DEVELOPMENT OF UNIFORM HAZARD GROUND MOTION RESPONSE SPECTRA FOR A SITE
|
|
- Verity Lester
- 6 years ago
- Views:
Transcription
1 13 th Worl Conference on Earthquake Engneerng Vancouver, B.C., Canaa August 1-6, 2004 Paper No DEVELOPMENT OF UNIFORM HAZARD GROUND MOTION REPONE PECTRA FOR A ITE A.K.GHOH 1 an H..KUHWAHA 2 UMMARY Tratonally, the sesmc esgn bass groun moton has been specfe by normalse response spectral shapes an peak groun acceleraton (PGA). The mean recurrence nterval (MRI) use to be compute for PGA only. The present work evelops unform hazar response spectra.e. spectra havng the same MRI at all frequences for Trombay ste. These results etermne the sesmc hazar at the gven ste an the assocate uncertantes. INTRODUCTION The objectve of asesmc esgn of power plant components an structures s to ensure safety of the plant an the people aroun n the event of an earthquake. afety nees to be ensure aganst a set of postulate events orgnatng at varous locatons, as ctate by the local geologcal an tectonc features an ata on past earthquakes. The esgn bass groun moton s generally specfe by normalse response spectra (also known as response spectral shapes or the ynamc amplfcatons factors, DAFs) for varous values of ampng an a PGA together wth a groun moton tme-hstory. The PGA s evaluate by emprcal relatons nvolvng earthquake magntue an the stance between the source an the ste. The former s obtane by a statstcal analyss of a large number of recors havng earthquake parameters n the range of nterest an selectng a shape wth an acceptable value of the probablty of exceeence. These ata shoul be rawn from stes havng smlar geologcal contons (rock/sol). The varous uncertantes an ranomness assocate wth the occurrence of earthquakes an the consequences of ther effects on the NPP components an structures call for a probablstc sesmc rsk assessment (PRA). esmc hazar at the ste s one of the key elements of the PRA [1]. The sesmc hazar at a gven ste s generally quantfe n terms of the probablty of exceeence of the esgn level PGA [2] an the probablty of exceeence of the specfe groun moton response spectral shapes [3-7]. 1 Reactor afety Dvson, Bhabha Atomc Research Centre, Mumba ; Ina 2 Health, afety & Envronment Group, Bhabha Atomc Research Centre, Mumba ; Ina
2 In the approach whch has tratonally been aopte the probablty of exceeence of the spectral shape s wth respect to the atabase from whch t has been erve an s not relate wth the temporal or spatal strbuton of earthquakes. The probablty of exceeence of the PGA s, however, evaluate conserng the spatal an temporal strbuton of earthquakes. The new RP [8] an Regulatory Gue [9] of UNRC recommen evelopment of unnormalse response spectra. UNRC [9] further proposes to carry out a probablstc safety hazar analyss (PHA) base on unform hazar response spectra (UHR). The present work ams to evelop UHR.e. response spectra havng the same mean recurrence nterval (MRI), or equvalently, the same probablty of exceeence n a specfe span of tme at all frequences for Trombay ste. The present paper evelops these spectra conserng lnear an pont sources of earthquakes. It s further recognse that the precte sesmc hazar can vary wth varous parameters nvolve. Numercal results have been presente to show ths varablty. These results wll help to etermne the sesmc hazar at the gven ste an the assocate uncertantes. THEORY Cornell [2] has presente a moel for evaluatng the MRI or the probablty of exceeence, P of a specfe value of PGA. Ghosh et al. [10] conserng aeral source strbuton extene the metho for more generalse forms for the correlaton for PGA. Ths work was extene to evelop UHR conserng a unform aeral source an lne an pont sources of earthquakes [11,12]. In ths report, a smlar methoology s apple to etermne a unform hazar response spectrum. esmc hazar analyss The sesmc hazar analyss presente by Cornell [2] s base on the peak groun acceleraton (a p ) whch s assume to be of the form b3 a = b exp( b M) R (1) p 1 2 where b 1, b 2 an b are constants, M s the earthquake magntue an R s the hypocentral stance. 3 It has been observe [13] that PGA precte by relatons of the type gven by equaton (1) oes not agree very well wth observatons partcularly for smaller values of R an a stance correcton term (D) has been consere by many workers. everal correlatons are avalable for efnng the peak groun acceleraton (a) for horzontal moton - each evelope from a partcular ata set, an therefore, best sute for nterpolaton wthn a partcular range of parameters. Two wely use forms for PGA are: a = b 1 exp(b 2 M) (R+D) -b 3 (2) a = b 1 10 b 2 M (R+D) -b 3 (3)
3 where M s the magntue, R s the stance an D s a correcton term to account for zero stance. For any applcaton, an equaton has to be chosen that s best sute to a gven source-ste combnaton an the range of parameters uner conseraton. Attenuaton relaton for spectral acceleraton The present regulatory ocuments [8,9] requre the groun moton to be presente as the unnormalse response spectrum tself wthout scalng t to PGA. Attenuaton relaton has been evelope for the unnormalse response spectrum [11,12]. The response spectral acceleraton s assume to be of the same form as gven by equaton (2).e. = (M, R, ζ,.t) = b 1 exp(b 2 M) (R+D) -b 3 (4) where M s the magntue an R s the hypocentral stance. D s a stance correcton factor, ζ s the value of ampng an T s the pero for whch the response spectrum s beng evaluate. The constants, b 1, b 2, b 3 epen on ζ an T. McGure [14] has use a form smlar to equaton (3). As has been shown by Ghosh et al. [10] equatons (2) an (3) are equvalent. Lne source moel Earthquakes occur along faults, whch are generally lnear features or represente as ones (lneaments). It s assume that earthquakes are equally lkely to occur anywhere along the length of a fault (lneament). The number of earthquake of magntue greater than or equal to M occurrng annually s gven by Rchter s equaton [15] log 10 N a bm M = (5) a an b for a gven regon are etermne from the earthquake occurrence recors of that regon. Conserng the effect of all possble values of the focal stances, the cumulatve probablty P[ ] s obtane. P ( = ) = C r 0 P [ b β 2 G R = r ] f ( r ) r (6) f R ( r ) the probablty ensty functon of fnng an earthquake at a raus r, an G for varous types of fault orentaton have been presente n [12]. C = e β M 0 b β 1 b 2 an β = b ln 10.
4 Equaton (6) yels the probablty that the spectral acceleraton (for gven values of ampng an pero) at ste, wll excee a certan value,, gven that an event of nterest ( M M 0 ) occurs anywhere on the fault. Next, we conser the ranom number of occurrences n any tme pero. It s assume that the occurrences of earthquake follow a Posson arrval process wth average occurrence rate of ν per year [2]. Then the number of events, N, of nterest occurrng n the area n a tme nterval of length t years s strbute as : ν t n e ( ν t ) P ( n) = P( N= n) = ; n = 012,,,... (7) N n! If certan events are Posson arrvals wth average arrval rate ν an f each of these events s nepenently, wth probablty p, a specal event, then these specal events are Posson arrvals wth average annual arrval rate p ν. The probablty, p, that any event of nterest M M 0 wll be a specal event s gven by equaton (6). Thus the number of tmes, N, that the spectral acceleraton (for gven values of ampng an pero) at the ste wll excee n an nterval of tme t has the probablty: p ν t n e ( p ν t ) PN ( n) = P( N = n ) = ; n= 0,1,2,... (8) n! Of partcular nterest s the probablty strbuton of max, the maxmum spectral acceleraton (at gven ampng an pero) over an nterval of tme t. p[ max ] = p[ N = 0 ]] Lettng t = 1 year, = e p ν t (9) p[ max ] = F a p = e P ν = exp( ν C G β / b 2 ) (10) The annual probablty of exceeence of max > s then 1 F a p = 1 exp( Cν G β / b 2 ) 1 [1 Cν G β / b 2 ]
5 β / b 2 = Cν G (11) The mean recurrence nterval ( T y ) of the spectral acceleraton s then the recprocal of ( 1 - F ap ).e., T y β 1 b 2 = (12) Cν G Then equatons (9) an (12) may be use to obtan the probablty of exceeence of n a gven span of t years as P= exp( t/ T ) (13) 1 y The sesmc hazar at a ste s quantfe by the probablty (P/ > ) an T y the uncertantes n these quanttes ue to varatons n the correlatons for spectral acceleraton an uncertantes n the sesmc source an occurrence moels.e. a an b, epth of focus, h. Pont ource Moel When there are clusters of earthquakes away from the ste, each cluster coul be moelle as a pont source of earthquakes. In case of a sngle pont source there s no ranomness wth respect to the locaton of the earthquake, hence for a specfe value of spectral acceleraton the magntue s also fxe by the chosen correlaton for spectral acceleraton. The probablty of exceeence of the specfe value of spectral acceleraton s therefore ece by the temporal strbuton of earthquakes. b 2 P[ ) = r] = C G (14) β where G β b 3 b 2 = ( r + D) (15) Multple Lne an Pont ources When there are a number of lne or pont sources the probablty of non-exceeence of a specfe value of spectral acceleraton s obtane by multplyng the probablty of non-exceeence of the specfe value of spectral acceleraton from each of the sources.e., p[ N max ] = p[ max ] fromtheth source = 1
6 = exp[ N = 1 C β b 2 G ν ] (16) The above equaton s the most general equaton for any number of sources. Assumng C, b 2 an β are constants, the above equaton smplfes to the followng. β b N 2 p[ max ] = exp[ ( C ) G ν = 1 (17) The mplcaton of the above assumpton s that 'a' can vary wth the source thus allowng fferent earthquake potental for each source, but 'b' an the constants b 1, b 2, b 3 reman unchange for the entre regon uner conseraton. When there are N sources assocate wth the parameters (a an b) for the Rchter's equaton an the parameters are (a,b) for the regon as a whole, then n orer to have the same number of earthquakes conserng ether the ensemble of the sources or the regon as a whole, the followng equalty hols. a 10 = 10 a.e. f all the sources have the same value of a then a = a log 10 ( N) (18) PREENT TUDY The present stuy uses 144 horzontal acceleraton recors from rock stes to evelop attenuaton relaton for response spectral acceleraton [11,12]. The range of magntue s generally from 4.1 to 8.1 an there are few recors of magntue lower than 4.1. The stance from the fault vare generally about from about 6 km to 125 km. The salent features of the accelerograms are gven n [12]. The gtse accelerograms were obtane on magnetc tapes from the Worl Data Center [16]. In these ata, the orgnal accelerograms have been ban-pass fltere between 0.07 Hz an 25 Hz an base lne correctons have been mae. Analyss has been carre out wth the recore accelerograms representng the free-fel contons. The geologcal contons of the recorng stes, entfe by the name an number of the recorng staton, are verfe from publshe sources. It has been observe that the response spectra of the two horzontal components recore at the same locaton are often sgnfcantly fferent. Ths may be attrbute to the orentaton of the nstrument wth respect to the fault. To ensure conservatsm, the attenuaton for spectral acceleraton (equaton (4)) at any frequency was evelope by selectng only the hgher of the two horzontal spectral values of the recors at a partcular ste. The attenuaton relatons thus evelope were use for the evelopment of unform hazar response spectra.
7 TABLE-1 EARTHQUAKE AROUND TROMBAY: Data from Global ources r. No. Magntue (M) Range M 0 M < M 1 No. of Earthquakes n ths Range KOYNA OTHER r. No. EARTHQUAKE AROUND TROMBAY: DATA FROM GBA Magntue (M) Range M 0 M < M 1 No. of Earthquakes n ths Range KOYNA OTHER The geologcal, tectonc an sesmc stuy for the ste was earler carre out to evelop the esgn bass Groun moton [17]. Each of these lneaments n the 300km. raus crcles aroun the ste has been consere as a lne source. An earler stuy [10] has shown that the nfluence of earthquake sources beyon 150km has nsgnfcant effect on the sesmc hazar. Earthquake ata for the pero AD has been obtane from varous catalogues ([18], for example) avalable as publshe lterature (global sources). Data have also been obtane from the Gaurbanur esmc Array (GBA) of Bhabha Atomc Research Centre pero for the pero AD [19]. Broaly the ata from both the sources can be vewe as () those belongng to Koyna an () others. The frst recore earthquake from Koyna s n the year A summary of these ata s presente n Table-1. A least square ft of the ata was carre out (see equaton 5) an the constant of the equaton ( a value) was ncrease to obtan a mofe ft to envelope. The a an b values obtane from [20] yels a rather unconservatve value of the occurrence rates of earthquakes n the Koyna regon. Base on all the ata a realstc set of values have been use for obtanng the UHR whch s close to the least square ft an conservatve for the magntue range M > 6 whch prouces acceleraton n the range of nterest for esgn. The least square analyss showe a large
8 varaton of a values obtane from the earthquake ata from global sources an GBA (see Table-2). The varaton of a for Koyna earthquakes was, however, not sgnfcantly large. The a an b values obtane from varous stues are presente n Table-2. TABLE 2 MAGNITUDE FREQUENCY RELATIONHIP Data Koyna Others Remarks a b a b Global Least quare Ft ata mofe to envelope the observe values GBA Least quare Ft ata mofe to envelope the observe values Ref [20] Base values use n analyss (see Fg. 2) The Koyna earthquakes occur n a small cluster. These earthquakes are assume to be generate from a pont source. The a an b values for all the lne sources are assume to be the same. The analyss has been carre out conserng a maxmum magntue of 6.5 for earthquakes occurrng n the regon uner stuy [20]. NUMERICAL REULT Usually, the value of T y for PGA s requre to be of the orer of hunre years for the operatng bass earthquake (OBE or 1 ) an of the orer of ten thousan years for the safe shutown earthquake (E or 2 ) [21]. Fg. 1 shows the varaton of MRI an the probablty of exceeence n 50 years as a functon of PGA. The a an b values for varous sources are the reference values gven n Table-2. Fgures 2a - 2c present the UHR for the base values of a an b for varous values of MRI an the probablty of exceeence. The spectral acceleraton at any frequency s hgher as the probablty of exceeence reuces.
9 Return pero (years) Return pero Probablty of exceeence Probablty of Exceeence pectral Acc. (g) % Ty=1. % Ty=10. % Ty=100. % Ty= E-3 1E PGA (g) Fg. 1: VARIATION OF MRI AND P V. PGA Per. (sec) Fg.2a: UHR for varous values of return pero DICUION From the earler stues [11,12] t has been observe that for a sngle source, as the stance from the fault, ncreases the value of the spectral acceleraton for a fxe MRI reuces. mlarly, for a fxe MRI, the spectral acceleraton reuces wth ncreasng value of l, the length of the fault. At smaller values of l, all the earthquakes are concentrate n a small zone aroun the ste. o for a gven value of MRI, the spectral acceleraton wll be more than that when earthquakes are lkely to occur over a wer range of stance. As l ncreases, the results ten to become asymptotc. Dstant earthquakes affect moton n the long pero (range 0.5s - 2s) Ty=7.50E+3 Ty=9.84E+3 Ty=1.77E+4 Ty=2.60E+4 Ty=3.44E P=0.1 P=0.2 P=0.01 P=0.02 P= pectral Acc. (g) pectral Acc. (g) Per.(sec) Fg.2b: UHR for varous values of return pero Per.(sec) Fg.2c: UHR for varous values of probablty of exceeence
10 As one moves away from the ste, the same spectral acceleraton at the ste woul be requre to be generate by an earthquake of a hgher magntue. Thus the value of MRI for the specfe spectral acceleraton wll be hgher. A hgher value of 'a' or a lower value of 'b' whle the other remans unchange woul mply a hgher value of M, leang to a hgher value of spectral acceleraton. It s seen that generally the spectral acceleraton for the pont source s hgher snce the earthquakes occur at the same stance, whereas the earthquake source stance s greater than or equal to for a lne source. However, for longer peros the two spectra appear to be closer. Ths s ue to contrbuton of the stant earthquakes to the long pero regon of the response spectra. These results wll be useful n carryng out the sesmc probablstc safety assessment of the plants at these stes.
11 REFERENCE 1. Kenney RP an Ravnra MP. esmc Fragltes for Nuclear Power Plant Hazar tues, Nuclear Engneerng an Desgn, 1984; 79, Cornell, C.A. Engneerng esmc Hazar Analyss, Bulletn of the esmologcal ocety of Amerca, 1968; 59, 5, U..A.E.C. Desgn Response pectra for esmc Desgn of Nuclear Power Plants, Regulatory Gue 1.60, U.. Atomc Energy Commsson, Drectorate of Regulatory tanars, ee HB, Ugas C an Lysmer J. te Depenent pectra for Earthquake Resstant Desgn, Bull. esm. oc. Am., 1976; 66, Ghosh AK, Muralharan, N an harma RD. pectral hapes for Accelerograms Recoe at Rock tes, Report B.A.R.C.-1314, Bhabha Atomc Research Centre, Government of Ina, Mumba, Ghosh AK an harma RD. pectral hapes for Accelerograms Recore at ol tes, Report B.A.R.C.-1365, Bhabha Atomc Research Centre, Government of Ina, Mumba, Ghosh AK, Rao K an Kushwaha H. Development of Responsepectral hapes an Attenuaton Relatons from Accelerograms Recore on Rock an ol tes, Report BARC/1998/016, Bhabha Atomc Research Centre, Government of Ina, U..N.R.C. Vbratory Groun Moton, tanar Revew Plan 2.5.2, NUREG- 800, Rev.3., U..N.R.C. Ientfcaton an Charactersaton of esmc ources an Determnaton of afe hutown Earthquake Groun Moton, Regulatory Gue , Ghosh AK an Kushwaha H. enstvty of esmc Hazar to Varous Parameters an Correlatons for Peak Groun Acceleraton, Report BARC/1998/025, Bhabha Atomc Research Centre, Government of Ina, Ghosh AK an Kushwaha H. Development of Unform Hazar Response pectra from Accelerograms Recore on Rock tes, Report BARC/2000/E/014, Bhabha Atomc Research Centre, Government of Ina, Ghosh AK an Kushwaha H. Development of Unform Hazar Response pectra for Rock tes Conserng Lne an Pont orces of Earthquakes, Report BARC/2001/E/031, Bhabha Atomc Research Centre, Government of Ina, Campbell KW. trong Moton Attenuaton Relatons : A Ten Year Perspectve, Earthquake pectra, 1985; 1(4), McGure RK. esmc Desgn pectra an Mappng Proceure usng Hazar Analyss base Drectly on Oscllator Response, Earthquake Engneerng an tructural Dynamcs, 1977; 5, Rchter CF. esmc Regonalsaton, Bulletn of the esmologcal ocety of Amerca, 1959; 49, Worl Data Centre. Catalogue of esmographs an trong Moton Recors, Report E-6, ol Earth Geophyscs Dvson, Envronmental Data ervce, Bouler, Colorao, U..A, Ghosh AK an Banerjee, D.C. Earthquake Desgn Bass for Tarapur te, Internal Report, Bhabha Atomc Research Centre; March Chanra U. Earthquakes of Pennsular Ina, esmotectonc tuy. Bulletn of the esmologcal ocety of Amerca, 1977, 67(5), Gangrae, BK et al. Earthquakes from Pennsular Ina: Data from Gaurbanur esmc Array Reports BARC 1347, 1987; BARC 1385, 1987; BARC 1454, 1989; BARC/1992/E/024, 1992; BARC/1994/E/040, 1994; BARC/1996/E/024, Bhabha Atomc Research Centre, Government of Ina. 20. Rav Kumar, M. an Bhata,.C. A New esmc Hazar Map for the Inan Plate Regon Uner the Global esmc Hazar Assessment Programme, Current cence,999, 77(3), IAEA. Earthquakes an Assocate Topcs n Relaton to Nuclear Power Plant tng: A afety Gue, afety Gue 50-G-1, Internatonal Atomc Energy Agency, Venna, 1979.
Development of Uniform Hazard Response Spectra for a Site
Transactons of the 17 th Internatonal Conference on Structural Mechancs n Reactor Technology (SMRT 17) Prague, Czech Republc, August 17 22, 2003 Paper # K11-3 Development of Unform Hazar Response Spectra
More informationSIMPLIFIED MODEL-BASED OPTIMAL CONTROL OF VAV AIR- CONDITIONING SYSTEM
Nnth Internatonal IBPSA Conference Montréal, Canaa August 5-8, 2005 SIMPLIFIED MODEL-BASED OPTIMAL CONTROL OF VAV AIR- CONDITIONING SYSTEM Nabl Nassf, Stanslaw Kajl, an Robert Sabourn École e technologe
More informationSimulated Power of the Discrete Cramér-von Mises Goodness-of-Fit Tests
Smulated of the Cramér-von Mses Goodness-of-Ft Tests Steele, M., Chaselng, J. and 3 Hurst, C. School of Mathematcal and Physcal Scences, James Cook Unversty, Australan School of Envronmental Studes, Grffth
More informationComparison of Regression Lines
STATGRAPHICS Rev. 9/13/2013 Comparson of Regresson Lnes Summary... 1 Data Input... 3 Analyss Summary... 4 Plot of Ftted Model... 6 Condtonal Sums of Squares... 6 Analyss Optons... 7 Forecasts... 8 Confdence
More informationCASE STUDIES ON PERFORMANCE BASED SEISMIC DESIGN USING CAPACITY SPECTRUM METHOD
CAE TUDIE ON PERFORMANCE BAED EIMIC DEIGN UING CAPACITY PECTRUM METHOD T NAGAO, H MUKAI An D NIHIKAWA 3 UMMARY Ths research ams to show the proceures an results of Performance Base esmc Desgn usng Capacty
More informationNew Liu Estimators for the Poisson Regression Model: Method and Application
New Lu Estmators for the Posson Regresson Moel: Metho an Applcaton By Krstofer Månsson B. M. Golam Kbra, Pär Sölaner an Ghaz Shukur,3 Department of Economcs, Fnance an Statstcs, Jönköpng Unversty Jönköpng,
More informationResearch on Time-history Input Methodology of Seismic Analysis
Transactons, SRT 19, Toronto, August 2007 Research on Tme-hstory Input ethoology of Sesmc Analyss Jang Nabn, ao Qng an Zhang Yxong State Key Laboratory of Reactor System Desgn Technology, Nuclear Power
More informationFINAL TECHNICAL REPORT AWARD NUMBER: 08HQAG0115
FINAL TECHNICAL REPORT AWARD NUMBER: 08HQAG0115 Ground Moton Target Spectra for Structures Senstve to Multple Perods of Exctaton: Condtonal Mean Spectrum Computaton Usng Multple Ground Moton Predcton Models
More informationA Robust Method for Calculating the Correlation Coefficient
A Robust Method for Calculatng the Correlaton Coeffcent E.B. Nven and C. V. Deutsch Relatonshps between prmary and secondary data are frequently quantfed usng the correlaton coeffcent; however, the tradtonal
More information2. High dimensional data
/8/00. Hgh mensons. Hgh mensonal ata Conser representng a ocument by a vector each component of whch correspons to the number of occurrences of a partcular wor n the ocument. The Englsh language has on
More informationChapter 3. Estimation of Earthquake Load Effects
Chapter 3. Estmaton of Earthquake Load Effects 3.1 Introducton Sesmc acton on chmneys forms an addtonal source of natural loads on the chmney. Sesmc acton or the earthquake s a short and strong upheaval
More informationVisualization of 2D Data By Rational Quadratic Functions
7659 Englan UK Journal of Informaton an Computng cence Vol. No. 007 pp. 7-6 Vsualzaton of D Data By Ratonal Quaratc Functons Malk Zawwar Hussan + Nausheen Ayub Msbah Irsha Department of Mathematcs Unversty
More informationp(z) = 1 a e z/a 1(z 0) yi a i x (1/a) exp y i a i x a i=1 n i=1 (y i a i x) inf 1 (y Ax) inf Ax y (1 ν) y if A (1 ν) = 0 otherwise
Dustn Lennon Math 582 Convex Optmzaton Problems from Boy, Chapter 7 Problem 7.1 Solve the MLE problem when the nose s exponentally strbute wth ensty p(z = 1 a e z/a 1(z 0 The MLE s gven by the followng:
More informationCENTRAL LIMIT THEORY FOR THE NUMBER OF SEEDS IN A GROWTH MODEL IN d WITH INHOMOGENEOUS POISSON ARRIVALS
The Annals of Apple Probablty 1997, Vol. 7, No. 3, 82 814 CENTRAL LIMIT THEORY FOR THE NUMBER OF SEEDS IN A GROWTH MODEL IN WITH INHOMOGENEOUS POISSON ARRIVALS By S. N. Chu 1 an M. P. Qune Hong Kong Baptst
More informationStructural Dynamics and Earthquake Engineering
Structural Dynamcs and Earthuake Engneerng Course 9 Sesmc-resstant desgn of structures (1) Sesmc acton Methods of elastc analyss Course notes are avalable for download at http://www.ct.upt.ro/users/aurelstratan/
More informationChapter 11: Simple Linear Regression and Correlation
Chapter 11: Smple Lnear Regresson and Correlaton 11-1 Emprcal Models 11-2 Smple Lnear Regresson 11-3 Propertes of the Least Squares Estmators 11-4 Hypothess Test n Smple Lnear Regresson 11-4.1 Use of t-tests
More informationRISK CONSISTENT RESPONSE SPECTRUM AND HAZARD CURVE FOR A TYPICAL LOCATION OF KATHMANDU VALLEY
3 th World Conference on Earthquae Engneerng Vancouver, B.C., Canada August -6, 004 Paper o. 34 RIK COITET REPOE PECTRUM AD HAZARD CURVE FOR A TYPICAL LOCATIO OF KATHMADU VALLEY Prem ath MAKEY and T. K.
More information( ) = : a torque vector composed of shoulder torque and elbow torque, corresponding to
Supplementary Materal for Hwan EJ, Donchn O, Smth MA, Shamehr R (3 A Gan-Fel Encon of Lmb Poston an Velocty n the Internal Moel of Arm Dynamcs. PLOS Boloy, :9-. Learnn of ynamcs usn bass elements he nternal
More informationChapter 1. Probability
Chapter. Probablty Mcroscopc propertes of matter: quantum mechancs, atomc and molecular propertes Macroscopc propertes of matter: thermodynamcs, E, H, C V, C p, S, A, G How do we relate these two propertes?
More informationChapter 2 Transformations and Expectations. , and define f
Revew for the prevous lecture Defnton: support set of a ranom varable, the monotone functon; Theorem: How to obtan a cf, pf (or pmf) of functons of a ranom varable; Eamples: several eamples Chapter Transformatons
More informationCalculation of Coherent Synchrotron Radiation in General Particle Tracer
Calculaton of Coherent Synchrotron Raaton n General Partcle Tracer T. Myajma, Ivan V. Bazarov KEK-PF, Cornell Unversty 9 July, 008 CSR n GPT D CSR wake calculaton n GPT usng D. Sagan s formula. General
More informationPROPOSAL OF THE CONDITIONAL PROBABILISTIC HAZARD MAP
The 4 th World Conference on Earthquake Engneerng October -, 008, Bejng, Chna PROPOSAL OF THE CODITIOAL PROBABILISTIC HAZARD MAP T. Hayash, S. Fukushma and H. Yashro 3 Senor Consultant, CatRsk Group, Toko
More informationWeek3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity
Week3, Chapter 4 Moton n Two Dmensons Lecture Quz A partcle confned to moton along the x axs moves wth constant acceleraton from x =.0 m to x = 8.0 m durng a 1-s tme nterval. The velocty of the partcle
More informationBOOTSTRAP METHOD FOR TESTING OF EQUALITY OF SEVERAL MEANS. M. Krishna Reddy, B. Naveen Kumar and Y. Ramu
BOOTSTRAP METHOD FOR TESTING OF EQUALITY OF SEVERAL MEANS M. Krshna Reddy, B. Naveen Kumar and Y. Ramu Department of Statstcs, Osmana Unversty, Hyderabad -500 007, Inda. nanbyrozu@gmal.com, ramu0@gmal.com
More informationAnalytical classical dynamics
Analytcal classcal ynamcs by Youun Hu Insttute of plasma physcs, Chnese Acaemy of Scences Emal: yhu@pp.cas.cn Abstract These notes were ntally wrtten when I rea tzpatrck s book[] an were later revse to
More informationWHY NOT USE THE ENTROPY METHOD FOR WEIGHT ESTIMATION?
ISAHP 001, Berne, Swtzerlan, August -4, 001 WHY NOT USE THE ENTROPY METHOD FOR WEIGHT ESTIMATION? Masaak SHINOHARA, Chkako MIYAKE an Kekch Ohsawa Department of Mathematcal Informaton Engneerng College
More informationChapter 9: Statistical Inference and the Relationship between Two Variables
Chapter 9: Statstcal Inference and the Relatonshp between Two Varables Key Words The Regresson Model The Sample Regresson Equaton The Pearson Correlaton Coeffcent Learnng Outcomes After studyng ths chapter,
More informationADVANCED PROBABILISTIC POWER FLOW METHODOLOGY
ADVANCED ROBABILITIC OWER FLOW METHODOLOY eorge tefopoulos, A.. Melopoulos an eorge J. Cokknes chool of Electrcal an Computer Engneerng eorga Insttute of Technology Atlanta, eorga 333-5, UA Abstract A
More informationFall 2012 Analysis of Experimental Measurements B. Eisenstein/rev. S. Errede
Fall Analyss of Expermental Measurements B. Esensten/rev. S. Erree Hypothess Testng, Lkelhoo Functons an Parameter Estmaton: We conser estmaton of (one or more parameters to be the expermental etermnaton
More informationExplicit bounds for the return probability of simple random walk
Explct bouns for the return probablty of smple ranom walk The runnng hea shoul be the same as the ttle.) Karen Ball Jacob Sterbenz Contact nformaton: Karen Ball IMA Unversty of Mnnesota 4 Ln Hall, 7 Church
More informationNegative Binomial Regression
STATGRAPHICS Rev. 9/16/2013 Negatve Bnomal Regresson Summary... 1 Data Input... 3 Statstcal Model... 3 Analyss Summary... 4 Analyss Optons... 7 Plot of Ftted Model... 8 Observed Versus Predcted... 10 Predctons...
More informationThe Finite Element Method
The Fnte Element Method GENERAL INTRODUCTION Read: Chapters 1 and 2 CONTENTS Engneerng and analyss Smulaton of a physcal process Examples mathematcal model development Approxmate solutons and methods of
More informationAnnex 10, page 1 of 19. Annex 10. Determination of the basic transmission loss in the Fixed Service. Annex 10, page 1
Annex 10, page 1 of 19 Annex 10 Determnaton of the basc transmsson loss n the Fxe Servce Annex 10, page 1 Annex 10, page of 19 PREDICTION PROCEDURE FOR THE EVALUATION OF BASIC TRANSMISSION LOSS 1 Introucton
More informationField and Wave Electromagnetic. Chapter.4
Fel an Wave Electromagnetc Chapter.4 Soluton of electrostatc Problems Posson s s an Laplace s Equatons D = ρ E = E = V D = ε E : Two funamental equatons for electrostatc problem Where, V s scalar electrc
More informationYukawa Potential and the Propagator Term
PHY304 Partcle Physcs 4 Dr C N Booth Yukawa Potental an the Propagator Term Conser the electrostatc potental about a charge pont partcle Ths s gven by φ = 0, e whch has the soluton φ = Ths escrbes the
More informationA capacitor is simply two pieces of metal near each other, separated by an insulator or air. A capacitor is used to store charge and energy.
-1 apactors A capactor s smply two peces of metal near each other, separate by an nsulator or ar. A capactor s use to store charge an energy. A parallel-plate capactor conssts of two parallel plates separate
More informationCHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE
CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE Analytcal soluton s usually not possble when exctaton vares arbtrarly wth tme or f the system s nonlnear. Such problems can be solved by numercal tmesteppng
More informationENGI9496 Lecture Notes Multiport Models in Mechanics
ENGI9496 Moellng an Smulaton of Dynamc Systems Mechancs an Mechansms ENGI9496 Lecture Notes Multport Moels n Mechancs (New text Secton 4..3; Secton 9.1 generalzes to 3D moton) Defntons Generalze coornates
More informationDEVELOPMENT OF UNIFORM HAZARD RESPONSE SPECTRA FOR KALPAKKAM, KAIGA AND KUDANKULAM
DEVELOPMENT OF UNIFORM HAZARD RESPONSE SPECTRA FOR KALPAKKAM, KAIGA AND KUDANKULAM by A.K. Ghosh & K.S. Rao Reactor Safety Division BARC/2009/E/025 BARC/2009/E/025 2009 BARC/2009/E/025 GOVERNMENT OF INDIA
More informationOptimum Design of Steel Frames Considering Uncertainty of Parameters
9 th World Congress on Structural and Multdscplnary Optmzaton June 13-17, 211, Shzuoka, Japan Optmum Desgn of Steel Frames Consderng ncertanty of Parameters Masahko Katsura 1, Makoto Ohsak 2 1 Hroshma
More informationA MULTIDIMENSIONAL ANALOGUE OF THE RADEMACHER-GAUSSIAN TAIL COMPARISON
A MULTIDIMENSIONAL ANALOGUE OF THE RADEMACHER-GAUSSIAN TAIL COMPARISON PIOTR NAYAR AND TOMASZ TKOCZ Abstract We prove a menson-free tal comparson between the Euclean norms of sums of nepenent ranom vectors
More informationUpdating Probabilistic Seismic Intensity at Kathmandu after 2015 Gorkha Earthquake
Journal of Cvl Engneerng and Archtecture 12 (2018) 454-461 do: 10.17265/1934-7359/2018.06.006 D DAVID PUBLISHING Updatng Probablstc Sesmc Intensty at Kathmandu after 2015 Gorkha Earthquake Har Ram Paraul
More informationχ x B E (c) Figure 2.1.1: (a) a material particle in a body, (b) a place in space, (c) a configuration of the body
Secton.. Moton.. The Materal Body and Moton hyscal materals n the real world are modeled usng an abstract mathematcal entty called a body. Ths body conssts of an nfnte number of materal partcles. Shown
More informationChapter 7: Conservation of Energy
Lecture 7: Conservaton o nergy Chapter 7: Conservaton o nergy Introucton I the quantty o a subject oes not change wth tme, t means that the quantty s conserve. The quantty o that subject remans constant
More informationFeedback Queue with Services in Different Stations under Reneging and Vacation Policies
Internatonal Journal of Apple Engneerng Research ISSN 973-456 Volume 1, Number (17) pp.11965-11969 Research Ina Publcatons. http://www.rpublcaton.com Feebac Queue wth Servces n Dfferent Statons uner Renegng
More informationDigital Signal Processing
Dgtal Sgnal Processng Dscrete-tme System Analyss Manar Mohasen Offce: F8 Emal: manar.subh@ut.ac.r School of IT Engneerng Revew of Precedent Class Contnuous Sgnal The value of the sgnal s avalable over
More informationSolutions to Practice Problems
Phys A Solutons to Practce Probles hapter Inucton an Maxwell s uatons (a) At t s, the ef has a agntue of t ag t Wb s t Wb s Wb s t Wb s V t 5 (a) Table - gves the resstvty of copper Thus, L A 8 9 5 (b)
More informationTemperature. Chapter Heat Engine
Chapter 3 Temperature In prevous chapters of these notes we ntroduced the Prncple of Maxmum ntropy as a technque for estmatng probablty dstrbutons consstent wth constrants. In Chapter 9 we dscussed the
More informationFUZZY FINITE ELEMENT METHOD
FUZZY FINITE ELEMENT METHOD RELIABILITY TRUCTURE ANALYI UING PROBABILITY 3.. Maxmum Normal tress Internal force s the shear force, V has a magntude equal to the load P and bendng moment, M. Bendng moments
More informationCHAPTER 4 HYDROTHERMAL COORDINATION OF UNITS CONSIDERING PROHIBITED OPERATING ZONES A HYBRID PSO(C)-SA-EP-TPSO APPROACH
77 CHAPTER 4 HYDROTHERMAL COORDINATION OF UNITS CONSIDERING PROHIBITED OPERATING ZONES A HYBRID PSO(C)-SA-EP-TPSO APPROACH 4.1 INTRODUCTION HTC consttutes the complete formulaton of the hyrothermal electrc
More informationDESIGN SPECTRUM-BASED SCALING OF STRENGTH REDUCTION FACTORS
13 th World Conference on Earthquake Engneerng Vancouver, B.C., Canada August 1-6, 2004 Paper No. 539 DESIGN SPECTRUM-BASED SCALING OF STRENGTH REDUCTION FACTORS Arndam CHAKRABORTI 1 and Vnay K. GUPTA
More informationSection 8.3 Polar Form of Complex Numbers
80 Chapter 8 Secton 8 Polar Form of Complex Numbers From prevous classes, you may have encountered magnary numbers the square roots of negatve numbers and, more generally, complex numbers whch are the
More informationPsychology 282 Lecture #24 Outline Regression Diagnostics: Outliers
Psychology 282 Lecture #24 Outlne Regresson Dagnostcs: Outlers In an earler lecture we studed the statstcal assumptons underlyng the regresson model, ncludng the followng ponts: Formal statement of assumptons.
More informationLecture 6 More on Complete Randomized Block Design (RBD)
Lecture 6 More on Complete Randomzed Block Desgn (RBD) Multple test Multple test The multple comparsons or multple testng problem occurs when one consders a set of statstcal nferences smultaneously. For
More informationLab 2e Thermal System Response and Effective Heat Transfer Coefficient
58:080 Expermental Engneerng 1 OBJECTIVE Lab 2e Thermal System Response and Effectve Heat Transfer Coeffcent Warnng: though the experment has educatonal objectves (to learn about bolng heat transfer, etc.),
More informationP R. Lecture 4. Theory and Applications of Pattern Recognition. Dept. of Electrical and Computer Engineering /
Theory and Applcatons of Pattern Recognton 003, Rob Polkar, Rowan Unversty, Glassboro, NJ Lecture 4 Bayes Classfcaton Rule Dept. of Electrcal and Computer Engneerng 0909.40.0 / 0909.504.04 Theory & Applcatons
More information2E Pattern Recognition Solutions to Introduction to Pattern Recognition, Chapter 2: Bayesian pattern classification
E395 - Pattern Recognton Solutons to Introducton to Pattern Recognton, Chapter : Bayesan pattern classfcaton Preface Ths document s a soluton manual for selected exercses from Introducton to Pattern Recognton
More information/ n ) are compared. The logic is: if the two
STAT C141, Sprng 2005 Lecture 13 Two sample tests One sample tests: examples of goodness of ft tests, where we are testng whether our data supports predctons. Two sample tests: called as tests of ndependence
More informationNEAR-FIELD PULSE-TYPE MOTION OF SMALL EVENTS IN DEEP GOLD MINES: OBSERVATIONS, RESPONSE SPECTRA AND DRIFT SPECTRA.
The 4 th October 2-7, 28, Bejng, Chna NEAR-FIELD PULSE-TYPE MOTION OF SMALL EVENTS IN DEEP GOLD MINES: OBSERVATIONS, RESPONSE SPECTRA AND DRIFT SPECTRA ABSTRACT: Artur Cchowcz Dr, Sesmology Unt, Councl
More information3.1 Expectation of Functions of Several Random Variables. )' be a k-dimensional discrete or continuous random vector, with joint PMF p (, E X E X1 E X
Statstcs 1: Probablty Theory II 37 3 EPECTATION OF SEVERAL RANDOM VARIABLES As n Probablty Theory I, the nterest n most stuatons les not on the actual dstrbuton of a random vector, but rather on a number
More informationSCALARS AND VECTORS All physical quantities in engineering mechanics are measured using either scalars or vectors.
SCALARS AND ECTORS All phscal uanttes n engneerng mechancs are measured usng ether scalars or vectors. Scalar. A scalar s an postve or negatve phscal uantt that can be completel specfed b ts magntude.
More informationA Note on the Numerical Solution for Fredholm Integral Equation of the Second Kind with Cauchy kernel
Journal of Mathematcs an Statstcs 7 (): 68-7, ISS 49-3644 Scence Publcatons ote on the umercal Soluton for Freholm Integral Equaton of the Secon Kn wth Cauchy kernel M. bulkaw,.m.. k Long an Z.K. Eshkuvatov
More informationLecture 9: Linear regression: centering, hypothesis testing, multiple covariates, and confounding
Recall: man dea of lnear regresson Lecture 9: Lnear regresson: centerng, hypothess testng, multple covarates, and confoundng Sandy Eckel seckel@jhsph.edu 6 May 8 Lnear regresson can be used to study an
More informationLecture 9: Linear regression: centering, hypothesis testing, multiple covariates, and confounding
Lecture 9: Lnear regresson: centerng, hypothess testng, multple covarates, and confoundng Sandy Eckel seckel@jhsph.edu 6 May 008 Recall: man dea of lnear regresson Lnear regresson can be used to study
More informationOn Liu Estimators for the Logit Regression Model
CESIS Electronc Workng Paper Seres Paper No. 59 On Lu Estmators for the Logt Regresson Moel Krstofer Månsson B. M. Golam Kbra October 011 The Royal Insttute of technology Centre of Excellence for Scence
More informationCopyright 2017 by Taylor Enterprises, Inc., All Rights Reserved. Adjusted Control Limits for U Charts. Dr. Wayne A. Taylor
Taylor Enterprses, Inc. Adjusted Control Lmts for U Charts Copyrght 207 by Taylor Enterprses, Inc., All Rghts Reserved. Adjusted Control Lmts for U Charts Dr. Wayne A. Taylor Abstract: U charts are used
More informationRELIABILITY ASSESSMENT
CHAPTER Rsk Analyss n Engneerng and Economcs RELIABILITY ASSESSMENT A. J. Clark School of Engneerng Department of Cvl and Envronmental Engneerng 4a CHAPMAN HALL/CRC Rsk Analyss for Engneerng Department
More informationUncertainty and auto-correlation in. Measurement
Uncertanty and auto-correlaton n arxv:1707.03276v2 [physcs.data-an] 30 Dec 2017 Measurement Markus Schebl Federal Offce of Metrology and Surveyng (BEV), 1160 Venna, Austra E-mal: markus.schebl@bev.gv.at
More informationENTROPIC QUESTIONING
ENTROPIC QUESTIONING NACHUM. Introucton Goal. Pck the queston that contrbutes most to fnng a sutable prouct. Iea. Use an nformaton-theoretc measure. Bascs. Entropy (a non-negatve real number) measures
More information8 Derivation of Network Rate Equations from Single- Cell Conductance Equations
Physcs 178/278 - Davd Klenfeld - Wnter 2019 8 Dervaton of Network Rate Equatons from Sngle- Cell Conductance Equatons Our goal to derve the form of the abstract quanttes n rate equatons, such as synaptc
More informationx = , so that calculated
Stat 4, secton Sngle Factor ANOVA notes by Tm Plachowsk n chapter 8 we conducted hypothess tests n whch we compared a sngle sample s mean or proporton to some hypotheszed value Chapter 9 expanded ths to
More informationGravitational Acceleration: A case of constant acceleration (approx. 2 hr.) (6/7/11)
Gravtatonal Acceleraton: A case of constant acceleraton (approx. hr.) (6/7/11) Introducton The gravtatonal force s one of the fundamental forces of nature. Under the nfluence of ths force all objects havng
More informationHigh-Order Hamilton s Principle and the Hamilton s Principle of High-Order Lagrangian Function
Commun. Theor. Phys. Bejng, Chna 49 008 pp. 97 30 c Chnese Physcal Socety Vol. 49, No., February 15, 008 Hgh-Orer Hamlton s Prncple an the Hamlton s Prncple of Hgh-Orer Lagrangan Functon ZHAO Hong-Xa an
More informationHard Problems from Advanced Partial Differential Equations (18.306)
Har Problems from Avance Partal Dfferental Equatons (18.306) Kenny Kamrn June 27, 2004 1. We are gven the PDE 2 Ψ = Ψ xx + Ψ yy = 0. We must fn solutons of the form Ψ = x γ f (ξ), where ξ x/y. We also
More informationPHYS 450 Spring semester Lecture 02: Dealing with Experimental Uncertainties. Ron Reifenberger Birck Nanotechnology Center Purdue University
PHYS 45 Sprng semester 7 Lecture : Dealng wth Expermental Uncertantes Ron Refenberger Brck anotechnology Center Purdue Unversty Lecture Introductory Comments Expermental errors (really expermental uncertantes)
More informationOn a one-parameter family of Riordan arrays and the weight distribution of MDS codes
On a one-parameter famly of Roran arrays an the weght strbuton of MDS coes Paul Barry School of Scence Waterfor Insttute of Technology Irelan pbarry@wte Patrck Ftzpatrck Department of Mathematcs Unversty
More informationLecture 16 Statistical Analysis in Biomaterials Research (Part II)
3.051J/0.340J 1 Lecture 16 Statstcal Analyss n Bomaterals Research (Part II) C. F Dstrbuton Allows comparson of varablty of behavor between populatons usng test of hypothess: σ x = σ x amed for Brtsh statstcan
More informationDistance-Based Approaches to Inferring Phylogenetic Trees
Dstance-Base Approaches to Inferrng Phylogenetc Trees BMI/CS 576 www.bostat.wsc.eu/bm576.html Mark Craven craven@bostat.wsc.eu Fall 0 Representng stances n roote an unroote trees st(a,c) = 8 st(a,d) =
More informationChapter 13: Multiple Regression
Chapter 13: Multple Regresson 13.1 Developng the multple-regresson Model The general model can be descrbed as: It smplfes for two ndependent varables: The sample ft parameter b 0, b 1, and b are used to
More informationUsing the estimated penetrances to determine the range of the underlying genetic model in casecontrol
Georgetown Unversty From the SelectedWorks of Mark J Meyer 8 Usng the estmated penetrances to determne the range of the underlyng genetc model n casecontrol desgn Mark J Meyer Neal Jeffres Gang Zheng Avalable
More informationSee Book Chapter 11 2 nd Edition (Chapter 10 1 st Edition)
Count Data Models See Book Chapter 11 2 nd Edton (Chapter 10 1 st Edton) Count data consst of non-negatve nteger values Examples: number of drver route changes per week, the number of trp departure changes
More informationAssessment of Site Amplification Effect from Input Energy Spectra of Strong Ground Motion
Assessment of Ste Amplfcaton Effect from Input Energy Spectra of Strong Ground Moton M.S. Gong & L.L Xe Key Laboratory of Earthquake Engneerng and Engneerng Vbraton,Insttute of Engneerng Mechancs, CEA,
More informationA MULTIDIMENSIONAL ANALOGUE OF THE RADEMACHER-GAUSSIAN TAIL COMPARISON
A MULTIDIMENSIONAL ANALOGUE OF THE RADEMACHER-GAUSSIAN TAIL COMPARISON PIOTR NAYAR AND TOMASZ TKOCZ Abstract We prove a menson-free tal comparson between the Euclean norms of sums of nepenent ranom vectors
More informationAP Physics 1 & 2 Summer Assignment
AP Physcs 1 & 2 Summer Assgnment AP Physcs 1 requres an exceptonal profcency n algebra, trgonometry, and geometry. It was desgned by a select group of college professors and hgh school scence teachers
More informationUNIVERSITY OF TORONTO Faculty of Arts and Science. December 2005 Examinations STA437H1F/STA1005HF. Duration - 3 hours
UNIVERSITY OF TORONTO Faculty of Arts and Scence December 005 Examnatons STA47HF/STA005HF Duraton - hours AIDS ALLOWED: (to be suppled by the student) Non-programmable calculator One handwrtten 8.5'' x
More informationVariable factor S-transform seismic data analysis
S-transform analyss Varable factor S-transform sesmc ata analyss Toor I. Toorov an Gary F. Margrave ABSTRACT Most of toay s geophyscal ata processng an analyss methos are base on the assumpton that the
More information18.1 Introduction and Recap
CS787: Advanced Algorthms Scrbe: Pryananda Shenoy and Shjn Kong Lecturer: Shuch Chawla Topc: Streamng Algorthmscontnued) Date: 0/26/2007 We contnue talng about streamng algorthms n ths lecture, ncludng
More informationAGC Introduction
. Introducton AGC 3 The prmary controller response to a load/generaton mbalance results n generaton adjustment so as to mantan load/generaton balance. However, due to droop, t also results n a non-zero
More information2016 Wiley. Study Session 2: Ethical and Professional Standards Application
6 Wley Study Sesson : Ethcal and Professonal Standards Applcaton LESSON : CORRECTION ANALYSIS Readng 9: Correlaton and Regresson LOS 9a: Calculate and nterpret a sample covarance and a sample correlaton
More informationALTERNATIVE METHODS FOR RELIABILITY-BASED ROBUST DESIGN OPTIMIZATION INCLUDING DIMENSION REDUCTION METHOD
Proceengs of IDETC/CIE 00 ASME 00 Internatonal Desgn Engneerng Techncal Conferences & Computers an Informaton n Engneerng Conference September 0-, 00, Phlaelpha, Pennsylvana, USA DETC00/DAC-997 ALTERATIVE
More informationChapter 7 Clustering Analysis (1)
Chater 7 Clusterng Analyss () Outlne Cluster Analyss Parttonng Clusterng Herarchcal Clusterng Large Sze Data Clusterng What s Cluster Analyss? Cluster: A collecton of ata obects smlar (or relate) to one
More informationApproximations for a Fork/Join Station with Inputs from Finite Populations
Approxmatons for a Fork/Jon Staton th Inputs from Fnte Populatons Ananth rshnamurthy epartment of ecson Scences ngneerng Systems Rensselaer Polytechnc Insttute 0 8 th Street Troy NY 80 USA Rajan Sur enter
More informationFeb 14: Spatial analysis of data fields
Feb 4: Spatal analyss of data felds Mappng rregularly sampled data onto a regular grd Many analyss technques for geophyscal data requre the data be located at regular ntervals n space and/or tme. hs s
More informationDepartment of Quantitative Methods & Information Systems. Time Series and Their Components QMIS 320. Chapter 6
Department of Quanttatve Methods & Informaton Systems Tme Seres and Ther Components QMIS 30 Chapter 6 Fall 00 Dr. Mohammad Zanal These sldes were modfed from ther orgnal source for educatonal purpose only.
More informationTopological Sensitivity Analysis for Three-dimensional Linear Elasticity Problem
6 th Worl Congress on Structural an Multscplnary Optmzaton Ro e Janero, 30 May - 03 June 2005, Brazl Topologcal Senstvty Analyss for Three-mensonal Lnear Elastcty Problem A.A. Novotny 1, R.A. Fejóo 1,
More informationThe Ordinary Least Squares (OLS) Estimator
The Ordnary Least Squares (OLS) Estmator 1 Regresson Analyss Regresson Analyss: a statstcal technque for nvestgatng and modelng the relatonshp between varables. Applcatons: Engneerng, the physcal and chemcal
More informationFlorida State University Libraries
Flora State Unversty Lbrares Electronc Theses, Treatses an Dssertatons The Grauate School 04 Wthn Stuy Depenence n Meta-Analyss: Comparson of GLS Metho an Multlevel Approaches Seungjn Lee Follow ths an
More informationIndeterminate pin-jointed frames (trusses)
Indetermnate pn-jonted frames (trusses) Calculaton of member forces usng force method I. Statcal determnacy. The degree of freedom of any truss can be derved as: w= k d a =, where k s the number of all
More informationPlasticity of Metals Subjected to Cyclic and Asymmetric Loads: Modeling of Uniaxial and Multiaxial Behavior
Plastcty of Metals Subjecte to Cyclc an Asymmetrc Loas: Moelng of Unaxal an Multaxal Behavor Dr Kyrakos I. Kourouss Captan, Hellenc Ar Force 1/16 Abstract Strength analyss of materals submtte to cyclc
More informationPhysics 181. Particle Systems
Physcs 181 Partcle Systems Overvew In these notes we dscuss the varables approprate to the descrpton of systems of partcles, ther defntons, ther relatons, and ther conservatons laws. We consder a system
More information