Damage of the urban gas network due to an earthquake can cause much loss including fire-induced loss to infrastructure and loss due to interruption of gas service and repairing or replacing of network elements. In this paper, a new fire ignition model is proposed and applied to a conventional semi-probabilistic model for estimating various losses due to damage of an urban gas network in an eart...

Global warming created by large scale emissions of Greenhouse Gases (GHG) are a worldwide concern. Due to this, the issue of green gas network has required more attention in the last decades. Here, we address the GHG-based problem that arises in a gas network where gas flow is transferred from the Town Board Station (TBS) to consumers by pipeline systems. Given this environment, an optimization...

In this study, the use of the three-layer feed forward neural network has been investigated for estimating of infinite dilute diffusion coefficient ( D12 ) of supercritical fluid (SCF), liquid and gas binary systems. Infinite dilute diffusion coefficient was spotted as a function of critical temperature, critical pressure, critical volume, normal boiling point, molecular volume in normal boilin...

energy, due to its increasing usage in various broad areas has been maintained as a vital factor in economic growth and development of societies. meanwhile, natural gas is considered as one of the most important energy sources. therefore, the efficiency and the productivity of the gas companies are crucial to be assessed. numerous examples from industrial multistage processes including internal...

gas hydrates are a costly problem when they plug oil and gas pipelines. the best way to determine the hft and pressure is to measure these conditions experimentally for every gas system. since this is not practical in terms of time and money, correlations are the other alternative tools. there are a small number of correlations for specific gravity method to predict the hydrate formation. as th...

The ability of Artificial Neural Network (ANN) for estimating the natural gas demand load for the next day and month of the populated cities has shown to be a real  concern. As the most applicable network, the ANN with multi-layer back propagation perceptrons is used to approximate functions. Throughout the current work, the daily effective temperature is determined, and then the weather data w...