Neural network-based modeling and parameter identification of switched reluctance motors

Phase windings of switched reluctance machines are modeled by a nonlinear inductance and a resistance that can be estimated from standstill test data. During online operation, the model structures and parameters of SRMs may differ from the standstill ones because of saturation and losses, especially at high current. To model this effect, a damper winding is added into the model structure. This paper proposes an application of artificial neural network to identify the nonlinear model of SRMs from operating data. A two-layer recurrent neural network has been adopted here to estimate the damper currents from phase voltage, phase current, rotor position, and rotor speed. Then, the damper parameters can be identified using maximum likelihood estimation techniques. Finally, the new model and parameters are validated from operating data.     

Electric circuit modeling of fuel cell system including compressor effect and current ripples

This study aims to investigate the development of an Electrical Circuit Model (ECM) that represents the behavior of a PEM fuel cell system. The ECM parameters are identified based on sets of impedance data obtained by using a characterization process known as Electrochemical Impedance Spectroscopy (EIS). In this process, a small magnitude of alternating current sweeping a broad spectrum of frequencies is superimposed on a DC current drawn from the fuel cell while measuring the resulting voltage response. The measured impedance is fitted to an ECM using a nonlinear least-square fitting method. The proposed ECM is able to reflect the voltage response of the system to current ripples and represent the effect of the compressor. The proposed model is validated using a commercial fuel cell power module. In general, such model representation is useful for analyzing the effects of the operating conditions on the fuel cell performance, efficiency and durability. It also helps in comprehending the effects of current ripple on the fuel cell while operating with power-conditioning units     

Reactive Oxygen Species: Modulators of Phenotypic Switch of Vascular Smooth Muscle Cells

Reactive oxygen species (ROS) are natural byproducts of oxygen metabolism in the cell. At physiological levels, they play a vital role in cell signaling. However, high ROS levels cause oxidative stress, which is implicated in cardiovascular diseases (CVD) such as atherosclerosis, hypertension, and restenosis after angioplasty. Despite the great amount of research conducted to identify the role of ROS in CVD, the image is still far from being complete. A common event in CVD pathophysiology is the switch of vascular smooth muscle cells (VSMCs) from a contractile to a synthetic phenotype. Interestingly, oxidative stress is a major contributor to this phenotypic switch. In this review, we focus on the effect of ROS on the hallmarks of VSMC phenotypic switch, particularly proliferation and migration. In addition, we speculate on the underlying molecular mechanisms of these cellular events. Along these lines, the impact of ROS on the expression of contractile markers of VSMCs is discussed in depth. We conclude by commenting on the efficiency of antioxidants as CVD therapies.     

Boiling local heat transfer enhancement in minichannels using nanofluids

This paper reports an experimental study on nanofluid convective boiling heat transfer in parallel rectangular minichannels of 800 μm hydraulic diameter. Experiments are conducted with pure water and silver nanoparticles suspended in water base fluid. Two small volume fractions of silver nanoparticles suspended in water are tested: 0.000237% and 0.000475%. The experimental results show that the local heat transfer coefficient, local heat flux, and local wall temperature are affected by silver nanoparticle concentration in water base fluid. In addition, different correlations established for boiling flow heat transfer in minichannels or macrochannels are evaluated. It is found that the correlation of Kandlikar and Balasubramanian is the closest to the water boiling heat transfer results. The boiling local heat transfer enhancement by adding silver nanoparticles in base fluid is not uniform along the channel flow. Better performances and highest effect of nanoparticle concentration on the heat transfer are obtained at the minichannels entrance.     

MoNGEL: monotonic nested generalized exemplar learning

In supervised prediction problems, the response attribute depends on certain explanatory attributes. Some real problems require the response attribute to represent ordinal values that should increase with some of the explaining attributes. They are called classification problems with monotonicity constraints. In this paper, we aim at formalizing the approach to nested generalized exemplar learning with monotonicity constraints, proposing the monotonic nested generalized exemplar learning (MoNGEL) method. It accomplishes learning by storing objects in \({\mathbb {R}}^n\), hybridizing instance-based learning and rule learning into a combined model. An experimental analysis is carried out over a wide range of monotonic data sets. The results obtained have been verified by non-parametric statistical tests and show that MoNGEL outperforms well-known techniques for monotonic classification, such as ordinal learning model, ordinal stochastic dominance learner and k-nearest neighbor, considering accuracy, mean absolute error and simplicity of constructed models.     

Improved analytical model to predict the effective elastic properties of 2.5D interlock woven fabrics composite

An improved analytical modeling, three stages homogenization method “3SHM”, of a 2.5D interlock woven composite is proposed. The development of the analytical model based on mixed iso-strain and iso-stress assembling models (the stiffness and the compliance averaging models) is presented. A finite element (FE) modeling is carried out in order to use its results in the development of the analytical model. It is proved that a model based only on an iso-strain condition could not give accurate results, while a mixed iso-strain and iso-stress model yields more accurate estimations. the developed homogenization method as well as the geometrical modeling, that takes into account the real geometry of undulated yarns, proposed by the analytical model leads to very good agreement in comparing with results obtained from FE models and available experimental data from the literature.     

Modeling and simulation of an electronically commutatedpermanent-magnet machine drive system using SPICE

This paper describes the design of high-efficiency, electronically commutated, permanent-magnet machine (ECPM) drives based on the finite-element/difference method, and the solution of the ensuing differential equations with the Simulation Program with Integrated Circuit Emphasis (SPICE). The permanent-magnet motor model includes the computation of load-dependent components of the motor-equivalent circuit (e.g., induced voltages and inductances). A new SPICE metal-oxide semiconductor field-effect transistor (MOSFET) model reflecting the reverse-recovery current phenomenon-which is very important for the design of variable-speed drives operating in the pulse-width-modulated (PWM) mode-is introduced. Results of this new model are compared with measurements. Since ECPMs lend themselves well to vehicle propulsion due to their inherent high efficiencies at light weight, it is desirable to have a very high output-power-to-weight ratio for such applications. In addition, high ECPM drive efficiencies are important for recovery of the braking energy     

FATIGUE CRACK INITIATION LIFE PREDICTION IN HIGH STRENGTH STRUCTURAL STEEL WELDED JOINTS

The local approach method is used to calculate the fatigue crack initiation/early crack growth lives (N_i) in high strength structural steel weldments. Weld-toe geometries, welding residual stresses and HAZ (heat affected zone) cyclic mechanical properties are taken into account in the N_i estimation procedure. Fatigue crack initiation lives are calculated from either a Basquin type or a Manson-Collin type equation. The local (HAZ) stress and strain amplitudes and the local mean stress are determined from an analysis based on the Neuber rule and the Molski-Glinka energy approach. The accuracy of the different methods is evaluated and discussed. Finally the previous methods are used with HAZ cyclic mechanical properties estimated from hardness measurements.     

eLearniXML: Towards a model-based approach for the development of e-Learning systems considering quality

With the evolution of technology, and especially of the Internet, a growing interest has appeared for on-line education. The many advantages of e-Learning have made this teaching philosophy an ideal partner for teachers, either as a complement to regular education or as a substitute for traditional education. The development of an e-Learning system poses extra challenges for software developers, since there are other facets, such as contents and user tracking, not usually considered in software development methodologies. In this paper eLearniXML approach to the development of e-Learning systems is presented. This approach enriches the development of e-Learning systems method proposed in ADDIE with the model-based development of user interfaces and software quality consideration. By doing so, we aim at the development of, what we have named, a Model-Based Instructional Development Environment (MB-ISDE), to include e-Learning development in the current trends of model-based software development.