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並列摘要


Resilient response of granular aggregate is a key input parameter in all three hierarchical levels of the new Mechanistic- Empirical pavement Design Guide (MEPDG), which requires a comprehensive evaluation of resilient modulus (M_r) database(s) for local conditions. To this end, Mr data and other routine properties (gradation, LA Abrasion loss, standard Proctor, and unconfined compressive strength (UCS)) of 105 samples of two different types of aggregate (limestone and sandstone) were analyzed in this study. A total of four stressbased regression models were evaluated using a statistical software package ("SPSS", Version 17), and material constants (k_1, k_2, and k_3) for these aggregates were determined. The octahedral model was found to outperform the other models and is recommended for use in Level 1 analysis. Correlation equations for material constants, required for Level 2, were developed using routine aggregate properties, and the universal model was found to be the "best fit" model with a R^2 value of 0.57. Default (Level 3) Mr values for these aggregates were also estimated using the average material constants. The estimated M_r values obtained from different models were in agreement with each other, and the variations of M_r values were within 4%. However, all of these models would result in conservative designs compared to the MEPDG recommended typical values. The findings of this study are expected to be helpful in the implementation of the MEPDG in Oklahoma and elsewhere.

被引用紀錄


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Lairi, N. O. (2017). 探討印尼海外直接投資、GDP與出口之間的關聯性 [doctoral dissertation, Chung Yuan Christian University]. Airiti Library. https://doi.org/10.6840/cycu201700919
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Wu, J. Z. (2017). 具覆蓋率限制異質性小細胞網路之功率控制 [master's thesis, National Chiao Tung University]. Airiti Library. https://www.airitilibrary.com/Article/Detail?DocID=U0030-2212201712253124

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