Contamination modeling provides important insights into the transport mechanisms among sources, sinks, and sensitive surfaces. It is an indispensable tool in the discipline of contamination control and is often used to predict the outcome of a contamination event. As problems in contamination control can span multiple flow regimes and types of contaminants, it is important to develop such capability using a versatile tool. The Open source Field Operation and Manipulation (OpenFOAM) open source software is a customizable numerical solver that provides a solid foundation for the development of contamination modeling capability. It is a computational fluid dynamics tool that over the years has added particle tracing capabilities rendering it extremely versatile for transport modeling. In this paper, we show how OpenFOAM can be modified for modeling particulates settling under a flow field and molecular flow under the space vacuum environment. We show how new boundaries are created to simulate sources and vents and the accumulation of contaminants on surfaces over time. Finally, we discuss performance of OpenFOAM using our load-balanced Atlas Cluster on a computational intensive simulation.
Contamination control plays an important role in sustaining spacecraft performance. One spacecraft degradation mechanism involves long-term on-orbit molecular outgassing from spacecraft materials. The outgassed molecules may accumulate on thermal control surfaces and/or optics, causing degradation. In this study, we performed outgassing measurements of multiple spacecraft materials, including adhesives, Nylon Velcro, and other assembly materials through a modified ASTM E595 test method. The modified ASTM E595 test had the source and receiver temperature remained at 125°C and 25°C, respectively, but with prolonged outgassing periods of two weeks. The condensable contaminants were analyzed by Fourier Transform Infrared Spectroscopy (FTIR) and Gas Chromatography/Mass Spectrometry (GC/MS) to determine their spectral transmission and chemical composition. The FTIR spectra showed several spacecraft materials, primarily adhesives and potting materials, exhibiting slight absorption from contaminants consisting of hydroxyl groups and carboxylic acids. To gain insight into molecular contaminant transport, simulations were conducted to characterize contaminant accumulation inside a hypothetical space system cavity. The simulation indicated that contaminant molecules bouncing inside the hypothetical payload cavity can lead to deposition on colder surfaces, even though large openings are available to provide venting pathways for escaping to space. The newly established molecular contaminant transport simulation capability holds the promise of providing quantitative guidance for future spacecraft and its venting design.
The notion of percent area coverage (PAC) has been used to characterize surface cleanliness levels in the spacecraft contamination control community. Due to the lack of detailed particle data, PAC has been conventionally calculated by multiplying the particle surface density in predetermined particle size bins by a set of coefficients per MIL-STD-1246C. In deriving the set of coefficients, the surface particle size distribution is assumed to follow a log-normal relation between particle density and particle size, while the cross-sectional area function is given as a combination of regular geometric shapes. For particles with irregular shapes, the cross-sectional area function cannot describe the true particle area and, therefore, may introduce error in the PAC calculation. Other errors may also be introduced by using the lognormal surface particle size distribution function that highly depends on the environmental cleanliness and cleaning process. In this paper, we present PAC measurements from silicon witness wafers that collected fallouts from a fabric material after vibration testing. PAC calculations were performed through analysis of microscope images and compare them to values derived through the MIL-STD-1246C method. Our results showed that the MIL-STD-1246C method does provide a reasonable upper bound to the PAC values determined through image analysis, in particular for PAC values below 0.1.
KEYWORDS: Molecules, Contamination, Monte Carlo methods, Particles, Systems modeling, Space telescopes, Telescopes, Argon, Optical components, Instrument modeling
We present a finite element model for the prediction of molecular contamination through narrow pathways in a hypothetical spaceborne instrument using the commercially available COMSOL Multiphysics software. The free molecular flow module of COMSOL uses the angular coefficient method as an alternative to particle based methods. In the angular coefficient method, the microscopic dynamical aspect of the material transport problem is reduced to a macroscopic problem by calculating emission and incident fluxes at each surface rather than the trajectories of individual molecules. The model was validated by comparing the simulated and experimentally measured pressure differential between two chambers separated by a mechanical test structure. The mechanical test structure was designed to exhibit narrow pathways with characteristic size that can be found on spaceborne optomechanical structures. It is shown that materials can slowly migrate through these pathways in a spaceborne instrument to cause noticeable performance degradation within a time scale of a few months. The model for material transport through the test structure was also verified using a stochastic method. To simulate water infiltration through narrow pathways of a hypothetical spaceborne instrument, nominal payload temperature profile was used in addition to setting empirical input parameters such as the desorption energy of water and the outgassing rate of water from multilayer insulator thermal blankets to the appropriate surfaces in the modeling domain. The rate of growth of ice films on low temperature optical components and how optical performance can be degraded over time are discussed in this paper.
We present parallel algorithms for fast subpixel detection of targets in hyperspectral imagery produced by our
Hyperspectral Airborne Tactical Instrument (HATI-2500). The HATI-2500 hyperspectral imaging system has a
blue-enhanced visible-near-IR (VNIR) and a full short-wave IR (SWIR) range response from 400 to 2500 nm.
It has an industry-leading spectral resolution that ranges from 6 nm down to 1.5 nm in the VNIR region.
The parallel detection algorithm selected for processing the hyperspectral data cubes is based on the adaptive
coherence/cosine estimator (ACE). The ACE detector is a robust detector that is built upon the theory of generalized
likelihood ratio testing (GLRT) in implementing the matched subspace detector to unknown parameters
such as the noise covariance matrix. Subspace detectors involve projection transformations whose matrices can
be efficiently manipulated through multithreaded massively parallel processors on modern graphics processing
units (GPU). The GPU kernels developed in this work are based on the CUDA computing architecture. We
constrain the detection problem to a model with known target spectral features and unstructured background.
The processing includes the following steps: 1) scale and offset applied to convert the data from digital numbers
to radiance values, 2) update the background inverse covariance estimate in a line-by-line manner, and 3) apply
the ACE detector for each pixel for binary hypothesis testing. As expected, the algorithm is extremely effective
for homogeneous background, such as open desert areas; and less effective in mixed spectral regions, such as
those over urban areas. The processing rate is shown to be faster than the maximum frame rate of the camera
(100 Hz) with a comfortable margin.
We present real-time 3D image processing of flash ladar data using our recently developed GPU parallel processing
kernels. Our laboratory and airborne experiences with flash ladar focal planes have shown that per laser flash, typically
only a small fraction of the pixels on the focal plane array actually produce a meaningful range signal. Therefore, to
optimize overall data processing speed, the large quantity of uninformative data are filtered out and removed from the
data stream prior to the mathematically intensive point cloud transformation processing. This front-end pre-processing,
which largely consists of control flow instructions, is specific to the particular type of flash ladar focal plane array being
used and is performed by the computer's CPU. The valid signals along with their corresponding inertial and navigation
metadata are then transferred to a GPU device to perform range-correction, geo-location, and ortho-rectification on each
3D data point so that data from multiple frames can be properly tiled together either to create a wide-area map or to
reconstruct an object from multiple look angles. GPU parallel processing kernels were developed using OpenCL. Postprocessing
to perform fine registration between data frames via complex iterative steps also benefits greatly from this
type of high-performance computing. The performance improvements obtained using GPU processing to create
corrected 3D images and for frame-to-frame fine-registration are presented.
We demonstrate a numerical technique for registering multiple frames of point cloud data from an airborne 3D flash
ladar system that we have designed, built, and flown. This technique stitches together ladar data even in the presence of
inaccuracies in the line-of-sight pointing knowledge as well as instabilities in the time-of-flight clock frequency. The
technique performs frame-to-frame in-track as well as cross-track stitching of multiple flight line data to create large area
maps of urban areas and vegetation. Filters remove data with spurious range values and high intensity specular back
flashes such as those from bodies of water. Signal averaging of nearly overlapping pixel data creates monolithic, wide
area 3D maps that are geo-located and thus readily superimposable with other types of sensor data, such as hyperspectral
images, for fused-data exploitations. The accuracy of the numerical technique used for stitching data from different
target types, such as urban, vegetation, or bare earth, was studied. This analysis provides guidance for future
improvements of algorithms used for registering airborne 3D flash ladar point cloud data sets.
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