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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRSDate not supplied

Investigation of the Glen Torridon Clay-Bearing Unit and Overlying Greenheugh Pediment by the Sample Analysis at Mars Instrument Suite

Exploring the Glen Torridon (GT) clay-bearing unit in Gale crater has long been a prime goal for the Mars Science Laboratory (MSL) because of spectral signatures of smectite identified from orbit. Smectite clay minerals can indicate habitable environments [1,2] and possibly facilitate the preservation of organic compounds [e.g., 3-7].Also, sulfate-bearing layers overlie GT and this sequence may record a large-scale change in aqueous conditions overtime [8].The Sample Analysis at Mars (SAM) instrument suitehas been essential in understanding volatile-bearing phases in Gale crater materials. SAM EGA has detected H2O, CO2, O2, H2, SO2, H2S, HCl, NO, and other trace gases, including organic fragments, evolved from many samples on heating. The identity and evolution temperature of evolved gases can support mineral detection by CheMin instrument X-ray diffraction (XRD)and place constraints on trace volatile-bearing phases, clay mineral compositions, and X-ray amorphous materials. In GT, SAM analyzed the sample Kilmarie (KM) from the Jura member, Glen Etive (GE), Mary Anning (MA) and Groken (GR)from the Knockfarril Hill member (KHm), Glasgow (GG) and Hutton (HU) from the fractured Intermediate Unit (fIU), and Edinburgh (EB) from the Stimson formation rocks of the Greenheugh Pediment (GP). The Jura, KHm and fIU are all members of the Murray formation. HU was sampled near the basal Siccar Point group (SPg) unconformity between the fIU and GP, in an area that exhibits a brighter tone and differences in geochemistry compared to Murray materials down-section [9,10]. CheMin XRD of most samples (except for HU and EB)showed large abundances of smectite clay minerals (~25-35%) and all samples showed X-ray amorphous materials and relatively low amounts of well-crystalline hematite[11]. SAM evaluated mineralogy through evolved gas analysis mass spectrometry (EGA) while detailed organic chemistry of several samples was examined by pyrolysis gas chromatography mass spectrometry and wet chemistry experiments [12,13].Here we discuss data and interpretations from SAM EGA analyses.

Mars↗
NASA NTRS2011

Lunar Reconnaissance Orbiter (LRO) Observations with the Lunar Exploration Neutron Detector (LEND): Neutron Suppression Regions (NSR) and Polar Hydrogen

Orbital detection of neutrons has become the dominant remote sensing technique for detecting and inferring H concentrations and its spatial distribution beneath planetary surfaces [Lawrence et al, (2010) Icarus, 205, pp. 195-209, Mitrofanov et al (2007) Science 297(5578), 78-81]. Indications for the presence of localized and relatively high water content was provided by LRO and LCROSS. LEND identified Cabeus, as the most promising LCROSS impact site [Mitrofanov I. et al. (2010) Science, 330, 483], and instruments onboard LRO and LCROSS have measured signatures of water, H2 and other volatiles in the impact plume [Colaprete A. et al. (2010) Science, 339,463, Gladstone R. et al. (2010) Science, 330, 472].

Chin, G.↗
NASA NTRS1996

(abstract) Topographic Signatures in Geology

Topographic information is required for many Earth Science investigations. For example, topography is an important element in regional and global geomorphic studies because it reflects the interplay between the climate-driven processes of erosion and the tectonic processes of uplift. A number of techniques have been developed to analyze digital topographic data, including Fourier texture analysis. A Fourier transform of the topography of an area allows the spatial frequency content of the topography to be analyzed. Band-pass filtering of the transform produces images representing the amplitude of different spatial wavelengths. These are then used in a multi-band classification to map units based on their spatial frequency content. The results using a radar image instead of digital topography showed good correspondence to a geologic map, however brightness variations in the image unrelated to topography caused errors. An additional benefit to the use of Fourier band-pass images for the classification is that the textural signatures of the units are quantative measures of the spatial characteristics of the units that may be used to map similar units in similar environments.

topography geology texture Fourier analysis↗
NASA NTRS2004

Space Technology 5: Pathfinder for Future Micro-Sat Constellations

The Space Technology 5 (ST-5) Project, currently in the implementation phase, is part of the National Aeronautics and Space Administration (NASA) s New Millennium Program (NMP). ST-5 will consist of a constellation of three miniature satellites, each with mass less than 25 kg and size approximately 60 cm by 30 cm. ST-5 addresses technology challenges, as well as fabrication, assembly, test and operations strategies for future micro-satellite missions. ST-5 will be deployed into a highly eccentric, geo-transfer orbit (GTO). This will expose the spacecraft to a high radiation environment as well as provide a low level magnetic background. A three-month flight demonstration phase is planned to validate the technologies and demonstrate concepts for future missions. Each ST-5 spacecraft incorporates NMP competitively-selected breakthrough technologies. These include Cold Gas Micro-Thrusters for propulsion and attitude control, miniature X-band transponder for space-ground communications, Variable Emittance Coatings for dynamic thermal control, and CULPRiT ultra low power logic chip used for Reed-Solomon encoding. The ST-5 spacecraft itself is a technology that can be infused into future missions. It is a fully functional micro-spacecraft built within tight volume and mass constraints. It is built to withstand a high radiation environment, large thermal variations, and high launch loads. The spacecraft power system is low-power and low-voltage, and is designed to turn on after separation &om the launch vehicle. Some of the innovations that are included in the ST-5 design are a custom spacecraft deployment structure, magnetometer deployment boom, nutation damper, X-band antenna, miniature spinning sun sensor, solar array with triple junction solar cells, integral card cage assembly containing single card Command and Data Handling and Power System Electronics, miniature magnetometer, and lithium ion battery. ST-5 will demonstrate the ability of a micro satellite to perform research-quality science. Each ST-5 spacecraft will deploy a precision magnetometer to be used both for attitude determination and as a representative science instrument. The spacecraft has been developed with a low magnetic signature to avoid interference with the magnetometer. The spacecraft will be able to detect and respond autonomously to science events, i.e. significant changes in the magnetic field measurements. The three spacecraft will be a pathfinder for future constellation missions. They will be deployed to demonstrate an appropriate geometry for scientific measurements as a constellation. They will be operationally managed as a constellation, demonstrating automation and communication strategies that will be useful for future missions. The technologies and future mission concepts will be validated both on the ground and in space. Technologies will be validated on the ground by a combination of component level and system level testing of the flight hardware in a thermal vacuum environment. In flight, specific validation runs are planned for each of the technologies. Each validation run consists of one or more orbits with a specific validation objective. This paper will describe the ST-5 mission, and the applicability of the NMP technologies, spacecraft, and mission concepts to future missions. It will also discuss the validation approach for the ST-5 technologies and mission concepts.

Carlisle, Candace↗
NASA NTRS2017

Kepler: A Search for Terrestrial Planets. K2 Handbook

The Kepler spacecraft was repurposed for the K2 mission a year after the failure of the second of Kepler's four reaction wheels in 2013 May. The purpose of this document, the K2 Handbook (K2H), is to describe features of K2 operations, performance, data analysis, and archive products which are common to most K2 campaigns, but different in degree or kind from the corresponding features of the Kepler mission.The K2 Handbook is meant to be read with the following companion documents, which are all publicly available:1. Kepler Instrument Handbook (KSCI-19033) provides information about the design, performance and operational constraints of the instrument and an overview of the types of pixel data that are available.2. Kepler Data Processing Handbook (KSCI-19081) describes how pixels downloaded from the spacecraft are converted by the Kepler Data Processing Pipeline into the data products available at the MAST archive3. Kepler Archive Manual (KDMC-100008) describes the format and content of the data products and how to search for them.4. Kepler Data Characteristics Handbook (KSCI-19040) describes recurring non-astrophysical features of the Kepler data due to instrument signatures, spacecraft events or solar activity and explains how these characteristics are handled by the Kepler pipeline.5. The Ecliptic Plane Input Catalog describes the provenance of the positions and Kepler magnitudes used for target management and aperature photometry.6. K2 Data Release Notes (DRN) are on-line documents available on the K2 science website which describe the data inventory, instrumental signatures and events peculiar to individual observing campaigns.

K2↗
NASA NTRS1992

Electrons in the ionosphere of Titan

A theoretical model of the spatial and energy distribution of electrons in the ionosphere of Titan has been constructed using the two-stream electron transport method and the electron energy equation. The calculated electron spectra show abrupt decreases that can contribute to the 'bite-out' signature observed by the Voyager 1 plasma science instrument. Energy deposition rates in the exosphere of Titan by photoelectrons and magnetospheric electrons are calculated. Calculated N2 EUV airglow emission rates lead to the conclusion that airglow emission due to photoelectron impact is much more important than airglow emission due to magnetospheric electron interactions. Thermal electron temperatures at Titan are calculated for the first time. The electron gas remains well thermalized with the neutral atmosphere for radial distances from the center of Titan less than 3500 km. For radial distances beyond about 4000 km, energy transport dominates the energetics, and the electrons are almost isothermal along magnetic field lines.

Gan, L.↗
NASA NTRS2017

Field Exploration and Life Detection Sampling Through Planetary Analogue Sampling (FELDSPAR).

Exploration missions to Mars rely on rovers to perform analyses over small sampling areas; however, landing sites for these missions are selected based on large-scale, low-resolution remote data. The use of Earth analogue environments to estimate the multi-scale spatial distributions of key signatures of habitability can help ensure mission science goals are met. A main goal of FELDSPAR is to conduct field operations analogous to Mars sample return in its science, operations, and technology from landing site selection, to in-field sampling location selection, remote or stand-off analysis, in situ analysis, and home laboratory analysis. Lava fields and volcanic regions are relevant analogues to Martian landscapes due to desiccation, low nutrient availability, and temperature extremes. Operationally, many Icelandic lava fields are remote enough to require that field expeditions address several sampling constraints that are experienced in robotic exploration, including in situ and sample return missions. The Fimmvruhls lava field was formed by a basaltic effusive eruption associated with the 2010 Eyjafjallajkull eruption. Mlifellssandur is a recently deglaciated plain to the north of the Myrdalsjkull glacier. Holuhraun was formed by a 2014 fissure eruptions just north of the large Vatnajkull glacier. Dyngjusandur is an alluvial plain apparently kept barren by repeated mechanical weathering. Informed by our 2013 expedition, we collected samples in nested triangular grids every decade from the 10 cm scale to the 1 km scale (as permitted by the size of the site). Satellite imagery is available for older sites, and for Mlifellssandur, Holuhraun, and Dyngjusandur we obtained overhead imagery at 1 m to 200 m elevation. PanCam-style photographs were taken in the field by sampling personnel. In-field reflectance spectroscopy was also obtained with an ASD spectrometer in Dyngjusandur. All sites chosen were 'homogeneous' in apparent color, morphology, moisture, grain size, and reflectance spectra at all scales greater than 10 cm. Field lab assays were conducted to monitor microbial habitation, including ATP quantification, qPCR for fungal, bacterial, and archaeal DNA, and direct cell imaging using fluorescence microscopy. Home laboratory analyses include Raman spectroscopy and community sequencing. ATP appeared to be significantly more sensitive to small changes in sampling location than qPCR or fluorescence microscopy. Bacterial and archaeal DNA content were more consistent at the smaller scales, but similarly variable across more distant sites. Conversely, cell counts and fungal DNA content have significant local variation but appear relatively homogeneous over scales of 1 km. ATP, bacterial DNA, and archaeal DNA content were relatively well correlated at many spatial scales. While we have observed spatial variation at various scales and are beginning to observe how that variation fluctuates over time as biodiversity recovers after an eruption, we do not yet fully understand what parameters lead to the observed spatial variation. Home laboratory analyses will help us further understand the elemental and structural composition of the basaltic matrices, but further field analyses are vital for the understanding how temperature, moisture, incident radiation, and so forth influence the habitability of a microclimate.

Field↗
NASA NTRS2021

Mars 2020 Radiometric Data and Telemetry Processing, Attitude Estimation, and Thruster Calibration for Orbit Determination

The Mars 2020 spacecraft was spin-stabilized during cruise, just like its predecessor, the Mars Science Laboratory. This spinning motion imparts a signature in the radiometric tracking data that must be dealt with in order to properly model the motion of the spacecraft's center of mass. We discuss how the Orbit Determination team pre-processed the data for efficient computations while also providing other benefits such as high-fidelity attitude modeling and on-board clock verification. Finally, we discuss the analysis and results of the in-flight thruster calibration activity.

Seubert, Jill↗
DOE OSTI2021

Advancing Enhanced Raman Spectroscopy to Detect and Measure NOW Pheromones (CPRB 2022 proposal)

Insect sex pheromones are chemical compounds that insects release to attract their partners over distances of hundreds of meters or even kilometers, in complete darkness and without any audible signals. Use of synthetic forms of key compounds have in some cases become an essential component of monitoring and/or managing key pests of agricultural crops, including navel orangeworm (Amyelois transitella) (NOW) in California tree nuts. These pheromone-based strategies can include monitoring, mating disruption, mass trapping, attract-and-kill and push-pull. There are currently multiple commercially available mating disruption products available for NOW and recent studies have demonstrated that they can be effectively used to reduce crop damage by this pest. Just how mating disruption works is not fully established and likely varies across products and target species. For instance, the extent to which synthetic pheromones compete with natural pheromone is not well understood, or in the case of monitoring, how efficaciously the insect follows the diffusing plumes, especially across large blocks and at plot borders. Furthermore, there may be specific conditions under which poor or impeded diffusion of synthetic pheromone diminishes the disruption effect, which could result in some males effectively locating females for reproduction. At the same time, many commercially available synthetic lures are also available, and growers have been effectively using them to track population development – although the attractive range of these lures remains unclear. That is, while pheromone lures can attract many moths, the relationship between trap capture and local populations, much less crop damage, remains unclear. Regardless of the emission source (aerosol puffers, meso emitters, lures etc.), we currently lack the ability to fully understand how these synthetic pheromone compounds diffuse away from their point-source of emission – and subsequently how this might affect the efficacy of mating disruption and/or the accuracy of monitoring efforts. Raman spectroscopy (RS) may offer a means to detect synthetic pheromone because of its analytical properties and recent technological advancements. In combination with nanostructured probes, RS has a demonstrated capability to detect volatiles at extremely low concentrations. While other methods for detecting pheromones have proven to be successful, such analytical methods like mass spectrometry (MS) gas chromatography (GC) require sampling in the fields and are not real-time. Other methods such as EAG/ EAD are also invasive (use antennas) but are of course valuable. Opto-electronic, micro and nano sensors just recently enticed interest. We fall in this latter category, proposing the use of optical spectroscopy (Raman) in a fiber aided by nanostructures to provide a chemical fingerprint without transductions and in real-time (i.e. no sampling). To date, we have been able to generate Raman signatures for the main chemicals in synthetic pheromones (a first for science, to the best of our knowledge), observe their trends at different concentrations, and also provide a clear distinction of such signatures in mixed samples via Principal Component Analysis (PCA) – all of which strengthens our conclusions on the ability of RS to detect emissions in more realistic conditions. We also established processes to enhance the detection sensitivity via preconcentration with Solid Phase Micro Extraction (SPME) fibers and Surface Enhanced Raman Spectroscopy (SERS) to increase the overall optical signals. Furthermore, we explored limitations and requirements for detecting from dispensers, lures, or live moths, including Dept. of Energy and CA State regulatory approvals. Finally, we setup some of our first “orchard in a box” experiments to measure pheromone diffusion along with developing appropriate models.

42 ENGINEERING↗
DOE OSTI2022

Results of the first implementation of RF phase signature matching at LANSCE

The LINAC at the Los Alamos Neutron Science Center (LANSCE) has been utilizing the Delta-t method to match the RF cavities to the design acceleration parameters since its commissioning in 1972. The differences in time-of-flight between two subsequent Beam Position and Phase Monitors (BPPMs) are measured with both accelerated and drifting beams, depending on the whether the module is set to on or off. The algorithm optimizes the module amplitude and phase via iterative measurements if the initial phase is in the vicinity of the design value. With an upgrade to a faster readout system, a scan over the whole RF cavity phase range requires relatively less time than the classical optimization procedure. The Phase Scan Signature Matching (PSSM) method provides a time-efficient method that ensures the phase selection lands on the bunching side and empowers future analyses to build module-specific models. The PSSM also utilizes a direct model to determine the correct amplitude to sub-percent level instead of using linearized matrices. Furthermore, lacking a reliable energy measurement method in the LINAC, we measure the beam phases at two downstream locations to increase the precision of energy measurements. In this letter, we also discuss the sensitivities of PSSM, error propagation, and the implementation results for the 2019 and 2020 beam cycles.

47 OTHER INSTRUMENTATION↗
DOE OSTI2013

Research towards a systematic signature discovery process

In its most general form, a signature is a unique or distinguishing measurement, pattern, or collection of data that identifies a phenomenon (object, action, or behavior) of interest. The discovery of signatures is an important aspect of a wide range of disciplines from basic science to national security for the rapid and efficient detection and/or prediction of phenomena. Current practice in signature discovery is typically accomplished by asking domain experts to characterize and/or model individual phenomena to identify what might compose a useful signature. What is lacking is an approach that can be applied across a broad spectrum of domains and information sources to efficiently and robustly construct candidate signatures, validate their reliability, measure their quality, and overcome the challenge of detection -- all in the face of dynamic conditions, measurement obfuscation and noisy data environments. Our research has focused on the identification of common elements of signature discovery across application domains and the synthesis of those elements into a systematic process for more robust and efficient signature development. In this way, a systematic signature discovery process lays the groundwork for leveraging knowledge obtained from signatures to a particular domain or problem area, and, more generally, to problems outside that domain. This paper presents the initial results of this research by discussing a mathematical framework for representing signatures and placing that framework in the context of a systematic signature discovery process. Additionally, the basic steps of this process are described with details about the methods available to support the different stages of signature discovery, development, and deployment.

signature discovery↗
DOE OSTI2021

Machine Learning and Economic Models to Enable Risk-Informed Condition Based Maintenance of a Nuclear Plant Asset

The primary objective of this research is to address challenges in the implementation of risk-informed, condition-based predictive maintenance (PdM), which reduces operating costs while still maintaining the safety and reliability of commercial nuclear power plants (NPPs). To achieve the objective, risk models are being developed by taking advantage of advancements in data analytics, deep learning, machine learning (ML), and artificial intelligence (AI). The notable outcomes presented in the report include ? Development of a ML models using heterogeneous plant process and vibration data collected at different spatial and temporal resolutions from the Salem?s CWS to diagnose a circulating water pump (CWP) failure based on salient fault signatures. The developed diagnostic models are extendable to other faults associated with CWPs and CWP motors given associated fault signatures. ? Development of a natural language processing (NLP) technique to automatically classify the WO data into different categories. The developed NLP technique was validated on independent WO data. This automates the tedious and time-consuming activity of mining and classifying WOs by subject matter experts. ? Estimation of mean time between downtime (i.e., time duration between time instances when 1 or more CWPs are not available) and developed an approach to establish reliability of CWS components using unstructured WO data along with CWS plant process data. ? Formulation of economic model based on Markov chain models. The parameters of associated with the transition rate between different states of Markov chain models were estimated using WO data. The economic model formulation and discussion captures both time-independent and time-dependent parameter variation, leading to risk-informed decision-making.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2022

A Novel DNA Repair Gene Signature for Immune Checkpoint Inhibitor-Based Therapy in Gastric Cancer

Gastric cancer is a heterogeneous group of diseases with only a fraction of patients responding to immunotherapy. The relationships between tumor DNA damage response, patient immune system and immunotherapy have recently attracted attention. Accumulating evidence suggests that DNA repair landscape is a significant factor in driving response to immune checkpoint blockade (ICB) therapy. In this study, to explore new prognostic and predictive biomarkers for gastric cancer patients who are sensitive and responsive to immunotherapies, we developed a novel 15-DNA repair gene signature (DRGS) and its related scoring system and evaluated the efficiency of the DRGS in discriminating different molecular and immune characteristics and therapeutic outcomes of patients with gastric adenocarcinoma, using publicly available datasets. The results demonstrated that DRGS high score patients showed significantly better therapeutic outcomes for ICB compared to DRGS low score patients (p < 0.001). Integrated analysis of multi-omics data demonstrated that the patients with high DRGS score were characteristic of high levels of anti-tumor lymphocyte infiltration, tumor mutation burden (TMB) and PD-L1 expression, and these patients exhibited a longer overall survival, as compared to the low-score patients. Results obtained from HPA and IHC supported significant dysregulation of the genes in DRGS in gastric cancer tissues, and a positive correlation in protein expression between DRGS and PD-L1. Therefore, the DRGS scoring system may have implications in tailoring immunotherapy in gastric cancers. A preprint has previously been published (Yuan et al., 2021).

60 APPLIED LIFE SCIENCES↗
DOE OSTI2017

Contaminant source identification using semi-supervised machine learning

Identification of the original groundwater types present in geochemical mixtures observed in an aquifer is a challenging but very important task. Frequently, some of the groundwater types are related to different infiltration and/or contamination sources associated with various geochemical signatures and origins. The characterization of groundwater mixing processes typically requires solving complex inverse models representing groundwater flow and geochemical transport in the aquifer, where the inverse analysis accounts for available site data. Usually, the model is calibrated against the available data characterizing the spatial and temporal distribution of the observed geochemical types. Numerous different geochemical constituents and processes may need to be simulated in these models which further complicates the analyses. In this paper, we propose a new contaminant source identification approach that performs decomposition of the observation mixtures based on Non-negative Matrix Factorization (NMF) method for Blind Source Separation (BSS), coupled with a custom semi-supervised clustering algorithm. Our methodology, called NMFk, is capable of identifying (a) the unknown number of groundwater types and (b) the original geochemical concentration of the contaminant sources from measured geochemical mixtures with unknown mixing ratios without any additional site information. NMFk is tested on synthetic and real-world site data. Finally, the NMFk algorithm works with geochemical data represented in the form of concentrations, ratios (of two constituents; for example, isotope ratios), and delta notations (standard normalized stable isotope ratios).

54 ENVIRONMENTAL SCIENCES↗