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Task 4 : testing Iowa Portland cement concrete mixtures for the AASHTO mechanistic-empirical pavement design procedure.

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  • Abstract:
    The present research project was designed to identify the typical Iowa material input values that are required by the Mechanistic- ; Empirical Pavement Design Guide (MEPDG) for the Level 3 concrete pavement design. It was also designed to investigate the existing ; equations that might be used to predict Iowa pavement concrete for the Level 2 pavement design. ; In this project, over 20,000 data were collected from the Iowa Department of Transportation (DOT) and other sources. These data, most ; of which were concrete compressive strength, slump, air content, and unit weight data, were synthesized and their statistical parameters ; (such as the mean values and standard variations) were analyzed. Based on the analyses, the typical input values of Iowa pavement ; concrete, such as 28-day compressive strength (f’c), splitting tensile strength (fsp), elastic modulus (Ec), and modulus of rupture (MOR), ; were evaluated. The study indicates that the 28-day MOR of Iowa concrete is 646 + 51 psi, very close to the MEPDG default value (650 ; psi). The 28-day Ec of Iowa concrete (based only on two available data of the Iowa Curling and Warping project) is 4.82 + 0.28x106 psi, ; which is quite different from the MEPDG default value (3.93 x106 psi); therefore, the researchers recommend re-evaluating after more ; Iowa test data become available. The drying shrinkage (εc) of a typical Iowa concrete (C-3WR-C20 mix) was tested at Concrete ; Technology Laboratory (CTL). The test results show that the ultimate shrinkage of the concrete is about 454 microstrain and the time ; for the concrete to reach 50% of ultimate shrinkage is at 32 days; both of these values are very close to the MEPDG default values. The ; comparison of the Iowa test data and the MEPDG default values, as well as the recommendations on the input values to be used in ; MEPDG for Iowa PCC pavement design, are summarized in Table 20 of this report. ; The available equations for predicting the above-mentioned concrete properties were also assembled. The validity of these equations for ; Iowa concrete materials was examined. Multiple-parameters nonlinear regression analyses, along with the artificial neural network ; (ANN) method, were employed to investigate the relationships among Iowa concrete material properties and to modify the existing ; equations so as to be suitable for Iowa concrete materials. However, due to lack of necessary data sets, the relationships between Iowa ; concrete properties were established based on the limited data from CP Tech Center’s projects and ISU classes only. The researchers ; suggest that the resulting relationships be used by Iowa pavement design engineers as references only. ; The present study furthermore indicates that appropriately documenting concrete properties, including flexural strength, elastic modulus, ; and information on concrete mix design, is essential for updating the typical Iowa material input values and providing rational ; prediction equations for concrete pavement design in the future.
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    urn:sha-512:5b062632bdeac351d15e1ed252b088f3041ce73ef13e8133a9526c2f302aa2093098bac1349606c878b33c872e4b1a62a54be5041e18c7692ccab32f99ecd553
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