Hyper-Spherical Search (HSS) algorithm: a novel meta-heuristic algorithm to optimize nonlinear functions

This paper proposes a novel optimization algorithm called Hyper-Spherical Search (HSS) algorithm. Like other evolutionary algorithms, the proposed algorithm starts with an initial population. Population individuals are of two types: particles and hyper-sphere centers that all together form particle sets. Searching the hyper-sphere inner space made by the hyper-sphere center and its particle is the basis of the proposed evolutionary algorithm. The HSS algorithm hopefully converges to a state at which there exists only one hyper-sphere center, and its particles are at the same position and have the same cost function value as the hyper-sphere center. Applying the proposed algorithm to some benchmark cost functions shows its ability in dealing with different types of optimization problems. The proposed method is compared with the genetic algorithm (GA), particle swarm optimization (PSO) and harmony search algorithm (HSA). The results show that the HSS algorithm has faster convergence and results in better solutions than GA, PSO and HSA.     

A Wavelet-ANFIS Hybrid Model for Groundwater Level Forecasting for Different Prediction Periods

Artificial neural network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) have an extensive range of applications in water resources management. Wavelet transformation as a preprocessing approach can improve the ability of a forecasting model by capturing useful information on various resolution levels. The objective of this research is to compare several data-driven models for forecasting groundwater level for different prediction periods. In this study, a number of model structures for Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), Wavelet-ANN and Wavelet-ANFIS models have been compared to evaluate their performances to forecast groundwater level with 1, 2, 3 and 4 months ahead under two case studies in two sub-basins. It was demonstrated that wavelet transform can improve accuracy of groundwater level forecasting. It has been also shown that the forecasts made by Wavelet-ANFIS models are more accurate than those by ANN, ANFIS and Wavelet-ANN models. This study confirms that the optimum number of neurons in the hidden layer cannot be always determined by using a specific formula but trial-and-error method. The decomposition level in wavelet transform should be determined according to the periodicity and seasonality of data series. The prediction of these models is more accurate for 1 and 2 months ahead (for example RMSE?=?0.12, E?=?0.93 and R ²?=?0.99 for wavelet-ANFIS model for 1 month ahead) than for 3 and 4 months ahead (for example RMSE?=?2.07, E?=?0.63 and R ²?=?0.91 for wavelet-ANFIS model for 4 months ahead).     

Preparation and characterization of foamed polyurethane/silicone rubber/graphite nanocomposite as radio frequency wave absorbing material: The role of interfacial compatibilization

A novel method for the preparation of radio frequency (RF) wave absorber polyurethane foam (PU) has been developed by impregnation of PU foam in n-hexane solution of room temperature vulcanizing (RTV) silicone rubber (SR) hybridized with graphite nanosheets (GNs) called doping solution. Extent of the GNs dispersion was optimized by the incorporation of a specific type of bifunctional compatibilizer. Insulator to conductive transition threshold as well as electromagnetic wave absorption characteristics of the fabricated nanocomposites was shown to be dependent upon the compatibilizer functionality. All PU/SR/GN nanocomposites generated from bifunctional compatibilizer exhibited higher electrical conductivity with enhanced permittivity implying enhanced formation of conductive networks by GN platelets. Permittivity of the PU/SR/GN nanocomposite based on bifunctional compatibilizer showed to be higher than uncompatibilized counterpart. Electromagnetic reflection loss behavior of the PU/SR/GN nanocomposites exhibited a non-linear correlation with the electrical conductivity. Although all PU/SR/GN prepared nanocomposites exhibited electromagnetic wave reflection loss behavior, but this revealed to be affected by the GN level as well as the size and dispersion state of the graphite nanosheets.     

A comparison of Zayandehrood River water values for agriculture and the environment

River water management is challenging not only since they are open systems with changing physical structures, but also because the water values are mostly unknown over varied sectors. If policymakers grasp water values, water management will be more efficient. This research intends to examine the values of water in agriculture, which receives the most substantial portion of water resources, with the values of water in the environment in Isfahan located in the Zayandehrood River basin of Iran. The consequences of contingent valuation and production function methods revealed that per cubic metre value of water is 13 times higher in the environment than agriculture. The government should reconsider the higher value of the environment despite it is a non‐market value. The contingent valuation model additionally proved that women exhibited 21% more willingness to pay than men in order to protect the environment; however, they are paid less by 36%.     

A Puzzle of Quantum Phase Transition on Gd-IMC by Tuning of Conduction Electron Concentration

Based on the critical unstable of both crystal and magnetic structure of Gd-intermetallic compound near the competition of two strongly independent subsystem （＂local 4f7＂ and ＂conduction electron concentration＂）, a new QPT （quantum point transition） is predicted by calculation of： （1） The band structure and density of state by density functional theory where a strong narrowing fluidity of fermions around EF with shifted to negative value ＂-0.8 eV ＂is observable in the Gd-intermetalliccompound system while in the Y-case, it is not dominated. An antiferromagnetic state on the fluidity of conduction band can be investigated; （2） The internal magnetic field due to short range exchange interaction Jij between the nearest neighbor of local magnetic moment of stable s-state of Gd （L = 0） through the mean field approximation and of Eigenvalue-Eigenfunction ~.（k） are calculated. While a strong negative value of Jy is predicted, the eigenvalue L（k） of the system shows a strong antiferromagnetic phase in the reciprocal lattice direction 〈010〉, 〈001〉 in the correlation length 3.38 ~A. Although the antiferromagnetic state at Rc 〈_ 3.38 °A is a puzzle but it is completely dominated at Rc = 9 °A after passing through the competition between ）.λmin（O） and λmin（π） in the ranger of 3.2 °A 〈 Rc 〈 9 °A. Since both of the antiferromagnetic subsystems are sensitive to the predicted KF, the effect of decreasing of conduction electron is proposed to investigate, the change of the antiferromagnetic ordering state to the competition of ferromagnetic state （in direction 〈010〉） and antiferromagnetic state （in direction 〈001 〉 and 〈 100〉） resulted to paramagnetic state in the long range Rc = 9 °A.     

Performance enhancement of a direct absorption solar collector using copper oxide porous foam and nanofluid

The current research proposes the idea of using water-saturated metal oxide foams and water-based nanofluids as solar absorber in the direct absorption solar collectors (DASCs). Specifically, the novel solar collector design utilizes copper oxide (CuO) porous foam and nanoparticle with high optical properties and is expected to have enhanced thermal performance than the conventional collectors utilizing pure water. The finite volume technique is used to solve the governing equations of flow and heat transfer in the radiative participating media. Also, to establish the reliability and accuracy of numerical solutions, the obtained results are compared with the corresponding numerical and experimental data. The computations are carried out for different nanoparticle volume fractions, foam pore sizes, working fluid mass flow rates, and both porous layer thicknesses and positions (inserted at the lower or upper wall of the collector). It is found that the efficiency of DASC partially/fully filled with metal oxide foam is maximized when the collector is completely filled with it. Compared with the water flow, the numerical results show that the collector efficiency using CuO nanofluid and metal oxide foam is improved by up to 26.8% and 23.8%, respectively. Moreover, considering the second law of thermodynamics, the use of CuO nanofluids in the DASC seems to be more effective than the use of CuO porous foam.     

Study of the sensitivity and resonant frequency of the torsional modes of an AFM cantilever with a sidewall probe based on a nonlocal elasticity theory

A relationship based on a nonlocal elasticity theory is developed to investigate the torsional sensitivity and resonant frequency of an atomic force microscope (AFM) with assembled cantilever probe (ACP). This ACP comprises a horizontal cantilever and a vertical extension, and a tip located at the free end of the extension, which makes the AFM capable of topography at sidewalls of microstructures. First, the governing differential equations of motion and boundary conditions for dynamic analysis are obtained by a combination of the basic equations of nonlocal elasticity theory and Hamilton's principle. Afterward, a closed‐form expression for the sensitivity of vibration modes has been obtained using the relationship between the resonant frequency and contact stiffness of cantilever and sample. These analysis accounts for a better representation of the torsional behavior of an AFM with sidewall probe where the small‐scale effect are significant. The results of the proposed model are compared with those of classical beam theory. The results show that the sensitivities and resonant frequencies of ACP predicted by the nonlocal elasticity theory are smaller than those obtained by the classical beam theory. Microsc. Res. Tech. 78:408–415, 2015. © 2015 Wiley Periodicals, Inc.