Results for “feature impact” — Page 7

NASA NTRS1995

Orbital impacts and the Space Shuttle windshield

The Space Transportation System (STS) fleet has flown more than sixty missions over the fourteen years since its first flight. As a result of encounters with on-orbit particulates (space debris and micrometeoroids), 177 impact features (chips) have been found on the STS outer windows (through STS-65). Forty-five of the damages were large enough to warrant replacement of the window. NASA's orbital operations and vehicle inspection procedures have changes over the history of the shuttle program, in response to concerns about the orbital environment and the cost of maintaining the space shuttle. These programmatic issues will be discussed, including safety concerns, maintenance issues, inspection procedures and flight rule changes. Examples of orbital debris impacts to the shuttle windows will be provided. There will also be a brief discussion of the impact properties of glass and what design changes have been considered to improve the impact properties of the windows.

Edelstein, Karen S.↗

NASA NTRS1994

Searching the Sinus Amoris: Using profiles of geological units, impact and volcanic features to characterize a major terrane interface on the Moon

Geochemical profiles of surface units, impact, and volcanic features are studied in detail to determine the underlying structure in an area of extensive mare/highland interface, Sinus Amoris. This study region includes and surrounds the northeastern embayment of Mare Tranquillitatis. The concentrations of two major rock-forming elements (Mg and Al), which were derived from the Apollo 15 orbital geochemical measurements, were used in this study. Mapped units and deposits associated with craters in the northwestern part of the region tend to have correlated low Mg and Al concentrations, indicating the presence of Potassium (K)-Rare Earth Elements (REE)-Phosphorus (P) (KREEP)-enriched basalt. Found along the northeastern rim of Tranquillitatis were areas with correlated high Mg and Al concentration, indicating the presence of troctolite. Distinctive west/east and north/south trends were observed in the concentrations of Mg and Al, and, by implication, in the distribution of major rock components on the surface. Evidence for a systematic geochemical transition in highland or basin-forming units may be observed here in the form of distinctive differences in chemistry in otherwise similar units in the western and eastern portions of the study region.

Clark, P.↗

NASA NTRS1992

Micrometeoroids and debris on LDEF

Part of the LDEF tray allocated to French Experiments (FRECOPA) was devoted to the study of dust particles. The tray was located on the face of LDEF directly opposed to the velocity vector. Two passive experiments were flown: a set of glass and metallic samples; and multilayer thin foil detectors. Crater size distribution made possible the evaluation of the incident microparticle flux in the near environment. Comparisons are made with measurements obtained on the other faces of LDEF and with results from similar experiments on the MIR. Of interest was the study of impact features on stacked thin foil detectors. The top foil acted as a shield, fragmenting the projectiles and spreading the fragments over the surface of the thick plate located underneath. EDS analysis has provided evidence of impactor fragments. Detectors consisting of a thin shield and thick bottom plate appear to offer a significantly higher return of data concerning chemical analysis of impactor residues than single plate detectors. The samples of various materials offer a unique opportunity for the study of the many processes involved upon hypervelocity impact phenomena.

Mandeville, Jean-Claude↗

NASA NTRS2014

Impacts on the Hubble Space Telescope Wide Field and Planetary Camera 2: Experimental Simulation of Micrometeoroid Capture

Hypervelocity impact features have been recognized on painted surfaces returned from the Hubble Space Telescope (HST). Here we describe experiments that help us to understand their creation, and the preservation of micrometeoroid (MM) remnants. We simulated capture of silicate and sulfide minerals on the Zinc orthotitanate (ZOT) paint and Al alloy plate of the Wide Field and Planetary Camera 2 (WFPC2) radiator, which was returned from HST after 16 years in low Earth orbit (LEO). Our results also allow us to validate analytical methods for identification of MM (and orbital debris) impacts in LEO.

Price, M. C.↗

NASA NTRSDate not supplied

Highlights of NASA’s Orbital Debris Program Office In Situ and Laboratory Measurements

NASA’s Orbital Debris Program Office (ODPO) maintains various returned spacecraft materials, capabilities, and facilities used for in situ and laboratory measurements that directly support orbital debris environmental models. In situ measurements include the analysis of exposed and returned hardware surfaces. These surfaces serve as passive sensors for the small-sized micrometeoroid and orbital debris (MMOD) flux below the sensitivity of ground-based radar and optical sensors. Various instruments and techniques are used to determine the size and depth of selected impact features, and – if feasible – the composition of the projectile material. Analysis of the impactor residues enables the differentiation of MM and OD for debris below 1 mm to support modeling the OD environment. In addition, projectiles identified as OD can be further differentiated in low-, medium-, and high- density impactors based on chemical analyses. In addition to in situ measurements, the ODPO has also worked in collaboration with the U.S. Space Force Space Systems Command (formerly the U.S. Air Force Space and Missile Systems Center), the Aerospace Corporation, and the University of Florida on a laboratory-based hypervelocity impact test, DebriSat, conducted at the Air Force Arnold Engineering Development Complex in 2014. The resulting data from this impact test series are being analyzed to assess the fragments’ sizes/masses, materials/densities, shapes, and other parameters of interest. The DebriSat project provides the data needed to update NASA’s breakup models and size estimation models using the simulated orbital breakup of a modern, low Earth orbit spacecraft. Ultimately, over 200,000 fragments from this impact test will be stored at NASA Johnson Space Center (JSC) and further analyzed by the ODPO. This project will also use machine learning techniques to infer physical parameters of fragments embedded in the soft-catch foam used in the impact experiment. Applied to X-ray imagery of the foam panels, these techniques promise to minimize human-in-the-loop processes for fragment extraction and physical characterization. A brief overview of this project and data collected will be presented. Lastly, the ODPO provides various capabilities hosted at NASA JSC for optical inspections and measurements using a variety of techniques and scientific instrumentation to support both in situ and laboratory measurements. The ODPO’s Optical Measurement Center (OMC) is an advanced facility for photometric and spectroscopic laboratory measurements of targets, including fragments from the DebriSat project. The OMC simulates telescopic observations by using space-like illumination conditions and source-target-sensor orientation techniques. Additionally, the OMC is uniquely equipped to acquire pseudo-bidirectional reflectance distribution data for broadband photometric measurements, thus removing aspect angle dependencies that can affect target size estimates using the optical size estimation model. Narrow-band surface material characterization using spectroscopic instrumentation gives insight into how the albedo parameter – also important in the optical size estimation model – may vary depending on the state of the material. The OMC also performs simulations of photometric measurements using optical ray-tracing software to model the OMC optical throughput. In addition to the OMC, the ODPO houses a start-of-the-art Fragment Analysis Facility that uses multiple microscopic inspection instruments to support in situ measurements and material characterization. An overview of both facilities will be highlighted in this paper.

Orbital Debris↗

NASA NTRSDate not supplied

Highlights of NASA’s Orbital Debris Program Office In Situ and Laboratory Measurements

NASA’s Orbital Debris Program Office (ODPO) maintains various returned spacecraft materials, capabilities, and facilities used for in situ and laboratory measurements that directly support orbital debris environmental models. In situ measurements include the analysis of exposed and returned hardware surfaces. These surfaces serve as passive sensors for the small-sized micrometeoroid and orbital debris (MMOD) flux below the sensitivity of ground-based radar and optical sensors. Various instruments and techniques are used to determine the size and depth of selected impact features, and – if feasible – the composition of the projectile material. Analysis of the impactor residues enables the differentiation of MM and OD for debris below 1 mm to support modeling the OD environment. In addition, projectiles identified as OD can be further differentiated in low-, medium-, and high- density impactors based on chemical analyses. In addition to in situ measurements, the ODPO has also worked in collaboration with the U.S. Space Force Space Systems Command (formerly the U.S. Air Force Space and Missile Systems Center), the Aerospace Corporation, and the University of Florida on a laboratory-based hypervelocity impact test, DebriSat, conducted at the Air Force Arnold Engineering Development Complex in 2014. The resulting data from this impact test series are being analyzed to assess the fragments’ sizes/masses, materials/densities, shapes, and other parameters of interest. The DebriSat project provides the data needed to update NASA’s breakup models and size estimation models using the simulated orbital breakup of a modern, low Earth orbit spacecraft. Ultimately, over 200,000 fragments from this impact test will be stored at NASA Johnson Space Center (JSC) and further analyzed by the ODPO. This project will also use machine learning techniques to infer physical parameters of fragments embedded in the soft-catch foam used in the impact experiment. Applied to X-ray imagery of the foam panels, these techniques promise to minimize human-in-the-loop processes for fragment extraction and physical characterization. A brief overview of this project and data collected will be presented. Lastly, the ODPO provides various capabilities hosted at NASA JSC for optical inspections and measurements using a variety of techniques and scientific instrumentation to support both in situ and laboratory measurements. The ODPO’s Optical Measurement Center (OMC) is an advanced facility for photometric and spectroscopic laboratory measurements of targets, including fragments from the DebriSat project. The OMC simulates telescopic observations by using space-like illumination conditions and source-target-sensor orientation techniques. Additionally, the OMC is uniquely equipped to acquire pseudo-bidirectional reflectance distribution data for broadband photometric measurements, thus removing aspect angle dependencies that can affect target size estimates using the optical size estimation model. Narrow-band surface material characterization using spectroscopic instrumentation gives insight into how the albedo parameter – also important in the optical size estimation model – may vary depending on the state of the material. The OMC also performs simulations of photometric measurements using optical ray-tracing software to model the OMC optical throughput. In addition to the OMC, the ODPO houses a start-of-the-art Fragment Analysis Facility that uses multiple microscopic inspection instruments to support in situ measurements and material characterization. An overview of both facilities will be highlighted in this paper.

Orbital Debris↗

NASA NTRS2012

In the Pursuit of Regolithic Howardites

The HED (Howardite, Eucrite and Diogenite) meteorite clan likely originate from the asteroid 4-Vesta [1]. Howardites (polymict breccias of eucritic and diogenitic material) are believed to originate from the vestan surface, and many contain regolith-like features (impact and/or melt clasts, fragmental breccia clasts, carbonaceous chondrite fragments), which may relate to regolith-formation processes. Noble gas analysis can help determine true regolithic nature, as Solar Wind (SW) is im-planted into grains at the upper-surfaces of solar system bodies lacking an atmosphere or magnetic field. Howardites from Ves-ta s true regolith would thus show evidence for SW components. Thus far, we have identified 5 regolithic howardites: LEW 85313; MET 00423; PRA 04401; SCO 06040 and EET 87513; based on our noble gas analyses, with the latter 3 showing some evidence for a planetary(+SW) component, likely related to CM-like material present in the assemblage [2-5]. However, we did not find a good correlation between SW content and other petro-logic regolithic features. Nor did we find an obvious correlation between SW and high siderophile element contents (Ni greater than 300 micrograms/gram), or an Al2O3 range of 8-9 wt% and eucrite/diogenite (E/D) ratio of 2:1 as suggested by [6] to be further regolith indicators. Here, we report our latest noble gas data for two howardites GRO 95535, GRO 95602 and a polymict eucrite EET 87518 in continuing research aimed at better understanding the vestan regolith. Results: Noble gas analysis was performed on an MAP 215-50 noble gas mass spectrometer using furnace step-heating. Our results, shown in Table 1, are compared with SW- (LEW 85313) and planetary-dominated (PRA 04401 ~60% CM) howardites [2]. EET 87518 is dominated by cosmogenic components. By comparison, both howardites show strong evidence for SW, with total Ne-20/Ne-22 ~8.7-8.8 (SW: Ne-20/Ne-22 13.78 [7]), and identical release patterns to our other CM-poor SW-rich samples. This suggests that these samples are from the vestan regolith. As they have lower Ni contents than suggested by [6], this further illustrates that these parameters may show some bias [2].

Cartwright, J. A.↗

NASA NTRS2016

Craters of the Pluto-Charon System

NASA's New Horizons flyby mission of the Pluto-Charon binary system and its four moons provided humanity with its first spacecraft-based look at a large Kuiper Belt Object beyond Triton. Excluding this system, multiple Kuiper Belt Objects (KBOs) have been observed for only 20 years from Earth, and the KBO size distribution is unconstrained except among the largest objects. Because small KBOs will remain beyond the capabilities of ground-based observatories for the foreseeable future, one of the best ways to constrain the small KBO population is to examine the craters they have made on the Pluto-Charon system. The first step to understanding the crater population is to map it. In this work, we describe the steps undertaken to produce a robust crater database of impact features on Pluto, Charon, and their two largest moons, Nix and Hydra. These include an examination of different types of images and image processing, and we present an analysis of variability among the crater mapping team, where crater diameters were found to average +/-10% uncertainty across all sizes measured (approx.0.5-300 km). We also present a few basic analyses of the crater databases, finding that Pluto's craters' differential size-frequency distribution across the encounter hemisphere has a power-law slope of approximately -3.1 +/- 0.1 over diameters D approx. = 15-200 km, and Charon's has a slope of -3.0 +/- 0.2 over diameters D approx. = 10-120 km; it is significantly shallower on both bodies at smaller diameters. We also better quantify evidence of resurfacing evidenced by Pluto's craters in contrast with Charon's. With this work, we are also releasing our database of potential and probable impact craters: 5287 on Pluto, 2287 on Charon, 35 on Nix, and 6 on Hydra.

Robbins, Stuart J.↗

NASA NTRSDate not supplied

Initial analysis of “stone” size Ryugu samples: current status

As a part of the initial analysis of the Ryugu samples, we perform a variety of analyses of millimeter-sized "stones". Our goals are to elucidate the entire formation process of C-type asteroid Ryugu from the viewpoint of petrology and mineralogy ande obtain necessary information by sample analysis, and then simulate the formation of Ryugu based on the evidencef obtained rom sample analysis. Eighteen stones (8 from Room A and 10 from Room C) were received from the ISAS curation facility on June 1, 2021, and brought into a fully nitrogen-displaced glove box at Tohoku University. At the same time, we also received the powder samples from Room A and Room C. To completely block the atmosphere from leaking into the container, all samples were put in the sample transport containers prepared by ISAS, transferred from the main chamber to the glovebox at ISAS, and then all containers were completely sealed in plastic bags with moisture and oxygen absorbers. No moisture or oxygen was detected when the bags were opened in the glove box at Tohoku University, so it was confirmed that there was no exposure to the atmosphere during transport. To date, a number of analyses have been carried out successfully and almost on schedule. The analysis started with the measurement of reflectance spectra, which are sensitive to atmospheric oxidation, hydroxylation, and adsorbed water. The visible, near-infrared, and mid-infrared reflectance spectra were measured while the samples were kept airtight. The spectra of powder samples and stone samples (as aggregates and as single stone) were successfully obtained. A major feature of the stone team's analysis is the use of synchrotron radiation facilities around the world. Since this analysis is non-destructive, stone samples whose reflectance spectra were measured were sent to KEK, SPring-8, ESRF (France), SOLEIL (France), DESY (Germany), and APS (USA). Using these synchrotron radiation facilities, high spatial resolution and sensitivity XRD, STXM, XANES, CT [1], IR-CT, FT-IR [2, 3], XRF, and Mössbauer analyses were performed. Most of the analyses were carried out under air-tight conditions on the stone samples and the particulates separated from the stone samples. These analyses allowed us to determine the three-dimensional distribution of minerals and elements, redox state, density and porosity of the stone samples. Furthermore, as a characteristic analysis of the stone team, light elemental analysis using negative Muon was performed at the MLF facility of J-PARC with an exceptionally long allocation of machine time. This is the only non-destructive method to measure the concentration of light elements in the whole (not the surface) of stone samples. Because the characteristic X-rays produced by muon irradiation are much higher in energy than the fluorescent X-rays produced by X-ray irradiation, there is little effect of self-absorption by the sample, and therefore, the concentration of light elements such as carbon, oxygen, and Na in the entire "stone" sample can be determined. Some stone samples are currently being measured for heat and strength physical properties in order to understand the physical properties of asteroid Ryugu. The data obtained from these measurements are useful for interpreting the remote-sensing data data taken from the surface layer of the asteroid Ryugu [4-7]. It is also important for understanding the behavior of the Ryugu material during impact events. The surfaces of many stone samples were observed by electron microscopy and other techniques, especially on natural “flat” surfaces formed on 5 stomes. As a result, characteristric mineral aggregates formed by the reactions with water and characteiristic impact features were observed on some of the samples. Based on the observations of surfaces and the synchrotron measurements of the whole stones, important objects such as characteristic structures and specific crystal aggregates for understanding the formation history of the asteroid were identified, and these parts were separated from the stone samples using an Xe beam (pFIB) and analyzed by various methods including transmission electron microscopy and synchrotron radiation analysis. Many stone samples, from which important objects have been separated, are embedded in epoxy resin and cut to produce many polished sections. Electron microscopy and spectroscopic measurements of the polished surfaces are being carried out to reveal the detailed mineralogical properties and elemental distribution inside the stone samples. In the fall, machine time for synchrotron radiation will begin, and we plan to analyze single crystals and characteristic objects separated from the stone samples.

Tomoki Nakamura↗

DOE OSTI2022

Performance and power modeling and prediction using MuMMI and 10 machine learning methods

Energy-efficient scientific applications require insight into how high performance computing system features impact the applications' power and performance. This insight can result from the development of performance and power models. Here, in this article, we use the modeling and prediction tool MuMMI (Multiple Metrics Modeling Infrastructure) and 10 machine learning methods to model and predict performance and power consumption and compare their prediction error rates. We use an algorithm-based fault-tolerant linear algebra code and a multilevel checkpointing fault-tolerant heat distribution code to conduct our modeling and prediction study on the Cray XC40 Theta and IBM BG/Q Mira at Argonne National Laboratory and the Intel Haswell cluster Shepard at Sandia National Laboratories. Our experimental results show that the prediction error rates in performance and power using MuMMI are less than 10% for most cases. By utilizing the models for runtime, node power, CPU power, and memory power, we identify the most significant performance counters for potential application optimizations, and we predict theoretical outcomes of the optimizations. Based on two collected datasets, we analyze and compare the prediction accuracy in performance and power consumption using MuMMI and 10 machine learning methods.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Investigating explainable transfer learning for battery lifetime prediction under state transitions

Battery lifetime prediction at early cycles is crucial for researchers and manufacturers to examine product quality and promote technology development. Machine learning has been widely utilized to construct data-driven solutions for high-accuracy predictions. However, the internal mechanisms of batteries are sensitive to many factors, such as charging/discharging protocols, manufacturing/storage conditions, and usage patterns. These factors will induce state transitions, thereby decreasing the prediction accuracy of data-driven approaches. Transfer learning is a promising technique that overcomes this difficulty and achieves accurate predictions by jointly utilizing information from various sources. Hence, we develop two transfer learning methods, Bayesian Model Fusion and Weighted Orthogonal Matching Pursuit, to strategically combine prior knowledge with limited information from the target dataset to achieve superior prediction performance. From our results, our transfer learning methods reduce root-mean-squared error by 41% through adapting to the target domain. Furthermore, the transfer learning strategies identify the variations of impactful features across different sets of batteries and therefore disentangle the battery degradation mechanisms and the root cause of state transitions from the perspective of data mining. These findings suggest that the transfer learning strategies proposed in our work are capable of acquiring knowledge across multiple data sources for solving specialized issues.

25 ENERGY STORAGE↗

DOE OSTI2024

An analytic theory for the degree of Arctic Amplification

Arctic Amplification (AA), the amplified surface warming in the Arctic relative to the global mean, is a robust and impactful feature of climate change. While the basic physical picture of AA has been depicted, a clear understanding of how the degree of AA is determined has not been established. Here, by deciphering the intricate role of atmospheric heat transport (AHT), we build a two-box energy-balance model of AA and derive that the degree of AA is a simple nonlinear function of the Arctic and global feedbacks, the meridional heterogeneity in radiative forcing, and the partial sensitivities of AHT to global mean warming and meridional warming gradient. The formula captures the varying degree of AA in individual climate models and attributes the variation to specific physical factors. It further conveys a concise picture of how essential physics mutually determine the degree of AA and limit the range within 1.5~3.5. Our results articulate AHT as both forcing and feedback to AA, highlighting its partial sensitivities instead of total change as the key parameters for understanding AA. We also find that the effect of lapse rate feedback, a widely-recognized major contributor to AA, is fully offset by the effect of water vapor feedback.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

A detailed study of interpretability of deep neural network based top taggers

Abstract Recent developments in the methods of explainable artificial intelligence (XAI) allow researchers to explore the inner workings of deep neural networks (DNNs), revealing crucial information about input–output relationships and realizing how data connects with machine learning models. In this paper we explore interpretability of DNN models designed to identify jets coming from top quark decay in high energy proton–proton collisions at the Large Hadron Collider. We review a subset of existing top tagger models and explore different quantitative methods to identify which features play the most important roles in identifying the top jets. We also investigate how and why feature importance varies across different XAI metrics, how correlations among features impact their explainability, and how latent space representations encode information as well as correlate with physically meaningful quantities. Our studies uncover some major pitfalls of existing XAI methods and illustrate how they can be overcome to obtain consistent and meaningful interpretation of these models. We additionally illustrate the activity of hidden layers as neural activation pattern diagrams and demonstrate how they can be used to understand how DNNs relay information across the layers and how this understanding can help to make such models significantly simpler by allowing effective model reoptimization and hyperparameter tuning. These studies not only facilitate a methodological approach to interpreting models but also unveil new insights about what these models learn. Incorporating these observations into augmented model design, we propose the particle flow interaction network model and demonstrate how interpretability-inspired model augmentation can improve top tagging performance.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

Expansion of Machine-Learning Method for Classifying Neutron Resonances

The understanding of astrophysics processes and the performance of nuclear reactors and other nuclear systems depend on a precise description of the neutron interaction cross sections for materials and nuclei present in these environments. At low neutron energies, these cross sections exhibit resonance structure represented by sharp enhancements when the neutron energy is sufficiently close to excited levels in a compound nucleus. Such resonances can be characterized by their quantum numbers relative to angular momenta, which are often deduced in an ad hoc and irreproducible manner from the shape of the cross sections. The correct assignment of the quantum numbers of neutron resonances is therefore of paramount importance. To address this we have developed a machine-learning method to automate the identification and correction of these spin assignments. The algorithm is trained from simulated data, generated from statistical properties of resonance data for a given nucleus, to mimic the errors found in real data. In this project we describe five independent approaches to further develop and expand the applicability of the machine-learning spin classifier: i) Feature impact; ii) Integration with the Atlas; iii) Training optimization; iv) Spacings systematics; and v) Validation with polarized data. The premises, methods, results, and future perspectives are discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

NASA NTRS1973

An overview of geologic results from Mariner 9

A summary of Mariner 9 mission operations insofar as they affected acquisition of geologic data is reported. Selected results with a minimum of supporting evidence are presented to give the geologic highlights of the mission. Volcanic features, tectonic features, channels, polar features, eolian features, impact craters, and the geological history of Mars are outlined.

Masursky, H.↗

NASA NTRS1972

Lunar glasses, breccias, and chondrules.

Glasses from Apollo 11, 12, 14, and 15 soil samples have been grouped on the basis of their chemistry and appear to provide an independent tool for identifying the presence of various rock types. The glasses also appear to constitute a record of complex differentiation processes that seem to have taken place within the moon. A green glass, abundant in some samples from Hadley Delta, could have been formed from a previously proposed differentiation model. Four breccias are described briefly and certain similarities between impact features, including chondrules, in lunar samples and meteorites are noted.

Nellen, J.↗

NASA NTRS1973

Mars - Crustal structure inferred from Bouguer gravity anomalies.

Bouguer gravity has been computed for the equatorial region of Mars by differencing free air gravity and the gravity predicted from topographic variations. The free air gravity was generated from an eighth-order set of spherical harmonic coefficients. The gravity from topographic variations was generated by integrating a two-dimensional Green's function over each contour level. The Bouguer gravity indicates crustal inhomogeneities on Mars that are postulated to be variations in crustal thickness. The Tharsis ridge is a region of thick continental type crust. The gravity data, structural patterns, topography, and surface geology of this region lead to the interpretation of the Tharsis topographic high as a broad crustal upwarp possibly associated with local formation of lower-density crustal material and subsequent rise of a thicker crust. The Amazonis region is one of several basins of relatively thin crust, analogous to terrestrial ocean basins. The Libya and Hellas basins, which are probable impact features, are also underlain by thin crust and are possible regions of mantle upwelling.

Phillips, R. J.↗

NASA NTRS1974

Preliminary results of the Apollo 17 infrared scanning radiometer

The thermal emission of the lunar surface has been mapped by an infrared scanner from lunar orbit. Samples from approximately 250,000 scans reveal the full range of lunar temperatures from 80 to 400 K. The temperature resolution was 1 K with about plus or minus 2 K absolute precision. Spatial resolution was approximately 2 km over most of the horizon-to-horizon scan. The total mapped area amounted to approximately 30% of the lunar surface. The data currently available confirms the large population of nighttime thermal anomalies in western Oceanus Procellarum predicted by earth-based observations. Most of these 'hot spots' are associated with fresh impact features or boulder fields. Also seen in the data are 'cold spots' where the local nighttime temperature is depressed relative to the general soil background. Such regions exhibiting low surface conductivity are inferred to be relatively young, nonimpact features.

Mendell, W. W.↗