Calculation of Nano-charged Particles Pulsation Frequency in Tokamak

One of the unknown problems that cause to perturbation of tokamak function is charged particles pulsation. Applying the toroidal magnetic field to the charged motive particles implicate plasma in the system. This plasma has a frequency that depends on the toroidal magnetic field. Another frequency exists in this system that is caused to the plasma self magnetism. This lateral pulsation is principal origin of perturbation in the system. In this paper, nano-charged particles pulsation is investigated and its frequency is calculated by Buckingham method. Knowing this frequency is necessary to control perturbation. The result of calculations shows that temperature increasing of the system cause to more intense perturbation.     

A Low Complexity Suboptimal Energy-Based Detection Method for SISO/MIMO Channels

In this paper, we propose an actually novel and simple method for detection of transmitted symbols in MIMO channels. This method is based on the energy level of the received signals. At the receiver, we assume the knowledge of channel state information which can be estimated by different methods, e.g. by sending pilots. So, we can determine all possible levels of energy. This computation of energy levels is done only once for the quasi-static channels. Energy of the received signals is a criterion by which we can estimate the transmitted symbols. Detection of transmitted signal is made based on the nearest energy level and the points which lie on it. In other words, we have restricted our search space to a new smaller space with different levels of energy. Simulation results confirm approximately the same performance between the maximum-likelihood detector and the proposed approach especially in high signal-to-noise ratios with a remarkable reduction in the computational complexity.     

Minimizing torque ripple in a brushless DC motor with fuzzy logic: applied to control rod driving mechanism of MNSR

A permanent magnet BLDC(brushless direct current) motor is used to move the control rod of a miniature neutron source reactor(MNSR). The BLDC motor drive is modeled using MATLAB/SIMULINK. Two main parts of the modeling are the inverter switching and the current control. Current control with chopping used to minimize the torque ripple of the MNSR control rod drive. Fuzzy logic current control together with soft chopping control shows the best response of all the three strategies. The prototype drive mechanism has an ATmega32 controller and power MOSFET switches. The simulation results are compared with experimental drive mechanism.     

The S-transform using a new window to improve frequency and time resolutions

The S-transform presents arbitrary time series as localized invertible time–frequency spectra. This transformation improves the short-time Fourier transform and the wavelet transform by merging the multiresolution and frequency-dependent analysis properties of wavelet transform with the absolute phase retaining of Fourier transform. The generalized S-transform utilizes a combination of a Fourier transform kernel and a scalable-sliding window. The common S-transform applies a Gaussian window to provide appropriate time and frequency resolution and minimizes the product of these resolutions. However, the Gaussian S-transform is unable to obtain uniform time and frequency resolution for all frequency components. In this paper, a novel window based on the $t$ student distribution is proposed for the S-transform to achieve a more uniform resolution. Simulation results show that the S-transform with the proposed window provides in comparison with the Gaussian window a more uniform resolution for the entire time and frequency range. The result is suitable for applications such as spectrum sensing.     

Support vector machine-based classification scheme for myoelectric control applied to upper limb

This paper proposes and evaluates the application of support vector machine (SVM) to classify upper limb motions using myoelectric signals. It explores the optimum configuration of SVM-based myoelectric control, by suggesting an advantageous data segmentation technique, feature set, model selection approach for SVM, and postprocessing methods. This work presents a method to adjust SVM parameters before classification, and examines overlapped segmentation and majority voting as two techniques to improve controller performance. A SVM, as the core of classification in myoelectric control, is compared with two commonly used classifiers: linear discriminant analysis (LDA) and multilayer perceptron (MLP) neural networks. It demonstrates exceptional accuracy, robust performance, and low computational load. The entropy of the output of the classifier is also examined as an online index to evaluate the correctness of classification; this can be used by online training for long-term myoelectric control operations.     

Influence of Ni/Co binders and Mo2C on the microstructure evolution and mechanical properties of (Ti0.93W0.07)C–based cermets

In this research, solid–solution powder of (Ti_0.93W_0.07)C was synthesized by high–energy ball mill method followed by carbothermal reduction process. Subsequently, the acquired powder was blended with Ni/Co and Mo₂C secondary carbide, and sintered under the optimized temperature (1510?°C) for 1?h to produce the modulated cermets. A typical core–rim structure formation with solid–solution phases was confirmed by backscattered electrons studies using a Field Emission electron scanning microscope. The hardness of the synthesized cermets was enhanced by increasing the specific amount of Mo₂C. The acquired results demonstrate that the binder type has a prominent influence on the microstructure and hardness of the prepared cermets. The hardness of (Ti_0.93W_0.07)C–xMo₂C–Ni cermet increased ~ 9%, when nickel was partially substituted by cobalt.     

Polyacrylonitrile/α-Fe2O3 Hybrid Photocatalytic Composite Adsorbents for Enhanced Dye Removal

The potential of a novel α-Fe₂O₃/polyacrylonitrile (PAN) hybrid composite adsorbent to eliminate methylene blue (MB) from aqueous solution was evaluated. PAN was selected as the base composite. The presence of α-Fe₂O₃ as nanophotocatalyst on the surface of PAN introduced an efficient photocatalytic hybrid composite adsorbent for degrading MB. Effects of α-Fe₂O₃ nanopowder loading, pH, temperature, MB initial concentration, solar light, and contact time were investigated. Langmuir, Freundlich, and Temkin isotherms were applied to analyze the adsorption behavior. The Freundlich equation provided the best correlation with experimental data. Pseudo-first-order, pseudo-second-order, and intraparticle models were employed. Thermodynamic studies indicated an endotherm and spontaneous adsorption process in a defined temperature range.     

An improved particle swarm optimisation for unit commitment in microgrids with battery energy storage systems considering battery degradation and uncertainties

Using electric storage systems (ESSs) is known as a viable strategy to mitigate the volatility and intermittency of renewable distributed generators (DGs) in microgrids (MGs). Among different electric storage technologies, battery energy storage (BES) is considered as the best option. In unit commitment (UC) module, the set of committed dispatchable DGs along with their power, power exported to/imported from macrogrid and status and power of ESS units are determined. In this paper, BES degradation is considered in UC formulation and an efficient particle swarm optimisation with quadratic transfer function is proposed for solving UC in BES‐integrated MGs, while the uncertainties of demand, renewable generation and market price are considered and dealt with robust optimisation. UC is formulated as a multi‐objective optimisation problem whose objectives are MG operation cost and BES degradation. The resultant multi‐objective optimisation problem is converted into a single‐objective optimisation problem and the effect of weight factors on MG operation cost and BES lifecycle are investigated. The results show that by consideration of BES degradation in objective function, BES lifecycle increases from 350 to 500 and the minimum depth of charge increases from 5.5% to 34%; however, MG operation cost increases from $8717 to $8910.2. The results also show that by consideration of uncertainties, MG's operation cost increases by 8.22%.