2013
DOI: 10.1080/10298436.2013.857772
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Packing theory-based framework for evaluating resilient modulus of unbound granular materials

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Cited by 29 publications
(9 citation statements)
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“…Comparing the two PD plots, the test with w ¼ 3.5% showed a much higher PD, which was probably due to the PC. Thus the probable explanation is that moisture aided the PC, reorientation and change in packing arrangement of the particles which in turn increased the M R of the material (Yideti et al 2013, Liu et al 2014. Thus when the w was increasing up to close to the optimum, the material experienced a faster PC aided by moisture that resulted in increased M R .…”
Section: Analysis Of the Resultsmentioning
confidence: 87%
“…Comparing the two PD plots, the test with w ¼ 3.5% showed a much higher PD, which was probably due to the PC. Thus the probable explanation is that moisture aided the PC, reorientation and change in packing arrangement of the particles which in turn increased the M R of the material (Yideti et al 2013, Liu et al 2014. Thus when the w was increasing up to close to the optimum, the material experienced a faster PC aided by moisture that resulted in increased M R .…”
Section: Analysis Of the Resultsmentioning
confidence: 87%
“…In unbound granular materials, packing arrangement which is to a great extend controlled by the PSD influences the mechanical behavior of granular materials (Santamarina & Cho, 2004). Effect of aggregate packing on potential for permanent deformation (Yideti, Birgisson, Jelagin, & Guarin, 2013), resilient behavior (Yideti, Birgisson, Jelagin, & Guarin, 2014) and California bearing ratio is approved through theoretical and experimental research and analysis.…”
Section: Stiffness Characteristicsmentioning
confidence: 99%
“…This type of approach is particularly beneficial as it not only allows to predict the materials performance based on its gradation, but also as it provides a tool to adjust the gradation to achieve optimal performance in the field. As the gradation model presented in Yideti et al (2013a) has already been used successfully to predict granular materials performance with respect to resistance to permanent deformation (Yideti et al, 2013a) and resilient modulus properties (Yideti, Birgisson, Jelagin, & Guarin 2013b), extending it further to describe the CBR performance of unbound materials also allows to establish a unified framework for unbound granular materials performance prediction. Yideti et al (2013a) presented the packing theory-based framework for unbound granular materials composed of stones with a size distribution described through a gradation analysis.…”
Section: Introductionmentioning
confidence: 99%