1、o psYnull樊 剑1, 2, 余倩倩1, 邵 丹1( 1. S/vr ! ,q430074;2. S/v e 8 L i,q430074)K1: loM L= 151. 1- 0. 020tt100. 9 t 10Sg0(t)1106. 16- 5. 17t+ 0. 088t2191. 15- 4. 07t+ 0. 063t21108. 16- 4. 45t+ 0. 061t2/% 4. 3 2. 5 3. 8 “ , T(9)o HMKanai-Tajimi b2 ?o HMKanai-Tajimi mm3 U,m9 E HM L=d9 ( HM HW qHf (L)1mb T(8)l
2、f E,V2 T( 9) E3 o HM vl,1V1V2 V, HMKanai-Tajimi 1 ( d Eo HM bm32 o HMKanai-Tajimi m# HWHf qHf 2.3 edp) =P(EDP edp nullIM =im) dnull(im)d( im) dim (15)TIM edp nullIM = im) IM = imH,EDP edpHq q(V K wL),null(im)im M ( q,4154 Kt,:o psY |Sewellyp ? E5Vr T14null(im) = k0im- k (16)Tk0, k V ! /imEbP(EDP edp
3、 nullIM= im)9 nullEDP1ob5 9 s(IDA)HE9 IM= im/EDP q15P (EDP edpnullIM= im)= # EDP edp nullIM= imns(17)T# cV U |Hqo “,nsV Uo“9 b9FIM, Vim)P (EDP edp nullIM= im)bYL !P(EDP edp nullIM= im)1im sP(EDP edp nullIM= im)= 1- null ln(im) - ln(nulledp)nulledp(18)Tnulledpnulledp VYVim)P (EDP edpnullIM= im) Kl=dL
4、 Eb T( 16)( 18) T( 15) Vnull(EDP edp) Tnull(EDP edp) = k0null- kedp exp 12 k2nulledp (19)Y V(EDP edp)C C(EDP edp)C( EDP edp) = 1/ null(EDP edp) (20) q psB1o IM4,KIM PGASa(T1,5%),S0IM, IDAHE9 T(15)P(EDP edpnullIM= im) H, 3BF MIM(MS0) ,i T( 11) “S HM _o, F_o , dL HsZE9 Yb 3BF MS0_o /:VD 16 V, Z_i, ? v
5、Z_1, ? M lZ_2, Z_ M b !1Z_F xf(t), T(11) T HM ,Sp( t,f ) T(5) ( d ,5 q f S0 . 2YV Lro f g(t) Sg07 3;Sp(t,f ) T(9) Eo,5No q f S0 . 2YV L HM ro f g(t) Sg0(t)7 3, V V / HMLsZF xff + 2nullf (t) nullnullf (t) nullxnullf + null2f (t) nullxf = n(t)xfg + 2nullg(t) nullnullg(t) nullxnullg + null2g(t) nullx g
6、 = - xffxf(t) = xff + xfge(t)e(t) = g(t) Sg0(t)(21)Txfxg ro Y, nullg( t)= 2nullf g(t),nullf (t)= 2nullf f (t),xf(t) 3o, e(t) f ,n(t) . 2V, / E n(t) = 0,En(t1)n(t2) = 2nullS0 nullnull(t1 - t2)(22)TEc ,null(c)Diracf bV1j3 ,YVsZF(21), V 3 75 MV C / M 2 475 M)C / M 75 MV C / M 2 475 M1 324 13 330 359.5
7、10 460 2 147. 5 4 414 140.4 3 905 3 95 2 013125.5 2 663 4 ( 1) loM L= , . q 4194 Kt,:o psYs J. ,2008,25( 3) :43i48. 2Spanos P D, JaleTezcan, Petros Tratskas. Stochasticprocesses evolutionary spectrum estimation viaharmonic wavelets. Comput J . Methods Appl.Mech. Engrg, 2005, 194( 12): 1 367i1 383. 3
8、Spanosa P D, Giaralisb A, Politis N P. Time-frequency representation of earthquake accelerogramsand inelastic structural response records using theadaptive chirplet decomposition and empirical modedecomposition J. Soil Dynamics and EarthquakeEngineering, 2007, 27(6) : 675i689. 4Wen Y K, Ping Gu. Des
9、cription and simulation of.non-stationary processes based on Hilbert spectraJ.Journal of Engineering MechanicsS . 2004, 130(9):942i951.5Kt, g,f. loMo HM9#d o J.,2009, 31(2) : 215i223. 6Kt, g,f.SMo H s# J.,2008,21( 4) :381i386. 7Junjie Wang; Lichu Fan, Shie Qian, et al.Simulations of non-stationary f
10、requency content andits importance to seismicassessment of structuresJ.Earthquake Engineering and Structural Dynamics,2002; 31(10): 993i1 005. 8r , ,. H l dLYY J.,2003,16( 2) : 207i211. 9Tothong P, Luco N. Probabilistic seismic demandanalysis using advanced ground motion intensitymeasuresJ. Earthqua
11、ke Engineering and StructuralDynamics, 2005, 34(10) : 1 193i1 217.10 Zareian F, Krawinkler H. Assessment of probabilityof collapse and design for collapse safety J .Earthquake Engineering and Structural Dynamics,2007, 36( 12) : 1 901i1 914. 11 Cornell C A, Jalayer F, Hamburger RO, et al.Probabilisti
12、c basis for 2000 SAC FEMA steel momentframe guidelines J . Journal of StructuralEngineering, 2002, 128(4) : 526i533.12, ,.y F !9?SGB50011-2001 M .:Sy,2001.13 Clough R W, Penzien J.Dynamics of StructuresM . 2nd ed. New York, M cGraw-Hill, Inc.,1993. 14 Sewell R T, Toro G R, M cGuire R K. Impact ofgro
13、und motion characterization on conservatism andvariability in seismic risk estimates M . NUREG/CR-6467, U . S. Nuclear Regulatory Commission,Washington, DC, 1996. 15 Jalayer F. Direct Probabilistic seismic analysis:implementing nonlinear dynamic assessments D .Department of Civil and Environmental E
14、ngineering,Stanford University, CA, 2003.16 Kubo T, Penzien J. Time and frequency analysis ofthree dimensional ground motionsR. San FernandoEarth-quake, 1976, Report No. 76/6.Effect of nonstationary stochastic model of earthquake recordson the probabilistic seismic demend analysis of base isolated s
15、tructuresFAN Jian1, 2, YU Qian-qian1, SHAO Dan1( 1. College of Civil Engineering and Mechanics, Huazhong University of Science and Technology, Wuhan 430074, China;2.Hubei Key Laboratory of Control Structure, Huazhong University of Science and Technology, Wuhan 430074, China)Abstract: The time variab
16、le spectrums of strong earthquake records are estimated based on the harmonic wavelet transform.The averagetime variablespectrums of earthquakerecords are simulated by uniform non-stationary stochastic model and timevariable modified Kanai-Tajimi non-stationary stochastic model. Theempirical formula
17、s for the timevariable spectrums of theearthquake records on three classes of sites soil are established by using nonlinear function fitting method. The step ispresented to analyze probabilistic seismic demand of base isolated structures subjected to two-direction horizontal groundmotions, and regar
18、d S0 (S0is spectrum intensity parameter) as the intensity measure (IM ) of ground motions. The effectof nonstationary stochastic model of earthquake records on the probabilistic seismic demand analysis ( PSDA) of base isolatedstructures is studied. It is showed that the effect is insignificant when
19、the IM is small, but increasing the IM, the effectbecomes significant. In addition, the effect is variant for different class of sites soil.Key words: harmonic wavelet transform; earthquake record; non-stationary stochastic model; isolated structure; PSDATe:Kt(1969- ) , 3,p V, qb: 13971157209;Email:fan-jian 42024
