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OFallon, IL, United States

Kang X.,Missouri University of Science and Technology | Ge L.,National Taiwan University | Kang G.-C.,K water | Mathews C.,Science Engineering
Road Materials and Pavement Design | Year: 2015

The effectiveness of Class-C fly ash (FA) (ASTM C-618) and lime kiln dust (LKD) used in clay pavement base materials stabilisation has been investigated in this research. Proctor compaction test, unconfined compression test, and non-destructive test (Briaud compaction device (BCD) modulus and thermal conductivity) were carried out on the chemically modified soil. Test specimens were reconstituted by static compaction, constructed at optimum water content, and tested at various curing periods. Test results revealed that the addition of Class-C FA up to 20 wt% could effectively increase the dry unit weight from 16.8 to 17.4 kN/m3 (105.0 to 108.3 pcf), improve the unconfined compressive strength (UCS, which increased from 181.2 to 497.2 kPa at the end of 28 days of curing), and raise the BCD modulus up to 40 MPa. The LKD was also found to be a good stabiliser for weak soil, which could raise the UCS and stiffness under relatively small mixing rations (4 and 8 wt%), but the dry unit weight decreased as the LKD mixing ratio increased. The thermal conductivity, however, decreased as the curing time and stabiliser mixing ratio increased. Parallel and series models were employed to understand the upper-and-lower bound of the mixtures' thermal conductivity. A thermal strength coupled empirical model which is based on the non-destructive testing results was developed to predict the UCS gain over curing time. The thermal conductivity and BCD modulus were also incorporated into a novel compaction quality check model. Based on the observed test data and regression analysis, both models were found to yield good results, indicating that they are robust tools for predicting the UCS and dry unit weight of chemically treated pavement base materials. © 2015 Taylor & Francis Source


Sudheer Reddy D.,Science Engineering
Journal of the Indian Society of Remote Sensing | Year: 2010

In the applications of remote-sensing it is a common task of finding out the overlap area of coverage between two images. There are several methods available to find overlap area of varying time complexities. In this paper a method based on Monte Carlo approach is presented along with an algorithm to find common area using only corner coordinate information of the images. This method take less time than compared to the image matching methods via correlations when complete images are given. Further, this algorithm facilitate finding optimal pairs(automatically) that can be mosaicked depending on the overlap area requirement. Another simplest and considerably fast algorithm is also elaborated for evaluation. A comparison of both methods is done with a sample of Cartosat-2 images and the results are presented. © 2011 Indian Society of Remote Sensing. Source


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Grant
Agency: National Aeronautics and Space Administration | Branch: | Program: SBIR | Phase: Phase II | Award Amount: 553.84K | Year: 1999

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Grant
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase II | Award Amount: 747.52K | Year: 1999

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Grant
Agency: Department of Defense | Branch: Air Force | Program: SBIR | Phase: Phase II | Award Amount: 776.30K | Year: 1999

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