مجله علوم و فناوری های پدافند نوین
سال سیزدهم شماره 2 (پیاپی 48، تابستان 1401)

In this paper, the simulation of a direct matrix converter and the thermal analysis of its protection devices are performed. Nowadays, due to the technological advances in the field of power electronic converters, matrix converters are receiving more and more attention. These converters have many capabilities and are used in various industrial and military applications such as the aerospace industry, offshore platforms, rail transport, borderline military sites, apart from the power grid and similar applications. The main purpose of this paper is to provide a procedure for designing protection subsystems including input filters, protection circuits (snubbers), and heat sinks. The input filter reduces the penetration of disturbances from the converter to the network. On the other hand, due to the high switching frequency, the use of snubber circuits in matrix converters is essential. Also, power circuit devices need thermal protection for long-term operation. In this paper, the aforementioned requirements have been studied using a proposed procedure for a 3 kW matrix converter. The results show the reduction of the input current harmonic distortion due to the performance of the input filter and also the improvement of the step response of the system while reducing the steady state error. Also, the designed snubber circuits have the ability to reduce the voltage stress on the switches by 20%. Moreover, through the finite element analysis, the effect of heat sink in reducing the thermal stress by 60% is demonstrated.

The contagious SARS virus CoV_2 spread rapidly around the world. The virus has infected more than 550 million people worldwide and killed about 7 million to date. Regarding the mechanism of infection, the receptor-binding domain (RBD) of the Spike protein plays an important role in the virus entry into the host cell. In this study, with a bioinformatics approach the cassette design, codon compatibility, protein stability and finally the structural accuracy (through examining the protein expression) were investigated. To increase the probability of RBD cassette expression, the gene codons and various parameters were optimized and the thermodynamic analysis of mRNA structure were performed to increase stability. The structure of the third protein was also predicted and the quality of the structures was evaluated. The linear and conformational B-cell epitopes were determined. The recombinant RBD protein showed the highest antigen index. The compatibility index of the recombinant protein codon increased to 0.96. The third predicted structure based on the I_TASSER server showed good quality. Thermodynamic analysis of the mRNA structure showed that the predicted structure is stable. The conformational and linear B-cell epitopes were observed in all three domains of the recombinant protein. Finally, the recombinant protein was expressed in a bacterial host. Immunoinformatics and expression results showed that the designed recombinant construct has a high antigenicity and production potential and can be considered as an immunogenic candidate against SARS CoV_2 virus in the future studies.

The Intrusion detection system (IDS) manages a massive volume of data that comprises irrelevant and redundant features, leading to more significant resource consumption, long-time training and testing procedures, and lower detection rate. Hence, Feature selection is a crucial phase in intrusion detection. The aim of this paper is to introduce an intersection-based strategy that optimally selects the features for classification. This feature selection involves an intersection of simultaneous mutual information based on the transductive model (MIT-MIT), Anova F-value, and Genetic Algorithm (GA) methods. A benchmark dataset, named NSL-KDD, is applied to evaluate the effectiveness of the proposed approach. This study includes accuracy, precision, recall, and F1 score as evaluation metrics for IDS, which analyzes the proposed method with state-of-the-art classifiers. The evaluation results confirm that our feature selection algorithm provides more essential features for IDS to achieve high accuracy, overwhelming the other comparative algorithms.

Solar generators have many applications in the field of modern defense systems. An important and fundamental application of this type of generator is to provide sustainable energy for telecommunication sites as well as increase their resilience during various accidents and crises.  The use of optimal and controlled solar generators under variable environmental conditions in order to increase the resilience of telecommunication sites is one of the main objectives of this research. Therefore, under variable temperature and radiation conditions the maximum power point characteristic of the solar generator is tracked and controlled with the aim of increasing efficiency. In this research, the dynamic programming method (DPM) is used by combining the perturbation and observation (P&O) algorithm and the famous Newton-Raphson numerical algorithm. The analysis is performed by the dynamic programming method, based on the data obtained from the measurement under variable temperature and radiation conditions, and then an intelligent decision is made. The efficiency obtained in this article has been compared with the other research works and shown to be the highest. Quantities and parameters have been obtained through both MATLAB simulations and practical measurements, and presented in the form of figures and tables. The percentage of relative error in tracking the maximum power point characteristic of the solar generator is very small.

Considering the high importance of the electricity industry as the infrastructure of other infrastructures of the country, increasing the reliability of the correct operation of the protection programs in the electricity transmission network is considered as one of the measures that can be mentioned in the direction of passive defense. One of these methods is the use of fault current limiters (FCL)  in the transmission network. In power systems, the technical and economic benefits of using FCL depend on the type, number, installation locations and optimal parameters of limiters. In the present study, the number, location and impedance of FCLs in the network are determined to achieve various goals such as reducing the short circuit level , then, the minimum number of limiters along with the installation locations and the optimal parameter of each limiter are calculated in two steps using a meta-heuristic algorithm, called the Hybrid Optimization algorithm (PSOGSA) (Combination of the Particle Swarm Optimization Algorithm (PSO) and Gravitational Search Algorithm (GSA)). In the following, the proposed meta-heuristic algorithm is compared with genetic algorithms, PSO and GSA. According to the results of the numerical studies conducted to compare the proposed algorithm with GA, PSO and GSA algorithms, the proposed hybrid algorithm instead of installing more fault current limiters, by increasing its impedance optimally while reducing the total cost of installing this equipment; has better performance in terms of reducing the short circuit level of buses and it converges to the optimal point faster..

One of the main factors in designing drones and submarines is the appropriate choice of an electrical energy storage device as the energy source of their propulsion systems. This review paper addresses the energy storage technologies, whether battery or fuel cell, applicable in drone and submarine industries. Batteries are widely used in drones due to their lower weight and occupation space and can act as a primary or secondary power supply. Among various chemical compounds, lithium-ion and lithium polymer batteries are the most common battery technologies with a higher energy density. Although the energy density of fuel cells is much higher than that of batteries and increases flight endurance and altitude, they are not yet common in the drone industry due to the high price and volume. This feature of fuel cells has led to their usage as an energy source in the air-independent propulsion technology of submarines. Also, extreme temperature variations for drones can reduce the efficiency and lifetime of batteries and even fuel cells. Battery insulation is provided for temperature drop due to an increase in altitude, and heat management systems are provided for temperature increase due to high current flow.