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Prediction of Coarse Aggregate Performance by Micro-Deval and Other Soundness, Strength, and Intrinsic Particle Property Tests

Authors: Alexander P. Lang; Peter H. Range; David W. Fowler; John J. Allen;

Prediction of Coarse Aggregate Performance by Micro-Deval and Other Soundness, Strength, and Intrinsic Particle Property Tests

Abstract

Aggregate samples were collected from the majority of the U.S. states, as well as several Canadian provinces, and subjected to micro-Deval, Los Angeles abrasion, magnesium sulfate soundness, Canadian freeze-thaw, aggregate crushing value, absorption, specific gravity, and particle shape characterization testing to determine whether a correlation exists between laboratory aggregate tests and observed aggregate field performance. Performance ratings were assigned to each aggregate on the basis of the type of distress observed and years of service in the field in hot-mix asphalt and portland cement concrete applications. Numerical and qualitative analyses were performed to evaluate the success of separating good performers from fair and poor performers, with the micro-Deval test alone as well as the micro-Deval test combined with other tests. Furthermore, attempts were made to determine whether a correlation exists between any two tests. The tests that most consistently correlated well with field performance, either alone or in combination with other tests, were micro-Deval, Canadian freeze-thaw, absorption, and specific gravity. Several correlations indicated specific loss limits, which appeared to correctly isolate good performers from the rest. The limits found from correlation of test results and field performance are believed to be effective in identifying good performing aggregates; how-ever, care should be taken in using the limits to exclude aggregates without further consideration because good performers with higher losses were identified. Each agency should develop criteria, including a performance history versus micro-Deval loss, for each aggregate to develop a database that provides accurate performance forecasting.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
9
Top 10%
Top 10%
Average
bronze