The potential of marble dust as a stabilizing additive to red tropical soils was evaluated. The evaluation involved the determination of the geotechnical properties of three different red tropical soils in their natural state as well as when mixed with varying proportions of marble dust. The parameters tested included the particle size distribution, specific gravity, Atterberg limits, the standard compaction characteristics, the compressive strength and the California bearing ratio (CBR). The strength tests were repeated after normal 28 day curing of the treated samples and also after accelerated 24 h curing at temperatures of 40°C, 60°C and 80°C.
Results showed that the geotechnical parameters of red tropical soils are improved substantially by the addition of marble dust; plasticity was reduced by 20 to 33% and strength and CBR increased by 30 to 46% and 27 to 55% respectively. The highest strength and CBR values were achieved at 8% marble dust. Results also showed that normal 28 day curing improved the strength of the marble dust-treated soil with over 80% strength gain achieved after 7 to 10 days of normal curing. Higher strength development was realised following accelerated 24 h curing at 60°C.
Although these results imply marked improvement in the geotechnical parameters of red tropical soils, the higher strength developed is not enough for the improved soil to be used as a base material in the construction of heavily trafficked flexible pavements. The improved material may, however, be successfully used as base material for lightly trafficked roads and as a sub-base material for heavily trafficked roads. 相似文献
Algal assemblages have been widely used as an ecological indicator of aquatic ecosystem health conditions because of their specific sensitivity to a wide variety of environmental conditions. In turbid rivers, as in other aquatic systems, phytoplankton structure plays an important role in structuring aquatic food webs. Worldwide, phytoplankton is less studied in turbid, large tropical rivers compared to temperate river systems. The present study aimed to describe the phytoplankton diversity and abundance in a turbid tropical river (the Red River, northern part of Vietnam from 20°00 to 25°30 North; from 100°00 to 107°10 East) and to determine the importance of a series of environmental variables in controlling the phytoplankton community composition. Phytoplankton community was composed of 169 phytoplankton taxa from six algal groups including Bacillariophyceae, Chlorophyceae, Cryptophyceae, Euglenophyceae, Dinophyceae and Cyanobacteria. Community composition varied both spatially and with season. Sixteen measurement environmental variables were used as input variables for a three-layer backpropagation neural network that was developed to predict the phytoplankton abundance. Phytoplankton abundance was successfully predicted using the tagsig transfer function and the Levenberg-Marquardt backpropagation algorithm. The network was trained to provide a good overall linear fit to the total data set with a slope (R) and mean square error (MSE) of 0.808 and 0.0107, respectively. The sensitivity analysis and neutral interpretation diagram revealed that total phosphorus (TP), flow discharge, water temperature and P-PO43− were the significant variables. The results showed that the developed ANN model was able to simulate phytoplankton abundance in the Red River. These findings can help for gaining insight into and the relationship between phytoplankton and environmental factors in this complex, turbid, tropical river. 相似文献