Synthetic Time Histories Research Articles

Study of the propagation and amplification of seismic waves in Caracas Valley with reference to the 29 July 1967 earthquake: SH waves

The antiplane response of a 2-D model of the valley of Caracas, Venezuela — a NS cross section through the Palos Grandes district — to seismic excitations such as those due to antiplane line (point) sources and incident plane SH waves is investigated. It is found that the steeply sloped northern edge of the valley is a more efficient generator and reflector of surface waves than the midly sloped southern edge. Also the spectral amplification and time response characteristics of this asymmetric wedge-shaped valley are a function of the direction of incidence of the excitation waves (e.g., incidence from the north versus incidence from the south versus vertical incidence). The same 2-D model of the valley is used to simulate also the antiplane response of the valley to synthetic strong motions equivalent — in amplitude, frequency content, and duration — to those that most likely were generated by the 29 July 1967 Caracas earthquake. This event has been found to consist of four subevents, of which the second subevent — located at a distance of 25 km from the valley — caused the damage in Caracas. The source spectrum of each of the subevents used in the generation of the synthetic time histories was assumed to be a simple ω-square model. The locations, relative times of occurrence, seismic moments, and mechanisms of the subevents were available from an inversion study of teleseismic data. It is found that peak acceleration was fairly uniform across the valley, varying from 0.15 to 0.21 g . On the contrary, peak velocities and peak rotational (torsional) strains varied considerably (factor of 2 to 3) across the valley, with the maximum values being 25 cm / sec for velocity and 1.5 × 10−4 for rotational strain. For sites in Palos Grandes, spectral accelerations Sa reached values as high as 0.4 g for periods in the range 0.4 ≦ T ≦ 1.4 sec and damping ratio 5%. Our estimates of the intensity of motion on rock and on the sediments are higher by a factor of 3 compared with estimates proposed by previous investigators, who assumed that all the seismic energy was released from a point located at a distance of 55 km from Caracas. Various pieces of evidence (e.g., seismoscope response recorded on rock) are presented that suggest that the intensity of motion was at least as high as estimated in this paper.

Aircraft/Deck Interface Dynamics for Destroyers

The interface between vertical takeoff and landing (VTOL) aircraft and destroyer and frigate-type warships involves a great many factors. This paper discusses a computer analytical technique which permits dynamic analysis of the aircraft landing or taking off from a moving deck or being handled or stowed on the ship. A condensed explanation of how the synthetic time histories are generated is contained in the Appendix. Two examples of how the technique has been used are included: first, a Recovery Assist and Secure System (RAS) analysis, and second, a pilot landing aid system, the Landing Period Designator (LPD) research program.

Extreme value estimates for arbitrary bandwidth Gaussian processes using the analytic envelope

A procedure is presented for the estimation of extreme values of stationary Gaussian random processes with arbitrary bandwidths. This approach is based on the analytic envelope defined by the Hilbert Transform; this envelope is Rayleigh distributed regardless of bandwidth. For experimentally derived data that has been converted into digital form, the Hilbert Transform is approximated using algorithms implemented on a digital computer to produce samples of the envelope's time history. Next, the degree of correlation between these envelope samples is taken into account using a method developed from simulation studies of a series of synthetic Gaussian time histories with varying bandwidths. Once this correlation effect has been estimated, the standard methods of order statistics are applied to these samples using the Rayleigh probability density function. Examples of applying this procedure to experimentally derived data are presented.