Design of an optimized ECCA microchannel for particle manipulation utilizing dean flow coupled elasto-inertial method

In this paper, an Eulerian-Lagrangian simulation was conducted to achieve optimal Expanded-Contracted Cavity Arrays microchannel. First, a new code was developed to solve the viscoelastic flow field, and then the particles were solved by adding appropriate forces to the OpenFOAM Lagrangian solver. This code was then validated for both Eulerian and Lagrangian models. Subsequently, the effect of different parameters such as flow rate, distance from the inlet, cavity depth and distance, and particle size were also studied to obtain the proper geometry for particle focusing. Finally, the selected channel was integrated with a straight channel to separate 4.8 and 13 μm particles. The results of current research can be used to find a proper design of an Expanded-Contracted Cavity Arrays channel to achieve precise focusing and efficient, continuous, and sheathless particle/cell separation, which is much worthy for applications such as high-speed cytometry, cell counting, sorting, and many biological applications.     

Lattice Boltzmann simulation of mixed convection in an inclined cavity with a wavy wall

In the present study, the effect of inclination on mixed convection heat transfer and fluid flow in a lid‐driven cavity with a wavy wall is investigated using the lattice Boltzmann method. The double‐population approach with second‐order accuracy at velocity and temperature fields is used to simulate the curved boundary in the lattice Boltzmann method. The problem is investigated for different Richardson numbers (0.1 ≤ Ri ≤ 10), curve amplitudes (0.05 ≤ A ≤ 0.25), and inclination angles (0 ≤ θ ≤ 180) when the Reynolds number is equal to 100. Results show that the inclination phenomenon has important effects on both flow and temperature fields at high Richardson numbers. It is also found that the inclination loses its role on mixed convection heat transfer from the wavy wall by the increase of the curve amplitude of the wavy wall for all Richardson numbers. © 2012 Wiley Periodicals, Inc. Heat Trans Asian Res; Published online in Wiley Online Library ( wileyonlinelibrary.com/journal/htj ). DOI 10.1002/htj.21005     

On the feasibility of a novel severe plastic deformation method for cylindrical tubes; friction assisted tubular channel pressing (FATCP)

Journal of Mechanical Science and Technology - This paper introduces a novel severe plastic deformation method entitled Friction assisted tubular channel pressing (FATCP) for producing...     

Auxiliary qubit selection: a physical synthesis technique for quantum circuits

Quantum circuit design flow consists of two main tasks: synthesis and physical design. Addressing the limitations imposed on optimization of the quantum circuit objectives because of no information sharing between synthesis and physical design processes, we introduced the concept of “physical synthesis” for quantum circuit flow and proposed a technique for it. Following that concept, in this paper we propose a new technique for physical synthesis using auxiliary qubit selection to improve the latency of quantum circuits. Moreover, it will be shown that the auxiliary qubit selection technique can be seamlessly integrated into the previously introduced physical synthesis flow. Our experimental results show that the proposed technique decreases the average latency objective of quantum circuits by about 11% for the attempted benchmarks.     

Numerical Analysis and Experimental Study of Buckling Behavior of Steel Cylindrical Panels

The effects of the length, sector angle and different boundary conditions on the buckling load and post buckling behavior of cylindrical panels have been investigated using experimental and numerical methods. The experimental tests have been performed using a servo hydraulic machine and for numerical analysis, Abaqus finite element package has been used. The numerical results are in good agreement with the experimental tests.     

Effects of solution treatment and sheath on mechanical properties of Al7075 processed by ECAP

Al7075 as a hard-to-work alloy is processed difficultly by Equal channel angular pressing (ECAP) at room temperature. In this paper, experiments were conducted at several heat treatment conditions and also with a new developing strategy using sheath copper to process this alloy at room temperature. Mechanical properties were evaluated by tensile and micro hardness tests. The results demonstrated that the ultimate and yield strength of ECAPed aged samples improved. Tensile test of 4 pass processed samples with copper sheath indicated an increase in the strength in comparison with samples without sheath. The hardness test results showed more uniform distribution of hardness in their cross section for copper sheath casing samples. It was found that by increasing the copper sheath thickness, the hardness variation decreased while the average hardness increased. By considering the time limitation for the process, only solid solution samples without sheath could be successfully ECAPed in 2 passes and samples with sheath could be ECAPed only in one pass.     

High impedance fault detection based on wavelet transform and statistical pattern recognition

A novel method for high impedance fault (HIF) detection based on pattern recognition systems is presented in this paper. Using this method, HIFs can be discriminated from insulator leakage current (ILC) and transients such as capacitor switching, load switching (high/low voltage), ground fault, inrush current and no load line switching. Wavelet transform is used for the decomposition of signals and feature extraction, feature selection is done by principal component analysis and Bayes classifier is used for classification. HIF and ILC data was acquired from experimental tests and the data for transients was obtained by simulation using EMTP program. Results show that the proposed procedure is efficient in identifying HIFs from other events.     

ECAP process capability in producing a power transmission bimetallic rod

In recent years, bimetallic rods have been considered by researchers due to the industrial applications in power transmission systems. In this paper, an Al-Steel rod is produced by equal channel angular pressing (ECAP) process. First, severe plastic deformation is applied to Al-Steel rod by ECAP process, and then some experiments such as microhardness measurement, interface strength evaluation, scanning electron microscope (SEM), and microstructure analysis have been accomplished to assess the capability of ECAP process in producing a power transmission bimetallic rod. Then, to evaluate significant parameters on strain distribution and pressing force, the FEM has been utilized. After verification of the numerical method, the effect of several parameters such as diameter, location, peripheral materials, and die angle on the applied strain and homogeneity are studied. The results indicate that the steel and aluminum hardness are increased about 59 and 61% after four passes ECAP, respectively. Also, the average grain size of steel core is reduced about 79% at the same conditions after four passes. In addition, the images received from SEM show that the interfaces between steel and aluminum have been improved significantly.     

Creep feed grinding optimization by an integrated GA-NN system

The present work is aimed to optimize creep feed grinding (CFG) process by an approach using integrated Genetic Algorithm-Neural Network (GA-NN) system. The aim of this creep feed grinding optimization is obtain the maximal metal removal rate (MRR) and the minimum of the surface roughness (R _a ). For optimization, metal removal rate is calculated with a mathematic formula and a Back Propagation (BP) artificial neural-network have been used to prediction of R _a . The parameters used in the optimization process were reduced to three grinding conditions which consist of wheel speed, workpiece speed and depth of cut. All of other parameters such as workpiece length, workpiece material, wheel diameter, wheel material and width of grinding were taken as constant. The BP neural network was trained using the scaled conjugate gradient algorithm (SCGA). The results of the neural network were compared with experimental values. It shows that the BP model can predict the surface roughness satisfactorily. For optimization of creep feed grinding process, an M-file program has been written in ‘Matlab’ software to integrate GA and NN. After generation of each population by GA, firstly, the BP network predicts R _a and then MRR has been calculated with mathematic formula. In this study, the importance of R _a and MRR is equal in the optimization process. By using this integrated GA-NN system optimal parameters of creep feed grinding process have been achieved. The obtained results show that, the integrated GA-NN system was successful in determining the optimal process parameters.