There are two approaches for simulating memory as well as learning in artificial intelligence; the functionalistic approach and the cognitive approach. The necessary condition to put the second approach into account is to provide a model of brain activity that contains a quite good congruence with observational facts such as mistakes and forgotten experiences. Given that human memory has a solid core that includes the components of our identity, our family and our hometown, the major and determinative events of our lives, and the countless repeated and accepted facts of our culture, the more we go to the peripheral spots the data becomes flimsier and more easily exposed to oblivion. It was essential to propose a model in which the topographical differences are quite distinguishable. In our proposed model, we have translated this topographical situation into quantities, which are attributed to the nodes. The result is an edge-weighted graph with mass-based values on the nodes which demonstrates the importance of each atomic proposition, as a truth, for an intelligent being. Furthermore, it dynamically develops and modifies, and in successive phases, it changes the mass of the nodes and weight of the edges depending on gathered inputs from the environment.

Fire behavior, especially its interaction with ventilation system in tunnels, is still a challenging issue for road tunnel designers. This paper presents the results of a study investigating the influence of a road tunnel ventilation system, on conventional Fires. For this purpose, a 25 MW Fire corresponding to a conventional Fire in a road tunnel was simulated using 2D numerical modeling, for transient viscous multi-component gas at low Mach numbers to study smoke and heat propagation within a road tunnel under Fire. Complete Navier-Stocks and Reynolds equations were solved using developed algorithm of numerical modeling. The results from a series of calculations were compared with results of experimental researches to examine the accuracy and stability of the calculations. The comparisons showed that the algorithm provided a good description of physical processes in selected class of flow. It was also concluded that calculation accuracy is not lower than those obtained from established simulation software programs.The stability and good convergence of the algorithm was confirmed by separate calculations with different grid patterns for the tunnel under consideration. The results revealed that the temperature at tunnel wall may rise up to 900oC. The concentration of smoke may also increase up to 95 % with a burning truck. Results were applied to assess the ventilation system designed for a new long road tunnel in case of Fire. The results from the study along with other information were applied to assess the designed ventilation system and to establish the suitable Firefighting and rescue plan.

Introduction: WildFires cause substantial losses of property and human lives in ecosystems in Iran and all around the world. Every year, about 6000 ha of forests are affected by Fires in Iran (Jahdi, Salis, Darvishsefat, Mostafavi, Alcasena, Etemad, Lozano, & Spano, 2015). These Fires can occur naturally due to climate change or abnormally caused by human activities in the forests. In fact, Fire is one of the most important factors in disrupting the structure and dynamics of forest in natural conditions that produces a large amount of dead wood caused by the destruction of trees (Coban & Mehmet, 2010). As a result, there are significant costs to prevent Fire every year in countries it takes place, and managing ecosystems is a way to reduce the effects of Fire on war and maintain perspectives. To manage Fire in forests, understanding the behavior of the Fire and the factors causing it in a prone environment and factors affecting its behavior are essential (Artes, Cencerrado, Cortes, & Margalef, 2013). One way to manage Fire is FARSITE model. This model has become popular due to its steady structure and simplicity of popularity in the modeling of Fire spreading. This model is considered as one of the main Fire simulation systems used to describe the behavior and release of horrific Fires and is a semi-experimental model (Shen, Prince, Gallacher, Fletcher, & Fletcher, 2017)...

In this paper, methane pool Fire and Fire plumes with two heat release rates of 14 and 45 kW are simulated using Large-Eddy simulation (LES) method. In order to investigate the accuracy of various combustion models, two combustion models of Eddy Dissipation Model (EDM) and Infinity Fast Chemistry (IFC) have been evaluated with a one-equation sub-grid scale model. The simulated results are in a good agreement with experimental measurements, and show the scaling relations of mean temperature and velocity in each pool Fire region including stable flame, intermittent and plume. Results indicate that, EDM combustion model have a better prediction of mean velocity and temperature while it has more computational time. In addition, by incorporating Fast Fourier Transform (FFT) analysis on the transient results of temperature and velocity, the prevailing frequency for the temperature and velocity is equal which is 2. 75 Hz for the current case. Moreover, energy cascade of eddies shows the accuracy of the LES in predicting pool Fire dynamic.

The mechanical ventilation smoke management system involves the use of supply fan, jet fan, and exhaust fans, which are activated at different times after a Fire is extinguished. This paper numerically investigates the effect of the priority and delay of smoke management systems on smoke distribution and visibility in a car park after a Fire, using Fire dynamic simulation Code 6.7.6. The flow rates of the exhaust fan, supply fan and jet fan are 1.9 m³/s, 1.43 m³/s, and 1.67 m³/s, respectively. The Fire, located near the supply fans, is modeled as a rectangle with dimensions of 2.0 × 0.8 m² and a power of 1.6 MW, lasting for one minute from ignition to extinguishment. Polyurethane is assumed as the flammable material. The priority and delay of the smoke management systems are evaluated through four scenarios over a period of 420 seconds. The results show that visibility reaches acceptable levels in all scenarios at all locations after 420 seconds. Additionally, the results indicate that the visibility of the upper half is highest for scenario a, at around 15 m. However, the visibility of the lower half is highest for scenario d, ranging between 20 and 30 m. It can be concluded that delaying the activation of smoke management systems is an effective strategy for facilitating smoke removal and fresh air intake.