Buoyancy effects on gaseous slip flow in a vertical rectangular microchannel

Consideration is given to the buoyancy effects on the fully developed gaseous slip flow in a vertical rectangular microduct. Two different cases of the thermal boundary conditions are considered, namely uniform temperature at two facing duct walls with different temperatures and adiabatic other walls (case A) and uniform heat flux at two walls and uniform temperature at other walls (case B). The rarefaction effects are treated using the first-order slip boundary conditions. By means of finite Fourier transform method, analytical solutions are obtained for the velocity and temperature distributions as well as the Poiseuille number. Furthermore, the threshold value of the mixed convection parameter to start the flow reversal is evaluated. The results show that the Poiseuille number of case A is an increasing function of the mixed convection parameter and a decreasing function of the channel aspect ratio, whereas its functionality on the Knudsen number is not monotonic. For case B, the Poiseuille number is decreased by increasing each of the mixed convection parameter, the Knudsen number, and the channel aspect ratio.     

Deep Neural Networks Regularization Using a Combination of Sparsity Inducing Feature Selection Methods

Neural Processing Letters - Deep learning is an important subcategory of machine learning approaches in which there is a hope of replacing man-made features with fully automatic extracted features....     

Preparation and characterization of poly(vinyl alcohol)/gum tragacanth/cellulose nanocomposite film

The effects of gum tragacanth obtained from two species of Astragalus Gossypinus (GT-G) and A. Parrowianus (GT-P) at two levels of 10% and 30% combined with cellulose nanofibers (CNF; 5%) on the physico-mechanical and structural properties of polyvinyl alcohol (PVA) nanocomposite film were investigated in this study. The water solubility and water vapor permeability of the films decreased with increasing the content of both gums, especially in the film containing 30% GT-P. The highest values of the tensile strength (39.3 MPa) and elongation at break (445%) belonged to the treatment containing 10% GT-P (90/10P/0). The FTIR and DSC analyses confirmed good interactions between GT and PVA in the 90/10P/0 treatment. SEM images indicated the dense structure of this film as the optimum treatment. Although the presence of CNF in the films containing GT-G improved some properties, especially the Young modulus, it impaired all the functional properties of nanocomposite GT-P film.     

Thin-skin analysis technique for interaction of arbitrary-shape inducer field with long cracks in ferromagnetic metals

In using the AC field measurement (ACFM) technique for non-destructive evaluation (NDE) of metals, a current-carrying wire structure is used to induce eddy current within a thin layer of the metal and a magnetic field sensor to measure the field perturbations in the vicinity of the metal. The sensitivity of ACFM crack detection and sizing relies on an appropriate design of the wire structure geometry together with a dully placement of the sensor. This paper presents an analytical modeling technique for evaluating the electromagnetic field interaction of an ACFM probe with a long uniform crack in a ferromagnetic metallic slab. The probe in the proposed model can have an arbitrary-shape wire inducer with no restrictions on its relative sensor position. The technique is accurate and very efficient computationally. It first uses the two-dimensional Fourier transform to obtain the field distribution at the metal surface. The Laplacian field distribution above the metal is then determined by satisfying the so-obtained boundary condition at air–metal interface. To demonstrate the accuracy of the model, we consider the special case of a rhombic wire inducer. The comparison of our results with those obtained using the conventional algorithm in the literature validates the accuracy of the model introduced in this paper. To show the generality of the model, we also present theoretical and experimental results associated with a solenoid inducer with a three-dimensional geometry for which no analytical solution is available in the literature. The theoretical prediction of crack signal supported by experimental results is used to develop a model-based method for inverting crack signal into crack depth.     

Nonlinear optimized adaptive trajectory control of helicopter

This paper attempts to develop an optimized adaptive trajectory control system for helicopters based on the dynamic inversion method. This control algorithm is implemented by three time-scale separation architectures. Pseudo control hedging (PCH) is used to protect the adaptive element from actuator saturation nonlinearities and also from the inner-outer-loop interaction. In addition, to augment the attitude control system, two online adaptive architectures that employ a neural network are used. By tuning the neural network based on the system model, a better and faster learning will be achieved, but this is a frustrating and time consuming process. Due to complexity in accurate tuning of neural network, this paper introduces a non-dominated sorting genetic algorithm II (NSGA-II) for off-line optimization of the neural network. Thus, in the proposed method, the neural network can compensate model inversion error caused by the deficiency of full knowledge of helicopter dynamics more accurately. The effectiveness of proposed method is demonstrated by numerical simulations.     

Development of degradation model for urban asphalt pavement

There is a lack of a profound understanding of urban pavement deterioration pattern. This is due to the complexity of traffic conditions and the variety of pavement structures in urban roads. The lack of a suitable deterioration model for the urban pavements limits the possibility of making any scientific and cost-effective repair and maintenance strategy. There is a need for a better understanding of the long-term behaviour of urban pavements by which predictive pavement condition models can be derived and consequently a suitable maintenance management system can be built. In response to this need, a comprehensive field study was performed in three Iranian cosmopolitan cities. Pervasive pavement damages were defined and an urban pavement condition index was established. A deterioration model was developed by monitoring and analysing the conditions of road pavements in a period of four years. This model varies as the structural and loading conditions of the pavement change. The efficiency and practicability of the model in predicting the conditions of the pavements were illustrated.     

Expert-driven genetic algorithms for simulating evaluation functions

In this paper we demonstrate how genetic algorithms can be used to reverse engineer an evaluation function’s parameters for computer chess. Our results show that using an appropriate expert (or mentor), we can evolve a program that is on par with top tournament-playing chess programs, outperforming a two-time World Computer Chess Champion. This performance gain is achieved by evolving a program that mimics the behavior of a superior expert. The resulting evaluation function of the evolved program consists of a much smaller number of parameters than the expert’s. The extended experimental results provided in this paper include a report on our successful participation in the 2008 World Computer Chess Championship. In principle, our expert-driven approach could be used in a wide range of problems for which appropriate experts are available.     

ARO: A new model free optimization algorithm for real time applications inspired by the asexual reproduction

This paper presents a new individual based optimization algorithm, which is inspired from asexual reproduction known as a remarkable biological phenomenon, called as asexual reproduction optimization (ARO). ARO can be essentially considered as an evolutionary based algorithm that mathematically models the budding mechanism of asexual reproduction. In ARO, a parent produces a bud through a reproduction operator; thereafter the parent and its bud compete to survive according to a performance index obtained from the underlying objective function of the optimization problem; this leads to the fitter individual. ARO adaptive search ability along with its strength and weakness points are fully described in the paper. Furthermore, the ARO convergence to the global optimum is mathematically analyzed. To approve the effectiveness of the ARO performance, it is tested with several benchmark functions frequently used in the area of optimization. Finally, the ARO performance is statistically compared with that of an improved genetic algorithm (GA). Results of simulation illustrate that ARO remarkably outperforms GA.