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Liquid Propellant Mass Measurement in Microgravity

Kevin M. Crosby
Kevin M. Crosby
, 
Rudy J. Werlink
Rudy J. Werlink
 and 
Eric A. Hurlbert
Eric A. Hurlbert
   | Feb 26, 2021
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Article Category: Research Note
Published Online: Feb 26, 2021
Page range: 50 - 61
DOI: https://doi.org/10.2478/gsr-2021-0004
Keywords
© 2021 Kevin M. Crosby et al., published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Figure 1

The MPG concept. Surface waves excited on the tank wall induce acoustic resonances with frequencies that depend sensitively on the mass of liquid adhered to the wall. Modal analysis is used to detect mode shifts. MPG: Modal Propellant Gauging.
The MPG concept. Surface waves excited on the tank wall induce acoustic resonances with frequencies that depend sensitively on the mass of liquid adhered to the wall. Modal analysis is used to detect mode shifts. MPG: Modal Propellant Gauging.

Figure 2

Typical modes in a subscale cylindrical tank at liquid fill levels between 10% and 31% of full-tank volume. A frequency resolution of 1-Hz results in gauging resolutions of below 1.0%.
Typical modes in a subscale cylindrical tank at liquid fill levels between 10% and 31% of full-tank volume. A frequency resolution of 1-Hz results in gauging resolutions of below 1.0%.

Figure 3

MPG mass measurements on the Orion ESM qualification tank. The point data are instantaneous mass estimates produced by MPG using the cross-correlation method during a drain cycle. The solid line is the facility mass data during the drain. ESM: European service module; MPG: Modal Propellant Gauging.
MPG mass measurements on the Orion ESM qualification tank. The point data are instantaneous mass estimates produced by MPG using the cross-correlation method during a drain cycle. The solid line is the facility mass data during the drain. ESM: European service module; MPG: Modal Propellant Gauging.

Figure 4

NS payload experiment rendering. Three transparent, cylindrical tanks contain water at different fill levels. MPG sensors and data acquisition system record the modal response of each tank while cameras record the liquid motion during the flight. MPG: Modal Propellant Gauging; NS: New Shepard.
NS payload experiment rendering. Three transparent, cylindrical tanks contain water at different fill levels. MPG sensors and data acquisition system record the modal response of each tank while cameras record the liquid motion during the flight. MPG: Modal Propellant Gauging; NS: New Shepard.

Figure 5

Tanks 3 (Blue) and 1 (Green) imaged 25 s after CCSEP when surface interface motion along the tank wall had essentially stopped. The liquid in each tank, scrambled by the impulse of CCSEP, reached an equilibrium state with roughly half of the volume adhered to the top and half to the bottom of each tank. CCSEP: Crew Capsule Separation.
Tanks 3 (Blue) and 1 (Green) imaged 25 s after CCSEP when surface interface motion along the tank wall had essentially stopped. The liquid in each tank, scrambled by the impulse of CCSEP, reached an equilibrium state with roughly half of the volume adhered to the top and half to the bottom of each tank. CCSEP: Crew Capsule Separation.

Figure 6

The NS flight profile. Altitude above ground level (AGL) vs. mission elapsed time (MET) is shown for the P9 mission. Courtesy: Blue Origin. NS: New Shepard
The NS flight profile. Altitude above ground level (AGL) vs. mission elapsed time (MET) is shown for the P9 mission. Courtesy: Blue Origin. NS: New Shepard

Figure 7

Representative equilibrated, zero-g liquid distribution from CFD simulations of the experiment tank at T+30 s after initial impulse. Fill fraction is 12% of full-tank volume (524 ml). CFD: Computational fluid dynamics.
Representative equilibrated, zero-g liquid distribution from CFD simulations of the experiment tank at T+30 s after initial impulse. Fill fraction is 12% of full-tank volume (524 ml). CFD: Computational fluid dynamics.

Figure 8

Summary data for FE calculations, 1-g laboratory data, and P9 flight data. LMF as a function of fill fraction. The solid curves are 2-parameter best-fit lines with functional form described by Eq. (2). The fit parameters are A = 19.3 and b = 2.69. FE: Finite element; LMF: Lowest mode frequency.
Summary data for FE calculations, 1-g laboratory data, and P9 flight data. LMF as a function of fill fraction. The solid curves are 2-parameter best-fit lines with functional form described by Eq. (2). The fit parameters are A = 19.3 and b = 2.69. FE: Finite element; LMF: Lowest mode frequency.

Summary of MPG tests and results.

Experiment Hardware Platform Test conditions Gravity level % Error in LMF % Error in CC predicted fill volume (%)
MPG-I-III Subscale Pill-shaped COPV and transparent polycarbonate tanks Lab Settled static 1-g <1% 0.25%
Parabolic Sloshing 0-g 3–5% -
KSC Cold-Tank test Shuttle OMS tank Lab Settled slow drain and fill 1-g – <0.5%
Airbus Orion ESM tank qualification Orion ESM qualification tank Lab Settled slow drain and fill 1-g <1% 0.24%
Morpheus hot-fire 48-in diameter spherical propellant tanks Morpheus Prototype Lander 30-s vacuum hot-fire at the NASA Plumbrook Station B-1 Chamber 1-g – 0.12%
P9 Mission Subscale polycarbonate cylindrical tanks NS P9 Suborbital Flight 0-g <1% < 1%

Cross-correlation-predicted fill fraction and NS P9 known fill fractions.% Error is calculated from 100 x [Predicted Fill Volume – Known Fill Volume|/Total Tank Volume. The total tank volume is 4356 ml.

Tank Fill volume (ml) Fill fraction MPG CC predicted fill volume (ml) % Error in CC predicted fill volume (%)
Tank 1 1000 0.230 1025 0.57%
Tank 2 500 0.115 540 0.92%
Tank 3 1500 0.344 1485 0.34%
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