scholarly journals A modal/WKB inversion method for determining sound‐speed profiles in the ocean and ocean bottom

1988 ◽  
Vol 84 (S1) ◽  
pp. S175-S175
Author(s):  
Kevin D. Casey ◽  
George V. Frisk
Keyword(s):  
Sound Speed ◽  
Inversion Method ◽  
Ocean Bottom

scholarly journals Application of a stochastic inversion method for estimating the sound speed in the ocean bottom

1995 ◽  
Vol 98 (5) ◽  
pp. 2972-2972
Author(s):  
Kazuhiko Ohta ◽  
Itaru Morishita ◽  
Shunji Ozaki ◽  
Tsuneo Ishiwata
Keyword(s):  
Sound Speed ◽  
Inversion Method ◽  
Ocean Bottom ◽  
Stochastic Inversion

Effects of tidally varying sound speed on acoustic propagation over a sloping ocean bottom

1979 ◽  
Vol 66 (4) ◽  
pp. 1108-1119 ◽  
Author(s):  
K. G. Hamilton ◽  
W. L. Siegmann ◽  
M. J. Jacobson
Keyword(s):  
Sound Speed ◽  
Acoustic Propagation ◽  
Ocean Bottom

FLUCTUATIONS OF THE MODAL ARRIVAL TIMES DUE TO LINEAR INTERNAL WAVES: APPLICATION TO INVERSION

2006 ◽  
Vol 14 (04) ◽  
pp. 469-487 ◽  
Author(s):  
GERALDINE BOUCHAGE ◽  
MICHAEL I. TAROUDAKIS
Keyword(s):  
Travel Time ◽  
Internal Waves ◽  
Acoustic Field ◽  
Sound Speed ◽  
Inversion Method ◽  
Perturbation Approach ◽  
Arrival Times ◽  
Inversion Procedure ◽  
Time Information ◽  
A Current

It is well known that internal waves in the ocean are an important source of environmental variability which has serious effects in the structure of an acoustic field due to a known source. When measurements of the acoustic field form the input data for an inversion procedure aiming at the recovery of the environmental parameters, the information they carry on includes the internal wave effects. It is therefore natural to assume that neglecting the effects of the internal waves in an inversion procedure based on acoustic field measurements, errors are induced in the inversion. The paper deals with this problem and addresses the case of inversion schemes using travel time information of an acoustic signal. Using a statistical 2D model of the internal waves, based on the Garrett and Munk spectrum, the spatial and temporal evolution of the internal waves field as well as the fluctuations of the sound speed profile is estimated for a characteristic shallow-water environment. Considering a sound speed anomaly in the water column as the oceanographic feature to be recovered, the paper studies the influence of the internal waves field on the modal travel time information obtained through the propagation of a tomographic signal through this environment. The sound speed anomaly denoted as "current" is described by a suitable Gaussian function. Using an analytical expression based on a perturbation approach, the difference in the modal arrival times calculated for a background environment and a perturbed one (considering that the sound speed perturbations are due either to a current or to the summation of a current and of the internal waves field) was calculated for each propagating mode of the waveguide. These calculations led to the conclusion that the internal waves have a non-negligible impact on the arrival times and that the maximum amplitude of a current can be under- or overestimated of several meters per second when these waves are not taken into account in the inversion method, whereas they are present in the oceanic medium.

scholarly journals Bayesian Inversion for Geoacoustic Parameters in Shallow Sea

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 2150 ◽  
Author(s):  
Guangxue Zheng ◽  
Hanhao Zhu ◽  
Xiaohan Wang ◽  
Sartaj Khan ◽  
Nansong Li ◽  
...  
Keyword(s):  
Experimental Data ◽  
Sound Speed ◽  
Acoustic Pressure ◽  
Low Frequency ◽  
Field Method ◽  
Bayesian Inversion ◽  
Inversion Method ◽  
Shallow Sea ◽  
Inversion Result ◽  
Uncertainty Estimates

Geoacoustic parameter inversion is a crucial issue in underwater acoustic research for shallow sea environments and has increasingly become popular in the recent past. This paper investigates the geoacoustic parameters in a shallow sea environment using a single-receiver geoacoustic inversion method based on Bayesian theory. In this context, the seabed is regarded as an elastic medium, the acoustic pressure at different positions under low-frequency is chosen as the study object, and the theoretical prediction value of the acoustic pressure is described by the Fast Field Method (FFM). The cost function between the measured and modeled acoustic fields is established under the assumption of Gaussian data errors using Bayesian methodology. The Bayesian inversion method enables the inference of the seabed geoacoustic parameters from the experimental data, including the optimal estimates of these parameters, such as density, sound speed and sound speed attenuation, and quantitative uncertainty estimates. The optimization is carried out by simulated annealing (SA), and the Posterior Probability Density (PPD) is given as the inversion result based on the Gibbs Sampler (GS) algorithm. Inversion results of the experimental data are in good agreement with both measured values and estimates from Genetic Algorithm (GA) inversion result in the same environment. Furthermore, the results also indicate that the sound speed and density in the seabed have fewer uncertainties and are more sensitive to acoustic pressure than the sound speed attenuation. The sea noise could increase the variance of PPD, which has less influence on the sensitive parameters. The mean value of PPD could still reflect the true values of geoacoustic parameters in simulation.

scholarly journals Case study on the identification and classification of small-scale flow patterns in flaring active region

2021 ◽  
Vol 645 ◽  
pp. A52
Author(s):  
E. Philishvili ◽  
B. M. Shergelashvili ◽  
S. Buitendag ◽  
J. Raes ◽  
S. Poedts ◽  
...  
Keyword(s):  
Active Region ◽  
Solar Atmosphere ◽  
Sound Speed ◽  
Complex Structure ◽  
Emission Measure ◽  
Image Data ◽  
Flow Patterns ◽  
Small Scale ◽  
Inversion Method ◽  
Solar Dynamics Observatory

Context. We propose a novel methodology to identity flows in the solar atmosphere and classify their velocities as either supersonic, subsonic, or sonic. Aims. The proposed methodology consists of three parts. First, an algorithm is applied to the Solar Dynamics Observatory (SDO) image data to locate and track flows, resulting in the trajectory of each flow over time. Thereafter, the differential emission measure inversion method is applied to six Atmospheric Imaging Assembly (AIA) channels along the trajectory of each flow in order to estimate its background temperature and sound speed. Finally, we classify each flow as supersonic, subsonic, or sonic by performing simultaneous hypothesis tests on whether the velocity bounds of the flow are larger, smaller, or equal to the background sound speed. Methods. The proposed methodology was applied to the SDO image data from the 171 Å spectral line for the date 6 March 2012 from 12:22:00 to 12:35:00 and again for the date 9 March 2012 from 03:00:00 to 03:24:00. Eighteen plasma flows were detected, 11 of which were classified as supersonic, 3 as subsonic, and 3 as sonic at a 70% level of significance. Out of all these cases, 2 flows cannot be strictly ascribed to one of the respective categories as they change from the subsonic state to supersonic and vice versa. We labeled them as a subclass of transonic flows. Results. The proposed methodology provides an automatic and scalable solution to identify small-scale flows and to classify their velocities as either supersonic, subsonic, or sonic. It can be used to characterize the physical properties of the solar atmosphere. Conclusions. We identified and classified small-scale flow patterns in flaring loops. The results show that the flows can be classified into four classes: sub-, super-, trans-sonic, and sonic. The flows occur in the complex structure of the active region magnetic loops. The detected flows from AIA images can be analyzed in combination with the other high-resolution observational data, such as Hi-C 2.1 data, and be used for the development of theories describing the physical conditions responsible for the formation of flow patterns.

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