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 (3/3 displayed)

  • 2020In silico trial to test COVID-19 candidate vaccines: a case study with UISS platform50citations
  • 2019Predicting the artificial immunity induced by RUTI® vaccine against tuberculosis using universal immune system simulator (UISS)36citations
  • 2012Accuracy of finite element predictions in sideways load configurations for the proximal human femurcitations

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Pappalardo, Francesco
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Raciti, Giuseppina
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Motta, Santo
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Fichera, Epifanio
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Pennisi, Marzio
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Walker, Kenneth B.
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Co-Authors (by relevance)

  • Pappalardo, Francesco
  • Raciti, Giuseppina
  • Motta, Santo
  • Russo, Giulia
  • Fichera, Epifanio
  • Pennisi, Marzio
  • Walker, Kenneth B.
  • Mitra, Dipendra Kumar
  • Palumbo, Giuseppe Alessandro Parasiliti
  • Cardona, Pere-Joan
  • Bonaccorso, Angela
  • Sgroi, Giuseppe
  • Amat, Merce
  • Zani, Lorenzo
  • Taddei, Fulvia
  • Schileo, Enrico
  • Cristofolini, Luca
  • Grassi, Lorenzo
  • Juszczyk, Mateusz
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article

Accuracy of finite element predictions in sideways load configurations for the proximal human femur

  • Zani, Lorenzo
  • Taddei, Fulvia
  • Schileo, Enrico
  • Viceconti, Marco
  • Cristofolini, Luca
  • Grassi, Lorenzo
  • Juszczyk, Mateusz
Abstract

in Undetermined<br/>Subject-specific finite element models have been used to predict stress-state and fracture risk in individual patients. While many studies analysed quasi-axial loading configurations, only few works simulated sideways load configurations, such as those arising in a fall. The majority among these latter directly predicted bone strength, without assessing elastic strain prediction accuracy. The aim of the present work was to evaluate if a subject-specific finite element modelling technique from CT data that accurately predicted strains in quasi-axial loading configurations is suitable to accurately predict strains also when applying low magnitude loads in sideways configurations. To this aim, a combined numerical–experimental study was performed to compare finite element predicted strains with strain-gauge measurements from three cadaver proximal femurs instrumented with sixteen strain rosettes and tested non-destructively under twelve loading configurations, spanning a wide cone (0–30° for both adduction and internal rotation angles) of sideways fall scenarios. The results of the present study evidenced a satisfactory agreement between experimentally measured and predicted strains (R2 greater than 0.9, RMSE% lower than 10%) and displacements. The achieved strain prediction accuracy is comparable to those obtained in state of the art studies in quasi-axial loading configurations. Still, the presence of the highest strain prediction errors (around 30%) in the lateral neck aspect would deserve attention in future studies targeting bone failure.

Topics
  • impedance spectroscopy
  • strength