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NASA NTRS2013

Observations of Titan 3C-4 Transtage Fragmentation Debris

The fragmentation of a Titan 3C-4 Transtage (1968-081) on 21 February 1992 is one of only two known break-ups in or near geosynchronous orbit. The original rocket body and 24 pieces of debris are currently being tracked by the US Space Surveillance Network (SSN). The rocket body (SSN# 3432) and several of the original fragments (SSN# 25000, 25001, 30000, and 33511) were observed in survey mode during 2004-2010 using the 0.6-m Michigan Orbital DEbris Survey Telescope (MODEST) in Chile using a broad R filter. This paper will present a size distribution for all calibrated magnitude data acquired on MODEST. Size distribution plots will also be shown using historical models for small fragmentation debris (down to 10 cm) believed to be associated with the Titan break-up. In November 2010, visible broadband photometry (Johnson/Kron-Cousins BVRI) was acquired with the 0.9-m Small and Moderate Aperture Research Telescope System (SMARTS) at the Cerro Tololo Inter-American Observatory (CTIO) in Chile on several Titan fragments (SSN# 25001, 33509, 33510) and the parent rocket body. Color index data will be used to determine the fragment brightness distribution and how the data compares to spacecraft materials measured in the laboratory using similar photometric measurement techniques. In 2012, the SSN added 16 additional fragments to the catalogue. MODEST acquired magnitude data on ten Titan fragments in late 2012 and early 2013. The magnitude distribution of all the observed fragments are analyzed as a function of time. In order to better characterize the breakup fragments spectral measurements were acquired on the original rocket body and five Titan fragments using the 6.5-m Magellan telescopes at Las Campanas Observatory in Chile. The telescopic spectra are compared with laboratory acquired spectra of materials (e.g., Aluminum and various paints) and categorized based on known absorption features for spacecraft materials.

Cowardin, Heather↗
NASA NTRS2014

An Analysis of the FY-1C, Iridium 33, and Cosmos 2251 Fragments

The beginning of the year 2013 marks the sixth anniversary of the destruction of the Fengyun-1C (FY-1C) weather satellite as the result of an anti-satellite test conducted by China in January 2007 and the fourth anniversary of the accidental collision between Cosmos 2251 and the operational Iridium 33 in February 2009. These two events represent the worst satellite breakups in history. A total of 5579 fragments have been cataloged by the U.S. Space Surveillance Network (SSN), and almost 5000 of them were still in orbit in January 2013. In addition to these cataloged objects, hundreds of thousands (or more) of fragments down to the millimeter size regime were also generated during the breakups. These fragments are too small to be tracked by the SSN, but are large enough to be a safety concern for human space activities and robotic missions in low Earth orbit (LEO, the region below 2000 km altitude). Like their cataloged siblings, many of them remain in orbit today. These two breakup events dramatically changed the landscape of the orbital debris environment in LEO. The spatial density of the cataloged population in January 2013 is shown as the top blue curve. The combined FY-1C, Iridium 33, and Cosmos 2251 fragments (black curve) account for about 50 percent of the cataloged population below an altitude of 1000 km. They are also responsible for the concentrations at 770 km and 850 km, altitudes at which the collisions occurred. The effects of the FY-1C, Iridium 33, and Cosmos 2251 fragments will continue to be felt for decades to come. For example, approximately half of the generated FY-1C fragments will remain in orbit 20 years from now. In general, the Iridium 33 and Cosmos 2251 fragments will decay faster than the FY-1C fragments because of their lower altitudes. Of the Iridium 33 and Cosmos 2251 fragments, the former have much shorter orbital lifetimes than the latter, because lightweight composite materials were heavily used in the construction of the Iridium vehicle, leading to the higher area-to-mass ratios of the fragments.

Liou, J.-C.↗
NASA NTRS2017

Imaging Systems for Size Measurements of Debrisat Fragments

The overall objective of the DebriSat project is to provide data to update existing standard spacecraft breakup models. One of the key sets of parameters used in these models is the physical dimensions of the fragments (i.e., length, average-cross sectional area, and volume). For the DebriSat project, only fragments with at least one dimension greater than 2 mm are collected and processed. Additionally, a significant portion of the fragments recovered from the impact test are needle-like and/or flat plate-like fragments where their heights are almost negligible in comparison to their other dimensions. As a result, two fragment size categories were defined: 2D objects and 3D objects. While measurement systems are commercially available, factors such as measurement rates, system adaptability, size characterization limitations and equipment costs presented significant challenges to the project and a decision was made to develop our own size characterization systems. The size characterization systems consist of two automated image systems, one referred to as the 3D imaging system and the other as the 2D imaging system. Which imaging system to use depends on the classification of the fragment being measured. Both imaging systems utilize point-and-shoot cameras for object image acquisition and create representative point clouds of the fragments. The 3D imaging system utilizes a space-carving algorithm to generate a 3D point cloud, while the 2D imaging system utilizes an edge detection algorithm to generate a 2D point cloud. From the point clouds, the three largest orthogonal dimensions are determined using a convex hull algorithm. For 3D objects, in addition to the three largest orthogonal dimensions, the volume is computed via an alpha-shape algorithm applied to the point clouds. The average cross-sectional area is also computed for 3D objects. Both imaging systems have automated size measurements (image acquisition and image processing) driven by the need to quickly and accurately measure tens of thousands of debris fragments. Moreover, the automated size measurement reduces potential fragment damage/mishandling and ability for accuracy and repeatability. As the fragment characterization progressed, it became evident that the imaging systems had to be revised. For example, an additional view was added to the 2D imaging system to capture the height of the 2D object. This paper presents the DebriSat project's imaging systems and calculation techniques in detail; from design and development to maturation. The experiences and challenges are also shared.

Shiotani, B.↗
NASA NTRSDate not supplied

X-Ray Imagery as the Record of All Data of Interest in Hypervelocity Impact Fragment Studies

Laboratory study of hypervelocity spacecraft fragmentation has traditionally involved the collection and analysis of fragments that were caught in deceleration material surrounding the impact. This process has typically involved the disintegration of the catchment material either through chemical dissolution, or through physical excavation to recover the fragments. Due to the scale of the three impact tests—the Satellite Orbital Debris Characterization Impact Test (SOCIT), the DebriSat satellite impact test, and the DebrisLV launch vehicle impact test—the latter two using more than 12 cubic meters of polyurethane foam to capture the fragments, hese projects have used x-ray imagery to precisely locate and thus, to more efficiently extract fragments in the soft-catch material. Three years into the DebriSat fragment extraction process, a side study was initiated to explore what additional information could be discerned from the x-rays, with significant results. This study was instrumental to a rapid replacement and retooling as the project was forced to replace the x-ray system around which the extraction process had been based. The revised process continues to map the debris for extraction. The project has, in parallel, systematically addressed the limits/tolerances of what x-rays can reveal about size, shape, density, mass, velocity, energy, and deformation/damage of the fragment during the deceleration in the catchment material while replicating the original extraction mapping function. All of these features have been optimized or have sufficient understanding to characterize the basic factors that will define a complete data set extracted solely from x-ray imagery. It is an ideal time to develop such a process, with extracted fragments providing “ground truth” against image-only data, and abundant available imagery of the same fragments under both the prior and replacement x-ray technologies, which have several fundamentally different characteristics. This paper addresses the types and quality of hypervelocity fragmentation data that can be and has been extracted from x-rays. It further addresses the question of whether and under what circumstances future hypervelocity experiments can use x-ray methods to largely—or to completely—avoid the extraction process in recording all appropriate results. Lastly, this paper addresses lessons learned and how future efforts can be further optimized.

John B. Bacon↗
NASA NTRSDate not supplied

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↗
NASA NTRS2023

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↗
NASA NTRS2016

Average Cross-Sectional Area of DebriSat Fragments Using Volumetrically Constructed 3D Representations

Debris fragments from the hypervelocity impact testing of DebriSat are being collected and characterized for use in updating existing satellite breakup models. One of the key parameters utilized in these models is the ballistic coefficient of the fragment which is directly related to its area‐to‐mass ratio. However, since the attitude of fragments varies during their orbital lifetime, it is customary to use the average cross‐sectional area in the calculation of the area‐to‐mass ratio. The average cross‐sectional area is defined as the average of the projected surface areas perpendicular to the direction of motion and has been shown to be equal to one‐fourth of the total surface area of a convex object. Unfortunately, numerous fragments obtained from the DebriSat experiment show significant concavity (i.e., shadowing) and thus we have explored alternate methods for computing the average cross‐sectional area of the fragments. An imaging system based on the volumetric reconstruction of a 3D object from multiple 2D photographs of the object was developed for use in determining the size characteristic (i.e., characteristics length) of the DebriSat fragments. For each fragment, the imaging system generates N number of images from varied azimuth and elevation angles and processes them using a space‐carving algorithm to construct a 3D point cloud of the fragment. This paper describes two approaches for calculating the average cross‐sectional area of debris fragments based on the 3D imager. Approach A utilizes the constructed 3D object to generate equally distributed cross‐sectional area projections and then averages them to determine the average cross‐sectional area. Approach B utilizes a weighted average of the area of the 2D photographs to directly compute the average cross‐sectional area. A comparison of the accuracy and computational needs of each approach is described as well as preliminary results of an analysis to determine the "optimal" number of images needed for the 3D imager to accurately measure the average cross sectional area of objects with known dimensions.

Scruggs, T.↗
NASA NTRSDate not supplied

Using X-Ray Computed Tomography to Catalog Rock Fragments in Apollo Drive Tube 73002

Overview: The Apollo missions collected 382 kg of rock, regolith, and core samples from six locations on the nearside of the Moon. Approximately 84% by mass of the Apollo collection remains in pristine condition within the curation facility at Johnson Space Center (i.e., never allocated, continuously stored in dry-N2 purged cabinets, exposure history restricted to Teflon, stainless steel, and Al-metal). Although most Apollo samples have been well characterized, there are several types of samples that have remained wholly or largely unstudied since their return, and/or that have been cu-rated under special conditions, e.g., frozen samples, samples stored in He-purged environment, and previously unopened drive tubes. NASA solicited proposals for the Apollo Next Generation Sample Analysis Pro-gram (ANGSA), and 9 teams were selected to study a subset of the unopened and frozen samples [1]. The first sample opened as part of the ANGSA pro-gram was drive tube 73002. This was originally a ~30 cm long, 4 cm diameter drive tube collected on a land-slide deposit near Lara Crater at the Apollo 17 landing site. It was part of a ~60 cm long double drive tube collected, and the bottom half of the tube (73001) was sealed under vacuum on the Moon [2]. Prior to opening sample 73002, the sample was imaged with a high resolution X-ray Computed Tomography (XCT) scan of the entire tube [3], which provided invaluable information during the dissection process [4]. In addition to the pre-dissection XCT scans, individual >4 mm particles were separated from the 73002 regolith during processing and scanned at high resolution by XCT. Here we pre-sent the initial lithologic classification of 134 individual >4 mm rock fragments separated from the 73002 core during the dissection process. Methodology: Drive tube 73002 was manually dissected in 0.5 cm depth intervals in three passes (Fig. 1) [4,5]. Each interval from pass 1 and 2 was sieved to <1 mm and >1 mm size fractions, and >1 mm particles were further manually subdivided into 1-2, 2-4, 4-10, and >10 mm size fractions. Pass 3 was not sieved, but >10 mm clasts were separated manually. Each 4-10 mm and >10 mm fragment was individually weighed, triply bagged in Teflon, and scanned by XCT. There are 60 rock fragments in Pass 1, 64 rock fragments in Pass 2 (from the 4-10 mm and >10 mm size fractions), and 8 rock fragments from Pass 3 (>10 mm size fraction). Each individually bagged rock fragment was scanned using the 180 kV nano-focus transmission source on the Nikon XTH 320 XCT system at NASA Johnson Space Center [6]. Scanning conditions varied considerably for individual particles, in large part be-cause of the large variation in size (0.008-19.623 g). All scans fell within the following range of scan conditions: 2.8-20.6 um voxel size; 90-155 kV voltage; 18-39 uA current; 1891-3141 projections; and 902-2000 slices. Results and Discussion: The 132 rock fragments from sample 73002 fall into the following general cat-gories: agglutinates (n = 6); basalts (13); impact melts (5); impact melt breccias (IMB; 42); regolith breccias (62); and soil breccias (4); see Figure 2 for representative examples of each lithology. Within most of these broad lithologic groups are recognizable subgroups. For example, a significant portion of regolith breccia fragments contain some agglutinate-like glass (n = 9) or are dilithologic (7) because they contain a single large clast (~50% or more by volume). Subgroups can be based on similarities to previously identified lunar lithologies, such as high-Ti basalts (9) and VLT basalts (4; Fig. 3), or based on commonly seen features within the fragments, such as poikilitic ilmenite IMB (10), ilmenite-lath IMB (12), or vesicular IMB (11) “groups”. Particles in the same “group” are not necessarily intended to be genetically related, but rather identify particles that are similar and that follow-up studies can classify in more detail [7]. Conclusion: Identification of lithologies based on XCT is a powerful tool, but a more absolute classification will sometimes require additional textural information from thin sections (e.g., glassy-matrix regolith vs. impact-melt vs. granulitic breccia) or quantitative mineral compositions (e.g., basalt vs. monomict breccia).

R A Zeigler↗
NASA NTRSDate not supplied

Analysis of Darkened Fragments Resulting from Laboratory Hypervelocity Experiments

NASA’s Orbital Debris Program Office (ODPO) relies on measurements from optical, radar, and in situ measurements to facilitate the development of data-driven orbital debris environmental engineering models such as the NASA Orbital Debris Engineering Model (ORDEM). For optical measurements, the ODPO relies on ground-based optical telescopes to statistically assess objects in geosynchronous orbit and, in the future, low Earth orbit (LEO). The data collected include the detected object’s orbital parameters, time of observation, and optical magnitude. The latter parameter can be converted to a size using NASA’s optical Size Estimation Model (oSEM). It is well known that the observed magnitude of orbital debris can vary based on an object's material constituents, observational geometry, and the effects of space weathering. To assess these magnitude variations, the ODPO uses the Optical Measurement Center (OMC) at NASA Johnson Space Center to characterize a variety of materials and fragments from laboratory impact tests representative of fragments that constitute the orbital debris population. One experiment was DebriSat: a 56 kg spacecraft was built to incorporate structural elements of a modern LEO spacecraft and was subjected to a hypervelocity impact test at the U.S. Air Force’s Arnold Engineering Development Complex using test parameters that may be encountered in LEO. The DebriSat project has provided an abundance of information for assessing fragmentation debris in terms of material, color, shape, size, density, mass, and other derived parameters. Prior to the impact test, the ODPO collected spectral measurements on a subset of the materials used to construct DebriSat for a “ground-truth” of their optical properties. After the successful hypervelocity impact test, the DebriSat team observed a fine, dark dust coating all the fragments. Prior research has suggested that this came from ablated material deposited on the fragments during the impact test, causing a change in the reflective properties [1]. Given that this lower reflectivity on the DebriSat fragments will influence the laboratory-acquired magnitudes used to calculate size and inform potential updates to the oSEM, it is critical to assess if this darkening effect on the DebriSat fragments is a laboratory bias or something that could occur in on-orbit breakup events. This paper will provide a brief overview of the OMC and DebriSat experiment, focused on the optical characterization of a subset of materials using broadband photometric measurements and spectroscopic measurements. In addition, elemental analysis of various DebriSat fragments and the soft-catch foam used in the hypervelocity experiment compared with pristine foam will be examined to further evaluate the source of the dark material coating all fragments. Finally, the authors will present a twofold plan 1) for assessing potential biases in laboratory impact experiments that could affect laboratory optical characterization and 2) for mitigating biases when compared with ground-based optical telescopic measurements of the orbital debris environment.

Heather Cowardin↗
NASA NTRSDate not supplied

Analysis of Darkened Fragments Resulting from Laboratory Hypervelocity Experiments

NASA’s Orbital Debris Program Office (ODPO) relies on measurements from optical, radar, and in situ measurements to facilitate the development of data-driven orbital debris environmental engineering models such as the NASA Orbital Debris Engineering Model (ORDEM). For optical measurements, the ODPO relies on ground-based optical telescopes to statistically assess objects in geosynchronous orbit and, in the future, low Earth orbit (LEO). The data collected include the detected object’s orbital parameters, time of observation, and optical magnitude. The latter parameter can be converted to a size using NASA’s optical Size Estimation Model (oSEM). It is well known that the observed magnitude of orbital debris can vary based on an object's material constituents, observational geometry, and the effects of space weathering. To assess these magnitude variations, the ODPO uses the Optical Measurement Center (OMC) at NASA Johnson Space Center to characterize a variety of materials and fragments from laboratory impact tests representative of fragments that constitute the orbital debris population. One experiment was DebriSat: a 56 kg spacecraft was built to incorporate structural elements of a modern LEO spacecraft and was subjected to a hypervelocity impact test at the U.S. Air Force’s Arnold Engineering Development Complex using test parameters that may be encountered in LEO. The DebriSat project has provided an abundance of information for assessing fragmentation debris in terms of material, color, shape, size, density, mass, and other derived parameters. Prior to the impact test, the ODPO collected spectral measurements on a subset of the materials used to construct DebriSat for a “ground-truth” of their optical properties. After the successful hypervelocity impact test, the DebriSat team observed a fine, dark dust coating all the fragments. Prior research has suggested that this came from ablated material deposited on the fragments during the impact test, causing a change in the reflective properties [1]. Given that this lower reflectivity on the DebriSat fragments will influence the laboratory-acquired magnitudes used to calculate size and inform potential updates to the oSEM, it is critical to assess if this darkening effect on the DebriSat fragments is a laboratory bias or something that could occur in on-orbit breakup events. This presentation will provide a brief overview of the OMC and DebriSat experiment, focused on the optical characterization of a subset of materials using broadband photometric measurements and spectroscopic measurements. In addition, elemental analysis of various DebriSat fragments and the soft-catch foam used in the hypervelocity experiment compared with pristine foam will be examined to further evaluate the source of the dark material coating all fragments. Finally, the authors will present a twofold plan 1) for assessing potential biases in laboratory impact experiments that could affect laboratory optical characterization and 2) for mitigating biases when compared with ground-based optical telescopic measurements of the orbital debris environment.

Heather Cowardin↗
DOE OSTI2024

Comparison of Gas Phase Fragmentation Behaviors of Nuclear Fuel Cycle Ligands in Lanthanide and Americium Metal Ligand Nitrate Clusters

Title (20 word): Comparison of Gas Phase Fragmentation Behaviors of Nuclear Fuel Cycle Ligands in Lanthanide and Americium Metal Ligand Nitrate Clusters Introduction (120 words): Transport of metal ions across the aqueous-organic phase boundary is an essential step in a hydrometallurgical nuclear fuel reprocessing strategy. The study of transport agents for nuclear fuel elements is imperative to guide the design of ligands that boost the separation efficiency of the recovery process from fission products. However, limited studies have been made on the chemistry of these transport agents when complexing with transuranic elements in gas-phase where all surrounding factors are essentially excluded. This work investigates the reagent ligand complexations to transuranic and other metals and their dissociations in the gas phase. Comparisons are made between 4f and 5f elements and between ligands. Methods (120 words): (N,N-diisobutylcarbamoylmethyl)phenyloctylphosphine oxide (CMPO) and N,N,N',N'-tetraoctyldiglycolamide (TODGA) have been selected to complex with metal nitrates. The actinide americium and lanthanides neodymium, samarium, and europium were investigated as part of this work. The lanthanides were selected to act as size and electron configuration analogues of the minor actinides. Metal complexes with two ligands and two nitrates ([M(NO3)2(CMPO)2]+, for example) are studied in Bruker micrOTOF-Q II mass spectrometer equipped with collision-induced dissociation capability. The comparisons of the mass spectra are made in groups of homogenous ligands and mixed TODGA-CMPO ligands clusters. Comparisons are also made based on the complexed metals (Am and lanthanides). Preliminary data (300 words): Collision-induced dissociation mass spectrometry data are collected on two ligands complexed with metal nitrates where the two ligands are homogenous, with (CMPO)2 or (TODGA)2, or heterogeneous, with (TODGA)(CMPO). Several fragmentation patterns are observed among complexes with the CMPO ligand whereas the TODGA ligand commonly dissociates intact from the complex. Most of the metal complexes exhibit similar fragmentation patterns, but there are a few notable deviations in fragmentation patterns between the Am and Ln-bearing complexes. For the [M(CMPO)2(NO3)2]+ complexes, the initial loss of nitrate in the form of nitric acid is observed in all four complexes. However, [Am(CMPO)2(NO3)2]+ exhibits an additional fragmentation not found in the lanthanide complexes. Also, a significantly different ratio of the second nitric acid loss is found in the Am complex. These deviations may indicate the different interaction behaviors between actinides and lanthanides. The [M(TODGA)2(NO3)2]+ complexes exhibit the fragmentation as the loss of one TODGA ligand as an intact form and the loss of nitrate as nitric acid. The Am complex exhibits an additional fragmentation after losing the TOGDA ligand, which is not observed among the Ln complexes. The heterogeneous [M(TODGA)(CMPO)(NO3)2]+ complexes exhibit both similarities and differences between the Am and Ln complexes. For example, the heterogenous Am complex does not exhibit the loss of an intact TODGA ligand while all three Ln complexes do. This indicates that TODGA may bind more strongly to Am than Ln. Additionally, the intensity of the loss of CMPO ligand (as partially or whole) is found to be significantly larger than that of the loss of TODGA (as partially of whole) indicating that TODGA is bound to the metal significantly stronger than CMPO. Planned computational analysis will help understand the deviation in fragmentation behaviors between americium and lanthanide metal centers, or between TODGA and CMPO ligands. Novel aspect (20 words): Gas-phase actinide and lanthanide complex formation and fragmentation provide insight into the coordination environment differences of f-element metals.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Measurement of fragment-correlated γ-ray emission from 252 Cf(sf)

This paper presents recent experimental results on the yield of prompt fission γ rays from the spontaneous fission of 252 Cf. We use an ionization chamber to tag fission events and measure the masses and kinetic energies of the fission fragments and trans-stilbene organic scintillators to measure the neutrons and γ rays emitted by the fission fragments. The combination of the ionization chamber and trans-stilbene scintillators allows us to determine the properties of neutrons and γ rays in coincidence with the fragments. The yield of γ rays is known to be influenced by the angular momenta (AM) of the fission fragments. We present experimental evidence indicating that the total γ-ray multiplicity, i.e., the sum of both fragments' emission, saturates at sufficiently high internal fragment excitation energies. We also observe distinct behaviors for the yield of γ rays from the light and heavy fragments, which for certain mass and total kinetic energy (TKE) regions are weakly or anticorrelated, indicating the presence of complex AM generation modes. We also observed a mass- and TKE-dependent anisotropy of the γ rays, which challenges and expands on the conventional notion that the fragments' AM are always aligned perpendicularly to the fission axis. Furthermore, the dependence of the anisotropy on mass and TKE indicates a dependence of these properties on the specific fission channels, thus providing an insight into the deformations and dynamics in fission and their connection with experimentally observable quantities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS1977

Blade fragment energy analysis

Two classes of fan blade fragments were considered in an analysis of blade fragment energy. The first, of relatively small size (.15 pound) and energy, tends to rebound from the fan and case when liberated in an FOD encounter. These small fragments have relatively low secondary damage potential and are less demanding in terms of protection. The larger fan blade fragments are ejected in a more direct release trajectory with higher energy and hence can represent a higher potential hazard. Simplified analytical methods were used to describe blade fragment energy transfer kinematics, establish fragment energy levels, evaluate damage potential and configure protection. The approach, methodology, and application are discussed as a possible building block for other applications. Development of effective local protection using Kevlar is also discussed. Analysis methods developed and applied to the rebound fragment problem and to the large direct release fragment problem are described.

Oconnor, M. A., Jr.↗
NASA NTRS1978

Fragmentation of molecular clouds

Fragmentation is generally considered to be the initial process that a molecular cloud must undergo before stars can form. Yet its role in determining the final mass spectrum remains obscure. It appears that gravitational fragmentation, considered as a unique process, is unsatisfactory. Both fragmentation and complementary physical processes are, therefore, discussed. One of the principle aims of the discussion is to indicate how stars of solar mass (and more generally, how the initial mass spectrum of stars) can form. Attention is given to the evidence for fragmentation, opacity-limited fragmentation, magnetic flux-limited fragmentation, fragmentation induced by molecule formation and excitation, protostellar heat input, fragment coalescence, accretion, binary formation, and probabilistic theories.

Silk, J.↗
NASA NTRS1978

Chemistry and petrology of Luna 24 lithic fragments and less than 250-micron soils - Constraints on the origin of VLT mare basalts

Results are reported on a combined INAA-petrologic study of 17 small (0.2-1.5 mg) Luna 24 lithic and mineral fragments and INAA study of 5 bulk soils and mineral separates from gabbro 24170. Lithic and mineral fragments are classified into VLT mare basalts (ferrobasalt and metabasalts), low-Ti, variolitic mare basalt, gabbros, melt rock and soil breccia. Data indicate 5 possible magma types, represented by: (1) VLT ferrobasalt and gabbro fragments, with low-TiO2 (about 1%), slightly bow-shaped REE pattern, and low REE concentrations (5-10X chondritic); (2) a ferrobasalt (Laul et al., 1978) and metabasalt fragments with major and trace element contents similar to (1), but positive Eu anomalies; (3) one gabbro fragment with distinctive pyroxene compositional trend (increasing Ti with nearly constant Fe/Fe + Mg) and highest REE contents of any Luna 24 mare basaltic sample, (4) a gabbro fragment with considerably less V and Cr2O3 than ferrobasalt and metabasalt fragments; and (5) variolitic basalt fragment with higher Ti2(2.3%) than other Luna 24 basalts and pyroxene that has increasing then decreasing Ti with increasing Fe/Fe + Mg. Trace element data place constraints on the nature of the source region and possible parent magmas for the Luna 24 VLT ferrobasalt.

Ma, M.-S.↗
NASA NTRS1983

Impact and explosion crater ejecta, fragment size, and velocity

A model was developed for the mass distribution of fragments that are ejected at a given velocity for impact and explosion craters. The model is semi-empirical in nature and is derived from (1) numerical calculations of cratering and the resultant mass versus ejection velocity, (2) observed ejecta blanket particle size distributions, (3) an empirical relationship between maximum ejecta fragment size and crater diameter and an assumption on the functional form for the distribution of fragements ejected at a given velocity. This model implies that for planetary impacts into competent rock, the distribution of fragments ejected at a given velocity are nearly monodisperse, e.g., 20% of the mass of the ejecta at a given velocity contain fragments having a mass less than 0.1 times a mass of the largest fragment moving at that velocity. Using this model, the largest fragment that can be ejected from asteroids, the moon, Mars, and Earth is calculated as a function of crater diameter. In addition, the internal energy of ejecta versus ejecta velocity is found. The internal energy of fragments having velocities exceeding the escape velocity of the moon will exceed the energy required for incipient melting for solid silicates and thus, constrains the maximum ejected solid fragment size.

Okeefe, J. D.↗
NASA NTRS1992

Gross-fragmentation of meteoroids and bulk density of Geminids from photographic fireball records

The explicit solution of the drag and ablation equations of a single nonfragmenting meteoroid moving in any actual atmosphere was published several years ago. The solution yields the theoretical relation of l, the distance flown by the meteoroid in its trajectory, as a function of time, t, assuming that the height, h, is a known function of l. The photographic records of meteors and fireballs are coded by time marks, using a rotating shutter or a similar device to break the moving image. Time is, thus, the independent variable and for each time mark on a meteoroid trajector, the observed distance along the trajectory, l sub obs, as well as the double- or multiple- station photographs of the same meteoroid. Applying this solution to all available Prairie Network (PN) fireball-records, we recognized that the majority of them gave good solutions with standard deviations somewhat bigger than the intrinsic geometrical precision of the data. We also noticed that, on an average, previous methods of evaluation of the meteoroid velocities (interpolation polynomials, numerical differenciation of the observed l sub obs) used up to only several tens of percent of the intrinsic precision of the PN observational data. When residuals of these solutions, i.e. l sub obs - l sub com, were represented as a function of time for about 75 percent of solutions. The remaining 25 percent of residuals showed systematic changes with time exceeding one standard deviation. We tried to explain these systematic time course of residuals by using different meteoroids first computed theoretically and then analyzed by the same model as the natural PN fireballs were. The conclusion of these model computations is that systematic time changes of residuals in the nonfragmenting model exceeding one standard of deviation are caused by sudden gross fragmentation at one or more trajectory points. Thus, we generalized the explicit solution of the drag and ablation equations of a single nonfragmenting meteoroid by allowing for one or more points, where sudden gross fragmentation can occur. Using this generalized solution, the distances along the meteoroid trajectory can be computed for any choice of input parameters and compared with the observed distances flown by the meteoroid. For the most precise and long fireball trajectories, the least-squares solution can, thus, yield the initial velocities, the ablation coefficients, the dynamical masses, the positions of gross-fragmentation points, and the terminal mass. At a gross-fragmentation point, the ratio of the main mass to all the remaining fragments can be compared with the dynamic mass determined from our gross-fragmentation model and, thus, the meteoroid bulk density can be evaluated. We applied the gross-fragmentation model to sever PN fireballs showing time changes of residuals, and we recognized that, in all these cases, the new computed bulk densities of meteoroids resulted higher in comparison with the meteoroid densities determined with the non-gross-fragmentation model. Other aspects of the study are discussed.

Ceplecha, Zdenek↗
NASA NTRS1993

Alkali-granitoids as fragments within the ordinary chondrite Adzhi-Bogdo: Evidence for highly fractionated, alkali-granitic liquids on asteroids

Adzhi-Bogdo is an ordinary chondrite regolith breccia (LL3-6) that fell October 30, 1949 in Gobi Altay, Mongolia. The rock consists of submm- to cm-sized fragments embedded in a fine-grained elastic matrix. The breccia contains various types of clasts, some of which must be of foreign heritage. Based on chemical compositions of olivine some components have to be classified as L-type. Components of the breccia include chondrules, impact melts (some are K-rich, similar to those found in other LL-chondrites, highly recrystalized rock fragments ('granulites'), pyroxene-rich fragments with achondritic textures, and alkali-granitoidal fragments that mainly consist of K-feldspar and quartz or tridymite. Probably, this is the first report on granitoids from asteroids. It can be ruled out that these fragments represent huge rock assemblages of the parent body like granites do on Earth. Therefore, to avoid misunderstandings, these rocks will be designated as granitoids. In one thin section four granitoids were observed. The main phases within these clasts are K-feldspar and SiO2-phases. Minor phases include albite, Cl-apatite, whitlockite, ilmenite, zircon, Ca-poor pyroxene, and an unidentified Na,Ti-bearing silicate. Based on chemical composition and on optical properties quartz appears to be the SiO2-phase in two fragments, whereas tridymite seems to occur in the other two. The calculated formula of the unknown Na,Ti-rich silicate is very close to (Na,Ca)2.7(Fe,Mg)6(Ti)1.3(Si)7(O)24. Quartz and K-feldspar can reach sizes of up to 700 microns. Thus, the fragments can be described as coarse-grained (by chondritic standards). This is especially the case considering that quartz and K-feldspar are very rare minerals in ordinary chondrites. Representative analyses of minerals from some granitoidal clasts are given. Based on the mineral compositions and the modal abundances the bulk compositions were calculated. Besides these granitoidal rocks, pyroxene-rich fragments occur that show exsolution textures that are similar to those found in eucrites.

Bischoff, A.↗