Nongeometric arrivals due to highly concentrated sources adjacent to plane interfaces

1983 ◽  
Vol 73 (6A) ◽  
pp. 1655-1671
Author(s):  
P. F. Daley ◽  
F. Hron
Keyword(s):  
Wave Field ◽  
High Frequency ◽  
Real Data ◽  
Synthetic Seismogram ◽  
Head Wave ◽  
Real Field ◽  
Branch Points ◽  
Good Match ◽  
Full Wave ◽  
Frequency Approximation

Abstract A high-frequency approximation for nongeometrical arrivals due to highly concentrated sources adjacent to the interfaces between two different elastic media has been developed following their detection in the real field data by Gutowski et al. (1982). In our approach, the “★” waves are associated with secondary saddle-point contributions of the contour of integration circumventing branch points in the integral representation of transmitted wave field. Our formulas are presented in a simple form suitable for an easy incorporation into any ray synthetic seismogram computation. The range of validity of our approximations is discussed and their accuracy tested by comparing the pertinent ray seismograms with their equivalents produced by the Alekseev-Mikhailenko method. A good match between both sets of seismograms suggests that our high-frequency approximations for “★” waves are well justified as are our formulas derived for the head wave-like arrivals driven by the “★” waves, and seen in the full wave field seismograms and detected in real data as well.

Wave‐equation traveltime inversion

Geophysics ◽  
1991 ◽  
Vol 56 (5) ◽  
pp. 645-653 ◽  
Author(s):  
Y. Luo ◽  
G. T. Schuster
Keyword(s):  
Wave Equation ◽  
Ray Tracing ◽  
High Frequency ◽  
Velocity Model ◽  
Head Wave ◽  
Inversion Method ◽  
Diffraction Reflection ◽  
Traveltime Inversion ◽  
Wave Inversion ◽  
Full Wave

This paper presents a new traveltime inversion method based on the wave equation. In this new method, designated as wave‐equation traveltime inversion (WT), seismograms are computed by any full‐wave forward modeling method (we use a finite‐difference method). The velocity model is perturbed until the traveltimes from the synthetic seismograms are best fitted to the observed traveltimes in a least squares sense. A gradient optimization method is used and the formula for the Frechét derivative (perturbation of traveltimes with respect to velocity) is derived directly from the wave equation. No traveltime picking or ray tracing is necessary, and there are no high frequency assumptions about the data. Body wave, diffraction, reflection and head wave traveltimes can be incorporated into the inversion. In the high‐frequency limit, WT inversion reduces to ray‐based traveltime tomography. It can also be shown that WT inversion is approximately equivalent to full‐wave inversion when the starting velocity model is “close” to the actual model. Numerical simulations show that WT inversion succeeds for models with up to 80 percent velocity contrasts compared to the failure of full‐wave inversion for some models with no more than 10 percent velocity contrast. We also show that the WT method succeeds in inverting a layered velocity model where a shooting ray‐tracing method fails to compute the correct first arrival times. The disadvantage of the WT method is that it appears to provide less model resolution compared to full‐wave inversion, but this problem can be remedied by a hybrid traveltime + full‐wave inversion method (Luo and Schuster, 1989).

scholarly journals Research of the process of vegetable oil extracting under the influence of a high frequency wave field

2020 ◽  
Vol 941 ◽  
pp. 012052
Author(s):  
V Yu Ovsyannikov ◽  
A A Berestovoy ◽  
N N Lobacheva ◽  
V V Toroptsev ◽  
S A Trunov
Keyword(s):  
Wave Field ◽  
Vegetable Oil ◽  
High Frequency ◽  
Frequency Wave ◽  
High Frequency Wave

scholarly journals Photovoltaic Prediction Software: Evaluation with Real Data from Northern Spain

2021 ◽  
Vol 11 (11) ◽  
pp. 5025
Author(s):  
David González-Peña ◽  
Ignacio García-Ruiz ◽  
Montserrat Díez-Mediavilla ◽  
Mª. Isabel Dieste-Velasco ◽  
Cristina Alonso-Tristán
Keyword(s):  
Energy Production ◽  
Field Data ◽  
Real Data ◽  
Software Tools ◽  
Horizontal Axis ◽  
Real Field ◽  
Tracking Systems ◽  
Northern Spain ◽  
Commercial Software ◽  
Solar Tracking

Prediction of energy production is crucial for the design and installation of PV plants. In this study, five free and commercial software tools to predict photovoltaic energy production are evaluated: RETScreen, Solar Advisor Model (SAM), PVGIS, PVSyst, and PV*SOL. The evaluation involves a comparison of monthly and annually predicted data on energy supplied to the national grid with real field data collected from three real PV plants. All the systems, located in Castile and Leon (Spain), have three different tilting systems: fixed mounting, horizontal-axis tracking, and dual-axis tracking. The last 12 years of operating data, from 2008 to 2020, are used in the evaluation. Although the commercial software tools were easier to use and their installations could be described in detail, their results were not appreciably superior. In annual global terms, the results hid poor estimations throughout the year, where overestimations were compensated by underestimated results. This fact was reflected in the monthly results: the software yielded overestimates during the colder months, while the models showed better estimates during the warmer months. In most studies, the deviation was below 10% when the annual results were analyzed. The accuracy of the software was also reduced when the complexity of the dual-axis solar tracking systems replaced the fixed installation.

Dynamic properties of reflected and head waves near the critical point

1979 ◽  
Vol 16 (7) ◽  
pp. 1388-1401 ◽  
Author(s):  
Larry W. Marks ◽  
F. Hron
Keyword(s):  
Exact Solution ◽  
High Frequency ◽  
Classical Problem ◽  
Plane Boundary ◽  
Head Wave ◽  
Disk File ◽  
Ray Theory ◽  
Computational Point ◽  
Spherical Waves ◽  
Head Waves

The classical problem of the incidence of spherical waves on a plane boundary has been reformulated from the computational point of view by providing a high frequency approximation to the exact solution applicable to any seismic body wave, regardless of the number of conversions or reflections from the bottoming interface. In our final expressions the ray amplitude of the interference reflected-head wave is cast in terms of a Weber function, the numerical values of which can be conveniently stored on a computer disk file and retrieved via direct access during an actual run. Our formulation also accounts for the increase of energy carried by multiple head waves arising during multiple reflections of the reflected wave from the bottoming interface. In this form our high frequency expression for the ray amplitude of the interference reflected-head wave can represent a complementary technique to asymptotic ray theory in the vicinity of critical regions where the latter cannot be used. Since numerical tests indicate that our method produces results very close to those obtained by the numerical integration of the exact solution, its combination with asymptotic ray theory yields a powerful technique for the speedy computation of synthetic seismograms for plane homogeneous layers.

scholarly journals Smart Ocean: A New Fast Deconvolved Beamforming Algorithm for Multibeam Sonar

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 4013 ◽  
Author(s):  
Jie Huang ◽  
Tian Zhou ◽  
Weidong Du ◽  
Jiajun Shen ◽  
Wanyuan Zhang
Keyword(s):  
High Frequency ◽  
Real Data ◽  
Side Lobe ◽  
Tunnel Effect ◽  
Computation Complexity ◽  
Acoustic Image ◽  
Multibeam Sonar ◽  
Sonar System ◽  
Topographic Survey ◽  
Beamforming Algorithm

A new fast deconvolved beamforming algorithm is proposed in this paper, and it can greatly reduce the computation complexity of the original Richardson–Lucy (R–L algorithm) deconvolution algorithm by utilizing the convolution theorem and the fast Fourier transform technique. This algorithm makes it possible for real-time high-resolution beamforming in a multibeam sonar system. This paper applies the new fast deconvolved beamforming algorithm to a high-frequency multibeam sonar system to obtain a high bearing resolution and low side lobe. In the sounding mode, it restrains the tunnel effect and makes the topographic survey more accurate. In the 2D acoustic image mode, it can obtain clear images, more details, and can better distinguish two close targets. Detailed implementation methods of the fast deconvolved beamforming are given, its computational complexity is analyzed, and its performance is evaluated with simulated and real data.

scholarly journals Machine Learning and Prediction-Based Resource Management in IoT Considering Qos

2019 ◽  
Vol 8 (2) ◽  
pp. 687-694
Keyword(s):  
Machine Learning ◽  
Prediction Model ◽  
Short Term Memory ◽  
Real Data ◽  
Computing Methods ◽  
Energy Utilization ◽  
Real Field ◽  
Proposed Model ◽  
Improved Performance ◽  
Video Sensors

Internet of Things (IoT) is one of the fast-growing technology paradigms used in every sectors, where in the Quality of Service (QoS) is a critical component in such systems and usage perspective with respect to ProSumers (producer and consumers). Most of the recent research works on QoS in IoT have used Machine Learning (ML) techniques as one of the computing methods for improved performance and solutions. The adoption of Machine Learning and its methodologies have become a common trend and need in every technologies and domain areas, such as open source frameworks, task specific algorithms and using AI and ML techniques. In this work we propose an ML based prediction model for resource optimization in the IoT environment for QoS provisioning. The proposed methodology is implemented by using a multi-layer neural network (MNN) for Long Short Term Memory (LSTM) learning in layered IoT environment. Here the model considers the resources like bandwidth and energy as QoS parameters and provides the required QoS by efficient utilization of the resources in the IoT environment. The performance of the proposed model is evaluated in a real field implementation by considering a civil construction project, where in the real data is collected by using video sensors and mobile devices as edge nodes. Performance of the prediction model is observed that there is an improved bandwidth and energy utilization in turn providing the required QoS in the IoT environment.

Large‐scale three‐dimensional seismic models and their interpretive significance

Geophysics ◽  
1990 ◽  
Vol 55 (9) ◽  
pp. 1166-1182 ◽  
Author(s):  
Irshad R. Mufti
Keyword(s):  
Finite Difference ◽  
Wave Field ◽  
Large Scale ◽  
Three Dimensional ◽  
Synthetic Data ◽  
Real Data ◽  
The Real ◽  
Need To Evaluate ◽  
Zero Offset ◽  
Seismic Models

Finite‐difference seismic models are commonly set up in 2-D space. Such models must be excited by a line source which leads to different amplitudes than those in the real data commonly generated from a point source. Moreover, there is no provision for any out‐of‐plane events. These problems can be eliminated by using 3-D finite‐difference models. The fundamental strategy in designing efficient 3-D models is to minimize computational work without sacrificing accuracy. This was accomplished by using a (4,2) differencing operator which ensures the accuracy of much larger operators but requires many fewer numerical operations as well as significantly reduced manipulation of data in the computer memory. Such a choice also simplifies the problem of evaluating the wave field near the subsurface boundaries of the model where large operators cannot be used. We also exploited the fact that, unlike the real data, the synthetic data are free from ambient noise; consequently, one can retain sufficient resolution in the results by optimizing the frequency content of the source signal. Further computational efficiency was achieved by using the concept of the exploding reflector which yields zero‐offset seismic sections without the need to evaluate the wave field for individual shot locations. These considerations opened up the possibility of carrying out a complete synthetic 3-D survey on a supercomputer to investigate the seismic response of a large‐scale structure located in Oklahoma. The analysis of results done on a geophysical workstation provides new insight regarding the role of interference and diffraction in the interpretation of seismic data.

scholarly journals Stationary Time Statistical Property of Ionospheric Clutter in High-Frequency Surface-Wave Radar

2019 ◽  
Vol 2019 ◽  
pp. 1-6
Author(s):  
Shang Shang ◽  
Kangning He ◽  
Zhaobin Wang ◽  
Xuguang Yang
Keyword(s):  
Surface Wave ◽  
High Frequency ◽  
Real Data ◽  
Radar System ◽  
Detection Performance ◽  
Frequency Selection ◽  
Statistical Property ◽  
Stationary Time ◽  
Wave Radar

In HFSWR (high-frequency surface-wave radar) system, the detection performance is impacted seriously by ionospheric clutter. Frequency selection is an effective method to avoid the effect of ionospheric clutter. The key to the method is the stationarity of ionospheric clutter over a period of time. This paper mainly researches the stationary time statistical property of the ionospheric clutter. A large number of real data including ionospheric clutter in HFSWR are processed and analyzed. It shows that ionospheric clutter in HFSWR has the characteristics of approximate stationarity within a period of time.

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