Your email was sent successfully. Check your inbox.

An error occurred while sending the email. Please try again.

Proceed reservation?

Export
  • 1
    Online Resource
    Online Resource
    ASME International ; 2020
    In:  Journal of Turbomachinery Vol. 142, No. 12 ( 2020-12-01)
    In: Journal of Turbomachinery, ASME International, Vol. 142, No. 12 ( 2020-12-01)
    Abstract: In this article, a numerical model of the full surge cycle is presented for the low-speed centrifugal blower and compared with the experiment. Surge phenomenon is very dangerous for the compressor operation. Therefore, the possibility of studying its physics experimentally is strongly limited. The application of numerical methods allows one to safely analyze surge physics without causing risks to the operating crew. This article presents a description of the applied numerical method and exhaustive analysis of the flow structures observed at consecutive stages of the surge cycle. The surge is known to be very difficult to be simulated due to large timescale and region of influence. This study also shows the importance of an appropriate choice of the simulation definition and the boundary conditions. The presented method allows gathering information about features such as the regions of flow reversal, pressure distributions, pressure rise, cycle frequency, and others. All the aforementioned information provides important input to the efficient antisurge system design. The model has been validated by a comparison with the experimental data. Thanks to simulation, standardized antisurge solutions could be possibly replaced with more efficient protection schemes tailored to a given machine.
    Type of Medium: Online Resource
    ISSN: 0889-504X , 1528-8900
    Language: English
    Publisher: ASME International
    Publication Date: 2020
    detail.hit.zdb_id: 56356-0
    detail.hit.zdb_id: 2010462-5
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
Close ⊗
This website uses cookies and the analysis tool Matomo. Further information can be found on the KOBV privacy pages