Showing 3 results for Keshavarzi
T. Honar, M. Javan, A. Keshavarzi,
Volume 6, Issue 3 (fall 2002)
Abstract
Side weirs as flow diversion devices are widely used in irrigation, land drainage and urban sewage systems. In the present study, the effects of the length and height of inclined side weir crest on discharge coefficient were investigated in prismatic and nonprismatic rectangular channels.. In this study, 675 laboratory tests were conducted.
Analysis of experimental tests showed that the discharge coefficient is strongly correlated with uptream Froude number, height of weir to depth ratio at upstream of weir, ratio of water depth on weir to length of weir, and with prismatic factor. Based on experimental results, a model is proposed. The model is capable of estimating the discharge coefficient under subcritical flow conditions. Finally, the data from the proposed model was compared with those obtained by other researchers under different side and bed slopes. There was a good agreement with a relative error of less than ten percent.
A. Keshavarzi, M. J. Kazemzadeh Parsi,
Volume 10, Issue 1 (spring 2006)
Abstract
Flow structure at water intake is very complicated and three-dimensional. Due to this the application of one and two-dimensional equations can not sufficiently explain the flow structure at water intake. In this study, the simulation of flow structure at a 45 degree water intake was investigated numerically and experimentally. Here, the characteristic of separation zone and velocity distribution at 45 degree water intake were investigated using Standard k-ε and RNG k-ε models. It was found that the Standard k-ε model enables to estimate the flow and separation zone at water intake. Also, the location of separate zone at the inlet of water intake was studied using experimental and numerical approach. It was found that the separation zone at 45 degree water intake occurs at the downstream of the inlet.
Z. Maghsodi, M. Rostaminia, M. Faramarzi, A Keshavarzi, A. Rahmani, S. R. Mousavi,
Volume 24, Issue 2 (Summer 2020)
Abstract
Digital soil mapping plays an important role in upgrading the knowledge of soil survey in line with the advances in the spatial data of infrastructure development. The main aim of this study was to provide a digital map of the soil family classes using the random forest (RF) models and boosting regression tree (BRT) in a semi-arid region of Ilam province. Environmental covariates were extracted from a digital elevation model with 30 m spatial resolution, using the SAGAGIS7.3 software. In this study area, 46 soil profiles were dug and sampled; after physico-chemical analysis, the soils were classified based on key to soil taxonomy (2014). In the studied area, three orders were recognized: Mollisols, Inceptisols, and Entisols. Based on the results of the environmental covariate data mining with variance inflation factor (VIF), some parameters including DEM, standard height and terrain ruggedness index were the most important variables. The best spatial prediction of soil classes belonged to Fine, carbonatic, thermic, Typic Haploxerolls. Also, the results showed that RF and BRT models had an overall accuracy and of 0.80, 0.64 and Kappa index 0.70, 0.55, respectively. Therefore, the RF method could serve as a reliable and accurate method to provide a reasonable prediction with a low sampling density.
