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Heather M. Cowardin

Publications and source records attributed to Heather M. Cowardin.

Optical Characterization of DebriSat Fragments in Support of Orbital Debris Environmental Models

The NASA Orbital Debris Program Office (ODPO) develops, maintains, and updates orbital debris environmental models, such as the NASA Orbital Debris Engineering Model (ORDEM), to support satellite designers and operators by estimating the risk from orbital debris impacts on their vehicles in orbit. Updates to ORDEM utilize the most recent validated datasets from radar, optical, and in situ sources to provide estimates of the debris flux as a function of size, material density, impact speed, and direction along a mission orbit. On-going efforts within the NASA ODPO to update the next version of ORDEM include a new parameter that highly affects the damage risk – shape. Shape can be binned by material density and size to better understand the damage assessments on spacecraft. The in situ and laboratory research activities at the NASA ODPO are focused on cataloging and characterizing fragments from a laboratory hypervelocity-impact test using a high-fidelity, mock-up satellite, DebriSat, in controlled and instrumented laboratory conditions. DebriSat is representative of present-day, low Earth orbit satellites, having been constructed with modern spacecraft materials and techniques. The DebriSat fragment ensemble provides a variety of shapes, bulk densities, and dimensions. Fragments down to 2 mm in size are being characterized by their physical and derived properties. A subset of fragments is being analyzed further in NASA’s Optical Measurement Center (OMC) using broadband, bidirectional reflectance measurements to provide insight into the optical-based NASA Size Estimation Model. Additionally, pre-impact spectral measurements on a subset of DebriSat materials were acquired for baseline material characterization. This paper provides an overview of DebriSat, the status of the project, and ongoing fragment characterization efforts within the OMC.

Heather M. Cowardin↗

Characterization of Modern Spacecraft Materials under Space-simulated Environment

External spacecraft materials play an important role in satellite protection from the harsh space environment. Research has shown that the physical, chemical, and optical properties of matter change continuously as a result of exposure to solar radiation and aggressive chemical species produced in Earth’s upper atmosphere. Thorough knowledge of the material properties evolution throughout a planned mission lifetime helps to improve the reliability of spacecraft. Moreover, the establishment of correlation factors between true space exposure and accelerated space weather experiments at ground facilities enables accurate prediction of on-orbit material performance based on laboratory-based testing. The presented work aims to evaluate the radiation effects of low Earth orbit (LEO) environment, namely, exposure to the high-energy electrons, atomic oxygen (AO), and vacuum ultraviolet (VUV), of several modern spacecraft materials. The studied materials represent the “flight duplicates” of samples that will be launched as a part of the Materials International Space Station Experiment Flight Facility (MISSE-FF) mission in 2022. MISSE-FF flight sample collection comprises different classes of polymers, including polyimides from the Kapton family, manufactured by E.I du Pont de Nemours and Co., Polyethylene terephthalate (PET) materials, liquid crystal polymers, PI/Polyhedral Oligomeric Silsesquioxanes (POSS), and carbon and glass fiber reinforced polymers. A sequential exposure approach was undertaken to allow monitoring of degradation induced by each environmental component (electrons, AO, and VUV) separately. Surface morphology, optical, and charge transport properties of selected materials were characterized using different techniques, namely, atomic force and scanning electron microscopy, ultraviolet visible (UV/Vis) transmission, reflectance, Bidirectional Reflectance Distribution Function (BRDF), and surface potential decay measurements.

Elena Plis↗

Ground Testing of the MISSE-16 Materials

External spacecraft materials play an important role in satellite protection from the harsh space environment. Research has shown that the physical, chemical, and optical properties of matter change continuously as a result of exposure to solar radiation and aggressive chemical species produced in Earth’s upper atmosphere. Thorough knowledge of the material properties evolution throughout a planned mission lifetime helps to improve the reliability of spacecraft. Moreover, the establishment of correlation factors between true space exposure and accelerated space weather experiments at ground facilities enables accurate prediction of on-orbit material performance based on laboratory-based testing. The presented work aims to evaluate the radiation effects of low Earth orbit (LEO) environment, namely, exposure to the high-energy electrons and atomic oxygen (AO), of heritage and novel spacecraft materials selection. The studied materials represent the “flight duplicates” of samples that are launched as a part of the 16th Materials International Space Station Experiment Flight Facility (MISSE-FF) mission in 2022.

Elena A. Plis↗

Analysis of Hypervelocity-Impacted Thin Films for Space Applications

Exposure to the harsh space environment and hypervelocity impacts from micrometeoroids and small orbital debris can affect space operations through long-term degradation of spacecraft materials, surfaces, or systems. Multi-layer insulation (MLI) and coated, polyimide films are spacecraft materials commonly found on the external surfaces of spacecraft for thermal control and protection. Characterizing the damage to these exposed materials with in situ and laboratory measurements can better inform spacecraft designers and operators in understanding and mitigating surface or system degradation. In this paper, we examine flown Hubble Space Telescope (HST) Equipment Bay 5 MLI and coated, polyimide ground test articles to characterize hypervelocity impact damage. Impact feature cavities are inspected to identify damage, which can validate long-term degradation models, improve thermal management systems, or improve accuracy of damage predictions. An overview of the impact characterization using optical microscopy, narrowband spectroscopy, and Scanning Election Microscopy/Energy Dispersive X- ray (SEM/EDX) of the two materials is presented. Observations of robustness in the space environment, as well as a detailed assessment of cratering and penetration statistics for the space-exposed sample, also are discussed.

Melissa A. Ward↗

Spectral Characterization of Modern Spacecraft Materials

One of the observational parameters of interest in ground-based optical measurements is ascertaining material properties using broadband filter photometry and spectroscopy for orbiting targets. Broadband photometry can provide reflectance measurements that can aid in producing color-color indices and assess if objects can be classified into families or taxonomies. However, these reflectance properties can vary due to aspect angle, phase angle, and general degradation of the target’s exterior material. Spectral characterization can aid in material characterization utilizing known absorption bands and spectral signatures, but these signatures are affected by the same conditions described for remote observations.When utilizing ground-based measurements, it is well understood that material characterization is subject to variability due to space weathering and/or other external events (i.e., collision or explosion). The focus of this study is on space weathering effects on spacecraft materials in low Earth orbit. To better assess how materials are affected by the harsh space environment, specifically modern materials, a collection of materials were analyzed in both their pristine condition and after electron bombardment. This sample collection is part of an upcoming mission with the Materials International Space Station Experiment Flight Facility (MISSE-FF) that will be launched in 2022. These laboratory analyses on the samples will provide a ground-truth to compare with the insitu collected data. The data will also be stored in the NASA Johnson Space Center’s Spacecraft Materials Spectral Database that is available to U.S. citizens and maintained by the Orbital Debris Program Office. The following paper provides an overview of the materials investigated, laboratory, and database overview, and spectral results for both pristine and post-electron exposed conditions. The spectral signature data highlights which materials are stable, or remain relatively unchanged, and which materials vary significantly due to exposure and material configuration (variations due to rotation of the sample on a flat surface).Initial results on changes in spectral directional reflectance of the materials as a function of incident illumination direction are also presented.This data also will benefit the space situational awareness community with spectral characterization of novel materials that can support their respective optical measurements focused on material identification.

Heather M. Cowardin↗

Goniometric and Polarized Imaging Spectroscopic Lab Measurements of Spacecraft Materials

To better characterize the spectral response of common spacecraft materials, the following laboratory measurements are presented to support the Space Situational Awareness community in the analysis of remotely sensed observational data. Of interest is classifying material reflective properties using directional reflectance spectroscopy and spatially resolved polarized imaging spectroscopy, allowing laboratory data to be applicable to ground-based optical telescope observations. The team acquired a typical CubeSat solar panel and a sample of multi-layer insulation (MLI) commonly used on spacecraft for initial measurements. The directional spectral data were collected at the Goniometer of the Rochester Institute of Technology (GRIT) laboratory with a lab and field goniometer incorporating two AnalyticalSpectral Device (ASD) spectrometers, a small Lab sphere integrating sphere also paired with an ASD spectrometer, and a Headwall micro-Hyperspec E-Series imaging spectrometer with an adjustable linear polarizer. The goniometer measures spectral bi-directional reflectance factor (BRF) data over a broad range from 350−2500 nm at 1 nm spacing with 3 nm spectral resolution in the visible and near infrared and 8 nm in the shortwave infrared. With the same spectral capabilities, the integrating sphere measures hemispherical-directional reflectance (HDR) in a 45◦-nadir configuration. The Headwall imager covers a spectral range from 400−1000 nm with 1.6 nm spectral resolution.Our initial BRF measurements show interference effects for both materials typically observed with thin films and high infrared reflectivity. In contrast, the interference effects are not present in the HDR measurements of the MLI likely due to the interference effects being averaged out over the reflecting hemisphere. Spatially resolved polarization ratio maps show variability across the materials due to the varying surface structure. We outline a plan for expanding our analysis to a broader range of materials to characterize their directional reflectance spectroscopy.

Chris H. Lee↗

Analysis of Spacecraft Materials Discrimination Using Color Indices for Remote Sensing for Space Situational Awareness

The increasing number of space missions have resulted in an augmented density of artificial objects positioned in orbital domains near Earth. Knowing the material composition of the resident space object can be of value in object identification and risk assessment using remote sensing techniques. To perform this task, it is increasingly imperative to optically characterize spacecraft materials to identify unique material-specific spectroscopic markers. In this work, a variety of materials frequently utilized by the aerospace industry in spacecraft design and construction were analyzed using reflectance spectroscopy. The collected data provide a spectral characterization baseline for modern-day and historical spacecraft materials. The color index was computed for standard astronomical and suggested theoretical filter passbands and compared to each other in their capability to discriminate materials belonging to different classes. The color index was calculated from reflectance spectra of common spacecraft materials in their pristine, as-received conditions that fell under different family groupings. Different color-index combinations were studied using color-color diagrams. Visual and quantitative analysis of the color-color diagrams were used to evaluate the possibility of discriminating materials from one another by means of optical measurements. Results of the analysis show that polyimide and photovoltaic materials are most easy to discriminate from all other materials via color indices using different filter passbands evaluated in this study.

spectral reflectance↗

Hypervelocity Impact Characterization on Hubble Space Telescope Multi-Layer Insulation

Multi-layer insulation (MLI) is a common material used on rocket bodies and spacecraft to provide thermal regulation. This material is typically attached on the surface of the object in orbit and is thus exposed to the space environment and to micrometeoroid and orbital debris (MMOD) impacts. Occasionally, these exposed surfaces are returned and used by NASA’s Orbital Debris Program Office (ODPO) for analysis. When used to assess impacts on surfaces over time, materials like MLI provide an opportunity for in situ measurements to support the Orbital Debris Engineering Model (ORDEM) development and validation. During the 2009 Hubble Space Telescope (HST) Serving Mission, the MLI blankets covering the HST electronics bays 5, 8, and 10 were removed and subsequently analyzed by the ODPO in 2010. The bay 5 blanket was used in concert with ground-based hypervelocity impact tests on single layer MLI to validate the ORDEM 3.1 computer model of the OD environment, but further research was required to properly differentiate the impact features attributed to MM or OD. The ORDEM 3.1 validation effort identified several areas of further study to improve model validation and understanding of the space environment. Among these topics are the effects of underlying MLI layers on first layer impact feature characteristics, the effects of space weathering and associated damage to the surface on impact feature characteristics, and the transition from perforating to cratering regions. To better understand hypervelocity impact damage and long-term degradation of MLI surfaces, further hypervelocity impact testing was proposed and completed from 2020 to 2022. This paper discusses test conditions and parameters with resultant impact hole analyses of single layer versus multi-layered samples, space-exposed samples versus pristine, equivalent samples, and perforation versus cratering criteria in the difficult transition region. Damage equations, with associated uncertainties, are estimated from the test parameters and presented. The results of a feasibility study are described, in which the Scanning Electron Microscopy/Electron Dispersive X-ray was used to examine the MLI layers to differentiate MM and OD impacts. Finally, the extension of HST MLI outcomes and analysis methodology as it applies to future returned MLI samples is discussed.

Melissa A. Murray↗

Using Machine Learning to Infer Material Properties of Debris Fragments from X-ray Images in the DebriSat Project

The DebriSat project is a collaboration effort with the NASA Orbital Debris Program Office, the U.S. Space Force Space Systems Command Center, The Aerospace Corporation, and the University of Florida. To date, over 200,000 fragments from this ground-based, hypervelocity impact experiment have been collected, and processing is underway to determine their physical characteristics, such as material, shape, color, characteristic length, and average cross-sectional area. The x-ray process is primarily used to identify the location of the fragments and estimated size for extraction, so that these physical characteristics can be assessed. This paper proposes a machine learning-based approach to characterize materials from x-ray images of debris fragments embedded in soft-catch foam used in the DebriSat project. The novel methodology discussed in this paper will highlight the use of x-ray imagery data to characterize these fragments without extraction or a human-in-the-loop. Both supervised and unsupervised machine learning techniques are utilized with this approach to infer the physical parameters of the fragments embedded in the soft-catch foam panels used in the impact experiment based on x-ray images of the foam panels. Additionally, 3D reconstructions of the extracted fragments are created with images taken from two different angles using the structure from motion (SfM) method. The characteristic lengths and shape from the 3D reconstruction, alongside the physical characteristics of the debris, are used in the inference of the material type. To develop and test the approach, a dataset of x-ray images of debris fragments of varying sizes and materials is collected. Supervised learning methods such as convolutional neural networks (CNNs), support vector machines (SVM), decision trees, and random forest classifiers are used due to the high-dimensional feature spaces of the debris and nonlinear decision boundaries for material categorization. Given the limited pre-labeled data of embedded debris materials smaller than 10 mm, unsupervised machine learning techniques such as clustering algorithms and autoencoders are used, in addition to supervised learning methods. The clustering algorithms group similar fragments together based on their physical properties, and autoencoders reduce the dimensionality of the x ray images and extract relevant features. The performance of the proposed approach's is analyzed using a range of statistical methods, including confusion matrices, receiver operating characteristic curves, and precision-recall curves. The results are compared with those obtained using a baseline approach that relies on manual identification and classification of debris fragments. To evaluate the effectiveness of different machine learning methods, statistical tests such as t-tests, ANOVA, and cross-validation are performed, comparing the performance of CNNs, SVMs, clustering algorithms, and autoencoders. Additional analysis needs to be conducted to identify any sources of bias or variability that may affect the results, such as variations in imaging conditions or fragmentation patterns. Other topics explored are limitations, refinements, and the potential use of semi-supervised learning techniques, such as self-training to label unlabeled datasets and co-training using x-ray images taken from two different angles as two different models.

Saik Anam Siam↗

Alteration of Optical Properties in Polymer Materials under Low Earth Orbit (LEO) Space and Simulated Exposure

This paper provides an overview of the 16th Materials International Space Station Experiment (MISSE) project, conducted by a multiorganizational team of researchers. The orbital environment during the mission, including environmental sensors data and unexpected occurrences, are discussed. The research further examines the spectral changes in selected material, Kapton TF, exposed to low Earth orbit conditions during the mission. Optical images of the material taken during the mission were analyzed using a machine learning approach. This process involved the use of a Radial Basis Function network to extract reflectance spectra from RGB/IR images. The findings were then compared with lab-based experiments of identical materials subjected to simulated space weather conditions. This comprehensive study aids in making accurate predictions about the performance of materials in space, thereby improving the reliability and safety of future space missions.

Insulators↗