Effect of Linear Soil Condition on Seismic Inputs

Seismic inputs to structures in terms of risk consistent response spectrum and seismic hazard curves are developed at bedrock level considering ten independent seismic source zone in the vicinity of the Kathmandu valley. The seismic hazard curve is derived by assuming temporal occurrence of earthquakes to follow Poisson model. Response spectrum is developed using an empirical relationship of spectral ordinates with magnitude of earthquakes and epicentral distance. The seismic risk factor is introduced in response spectrum using conditional probabilities. Power spectral density function consistent with response spectrum is derived and ground acceleration time histories are derived from power spectral density function using Monte Carlo technique. To obtain free field hazard curves and ground motion parameters, one dimensional wave propagation analysis is used for two different underlying soil conditions.

Strain energy released by earthquake faulting with random slip components

SUMMARY This study investigates the strain energy change caused by earthquake faulting. While conventional theories often assumed uniform stress change on the fault plane, this study supposed the slip fluctuation and non-uniform stress change on the fault. By using a stochastic modelling of the slip distribution, we represent the ensemble average of the strain energy change by using the power spectral density function of the slip fluctuation. This yields the following results. (1) When the initial stress is uniform and the earthquake contains a fluctuating slip distribution, the released strain energy is less than the one by an earthquake with the uniform stress change on the fault with the same seismic moment. (2) On the other hand, when the initial stress is fluctuating, the earthquake contains a fluctuating slip distribution, and the final stress is uniform, the released strain energy is more than the one by an earthquake with the uniform stress change on the fault. (3) The stress drop becomes large due to the fluctuating slip distribution from the viewpoint of the strain energy release. We derived the analytical solution of the stress change by using the power spectral density function of the random slip fluctuation. (4) The strain energy change is proportional to the seismic moment when ${\epsilon ^2}/a \propto {( {{M_0}} )^{ - 1/3}}$ (${\epsilon ^2}$ is the variance of the fractional slip fluctuation and $a$ is the correlation distance). (5) The energy balance gives the value of initial stress that is required for the earthquake generation. In order to generate an earthquake, the initial stress needs to be larger than the sum of half of the stress drop and the apparent stress. In other words, earthquakes having rich short-wavelength components in the slip distribution are not generated under a low initial stress level.

Extreme and spectrum characteristics of wind loads on super-large cooling tower under different four-tower combinations

The wind loads distribution on the super-large cooling tower under the interference effect of tower group is very complicated. Particularly, energy distribution of fluctuation wind loads and extreme model is difficult to be predicted. However, accurate calculations of these two factors are the most direct ways for analysis of wind resistance dynamics of super-large cooling tower. The wind tunnel tests of the highest super-large cooling tower under five typical tower combinations (serial, rectangular, rhombus, L-shaped, and inclined L-shaped) with 320 working conditions were performed. On this basis, non-Gaussian and non-stationary properties of local wind pressure and overall force coefficient of super-large cooling tower were analyzed. Distribution laws of local wind pressure extremes and overall force coefficient extremes were discussed based on Hermite method and peak factor method. Key attention was paid to the mapping relationships of characteristic angles with local and overall aerodynamic force extremes. The effects of four-tower combination modes on fluctuation wind loads energy of super-large cooling tower were studied based on the power spectral density function, intrinsic mode function, and evolution power spectral density function. Besides, the estimation formulas of local wind pressure spectrum and overall pressure coefficient spectrum of super-large cooling tower under four-tower combination were proposed. It can be found that the extremes of local wind pressure and overall aerodynamic force could be predicted based on the linear relationship between characteristic angles and fluctuation wind loads. In addition, it is suggested to choose serial combination first, followed by inclined L-shaped, L-shaped, rhombus, and rectangular modes successively.

Power Spectral Density Function for Individual Jumping Load

Modern slender structures such as long-span floors and cantilever stands are sensitive to jumping-induced vibrations. A conventional deterministic Fourier series model for the human jumping load may overestimate a structure's responses in resonance condition. This paper suggests a power spectral density (PSD) function for the individual jumping load, which was treated as a narrowband stationary stochastic process. Experiments were conducted on individual jumping loads resulting in 334 records from 73 subjects. Statistical analysis of the records led to experimental PSD curves on which a symmetrical bilinear function was suggested. The proposed PSD function is centered on the given jumping frequency and its integer multiples. The function's parameters were determined by equating the total energy of the proposed PSD with that of the experimental PSD. Application of the proposed PSD for predicting a floor's peak response via the stochastic vibration theory was then presented. The predictions for an experimental floor model subjected to individual jumping were compared with the measured peak responses. The comparisons demonstrated that the proposed PSD function was applicable for predicting the floor's response to individual jumping. Finally, the framework for calculating crowd-induced structure vibrations using the suggested PSD was also discussed.

Time-Domain Simulation of High-Speed Railway Track Irregularity

It was more convenient to describe track irregularity by the spatial frequency.The conventional frequency-domain transfer function can not effectively solve the vibration equation when anlysis of the vibration response to structure of vehicle-track dynamic coupling system, the time domain numerical integration must be used to solve it.The trigonometric series superposition method can be used to convert track irregularity spectrum into time domain frequency power spectral density function, and then turn the simulated irregularity samples into spectral density by the Inverse Fast Fourier Transform (IFFT), which compared with the theoretical spectral density to test the reliability of the sample. The results show that the simulated sample have the same characteristics with the given power spectral density function, which demonstrate the high reliability of this sample and it can be used as the external excitation of the locomotive vehicle system.

Study of Intake Tower under an Earthquake Using the Power Spectral Method Based on ANSYS

In this paper, the power spectral density method based on ANSYS is carried out to study the intake tower finite element model under an earthquake. A power spectral density function is obtained and disposed to be smooth. Then it is used to study the intake tower when the seismic wave occurs in the direction of flow and perpendicular to the direction of flow .This study provides theoretical basis for reinforce and transform of the intake tower structure.

Identification of Cardiac Diseases from(ECG) Signals based on Fractal Analysis

This paper investigates the use of fractal geometry for analyzing ECG time series signals. A technique of identifying cardiac diseases is proposed which is based on estimation of Fractal Dimension (FD) of ECG recordings. Using this approach, variations in texture across an ECG signal can be characterized in terms of variations in the FD values. An overview of methods for computing the FD is presented focusing on the Power Spectrum Method (PSM) that makes use of the characteristic of Power Spectral Density Function (PSDF) of a Random Scaling Fractal Signal. A 20 dataset of ECG signals taken from MIT-BIH arrhythmia database has been utilized to estimate the FD, which established ranges of FD for healthy person and persons with various heart diseases. The obtained ranges of FD are presented in tabular fashion with proper analysis. Moreover, the experimental results showing comparison of Normal and Abnormal (arrhythmia) ECG signals and demonstrated that the PSM shows a better distinguish between the ECG signals for healthy and non-healthy persons versus the other methods.