Comparison of LLR,MLP, Elman,NNARX and ANFIS Models—with a case study in solar radiation estimation

Despite the widespread application of nonlinear mathematical models, comparative studies of different models are still a huge task for modellers. This is because a large number of trial and error processes are needed to develop each model, so the workload will be multiplied into an unmanageable level if many types of models are involved. This study presents an efficient approach by using the Gamma test (GT) to select the input variables and the training data length, so that the trial and error workload can be greatly reduced. The methodology is tested in estimating solar radiation at the Brue catchment, UK. Several nonlinear models have been developed efficiently with the aid of the GT, including local linear regression, multi-layer perceptron (MLP), Elman neural network, neural network auto-regressive model with exogenous inputs (NNARX) and adaptive neuro-fuzzy inference system (ANFIS). This work is only feasible within the time and resources constraint, due to the GT in reducing huge workload of the trial and error process.     

Spatial downscaling of climate variables using three statistical methods in Central Iran

Spatial downscaling methods are widely used for the production of bioclimatic variables(e.g. temperature and precipitation) in studies related to species ecological niche and drainage basin management and planning. This study applied three different statistical methods, i.e. the moving window regression(MWR), nonparametric multiplicative regression(NPMR), and generalized linear model(GLM), to downscale the annual mean temperature(Bio1) and annual precipitation(Bio12) in central Iran from coarse scale(1 km × 1 km) to fine scale(250 m ×250 m). Elevation, aspect, distance from sea and normalized difference vegetation index(NDVI) were used as covariates to create downscaled bioclimatic variables. Model assessment was performed by comparing model outcomes with observational data from weather stations. Coefficients of determination(R2), bias, and root-mean-square error(RMSE) were used to evaluate models and covariates. The elevation could effectively justify the changes in bioclimatic factors related to temperature and precipitation. Allthree models could downscale the mean annual temperature data with similar R2, RMSE, and bias values. The MWR had the best performance and highest accuracy in downscaling annual precipitation(R2=0.70; RMSE=123.44). In general, the two nonparametric models, i.e. MWR and NPMR, can be reliably used for the downscaling of bioclimatic variables which have wide applications in species distribution modeling.     

A study of crude oil‐degrading bacteria from mangrove forests in the Persian Gulf

Mangroves are coastal ecosystems, found in tropical and subtropical regions around the world. They are found in the transitional zones between land, sea, and rivers. Petroleum hydrocarbons are the most common environmental pollutants, and oil spills pose a great hazard to mangroves forests. This research was focused on the isolation and characterization of crude oil‐degrading bacteria from mangrove ecosystems at the Persian Gulf. Sixty‐one crude oil‐degrading bacteria were isolated from mangrove samples (plant, sediment, and seawater) that enriched in ONR7a medium with crude oil as only carbon source. Some screening tests such as growth at high concentration of crude oil, bioemulsifier production, and surface hydrophobicity were done to select the most efficient strains for crude oil degradation. Molecular identification of strains was carried out by amplification of the 16S rRNA gene by PCR. The results of this study were indicated that the quantity of crude oil‐degrading bacteria was higher in the root of mangrove plants compare to other mangrove samples (sediment and seawater). Also, identification results confirmed that these isolated strains belong to Vibrio sp. strain NW4, Idiomarina sp. strain BW32, Kangiella sp. strain DP40, Marinobacter sp. strain DW44, Halomonas sp. strain BS53, and Vibrio sp. strain DS35. The application of bioremediation strategies with these bacteria can reduce crude oil pollution in this important marine environment.     

Statistical analysis of stress transmission in wet granular materials

The micromechanics of wet granular materials encompasses complex microstructural and capillary interconnects that can be readily described through a formal derivation of stress transmission in such a 3‐phase medium. In the quest for defining an appropriate stress measure, the stress tensor expression that results from homogenization [Duriez et al. J Mech Phys Solids 99 (2017): 495‐511] of such a medium provides theoretical insights necessary to extract useful information on the relationship between capillary effects and microforce interactions via several small‐scale parameters whose evaluation can be challenging. Using instead a statistical approach where microvariable distributions are described by probability density functions, the current study provides simple estimates of stress components in terms of only a few tractable microvariables such as coordination number and fabric anisotropy. In particular, the latter recognizes details of contacts such as force interactions being either mechanical or capillary, including interactions with and without mechanical contact. The developed expressions are in a good agreement with discrete element method simulation results of the triaxial loading of a wet granular assembly, notably for hydrostatic (mean) pressure. A new set of dimensionless groups is also identified to characterize the significance of mechanical and capillary physics, which facilitates a better understanding of the contribution of dominating elements to stress, while also providing the opportunity to incorporate important capillary effects in micromechanically based constitutive formulations.     

A transparent aqueous-saturated sand surrogate for use in physical modeling

This paper presents the geotechnical properties of a new family of synthetic transparent soils made of fused quartz, saturated with a matched refractive index water-based sucrose solution, suitable for modeling the behavior of sand in small-scale model tests. The dry density ranged between 1,134 and 1,358 kg/m³. The peak angle of friction was found to range from 46° to 57°. The average hydraulic conductivity was 1.7 × 10^?5 cm/s. The compressibility index (C _c) ranged from 0.34 to 0.57. The main advantage of fused quartz over available sand surrogates made of silica gel is that its solid structure better models the behavior of natural sand. The matching pore fluids are inert and non-toxic, which facilitates their use in educational settings. The availability of a safe and easy-to-use transparent sand permits measurement of three-dimensional deformation patterns and flow characteristics in controlled research experiments. The introduction of an aqueous solution permits the use of two immiscible pore fluids, one made of mineral oil and the other made of a sucrose solution, for modeling multiphase flow problems, as well as coupled flow-deformation problems.     

Assessment of reference evapotranspiration across an arid urban environment having poor data monitoring system

Estimation of reference evapotranspiration (ET₀) in urban areas is challenging but essential in arid urban climates. To evaluate ET₀ in an urban environment and non-urban areas, air temperature and relative humidity were measured at five different sites across the arid city of Isfahan, Iran, over 4 years. Wind speed and sunshine hours were obtained from an urban surrounding weather station over the same period and used to estimate ET₀. Calculated ET₀ was compared with satellite-based ET₀ retrieved from the MOD16A2 PET product. Although MODIS PET was strongly correlated with the Valiantzas equation, it overestimated ET₀ and showed average accuracy (r = 0.93–0.94, RMSE = 1.18–1.28 mm/day, MBE = 0.73–0.84 mm/day). The highest ET₀ differences between an urban green space and a non-urban area were 1.1 and 0.87 mm/day, which were estimated by ground measurements and MODIS PET, respectively. The sensitivity of ET₀ to wind speed and sunshine hours indicated a significant effect on cumulative ET₀ at urban sites compared to the non-urban site, which has a considerable impact on the amount of irrigation required in those areas. Although MODIS PET requires improvement to accurately reflect field level microclimate conditions affecting ET₀, it is beneficial to hydrological applications and water resource managers especially in areas where data is limited. In addition, our results indicated that using limited data methods or meteorological data from regional weather stations, leads to incorrect estimation of ET₀ in urban areas. Therefore, decision-makers and urban planners should consider the importance of precisely estimating ET₀ to optimize management of urban green space irrigation, especially in arid and semi-arid climates such as the city of Isfahan.     

Application of the Dynamic Cone Penetrometer (DCP) for determination of the engineering parameters of sandy soils

Determination of the in situ engineering properties of foundation materials has always been a challenge for geotechnical engineers and, thus, several methods have been developed so far. Dynamic Cone Penetration (DCP) test is one of the most versatile amongst them. In the present research, a light weight simple DCP device was developed and used for evaluation of the engineering properties of sandy soils in laboratory conditions. The device consisted of an 8-kg hammer that drops over a height of 575 mm, and drives a 60° cone tip with 20 mm base diameter into the ground. To control the validation of the results, laboratory direct shear and plate load tests were used as reference tests. The soil sample was a poorly graded sandy soil (SP) taken from alluvial deposits of the Tehran plain. All DCP tests and PLTs were undertaken on compacted soil in a mould with 700 mm diameter and 700 mm height. Based on the results of the experiments, the relationships between Dynamic Penetration Index (DPI), relative density (D_r), modulus of elasticity (E), shear modulus (G), modulus of subgrade reaction (K_S), and the friction angle of the soil were obtained with a high coefficient of determination (> 90%). The repeatability of the test results was also evaluated by calculating the coefficient of variations (C_v), which was less than 30% for all tests.     

A Geometric Computational Model for Calculation of Longwall Face Effect on Gate Roadways

In this paper a geometric computational model (GCM) has been developed for calculating the effect of longwall face on the extension of excavation-damaged zone (EDZ) above the gate roadways (main and tail gates), considering the advance longwall mining method. In this model, the stability of gate roadways are investigated based on loading effects due to EDZ and caving zone (CZ) above the longwall face, which can extend the EDZ size. The structure of GCM depends on four important factors: (1) geomechanical properties of hanging wall, (2) dip and thickness of coal seam, (3) CZ characteristics, and (4) pillar width. The investigations demonstrated that the extension of EDZ is a function of pillar width. Considering the effect of pillar width, new mathematical relationships were presented to calculate the face influence coefficient and characteristics of extended EDZ. Furthermore, taking GCM into account, a computational algorithm for stability analysis of gate roadways was suggested. Validation was carried out through instrumentation and monitoring results of a longwall face at Parvade-2 coal mine in Tabas, Iran, demonstrating good agreement between the new model and measured results. Finally, a sensitivity analysis was carried out on the effect of pillar width, bearing capacity of support system and coal seam dip.