↓ Skip to main content

What makes an accurate and reliable subject-specific finite element model? A case study of an elephant femur

Overview of attention for article published in Journal of The Royal Society Interface, July 2011
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

blogs
2 blogs
twitter
1 X user

Citations

dimensions_citation
18 Dimensions

Readers on

mendeley
65 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
What makes an accurate and reliable subject-specific finite element model? A case study of an elephant femur
Published in
Journal of The Royal Society Interface, July 2011
DOI 10.1098/rsif.2011.0323
Pubmed ID
Authors

O. Panagiotopoulou, S. D. Wilshin, E. J. Rayfield, S. J. Shefelbine, J. R. Hutchinson

Abstract

Finite element modelling is well entrenched in comparative vertebrate biomechanics as a tool to assess the mechanical design of skeletal structures and to better comprehend the complex interaction of their form-function relationships. But what makes a reliable subject-specific finite element model? To approach this question, we here present a set of convergence and sensitivity analyses and a validation study as an example, for finite element analysis (FEA) in general, of ways to ensure a reliable model. We detail how choices of element size, type and material properties in FEA influence the results of simulations. We also present an empirical model for estimating heterogeneous material properties throughout an elephant femur (but of broad applicability to FEA). We then use an ex vivo experimental validation test of a cadaveric femur to check our FEA results and find that the heterogeneous model matches the experimental results extremely well, and far better than the homogeneous model. We emphasize how considering heterogeneous material properties in FEA may be critical, so this should become standard practice in comparative FEA studies along with convergence analyses, consideration of element size, type and experimental validation. These steps may be required to obtain accurate models and derive reliable conclusions from them.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 65 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 2%
Portugal 1 2%
Germany 1 2%
Belgium 1 2%
Unknown 61 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 14 22%
Student > Bachelor 8 12%
Researcher 7 11%
Professor 7 11%
Professor > Associate Professor 6 9%
Other 16 25%
Unknown 7 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 21 32%
Engineering 15 23%
Earth and Planetary Sciences 5 8%
Medicine and Dentistry 3 5%
Materials Science 2 3%
Other 8 12%
Unknown 11 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 20 August 2014.
All research outputs
#1,835,880
of 22,758,963 outputs
Outputs from Journal of The Royal Society Interface
#781
of 3,051 outputs
Outputs of similar age
#8,637
of 116,876 outputs
Outputs of similar age from Journal of The Royal Society Interface
#8
of 40 outputs
Altmetric has tracked 22,758,963 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,051 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.8. This one has gotten more attention than average, scoring higher than 74% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 116,876 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 92% of its contemporaries.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.