3 resultados para Gas pipes

em QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast


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This note presents a simple model for prediction of liquid hold-up in two-phase horizontal pipe flow for the stratified roll wave (St+RW) flow regime. Liquid hold-up data for horizontal two-phase pipe flow [1, 2, 3, 4, 5 and 6] exhibit a steady increase with liquid velocity and a more dramatic fall with increasing gas rate as shown by Hand et al. [7 and 8] for example. In addition the liquid hold-up is reported to show an additional variation with pipe diameter. Generally, if the initial liquid rate for the no-gas flow condition gives a liquid height below the pipe centre line, the flow patterns pass successively through the stratified (St), stratified ripple (St+R), stratified roll wave, film plus droplet (F+D) and finally the annular (A+D, A+RW, A+BTS) regimes as the gas rate is increased. Hand et al. [7 and 8] have given a detailed description of this progression in flow regime development and definitions of the patterns involved. Despite the fact that there are over one hundred models which have been developed to predict liquid hold-up, none have been shown to be universally useful, while only a handful have proven to be applicable to specific flow regimes [9, 10, 11 and 12]. One of the most intractable regimes to predict has been the stratified roll wave pattern where the liquid hold-up shows the most dramatic change with gas flow rate. It has been suggested that the momentum balance-type models, which give both hold-up and pressure drop prediction, can predict universally for all flow regimes but particularly in the case of the difficult stratified roll wave pattern. Donnelly [1] recently demonstrated that the momentum balance models experienced some difficulties in the prediction of this regime. Without going into lengthy details, these models differ in the assumed friction factor or shear stress on the surfaces within the pipe particularly at the liquid–gas interface. The Baker–Jardine model [13] when tested against the 0.0454 m i.d. data of Nguyen [2] exhibited a wide scatter for both liquid hold-up and pressure drop as shown in Fig. 1. The Andritsos–Hanratty model [14] gave better prediction of pressure drop but a wide scatter for liquid hold-up estimation (cf. Fig. 2) when tested against the 0.0935 m i.d. data of Hand [5]. The Spedding–Hand model [15], shown in Fig. 3 against the data of Hand [5], gave improved performance but was still unsatisfactory with the prediction of hold-up for stratified-type flows. The MARS model of Grolman [6] gave better prediction of hold-up (cf. Fig. 4) but deterioration in the estimation of pressure drop when tested against the data of Nguyen [2]. Thus no method is available that will accurately predict liquid hold-up across the whole range of flow patterns but particularly for the stratified plus roll wavy regime. The position is particularly unfortunate since the stratified-type regimes are perhaps the most predominant pattern found in multiphase lines.

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Natural gas (NG) network and electric network are becoming tightly integrated by microturbines in the microgrid. Interactions between these two networks are not well captured by the traditional microturbine (MT) models. To address this issue, two improved models for single-shaft MT and split-shaft MT are proposed in this paper. In addition, dynamic models of the hybrid natural gas and electricity system (HGES) are developed for the analysis of their interactions. Dynamic behaviors of natural gas in pipes are described by partial differential equations (PDEs), while the electric network is described by differential algebraic equations (DAEs). So the overall network is a typical two-time scale dynamic system. Numerical studies indicate that the two-time scale algorithm is faster and can capture the interactions between the two networks. The results also show the HGES with a single-shaft MT is a weakly coupled system in which disturbances in the two networks mainly influence the dc link voltage of the MT, while the split-shaft MT is a strongly coupled system where the impact of an event will affect both networks.