Chapter 7: Dissertation Accomplishments and Future Work
7.2 Future Work
The ultimate goal of NASA fire characterization research is the design of the next generation
of smoke detectors and post-fire cleanup equipment. GASP laboratory will continue to be the
center of research, testing and instrument validation toward that end.
A goal for future GASP testing is to add surface area concentration measurement capability to
determine the value of this metric for environmental monitoring and/or fire detection in
spacecraft. While surface area concentration is not an intuitive quantity, it can be correlated to
health effects of aerosols by conversion to Lung Deposited Surface Area (LDSA). Several
portable diffusion charging instruments are commercially available which measure LDSA
concentration (Asbach et al. 2012). Understanding the surface area concentrations of smoke
from the various fuels can give insight into a potential second moment device in a suite of
moment instruments for fire detection. Furthermore, LDSA could be a valuable metric for
ambient aerosol monitoring in the spacecraft cabin with regards to crew health.
The next generation technology for fire suppression on space missions is a portable water mist
fire extinguisher which is under development (Rodriguez and Young, 2013). The introduction of
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will entail incorporating different levels of humidity in smoke tests, not only for the purpose of
promoting acid gas production, as mentioned in chapter 3 (Babushok et al. 2015), but also to
determine the effects on aerosol measurements and the performance of the aerosol monitor that
will ultimately be used to characterize the post-fire environment. In addition to varying levels of
humidity in the GASP smoke chamber, experiments will be performed to characterize acid gas
and aerosol concentrations in the smoke chamber before and after the introduction of water mist.
There is potential for the water mist extinguisher to ‘clean’ the post-fire environment and experiments are planned to determine the affinity of the water droplets for the acid gases and
particles. This will shed light on the cleanup process for the water introduced for fire
suppression and the potential for corrosive damage to spacecraft infrastructure by the water
(Peacock et al. 2012)
While most of the ISS is at ambient temperature and pressure for the comfort of the crew,
airlocks have protocols for different conditions for the purpose of preventing decompression
sickness before and after space walks or extra-vehicular activity (EVA) in pressurized space
suits. The airlock pressure is reduced to 70.3 kPa (from 101 kPa) with varying oxygen levels
over a period of time (Anderson et al. 2015). Understanding the implications of the altered
environment on fire signatures and smoke detection is a question that will be addressed in future
GASP testing.
Further testing is planned to evaluate smoke removal technologies, such as the Soft-X-Ray-
Enhanced Electrostatic Precipitator (Kettleson et al. 2013) in the GASP smoke chamber. The
reduction in aerosol concentrations will be measured and compared for the various spacecraft
fuels. Size-dependent removal efficiency will be noted, particularly for Teflon smoke particles
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An aerosol sampling experiment has been proposed for the ISS and has recently been funded
by the NASA Advanced Exploration Systems Program. This will validate and update the ISS
aerosol inventory documented in chapter 6. Both active thermophoretic sampling and passive
sampling (directly on microscopy substrates) will be performed by the astronauts in different ISS
modules and samples will be returned to Earth for microscopic analyses. Resulting data will
include the following data: average number concentration, mass concentration (PM10, PM2.5),
size distribution, morphology, and elemental composition of airborne particles. This will
provide important information for the down-selection of appropriate aerosol monitoring devices
for future manned space missions, and knowledge of background aerosols will contribute to
smoke detection systems that are resistant to false alarms.
7.3 References
Anderson, M.S., Ewert, M.K., Keener, J.F., Wagner, S.A. (2015) Life support Baseline Values and Assumptions Document, NASA Technical Publication, NASA/TP-2015-218570, NASA Johnson Space Center, Houston, Texas.
Asbach, C., Kaminski, H., von Barany, D., Kuhlbusch, T.A., Monz, C., Dziurowitz, N., Pelzer, J., Vossen, K., Berlin, K., Dietrich, S., Götz, U., Kiesling, H.J., Schierl, R., Dahmann, D. (2012) Comparability of portable nanoparticle exposure monitors, Ann. Occup. Hyg., Vol. 56, No. 5, pp. 606–621.
Babushok, V.I., Linteris, G.T., Baker, P.T. (2015) Influence of water vapor on hydrocarbon combustion in the presence of hydrofluorocarbon agents, Combustion and Flame 162 pp. 2307- 2310.
Kettleson, E.M., Schriewer, J.M., Buller, R.M.L., Biswas, P. (2013) Soft-X-Ray-Enhanced Electrostatic Precipitation for Protection against Inhalable Allergens, Ultrafine Particles, and Microbial Infections. Appl. Environ. Microbiol. Vol. 79 No. 4, pp. 1333-1341.
Meyer, M.E., Mulholland, G. W., Bryg, V., Urban, D. L., Yuan, Z., Ruff, G. A., Cleary, T., and Yang, J. (2015). Smoke Characterization and Feasibility of the Moment Method for Spacecraft Fire Detection. Aerosol Sci. Tech., 49(5):299–309.
Peacock, R.D., Cleary, T.G., Reneke, P.A., Murphy, D.C. A Literature Review of the Effects of
Smoke from a Fire on Electrical Equipment. NUREG/CR-7123, Office of Nuclear Regulatory
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Rodriquez, B., Young, G. (2013). Development of the International Space Station Fine Water Mist Portable Fire Extinguisher, 43rd International Conference on Environmental Systems, American Institute of Aeronautics and Astronautics (AIAA), Vail, Colorado, July, 2013, 1-8.
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Appendix A: Numerical Modeling of a Unipolar Corona-
based Aerosol Charger
A1 Introduction
Particle charging is an important phenomenon in the field of aerosol science and technology. It
is the basis for particle sensing and measurement in the differential mobility analyzer. One
limitation of this instrument is that the quality of data depends on the accurate characterization of
the charge state of the aerosol, which is an input in the inversion algorithm that corrects for
multiply charged particles. Knowing the resulting charge distribution of a charger is an
important step in the deconvolution of data to provide the final particle size distribution in
electrical mobility classifying instruments (Hogan et al. 2009). Furthermore, attaining a high
particle charging efficiency for particles in the nanometer range is very challenging
(Wiedensohler et al. 1994). Increasing charging efficiency and accurately characterizing the
final charged state of an aerosol is an important research pursuit that can be approached through
numerical modeling and simulation. Unipolar diffusion charging most often employs a corona
discharge that provides an abundant source of ions that collide with particles, imparting charge
on them (Hinds, 1999). A numerical model of a particle charger is a useful tool for
parametrically studying charger design variables and improving charging efficiency. A review
of unipolar chargers for nanoparticle charging by Intra and Tippayawong (2011) outlines the
need for numerical modeling of particle charging. Specifically, they recommend numerical
investigation on phenomena affecting charging performance, such as non-ideal flow fields,
electric field lines or alignment of the components within the charger. Furthermore, they assert
that improvements in nanoparticle charging can be realized by investigating particle residence
times in the charger, including characterizing residence time distributions. For detailed
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transport (ions, neutral particles and charged particles with different charge levels), the electric
field present in the charger and the birth and death equations for particle charging. Most models
are not based on detailed modeling of charger geometry, but rather generalize a constant ion
concentration and particle residence time product (known as Niont) which is a non-physical
assumption often created to fit the experimental data. Often this type of model does not correlate
to experimental charge distribution measurements, which is the case for the charger under the
current investigation (Qi et al. 2008). Even if the Ni were relatively constant, the residence time
of a particle in the charger, t, can vary significantly, depending on the charger geometry and flow
field. The unique feature of this charger modeling approach is the use of location-specific ion
concentration within the charger and neutral and charged particle trajectories to determine the
aerosol charge distribution with the birth and death equations. This level of fidelity takes into
account details which affect the final charging efficiency, such as non-uniform ion concentration,
or flow patterns resulting in a distribution of particle residence times within the charger. The
charger to which this model is applied is a mini-charger used in a personal particle sizer (Qi et al.
2008), shown in Figure A1. The numerical modeling effort to characterize this charger was
funded by NASA’s Advanced Exploration Systems (AES) Fire Safety Project, as it was under consideration for use in future spacecraft fire detection systems. This charger, along with a
miniature electrostatic classifier, was a candidate aerosol instrument for use in low gravity;
however, it has been overcome by events, and is not currently planned for use by the AES
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Figure A1: Mini-charger Design (Qi et al. 2009)
In the interest of documenting the modeling effort, this appendix gives pertinent information on
the aerosol physics, charging model, equations and a complete description of the unique charging
algorithm, along with preliminary results. Suggestions for future work that will improve and
apply the charger model is also described.
A2 Physical Properties Considered in Detailed Charger Model
Aerosols are particles suspended in a gas, therefore both the gas and particle phases must be
accurately described in theoretical detail in order to capture their behavior in a numerical model.
Modeling an aerosol charger requires additional information on the ions, their properties and
charging theories. This section gives an overview of the aerosol physics and electrostatic effects
necessary for modeling the unipolar charging process.
A2.1 Fluid Properties
Although fluids consist of discrete molecules, they can be assumed to have continuous
properties at certain length scales.
A2.1.1 Properties of Air
Kinetic theory postulates that air molecules are continually colliding with one another in a