Materials Map

Discover the materials research landscape. Find experts, partners, networks.

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The Materials Map is an open tool for improving networking and interdisciplinary exchange within materials research. It enables cross-database search for cooperation and network partners and discovering of the research landscape.

The dashboard provides detailed information about the selected scientist, e.g. publications. The dashboard can be filtered and shows the relationship to co-authors in different diagrams. In addition, a link is provided to find contact information.

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The Materials Map is still under development. In its current state, it is only based on one single data source and, thus, incomplete and contains duplicates. We are working on incorporating new open data sources like ORCID to improve the quality and the timeliness of our data. We will update Materials Map as soon as possible and kindly ask for your patience.

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in Cooperation with on an Cooperation-Score of 37%

Topics

Publications (1/1 displayed)

  • 2021A preoperative predictive study of advantages of airway changes after maxillomandibular advancement surgery using computational fluid dynamics analysis.1citations

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Chart of shared publication
Sato, T.
1 / 12 shared
Tonogi, M.
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Tanuma, T.
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Suzuki, M.
1 / 6 shared
Azaki, H.
1 / 1 shared
Yamagata, K.
1 / 1 shared
Himejima, A.
1 / 1 shared
Ogisawa, S.
1 / 1 shared
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2021

Co-Authors (by relevance)

  • Sato, T.
  • Tonogi, M.
  • Tanuma, T.
  • Suzuki, M.
  • Azaki, H.
  • Yamagata, K.
  • Himejima, A.
  • Ogisawa, S.
OrganizationsLocationPeople

article

A preoperative predictive study of advantages of airway changes after maxillomandibular advancement surgery using computational fluid dynamics analysis.

  • Sato, T.
  • Shinozuka, Keiji
  • Tonogi, M.
  • Tanuma, T.
  • Suzuki, M.
  • Azaki, H.
  • Yamagata, K.
  • Himejima, A.
  • Ogisawa, S.
Abstract

The purpose of this study was to develop a simulation approach for predicting maxillomandibular advancement-induced airway changes using computational fluid dynamics. Eight patients with jaw deformities who underwent maxillomandibular advancement and genioglossus advancement surgery were included in this study. Computed tomography scans and rhinomanometric readings were performed both preoperatively and postoperatively. Computational fluid dynamics models were created, and airflow simulations were performed using computational fluid dynamics software; the preferable number of computational mesh points was at least 10 million cells. The results for the right and left nares, including simulation and postoperative measurements, were qualitatively consistent, and surgery reduced airflow pressure loss. Geometry prediction simulation results were qualitatively consistent with the postoperative stereolithography data and postoperative simulation results. Simulations were performed with either the right or left naris blocked, and the predicted values were similar to those found clinically. In addition, geometry prediction simulation results were qualitatively consistent with the postoperative stereolithography data and postoperative simulation results. These findings suggest that geometry prediction simulation facilitates the preoperative prediction of the postoperative structural outcome.

Topics
  • simulation
  • computed tomography scan