Abstract:This paper presents a model and an algorithm for the simulation of pipeline networks with compressible fluids. The model can predict pressures, flow rates, temperatures and gas compositions at any point of the network. Any network configuration can be simulated; the existence of cycles is not an obstacle. Numerical results from simulated data on a proposed network are shown for illustration. The potential of the simulator is explored by the analysis of a pressure relief network, using a stochastic procedure fo… Show more
“…The solution of the non-linear system both satisfies the head loss and continuity equations. This method was described in the works of Costa et al [8]. The simplified solution of the nodal equations is based on the linear theory method (LTM).…”
Gas turbine combustor performance was explored by utilizing a 1-D flow network model. To obtain the preliminary performance of combustion chamber, three different flow network solvers were coupled with a chemical reactor network scheme. These flow solvers were developed via simplified, segregated and direct solutions of the nodal equations. Flow models were utilized to predict the flow field, pressure, density and temperature distribution inside the chamber network. The network model followed a segregated flow and chemical network scheme, and could supply information about the pressure drop, nodal pressure, average temperature, species distribution, and flow split. For the verification of the model's results, analyses were performed using CFD on a seven-stage annular test combustor from TUSAS Engine Industries, and the results were then compared with actual performance tests of the combustor. The results showed that the preliminary performance predictor code accurately estimated the flow distribution. Pressure distribution was also consistent with the CFD results, but with varying levels of conformity. The same was true for the average temperature predictions of the inner combustor at the dilution and exit zones. However, the reactor network predicted higher elemental temperatures at the entry zones.
“…The solution of the non-linear system both satisfies the head loss and continuity equations. This method was described in the works of Costa et al [8]. The simplified solution of the nodal equations is based on the linear theory method (LTM).…”
Gas turbine combustor performance was explored by utilizing a 1-D flow network model. To obtain the preliminary performance of combustion chamber, three different flow network solvers were coupled with a chemical reactor network scheme. These flow solvers were developed via simplified, segregated and direct solutions of the nodal equations. Flow models were utilized to predict the flow field, pressure, density and temperature distribution inside the chamber network. The network model followed a segregated flow and chemical network scheme, and could supply information about the pressure drop, nodal pressure, average temperature, species distribution, and flow split. For the verification of the model's results, analyses were performed using CFD on a seven-stage annular test combustor from TUSAS Engine Industries, and the results were then compared with actual performance tests of the combustor. The results showed that the preliminary performance predictor code accurately estimated the flow distribution. Pressure distribution was also consistent with the CFD results, but with varying levels of conformity. The same was true for the average temperature predictions of the inner combustor at the dilution and exit zones. However, the reactor network predicted higher elemental temperatures at the entry zones.
“…Most of the literature on the analysis of gas networks focuses on the fluid-dynamics perspective, mainly oriented to assess flow rates and pressures across network elements [30,16,49]. Optimisation of operations has been addressed in various ways, notably to favour efficient integration within multi-carrier systems combining provisioning of electric and gas power [48,37,34,43].…”
The infrastructures used in cities to supply power, water and gas are consistently becoming more automated. As society depends critically on these cyber-physical infrastructures, their survivability assessment deserves more attention. In this overview, we first touch upon a taxonomy on survivability of cyber-physical infrastructures, before we focus on three classes of infrastructures (gas, water and electricity) and discuss recent modelling and evaluation approaches and challenges.
“…Boyd et al 8 have studied steady-state gas pipeline networks by modeling the compressor stations. Costa et al 9 have developed a steady-state gas pipeline simulation. Sung 10 have based their modeling approach on a hybrid network using minimum cost spanning tree.…”
Section: Previous Work Transmission Pipeline Modelingmentioning
in Wiley InterScience (www.interscience.wiley.com).As the gas industry has developed, gas pipeline networks have evolved over decades into very complex systems. A typical network today might consist of thousands of pipes, dozens of stations, and many other devices, such as valves and regulators. Inside each station, there can be several groups of compressor units of various vintages that were installed as the capacity of the system expanded. The compressor stations typically consume about 3-5% of the transported gas. It is estimated that the global optimization of operations can save considerably the fuel consumed by the stations. Hence, the problem of minimizing fuel cost is of great importance. Consequently, the objective is to operate a given compressor station or a set of compressor stations so that the total fuel consumption is reduced while maintaining the desired throughput in the line. Two case studies illustrate the proposed methodology. Case 1 was chosen for its simple and small-size design, developed for the sake of illustration. The implementation of the methodology is thoroughly presented and typical results are analyzed. Case 2 was submitted by the French Company Gaz de France. It is a more complex network containing several loops, supply nodes, and delivery points, referred as a multisupply multidelivery transmission network. The key points of implementation of an optimization framework are presented. The treatment of both case studies provides some guidelines for optimization of the operating performances of pipeline networks, according to the complexity of the involved problems. V V C 2009 American Institute of Chemical Engineers AIChE J, 56: 946-964, 2010
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