Explore the vast range of titles available.

One of the most important parameters specially in mining and oil drilling fields is the type of rocks. It is important to determine that rock structure is in which of the three categories of igneous, metamorphic, and sedimentary rocks. By identifying and determining the characteristics of the rocks with an accurate method, it is possible to complete the exploration information or selecting the appropriate operating parameters such as drill bit, ROP for real-time optimizing the drilling operation. One of the most accurate methods used in various engineering fields is the use of acoustic signals processing. The acoustic signals can be applied to get useful information about operating parameters. The purpose of this paper is rock type identification while drilling operation. For this purpose, 9 various rock samples with different types and properties were selected and prepared for laboratory-scale drilling tests. After the drilling tests, acoustic signals were analyzed and interpreted. The time domain, frequency and time–frequency spectrums of each acoustic signal were analyzed. Fast Fourier Transform and Short Time Fourier Transform algorithms used to determine the distinctions of dominant frequencies and selected frequency bands for the rock type determination. According to the results obtained from time–frequency Spectrum, it can be maintained that by investigating and analyzing the frequency behavior of different rocks, the rock type can be detected. This can be very useful and important for rock type identification in early phases of the projects, oil drilling, deep excavations, or projects without exploration information or to complete and update the geological data. Graphic Abstract

Wavelet transform is one of the mathematical concepts for studying the frequency content of waves. It can be divided into two groups, continuous and discrete. In general, the continuous wavelet transform is used to examine the time-frequency relationship, whereas the discrete wavelet transform is used for filtering and noise reduction in waves. In this paper, for the first time, the combination of these two concepts is used for the earthquake acceleration wave. For this purpose, eight earthquakes from four different locations in the world have been selected. Initially, each earthquake is filtered up to 5 stages using a discrete wavelet transform. At each stage of the filter, two waves of approximations and details are obtained. Due to the close approximation of the frequency content of the wave to the original earthquake, the approximate wave is used for subsequent calculations. The Fourier spectrum and the diagram of five of the dominant frequency of the earthquake are plotted in the next step. Also, using the continuous wavelet transform, the time-frequency curves of the main earthquakes and the time-frequency curves of the wave obtained from the discrete wavelet transform are investigated. The goal was to find the best stage of a discrete wavelet filter based on frequency content to reduce computations by more than 80%. The time of the strong ground motion, the structural response of a single degree of freedom, and the dynamical response of the timing of the structure of a degree of freedom are all investigated in the following step. By examining the above parameters, the best-performing wavelet transformation step is inferred.

This study aims to primarily assess the dynamic behavior of ground-supported cylindrical tanks to real near-fault earthquake records with different frequency contents including soil-structure interaction effects. A cylindrical tank’s fluid-tank-soil interaction is modeled using a three-degree-of-freedom lumped mass model for the fluid. A mass-spring-dashpot model with frequency independence is used to model the soil/foundation system. Broad, medium, and slender tank models are developed considering and ignoring the soil flexibility effect. An algorithm based on discrete-time state-space approaches is developed for performing numerical simulations of the modeled tanks excited by the low-, medium-, and high-frequency contents. The obtained results for the modeled tanks in terms of base shear, overturning moment, and connective and impulsive mass displacements incorporating the influence of supporting soils as well as the frequency contents of excitation records are evaluated and compared with the corresponding results for modeled tanks with a fixed base. In addition, the liquid sloshing height for all aspect ratios is also evaluated and compared. The study’s findings clearly indicate that records with low-frequency contents require significantly more seismically demanding than other records for the considered soil types. Remarkably, soil-tank interaction under earthquake motions substantially amplifies the induced response.

Background: Fragmentation and delayed potentials in the QRS signal of patients have been postulated as risk markers for Sudden Cardiac Death (SCD). The analysis of the high-frequency spectral content may be useful for quantification. Methods: Forty-two consecutive patients with prior history of SCD or malignant arrhythmias (patients) where compared with 120 healthy individuals (controls). The QRS complexes were extracted with a modified Pan-Tompkins algorithm and processed with the Continuous Wavelet Transform to analyze the high-frequency content (85–130 Hz). Results: Overall, the power of the high-frequency content was higher in patients compared with controls (170.9 vs. 47.3 103nV2Hz−1; p = 0.007), with a prolonged time to reach the maximal power (68.9 vs. 64.8 ms; p = 0.002). An analysis of the signal intensity (instantaneous average of cumulative power), revealed a distinct function between patients and controls. The total intensity was higher in patients compared with controls (137.1 vs. 39 103nV2Hz−1s−1; p = 0.001) and the time to reach the maximal intensity was also prolonged (88.7 vs. 82.1 ms; p < 0.001). Discussion: The high-frequency content of the QRS complexes was distinct between patients at risk of SCD and healthy controls. The wavelet transform is an efficient tool for spectral analysis of the QRS complexes that may contribute to stratification of risk.

Recently, a class of fractional multi-frequency oscillators, constructed based on using n integrators and n half-order ones, has been introduced, whose steady-state responses contain sinusoidal components with 0.5(3n-1) number of selectable frequencies. In this paper, the structure of the introduced multi-frequency oscillator is modified such that, notwithstanding the frequency content preservation, the number of its involved integrators is reduced. With no effect on the frequency content of the generated oscillations, this modification causes that the circuitry implementation of the considered class of multi-frequency oscillators can be done with a less number of energy storage elements.

The Lombard effect is an unconscious reflex of speakers to increase vocal effort when disturbed by noise, aiming to enhance speech intelligibility. This study aims to evaluate the effect of noise with different energetic content and levels at various frequencies on the Lombard effect, communication disturbance, vocal comfort, and speech intelligibility. Twenty university students participated in the study, reading a six-sentence excerpt and performing an intelligibility test under 12 randomized noise conditions. These conditions included noises at low (20–500 Hz), medium (500–4000 Hz), and high frequencies (4000–20,000 Hz), at four levels (45 dB, 55 dB, 65 dB, 75 dB). After each condition, participants rated their perceived communication disturbance and vocal discomfort. The results indicated that noise with energetic content at medium frequencies produced the highest Lombard effect, produced the most detrimental effect on communication disturbance and vocal comfort, and caused the strongest decrease in speech intelligibility, whereas it was minimally affected by low- and high-frequency noise. In conclusion, this study highlights that medium-frequency noise has the greatest impact on vocal effort, communication disturbance, and vocal comfort, while low- and high-frequency noise has minimal effect on speech intelligibility.

Compared to intact limbs, running-specific prostheses have high resonance non-biologic materials and lack active tissues to damp high frequencies. These differences may lead to ground reaction forces (GRFs) with high frequency content. If so, ubiquitously applying low-pass filters to prosthetic and intact limb GRFs may attenuate veridical high frequency content and mask important and ecologically valid data from prostheses. To explore differences in frequency content between prosthetic and intact limbs we divided signal power from transtibial unilateral amputees and controls running at 2.5, 3.0, and 3.5m/s into Low (<10Hz), High (10–25Hz), and Non-biologic (>25Hz) frequency bandwidths. Faster speeds tended to reduce the proportion of signal power in the Low bandwidth while increasing it in the High and Non-biologic bandwidths. Further, prostheses had lower proportions of signal power at the High frequency bandwidth but greater proportions at the Non-biologic bandwidth. To evaluate whether these differences in frequency content interact with filter cut-offs and alter results, we filtered GRFs with cut-offs from 1 to 100Hz and calculated vertical impact peak (VIP). Changing cut-off had inconsistent effects on VIP across speeds and limbs: Faster speeds had significantly larger changes in VIP per change in cut-off while, compared to controls, prosthetic limbs had significantly smaller changes in VIP per change in cut-off. These findings reveal differences in GRF frequency content between prosthetic and intact limbs and suggest that a cut-off frequency that is appropriate for one limb or speed may be inappropriate for another.

Evaluation of seismic risk by capturing the influences of strong motion duration and frequency contents of ground motion through probabilistic approaches is the main element of this study. Unlike most existing studies that mainly focus on intensity measures such as peak ground acceleration or spectral acceleration, this work highlights how duration and frequency characteristics critically influence dam response. To achieve this, a total of 45 ground motion records, categorized by strong motion duration (long, medium, and short) and frequency content (low, medium, and high), were selected from the PEER database. Nonlinear numerical dynamic analysis was performed by scaling each ground motion from 0.05 g to 0.5 g, with the drift ratio at the dam crest used as the Engineering Demand Parameter. It is revealed that long-duration and low-frequency ground motions induced significantly higher drift demands. The fragility analysis was conducted using a lognormal distribution considering extensive damage threshold drift ratio. Finally, the probabilistic seismic risk was carried out by integrating the site-specific hazard curve and fragility curves which yield the height risk for long durations and low frequencies. The outcomes emphasize the importance of ground motion strong duration and frequency in seismic performance and these findings can be utilized in the dam safety evaluation.

The frequency content of strong ground motion significantly affects the response of engineered systems under seismic excitation. Among some scalar parameters which exist in the literature, the mean period Tm has proved to be the most efficient. Ground Motion Predictive Equations (GMPEs) are usually developed for ground motion parameters through the calibration of coefficients of predefined functional forms, via linear or nonlinear regression, and based on recorded ground motion data. Such expressions of Tm are rare in the literature. Recently, the use of machine learning (ML) algorithms in earthquake engineering and engineering seismology has increased. The Artificial Neural Network (ANN) is an effective ML algorithm which has already been explored for the development of GMPEs for amplitude-based ground motion parameters. Within the work presented herein, multiple nonlinear regression (NLR)- and ANN-based GMPEs are developed for Tm using the latest strong motion database for shallow earthquakes in Greece. To the author’s knowledge, the implementation of ANN for producing GMPEs for Tm for shallow earthquake events has not been explored. Direct comparison between the NLR- and ANN-based GMPEs is performed, in terms of performance indexes, aleatory uncertainty, and working examples, as well as testing against earthquake events not included in the original dataset. The results reveal that the ANN-based GMPEs are useful in reducing aleatory uncertainty, although care should be taken in their implementation to avoid overfitting issues.

This study aims to assess the seismic response of a newly developed buried arch bridge system. The proposed buried arch bridge system is comprised of precast concrete panels, external steel outriggers, and steel V-strips to solve the limitation encountered in the storage, transportation, and construction of traditional buried arch structures. The three-dimensional finite element analysis of this arch system is conducted under dynamic analysis emphasizing the frequency content of earthquakes. Then, the fragility curves are suggested for this arch system based on two damage states defined via incremental dynamic analysis. The results show that this proposed arch system is significantly affected under a high frequency content earthquake compared to the low and intermediate ones. Additionally, the arch system deflects the most at the mid-high position rather than at the arch crown. The deflection at the arch crown or at the mid-high position can be used for establishing the fragility curves as they both connect with the failure mechanism of the arch structure.