Data-Driven Modeling for Wave-Propagation

Tristan van Leeuwen; Peter Jan van Leeuwen; Sergiy Zhuk

doi:10.1007/978-3-030-55874-1_67

Data-Driven Modeling for Wave-Propagation

Tristan van Leeuwen^*
, Peter Jan van Leeuwen
, Sergiy Zhuk

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Many imaging modalities, such as ultrasound and radar, rely heavily on the ability to accurately model wave propagation. In most applications, the response of an object to an incident wave is recorded and the goal is to characterize the object in terms of its physical parameters (e.g., density or soundspeed). We can cast this as a joint parameter and state estimation problem. In particular, we consider the case where the inner problem of estimating the state is a weakly constrained data-assimilation problem. In this paper, we discuss a numerical method for solving this variational problem.

Original language	English
Title of host publication	Numerical Mathematics and Advanced Applications, ENUMATH 2019 - European Conference
Editors	Fred J. Vermolen, Cornelis Vuik
Publisher	Springer
Pages	683-691
Number of pages	9
ISBN (Print)	9783030558734
DOIs	https://doi.org/10.1007/978-3-030-55874-1_67
Publication status	Published - 2021
Externally published	Yes
Event	European Conference on Numerical Mathematics and Advanced Applications, ENUMATH 2019 - Egmond aan Zee, Netherlands Duration: 30 Sept 2019 → 4 Oct 2019

Publication series

Name	Lecture Notes in Computational Science and Engineering
Volume	139
ISSN (Print)	1439-7358
ISSN (Electronic)	2197-7100

Conference

Conference	European Conference on Numerical Mathematics and Advanced Applications, ENUMATH 2019
Country/Territory	Netherlands
City	Egmond aan Zee
Period	30/09/19 → 4/10/19

Bibliographical note

Publisher Copyright:
© 2021, Springer Nature Switzerland AG.

Access to Document

10.1007/978-3-030-55874-1_67

Cite this

@inproceedings{6b67cd0a5071417c80646d7dc86d64f6,

title = "Data-Driven Modeling for Wave-Propagation",

abstract = "Many imaging modalities, such as ultrasound and radar, rely heavily on the ability to accurately model wave propagation. In most applications, the response of an object to an incident wave is recorded and the goal is to characterize the object in terms of its physical parameters (e.g., density or soundspeed). We can cast this as a joint parameter and state estimation problem. In particular, we consider the case where the inner problem of estimating the state is a weakly constrained data-assimilation problem. In this paper, we discuss a numerical method for solving this variational problem.",

author = "\{van Leeuwen\}, Tristan and \{van Leeuwen\}, \{Peter Jan\} and Sergiy Zhuk",

note = "Publisher Copyright: {\textcopyright} 2021, Springer Nature Switzerland AG.; European Conference on Numerical Mathematics and Advanced Applications, ENUMATH 2019 ; Conference date: 30-09-2019 Through 04-10-2019",

year = "2021",

doi = "10.1007/978-3-030-55874-1\_67",

language = "English",

isbn = "9783030558734",

series = "Lecture Notes in Computational Science and Engineering",

publisher = "Springer",

pages = "683--691",

editor = "Vermolen, \{Fred J.\} and Cornelis Vuik",

booktitle = "Numerical Mathematics and Advanced Applications, ENUMATH 2019 - European Conference",

}

van Leeuwen, T, van Leeuwen, PJ & Zhuk, S 2021, Data-Driven Modeling for Wave-Propagation. in FJ Vermolen & C Vuik (eds), Numerical Mathematics and Advanced Applications, ENUMATH 2019 - European Conference. Lecture Notes in Computational Science and Engineering, vol. 139, Springer, pp. 683-691, European Conference on Numerical Mathematics and Advanced Applications, ENUMATH 2019, Egmond aan Zee, Netherlands, 30/09/19. https://doi.org/10.1007/978-3-030-55874-1_67

Data-Driven Modeling for Wave-Propagation. / van Leeuwen, Tristan; van Leeuwen, Peter Jan; Zhuk, Sergiy.
Numerical Mathematics and Advanced Applications, ENUMATH 2019 - European Conference. ed. / Fred J. Vermolen; Cornelis Vuik. Springer, 2021. p. 683-691 (Lecture Notes in Computational Science and Engineering; Vol. 139).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

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AU - van Leeuwen, Peter Jan

AU - Zhuk, Sergiy

PY - 2021

Y1 - 2021

N2 - Many imaging modalities, such as ultrasound and radar, rely heavily on the ability to accurately model wave propagation. In most applications, the response of an object to an incident wave is recorded and the goal is to characterize the object in terms of its physical parameters (e.g., density or soundspeed). We can cast this as a joint parameter and state estimation problem. In particular, we consider the case where the inner problem of estimating the state is a weakly constrained data-assimilation problem. In this paper, we discuss a numerical method for solving this variational problem.

AB - Many imaging modalities, such as ultrasound and radar, rely heavily on the ability to accurately model wave propagation. In most applications, the response of an object to an incident wave is recorded and the goal is to characterize the object in terms of its physical parameters (e.g., density or soundspeed). We can cast this as a joint parameter and state estimation problem. In particular, we consider the case where the inner problem of estimating the state is a weakly constrained data-assimilation problem. In this paper, we discuss a numerical method for solving this variational problem.

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U2 - 10.1007/978-3-030-55874-1_67

DO - 10.1007/978-3-030-55874-1_67

M3 - Conference contribution

AN - SCOPUS:85106439803

SN - 9783030558734

T3 - Lecture Notes in Computational Science and Engineering

SP - 683

EP - 691

BT - Numerical Mathematics and Advanced Applications, ENUMATH 2019 - European Conference

A2 - Vermolen, Fred J.

A2 - Vuik, Cornelis

PB - Springer

T2 - European Conference on Numerical Mathematics and Advanced Applications, ENUMATH 2019

Y2 - 30 September 2019 through 4 October 2019

ER -

Data-Driven Modeling for Wave-Propagation

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