Evaluating RLWT Rutting Test of Asphalt Mixtures Based on Industrial Computerized Tomography

Joint Authors

Zhang, Xiaoning
Wu, Wenliang
Li, Zhi
Li, Minghui

Source

Advances in Materials Science and Engineering

Issue

Vol. 2018, Issue 2018 (31 Dec. 2018), pp.1-8, 8 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2018-06-24

Country of Publication

Egypt

No. of Pages

8

Abstract EN

To eliminate the effects of image’s light and shade difference when separating and distinguishing the material composition, a method is put forward, namely, ring-type and partitions threshold segmentation.

It means setting up different segment threshold for different areas of the same image and then combining these different areas into one image.

Furthermore, by analyzing the CT image before and after the RLWT rutting test for the drilling specimen and Marshall specimen and taking the volume of air voids and the angle (alpha) between max main axis and X axis, the differences of two kinds of specimens’ macrotest results were discussed from internal structure distribution.

Here, we show that there are differences between macrotest results of two kinds of specimens because of internal air voids and aggregate distribution, which should be considered for compliance testing.

American Psychological Association (APA)

Wu, Wenliang& Li, Zhi& Zhang, Xiaoning& Li, Minghui. 2018. Evaluating RLWT Rutting Test of Asphalt Mixtures Based on Industrial Computerized Tomography. Advances in Materials Science and Engineering،Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1121480

Modern Language Association (MLA)

Wu, Wenliang…[et al.]. Evaluating RLWT Rutting Test of Asphalt Mixtures Based on Industrial Computerized Tomography. Advances in Materials Science and Engineering No. 2018 (2018), pp.1-8.
https://search.emarefa.net/detail/BIM-1121480

American Medical Association (AMA)

Wu, Wenliang& Li, Zhi& Zhang, Xiaoning& Li, Minghui. Evaluating RLWT Rutting Test of Asphalt Mixtures Based on Industrial Computerized Tomography. Advances in Materials Science and Engineering. 2018. Vol. 2018, no. 2018, pp.1-8.
https://search.emarefa.net/detail/BIM-1121480

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1121480