Advanced Defense Science and Technology
Year:2019 | Volume:10 | Issue:3 |Papers Count:15

According the increasing use of concrete filled double-skin steel tubular (CFDST), this study investigate the effect of axial compressive force on the lateral deformation caused via blast wave by using numerical simulation by AUTODYN software. For this purpose, CFDST with square section and different levels of axial load (p/pu from 0 to 80%) were modeled and subjected to 35 Kg TNT explosion loading. The current research shows that the residual and maximum displacements as well as columns’ damage index caused by blast load are decreased with increasing axial compressive load for lower values of axial force, but by exceeding the axial force over 0. 6 of ultimate capacity, the aforementioned parameters are increased. Compared when using plates of different thickness, the minimum deformation and damage could be achieved by applying steel sheets of the same thickness for external and internal cover.

In recent years by increasing the terrorist threats and explosive operations in urban areas, protecting the important life line infrastructures against threats that arise from the explosion has become more important. Hence, predicting the extent of the destructive power of the explosion and its effects on soil layers necessitates further studies and researches. In order to reduce stress caused by the explosion and to control increasing compressive and shear stresses in the soil and lateral pressure on the pipes, several solutions have been presented. One of these solutions is utilizing geosynthetic reinforcement. In reinforced soils, the mechanism of stress transfer is based on the interaction of soil and reinforcement elements. The shear stress reaction causes tensile forces in reinforcement elements. This phenomenon leads to an increment of shear strength, elasticity and ductility of the reinforced soil. In this study, FEM method is used for modeling pipelines buried in the reinforced sandy soil exposed to surface blast loading. By comparing the results, it can be concluded that by using reinforcement in the soil, the stresses and deformations in the buried pipeline could be reduced. The results show that the deformation rate obtained from the placement of reinforcements at a depth of 1. 5 m from the ground level (with a fixed width), has decreased by an amount of 35%. In addition, the rate of reduction in deformation of the pipe crest has decreased about 51% using a 4 meter wide reinforcement at a constant depth of 1 meter.

Nowadays, design of buildings against shock loads caused by explosion has attracted special attention, due to an increase in terrorist attacks. Thus, introducing the nature of explosion and its loads are regarded as the first step in achieving this goal. Blast is an abrupt release of big amounts of energy in which light, heat, sound, shock wave, and dense air are produced. The present study aims to examine the nonlinear dynamic response of a masonry wall including two openings by the underground explosion that employedto produce earthquake-like waves. In this study, Dynamic analysis is conducted through ANSYS software. Menetrey-Willam and Drucker-Prager are used to model the structure and soil, respectively. Finally, the results of analyzing numerical model based on finite element method were compared with the field data. The outcomes demonstratedthat there is good agreement between numerical results and field data.

In this paper, the optimal planning of renewable energy systems including the wind turbine photovoltaic solar panels and energy storage systems has been done for a sample garrison considering the weather condition’ s uncertainty. The target case study is Tatavar1 garrison which has been located in Kermanshah province of Iran. Utilizing renewable based energy system for providing the energy demand of areas which are far from main grid is a suitable and practical suggestion. Consideration of uncertainty of energy production of these systems during the optimization studies affords more comprehensive and more practical results. The simulation results show that the using of renewable based energy systems caused considerable reduction of energy cost. Simulation results indicate that for case study of Tatavar 1, using the renewable energy system decrease the consumption of gasoil fuel about 87% and total cost up to 81% during the 5 years of optimization period, beside the eliminating the whole of load shedding hours.

IRAN and the world are moving away from central energy resource to distributed generation (DG) in order to lower carbon emissions. Renewable energy resources comprise a big percentage of DGs and their optimal integration to the grid is the main attempt of planning/developing projects with in electricity network. Feasibility and thorough conceptual design studies are required in the planning/development process as the most of the electricity networks are designed in the passed decades, not considering the challenges imposed by DGs. As an example, the issue of optimal placement and the capacity of DG’ s become problematic when large amount of dispersed generation is connected to a distribution network. Therefore, optimized algorithms have been developed over the last decade in order to do the planning purpose optimally such as to alleviate the unwanted effects of DGs. In this article, after explaining the two proposed methods, the modified non-sorting genetic algorithm (NSGA)’ s and Exchange Market Algorithm (EMA)’ s results, based on MATPOWER’ s systems have been compared, in order to find a fast and reliable solution to optimum planning.

The aim of this paper is to provide a new approach for assessing the risk of a power system against natural events and the threats imposed by the terrorist attacks. In this regard, the main determinants of the importance of an area are quantified in the form of 16 introduced items. Subsequently, by combining these 16 sub-indicators, the main index for risk assessment is calculated for each region. In order to analyze the total risk of the system, the outage probability of each element (including the transmission line and the bus) is determined considering the sixteen proposed factors involved. Finally, a new model is proposed to calculate the unserved power of each event using the proposed risk index and region value. The proposed method has been simulated on the geographic information of a case study. The proposed model can help to identify the critical points, as well as the quantitative assessment of the vulnerability level.

In this paper, the design, simulation, and optimization of a three-port waveguide circulator for microwave applications in X-band frequency with low insertion and reflection losses are investigated. To operate this circulator in high power application, the design is based on the waveguide structure. The ferrite design and its location are outlined while designed and fabricated circulator has a wide band frequency range in comparison to the conventional structures. It should be noted that the design and optimization procedure are completely considered. The fabricated circulator has the input standard WR-90 flange at the center frequency of 9. 4 GHz and the frequency band width, minimum isolation, and maximum insertion loss are about 4%, 20 dB, and 0. 25 dB, respectively. Finally, the results of simulation and measurements are compared together and close accordance is observed between them.

As computer networks grow, so attacks and intrusions to these networks are increased. In order to have a fully secure computer network, one needs ‘ intrusion detection systems’ (IDS) on top of firewalls. The goal of using an IDS is to supervise the abnormal activities and differentiate between normal and abnormal activities in a host system or in a network. An efficient IDS has high detection rate while keeping a low false alarm rate. In this paper, a new approach to classify KDD-Cup-99 data set using a combination of random forest method and genetic algorithm is presented. The purpose is to increase the speed of learning and test phases while improving the accuracy. Random forest is an ensemble learning method based on decision trees. Due to its relatively simple structure and good performance, it is used in many supervised learning applications. However, like all tree based machine learning algorithms, having too many categorical features, can be a problem both for the speed and accuracy. This is exactly the case with the problem in hand, i. e. intrusion detection; many of the features are in the form of categorical data. For example, in R language, the maximum number of definable categorical features for random forest is 53. The contribution of this work is resolving this issue with the aid of Genetic Algorithm (GA). In this research information gain as a measure of importance is defined and the number of features is reduced based on genetic algorithm.

Visual cryptography is one of the newest techniques is image encryption. Visual cryptography encrypts visual information and generates two or more shares which contain no information separately, but reveal the secret when superposed. The main advantage of this scheme is that the decoding process does not need any knowledge of cryptography and human visual system is able to decrypt the secret message. In this article, a new encryption method based on particle swarm optimization is provided. The basis matrices are obtained using this approach and then used for encryption. In previous work, a Genetic Algorithm based method was proposed. In our work we fix a subtle yet crucial bug in the GA based method which is generating pictures with negative contrast in some cases and propose a simpler alternative. Simulation results show that the proposed method meets all the initial conditions of visual cryptography while decreasing the number of function evaluations and can provide a contrast enhancement. Moreover, the proposed method has the advantage of being generic and can be used in various threshold based visual cryptography.

In this paper, a gray box fuzzer is presented to detect vulnerabilities in executable binary code. The literature surveys show that fuzz testing has three major problems. At first, the input space provided by the fuzzers to coverage execution paths in a binary program, can be very large. Secondly, most fuzzers can not support sufficient coverage of execution paths because of large input space. Finally, a large number of possible vulnerabilities can not reveal within an unseen execution path because of this unsufficient coverage. The proposed method, resolves the problem of large input space, in an evolutionary process, by conducting the test data generation towards suspicious paths in which one or more vulnerability patterns are observed. In the presented method, when a vulnerablility pattern is observed in an execution path by a test data, the next test data is generated revealing the vulnerablity. As a result, the number of detected vulnerabilities can increase. Our evaluations show better performance of presented method compared to other fuzz testing methods.

Using cloud computing helps enterprises to reduce their operational costs as well as to improve the scalability, availability, and reliability of their services. To improve system availability and protecting against disasters, enterprises have to decide how to migrate their on-premise applications to the cloud. Migrating of a legacy application to the cloud is a very complicated and time-consuming process, due to the complexity of applications, the dynamic environment of the enterprises and the variety of available cloud services. Despite many types of research in this context, a formal migration model based on known patterns has not been presented yet. In this paper, the Finite State Process (FSP) algebra is applied as a formal basis by which a step by step migration support system can be built automatically from the known application and cloud profiles. The proposed step by step migration model is superior to the current optimization methods that search the optimal deployment of application components to cloud services due to the fact that a step by step approach is more appropriate for dynamic environments. In fact, the main advantage of this method over previous methods is that it supports the automation of the migration plan with the possibility of modifying the migration path based on changing objectives in dynamic enterprise environments.