Computational generation of statistical volume elements of biphasic asphalt concrete and its material behavior

Computational generation of statistical volume elements of biphasic asphalt concrete and its... Asphalt concrete is a complex mixture appearing as a biphasic material containing mineral aggregates and bitumen and as a triphasic material containing voids in addition [1]. Because of that, the overall material behavior of the asphalt concrete cannot be obtained easily from the known material data of its components and therefore, we apply computational homogenization based on statistical volume elements (SVEs). These SVEs are assumed to be statistically representative to obtain the material properties by finite element simulations and homogenization. We generate these microstructures computationally based on data from XRCT scans. The artificial microstructures show reduced geometrical complexity and therefore, reduced numerical costs compared to direct numerical simulations based on XRCT data. (© 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim) http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Proceedings in Applied Mathematics & Mechanics Wiley

Computational generation of statistical volume elements of biphasic asphalt concrete and its material behavior

Loading next page...
 
/lp/wiley/computational-generation-of-statistical-volume-elements-of-biphasic-uE0PHK81GD
Publisher
Wiley Subscription Services, Inc., A Wiley Company
Copyright
Copyright © 2017 Wiley Subscription Services
ISSN
1617-7061
eISSN
1617-7061
D.O.I.
10.1002/pamm.201710212
Publisher site
See Article on Publisher Site

Abstract

Asphalt concrete is a complex mixture appearing as a biphasic material containing mineral aggregates and bitumen and as a triphasic material containing voids in addition [1]. Because of that, the overall material behavior of the asphalt concrete cannot be obtained easily from the known material data of its components and therefore, we apply computational homogenization based on statistical volume elements (SVEs). These SVEs are assumed to be statistically representative to obtain the material properties by finite element simulations and homogenization. We generate these microstructures computationally based on data from XRCT scans. The artificial microstructures show reduced geometrical complexity and therefore, reduced numerical costs compared to direct numerical simulations based on XRCT data. (© 2017 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Journal

Proceedings in Applied Mathematics & MechanicsWiley

Published: Jan 1, 2017

References

You’re reading a free preview. Subscribe to read the entire article.


DeepDyve is your
personal research library

It’s your single place to instantly
discover and read the research
that matters to you.

Enjoy affordable access to
over 12 million articles from more than
10,000 peer-reviewed journals.

All for just $49/month

Explore the DeepDyve Library

Unlimited reading

Read as many articles as you need. Full articles with original layout, charts and figures. Read online, from anywhere.

Stay up to date

Keep up with your field with Personalized Recommendations and Follow Journals to get automatic updates.

Organize your research

It’s easy to organize your research with our built-in tools.

Your journals are on DeepDyve

Read from thousands of the leading scholarly journals from SpringerNature, Elsevier, Wiley-Blackwell, Oxford University Press and more.

All the latest content is available, no embargo periods.

See the journals in your area

DeepDyve Freelancer

DeepDyve Pro

Price
FREE
$49/month

$360/year
Save searches from
Google Scholar,
PubMed
Create lists to
organize your research
Export lists, citations
Read DeepDyve articles
Abstract access only
Unlimited access to over
18 million full-text articles
Print
20 pages/month
PDF Discount
20% off