Supercomputer Simulation Study of the Convergence of Iterative Methods for Solving Inverse Problems of 3D Acoustic Tomography with the Data on a Cylindrical Surface

Romanov, S. Yu.

doi:10.1007/978-3-030-05807-4_33

Cited by 3 publications

(2 citation statements)

References 23 publications

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“…Furthermore, the proposed scalable numerical algorithms can be efficiently parallelized in the calculations performed on 384 computing CPU cores of the supercomputer "Lomonosov-2" at Lomonosov Moscow State University. Romanov [12] presents the development of effective methods of 3D acoustic tomography. The inverse problem of coefficients for a hyperbolic equation of acoustic tomography, where the speed of sound and the absorption factor in 3D space is unknown.…”

Section: Bazulin Et Al [10] [9] [11]mentioning

confidence: 99%

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Supercomputing for Acoustic Simulation. A Review

FABIÁN BASTIDAS-ALARCÓN et al.

2023

RLJ

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Acoustics plays a significant role in various aspects of everyday life and finds applications in diverse fields such as medicine, where ultrasound is used to detect anomalies in the human body, noise pollution control, music, and the study of the universe, among others. This article explores the extent of scientific literature on supercomputing for acoustic simulation. The methodology consists of four steps: formulating research questions, conducting a literature search, selecting highly impactful articles, and data compilation. Out of a total of 211 articles obtained from reviewed databases, including Springer, Google Scholar, ScienceDirect, Scientific Reports, ChEES, Journal of Physics, Hindawi, and Research Article, 20 articles were chosen for analysis. It was concluded that the dynamic study of sound is indeed complex, requiring intensive data processing. This necessitates the use of supercomputers with multiple cores to solve various mathematical models, with the fundamental focus of the study being the resolution of the wave equation.

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Section: Bazulin Et Al [10] [9] [11]mentioning

confidence: 99%

“…By obtaining a 3D image of the material's behavior. It can be more accurate in its evaluation[12],[9]. Finally, noise mapping of urban areas over time is possible thanks to simulation since it collects pollution data, processes it and can make approximations as a function of time, improving noise mitigation plans and monitoring [14],[16],[11],[3],[18].…”

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confidence: 99%

Supercomputing for Acoustic Simulation. A Review

FABIÁN BASTIDAS-ALARCÓN et al.

2023

RLJ

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Three-Dimensional Ultrasound Tomography: Mathematical Methods and Experimental Results

Goncharsky

Seryozhnikov

2019

Communications in Computer and Information Science

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Inverse problems of experimental data interpretation in 3D ultrasound tomography

Goncharskii

Кубышкин

Романов

et al. 2019

Numerical Methods and Programming (Vychislitel'nye Metody I Programmirovanie)

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Обратная задача 3D ультразвуковой томографии рассматривается в статье как нелинейная коэффициентная обратная задача для уравнения гиперболического типа. Используемая математическая модель хорошо описывает как дифракционные эффекты, так и поглощение ультразвука в неоднородной среде. В рассматриваемой постановке реконструируется скорость распространения акустической волны как функция трех координат. Количество неизвестных в нелинейной обратной задаче составляет порядка 50 миллионов. Разработанные итерационные алгоритмы решения обратной задачи ориентированы на использование GPUкластеров. Основным результатом работы является апробация алгоритмов на экспериментальных данных. В эксперименте использовался стенд для 3D ультразвуковых томографических исследований, разработанный в МГУ имени М.В. Ломоносова. Акустические параметры фантомов близки к акустическим параметрам мягких тканей человека. Объем экспериментальных данных составляет порядка 3 ГБ. Интерпретация данных эксперимента позволила не только продемонстрировать эффективность разработанных алгоритмов, но и подтвердила адекватность математической модели реальности. Для реализации разработанных численных алгоритмов использовался графический кластер суперкомпьютера Ломоносов-2. The inverse problem of 3D ultrasound tomography is considered in this paper as a nonlinear coefficient inverse problem for a hyperbolic equation. The employed mathematical model accurately describes the effects of ultrasound wave diffraction and absorption in inhomogeneous media. The velocity of acoustic waves inside the test sample is reconstructed as an unknown function of three spatial coordinates. The number of unknowns in the nonlinear inverse problem reaches 50 million. The developed iterative algorithms for solving the inverse problem are designed for GPU clusters. The main result of this study is testing the developed algorithms on experimental data. The experiments were carried out using a 3D ultrasound tomographic setup developed at Lomonosov Moscow State University. Acoustic properties of the test samples were close to those of human soft tissues. The volume of data collected in experiments is up to 3 GB. Experimental results show the efficiency of the proposed algorithms and confirm that the mathematical model is adequate to reality. The proposed algorithms were tested on the GPU partition of Lomonosov2 supercomputer.

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Supercomputer Simulation Study of the Convergence of Iterative Methods for Solving Inverse Problems of 3D Acoustic Tomography with the Data on a Cylindrical Surface

Cited by 3 publications

References 23 publications

Supercomputing for Acoustic Simulation. A Review

Supercomputing for Acoustic Simulation. A Review

Three-Dimensional Ultrasound Tomography: Mathematical Methods and Experimental Results

Inverse problems of experimental data interpretation in 3D ultrasound tomography

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