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Afterwards, based on the compaction index concept and virtual packing density, the compressible packing model (CPM) for the mixture design of UHPC was proposed (Larrard and Sedran 2002).
Our results indicated that the application of CR has significant effect on decreasing the amount of soil compaction index (based on decreasing of bulk density and penetration resistance) and increasing volumetric water content at different suction points so that adding crumb rubber modified the water retention curve coefficients.
Following our small and simple modifications, the Stovall and de Larrard models could accurately simulate the packing densities of blended cements with different particle sizes in various combinations, mainly those related to the interaction functions accounting for loosening l(r) and wall w(r) effects and the compaction index, K.
We previously calculated the compaction index (CI) of ELP by calculating the hydrodynamic radius of a polypeptide of the same MW of ELP adopting either a globular or unfolded conformation and compared these values to the hydrodynamic radius of ELP measured by DLS and SV.
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Those values of reduction in mixing and compaction temperatures were obtained comparing the compaction densification index (CDI) and the traffic densification index (TDI) results with the ones found for conventional HMA.
Topographic data sampled using a GPS receiver embedded on an ATV were accurate (<10 cm) compared to TS. Soil compaction indexes (bulk density, clay and clay/OM ratio) were the most closely related to yield (r2=−0.57 to −0.60).
We were inspired to furnish information concerning the promising applicability of a hybrid approach involving artificial neural networks (ANNs), with manifold network functions, and a meta-heuristic optimization algorithm for prediction of soil compaction indices.
The DCC mixtures made with 5%, 10%, or 15% BFA and 25% of BBA can reach a compactness index of 99% with a compaction work lower than specified by the Standards.
The compaction energy index proved that using RCA would save some amount of compaction energy.
However, the compaction energy index (CEI) of WMA samples containing FA is more sensitive to the Sasobit® content variations at each mixing temperature.
The predictor variables included in the formulations are bottom ash dosage, dry unit weight, relative compaction, brittleness index and energy absorption capacity.
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