Jiwan D. Gupta

Analysis of Resilient Modulus of Dense- and Open-Graded Aggregates

The results of analyses of laboratory resilient modulus testing conducted on dense-graded and open-graded aggregates are presented. The testing program included three different aggregate materials (crushed limestone, natural stone, and slag), five different gradation specifications, and three different moisture conditions (dry, moist, and saturated). In addition to the five aggregate specifications, test specimens were prepared so that they would satisfy the lower, central, and upper bounds for the gradations. Resilient modulus tests were conducted as closely as possible according to Strategic Highway Research Program Protocol P-46 (AASHTO T 294-92 I). The test results were analyzed using log-linear regression analysis with two-parameter (bulk stress) and three-parameter (bulk stress and octahedral shear stress) expressions for resilient modulus. The results of the testing indicate that the resilient modulus of aggregates and regression constants vary significantly depending on the type of material and va...

A thermal analysis study of recycled portland cement concrete (RPCC) aggregates

Abstract It is shown that thermal analysis and XRD data can identify the component of RPCCA which may be hydrated cement or slag (generally considered as an aggregate component). The other coarse aggregates present may be gravel or limestone. The fine aggregate often referred to as sand may be quartz or limestone in origin. The limestone may be dolomite and/or calcite in nature. The TG reveals the extent of the hydration product portlandite [Ca(OH) 2 ] in the sample, the amount of CaCO 3 present, and the amount of dolomite. XRD studies confirm the presence of these materials. In old concrete samples, the portlandite may be partially carbonated. TG data in CO 2 allows the presence of dolomite to be identified.

LABORATORY STUDY OF HYDRAULIC CONDUCTIVITY FOR COARSE AGGREGATE BASES

Inadequate drainage of pavement structures has been identified as a primary cause of pavement distress. Hydraulic conductivity is the most important factor controlling drainage capability. Coarse grained materials have high values of hydraulic conductivity. ASTM and AASHTO standard test methods are limited for coarse materials used in pavement bases and subbases because of their high permeability and large particle sizes and the horizontal flow in the field conditions. A large scale horizontal permeameter and a testing procedure were developed and the range of hydraulic conductivities of six base and subbase specifications made up of three material types provided by the Ohio Department of Transportation were evaluated. A horizontal permeameter (305 X 305 X 457 mm) and a testing procedure were developed to reduce errors produced by sidewall leakage, partial saturation, measurement of small head differences, and interpretation of turbulent flow as laminar flow. Fifty-four samples were tested, including vari...

An examination of recycled Portland cement concrete rich in dolomite and low in calcite obtained from various locations in Ohio

Thermal analysis is used to investigate 30 year old samples of concrete. In this study, thermal analysis data is combined with XRD data. The contents of these concrete samples are identified in terms of portlandite, calcite, dolomite, gypsum, and quartz. However, the calcium carbonate comes from the carbonation of the portlandite, from the fine and coarse aggregate used in the preparation of the concrete, and also from the second stage of the thermal decomposition of the dolomite. In the present study, samples of recycled Portland cement concrete are investigated which were low in calcite but high in dolomite content. The original presence of slag in these samples influences the long term leaching potential of the concrete. Leaching experiments reveal the presence of both calcium and magnesium ions in the leachate.

In Situ Test for Hydraulic Conductivity of Drainable Bases

The development and use of an in situ hydraulic conductivity test for drainable bases under existing pavements is presented. Six highway test sections were constructed by the Ohio Department of Transportation to test the drainage characteristics and durability of four unbound and two stabilized base materials. The in situ test was then used to determine the field hydraulic conductivity of the highway test section bases. This test uses an approach to Darcys law called the direct velocity technique. A standpipe is placed in a cored hole in the pavement to establish steady-state horizontal flow through the base toward the edge drains. Two probes along a radial flow line measure differential pressure and electrical resistance in the water. An electrolytic solution injected at the standpipe is used to determine the water velocity as the median resistance is noted at each probe. The in situ hydraulic conductivity is calculated by dividing the discharge velocity by the hydraulic gradient. The in situ test provided results that compare favorably with published values from carefully controlled laboratory tests. It proved to work well for high-hydraulic-conductivity drainable bases, and it has the potential to be a valuable tool for condition assessment of bases under existing pavements.

Estimation of shift parameter of headway distributions using crosscorrelation function method

The headway distributions are key building blocks for microscopic traffic flow characteristics which involves in the safety, level of service, driver behavior, and capacity of a transportation system. Usually, theoretical headway distributions show shift patterns compared to measured headway distributions. Therefore, an evaluation of the magnitude of shift is important in microscopic traffic flow. A crosscorrelation function method is used to estimate shift parameter that matches measured relative frequency and theoretical relative frequency (density function) in an optimal manner. In a worked example, both simple shift model and complicated shift model are examined. In the simple shift model, shift value does not affect the estimated parameters of density function. The complicated shift model considers the effect of shift value on the estimated parameters of density function. In the worked example, using crosscorrelation function method, 0.4 second is selected as shift value for density function. It concludes that crosscorrelation method demonstrates simple and intuitive advantages over random selection of shift parameter.