Ahmad Mousaei; Mohammad Ali Hatefi
Abstract
A value chain is a series of events that takes a raw material and with each step adds value to it. Global interest in the application of natural gas (NG) in production and transportation has grown dramatically, representing a long-term, low-cost, domestic, and secure alternative to petroleum-based fuels. ...
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A value chain is a series of events that takes a raw material and with each step adds value to it. Global interest in the application of natural gas (NG) in production and transportation has grown dramatically, representing a long-term, low-cost, domestic, and secure alternative to petroleum-based fuels. Many technological solutions are currently considered on the market or in development, which address the challenge and opportunity of NG. In this paper, a decision support system (DSS) is introduced for selecting the best fuel to develop in the value chain of NG through four options, namely compressed NG (CNG), liquefied NG (LNG), dimethyl ether (DME), and gas-to-liquids (GTL). The DSS includes a model which uses the technique for order performance by similarity to ideal solution (TOPSIS) to select the best fuel in the value chain of NG based on the attributes such as market situations, technology availability, and transportation infrastructure. The model recommends some key guidelines for two branches of countries, i.e. those which have NG resources and the others. We believe that applying the proposed DSS helps the oil and gas/energy ministries in a most effective and productive manner dealing with the complicated fuel-related production and transportation decision-making situations.
Mohammad Golshadi; Reza Mosayebi Behbahani; Mohammad Reza Irani
Abstract
A computational fluid dynamic (CFD) study of methanol (MeOH) to dimethyl ether (DME) process in an adiabatic fixed-bed reactor is presented. One of the methods of industrial DME production is the catalytic dehydration of MeOH. Kinetic model was derived based on Bercic rate. The parameters of this equation ...
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A computational fluid dynamic (CFD) study of methanol (MeOH) to dimethyl ether (DME) process in an adiabatic fixed-bed reactor is presented. One of the methods of industrial DME production is the catalytic dehydration of MeOH. Kinetic model was derived based on Bercic rate. The parameters of this equation for a specific catalyst were tuned by solving a one-dimensional homogenous model using MATLAB optimization module. A two-dimensional CFD simulation of the reaction is demonstrated and considered as numerical experiments. A sensitivity analysis was run in order to find the effect of temperature, pressure, and WHSV on the reactor performance. Good agreement was achieved between bench experimental data and the model. The results show that the maximum conversion of reaction (about 85.03%) is obtained at WHSV=10 h-1 and T=563.15 K, whereas the inlet temperature has a greater effect on methanol conversion. Moreover, the effect of water in inlet feed on methanol conversion is quantitatively studied. It was concluded that the results obtained from CFD analysis give precise guidelines for further studies on the optimization of reactor performance.
