فصلنامه پدافند غیرعامل
سال سیزدهم شماره 3 (پیاپی 51، پاییز 1401)

In today's societies, the power systems despite their vast developments as critical infrastructures (CI), are exposed to numerous natural and unnatural threats. In the past, power grids were designed only to withstand typical events which would have predictable probabilities. However, nowadays events with low probabilities and high effects are considered a major challenge. Power grids are expected to have the necessary flexibility in the face of such events and should not be disrupted quickly. This demonstrates the concept of resilience. In this article the resilience enhancement strategies, and in particular, the undergrounding as the best solution, are examined considering focused physical attacks. Taking budget constraints into account, the proposed algorithm determines the priorities of lines and buses to be undergrounded. This algorithm considers two approaches of the contingency analysis, namely the experts views and the index of load loss, in order to get the best choices for undergrounding. It should be noted that in this paper the static status of the grid is considered. Finally, the proposed method is implemented on the IEEE 39-bus test grid using Digsilent software, and the results are presented and discussed to evaluate the capabilities of the proposed method.

Today, the construction of highly critical structures (such as military and nuclear structures, hospitals and infrastructures), with high resistance to impact loads and high temperatures, is of particular importance in the field of passive defense. In this regard, the production of high-strength and nature-friendly concrete as the main material used in these types of structures plays a significant role. In this paper, the laboratory properties of the slag geopolymer concrete containing 0 to 8% nanosilica and 1 to 2% polyalphin fibers have been investigated. The concrete samples made at 90 days of curing age at 25 and 500 °C Celsius underwent weightlifting, weight loss, scanning electron microscopy (SEM), X-ray diffraction (XRD) spectroscopy, and X-ray fluorescence (XRF) at 25 °C. At the age of seven days, the processing was performed on the concrete samples. The results indicate the weakening of the microstructure of concrete exposed to high temperatures. Also, the improvement of test results in the geopolymer concrete compared to ordinary concrete is evident. The best and worst performance in the weight loss test of the samples belonged to the geopolymer concrete containing 8% nanosilica and the geopolymer concrete containing 8% nanosilica and 2% fibers, by 0.061% and 0.12% weight loss of the sample, respectively. The best performance in the energy absorption of falling weight at 25 and 500 degrees Celsius belongs to the geopolymer concrete (containing 8% nanosilica and 2% fiber) at 2928.25 and 773.44 joules, respectively. The highest and lowest energy loss of concrete samples at 500 °C compared to 25 °C belong to the ordinary concrete and the geopolymer concrete (containing 8% nanosilica) by 83.33% and 53.33%, respectively.

One of the passive defense policies is to protect citizen life and reduce vulnerability during a crisis. Enemy attacks on cities with the purpose of psychological goals achievements is a military tactic widely used in recent wars. The concentration of human and material capital in cities and the ease of targeting them show the need to build shelters to reduce the vulnerability of ordinary people. In this article, in order to choose a suitable and optimal place to build a shelter in the 18th district of Tehran, library studies, field observations and interviews with experts have been performed and10 indicators have been chosen from the obtained indicators, and weighted using the FAHP method with the aims of ensuring citizen safety, multi-purpose usability and minimal construction costs. In the next step, by constructing the layers related to these indicators, shelter location has been implemented based on a systematic process in the GIS geographic information system and desirable locations in the region have been determined.

One of the national and vital infrastructures of any country is the electricity network of that country. Vulnerability in power stations, which are the main artery in the cycle of electricity production, transmission and distribution, would result in irreparable damage. One of the ways to create a crisis is vandalism on electric substations, which causes public dissatisfaction, economic, social and even political crises on a large scale. One of the strategic goals of passive defense is to reduce this vulnerability and ensure the continuous functionality of vital and sensitive centers of the country against the actions of the enemy. Meanwhile, passive defense is known as one of the most effective and stable methods of defense against threats. The purpose of this research is to assess the risk of vandalism in substations from the passive defense point of view and provide solutions to deal with it. A 400 KV substation, being in the category of important and sensitive substations, is one of the most desirable goals to achieve this objective. For this purpose, in this article, a number of possible threats to the post were examined and the equipment was evaluated. In the evaluation of the final risk of sabotage threat, the auto-transformer, transformer and breaker were ranked at high, medium and low risk levels respectively, while the control room had the risk of medium upwards. In this research, the RAMCAP methodology was used as a research framework in risk assessment. Considering the network nature of the studied infrastructure, the network structures were used for information analysis and the multi-criteria decision-making method using the ANP method and Super Decisions software was used for the analysis.

Today, the interest in predicting and detecting events using the data available on social networks has increased. Social networks can be called the sensors of society, because the users always express their positive and negative opinions about the events of the world around them, which results in an environment full of real-time reactions to real-world events. Social networks are one of the best tools for assessing the society and predicting upcoming events. Although the automatic detection and classification of events, especially social anomalies such as riots, is a trivial task, it is of great value to governments and security organizations that need to respond quickly and appropriately; because the costs and damages caused by these unrests can be reduced. For this challenge, we have developed an event predicting framework that can distinguish "disruptive events" that threaten social security and order from daily events. To do this, we have used natural language processing techniques to comprehend texts, remove the limitations of human language, and perform sentiment analysis and topic detection. We have classified the events using machine learning techniques such as the Naïve Bayes and Support Vector Machines. Finally, we have evaluated our framework in a large and real data set from Twitter to show the efficiency and effectiveness of our system in predicting future events. The results show that the proposed framework has the ability to detect tweets reflecting dissatisfaction with 79% accuracy. We have also managed to extract the useful information related to an event with 40% accuracy from these tweets in the form of 5 topics namely, the place, time, people, goals and event related factors.

Preventing the spread of fire and reducing the associated risks, is a significant issue in passive defense. Underground places housing mechanical and electrical installations, tunnels, and underground infrastructures, are always at risk of fire, and timely information about fires in these places is doubly important. The use of fire extinguisher balls is one of the newest methods that has been proposed in order to deal with fire hazards in these places. These balls explode with the heat of the fire and sound a terrible alarm. In this study, the acoustic performance of these balls during the explosion in a hypothetical underground location was simulated and investigated by Comsol software and the parameters of acoustic pressure, total sound level and transmission loss during the explosion of the ball were studied. The results of the present study showed that at low to medium frequencies (below 900 Hz), the sound caused by the explosion of the ball would be well heard by those present in the surrounding area, which confirms the optimal sound performance of the ball in fire alarm and warning.

Nowadays, the use of integrated water and electricity microgrids has become a suitable solution for increasing the influence of renewable energies in solving economic problems related to this field. However, an efficient model is needed to increase the energy efficiency and overcome the environmental and economic challenges associated with the integrated water and electricity microgrid planning. This paper presents a multi-objective optimization model for system scheduling. In this model, variable speed pumps in the water system as well as storage tanks and flexible sources are optimally programmed to reduce the operation costs and pollution. The proposed model is a two-objective optimization problem. In this paper, the Epsilon constraint method and the fuzzy method are used to solve the proposed two-objectives problem. The proposed model has been tested on 33 micro-buses and 15 water nodes and has been investigated for different cases. The simulation results prove the effect of water and electricity network planning integration on reducing the operation costs and pollutant emissions.