H 2 has a great potential to replace fossil fuels and contribute to clean energy by reducing the environmental carbon foot-print. This study reports H 2 generation from a thermochemical water-splitting reaction using sol-gel derived Sn x Fe y O z powders. The sol-gel synthesis involved the addition of SnCl 2 Á 2H 2 O and FeCl 2 Á 4H 2 O in ethanol followed by gelation using propylene oxide. As-synthesized gels were aged, dried, and heated rapidly upto different temperatures and quenched in air or N 2 environment. The calcined powders were characterized using powder x-ray diffraction, BET surface area analyzer, and scanning electron microscopy (SEM). Calcination temperature and environment were found to have a significant effect on phase composition and specific surface area (SSA). The calcined Sn x Fe y O z powders were placed in a tubular Inconel reactor and four consecutive thermochemical cycles were performed. Water-splitting and regeneration steps were carried out at 900 C and 1100 C, respectively. The powder calcined in N 2 environment showed a mixed phase composition containing Sn 0.4 Fe 2.6 O 4 and SnO 2 and it generated an average of 1.88 ml of H 2 g À1 cycle À1 .
Pavement evaluation is the most significant procedure to minimize the degradation of the pavement both functionally and structurally. Proper evaluation of pavement is hence required to prolong the life year of the pavement, which thus needs to be addressed in the policy level. By this, the development of genuine indices are to be formulated and used for the evaluation. In context of evaluating the pavement indices for measuring the pavement roughness, International Roughness Index (IRI) is used, whereas for calculating the surface distress, indices as such Surface Distress Index (SDI) and Pavement Condition Index (PCI) are used. Past evaluating schemes used by Department of Roads (DOR) were limited to IRI for evaluating the pavement roughness and SDI for measuring the surface distress, which has least variability in categorizing the pavement according to the deformation. Apart from these, PCI which has wide range of categories for evaluating pavement, is not seen in practice in Nepal due to its cumbersome field work and calculations. In this paper the relationship is developed relating PCI with IRI and SDI using regression analysis by using Microsoft excel. In the other words, the pavement roughness index is compared with the surface distress indices. In 2017, 23.6Km of feeder roads in various locations of Kathmandu and Lalitpur districts were taken for this study which comprised of 236 sample data, each segmented to 100m. For this, IRI was sourced as secondary data, obtained from Highway Maintenance and Information System (HMIS) unit, Kathmandu, whereas, PCI and SDI were calculated from the field data obtained from the survey carried out in those sections manually. Then after, among 236 samples, 189 samples were taken for the relationship development which was then validated using 47 remaining samples. Furthermore, in the year, 2019 additional 3 Km of data was taken for validating the obtained relationships. It was done to improve the numerical predictions of data with such variation and thus satisfactory relationships were developed among the indices discussed in this study. The regression relationships between the two indices, IRI-PCI and IRI-SDI were thus significantly obtained. It has been found that the R² value for these relationships developed were statistically significant with 5% level of significance. The R² value for all the relationships showed that these relationships could be used for predicting the indices which would help in evaluating the pavement.
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