Site response analysis of liquefiable soil employing continuous wavelet transform

Propagation of the earthquake motion towards the ground surface alters both the acceleration and frequency content of the motion. Acceleration time record and Fourier amplitude spectrum of the motion reveal changes in the acceleration and frequency content. However, Fourier amplitude spectrum fails to give frequency-time variation. Wavelet transform overcomes this difficulty. In the present study, site response analysis of a liquefiable soil domain has been investigated employing wavelet transform. Three earthquake motions with distinct predominant frequencies are considered. It is revealed that the moment soil undergoes initial liquefaction, it causes a spike in the acceleration time history. Frequency of the spikes is found to be greater than the predominant frequency of the acceleration-time history recorded at the ground surface from the analysis. Interestingly, the spikes belong to the sharp tips of the shear stress-shear strain curve. Immediately after the spike, acceleration deamplification is observed. Post-liquefaction deamplification (filtering) of the frequency components is also observed.

Life Prediction Method of Remanufactured Machinery Equipment Based on Vibration Signal Feature Extraction

Mechanical equipment is a key component of mechanical equipment, and its working condition is directly related to the overall performance of mechanical equipment. Accurate evaluation and prediction of the performance degradation trend of mechanical equipment is of great significance to ensure the reliability and safety of the mechanical equipment system. Based on the data of typical faulty equipment, this paper analyzes the energy characteristic parameters of mechanical equipment under different types and degrees of failure in the time domain. Using amplitude spectrum analysis, Hilbert envelope demodulation and wavelet packet decomposition method, and other vibration signal processing methods, preliminary extraction of multiple statistical feature parameters are given. Secondly, in view of the irrelevant and redundant components of multiple statistical parameters, a new method for extracting fault features of mechanical equipment based on variance value and principal component analysis is proposed. This method can effectively classify the fault status of mechanical equipment. The effectiveness of the method is verified by actual equipment signals. After that, the value extracted from the vibration signal of the double-row roller equipment is used as the degradation feature. In order to reduce the influence of irregular characteristics in the vibration signal and simplify the complexity of the vibration signal, the wavelet transform and the support vector machine model are combined, according to the degradation after decomposition. The 95% confidence interval of the predicted value is also given. The SVM model is established based on data characteristics, and single-step and multistep prediction of equipment degradation trends are carried out. The prediction result shows that, according to the mapping position formula, the distribution of equipment degradation prediction points is obtained, and a 95% confidence interval based on the distribution of the prediction points is given. Finally, on the basis of completing feature extraction, this paper applies an unsupervised feature selection method. The sensitive characteristics of life prediction and the prediction results of a single SVM model and a neural network model are compared and analyzed at the same time.

Calculation model for the evaluation of tired defect development in the freight wagon side frame

The reliability and safe operation of mechanical elements of rail transport is an important and relevant scientific and technical issue since high-loaded units and elements of its chassis are exposed to prolonged operation and their failure can lead to damage with catastrophic consequences. To prevent the possible failure of such objects, there is a necessity for a reliable estimation of their residual life. Among the cast parts of the freight car trolley, the side frames are one of the most loaded elements, which take on dynamic loads that cause vibrations of the unsprung parts of the freight car. The side frame of the 18-100 trolley, as a typical representative of a number of trolleys of freight cars, does not have a sufficient margin of resistance to fatigue and survivability, so it is sensitive to some deviations and defects (different wall thickness, sinks, and pores, residual stresses) that are detected during the operation process. Based on the energy approach of the mechanics of materials fatigue failure, the calculation models for estimating the dynamics of the development of crack-like defects under the action of operational load are developed in this work. The calculation models constructed using modern information technologies, and the software developed for their numerical implementation allow predicting the impact of irregular cyclic loading and complex stress on the growth of surface fatigue crack in the side frame of the carriage, which significantly brings the problem closer to real operating conditions. Numerical calculations were performed using a computer program of our own development in the Python programming language. At the first stage of the program functioning the spectrum of amplitudes of irregular cyclic loading is built, at the second - the program module of numerical solution construction for systems of usual differential equations of the proposed mathematical model of fatigue defect development is started. Calculations of the fatigue crack growth dynamics taking into account the action of shear stresses in the section with the crack of the side frame showed a slight effect of shear stresses on the residual durability of the frame. It is demonstrated that the dynamics of surface crack development significantly depend on its initial geometry. The proposed calculation method for determining the initial shape of the surface crack with a minimum period to critical growth can be effectively used to predict the residual durability during the technical diagnosis of the running gear parts of railway rolling stock. Keywords: wagon side frame; fatigue crack; probability distribution function; load amplitude spectrum; numerical method.

On an eddy viscosity model for energetic deep-water surface gravity wave breaking

We present an investigation of the fundamental physical processes involved in deep-water gravity wave breaking. Our motivation is to identify the underlying reason causing the deficiency of the eddy viscosity breaking model (EVBM) in predicting surface elevation for strongly nonlinear waves. Owing to the limitation of experimental methods in the provision of high-resolution flow information, we propose a numerical methodology by developing an EVBM enclosed standalone fully nonlinear quasi-potential (FNP) flow model and a coupled FNP plus Navier–Stokes flow model. The numerical models were firstly verified with a wave train subject to modulational instability, then used to simulate a series of broad-banded focusing wave trains under non-, moderate- and strong-breaking conditions. A systematic analysis was carried out to investigate the discrepancies of numerical solutions produced by the two models in surface elevation and other important physical properties. It is found that EVBM predicts accurately the energy dissipated by breaking and the amplitude spectrum of free waves in terms of magnitude, but fails to capture accurately breaking induced phase shifting. The shift of phase grows with breaking intensity and is especially strong for high-wavenumber components. This is identified as a cause of the upshift of the wave dispersion relation, which increases the frequencies of large-wavenumber components. Such a variation drives large-wavenumber components to propagate at nearly the same speed, which is significantly higher than the linear dispersion levels. This suppresses the instant dispersive spreading of harmonics after the focal point, prolonging the lifespan of focused waves and expanding their propagation space.

Insights From the Ventricular Fibrillation Waveform Into the Mechanism of Survival Benefit From Bystander Cardiopulmonary Resuscitation

Background The mechanism by which bystander cardiopulmonary resuscitation (CPR) improves survival following out‐of‐hospital cardiac arrest is unclear. We hypothesized that ventricular fibrillation (VF) waveform measures, as surrogates of myocardial physiology, mediate the relationship between bystander CPR and survival. Methods and Results We performed a retrospective cohort study of adult, bystander‐witnessed patients with out‐of‐hospital cardiac arrest with an initial rhythm of VF who were treated by a metropolitan emergency medical services system from 2005 to 2018. Patient, resuscitation, and outcome variables were extracted from emergency medical services and hospital records. A total of 3 VF waveform measures (amplitude spectrum area, peak frequency, and median peak amplitude) were computed from a 3‐second ECG segment before the initial shock. Multivariable logistic regression estimated the association between bystander CPR and survival to hospital discharge adjusted for Utstein elements. Causal mediation analysis quantified the proportion of survival benefit that was mediated by each VF waveform measure. Of 1069 patients, survival to hospital discharge was significantly higher among the 814 patients who received bystander CPR than those who did not (0.52 versus 0.43, respectively; P <0.01). The multivariable‐adjusted odds ratio for bystander CPR and survival was 1.6 (95% CI, 1.2, 2.1), and each VF waveform measure attenuated this association. Depending on the specific waveform measure, the proportion of mediation varied: 53% for amplitude spectrum area, 31% for peak frequency, and 29% for median peak amplitude. Conclusions Bystander CPR correlated with more robust initial VF waveform measures, which in turn mediated up to one‐half of the survival benefit associated with bystander CPR. These results provide insight into the biological mechanism of bystander CPR in VF out‐of‐hospital cardiac arrest.

A method for simulation the effect of the reduced frequency resolution of the ear in patients with sensorineural hearing loss

A method for the simulation of reduced frequency resolution of the ear in patients with sensorineural hearing loss is proposed. The method is based upon the ability to adjust it according to the audiogram of a concrete person by frame-by-frame signal processing in the frequency domain. Simulation of the effect of the reduced frequency resolution of the ear is achieved by processing the components of amplitude spectrum of the original sound signal by the "smearing" function. The "smearing" function is formed from the amplitude-frequency characteristics of the auditory filters, which bandwidth is determined by the audiogram of the deaf person. The proposed method is implemented in the MATLAB. An experimental study of the effect of the reduced frequency resolution of the ear using the speech intelligibility test was conducted. The experiment involved 15 people who listened the records processed by the proposed method with various settings and noise conditions. Experimental data have shown that reduced frequency resolution of the ear leads to the deterioration in speech intelligibility, especially in the presence of background noise. Based on the answers of the participants of the experiment, the confusion tables of sounds were compiled, reflecting the fact of indistinguishability of sounds similar in frequency, that confirms the correctness of the proposed method.

Immersion in Modified Reality: Sensitivity to the Slope (α) of the Amplitude Spectrum is Dependent on the α of Recently Viewed Environments

Scenes contain many statistical regularities that, if accounted for by the visual system, could greatly benefit visual processing. One such statistic to consider is the orientation-averaged slope (α) of the amplitude spectrum of natural scenes. Human observers are differently sensitive to αs, and they may utilize this statistic when processing natural scenes. Here, we explore whether discrimination sensitivity to α is associated with the recently viewed environment. Observers were immersed, using a Head-Mounted Display, in an environment that was either unaltered or had its average α steepened or shallowed. Discrimination thresholds were affected by the average shift in α: a steeper environment decreased thresholds for very steep reference αs while a shallower environment decreased thresholds for shallow values. We modelled these data with a Bayesian observer model and explored how different prior shapes may influence the ability of the model to fit observer thresholds. We explore three potential prior shapes: unimodal, bimodal and trimodal modified-PERT distributions and found the bimodal prior to best-capture observer thresholds for all experimental conditions. Notably, the prior modes' position was shifted following adaptation, which suggests that a priori expectations for α are sufficiently malleable to account for changes in the average α of the recently viewed scenes.

Predicting the Amplitude of Thermoacoustic Instability Using Universal Scaling Behaviour

The complex interaction between the turbulent flow, combustion and the acoustic field in gas turbine engines often results in thermoacoustic instability that produces ruinously high-amplitude pressure oscillations. These self-sustained periodic oscillations may result in a sudden failure of engine components and associated electronics, and increased thermal and vibrational loads. Estimating the amplitude of the limit cycle oscillations (LCO) that are expected during thermoacoustic instability helps in devising strategies to mitigate and to limit the possible damages due to thermoacoustic instability. We propose two methodologies to estimate the amplitude using only the pressure measurements acquired during stable operation. First, we use the universal scaling relation of the amplitude of the dominant mode of oscillations with the Hurst exponent to predict the amplitude of the LCO. We also present a methodology to estimate the amplitudes of different modes of oscillations separately using ''spectral measures' which quantify the sharpening of peaks in the amplitude spectrum. The scaling relation enables us to predict the peak amplitude at thermoacoustic instability, given the data during the safe operating condition. The accuracy of prediction is tested for both methods, using the data acquired from a laboratory-scale turbulent combustor. The estimates are in good agreement with the actual amplitudes.