece & Sascal Decso IMPROVED PORTFOLIO OPTIMIZATION MODEL WITH TRANSACTION COST AND MINIMAL TRANSACTION LOTS TIANXIANG YAO AND ZAIWU GONG College of Ecoomcs &

More information

Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations

Solution of Impulsive Differential Equations with Boundary Conditions in Terms of Integral Equations Joural of aheacs ad copuer Scece (4 39-38 Soluo of Ipulsve Dffereal Equaos wh Boudary Codos Ters of Iegral Equaos Arcle hsory: Receved Ocober 3 Acceped February 4 Avalable ole July 4 ohse Rabba Depare

More information

Fresnel Equations cont.

Fresnel Equations cont. Lecure 12 Chaper 4 Fresel quaos co. Toal eral refleco ad evaesce waves Opcal properes of meals Laer: Famlar aspecs of he eraco of lgh ad maer Fresel quaos r 2 Usg Sell s law, we ca re-wre: r s s r a a

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

Atomic units The atomic units have been chosen such that the fundamental electron properties are all equal to one atomic unit.

Atomic units The atomic units have been chosen such that the fundamental electron properties are all equal to one atomic unit. tomc uts The atomc uts have bee chose such that the fudametal electo popetes ae all equal to oe atomc ut. m e, e, h/, a o, ad the potetal eegy the hydoge atom e /a o. D3.33564 0-30 Cm The use of atomc

More information

Generalisation on the Zeros of a Family of Complex Polynomials

Generalisation on the Zeros of a Family of Complex Polynomials Ieol Joul of hemcs esech. ISSN 976-584 Volume 6 Numbe 4. 93-97 Ieol esech Publco House h://www.house.com Geelso o he Zeos of Fmly of Comlex Polyomls Aee sgh Neh d S.K.Shu Deme of hemcs Lgys Uvesy Fdbd-

More information

Photon Statistics. photons/s. Light beam stream of photons Difference with classical waves relies on different statistical properties

Photon Statistics. photons/s. Light beam stream of photons Difference with classical waves relies on different statistical properties hoo Sascs Lgh beam sream of phoos Dfferece wh classcal waves reles o dffere sascal properes Average cou rae correspods o Iesy of lgh beam Acual cou rae flucuaes from measureme o measureme The pulse aure

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

Quasiparticle Band Structures and the GW Approximation

Quasiparticle Band Structures and the GW Approximation Quapacle Ba Sucue a he W Appoxmao Ao Schlmay Iu fü Feöpefochug Fochugzeum Jülch 545 Jülch emay Ba-Sucue Meaueme Agle-Reolve (Ivee) Phooemo Specocopy Specum of a ω pl :plamoeegy Meaue bg eegy (ba ucue):

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

Survival Prediction Based on Compound Covariate under Cox Proportional Hazard Models

Survival Prediction Based on Compound Covariate under Cox Proportional Hazard Models Ieraoal Bomerc Coferece 22/8/3, Kobe JAPAN Survval Predco Based o Compoud Covarae uder Co Proporoal Hazard Models PLoS ONE 7. do:.37/oural.poe.47627. hp://d.plos.org/.37/oural.poe.47627 Takesh Emura Graduae

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

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

Computational Fluid Dynamics. Numerical Methods for Parabolic Equations. Numerical Methods for One-Dimensional Heat Equations

Computational Fluid Dynamics. Numerical Methods for Parabolic Equations. Numerical Methods for One-Dimensional Heat Equations Compuaoal Flud Dyamcs p://www.d.edu/~gyggva/cfd-couse/ Compuaoal Flud Dyamcs p://www.d.edu/~gyggva/cfd-couse/ Compuaoal Flud Dyamcs Numecal Meods o Paabolc Equaos Lecue Mac 6 7 Géa Tyggvaso Compuaoal Flud

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

θ = θ Π Π Parametric counting process models θ θ θ Log-likelihood: Consider counting processes: Score functions:

θ = θ Π Π Parametric counting process models θ θ θ Log-likelihood: Consider counting processes: Score functions: Paramerc coug process models Cosder coug processes: N,,..., ha cou he occurreces of a eve of eres for dvduals Iesy processes: Lelhood λ ( ;,,..., N { } λ < Log-lelhood: l( log L( Score fucos: U ( l( log

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