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Natural Resources Research - Solar radiation data are crucial for the design and evaluation of solar energy systems, climatic studies, water resources management, estimating crop productivity, etc....  相似文献   
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This paper presents a novel triple‐layer model, called VART DO‐3L, for simulation of spatial variations in dissolved oxygen (DO) in fine‐grained streams, characterized by a fluid mud (fluff or flocculent) layer (an advection‐dominated storage zone) as the interface between overlying stream water and relatively consolidated streambed sediment (a diffusion‐dominated storage zone). A global sensitivity analysis is conducted to investigate the sensitivity of VART DO‐3L model input parameters. Results of the sensitivity analysis indicate that the most sensitive parameter is the relative size of the advection‐dominated storage zones (As/A), followed by a lumped reaction term (R) for the flocculent layer, biological reaction rate (μo) in diffusive layer and biochemical oxygen demand concentration (L) in water column. In order to address uncertainty in model input parameters, Monte Carlo simulations are performed to sample parameter values and to produce various parameter combinations or cases. The VART DO‐3L model is applied to the Lower Amite River in Louisiana, USA, to simulate vertical and longitudinal variations in DO under the cases. In terms of longitudinal variation, the DO level decreases from 7.9 mg l at the Denham Springs station to about 2.89 mg l?1 at the Port Vincent station. In terms of vertical variation, the DO level drops rapidly from the overlying water column to the advection‐dominated storage zone and further to the diffusive layer. The DO level (CF) in the advective layer (flocculent layer) can reach as high as 40% of DO concentration (C) in the water column. The VART DO‐3L model may be applied to similar rivers for simulation of spatial variations in DO level. Copyright © 2014 John Wiley & Sons, Ltd.  相似文献   
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Soil is a material which is weak in tension; however, different materials such as geotextiles are used to address this inadequacy. In recent years more than one million square metres of geotextiles were used for reinforcing soil. Nevertheless, there are several significant problems associated with geotextiles, such as creep, low modulus of elasticity and susceptibility to aggressive environments. Carbon fibre reinforced polymer (CFRP) was introduced over two decades ago to the field of structural engineering and it can also be used in geotechnical engineering. CFRP has all the benefits associated with geotextiles and it boasts a higher strength, higher modulus, no creep and reliability in aggressive environments. In this investigation, the interface properties of CFRP-sand and fine sand were investigated using the pull-out test. The pull-out test device was designed and assembled using a triaxial loading device and a direct shear device. In the pull-out test, the normal force applied by the triaxial loading and pull-out force is applied by a direct shear device. CFRP samples were prepared in the lab. Precast and cast-in-place samples were tested. The pull-out force and corresponding displacements of each of the materials were recorded and compared.  相似文献   
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Nowadays, the world is witnessing the ever increasing need of Tunnel excavation due to their unique features and the kind of human applied plans. This has led to increase in demand of excavating this engineering factor. Tunnel excavation process faces a lot of challenges due to environmental and technological complexities which causes the economic evaluation and investigation of this project to be difficult. It is tried to develop the proposed model with regard to efficiency concept in order to evaluate and investigate the efficiency of relative economic performance of Tunnel excavation projects and turn to its modeling and implementing by data envelopment analysis and Fuzzy DEMATEL techniques. The results in Iran showed that the proposed model can turn to investigation and evaluation of economic efficiency of Tunnel excavation by considering two optimistic (ideal) and pessimistic perspectives such that the Tunnel excavation process of “Karaj water transition” and “Cheshmelangan water transition” among 12 rock Tunnel excavation projects of Iran in the time period of 1998–2013 were respectively introduced as the most efficient and the most inefficient rock Tunnel excavation projects.  相似文献   
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Backbreak is one of the destructive side effects of the blasting operation. Reducing of this event is very important for economic of a mining project. Involvement of various parameters has made the backbreak analyzing difficult. Currently there is no any specific method to predict or control the phenomenon considering all the effective parameters. In this paper, artificial neural network (ANN) as a powerful tool for solving such complicated problems is used to predict backbreak in blasting operation of the Sangan iron mine, Iran. Network training was fulfilled using a collected database of the practiced operation including blast design details and rock condition. Trying various types of the networks, a network with two hidden layers was found to be optimum. Performance of the ANN model was compared with statistical analysis using datasets which were kept apart from the original database. According to the obtained results, for the ANN model there existed a higher correlation (R2 = 0.868) and lesser error (RMSE = 0.495) between the predicted and measured backbreak as compared to the regression model. Also, sensitivity analysis revealed that the inputs rock factor and number of rows are the most and the least sensitive parameters on the output backbreak, respectively.  相似文献   
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