Introducing an empirical model for prediction of disc cutter life for TBM application in jointed rocks: case study,Kerman water conveyance tunnel

Bulletin of Engineering Geology and the Environment - Disc cutters wear and need to be replaced when using tunnel boring machines (TBMs) to excavate through rock, often becoming a high ticket item...     

The effect of scale on the water leakage from the reservoir and abutment of Beheshtabad Dam

Bulletin of Engineering Geology and the Environment - Dam construction on karstic carbonate formations usually involves leakage problems from their abutments and reservoirs. Constructing a dam in...     

Scene classification using a new radial basis function classifier and integrated SIFT–LBP features

Pattern Analysis and Applications - Scene classification is one of the most significant and challenging tasks in computer vision. This paper presents a new method for scene classification using bag...     

Optimal Reservoir Operation Using Bat and Particle Swarm Algorithm and Game Theory Based on Optimal Water Allocation among Consumers

Water Resources Management - Water resources scarcity and competition among stakeholders in water allocation always highlights the optimal operation of water resources. This research examines the...     

A comparison between radial basis function (RBF) and adaptive neuro-fuzzy inference system (ANFIS) to model the free convection in an open round cavity

This study demonstrates the capability of radial basis function (RBF) and adaptive neuro-fuzzy inference system (ANFIS) to model and predict the free convection heat transfer in an open round cavity. In fact, the effects of the Rayleigh number (Ra) and ratio of the nonconductor barrier distance from the bottom of the cavity to the cavity diameter (H/D), on the free convection in the cavity, are modeled via the RBF and ANFIS models. To start modeling, sufficient data are gathered. Here, data are experimentally generated using a Mach-Zehnder interferometer. In the next step, the RBF and ANFIS models are trained. According to the results, there is an optimum ratio (H/D), in which the heat transfer is maximum. This maximum value increases by increasing the Rayleigh number (Ra). Moreover, based on the results obtained by the RBF and ANFIS, the predicted results for the convection heat transfer are in good agreement with similar ones obtained experimentally. The mean relative errors of the training, testing, and checking data for the RBF model were found as 0.1348%, 1.1972%, and 2.4967%, respectively. Moreover, for the ANFIS model, the error values were 0.0731%, 0.9110%, and 1.9144%, which shows that RBF and ANFIS can predict the results precisely.     

Reducing Irrigation Deficiencies Based Optimizing Model for Multi-Reservoir Systems Utilizing Spider Monkey Algorithm

Continuous droughts and water scarcity have led to the need for optimal exploitation of dams’ reservoirs. Thus, the new meta-heuristic algorithm, spider monkey, is suggested for complex modeling of the multi-reservoir system in Iran with the aim of decreasing irrigation deficiencies. Golestan and Voshmgir dams’ operations are optimized with the spider monkey algorithm. The algorithm based on the exchange of information between local and global leaders with the other monkeys which improves the convergence speed. Average deficiencies for Golestan dam is computed as 2.1 and 1.9 MCM by spider monkey algorithm while it is respectively computed as 6.7, 16.4, 11.1, 4.1, 14.6, 19 MCM by particle swarm algorithm, harmony search algorithm, imperialist competitive algorithm, water cycle algorithm, genetic algorithm, and standards operation policy method. Also, the computation time of the spider monkey algorithm is 50 and 47 s for the Golestan and Voshmgir dams while the genetic algorithm optimizes the problem in 172.6 s and 112 s and the particle swarm algorithm needs 117.4 s and 100 s for the Golestan and Voshmgir, respectively. Also, root means square error (RMSE) and mean absolute error between demand and released water for the spider monkey algorithm have the least values among the applied evolutionary algorithms. Thus, the spider monkey algorithm is suggested as an appropriate method for optimizing the operation policy for the dam and reservoir systems.     

Comprehensive nonlinear seismic performance assessment of MR damper controlled systems using virtual real‐time hybrid simulation

Magnetorheological (MR) dampers have gained significant attention in seismic mitigation of structural systems due to their distinguished characteristics such as inherent stability and minimum power requirements. Their performance in control of nonlinear structural response, however, has not been widely investigated. This paper provides comprehensive nonlinear seismic performance assessment of a three‐story benchmark structure equipped with a large‐scale MR damper using virtual real‐time hybrid simulation to efficiently capture the nonlinear behavior of the damper. The framework is first verified by means of available experimental results of an actual RTHS on the same structural system. A set of 12 earthquake ground motions, each one scaled to have 12 different intensities are then utilized to perform nonlinear dynamic analyses. An energy‐based adaptive passive‐on control strategy is proposed, and its performance is compared with passive‐on, passive‐off, and uncontrolled response of the structure in terms of interstory drifts shown by fragility curves, residual drifts, MR damper control force, and the ability to maintain a uniform interstory drift along the height of the structure.     

Numerical simulation of counter-flow wet-cooling towers

Cooling towers are used to cool a warm water stream through evaporation of part of the water into an air stream. A cooling tower consists of three zones; namely spray, packing and rain zones. In cooling towers, a significant portion of the total heat rejected may occur in the spray and rain zones. These zones are modeled and solved numerically using a computer code. The developed models of these zones are validated against experimental data. For the case study under consideration, the error in calculation of the tower volume is 1.5% when the spray and rain zones are neglected. This error is reduced to 1.1% and 0.25% as the spray and rain zones are incorporated in the model, respectively. Furthermore, the effect of the Lewis factor on the performance prediction of wet-cooling towers is investigated using Bosnjakovic equation.     

Heavy metal uptake by wheat from a sewage sludge-amended calcareous soil

The objective of this 4-year study was to determine single and repetitive effects of sewage sludge applications on the accumulation of lead (Pb), cadmium (Cd), zinc (Zn) and copper (Cu) in soil and wheat (Triticum aestivum). A single sludge application at a rate of 100 Mg ha⁻¹ (for all the metals) and at a rate of 50 Mg ha⁻¹ (for Cu) significantly increased DTPA-extractable metal concentrations 4 years later. DTPA-extractable concentrations of Pb, Zn and Cu were closely correlated with the total concentrations in soil. Their relationships between metal uptake in stalks and DTPA-extractable metal concentrations in soil were approximately linear for Pb, Cd and Cu, but better described by a quadratic equation for Cd and Zn. TF for Pb, Zn and Cu, BF for all metals and BCF for Pb, Cd and Zn were lower in wheat grown on sludge-treated than control plots.