نشریه مهندسی برق
سال پنجاه و دوم شماره 4 (پیاپی 102، زمستان 1401)

The proposed converter is an interleaved ultra-large gain converter based on coupled-inductor (CI), built-in transformer (BIT) and switched capacitor (SC). The main novelty of the proposed converter is that the voltage gain can be achieved in proportionate to the multiplication of the turn ratios of the CIs and BIT that increase the voltage gain of the proposed converter. Also, through this topology, the voltage stresses across the power switches are effectively reduced and as a result MOSFETs with low ON-state resistances can be implemented that reduces the cost and conduction losses. Implementation of active clamp technique not only facilitates zero voltage switching (ZVS) turn-ON and turn-OFF for all switches, but also recycles the energy of the leakage inductances. Moreover, due to the presence of the leakage inductances, all of the diodes are turned OFF with zero current switching (ZCS) performance and the associated reverse recovery problem is solved, effectively. Through extensive comparison discussion, it is concluded that the proposed converter with low number of components outperforms previously presented ones in the terms of the voltage gain and voltage stresses across switches. Finally, the performance of the proposed converter is validated through developing a 100kHz 600W 22-380V prototype.

A reconfigurable plasmonic metasurface lens using TiO2 thin film is designed and simulated. Such a planar lens consists of an array with gold nano-antennas mounted on an uniaxial anisotropic substrate. The element of this array is a class of V-shaped nano-antenna with two freedom degrees for extracting phase diagram needed for plasmonic lens design. Two different parameters of this element are the length V arms and its angle. The used Titanium dioxide (TiO2) as a substrate of this metasurface leads to adding another freedom degree into the unit cell due to its anisotropy property at optical regime. Such a unit cell is analyzed using Method of Moments (MoM) in which its dyadic Green's function is evaluated by means of the Equivalent Transmission Line Model (ETLM). Using MoM/ETLM, the cross-polar phase diagram of unit cell is extracted once the optical axis of anisotropic thin film is aligned in x-direction. Then, the elements' dimensions of the lens's array is selected by means of the obtained phase diagram and the equal optical length principle to fulfill the required phase discontinuities of each cell and produce double focus points. Finally, the entire of structure is simulated using a Finite Element Method (FEM) based simulator. It is numerically shown that a double focus planar lens is achieved once lens surface is illuminated by a plane wave and the intensity of lens focuses can be controlled by rotation of TiO2 optic axis. Such a controllable behavior can also be achieved by changing the incident polarization.

To measure the transient current of very fast switching circuits, sensors with a high frequency bandwidth are needed. For such an accurate current sensor, the voltage measured from the two ends of the sensor conductor must be proportional to the passing current in all conditions. The main problem of these sensors is the change in the impedance of this conductor at different frequencies. In this way, the relationship between the measured voltage and the desired current is not linear and the measured value is not valid. Also, the change of conductor resistance due to skin effect can also be the cause. In this article, it is shown that based on coaxial shunt sensors and the selection of the thickness of the sensor conductors, the effect of internal conductor inductance and skin effect can be eliminated in the desired bandwidth. The conductor of the inner pipe of the sensor is divided into several parallel parts, which causes a greater increase in the ratio of ohmic resistance to inductance. Also, the inductance of this conductor has been calculated analytically. To design the sensor based on the frequency bandwidth and current pulse characteristics, the sensor design flowchart was proposed and based on that, a current sensor for the MHz frequency bandwidth and a sensor for the GHz frequency bandwidth were designed and then a sample current sensor was made. And by that, the flat current pulse with the amplitude of 146A and the width of 2.5ms and the standard current pulse of 20.8µs with the amplitude of 2kA and the width of 32µs have been accurately measured.

In areas where the motor load is the predominant load, when the short circuit occurs, the speed of the motors decreases and their power reactive consumption increases, which causes some delays in voltage recovery after fault clearance. This delay can cause operation of protection systems and load shedding. Fault-Induced Delayed Voltage Recovery is a phenomenon in which the voltage level does not reach the pre-fault value immediately after the fault is cleared. If the Voltage recovery delay is significant, the wind power plant will be disconnected from the power system, which causes other problems in the power system. The purpose of this paper is to evaluate the effect of different wind power plant controls on voltage recovery delay. Wind power plant modeling is based on IEC61400-27-1 standard. Also in this paper the effect of location of wind power plant and the ability to Low Voltage Rid Through of wind power plant is considered. All the simulations are performed in DIgSILENT PowerFactory 2021 software.

In this paper, a comparator is introduced for use in CMOS image sensor which can suppress the FPN noise of the pixel in addition to comparing voltages. Due to a large number of circuits in the column-parallel image sensors, this technique can help save power, silicon area, and imaging time by merging the noise suppression circuit in the data converter. Simulation results show that the proposed comparator for the input range of 0.7 to 1.7 volts with an accuracy of 1 mV can do the comparison and subtraction in 25 nanoseconds. The total power consumption of the comparator is about 64 microwatts, which has 1.8- & 2.5-volt power supply and removes FPN noise up to the range of 50 mV with good accuracy. Total noise referred to the input of the comparator for the bandwidth of 1 Hz to 1GHz was obtained 500µV. All circuits are designed in 0.18μm CMOS technology and simulated by Specter simulator.

One of the obvious reasons for most disorders in network service provisioning is network path congestion. Congestion avoidance in today's networks is too costly and sometimes impossible. With the introduction of SDN, centralizing the equipment's control plane has become possible. This paper presents an enhanced method named ESV-DBRA to avoid congestion in multi-tenant SDN networks. At first, ESV-DBRA monitors the traffic load and delay of all network paths for each tenant individually. Then, by merging the parameters obtained from the monitoring, the Service Level Agreements (SLA), and a novel proposed cost function, it calculates the cost of the network paths per tenant. As a result, traffic for each tenant is routed through the path/paths at the lowest possible cost from the tenant's perspective. Next, the bandwidth quotas will be calculated and assigned to the tenants over their optimal routes. Afterward, whenever congestion is likely to occur in a path, ESV-DBRA automatically changes the route or bandwidth of the tenants' traffic related to this path to avoid congestion. Related algorithms are also proposed.Eventually, simulations show that the proposed method effectively increases bandwidth utilization by 10.76%.

Automatic topic detection seems unavoidable in social media analysis due to big text data which their users generate. Clustering-based methods are one of the most important and up-to-date categories in topic detection. The goal of this research is to have a wide study on this category. Therefore, this paper aims to study the main components of clustering-based-topic-detection, which are embedding methods, distance metrics, and clustering algorithms. Transfer learning and consequently pretrained language models and word embeddings have been considered in recent years. Regarding the importance of embedding methods, the efficiency of five new embedding methods, from earlier to recent ones, are compared in this paper. To conduct our study, two commonly used distance metrics, in addition to five important clustering algorithms in the field of topic detection, are implemented by the authors. As COVID-19 has turned into a hot trending topic on social networks in recent years, a dataset including one-month tweets collected with COVID-19-related hashtags is used for this study. More than 7500 experiments are performed to determine tunable parameters. Then all combinations of embedding methods, distance metrics and clustering algorithms (50 combinations) are evaluated using Silhouette metric. Results show that T5 strongly outperforms other embedding methods, cosine distance is weakly better than other distance metrics, and DBSCAN is superior to other clustering algorithms.