whch make the dyamc characterstcs of teso structures are obvously dfferet from those of brdges ad hgh-rsg buldgs, so tradtoal methods of radom vbrato

Size: px
Start display at page:

Download "whch make the dyamc characterstcs of teso structures are obvously dfferet from those of brdges ad hgh-rsg buldgs, so tradtoal methods of radom vbrato"

Transcription

1 The Seveth Iteratoal Colloquum o Bluff Body Aerodyamcs ad Applcatos (BBAA7) Shagha, Cha; September -6, 01 Numercal studes o the behavors of wd-structure teracto for membrae structures Xao-Yg SUN a, Zhao-Qg CEN b, Yue WU c ad Sh-Zhao SEN d a School of Cvl Egeerg, arb Isttuted of Techology, Cha, s _ht@163.com b School of Cvl Egeerg, arb Isttuted of Techology, Cha, chezhq004@163.com c School of Cvl Egeerg, arb Isttuted of Techology, Cha, wuyue_000@163.com d School of Cvl Egeerg, arb Isttuted of Techology, Cha, szshe@ht.edu.c ABSTRACT: I ths paper, a combed umercal approach o the tmedepedet flud-structure teracto for teso structures wth large dsplacemets s preseted. The geeral dea of ths approach s to dvde the structural respose uder wd actos to three compoets: mea respose, backgroud respose ad resoat respose. The frst compoet s a statc teracto process, whch s due to the chage of structural geometry uder mea wd pressure. The secod compoet ca be regard as a steady teracto process, whch relates to the moto of large scale eddes. The last compoet ca be called as a traset teracto process, whch the dyamc magfcato effect should be cosdered maly. Due to the dfferet characterstcs of each compoet, dfferet methods should be adopted respectvely. For statc ad steady teracto, the sutable method s CFD smulato, whch the wd pressure chage due to structural deformato wll be cosdered maly; for traset teracto, the sutable method s olear radom vbrato aalyss tme doma. Base upo the combed procedure, some umercal examples clude oe-way type roofs ad saddleshaped membrae structures are carred out fally. From the comparso wth drect umercal method, whch ca be see as a accurate method, t ca be cocluded that the results obtaed from the combed procedure are very close to the drect umercal method; moreover, the combed procedure seems easer for applcato. KEYWORDS: membrae structures; wd-structure teracto; CFD umercal smulato; aeroelastc effects; aerodyamc respose; geometrcal olearty 1 INTRODUCTION Membrae structures are the most wdely used log-spa teso structures. As beg characterzed by lghtweght ad flexble, they are hghly susceptble to the wd acto. ow to determe the aerostatc ad aerodyamc respose due to the wd acto s a major cocered problem for the desg of teso structures. Up to ow, comprehesve studes have bee performed, but the mechasm of wd-duced vbrato of membrae structures has ot bee recogzed eough detal. The ma reasos le two aspects: oe s the strogly geometrcal olearty, 34

2 whch make the dyamc characterstcs of teso structures are obvously dfferet from those of brdges ad hgh-rsg buldgs, so tradtoal methods of radom vbrato aalyss frequecy doma ca ot be used drectly. The other reaso s the weak local rgdty, whch ca make membrae structures produce rather large vbrato uder wd exctato. Sometme, these large vbratos ca eve affect the surroudg flud feld remarkably; that s to say, the wd-structure teracto or the aeroelastc effects ca ot be eglected. To solve the prevous problem, some olear radom vbrato aalyss methods tme doma have bee developed successfully [1]. But all those methods are based o the codto that the let flow or the wd pressure process has bee determed beforehad, so they ca ot cosder the fludstructure teracto actually. To determe the actual wd loads o teso structures, especally to reveal the mechasm of wd-structure teracto, some sem-emprcal methods have bee developed [], also some wd tuel tests has bee carred out [3]. owever, some uavodable errors wll occur whe usg smplfed methods, ad wd tuel tests are too expesve to carry out extesve studes, therefore those methods are oly lmted to certa specal structures. I recet years, wth the developmet of hgh speed computer ad umercal computatoal methods, t has bee avalable to tegrate computatoal flud dyamcs (CFD) ad computatoal structure dyamcs (CSD) techque to smulate structures ad surroudg flow smultaeously, whch s called as umercal wd tuel method. Comparg to those smplfed methods ad wd tuel tests, umercal wd tuel method ca solve flowg problems of complex geometrcal bodes wthout dsturbg the flud feld, costruct computatoal models whose dmeso are same as that of orgal structures so as to avod the smlarty requremets wd tuel test, completely cotrol the propertes of flud ad provde great flexblty for selectg flowg parameters to carry out parametrc aalyss. Because of these superor characterstcs, umercal wd tuel method s hghly valued by researches ad developed quckly. Now ths method has bee appled to solve some aeroelastc problems, such as for brdges [4] ad also for membrae structures [5]. But due to the tremedous calculate work, ths method also ca ot be used egeerg practce. I ths paper, a overvew of the studes o wd-structure teracto of teso structures s provded frstly. The a combed umercal approach based o CFD smulato method ad radom vbrato aalyss method s preseted. Fally, Base upo the combed procedure, some umercal examples clude oe-way type roofs ad saddle-shaped membrae structures are carred out. METODOOGY Wd-duced respose of teso structures ca be theoretcally descrbed as a problem of usteady couplg vbrato betwee compressble vscous flud ad geometrcal olear elastc body. Due to the flud forces ad structure dsplacemets o the terface betwee flud ad structure are ukow, t s mpossble to solve the flud feld ad structural feld separately, so we have to fd some methods that ca solve these two felds smultaeously. Udoubtedly, the umercal wd tuel method provdes a good platform for solvg ths problem. I Ref. [6], the author had developed a FEM program for calculatg two-dmeso problem. There were three modules cluded ths program, each for CFD, CSD ad CMD (Computatoal Mesh Dyamcs) calculato, respectvely. The flowchart s show fg.1. The dyamc flud-structure teracto was performed by a parttoed soluto approach, ad the tmedepedet smulato process was cotrolled by a terato procedure betwee these three modules utl covergece was reached each tme-step. Based o ths program, the aeroelastc re- 35

3 The Seveth Iteratoal Colloquum o Bluff Body Aerodyamcs ad Applcatos (BBAA7) Shagha, Cha; September -6, 01 spose of oe-way type pretesoed membrae roofs has bee studed. The effects of several factors, such as heght-spa rato, roof slope, roof mass ad preteso force et al, were vestgated. From these studes, some prelmary but very mportat coclusos about the mechasm of wd-structure teracto were obtaed [7]. Fg. 1 Flowchart of CFD smulato program The practcal cable/membrae structures are 3-dmesoal wth complcated surfaces. Usg the CFD smulato approach as metoed above to study the aeroelastc effects of 3-D structures has theoretcally possble, but wll be very dffcult practce at preset. Frstly, the tme-cosumg of smulatg 3-D problem s hudreds tmes of -D problem, whch ca ot be tolerated for systemcally studes. Secodly, the creasg computg tme wll cause lots of umercal dsspato ad error cumulato. So f we use the method proposed Ref. [9] to solve 3-D problem, t meas that all the umercal methods ths -D program should be mproved to get more computg effcecy ad precso, however the work s obvously eormous. At the same tme, there are two facts: (1) Varous CFD commercal software are developg quckly, they have provde more effcet umercal platform to solve flud problem, however, the problem of flud-structure teracto ca hardly be resolved by these software. () From the vewpot of egeerg, egeers usually do t cocer about the detals of couplg vbrato process but some statstc formato, such as the mea ad peak value, ad whether or whe wll the aeroelastc stablty occur. So t s possble to solve the couplg problem by aother ew method, whch s to adopt some smplfed aalytcal methods ad umercal methods to get the statstcal formato of the couplg process, ad gve up the smulato o wdstructure teracto detal. The precodto of ths method s to gve a reasoable explaato about the couplg mechasm of wd-structure teracto. Accordg to the wd-duced structural vbrato theory proposed by Daveport [8], the structural respose ca be broke to three compoets: mea respose r, backgroud respose r B ad resoat respose r R (Fg.). The mea respose s duced by average wd pressure, ad does ot chage wth tme. The backgroud resposes relates to the moto of large scale eddes, ad vary slowly ad rregularly wth tme. It s essetally a quas-statc process ad has o dyamc amplfcatory effect. The resoat respose usually happes at frequeces adjacet wth the structural atural frequecy, ad has obvous dyamc amplfcatory effect. If we assume that the wd-duced vbrato respose of membrae structures has the same characterstcs as metoed above, the dfferet methods ca be adopted for dfferet compoets to get the statstc formato separately. 36

4 Fg. Respose to wd For the mea respose, the couplg effects are maly duced by the structural average deformato, whch wll make the mea wd pressure chage cosequetly. It s a statc process ad ca be solved drectly by steady CFD umercal smulato wth several teratve steps. For the backgroud respose, the couplg effects are maly duced by the effect of the spatal correlato of fluctuatg wd, that s to say, we have to fd these crtcal dstrbutos of fluctuatg wd pressure whch ca make structure produce maxmum or mmum steady respose. It s a quas-statc process whch the dyamc amplfcatory effect ca be gored ad oly some modes of steady deformato are cosdered. For the resoat resposes, dyamc couplg betwee the hgher frequecy parts of fluctuatg wd ad structure s maly cosdered, t meas that the resoat respose of structure s maly duced by those small-scale eddes. Due to the effect of those small-scale eddes s a radom process, the sutable method for solvg the resoat resposes s olear radom vbrato aalyss methods tme doma. It s worth to expla that the calculato of each compoet wll based o the result of the calculato o the former compoet. To sum up, the wd-structure teracto ca be dvded to three parts (Fg.3): statc teracto, steady teracto ad traset teracto. Mea respose belogs to the statc teracto, backgroud respose belogs to the steady teracto, ad resoat respose belogs to traset teracto. The statc teracto ad the steady teracto should be studed specally by meas of CFD umercal smulato. The traset teracto should be studed by meas of olear radom smulato tme doma. Fg. 3 the sketch of wd-structure teracto 3 GENNERA FORMUATIONS 3.1 Statc Iteracto Statc teracto s expressed as follow: 37

5 The Seveth Iteratoal Colloquum o Bluff Body Aerodyamcs ad Applcatos (BBAA7) Shagha, Cha; September -6, 01 Ks0 x0 p (1) Where x0 s the mea respose; Ks0 ad p are the stffess ad mea wd pressure correspodg to the mea deformato respectvely; p ca be calculated by meas of CFD smulato. 3. Steady Iteracto Steady teracto s expressed as follow: Ks1 x1 () t p() t () Where p() t s the fluctuatg wd pressure, whch ca be calculated by CFD smulato. Accordg to the Proper Orthogoal Decomposto (POD) techque, p() t ca be decomposed as follow: pxyzt (,,, ) pˆ ( xyzt,,, ) a( t)g 1 1 (3) whereg s the th egemode of the wd pressure feld, ak () t s the correspodg prcpal coordate, pˆ () t s the wd pressure tme hstory correspodg to the th egemode, represets the domat wd pressure dstrbuto o structural surface. Substtute Eq.(3) to Eq.(), Eq.()ca be rewrtte as: s1 1 1 K x t pˆ t (4) Assumg the steady deformato s the summato of the effects of each egemode ˆ s1 1 K x t p t x 1 () t x 1 () t (5) 1 where x () 1 t s defed as the tme-hstory of the quas-statc respose duced by the th egemode. The the varace of backgroud respose 1 ca be expressed as (6) s1 where 1 s the varace of steady deformato x 1 () t duced by the th egemode. So the followg formula ca be used to estmate the cotrbuto of each egemode to the whole steady deformato. 1 1 (7) 1 Accordg to the POD techque, Eq. (4) ca be expressed as: Ks 1 x1 t a()g t (8) From Eq. (8), t s educed that the vbrato mode of x 1 () t s determed by the stffess K ad the th egemode G, ad the vbrato ampltude of x () 1 t s determed by the prcpal coordate () fdg the momet a t. So the maxmal steady deformato 1 j t, whch s correspodg to the peak value of a () t. j x t of x () 1 t ca be determed by 38

6 3.3 Traset Iteracto Traset teracto s expressed as follow: M x t C x t K x t p t, x t, x t, x t (9) s s s,,,,, p t x t x t x t p t f x t x t x t (10) Where x () t s traset deformato relatve to the peak steady deformato of the th egemode; ~ p ( ) represets the hgh frequecy part fluctuatg wd cludg the moto-duced aerodyamc force; ~ p ( ) ca be decomposed to p () t whch does ot cosder the structure vbrato ad f ( ) whch s duced by structure vbrato. p () t s gaed from the hgh frequecy parts of results of CFD smulato, whch based o the form correspodg to each peak steady respose; f ( ) s added aerodyamc term whch ca be trasformed to added mass M a ad aerodyamc damp Eq.(8)ca be rewrtte as: C a by meas of smplfed aeroelastc model theory[9]. So ( M s M ) a x() t ( Cs Ca) x () t Ksx() t p () t (11) It s especally emphaszed that traset teracto s based o the possble peak steady deformato of the th egemode x x ( ) 1 tj,.e. dfferet x x ( ) 1 tj correspod to dfferet traset teracto respose. 3.4 Peak Respose The peak respose of structure s solved by meas of superposto theory after gettg x, x1 t ad x t : xmax x 1 max (1) 1 Based o the theory metoed above, the flowchart of the combed umercal approach s show as fgure 4. Fg. 4 Flowchart of the combed umercal approach 39

7 The Seveth Iteratoal Colloquum o Bluff Body Aerodyamcs ad Applcatos (BBAA7) Shagha, Cha; September -6, 01 4 NUMERICA EXAMPE 4.1 Couplg Effects of Oe-Way type roofs The roof spa s 40m ad 10m hgh, the computatoal doma s show fgure 5. The flow 0.16 velocty profle s defed by V ( y) 30( y /10) m/s leadg to a velocty value of 30m/s at 7 roof level. Thus, the Reyolds umber becomes Re The fxed wall s assumed as oslp flow boudary, local oe-way codto s adopted o the boudary of the outlet, ad the gradet of flow speed of the outlet s zero; o-dmesoal tme step t ere we assume the roof s a cable structure, the mass per legth g s 5kg/m, the prestressg teso force T s 0kN. Accordg to the results of computato, the frst ad secod frequecy of structure s 0.8z ad.34z, respectvely. Fgure 6 shows the streamle drawg of flow aroud the fxed roof, t meas that the couplg effect does ot bee cosdered. Fgure 7 shows the streamle drawg of flow aroud the elastc roof wth the cosderato of couplg effect. It ca be see that, because the shape of the elastc roof chages wth wd acto, whch drectly chage the boudary of the flud feld, so the characterstcs of flow aroud a elastc roof s much dfferet from those of rgd roof. For the elastc roof, the separato pot of arflow appears at the back of the frot of the roof, ad the effects of vortex droppg weake sgfcatly. The whole average wg pressure o the elastc roof s close to that of rgd roof, but the pulse wd pressure decrease sgfcatly, whch llustrates that whe vortex dowstream alog the roof, couplg effect duced eergy dsspato lead to mor pulse pressure. Fg. 5 Computatoal doma for flow aroud a oe-way type roof It worth to be explaed that the above result was gotte from the method ref. [6], here we call t as drect umercal method, whch ca be see as a accurate method. It ca be see that by the drect umercal method, we ca get the etre formato of the couplg process. But from the vewpot of egeerg, we usually oly cocer about those statstc formato, such as the mea ad peak value, t meas that we sped a large amout of tme to get those useless formato. Next, the combed procedure proposed ths paper wll be adopted to calculate that statstc formato. The result s show fgure 8. It ca be see that the result of combed approach seems very close to that of drect umercal method, but qute dfferet to the result of radom vbrato aalyss. It shows that by usg the combed approach we ca also get farly accurate result, ad the tme cosumg by ths method s qute small compare to the drect umercal method. 40

8 Fg. 6 Streamle aroud the fxed roof Fg. 7 Streamle aroud the elastc roof We also calculate the oe-way type roof wth 1/10 sag (as show fg. 9) ad wth 1/10 rse (as show fg. 10). It ca be see that for these two dfferet shape roofs, the combed procedure ca get very close results to that of accurate method. For the arch-shaped roof, the effect of flud-structure teracto seams very small, t ca be explaed that the roof shape plays a mportat role to the couplg effect. The couplg effect wll chage the structural shape from bluff body to streamled body, f the structural shape close to streamle body, the the couplg effect wll be small. Dsplacemet (m) Drect Numercal Smulato(cosderg FSI) Radom Smulato tme doma(wthout cosderg FSI) Combed Numercal Approach(cosderg FSI) x/ Dsplacemet (m) Drect Numercal Smulato(cosderg FSI) Radom Smulato tme doma(wthout cosderg FSI) Combed Numercal Approach(cosderg FSI) x/ Dsplacemet (m) Drect Numercal Smulato(cosderg FSI) Radom Smulato tme doma(wthout cosderg FSI) Combed Numercal Approach(cosderg FSI) x/ Fg. 8 Maxmum respose of flat roof Fg. 9 Maxmum respose of suspeso roof Fg. 10 Maxmum respose of arch roof 4. Couplg Effects of Shaddle-Shape Membrae Structures The roof spa s 8m, the rato of sag to spa (f/) s 1/16, the mass per area s 1.5kg/m, the teso force s.5kn/m. The frst ad secod frequecy of structure s.6z ad 3.03z, respectvely. The calculate model s show fgure 10. The other calculate parameters are same as the two-way type roof. Fg. 10 The calculate model Fgure 11 shows the maxmum dsplacemet of membrae structure calculated by these three methods. It ca be see that the couplg effect of 3-D structures seems more complcate tha - D structures, but f we compare the maxmum dsplacemet pot betwee the results of these three methods, t s also show that the result from combed procedure seems farly close to the drect umercal method, but larger tha the result of radom vbrato aalyss. 41

9 The Seveth Iteratoal Colloquum o Bluff Body Aerodyamcs ad Applcatos (BBAA7) Shagha, Cha; September -6, 01 a) Combed Approach b) Drect Numercal Method c) Radom vbrato aalyss Fg. 11 Maxmum dsplacemet o roof by dfferet methods 5 CONCUSION I ths paper, a combed umercal approach for solvg the flud-structure teracto for teso structures was proposed. Wth the comparso to the drect umercal method ad radom vbrato method, t ca be see that the combed approach seems more accurate tha the radom vbrato method ad more effcet tha the drect umercal method. Accordg to the calculate result of two-way type, t ca be coclude that the couplg effect tred to chage the structural shape from bluff body to streamled body, so f the structural shape close to streamle body, the the couplg effect wll be small. ACKNOWEDGEMENTS The vestgato s supported by the Natoal Scece Fud Coucl of People s Republc of Cha uder Cotract No ad No REFERENCE 1 S.Z. She ad Q.S. Yag (1999), Wd-duced Respose Aalyss ad Wd-resstat Desg of yperbolc Parabolod Cable Net Structures, It. J. Space Structures, 14(1), T. Matsumoto (1990), Self-excted Oscllato of a Pretesoed Cable Roof wth Sgle Curvature Smooth Flow, J. Wd Eg. Id. Aerody., 34 (3), P. A.. Irw ad R.. Wardlaw (1981), A Wd Tuel Ivestgato of a Retractable Fabrc Roof for the Motreal Olympc Stadum, Proc. 5th It. Cof. o Wd Eg., Pergamo, A. arse (1998), Computer Smulato of Wd-Structure Iteracto Brdge Aerodyamcs, J. Struct. Egrg. IABSE, 8(), M. Glück, M. Breuer, F. Durst, A. alfma, E. Rak (001), Computato of Flud- Structure Iteracto o ghtweght Structures, J. Wd Eg. Id. Aerody, 89(14-15): Y. Wu ad S. Z. She (005), Computato of Wd-Structure Iteracto o Teso Structures, Proc. 6th Asa-Pacfc Coferece o Wd Egeerg. Seoul, Korea, Y. Wu ad S. Z. She (006). Numercal studes o the behavors of wd-structure teracto for oe-way type roofs. Proc. 4th It. Cof. o Computatoal Wd 4

10 Egeerg. Yokohama, Japa, A. G. Daveport (1967), Gust oadg Factor, J. Struct. Dv. ASCE., 93(ST3), Wu, Y., Yag, Q. S. et al, Studes o Wd-Structure Iteracto by Wd Tuel Tests, Proceedgs of the 11th Natoal Coferece o Wd Egeerg, Saya, Cha, 003. ( Chese) 43

Dynamic Analysis of Axially Beam on Visco - Elastic Foundation with Elastic Supports under Moving Load

Dynamic Analysis of Axially Beam on Visco - Elastic Foundation with Elastic Supports under Moving Load Dyamc Aalyss of Axally Beam o Vsco - Elastc Foudato wth Elastc Supports uder Movg oad Saeed Mohammadzadeh, Seyed Al Mosayeb * Abstract: For dyamc aalyses of ralway track structures, the algorthm of soluto

More information

A Method for Damping Estimation Based On Least Square Fit

A Method for Damping Estimation Based On Least Square Fit Amerca Joural of Egeerg Research (AJER) 5 Amerca Joural of Egeerg Research (AJER) e-issn: 3-847 p-issn : 3-936 Volume-4, Issue-7, pp-5-9 www.ajer.org Research Paper Ope Access A Method for Dampg Estmato

More information

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory

C-1: Aerodynamics of Airfoils 1 C-2: Aerodynamics of Airfoils 2 C-3: Panel Methods C-4: Thin Airfoil Theory ROAD MAP... AE301 Aerodyamcs I UNIT C: 2-D Arfols C-1: Aerodyamcs of Arfols 1 C-2: Aerodyamcs of Arfols 2 C-3: Pael Methods C-4: Th Arfol Theory AE301 Aerodyamcs I Ut C-3: Lst of Subects Problem Solutos?

More information

Functions of Random Variables

Functions of Random Variables Fuctos of Radom Varables Chapter Fve Fuctos of Radom Varables 5. Itroducto A geeral egeerg aalyss model s show Fg. 5.. The model output (respose) cotas the performaces of a system or product, such as weght,

More information

2C09 Design for seismic and climate changes

2C09 Design for seismic and climate changes 2C09 Desg for sesmc ad clmate chages Lecture 08: Sesmc aalyss of elastc MDOF systems Aurel Strata, Poltehca Uversty of Tmsoara 06/04/2017 Europea Erasmus Mudus Master Course Sustaable Costructos uder atural

More information

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions

Estimation of Stress- Strength Reliability model using finite mixture of exponential distributions Iteratoal Joural of Computatoal Egeerg Research Vol, 0 Issue, Estmato of Stress- Stregth Relablty model usg fte mxture of expoetal dstrbutos K.Sadhya, T.S.Umamaheswar Departmet of Mathematcs, Lal Bhadur

More information

Ahmed Elgamal. MDOF Systems & Modal Analysis

Ahmed Elgamal. MDOF Systems & Modal Analysis DOF Systems & odal Aalyss odal Aalyss (hese otes cover sectos from Ch. 0, Dyamcs of Structures, Al Chopra, Pretce Hall, 995). Refereces Dyamcs of Structures, Al K. Chopra, Pretce Hall, New Jersey, ISBN

More information

Introduction to local (nonparametric) density estimation. methods

Introduction to local (nonparametric) density estimation. methods Itroducto to local (oparametrc) desty estmato methods A slecture by Yu Lu for ECE 66 Sprg 014 1. Itroducto Ths slecture troduces two local desty estmato methods whch are Parze desty estmato ad k-earest

More information

CHAPTER VI Statistical Analysis of Experimental Data

CHAPTER VI Statistical Analysis of Experimental Data Chapter VI Statstcal Aalyss of Expermetal Data CHAPTER VI Statstcal Aalyss of Expermetal Data Measuremets do ot lead to a uque value. Ths s a result of the multtude of errors (maly radom errors) that ca

More information

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines

Solving Constrained Flow-Shop Scheduling. Problems with Three Machines It J Cotemp Math Sceces, Vol 5, 2010, o 19, 921-929 Solvg Costraed Flow-Shop Schedulg Problems wth Three Maches P Pada ad P Rajedra Departmet of Mathematcs, School of Advaced Sceces, VIT Uversty, Vellore-632

More information

DYNAMIC ANALYSIS OF CONCRETE RECTANGULAR LIQUID STORAGE TANKS

DYNAMIC ANALYSIS OF CONCRETE RECTANGULAR LIQUID STORAGE TANKS The 4 th World Coferece o Earthquake Egeerg October 2-7, 28, Bejg, Cha DYNAMIC ANAYSIS OF CONCRETE RECTANGUAR IQUID STORAGE TANKS J.Z. Che, A.R. Ghaemmagham 2 ad M.R. Kaoush 3 Structural Egeer, C2M I Caada,

More information

MOLECULAR VIBRATIONS

MOLECULAR VIBRATIONS MOLECULAR VIBRATIONS Here we wsh to vestgate molecular vbratos ad draw a smlarty betwee the theory of molecular vbratos ad Hückel theory. 1. Smple Harmoc Oscllator Recall that the eergy of a oe-dmesoal

More information

Chapter 2 - Free Vibration of Multi-Degree-of-Freedom Systems - II

Chapter 2 - Free Vibration of Multi-Degree-of-Freedom Systems - II CEE49b Chapter - Free Vbrato of Mult-Degree-of-Freedom Systems - II We ca obta a approxmate soluto to the fudametal atural frequecy through a approxmate formula developed usg eergy prcples by Lord Raylegh

More information

ECONOMETRIC THEORY. MODULE VIII Lecture - 26 Heteroskedasticity

ECONOMETRIC THEORY. MODULE VIII Lecture - 26 Heteroskedasticity ECONOMETRIC THEORY MODULE VIII Lecture - 6 Heteroskedastcty Dr. Shalabh Departmet of Mathematcs ad Statstcs Ida Isttute of Techology Kapur . Breusch Paga test Ths test ca be appled whe the replcated data

More information

Research on SVM Prediction Model Based on Chaos Theory

Research on SVM Prediction Model Based on Chaos Theory Advaced Scece ad Techology Letters Vol.3 (SoftTech 06, pp.59-63 http://dx.do.org/0.457/astl.06.3.3 Research o SVM Predcto Model Based o Chaos Theory Sog Lagog, Wu Hux, Zhag Zezhog 3, College of Iformato

More information

A Study of the Reproducibility of Measurements with HUR Leg Extension/Curl Research Line

A Study of the Reproducibility of Measurements with HUR Leg Extension/Curl Research Line HUR Techcal Report 000--9 verso.05 / Frak Borg (borgbros@ett.f) A Study of the Reproducblty of Measuremets wth HUR Leg Eteso/Curl Research Le A mportat property of measuremets s that the results should

More information

LINEAR REGRESSION ANALYSIS

LINEAR REGRESSION ANALYSIS LINEAR REGRESSION ANALYSIS MODULE V Lecture - Correctg Model Iadequaces Through Trasformato ad Weghtg Dr. Shalabh Departmet of Mathematcs ad Statstcs Ida Isttute of Techology Kapur Aalytcal methods for

More information

Convergence of the Desroziers scheme and its relation to the lag innovation diagnostic

Convergence of the Desroziers scheme and its relation to the lag innovation diagnostic Covergece of the Desrozers scheme ad ts relato to the lag ovato dagostc chard Méard Evromet Caada, Ar Qualty esearch Dvso World Weather Ope Scece Coferece Motreal, August 9, 04 o t t O x x x y x y Oservato

More information

Comparison of Dual to Ratio-Cum-Product Estimators of Population Mean

Comparison of Dual to Ratio-Cum-Product Estimators of Population Mean Research Joural of Mathematcal ad Statstcal Sceces ISS 30 6047 Vol. 1(), 5-1, ovember (013) Res. J. Mathematcal ad Statstcal Sc. Comparso of Dual to Rato-Cum-Product Estmators of Populato Mea Abstract

More information

Block-Based Compact Thermal Modeling of Semiconductor Integrated Circuits

Block-Based Compact Thermal Modeling of Semiconductor Integrated Circuits Block-Based Compact hermal Modelg of Semcoductor Itegrated Crcuts Master s hess Defese Caddate: Jg Ba Commttee Members: Dr. Mg-Cheg Cheg Dr. Daqg Hou Dr. Robert Schllg July 27, 2009 Outle Itroducto Backgroud

More information

Chapter 4 (Part 1): Non-Parametric Classification (Sections ) Pattern Classification 4.3) Announcements

Chapter 4 (Part 1): Non-Parametric Classification (Sections ) Pattern Classification 4.3) Announcements Aoucemets No-Parametrc Desty Estmato Techques HW assged Most of ths lecture was o the blacboard. These sldes cover the same materal as preseted DHS Bometrcs CSE 90-a Lecture 7 CSE90a Fall 06 CSE90a Fall

More information

Engineering Vibration 1. Introduction

Engineering Vibration 1. Introduction Egeerg Vbrato. Itroducto he study of the moto of physcal systems resultg from the appled forces s referred to as dyamcs. Oe type of dyamcs of physcal systems s vbrato, whch the system oscllates about certa

More information

Beam Warming Second-Order Upwind Method

Beam Warming Second-Order Upwind Method Beam Warmg Secod-Order Upwd Method Petr Valeta Jauary 6, 015 Ths documet s a part of the assessmet work for the subject 1DRP Dfferetal Equatos o Computer lectured o FNSPE CTU Prague. Abstract Ths documet

More information

Bayes Interval Estimation for binomial proportion and difference of two binomial proportions with Simulation Study

Bayes Interval Estimation for binomial proportion and difference of two binomial proportions with Simulation Study IJIEST Iteratoal Joural of Iovatve Scece, Egeerg & Techology, Vol. Issue 5, July 04. Bayes Iterval Estmato for bomal proporto ad dfferece of two bomal proportos wth Smulato Study Masoud Gaj, Solmaz hlmad

More information

d dt d d dt dt Also recall that by Taylor series, / 2 (enables use of sin instead of cos-see p.27 of A&F) dsin

d dt d d dt dt Also recall that by Taylor series, / 2 (enables use of sin instead of cos-see p.27 of A&F) dsin Learzato of the Swg Equato We wll cover sectos.5.-.6 ad begg of Secto 3.3 these otes. 1. Sgle mache-fte bus case Cosder a sgle mache coected to a fte bus, as show Fg. 1 below. E y1 V=1./_ Fg. 1 The admttace

More information

Bayes Estimator for Exponential Distribution with Extension of Jeffery Prior Information

Bayes Estimator for Exponential Distribution with Extension of Jeffery Prior Information Malaysa Joural of Mathematcal Sceces (): 97- (9) Bayes Estmator for Expoetal Dstrbuto wth Exteso of Jeffery Pror Iformato Hadeel Salm Al-Kutub ad Noor Akma Ibrahm Isttute for Mathematcal Research, Uverst

More information

L5 Polynomial / Spline Curves

L5 Polynomial / Spline Curves L5 Polyomal / Sple Curves Cotets Coc sectos Polyomal Curves Hermte Curves Bezer Curves B-Sples No-Uform Ratoal B-Sples (NURBS) Mapulato ad Represetato of Curves Types of Curve Equatos Implct: Descrbe a

More information

MEASURES OF DISPERSION

MEASURES OF DISPERSION MEASURES OF DISPERSION Measure of Cetral Tedecy: Measures of Cetral Tedecy ad Dsperso ) Mathematcal Average: a) Arthmetc mea (A.M.) b) Geometrc mea (G.M.) c) Harmoc mea (H.M.) ) Averages of Posto: a) Meda

More information

LECTURE - 4 SIMPLE RANDOM SAMPLING DR. SHALABH DEPARTMENT OF MATHEMATICS AND STATISTICS INDIAN INSTITUTE OF TECHNOLOGY KANPUR

LECTURE - 4 SIMPLE RANDOM SAMPLING DR. SHALABH DEPARTMENT OF MATHEMATICS AND STATISTICS INDIAN INSTITUTE OF TECHNOLOGY KANPUR amplg Theory MODULE II LECTURE - 4 IMPLE RADOM AMPLIG DR. HALABH DEPARTMET OF MATHEMATIC AD TATITIC IDIA ITITUTE OF TECHOLOGY KAPUR Estmato of populato mea ad populato varace Oe of the ma objectves after

More information

2006 Jamie Trahan, Autar Kaw, Kevin Martin University of South Florida United States of America

2006 Jamie Trahan, Autar Kaw, Kevin Martin University of South Florida United States of America SOLUTION OF SYSTEMS OF SIMULTANEOUS LINEAR EQUATIONS Gauss-Sedel Method 006 Jame Traha, Autar Kaw, Kev Mart Uversty of South Florda Uted States of Amerca kaw@eg.usf.edu Itroducto Ths worksheet demostrates

More information

Generating Multivariate Nonnormal Distribution Random Numbers Based on Copula Function

Generating Multivariate Nonnormal Distribution Random Numbers Based on Copula Function 7659, Eglad, UK Joural of Iformato ad Computg Scece Vol. 2, No. 3, 2007, pp. 9-96 Geeratg Multvarate Noormal Dstrbuto Radom Numbers Based o Copula Fucto Xaopg Hu +, Jam He ad Hogsheg Ly School of Ecoomcs

More information

Analysis of Variance with Weibull Data

Analysis of Variance with Weibull Data Aalyss of Varace wth Webull Data Lahaa Watthaacheewaul Abstract I statstcal data aalyss by aalyss of varace, the usual basc assumptos are that the model s addtve ad the errors are radomly, depedetly, ad

More information

A New Family of Transformations for Lifetime Data

A New Family of Transformations for Lifetime Data Proceedgs of the World Cogress o Egeerg 4 Vol I, WCE 4, July - 4, 4, Lodo, U.K. A New Famly of Trasformatos for Lfetme Data Lakhaa Watthaacheewakul Abstract A famly of trasformatos s the oe of several

More information

{ }{ ( )} (, ) = ( ) ( ) ( ) Chapter 14 Exercises in Sampling Theory. Exercise 1 (Simple random sampling): Solution:

{ }{ ( )} (, ) = ( ) ( ) ( ) Chapter 14 Exercises in Sampling Theory. Exercise 1 (Simple random sampling): Solution: Chapter 4 Exercses Samplg Theory Exercse (Smple radom samplg: Let there be two correlated radom varables X ad A sample of sze s draw from a populato by smple radom samplg wthout replacemet The observed

More information

SPATIAL RAINFALL FIELD SIMULATION WITH RANDOM CASCADE INTRODUCING OROGRAPHIC EFFECTS ON RAINFAL

SPATIAL RAINFALL FIELD SIMULATION WITH RANDOM CASCADE INTRODUCING OROGRAPHIC EFFECTS ON RAINFAL Proc. of the d Asa Pacfc Assocato of Hydrology ad Water Resources (APHW) Coferece, July 5-8, 4, Sutec Sgapore Iteratoal Coveto Exhbto Cetre, Sgapore, vol., pp. 67-64, 4 SPATIAL RAINFALL FIELD SIMULATION

More information

Lecture 3. Sampling, sampling distributions, and parameter estimation

Lecture 3. Sampling, sampling distributions, and parameter estimation Lecture 3 Samplg, samplg dstrbutos, ad parameter estmato Samplg Defto Populato s defed as the collecto of all the possble observatos of terest. The collecto of observatos we take from the populato s called

More information

Simulation Output Analysis

Simulation Output Analysis Smulato Output Aalyss Summary Examples Parameter Estmato Sample Mea ad Varace Pot ad Iterval Estmato ermatg ad o-ermatg Smulato Mea Square Errors Example: Sgle Server Queueg System x(t) S 4 S 4 S 3 S 5

More information

Point Estimation: definition of estimators

Point Estimation: definition of estimators Pot Estmato: defto of estmators Pot estmator: ay fucto W (X,..., X ) of a data sample. The exercse of pot estmato s to use partcular fuctos of the data order to estmate certa ukow populato parameters.

More information

Econometric Methods. Review of Estimation

Econometric Methods. Review of Estimation Ecoometrc Methods Revew of Estmato Estmatg the populato mea Radom samplg Pot ad terval estmators Lear estmators Ubased estmators Lear Ubased Estmators (LUEs) Effcecy (mmum varace) ad Best Lear Ubased Estmators

More information

( q Modal Analysis. Eigenvectors = Mode Shapes? Eigenproblem (cont) = x x 2 u 2. u 1. x 1 (4.55) vector and M and K are matrices.

( q Modal Analysis. Eigenvectors = Mode Shapes? Eigenproblem (cont) = x x 2 u 2. u 1. x 1 (4.55) vector and M and K are matrices. 4.3 - Modal Aalyss Physcal coordates are ot always the easest to work Egevectors provde a coveet trasformato to modal coordates Modal coordates are lear combato of physcal coordates Say we have physcal

More information

Comparing Different Estimators of three Parameters for Transmuted Weibull Distribution

Comparing Different Estimators of three Parameters for Transmuted Weibull Distribution Global Joural of Pure ad Appled Mathematcs. ISSN 0973-768 Volume 3, Number 9 (207), pp. 55-528 Research Ida Publcatos http://www.rpublcato.com Comparg Dfferet Estmators of three Parameters for Trasmuted

More information

Unimodality Tests for Global Optimization of Single Variable Functions Using Statistical Methods

Unimodality Tests for Global Optimization of Single Variable Functions Using Statistical Methods Malaysa Umodalty Joural Tests of Mathematcal for Global Optmzato Sceces (): of 05 Sgle - 5 Varable (007) Fuctos Usg Statstcal Methods Umodalty Tests for Global Optmzato of Sgle Varable Fuctos Usg Statstcal

More information

Summary of the lecture in Biostatistics

Summary of the lecture in Biostatistics Summary of the lecture Bostatstcs Probablty Desty Fucto For a cotuos radom varable, a probablty desty fucto s a fucto such that: 0 dx a b) b a dx A probablty desty fucto provdes a smple descrpto of the

More information

Simple Linear Regression

Simple Linear Regression Statstcal Methods I (EST 75) Page 139 Smple Lear Regresso Smple regresso applcatos are used to ft a model descrbg a lear relatoshp betwee two varables. The aspects of least squares regresso ad correlato

More information

FREQUENCY ANALYSIS OF A DOUBLE-WALLED NANOTUBES SYSTEM

FREQUENCY ANALYSIS OF A DOUBLE-WALLED NANOTUBES SYSTEM Joural of Appled Matematcs ad Computatoal Mecacs 04, 3(4), 7-34 FREQUENCY ANALYSIS OF A DOUBLE-WALLED NANOTUBES SYSTEM Ata Cekot, Stasław Kukla Isttute of Matematcs, Czestocowa Uversty of Tecology Częstocowa,

More information

A Robust Total Least Mean Square Algorithm For Nonlinear Adaptive Filter

A Robust Total Least Mean Square Algorithm For Nonlinear Adaptive Filter A Robust otal east Mea Square Algorthm For Nolear Adaptve Flter Ruxua We School of Electroc ad Iformato Egeerg X'a Jaotog Uversty X'a 70049, P.R. Cha rxwe@chare.com Chogzhao Ha, azhe u School of Electroc

More information

Bounds on the expected entropy and KL-divergence of sampled multinomial distributions. Brandon C. Roy

Bounds on the expected entropy and KL-divergence of sampled multinomial distributions. Brandon C. Roy Bouds o the expected etropy ad KL-dvergece of sampled multomal dstrbutos Brado C. Roy bcroy@meda.mt.edu Orgal: May 18, 2011 Revsed: Jue 6, 2011 Abstract Iformato theoretc quattes calculated from a sampled

More information

PTAS for Bin-Packing

PTAS for Bin-Packing CS 663: Patter Matchg Algorthms Scrbe: Che Jag /9/00. Itroducto PTAS for B-Packg The B-Packg problem s NP-hard. If we use approxmato algorthms, the B-Packg problem could be solved polyomal tme. For example,

More information

TESTS BASED ON MAXIMUM LIKELIHOOD

TESTS BASED ON MAXIMUM LIKELIHOOD ESE 5 Toy E. Smth. The Basc Example. TESTS BASED ON MAXIMUM LIKELIHOOD To llustrate the propertes of maxmum lkelhood estmates ad tests, we cosder the smplest possble case of estmatg the mea of the ormal

More information

Feature Selection: Part 2. 1 Greedy Algorithms (continued from the last lecture)

Feature Selection: Part 2. 1 Greedy Algorithms (continued from the last lecture) CSE 546: Mache Learg Lecture 6 Feature Selecto: Part 2 Istructor: Sham Kakade Greedy Algorthms (cotued from the last lecture) There are varety of greedy algorthms ad umerous amg covetos for these algorthms.

More information

UNIT 2 SOLUTION OF ALGEBRAIC AND TRANSCENDENTAL EQUATIONS

UNIT 2 SOLUTION OF ALGEBRAIC AND TRANSCENDENTAL EQUATIONS Numercal Computg -I UNIT SOLUTION OF ALGEBRAIC AND TRANSCENDENTAL EQUATIONS Structure Page Nos..0 Itroducto 6. Objectves 7. Ital Approxmato to a Root 7. Bsecto Method 8.. Error Aalyss 9.4 Regula Fals Method

More information

MULTIDIMENSIONAL HETEROGENEOUS VARIABLE PREDICTION BASED ON EXPERTS STATEMENTS. Gennadiy Lbov, Maxim Gerasimov

MULTIDIMENSIONAL HETEROGENEOUS VARIABLE PREDICTION BASED ON EXPERTS STATEMENTS. Gennadiy Lbov, Maxim Gerasimov Iteratoal Boo Seres "Iformato Scece ad Computg" 97 MULTIIMNSIONAL HTROGNOUS VARIABL PRICTION BAS ON PRTS STATMNTS Geady Lbov Maxm Gerasmov Abstract: I the wors [ ] we proposed a approach of formg a cosesus

More information

Comparison of Parameters of Lognormal Distribution Based On the Classical and Posterior Estimates

Comparison of Parameters of Lognormal Distribution Based On the Classical and Posterior Estimates Joural of Moder Appled Statstcal Methods Volume Issue Artcle 8 --03 Comparso of Parameters of Logormal Dstrbuto Based O the Classcal ad Posteror Estmates Raja Sulta Uversty of Kashmr, Sragar, Ida, hamzasulta8@yahoo.com

More information

Bootstrap Method for Testing of Equality of Several Coefficients of Variation

Bootstrap Method for Testing of Equality of Several Coefficients of Variation Cloud Publcatos Iteratoal Joural of Advaced Mathematcs ad Statstcs Volume, pp. -6, Artcle ID Sc- Research Artcle Ope Access Bootstrap Method for Testg of Equalty of Several Coeffcets of Varato Dr. Navee

More information

Analysis of Lagrange Interpolation Formula

Analysis of Lagrange Interpolation Formula P IJISET - Iteratoal Joural of Iovatve Scece, Egeerg & Techology, Vol. Issue, December 4. www.jset.com ISS 348 7968 Aalyss of Lagrage Iterpolato Formula Vjay Dahya PDepartmet of MathematcsMaharaja Surajmal

More information

DISPLACEMENT-BASED SEISMIC DESIGN OF MDOF CONTINUOUS GIRDER BRIDGES

DISPLACEMENT-BASED SEISMIC DESIGN OF MDOF CONTINUOUS GIRDER BRIDGES 3 th World Coferece o Earthquake Egeerg Vacouver, B.C., Caada August -6, 004 Paper No. 05 DISPLACEMENT-BASED SEISMIC DESIGN OF MDOF CONTINUOUS GIRDER BRIDGES X ZHU ad Jawe HUANG SUMMARY The proposed procedure

More information

A Note on Ratio Estimators in two Stage Sampling

A Note on Ratio Estimators in two Stage Sampling Iteratoal Joural of Scetfc ad Research Publcatos, Volume, Issue, December 0 ISS 0- A ote o Rato Estmators two Stage Samplg Stashu Shekhar Mshra Lecturer Statstcs, Trdet Academy of Creatve Techology (TACT),

More information

ESS Line Fitting

ESS Line Fitting ESS 5 014 17. Le Fttg A very commo problem data aalyss s lookg for relatoshpetwee dfferet parameters ad fttg les or surfaces to data. The smplest example s fttg a straght le ad we wll dscuss that here

More information

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best

best estimate (mean) for X uncertainty or error in the measurement (systematic, random or statistical) best Error Aalyss Preamble Wheever a measuremet s made, the result followg from that measuremet s always subject to ucertaty The ucertaty ca be reduced by makg several measuremets of the same quatty or by mprovg

More information

Chapter 11 Systematic Sampling

Chapter 11 Systematic Sampling Chapter stematc amplg The sstematc samplg techue s operatoall more coveet tha the smple radom samplg. It also esures at the same tme that each ut has eual probablt of cluso the sample. I ths method of

More information

Fourth Order Four-Stage Diagonally Implicit Runge-Kutta Method for Linear Ordinary Differential Equations ABSTRACT INTRODUCTION

Fourth Order Four-Stage Diagonally Implicit Runge-Kutta Method for Linear Ordinary Differential Equations ABSTRACT INTRODUCTION Malasa Joural of Mathematcal Sceces (): 95-05 (00) Fourth Order Four-Stage Dagoall Implct Ruge-Kutta Method for Lear Ordar Dfferetal Equatos Nur Izzat Che Jawas, Fudzah Ismal, Mohamed Sulema, 3 Azm Jaafar

More information

Outline. Point Pattern Analysis Part I. Revisit IRP/CSR

Outline. Point Pattern Analysis Part I. Revisit IRP/CSR Pot Patter Aalyss Part I Outle Revst IRP/CSR, frst- ad secod order effects What s pot patter aalyss (PPA)? Desty-based pot patter measures Dstace-based pot patter measures Revst IRP/CSR Equal probablty:

More information

Lecture 07: Poles and Zeros

Lecture 07: Poles and Zeros Lecture 07: Poles ad Zeros Defto of poles ad zeros The trasfer fucto provdes a bass for determg mportat system respose characterstcs wthout solvg the complete dfferetal equato. As defed, the trasfer fucto

More information

Comparison of Analytical and Numerical Results in Modal Analysis of Multispan Continuous Beams with LS-DYNA

Comparison of Analytical and Numerical Results in Modal Analysis of Multispan Continuous Beams with LS-DYNA th Iteratoal S-N Users oferece Smulato Techology omparso of alytcal ad Numercal Results Modal alyss of Multspa otuous eams wth S-N bht Mahapatra ad vk hatteree etral Mechacal Egeerg Research Isttute, urgapur

More information

Lecture 9: Tolerant Testing

Lecture 9: Tolerant Testing Lecture 9: Tolerat Testg Dael Kae Scrbe: Sakeerth Rao Aprl 4, 07 Abstract I ths lecture we prove a quas lear lower boud o the umber of samples eeded to do tolerat testg for L dstace. Tolerat Testg We have

More information

The solution of Euler-Bernoulli beams using variational derivative method

The solution of Euler-Bernoulli beams using variational derivative method Scetfc Research ad Essays Vol. 5(9), pp. 9-4, 4 May Avalable ole at http://www.academcjourals.org/sre ISSN 99-48 Academc Jourals Full egth Research Paper The soluto of Euler-Beroull beams usg varatoal

More information

Chapter 8. Inferences about More Than Two Population Central Values

Chapter 8. Inferences about More Than Two Population Central Values Chapter 8. Ifereces about More Tha Two Populato Cetral Values Case tudy: Effect of Tmg of the Treatmet of Port-We tas wth Lasers ) To vestgate whether treatmet at a youg age would yeld better results tha

More information

Derivation of 3-Point Block Method Formula for Solving First Order Stiff Ordinary Differential Equations

Derivation of 3-Point Block Method Formula for Solving First Order Stiff Ordinary Differential Equations Dervato of -Pot Block Method Formula for Solvg Frst Order Stff Ordary Dfferetal Equatos Kharul Hamd Kharul Auar, Kharl Iskadar Othma, Zara Bb Ibrahm Abstract Dervato of pot block method formula wth costat

More information

Cubic Nonpolynomial Spline Approach to the Solution of a Second Order Two-Point Boundary Value Problem

Cubic Nonpolynomial Spline Approach to the Solution of a Second Order Two-Point Boundary Value Problem Joural of Amerca Scece ;6( Cubc Nopolyomal Sple Approach to the Soluto of a Secod Order Two-Pot Boudary Value Problem W.K. Zahra, F.A. Abd El-Salam, A.A. El-Sabbagh ad Z.A. ZAk * Departmet of Egeerg athematcs

More information

Quantization in Dynamic Smarandache Multi-Space

Quantization in Dynamic Smarandache Multi-Space Quatzato Dyamc Smaradache Mult-Space Fu Yuhua Cha Offshore Ol Research Ceter, Beg, 7, Cha (E-mal: fuyh@cooc.com.c ) Abstract: Dscussg the applcatos of Dyamc Smaradache Mult-Space (DSMS) Theory. Supposg

More information

Chapter 3 Sampling For Proportions and Percentages

Chapter 3 Sampling For Proportions and Percentages Chapter 3 Samplg For Proportos ad Percetages I may stuatos, the characterstc uder study o whch the observatos are collected are qualtatve ature For example, the resposes of customers may marketg surveys

More information

PGE 310: Formulation and Solution in Geosystems Engineering. Dr. Balhoff. Interpolation

PGE 310: Formulation and Solution in Geosystems Engineering. Dr. Balhoff. Interpolation PGE 30: Formulato ad Soluto Geosystems Egeerg Dr. Balhoff Iterpolato Numercal Methods wth MATLAB, Recktewald, Chapter 0 ad Numercal Methods for Egeers, Chapra ad Caale, 5 th Ed., Part Fve, Chapter 8 ad

More information

p y A modified p-y curve method considering rotation of soil resistance

p y A modified p-y curve method considering rotation of soil resistance DOI.779/CJGE48 p p p 5 p 3 p p TU43 A 4548(4)8569 989 E-mal: shagguasq@gmal.com A modfed p- curve method cosderg rotato of sol resstace SHANGGUAN Sh-qg, LIU Hog-ju, PIAO Chu-de 3 (. Collage of Cvl Egeerg,

More information

CHAPTER 3 POSTERIOR DISTRIBUTIONS

CHAPTER 3 POSTERIOR DISTRIBUTIONS CHAPTER 3 POSTERIOR DISTRIBUTIONS If scece caot measure the degree of probablt volved, so much the worse for scece. The practcal ma wll stck to hs apprecatve methods utl t does, or wll accept the results

More information

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model

Lecture 7. Confidence Intervals and Hypothesis Tests in the Simple CLR Model Lecture 7. Cofdece Itervals ad Hypothess Tests the Smple CLR Model I lecture 6 we troduced the Classcal Lear Regresso (CLR) model that s the radom expermet of whch the data Y,,, K, are the outcomes. The

More information

1. A real number x is represented approximately by , and we are told that the relative error is 0.1 %. What is x? Note: There are two answers.

1. A real number x is represented approximately by , and we are told that the relative error is 0.1 %. What is x? Note: There are two answers. PROBLEMS A real umber s represeted appromately by 63, ad we are told that the relatve error s % What s? Note: There are two aswers Ht : Recall that % relatve error s What s the relatve error volved roudg

More information

On the Interval Zoro Symmetric Single Step. Procedure IZSS1-5D for the Simultaneous. Bounding of Real Polynomial Zeros

On the Interval Zoro Symmetric Single Step. Procedure IZSS1-5D for the Simultaneous. Bounding of Real Polynomial Zeros It. Joural of Math. Aalyss, Vol. 7, 2013, o. 59, 2947-2951 HIKARI Ltd, www.m-hkar.com http://dx.do.org/10.12988/ma.2013.310259 O the Iterval Zoro Symmetrc Sgle Step Procedure IZSS1-5D for the Smultaeous

More information

(Monte Carlo) Resampling Technique in Validity Testing and Reliability Testing

(Monte Carlo) Resampling Technique in Validity Testing and Reliability Testing Iteratoal Joural of Computer Applcatos (0975 8887) (Mote Carlo) Resamplg Techque Valdty Testg ad Relablty Testg Ad Setawa Departmet of Mathematcs, Faculty of Scece ad Mathematcs, Satya Wacaa Chrsta Uversty

More information

BIOREPS Problem Set #11 The Evolution of DNA Strands

BIOREPS Problem Set #11 The Evolution of DNA Strands BIOREPS Problem Set #11 The Evoluto of DNA Strads 1 Backgroud I the md 2000s, evolutoary bologsts studyg DNA mutato rates brds ad prmates dscovered somethg surprsg. There were a large umber of mutatos

More information

Chapter 13, Part A Analysis of Variance and Experimental Design. Introduction to Analysis of Variance. Introduction to Analysis of Variance

Chapter 13, Part A Analysis of Variance and Experimental Design. Introduction to Analysis of Variance. Introduction to Analysis of Variance Chapter, Part A Aalyss of Varace ad Epermetal Desg Itroducto to Aalyss of Varace Aalyss of Varace: Testg for the Equalty of Populato Meas Multple Comparso Procedures Itroducto to Aalyss of Varace Aalyss

More information

Module 7: Probability and Statistics

Module 7: Probability and Statistics Lecture 4: Goodess of ft tests. Itroducto Module 7: Probablty ad Statstcs I the prevous two lectures, the cocepts, steps ad applcatos of Hypotheses testg were dscussed. Hypotheses testg may be used to

More information

Uniform asymptotical stability of almost periodic solution of a discrete multispecies Lotka-Volterra competition system

Uniform asymptotical stability of almost periodic solution of a discrete multispecies Lotka-Volterra competition system Iteratoal Joural of Egeerg ad Advaced Research Techology (IJEART) ISSN: 2454-9290, Volume-2, Issue-1, Jauary 2016 Uform asymptotcal stablty of almost perodc soluto of a dscrete multspeces Lotka-Volterra

More information

MA/CSSE 473 Day 27. Dynamic programming

MA/CSSE 473 Day 27. Dynamic programming MA/CSSE 473 Day 7 Dyamc Programmg Bomal Coeffcets Warshall's algorthm (Optmal BSTs) Studet questos? Dyamc programmg Used for problems wth recursve solutos ad overlappg subproblems Typcally, we save (memoze)

More information

Journal of Chemical and Pharmaceutical Research, 2014, 6(7): Research Article

Journal of Chemical and Pharmaceutical Research, 2014, 6(7): Research Article Avalable ole www.jocpr.com Joural of Chemcal ad Pharmaceutcal Research, 04, 6(7):4-47 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 Predcto of CNG automoble owershp by usg the combed model Ku Huag,

More information

Stochastic Finite Element Based on Stochastic Linearization for Stochastic Nonlinear Ordinary Differential Equations with Random coefficients

Stochastic Finite Element Based on Stochastic Linearization for Stochastic Nonlinear Ordinary Differential Equations with Random coefficients Proc. of the 5th WSEAS It. Cof. o No-Lear Aalyss, No-Lear Systems ad Chaos, Bucharest, Romaa, October 6-8, 6 Stochastc Fte Elemet Based o Stochastc Learzato for Stochastc Nolear Ordary Dfferetal Equatos

More information

Objectives of Multiple Regression

Objectives of Multiple Regression Obectves of Multple Regresso Establsh the lear equato that best predcts values of a depedet varable Y usg more tha oe eplaator varable from a large set of potetal predctors {,,... k }. Fd that subset of

More information

Earthquake Resistant Design According to UBC Major Changes from UBC 1994

Earthquake Resistant Design According to UBC Major Changes from UBC 1994 Earthquake Resstat Desg Accordg to UBC 1997 Major Chages from UBC 1994 (1) Sol Profle Types: The four ste coeffcets S 1 to S 4 of the UBC 1994, whch are depedet of the level of groud shakg, were epaded

More information

Discrete Mathematics and Probability Theory Fall 2016 Seshia and Walrand DIS 10b

Discrete Mathematics and Probability Theory Fall 2016 Seshia and Walrand DIS 10b CS 70 Dscrete Mathematcs ad Probablty Theory Fall 206 Sesha ad Walrad DIS 0b. Wll I Get My Package? Seaky delvery guy of some compay s out delverg packages to customers. Not oly does he had a radom package

More information

A Combination of Adaptive and Line Intercept Sampling Applicable in Agricultural and Environmental Studies

A Combination of Adaptive and Line Intercept Sampling Applicable in Agricultural and Environmental Studies ISSN 1684-8403 Joural of Statstcs Volume 15, 008, pp. 44-53 Abstract A Combato of Adaptve ad Le Itercept Samplg Applcable Agrcultural ad Evrometal Studes Azmer Kha 1 A adaptve procedure s descrbed for

More information

hp calculators HP 30S Statistics Averages and Standard Deviations Average and Standard Deviation Practice Finding Averages and Standard Deviations

hp calculators HP 30S Statistics Averages and Standard Deviations Average and Standard Deviation Practice Finding Averages and Standard Deviations HP 30S Statstcs Averages ad Stadard Devatos Average ad Stadard Devato Practce Fdg Averages ad Stadard Devatos HP 30S Statstcs Averages ad Stadard Devatos Average ad stadard devato The HP 30S provdes several

More information

f f... f 1 n n (ii) Median : It is the value of the middle-most observation(s).

f f... f 1 n n (ii) Median : It is the value of the middle-most observation(s). CHAPTER STATISTICS Pots to Remember :. Facts or fgures, collected wth a defte pupose, are called Data.. Statstcs s the area of study dealg wth the collecto, presetato, aalyss ad terpretato of data.. The

More information

A New Measure of Probabilistic Entropy. and its Properties

A New Measure of Probabilistic Entropy. and its Properties Appled Mathematcal Sceces, Vol. 4, 200, o. 28, 387-394 A New Measure of Probablstc Etropy ad ts Propertes Rajeesh Kumar Departmet of Mathematcs Kurukshetra Uversty Kurukshetra, Ida rajeesh_kuk@redffmal.com

More information

Statistics MINITAB - Lab 5

Statistics MINITAB - Lab 5 Statstcs 10010 MINITAB - Lab 5 PART I: The Correlato Coeffcet Qute ofte statstcs we are preseted wth data that suggests that a lear relatoshp exsts betwee two varables. For example the plot below s of

More information

An Indian Journal FULL PAPER ABSTRACT KEYWORDS. Trade Science Inc. Research on scheme evaluation method of automation mechatronic systems

An Indian Journal FULL PAPER ABSTRACT KEYWORDS. Trade Science Inc. Research on scheme evaluation method of automation mechatronic systems [ype text] [ype text] [ype text] ISSN : 0974-7435 Volume 0 Issue 6 Boechology 204 Ida Joural FULL PPER BIJ, 0(6, 204 [927-9275] Research o scheme evaluato method of automato mechatroc systems BSRC Che

More information

STRONG CONSISTENCY FOR SIMPLE LINEAR EV MODEL WITH v/ -MIXING

STRONG CONSISTENCY FOR SIMPLE LINEAR EV MODEL WITH v/ -MIXING Joural of tatstcs: Advaces Theory ad Alcatos Volume 5, Number, 6, Pages 3- Avalable at htt://scetfcadvaces.co. DOI: htt://d.do.org/.864/jsata_7678 TRONG CONITENCY FOR IMPLE LINEAR EV MODEL WITH v/ -MIXING

More information

Investigating Cellular Automata

Investigating Cellular Automata Researcher: Taylor Dupuy Advsor: Aaro Wootto Semester: Fall 4 Ivestgatg Cellular Automata A Overvew of Cellular Automata: Cellular Automata are smple computer programs that geerate rows of black ad whte

More information

CHAPTER 4 RADICAL EXPRESSIONS

CHAPTER 4 RADICAL EXPRESSIONS 6 CHAPTER RADICAL EXPRESSIONS. The th Root of a Real Number A real umber a s called the th root of a real umber b f Thus, for example: s a square root of sce. s also a square root of sce ( ). s a cube

More information

PERFORMANCE-BASED SEISMIC DESIGN OF STEEL MOMENT FRAMES USING TARGET DRIFT AND YIELD MECHANISM

PERFORMANCE-BASED SEISMIC DESIGN OF STEEL MOMENT FRAMES USING TARGET DRIFT AND YIELD MECHANISM 3 th World Coferece o Earthquake Egeerg Vacouver, B.C., Caada August -6, 004 Paper No. 66 PERFORMANCE-BASED SEISMIC DESIGN OF STEEL MOMENT FRAMES USING TARGET DRIFT AND YIELD MECHANISM Soo-Sk LEE, Subhash

More information

Determination of angle of attack for rotating blades

Determination of angle of attack for rotating blades Determato of agle of attack for rotatg blades Hora DUMITRESCU 1, Vladmr CARDOS*,1, Flor FRUNZULICA 1,, Alexadru DUMITRACHE 1 *Correspodg author *,1 Gheorghe Mhoc-Caus Iacob Isttute of Mathematcal Statstcs

More information

Reliability evaluation of distribution network based on improved non. sequential Monte Carlo method

Reliability evaluation of distribution network based on improved non. sequential Monte Carlo method 3rd Iteratoal Coferece o Mecatrocs, Robotcs ad Automato (ICMRA 205) Relablty evaluato of dstrbuto etwork based o mproved o sequetal Mote Carlo metod Je Zu, a, Cao L, b, Aog Tag, c Scool of Automato, Wua

More information