Nonstationary Spectral Response of Dam Reservoir to Random Excitation

Author(s):  
Rita Bhobe ◽  
C. Y. Yang
2014 ◽  
Vol 9 (1) ◽  
pp. 69-78
Author(s):  
Ivo Demjan ◽  
Michal Tomko

Abstract A 3D model of a reinforced concrete building and was created in software ANSYS. The dynamic analysis was focused on the spectral response of the object represented by a random excitation experiment found in records in the form of load spectra


2014 ◽  
Vol 969 ◽  
pp. 182-187 ◽  
Author(s):  
Ivo Demjan ◽  
Michal Tomko

A 3D model of a reinforced concrete building was created using a dynamic analysis which focused on the spectral response of the object represented by a random excitation experiment found in records in the form of load spectra.


1994 ◽  
Vol 1 (4) ◽  
pp. 349-356 ◽  
Author(s):  
Mostafa Rassaian

To predict the vibration environment of a payload carried by a ground or air transporter, mathematical models are required from which a transfer function to a prescribed input can be calculated. For sensitive payloads these models typically include linear shock isolation system stiffness and damping elements relying on the assumption that the isolation system has a predetermined characteristic frequency and damping ratio independent of excitation magnitude. In order to achieve a practical spectral analysis method, the nonlinear system has to be linearized when the input transportation and handling vibration environment is in the form of an acceleration power spectral density. Test data from commercial isolators show that when nonlinear stiffness and damping effects exist the level of vibration input causes a variation in isolator resonant frequency. This phenomenon, described by the stationary response of the Duffing oscillator to narrow-band Gaussian random excitation, requires an alternative approach for calculation of power spectral density acceleration response at a shock isolated payload under random vibration. This article details the development of a plausible alternative approach for analyzing the spectral response of a nonlinear system subject to random Gaussian excitations.


1979 ◽  
Vol 44 ◽  
pp. 41-47
Author(s):  
Donald A. Landman

This paper describes some recent results of our quiescent prominence spectrometry program at the Mees Solar Observatory on Haleakala. The observations were made with the 25 cm coronagraph/coudé spectrograph system using a silicon vidicon detector. This detector consists of 500 contiguous channels covering approximately 6 or 80 Å, depending on the grating used. The instrument is interfaced to the Observatory’s PDP 11/45 computer system, and has the important advantages of wide spectral response, linearity and signal-averaging with real-time display. Its principal drawback is the relatively small target size. For the present work, the aperture was about 3″ × 5″. Absolute intensity calibrations were made by measuring quiet regions near sun center.


2002 ◽  
Vol 715 ◽  
Author(s):  
P. Louro ◽  
A. Fantoni ◽  
Yu. Vygranenko ◽  
M. Fernandes ◽  
M. Vieira

AbstractThe bias voltage dependent spectral response (with and without steady state bias light) and the current voltage dependence has been simulated and compared to experimentally obtained values. Results show that in the heterostructures the bias voltage influences differently the field and the diffusion part of the photocurrent. The interchange between primary and secondary photocurrent (i. e. between generator and load device operation) is explained by the interaction of the field and the diffusion components of the photocurrent. A field reversal that depends on the light bias conditions (wavelength and intensity) explains the photocurrent reversal. The field reversal leads to the collapse of the diode regime (primary photocurrent) launches surface recombination at the p-i and i-n interfaces which is responsible for a double-injection regime (secondary photocurrent). Considerations about conduction band offsets, electrical field profiles and inversion layers will be taken into account to explain the optical and voltage bias dependence of the spectral response.


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