Effects of windy sand and LECA mulches on decreasing evaporation from soil surface

Inadequate moisture supply is one of the important factors limiting crop yields in the world. Increasing the efficiency of moisture available has an important role on the crop-producing capacity of the soil. This paper presents the results of the laboratory experiments conducted to assess the influence of two mulches of windy sand and light expanded clay aggregate (LECA) with three thicknesses (1, 3, and 4 cm) on soil surface in soil columns. Loamy soil was taken from the experimental site in Bayaz of Rafsanjan (a city in Kerman province in Iran). These experiments were done as completely randomized design with two treatments of mulches (windy sand and LECA) and tree replicates. The results show that the columns of treated soil with mulches had lower evaporation as compared to the control. The rate of evaporation from the soil surface of columns was decreased with increasing the thickness from 1 to 4 cm of each of the two mulches. The LECA mulch was more effective in reducing evaporation from the soil surface than the windy sand mulch with the same thicknesses. The most effective among the thicknesses for mulches was 3 cm.     

Evidence of the formation of landslide-dammed lakes in the Zagros Mountains range,Iran

Alternation of high and low resistance sedimentary beds,active tectonics,large rivers,and slope erosion in valleys consequently resulted in landslide in dammed lakes within the Zagros range.This study presents the results in the analysis of geological and topographic data,satellite imageries,morphotectonics and hydrodynamics of drainage networks about the landslide dammed lakes.There are four landslides in central Zagros(Zagros FoldThrust Belt,ZFTB)which have formed five dammed lakes named,Seymareh,Jaidar,Shur,Shimbar,and Godar.According to the results,damming landslides occurred in the active-tectonic regions on the slopes of anticlines and in valleys with undercutting effects of rivers on their slopes consisting of alternations of loose and resistant beds.The studied landslide dams in narrow valleys are formed as a result of blocking river by sliding debris slopes and rock slides.This study also indicates the formation of Jaidar and Godar in one stage and the presence of Lake Terrace sequence in Seymareh,Shur and Shimbar lakes.The observed sequences of terrace formation in these lakes are caused by four Seymareh Landslides followed by the three-stage excavation of Shur andShimbar lakes.     

Effectiveness of two conventional methods for seismic retrofit of steel and RC moment resisting frames based on damage control criteria

This study investigates the efficiency of two types of rehabilitation methods based on economic justification that can lead to logical decision making between the retrofitting schemes. Among various rehabilitation methods, concentric chevron bracing (CCB) and cylindrical friction damper (CFD) were selected. The performance assessment procedure of the frames is divided into two distinct phases. First, the limit state probabilities of the structures before and after rehabilitation are investigated. In the second phase, the seismic risk of structures in terms of life safety and financial losses (decision variables) using the recently published FEMA P58 methodology is evaluated. The results show that the proposed retrofitting methods improve the serviceability and life safety performance levels of steel and RC structures at different rates when subjected to earthquake loads. Moreover, these procedures reveal that financial losses are greatly decreased, and were more tangible by the application of CFD rather than using CCB. Although using both retrofitting methods reduced damage state probabilities, incorporation of a site-specific seismic hazard curve to evaluate mean annual occurrence frequency at the collapse prevention limit state caused unexpected results to be obtained. Contrary to CFD, the collapse probability of the structures retrofitted with CCB increased when compared with the primary structures.     

Comparison of conventional and Monte Carlo simulation-based probabilistic seismic hazard analyses for Shiraz city,southern Iran

Estimation of ground-motion amplitudes of different hazard levels is of paramount importance in planning of urban development of any metropolis. Such estimation can be computed through a probabilistic seismic hazard analysis (PSHA). This paper concentrates on the PSHA of an area located in Shiraz city, southern Iran. The area includes whole of Shiraz city (i.e., one of the largest and most populous cities of Iran) and its outskirts. Conventional and Monte Carlo simulation-based approaches are utilized to perform the PSHA of the studied area. Two areal seismic source models are delineated, and thence seismicity parameters of all zones associated with their corresponding uncertainties are computed. Uncertainties in ground-motion prediction are accounted for via three ground-motion prediction equations (GMPEs) within the logic tree framework. These GMPEs are applied to estimate bedrock ground shaking (V_s30?=?760 m/s) for several return periods (i.e., 75, 475, 975, and 2475 years). In general, the results of the two abovementioned PSHA approaches show relatively similar results. However, the Monte Carlo simulation-based approach overpredicts bedrock spectral accelerations at periods of 0.4–2.5 s compared to the conventional PSHA approach for return periods of 475, 975, and 2475 years.     

Health risk assessments due to nitrate levels in drinking water in villages of Azadshahr,northeastern Iran

Groundwater is the main water source used for drinking and cooking purposes globally. Nitrate level in most groundwater resources in arid and semi-arid areas has increased in the past several decades as a result of human activities and natural processes. This may exert a great impact on human health. To learn the contamination circumstances of groundwater nitrate in villages of Azadshahr, Iran and assess its probable risk to the health of adults, children and infants, fifty-eight groundwater samples were collected from wells and springs in 2018. Nitrate concentrations had a wide spatial variability in wells and springs of the studied villages, with values going from 1 up to 51 mg/L. Exceedances of the EPA standard value were limited to two village springs (villages Nili and Narab, with nitrate level of 51 and 46 mg/L, respectively). The hazard quotients (HQ) values for 41% of children and infants were above the safety level (i.e., HQ?>?1), suggesting that groundwater nitrate would have significant health effects on these age groups. Therefore, appropriate control measures and sanitation improvement programs should be put in place to protect the health of the residents in the contaminated villages.     

Numerical and intelligent modeling of triaxial strength of anisotropic jointed rock specimens

The strength of anisotropic rock masses can be evaluated through either theoretical or experimental methods. The latter is more precise but also more expensive and time-consuming especially due to difficulties of preparing high-quality samples. Numerical methods, such as finite element method (FEM), finite difference method (FDM), distinct element method (DEM), etc. have been regarded as precise and low-cost theoretical approaches in different fields of rock engineering. On the other hand, applicability of intelligent approaches such as fuzzy systems, neural networks and decision trees in rock mechanics problems has been recognized through numerous published papers. In current study, it is aimed to theoretically evaluate the strength of anisotropic rocks with through-going discontinuity using numerical and intelligent methods. In order to do this, first, strength data of such rocks are collected from the literature. Then FlAC, a commercially well-known software for FDM analysis, is applied to simulate the situation of triaxial test on anisotropic jointed specimens. Reliability of this simulation in predicting the strength of jointed specimens has been verified by previous researches. Therefore, the few gaps of the experimental data are filled by numerical simulation to prevent unexpected learning errors. Furthermore, a sensitivity analysis is carried out based on the numerical process applied herein. Finally, two intelligent methods namely feed forward neural network and a newly developed fuzzy modeling approach are utilized to predict the strength of above-mentioned specimens. Comparison of the results with experimental data demonstrates that the intelligent models result in desirable prediction accuracy.     

Degradation and Leaching of Napropamide in BRIS Soil Amended with Chicken Dung and Palm Oil Mill Effluent

The degradation and leaching of napropamide were compared between Beach Ridges Interspersed with Swales (BRIS) soil samples, and the same soil samples amended with 20 mg ha^?1 of either chicken dung (CD) or palm oil mill effluent (POME). The effects of removing dissolved organic carbon (DOC) from the soil samples on napropamide degradation and leaching were also studied. The addition of CD and POME to BRIS soil increased the napropamide half‐life values to 69 and 49.5 days, respectively. Sterilization of the soil samples resulted in partial inhibition of napropamide degradation in all soil samples. The half‐lives of napropamide in BRIS soils receiving 0, 20, 100, and 200 mg kg^?1 of DOC derived from CD were 43, 46.2, 53.4, and 63 days, respectively. The napropamide half‐lives in soil samples treated with 0, 20, 100, and 200 mg kg^?1 of DOC derived from POME were 43, 49.2, 57.7, and 69 days, respectively. However, in the sterilized soil samples, there were no significant effects of adding DOC derived from either CD or POME on napropamide half‐lives. Incorporating either CD or POME decreased napropamide leaching and total amounts of napropamide remained in the soil columns after two pore volumes of water has been leached were higher in the amended than the non‐amended soil. The CD was more effective in decreasing napropamide leaching than the POME. There were no effects of DOC on napropamide leaching in all soil treatments.     

Oil formation volume factor modeling: Traditional vs. Stochastically optimized neural networks

Oil formation volume factor (FVF) is considered as relative change in oil volume between reservoir condition and standard surface condition. FVF, always greater than one, is dominated by reservoir temperature, amount of dissolved gas in oil, and specific gravity of oil and dissolved gas. In addition to limitations on reliable sampling, experimental determination of FVF is associated with high costs and time-consumption. Therefore, this study proposes a novel approach based on hybrid genetic algorithm-pattern search (GA-PS) optimized neural network (NN) for fast, accurate, and cheap determination of oil FVF from available measured pressure-volume-temperature (PVT) data. Contrasting to traditional neural network which is in danger of sticking in local minima, GA-PS optimized NN is in charge of escaping from local minima and converging to global minimum. A group of 342 data points were used for model construction and a group of 219 data points were employed for model assessment. Results indicated superiority of GA-PS optimized NN to traditional NN. Oil FVF values, determined by GA-PS optimized NN were in good agreement with reality.