فهرست مطالب

Applied Research - Volume:3 Issue: 11, Nov 2017

Applied Research Journal
Volume:3 Issue: 11, Nov 2017

  • تاریخ انتشار: 1396/10/15
  • تعداد عناوین: 3
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  • Haifaa Abdulrasool Ali *, Yasir Muyuad Yousuf Pages 321-331
    The effects of the permeation cement grout with Meta-kaolin on sandy soil skeleton was studied was this research on two phases. Phase no. (1) was the effect on shear strength parameters on the grouted soil. While phase no.(2) was the effect of these grouted materials on volume grouted zone by injecting (51) cm³ of slurry to sandy soil placed in a steel cylinder model as a small scale model (150 mm diameter X 300 mm height). The soil sample used in this study was a poorly graded sandy soil (SP according to USCS) obtained from Karbala city. Soil samples were tested using different water cement ratio (w:c); (0.9:0.1, 0.8:0.2, and 0.7:0.3 respectively), a dehydration and curing of one day was given to the grouted samples before testing them. Also in this research, Metakaolin was applied as a filler to replace the cement material in percentages of (5%, 10% and 15%) by weight. Results showed that the increase in soil shear parameter is inversely proportional to the water – cement ratio. While Metakaoline material added to the mix required an increase in water percentage to obtain better shear results.
    Keywords: Soil Improvement, Grouting With Cement, Filler Materials, Metakaolin Material, Nano Materials
  • Israa Saeed Jawad Al-Haydari *, Ghadah Ghassan Masued Pages 332-342
    Nowadays, large amounts of waste materials are being globally produced. One of these waste plastic materials is Expanded Polystyrene (EPS) which is widely used as a packaging material, construction material, and in domestic appliances. The disposal of the waste EPS is necessary due to its biodegradability and anesthetically view. So, the aim of this research is to assess the feasibility of using waste EPS as a secondary pavement material. Laboratory investigation was conducted to evaluate the Physical properties of modified and unmodified asphalt binder as; Penetration value, Softening point, and Ductility. In addition, Mechanical properties of asphalt pavement mixture were also evaluated through Marshall’s tests and Indirect Tensile Strength, for five percentages of EPS (1, 2, 3, 4, and 5) percent by weight of asphalt. The results revealed that although the EPS does not modify the asphalt binder, it enhances the mechanical performance of asphalt pavement mixture.
    Keywords: Waste plastic, EPS packaging, Asphalt Binder, Asphalt Mixture, Indirect Tensile Strength
  • Nawar O. Al-Musawi, Fatima M. Al-Rubaie* Pages 343-353
    In this research, nine sampling locations were selected for Tigris River to assess water quality by analyzing Water Quality Index (WQI). The analysis includes different water quality parameters: Turbidity (Tur.), Alkalinity (Alk.), pH, Total hardness (T.H), Magnesium (Mg), Calcium (Ca), Chloride (Cl), Iron (Fe), Conductivity (EC), Sulfate (SO4), Ammonia (NH3), Nitrate (NO3), Orthophosphate (PO4) and Total solids (T.S) for the period 2011 to 2017. The techniques used in this research for water quality assessment involve WQI, Artificial Neural Networks (ANNs) and Geographical Information System (GIS). The values of maximum for WQI reached to 632.8 and 862.8 at Al-Wathba WTP in 2011 and 2013 respectively (WTP at the middle part of Baghdad). High iron concentrations have been found in the river and are the main reason for the increase in WQI values. Neural network model was used to predict changes in the condition of Tigris River in Baghdad city. GIS was used to correlate the WQI results with the satellite image for developing colored analytical maps which classifies water quality of the river for public usage. For the NNM, the confusion matrix gave overall prediction rate about 93% for model training, 90% for testing and 70% for holdout sample. The general conclusion from this model may predict that river quality is of a poor to polluted condition, which are the same results as GIS.
    Keywords: Water quality index, Neural network model, GIS, Tigris River