An Efficient Solution for Model Checking Graph Transformation Systems

This paper presents an efficient solution for modeling checking graph transformation systems. The approach transforms AGG specifications into Bogor models and supports both attributed typed graphs and layered transformations. Resulting models are amenable to check interesting properties expressed as combinations of LTL (Linear Temporal Logic) and graph transformation rules. The first experimental results are encouraging and show that in most cases our proposal improves existing approaches, both in terms of performance and expressiveness.     

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).     

A fast wavelet-based moment method for solving thin-wire EFIE

Solving the thin-wire electric field integral equation (EFIE) by the multiresolution wavelet expansion method involves a time-consuming double numerical integration for each nonzero element of the moment matrix which in turn can outweigh the advantages of achieving a sparse matrix. To speed up the matrix fill process in wavelet-based moment method codes, first, the triangular scaling functions of a nonorthogonal piecewise liner wavelet at the finest spatial resolution are appropriately replaced by sinusoidal dipoles for which mutual impedances are available in closed-form analytical expressions. The fast wavelet bases transform is then exploited to effectively transfer the resultant matrix equation to multiresolution wavelet domain. Numerical results obtained by the compactly supported semi-orthogonal linear B-spline wavelet demonstrate dramatic reduction of the overall solution time without any degradation in the accuracy of the final solution.     

A solid modeler based ball-end milling process simulation

A system for geometric and physical simulation of the ball-end milling process using solid modeling is presented in this paper. A commercially available geometric engine is used to represent the cutting edge, cutter and updated part. The ball-end mill cutter modeled in this study is an insert type ball-end mill and the cutting edge is generated by intersecting an inclined plane with the cutter ball nose. The contact face between cutter and updated part is determined from the solid model of the updated part and cutter solid model. To determine cutting edge engagement for each tool rotational step, the intersections between the cutting edge with boundary of the contact face are determined. The engaged portion of the cutting edge for each tool rotational step is divided into small differential oblique cutting edge segments. Friction, shear angles and shear stresses are identified from orthogonal cutting data base available in the open literature. For each tool rotational position, the cutting force components are calculated by summing up the differential cutting forces. The instantaneous dynamic chip thickness is computed by summing up the rigid chip thickness, the tool deflection and the undulations left from the previous tooth, and then the dynamic cutting forces are obtained. For calculating the ploughing forces, Wu's model is extended to the ball-end milling process [21]. The total forces, including the cutting and ploughing forces, are applied to the structural vibratory model of the system and the dynamic deflections at the tool tip are predicted. The developed system is verified experimentally for various up-hill and down-hill angles.     

Acoustic damping flexible polyurethane foams: Effect of isocyanate index and water content on the soundproofing

High-efficiency sound absorbing flexible polyurethane foams (FPUFs) are manufactured using nonpolar polyester resin, methylene diphenyl diisocyanate, and other reagents by one-shot bulk polymerization. In this study, the impact of the isocyanate index (90, 100, and 110) and water content (2.5 and 5%) on the microphase separation and soundproofing behavior of FPUFs are examined using atomic force microscopy, Fourier transform infrared spectroscopy, optical microscope, and an impedance tube device. The results reveal that the increase of the isocyanate index and water content leads to the increase of the cell size, cell size distribution, open-cell content, cell wall roughness, and microphase separation. Also, maximum sound absorption coefficient (α) reaches to 0.98 and the average of α in the frequency range of 1500–4000 Hz increases from 0.7 to 0.87 by increasing the water content from 2.5 to 5% and isocyanate index from 90 to 110; therefore, acoustic damping performance enhances up to 26.24% due to the synergic effects of microphase separation on the viscose media formation, open-cell content, cell wall roughness, cell size, and cell size distribution. In conclusion, FPUFs with an optimal amount of microphase separation and drainage flow can be a promising candidate for sound insulating materials. © 2018 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47363.     

Circular Functions Based Comprehensive Analysis of Plastic Creep Deformations in the Fiber Reinforced Composites

Analytically based model is presented for behavioral analysis of the plastic deformations in the reinforced materials using the circular (trigonometric) functions. The analytical method is proposed to predict creep behavior of the fibrous composites based on basic and constitutive equations under a tensile axial stress. New insight of the work is to predict some important behaviors of the creeping matrix. In the present model, the prediction of the behaviors is simpler than the available methods. Principal creep strain rate behaviors are very noteworthy for designing the fibrous composites in the creeping composites. Analysis of the mentioned parameter behavior in the reinforced materials is necessary to analyze failure, fracture, and fatigue studies in the creep of the short fiber composites. Shuttles, spaceships, turbine blades and discs, and nozzle guide vanes are commonly subjected to the creep effects. Also, predicting the creep behavior is significant to design the optoelectronic and photonic advanced composites with optical fibers. As a result, the uniform behavior with constant gradient is seen in the principal creep strain rate behavior, and also creep rupture may happen at the fiber end. Finally, good agreements are found through comparing the obtained analytical and FEM results.     

Applying artificial optimization methods for transformer model reduction of lumped parameter models

Detailed R-C-L-M models of power transformers, which are based on lumped parameters, are used extensively not only for transient analysis of power transformers to determine electrical stresses in windings, but also for studying transients in power systems. Models with few elements are generally more practicable for power system studies but at the expense of accuracy. The use of artificial methods to reduce an R-C-L-M model is the main contribution of this paper. Advantages of the suggested method include: (1) a reduced loss of accuracy compared with the original model and (2) the flexibility to choose the number of model elements to achieve the desired model depending on size and accuracy. The ability of three different artificial methods, genetic algorithm, particle swarm optimization, and bacterial foraging algorithm, to model reduction is evaluated using measurements on an actual 400 kV test object and the results are compared with those obtained by common analytical formulae.     

First-principles DFT study of SO2 and SO3 adsorption on 2PANI: a model for polyaniline response

Interaction of SO_x (x?=?2,3) molecules on active sites of dianiline (as a model for polyaniline, denoted here as 2PANI) was studied using density functional theory at the BLYP-D/6-31+G(d) level of theory. Natural population analysis was used to find out the charge distribution as well as the net transferred charge of SO_x upon adsorption on 2PANI and the result has been compared with Mulliken charge analysis to evaluate the sensing ability of 2PANI. The computed density of states point to the remarkable orbital hybridization between SO_x and 2PANI during the adsorption process. As a consequence, the results of UV–VIS confirm the sensing ability of 2PANI toward SO₂ and SO₃. Based on our results, it can be found that at proper configuration the SO₂ and SO₃ molecules can be adsorbed on 2PANI with adsorption energies (E_ads) of ?18.2 and ?62.9?kJ/mol (BSSE), respectively.