Open Access
,
страницы 416-428
Graph-Based M-tortuosity Estimation
Тип публикации: Book Chapter
Дата публикации: 2021-05-15
scimago Q2
SJR: 0.352
CiteScore: 2.4
Impact factor: —
ISSN: 03029743, 16113349, 18612075, 18612083
Краткое описание
The sinuosity of a porous microstructure may be quantified by geometric tortuosity characterization, namely the ratio of geodesic and euclidean distances. The assessment of geometric tortuosity, among other descriptors, is of importance for rigorous characterization of complex materials. This paper proposes a new way of calculation, based on a graph structure, of the topological descriptor M-tortuosity introduced in [3]. The original M-tortuosity descriptor is based on a geodesic distance computation algorithm. A pore network partition [7] method is used to extract pores and construct a graph from the void of a porous microstructure. Through this scheme, pores are the nodes, distances between pores are the arcs between nodes and the goal boils down to the determination of the shortest paths between nodes. Solving this on a graph requires a tree search formulation of the problem. Our results have shown a drastic time complexity decrease while preserving good agreement with the original results. The added value of our method consists in its simplicity of implementation and its reduced execution time.
Найдено
Ничего не найдено, попробуйте изменить настройки фильтра.
Для доступа к списку цитирований публикации необходимо авторизоваться.
Топ-30
Журналы
|
1
|
|
|
Science and Technology for Energy Transition
1 публикация, 100%
|
|
|
1
|
Издатели
|
1
|
|
|
EDP Sciences
1 публикация, 100%
|
|
|
1
|
- Мы не учитываем публикации, у которых нет DOI.
- Статистика публикаций обновляется еженедельно.
Вы ученый?
Создайте профиль, чтобы получать персональные рекомендации коллег, конференций и новых статей.
Метрики
1
Всего цитирований:
1
Цитирований c 2025:
0
Цитировать
ГОСТ |
RIS |
BibTex
Цитировать
ГОСТ
Скопировать
Hammoumi A. et al. Graph-Based M-tortuosity Estimation // Lecture Notes in Computer Science. 2021. pp. 416-428.
ГОСТ со всеми авторами (до 50)
Скопировать
Hammoumi A., Moreaud M., Jolimaitre E., Chevalier T., Novikov A., Klotz M. Graph-Based M-tortuosity Estimation // Lecture Notes in Computer Science. 2021. pp. 416-428.
Цитировать
RIS
Скопировать
TY - GENERIC
DO - 10.1007/978-3-030-76657-3_30
UR - https://doi.org/10.1007/978-3-030-76657-3_30
TI - Graph-Based M-tortuosity Estimation
T2 - Lecture Notes in Computer Science
AU - Hammoumi, Adam
AU - Moreaud, Maxime
AU - Jolimaitre, Elsa
AU - Chevalier, Thibaud
AU - Novikov, Alexey
AU - Klotz, Michaela
PY - 2021
DA - 2021/05/15
PB - Springer Nature
SP - 416-428
SN - 0302-9743
SN - 1611-3349
SN - 1861-2075
SN - 1861-2083
ER -
Цитировать
BibTex (до 50 авторов)
Скопировать
@incollection{2021_Hammoumi,
author = {Adam Hammoumi and Maxime Moreaud and Elsa Jolimaitre and Thibaud Chevalier and Alexey Novikov and Michaela Klotz},
title = {Graph-Based M-tortuosity Estimation},
publisher = {Springer Nature},
year = {2021},
pages = {416--428},
month = {may}
}
Ошибка в публикации?