Search results

Filters

  • Journals
  • Authors
  • Keywords
  • Date
  • Type

Search results

Number of results: 5
items per page: 25 50 75
Sort by:
Download PDF Download RIS Download Bibtex

Abstract

The two dimensional steady and unsteady flow field at midspan in a low speed axial flow compressor stage has been investigated experimentally, using two systems, based on totally different principles: a 2-sensor fast response straight and 90° triple split fiber probes (TSFP) and two dimensional LOA system with an emphasis on the interaction of the inlet guide vane (IGY) wake with the rotor flow field. To account for the uniformity of the rotor absolute inlet flow field, measurements has been made at eight tangential locations in the absolute frame equally spaced over one IGY pitch. The time resolved investigation, done by TSFP and LOA allows to presenting velocity fields, flow angles and turbulence data at different [GY-rotor positions during one blade passing period. The velocity measurements are decomposed into a time averaged velocity, a periodic velocity component and a unresolved velocity component. Using two measurement systems, one being intrusive and the other non-intrusive, in the same complex flow field, gives the opportunity for a critical comparison of results and opens the view for further improvements. Averaging these results, enabled also comparison with the pneumatic five-hole probe measurement.
Go to article

Authors and Affiliations

Andrzej Witkowski
Mirosław Majkut
Download PDF Download RIS Download Bibtex

Abstract

Casing treatment in the form of circumferential grooves over a rotor blade tips is used for improvement of an axial compressor performance. Usually, these grooves extend compressor’s stall range (stable operational range) but decrease its efficiency. In the paper, there are presented main results of investigations on grooves that influence positively efficiency of compressor. There were investigated traditional (typical) and newly developed groove configurations. Certain grooves combine increase in efficiency with extension in stall range.

Go to article

Authors and Affiliations

Vitaliy Nezym
Download PDF Download RIS Download Bibtex

Abstract

The development of a reliable mathematical model of an axial compressor requires applying flow and efficiency characteristics. This approach provides performance parameters of a machine depending on varying conditions. In this paper, a method for developing characteristics of an axial compressor is presented, based on general compressor maps available in the literature or measurement data from industrial facilities. The novelty that constitutes the core of this article is introducing an improved method describing the performance lines of an axial compressor with the modified ellipse equation. The proposed model is extended with bleed air extraction for the purposes of cooling the blades in the expander part of the gas turbine. The variable inlet guide vanes angle is also considered using the vane angle correction factor. All developed dependencies are fully analytical. The presented approach does not require knowledge of machine geometry. The set of input parameters is based on reference data. The presented approach makes it possible to determine the allowed operating area and study the machine’s performance in variable conditions. The introduced mathematical correlations provide a fully analytical study of optimum operating points concerning the chosen criterion. The final section presents a mathematical model of an axial compressor built using the developed method. A detailed study of the exemplary flow and efficiency characteristics of an axial compressor operating with a gas turbine is also provided.
Go to article

Bibliography

[1] Plis M.: Mathematical modeling of an axial compressor in a gas turbine system. J. Power Technol. 96(2016), 3, 194–199.
[2] Badyda K., Miller A.: Power Gas Turbines and Systems with Their Application. Kaprint, Lublin 2014 (in Polish).
[3] Kehlhofer R., Rukes B., Hennemann F., Stirnimann F.: Combined-Cycle Gas and Steam Turbine Power Plants. PennWell, Tusla 2009.
[4] Boyce M.P.: Gas Turbine Engineering Handbook. Butterworth-Heinemann, Houston 2011.
[5] Kotowicz J.: The current state and prospects of development of gas-steam systems. Arch. Energ. 42(2012), 1 23–28, (in Polish).
[6] Horlock J.H.: Advanced Gas Turbine Cycles. Pergamon, Kidlington 2013.
[7] Tsoutsanis E., Li Y. G., Pilidis P., Newby M.: Part-load performance of gas turbines: Part I: – A novel compr/essor map generation approach suitable for adaptive simulation. In: Proc. ASME Gas Turbine India Conf., Mumbai, 1 Dec. 2012, GTINDIA2012-9580, 733–742.
[8] Tsoutsanis E., Meskin N., Benammar M., Khashayar K.: A component map tuning method for performance prediction and diagnostics of gas turbine compressors. Appl. Energ. 135(2014), 572–585.
[9] Giampaolo A.J.: Gas Turbine Handbook: Principles and Practices. Fairmont CRC / Taylor&Francis, Lilburn Boca Raton 2006.
[10] Eckert B.: Axial and Radial Compressors. PWT, Warszawa 1959 (in Polish).
[11] Saravanamuttoo H.I.H.: Gas Turbine Theory. Pearson/Prentice Hall, Harlow 2009.
[12] Kalman D.: The most marvelous theorem in mathematics. J. Online Math. Appl. 8(2008).
[13] Halir R., Flusser J.: Numerically stable direct least squares fitting of ellipses. In: Proc. 6th Int. Conf. Central Europe on Computer Graphics and Visualization, Plzen, 1998, 125–132
[14] https://www.solver.com/excel-solver-grg-nonlinear-solving-method-stopping-conditions (accessed 27 May 2021).
[15] Perycz S.: Steam and Gas Turbines. Ossolineum, Wydawn. IMP PAN, Wrocław 1992 (in Polish).
[16] Trawinski P.: Development of real gas model operating in gas turbine system in Python programming environment. Arch. Thermodyn. 41(2020), 4, 23–61.
Go to article

Authors and Affiliations

Paweł Trawiński
1

  1. Institute of Heat Engineering, Warsaw University of Technology, Nowowiejska 21/25, 00-665, Warsaw, Poland
Download PDF Download RIS Download Bibtex

Abstract

In the presented paper, two different meshing strategies are compared to show the accuracy advantage of properly constructed mesh. For this purpose, it was necessary to automatize simulation process, in order to perform a number of calculations without the necessity of user interaction. Later, a method of results extrapolation as well as a way of judging mesh quality are introduced for more throughout comparison of presented discretization strategies. The latter method, called grid convergence index, is also used to calculate probability range of accurate result. To conclude, outcomes of this study are in agreement with general opinon on pracitces for an accurate CFD result. Structured O-type mesh with refinement at wall boundaries (often referred to as “inflation layers”) performs better than simple free mesh.
Go to article

Authors and Affiliations

Adam Tater
1
ORCID: ORCID
Pavel Mačák
1
Patrik Kovář
1

  1. Center of Aviation and Space Research, Faculty of Mechanical Engineering, Czech Technical University in Prague, Jugoslávských partyzán˚u1580/3, 16000, Prague 6, Czech Republic
Download PDF Download RIS Download Bibtex

Abstract

The paper presents a research program carried out to improve understanding of the fluid dynamics mechanisms that lead to rotating stall in the axial flow low speed compressor stage. The stalling behavior of this compressor stage was studied by measuring unsteady casing pressure by means of a circumferentially and axially spaced array of high frequency pressure transducers. Another probe used was a disc static pressure probe, with the pressure transducer, for in-flow and out-flow measurements along the blade span. It was expected that understanding of the fluid dynamics will facilitate at least two important tasks. The first was to accurately predict of when and how a particular compressor would stall. The second was to control, delay, or eventually suppress the rotating stall and surge. In consequence, one could extend the useful operating range of the axial compressor. Another motivation for the research was to compare the results from the three applied analysis techniques by using a single stall inception event. The first one was a simple visual inspection of the traces, which brought about a very satisfactory effect. The second one was application of spatial Fourier decomposition to the analysis of stall inception data, and the third method of analysis consisted in application of wavelet filtering in order to better understand the physical mechanisms which lead to rotating stall. It was shown that each of these techniques would provide different information about compressor stall behavior, and each method had unique advantages and limitations.

Go to article

Authors and Affiliations

Marcin Ziach
Mirosław Majkut
Andrzej Witkowski

This page uses 'cookies'. Learn more