Characterization of the Flow and Surface Pressure Fields of an Oscillating Fence Actuator

The high-speed train interior noise induced by the exterior flow field is one of the critical issues for product developers to consider during design. The reliable numerical prediction of noise in a passenger cabin due to exterior flow requires the decomposition of surface pressure fluctuations into the hydrodynamic (incompressible) and the acoustic (compressible) components, as well as the accurate computation of the near aeroacoustic field, since the transmission characteristics of incompressible and compressible pressure waves through the wall panel of the cabin are quite different from each other. In this paper, a systematic numerical methodology is presented to obtain separate incompressible and compressible surface pressure fields in the wavenumber–frequency and space–time domains. First, large eddy simulation techniques were employed to predict the exterior flow field, including a highly-resolved acoustic near-field, around a high-speed train running at the speed of 300 km/h in an open field. Pressure fluctuations on the train surface were then decomposed into incompressible and compressible fluctuations using the wavenumber–frequency analysis. Finally, the separated incompressible and compressible surface pressure fields were obtained from the inverse Fourier transform of the wavenumber–frequency spectrum. The current method was illustratively applied to the high-speed train HEMU-430X running at a speed of 300 km/h in an open field. The results showed that the separate incompressible and compressible surface pressure fields in the time–space domain could be obtained together with the associated aerodynamic source mechanism. The power levels due to each pressure field were also estimated, and these can be directly used for interior noise prediction.

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Aspects of the use of proper orthogonal decomposition of surface pressure fields

Wind and Structures ◽

10.12989/was.2000.3.2.097 ◽

2000 ◽

Vol 3 (2) ◽

pp. 97-115 ◽

Cited By ~ 28

Author(s):

C.J. Baker

Keyword(s):

Proper Orthogonal Decomposition ◽

Surface Pressure ◽

Orthogonal Decomposition ◽

Pressure Fields ◽

Proper Orthogonal

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Characterization of Pressure Fields of Focused Transducers at TÜBİTAK UME

Physics Procedia ◽

10.1016/j.phpro.2015.08.276 ◽

2015 ◽

Vol 70 ◽

pp. 1241-1245 ◽

Cited By ~ 2

Author(s):

B. Karaböce ◽

A. Şahin ◽

A.T. İnce ◽

Y. Skarlatos

Keyword(s):

Pressure Fields ◽

Focused Transducers

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Construction of Marine Surface Pressure Fields from Scatterometer Winds Alone

Journal of Applied Meteorology ◽

10.1175/1520-0450(1997)036<1249:comspf>2.0.co;2 ◽

1997 ◽

Vol 36 (9) ◽

pp. 1249-1261 ◽

Cited By ~ 14

Author(s):

Carol S. Hsu ◽

Morton G. Wurtele ◽

Glenn F. Cunningham ◽

Peter M. Woiceshyn

Keyword(s):

Surface Pressure ◽

Pressure Fields ◽

Marine Surface

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Classification of surface atmospheric pressure fields in the Laptev and East Siberian seas

Arctic and Antarctic Research ◽

10.30758/0555-2648-2021-67-4-394-405 ◽

2021 ◽

Vol 67 (4) ◽

pp. 394-405

Author(s):

V. S. Porubaev ◽

L. N. Dyment

Keyword(s):

Surface Pressure ◽

Atmospheric Pressure ◽

Ice Cover ◽

The Arctic ◽

Wind Fields ◽

Arctic Seas ◽

Pressure Fields ◽

Ice Drift ◽

Waves And Currents

The need for classifying surface atmospheric pressure fields over the Arctic seas arose as a method was being developed for predicting the characteristics of discontinuities (leads) in the sea ice cover. Wind, which is determined by the atmospheric pressure field, acts on the ice cover and causes it to drift. Leads are formed in the ice cover due to the irregularity of ice drift. Ice drift can be caused by several factors, such as skewed sea level, tidal waves and currents. However, the main cause of ice drift in the Arctic seas is wind. Each typical field of surface atmospheric pressure corresponds to a certain field of leads in the ice cover. This makes it possible to predict the characteristics of leads in the ice cover by selecting fields similar to predictive fields of atmospheric pressure based on archived data.The variety of atmospheric pressure fields makes it difficult to find an analogue to a given field by simply going through all the corresponding data available in the electronic archive. Classification of atmospheric pressure fields makes it possible to simplify the process of selecting an analogue.To develop the classification, we used daily surface pressure maps at 00 hours GMT for the cold seasons (from mid- October to the end of May) 2016–2021. The atmospheric pressure fields, which were similar in configuration, and hence the wind fields, belonged to the same type. In total, 27 types were identified, applicable both to the Laptev Sea and the East Siberian Sea. Within one type, a division into subtypes was made, depending on the speed of the geostrophic wind.The wind intensity was estimated by the number of isobars multiples of 5 mb on the surface atmospheric pressure map. All the surface pressure fields observed over the waters of the Laptev and East Siberian Seas over the past 5 years have been assigned to one of the types identified using cluster analysis. Each type of atmospheric pressure within the framework of the forecasting method being developed is supposed to correspond to a field of discontinuities in the ice cover.

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Physicochemical Characterization of Tetraether Lipids from Thermoplasma acidophilum. II. Film Balance Studies on the Monomolecular Organization of the Main Glycophospholipid in Monofilms

Zeitschrift für Naturforschung C ◽

10.1515/znc-1985-3-414 ◽

1985 ◽

Vol 40 (3-4) ◽

pp. 219-222 ◽

Cited By ~ 21

Author(s):

Christoph Strobl ◽

Lambert Six ◽

Klaus Heckmann ◽

Birgit Henkel ◽

Klaus Ring

Keyword(s):

Surface Pressure ◽

High Surface ◽

Physicochemical Characterization ◽

Thermoplasma Acidophilum ◽

Alkyl Chains ◽

Head Groups ◽

Air Water Interface ◽

Tetraether Lipids ◽

High Surface Pressure

The bipolar main tetraether lipid (MPL) of Thermoplasma acidophilum has been shown to form typical liquid expanded films at the air-water interface. The limiting molecular area at the collaps pressure is approximately Ac=73 Å2 per molecule. Monopolar aiphytanyl diether lipids were found to occupy the same area at high surface pressure as MPL. Thus, it was concluded that in the monofilm only one of the two polar headgroups of the MPL molecules is hydrated, i.e. that the single MPL molecules arc oriented upright. The packing properties of MPT. in the monofilm are determined by the properties of the branched alkyl chains only; the polar head groups do not contribute to the space requirement in the film. The collaps pressure of the MPL film is approximately 39 mN m-1 at 8°C. At a surface pressure of π = 30 mN m-1 and 20 °C the film is stable for many hours.

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An Evaluation of Scatterometer-Derived Oceanic Surface Pressure Fields

Journal of Applied Meteorology and Climatology ◽

10.1175/2007jamc1683.1 ◽

2008 ◽

Vol 47 (3) ◽

pp. 835-852 ◽

Cited By ~ 14

Author(s):

Jérôme Patoux ◽

Ralph C. Foster ◽

Robert A. Brown

Keyword(s):

Boundary Layer ◽

Planetary Boundary Layer ◽

Surface Pressure ◽

Weather Prediction ◽

Layer Model ◽

Boundary Layer Model ◽

Pressure Fields ◽

Oceanic Surface ◽

The Tropics ◽

Planetary Boundary Layer Model

Abstract Oceanic surface pressure fields are derived from the NASA Quick Scatterometer (QuikSCAT) surface wind vector measurements using a two-layer similarity planetary boundary layer model in the midlatitudes and a mixed layer planetary boundary layer model in the tropics. These swath-based surface pressure fields are evaluated using the following three methods: 1) a comparison of bulk pressure gradients with buoy pressure measurements in the North Pacific and North Atlantic Oceans, 2) a least squares difference comparison with the European Centre for Medium-Range Weather Forecasts (ECMWF) surface pressure analyses, and 3) a parallel spectral analysis of the QuikSCAT and ECMWF surface pressure fields. The correlation coefficient squared between scatterometer-derived pressure fields and buoys is found to be R2 = 0.936. The average root-mean-square difference between the scatterometer-derived and the ECMWF pressure fields ranges from 1 to 3 hPa, depending on the latitude and season, and decreases after the assimilation of QuikSCAT winds in the ECMWF numerical weather prediction model. The spectral components of the scatterometer-derived pressure fields are larger than those of ECMWF surface analyses at all scales in the midlatitudes and only at shorter wavelengths in the tropics.

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