Inverse problem for the nonlinear convection–diffusion equation by using the multigrid method and constraint data

In the article, we propose a combination method based on the multigrid method and constraint data to solve the inverse problem in the context of the nonlinear convection–diffusion equation in the multiphase porous media flow. The inverse problem consists of a data-fitting term involving the discreti...

Full description

Saved in:
Bibliographic Details
Main Authors: Wang, Shuai, Ling, Shiyi, Chao, Heyang, Qi, Yunfei, Zhang, Wenwen, Ma, Qiang, Liu, Tao
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2024
Subjects:
Online Access:https://hdl.handle.net/10356/181479
Tags: Add Tag
No Tags, Be the first to tag this record!
Institution: Nanyang Technological University
Language: English
id sg-ntu-dr.10356-181479
record_format dspace
spelling sg-ntu-dr.10356-1814792024-12-06T15:44:20Z Inverse problem for the nonlinear convection–diffusion equation by using the multigrid method and constraint data Wang, Shuai Ling, Shiyi Chao, Heyang Qi, Yunfei Zhang, Wenwen Ma, Qiang Liu, Tao School of Electrical and Electronic Engineering Engineering Nonlinear convection–diffusion equation Constraint data In the article, we propose a combination method based on the multigrid method and constraint data to solve the inverse problem in the context of the nonlinear convection–diffusion equation in the multiphase porous media flow. The inverse problem consists of a data-fitting term involving the discretization of a direct problem, a constraint term concerning the incorporation of constraint data, and a regularization term dealing with the improvement of stability. A multigrid method, which is specialized for large-scale problems and works by keeping the consistence of objective functionals between different grids, is applied in the process of inversion. Based on the numerical results, the proposed combination method has the advantages of fast calculation, high precision, good stability, and strong anti-noise ability in computation. It obtains good performance under various noise levels, as well as outperforming any one method used alone. Published version This research was funded by the Research Project on Graduate Education and Teaching Reform of Hebei Province of China (YJG2024133), the Open Fund Project of Marine Ecological Restoration and Smart Ocean Engineering Research Center of Hebei Province (HBMESO2321), the Technical Service Project of Eighth Geological Brigade of Hebei Bureau of Geology and Mineral Resources Exploration (KJ2022-021), the Technical Service Project of Hebei Baodi Construction Engineering Co., Ltd. (KJ2024-012), the Natural Science Foundation of Hebei Province of China (A2020501007), the Fundamental Research Funds for the Central Universities (N2123015). 2024-12-03T08:35:46Z 2024-12-03T08:35:46Z 2024 Journal Article Wang, S., Ling, S., Chao, H., Qi, Y., Zhang, W., Ma, Q. & Liu, T. (2024). Inverse problem for the nonlinear convection–diffusion equation by using the multigrid method and constraint data. Mathematics, 12(15), 2402-. https://dx.doi.org/10.3390/math12152402 2227-7390 https://hdl.handle.net/10356/181479 10.3390/math12152402 2-s2.0-85200763654 15 12 2402 en Mathematics © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering
Nonlinear convection–diffusion equation
Constraint data
spellingShingle Engineering
Nonlinear convection–diffusion equation
Constraint data
Wang, Shuai
Ling, Shiyi
Chao, Heyang
Qi, Yunfei
Zhang, Wenwen
Ma, Qiang
Liu, Tao
Inverse problem for the nonlinear convection–diffusion equation by using the multigrid method and constraint data
description In the article, we propose a combination method based on the multigrid method and constraint data to solve the inverse problem in the context of the nonlinear convection–diffusion equation in the multiphase porous media flow. The inverse problem consists of a data-fitting term involving the discretization of a direct problem, a constraint term concerning the incorporation of constraint data, and a regularization term dealing with the improvement of stability. A multigrid method, which is specialized for large-scale problems and works by keeping the consistence of objective functionals between different grids, is applied in the process of inversion. Based on the numerical results, the proposed combination method has the advantages of fast calculation, high precision, good stability, and strong anti-noise ability in computation. It obtains good performance under various noise levels, as well as outperforming any one method used alone.
author2 School of Electrical and Electronic Engineering
author_facet School of Electrical and Electronic Engineering
Wang, Shuai
Ling, Shiyi
Chao, Heyang
Qi, Yunfei
Zhang, Wenwen
Ma, Qiang
Liu, Tao
format Article
author Wang, Shuai
Ling, Shiyi
Chao, Heyang
Qi, Yunfei
Zhang, Wenwen
Ma, Qiang
Liu, Tao
author_sort Wang, Shuai
title Inverse problem for the nonlinear convection–diffusion equation by using the multigrid method and constraint data
title_short Inverse problem for the nonlinear convection–diffusion equation by using the multigrid method and constraint data
title_full Inverse problem for the nonlinear convection–diffusion equation by using the multigrid method and constraint data
title_fullStr Inverse problem for the nonlinear convection–diffusion equation by using the multigrid method and constraint data
title_full_unstemmed Inverse problem for the nonlinear convection–diffusion equation by using the multigrid method and constraint data
title_sort inverse problem for the nonlinear convection–diffusion equation by using the multigrid method and constraint data
publishDate 2024
url https://hdl.handle.net/10356/181479
_version_ 1819112941762379776