In [9], De Wolf and Smeers consider the problem of the optimal dimensioning of a gas transmission network when the topology of the network is known. The pipe diameters must been chosen to minimize the sum of the investment and operating costs. This two stage problem was solved by application of the bundle method for nonsmooth optimization. This model does not reflect any more the current situat...

The present chapter addresses the problems of gas turbine gas path diagnostics solved using artificial neural networks. As a very complex and expensive mechanical system, a gas turbine should be effectively monitored and diagnosed. Being universal and powerful approximation and classification techniques, neural networks have become widespread in gas turbine health monitoring over the past few y...

Modern gas-fired power stations are discussed as an alternative for replacing eventually decommissioned nuclear power stations. With an also increasing number of smallest-scale gas turbines, the importance of the gas network is hence likely to increase in coming years. The presence of converters as e.g. a combined cycle gas turbine raises the question if and to what extent the electrical networ...

the most costly operation in the oil exploration is the well network drilling. one of the most effectiveways to reduce the cost of drilling networks is decreasing the number of the required wells byselecting the optimum situation of the rig placement. in this paper, balas algorithm is used as a modelfor optimizing the cost function in oil well network, where the vertical and directional drillin...

Design of optimal microstructures for infiltrated solid oxide fuel cell (SOFC) electrodes is a complicated process because of the multitude of the electrochemical and physical phenomena taking place in the electrodes in different temperatures, current densities and reactant flow rates. In this study, a stochastic geometric modeling method is used to create a range of digitally realized infi...

Prediction of viscosity of natural gas is an important parameter in the energy industries such as natural gas storage and transportation. In this study viscosity of different compositions of natural gas is modeled by using an artificial neural network (ANN) based on back-propagation method. A reliable database including more than 3841 experimental data of viscosity for testing and training of A...

Gas sensors are generally defined as devices to detect or measure concentration of (bio-) chemicals in gaseous state. The demands of highly sensitive gas sensors for industry, environmental monitoring, safety, biomedicine, and pharmaceutics have provoked the intensive research interests in micro-electromechanical systems (MEMS) and nanotechnology. The nanotechnology in conjunction with MEMS has...