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At least 217 records · Page 12

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NASA NTRS2013

Multi-Pass Quadrupole Mass Analyzer

Analysis of the composition of planetary atmospheres is one of the most important and fundamental measurements in planetary robotic exploration. Quadrupole mass analyzers (QMAs) are the primary tool used to execute these investigations, but reductions in size of these instruments has sacrificed mass resolving power so that the best present-day QMA devices are still large, expensive, and do not deliver performance of laboratory instruments. An ultra-high-resolution QMA was developed to resolve N2 +/CO+ by trapping ions in a linear trap quadrupole filter. Because N2 and CO are resolved, gas chromatography columns used to separate species before analysis are eliminated, greatly simplifying gas analysis instrumentation. For highest performance, the ion trap mode is used. High-resolution (or narrow-band) mass selection is carried out in the central region, but near the DC electrodes at each end, RF/DC field settings are adjusted to allow broadband ion passage. This is to prevent ion loss during ion reflection at each end. Ions are created inside the trap so that low-energy particles are selected by low-voltage settings on the end electrodes. This is beneficial to good mass resolution since low-energy particles traverse many cycles of the RF filtering fields. Through Monte Carlo simulations, it is shown that ions are reflected at each end many tens of times, each time being sent back through the central section of the quadrupole where ultrahigh mass filtering is carried out. An analyzer was produced with electrical length orders of magnitude longer than its physical length. Since the selector fields are sized as in conventional devices, the loss of sensitivity inherent in miniaturizing quadrupole instruments is avoided. The no-loss, multi-pass QMA architecture will improve mass resolution of planetary QMA instruments while reducing demands on the RF electronics for high-voltage/high-frequency production since ion transit time is no longer limited to a single pass. The QMA-based instrument will thus give way to substantial reductions of the mass of flight instruments.

Prestage, John D.↗

NASA NTRS2013

Investigation of International Space Station Major Constituent Analyzer Anomalous ORU 02 Performance

The Major Constituent Analyzer (MCA) is a mass spectrometer based system that measures the major atmospheric constituents on the International Space Station. In 2011, two MCA ORU 02 analyzer assemblies experienced premature on-orbit failures. These failures were determined to be the result of off-nominal ion source filament performance. Recent product improvements to ORU 02 designed to improve the lifetime of the ion pump also constrained the allowable tuning criteria for the ion source filaments. This presentation describes the filament failures as well as the corrective actions implemented to preclude such failures in the future.

Gardner, Ben D.↗

NASA NTRS2013

Soft Decision Analyzer

We describe the benefit of using closed-loop measurements for a radio receiver paired with a counterpart transmitter. We show that real-time analysis of the soft decision output of a receiver can provide rich and relevant insight far beyond the traditional hard-decision bit error rate (BER) test statistic. We describe a Soft Decision Analyzer (SDA) implementation for closed-loop measurements on single- or dual- (orthogonal) channel serial data communication links. The analyzer has been used to identify, quantify, and prioritize contributors to implementation loss in live-time during the development of software defined radios. This test technique gains importance as modern receivers are providing soft decision symbol synchronization as radio links are challenged to push more data and more protocol overhead through noisier channels, and software-defined radios (SDRs) use error-correction codes that approach Shannon's theoretical limit of performance.

Lansdowne, Chatwin↗

NASA NTRS2014

Analyzing Source Apportioned Methane in Northern California During DISCOVER-AQ-CA Using Airborne Measurements and Model Simulations

This study analyzes source apportioned methane (CH4) emissions and atmospheric concentrations in northern California during the Discover-AQ-CA field campaign using airborne measurement data and model simulations. Source apportioned CH4 emissions from the Emissions Database for Global Atmospheric Research (EDGAR) version 4.2 were applied in the 3-D chemical transport model GEOS-Chem and analyzed using airborne measurements taken as part of the Alpha Jet Atmospheric eXperiment over the San Francisco Bay Area (SFBA) and northern San Joaquin Valley (SJV). During the time period of the Discover-AQ-CA field campaign EDGAR inventory CH4 emissions were 5.30 Gg/day (Gg 1.0 109 grams) (equating to 1.9 103 Gg/yr) for all of California. According to EDGAR, the SFBA and northern SJV region contributes 30 of total emissions from California. Source apportionment analysis during this study shows that CH4 concentrations over this area of northern California are largely influenced by global emissions from wetlands and local/global emissions from gas and oil production and distribution, waste treatment processes, and livestock management. Model simulations, using EDGAR emissions, suggest that the model under-estimates CH4 concentrations in northern California (average normalized mean bias (NMB) -5 and linear regression slope 0.25). The largest negative biases in the model were calculated on days when hot spots of local emission sources were measured and atmospheric CH4 concentrations reached values 3.0 parts per million (model NMB -10). Sensitivity emission studies conducted during this research suggest that local emissions of CH4 from livestock management processes are likely the primary source of the negative model bias. These results indicate that a variety, and larger quantity, of measurement data needs to be obtained and additional research is necessary to better quantify source apportioned CH4 emissions in California and further the understanding of the physical processes controlling them.

Methane↗

NASA NTRS2014

Performance of the Linear Ion Trap Mass Spectrometer for the Mars Organic Molecule Analyzer (MOMA) Investigation on the 2018 Exomars Rover

The 2018 ExoMars rover mission includes the Mars Organic Molecule Analyzer (MOMA) investigation. MOMA will examine the chemical composition of samples acquired from depths of up to two meters below the martian surface, where organics may be protected from degradation derived from cosmic radiation and/or oxidative chemical reactions. When combined with the complement of instruments in the rover's Pasteur Payload, MOMA has the potential to reveal the presence of a wide range of organics preserved in a variety of mineralogical environments, and to begin to understand the structural character and potential origin of those compounds. The MOMA investigation is led by the Max Planck Institute for Solar System Research (MPS) with the mass spectrometer subsystem provided by NASA GSFC. MOMA's linear ion trap mass spectrometer (ITMS) is designed to analyze molecular composition of: (i) gas evolved from pyrolyzed powder samples and separated in a gas chromatograph; and, (ii) ions directly desorbed from crushed solid samples at Mars ambient pressure, as enabled by a pulsed UV laser system, fast-actuating aperture valve and capillary ion inlet. Breadboard ITMS and associated electronics have been advanced to high end-to-end fidelity in preparation for flight hardware delivery to Germany in 2015.

linear ion trap mass spectrometer↗

NASA NTRS2015

Soft Decision Analyzer and Method

A soft decision analyzer system is operable to interconnect soft decision communication equipment and analyze the operation thereof to detect symbol wise alignment between a test data stream and a reference data stream in a variety of operating conditions.

Steele, Glen F.↗

NASA NTRS2014

Analyzing a 35-Year Hourly Data Record: Why So Difficult?

At the Goddard Distributed Active Archive Center, we have recently added a 35-Year record of output data from the North American Land Assimilation System (NLDAS) to the Giovanni web-based analysis and visualization tool. Giovanni (Geospatial Interactive Online Visualization ANd aNalysis Infrastructure) offers a variety of data summarization and visualization to users that operate at the data center, obviating the need for users to download and read the data themselves for exploratory data analysis. However, the NLDAS data has proven surprisingly resistant to application of the summarization algorithms. Algorithms that were perfectly happy analyzing 15 years of daily satellite data encountered limitations both at the algorithm and system level for 35 years of hourly data. Failures arose, sometimes unexpectedly, from command line overflows, memory overflows, internal buffer overflows, and time-outs, among others. These serve as an early warning sign for the problems likely to be encountered by the general user community as they try to scale up to Big Data analytics. Indeed, it is likely that more users will seek to perform remote web-based analysis precisely to avoid the issues, or the need to reprogram around them. We will discuss approaches to mitigating the limitations and the implications for data systems serving the user communities that try to scale up their current techniques to analyze Big Data.

computational performance↗

NASA NTRS2015

Charge Analyzer Responsive Local Oscillations

The first transatlantic radio transmission, demonstrated by Marconi in December of 1901, revealed the essential role of the ionosphere for radio communications. This ionized layer of the upper atmosphere controls the amount of radio power transmitted through, reflected off of, and absorbed by the atmospheric medium. Low-frequency radio signals can propagate long distances around the globe via repeated reflections off of the ionosphere and the Earth's surface. Higher frequency radio signals can punch through the ionosphere to be received at orbiting satellites. However, any turbulence in the ionosphere can distort these signals, compromising the performance or even availability of space-based communication and navigations systems. The physics associated with this distortion effect is analogous to the situation when underwater images are distorted by convecting air bubbles. In fact, these ionospheric features are often called 'plasma bubbles' since they exhibit some of the similar behavior as underwater air bubbles. These events, instigated by solar and geomagnetic storms, can cause communication and navigation outages that last for hours. To help understand and predict these outages, a world-wide community of space scientists and technologists are devoted to researching this topic. One aspect of this research is to develop instruments capable of measuring the ionospheric plasma bubbles. Figure 1 shows a photo of the Charge Analyzer Responsive to Local Oscillations (CARLO), a new instrument under development at NASA Marshall Space Flight Center (MSFC). It is a frequency-domain ion spectrum analyzer designed to measure the distributions of ionospheric turbulence from 1 Hz to 10 kHz (i.e., spatial scales from a few kilometers down to a few centimeters). This frequency range is important since it focuses on turbulence scales that affect VHF/UHF satellite communications, GPS systems, and over-the-horizon radar systems. CARLO is based on the flight-proven Plasma Local Anomalous Noise Environment (PLANE) instrument, previously flown on a U.S. Air Force low-Earth orbiting satellite, which successfully measured ion turbulence in five frequency decades from 0.1 Hz to 10 kHz (fig 2).

Krause, Linda Habash↗

NASA NTRS2016

Soft Decision Analyzer and Method

Steele, Glen F.↗

NASA NTRS2017

International Space Station Major Constituent Analyzer On-Orbit Performance

The Major Constituent Analyzer (MCA) is a mass spectrometer based system that measures the major atmospheric constituents on the International Space Station. A number of limited-life components require periodic change-out, including the ORU 02 analyzer and the ORU 08 Verification Gas Assembly. The most recent ORU 02 and ORU 08 assemblies in the LAB MCA are operating nominally. For ORU 02, the ion source filaments and ion pump lifetime continue to be key determinants of MCA performance. Finally, the Node 3 MCA is being brought to an operational configuration.

Gardner, Ben D.↗

NASA NTRS2015

Analyzing Cyber Security Threats on Cyber-Physical Systems Using Model-Based Systems Engineering

The spectre of cyber attacks on aerospace systems can no longer be ignored given that many of the components and vulnerabilities that have been successfully exploited by the adversary on other infrastructures are the same as those deployed and used within the aerospace environment. An important consideration with respect to the mission/safety critical infrastructure supporting space operations is that an appropriate defensive response to an attack invariably involves the need for high precision and accuracy, because an incorrect response can trigger unacceptable losses involving lives and/or significant financial damage. A highly precise defensive response, considering the typical complexity of aerospace environments, requires a detailed and well-founded understanding of the underlying system where the goal of the defensive response is to preserve critical mission objectives in the presence of adversarial activity. In this paper, a structured approach for modeling aerospace systems is described. The approach includes physical elements, network topology, software applications, system functions, and usage scenarios. We leverage Model-Based Systems Engineering methodology by utilizing the Object Management Group's Systems Modeling Language to represent the system being analyzed and also utilize model transformations to change relevant aspects of the model into specialized analyses. A novel visualization approach is utilized to visualize the entire model as a three-dimensional graph, allowing easier interaction with subject matter experts. The model provides a unifying structure for analyzing the impact of a particular attack or a particular type of attack. Two different example analysis types are demonstrated in this paper: a graph-based propagation analysis based on edge labels, and a graph-based propagation analysis based on node labels.

MBSE↗

NASA NTRS2017

Mars Organic Molecule Analyzer (MOMA) Laser Desorption/Ionization Source Design and Performance Characterization

The Mars Organic Molecule Analyzer (MOMA), a dual-source, ion trap-based instrument capable of both pyrolysis-gas chromatography mass spectrometry (pyr/GC-MS) and laser desorption/ionization mass spectrometry (LDI-MS), is the core astrobiology investigation on the ExoMars rover. The MOMA instrument will be the first spaceflight mass analyzer to exploit the LDI technique to detect refractory organic compounds and characterize host mineralogy; this mode of analysis will be conducted at Mars ambient conditions. In order to achieve high performance in the Martian environment while keeping the instrument compact and low power, a number of innovative designs and components have been implemented for MOMA. These include a miniaturized linear ion trap (LIT), a fast actuating aperture valve with ion inlet tube, and a Microelectromechanical System (MEMS) Pirani sensor. Advanced analytical capabilities like Stored Waveform Inverse Fourier Transform (SWIFT) for selected ion ejection and tandem mass spectrometry (MS/MS) are realized in LDI-MS mode, and enable the isolation and enhancement of specific mass ranges and structural analysis, respectively. We report here the technical details of these instrument components as well as system-level analytical capabilities, and we review the applications of this technology to Mars and other high-priority targets of planetary exploration.

Xiang Li↗

NASA NTRS2013

Analyzing Carbon Dioxide and Methane Emissions in California Using Airborne Measurements and Model Simulations

Greenhouse gas (GHG) concentrations have increased over the past decades and are linked to global temperature increases and climate change. These changes in climate have been suggested to have varying effects, and uncertain consequences, on agriculture, water supply, weather, sea-level rise, the economy, and energy. To counteract the trend of increasing atmospheric concentrations of GHGs, the state of California has passed the California Global Warming Act of 2006 (AB-32). This requires that by the year 2020, GHG (e.g., carbon dioxide (CO2) and methane (CH4)) emissions will be reduced to 1990 levels. To quantify GHG fluxes, emission inventories are routinely compiled for the State of California (e.g., CH4 emissions from the California Greenhouse Gas Emissions Measurement (CALGEM) Project). The major sources of CO2 and CH4 in the state of California are: transportation, electricity production, oil and gas extraction, cement plants, agriculture, landfills/waste, livestock, and wetlands. However, uncertainties remain in these emission inventories because many factors contributing to these processes are poorly quantified. To alleviate these uncertainties, a synergistic approach of applying air-borne measurements and chemical transport modeling (CTM) efforts to provide a method of quantifying local and regional GHG emissions will be performed during this study. Additionally, in order to further understand the temporal and spatial distributions of GHG fluxes in California and the impact these species have on regional climate, CTM simulations of daily variations and seasonality of total column CO2 and CH4 will be analyzed. To assess the magnitude and spatial variation of GHG emissions and to identify local “hot spots”, airborne measurements of CH4 and CO2 were made by the Alpha Jet Atmospheric eXperiment (AJAX) over the San Francisco Bay Area (SFBA) and San Joaquin Valley (SJV) in January and February 2013 during the Discover-AQ-CA study. High mixing ratios of GHGs were observed in-flight with a high degree of spatial variability. To provide an additional method to quantify GHG emissions, and analyze AJAX measurement data, the GEOS-Chem CTM is used to simulate SFBA/SJV GHG measurements. A nested-grid version of GEOS-Chem will be applied and utilizes varying emission inventories and model parameterizations to simulate GHG fluxes/emissions. The model considers CO2 fluxes from fossil fuel use, biomass/biofuel burning, terrestrial and oceanic biosphere exchanges, shipping and aviation, and production from the oxidation of carbon monoxide, CH4, and non-methane volatile organic carbons. The major sources of CH4 simulated in GEOS-Chem are domesticated animals, rice fields, natural gas leakage, natural gas venting/flaring (oil production), coal mining, wetlands, and biomass burning. Preliminary results from the comparison between available observations (e.g., AJAX and CALGEM CH4 emission maps) and GEOS-Chem results will be presented, along with a discussion of CO2 and CH4 source apportionment and the use of the GEOS-Chem-adjoint to perform inverse GHG modeling.

Johnson, Matthew S.↗

NASA NTRS2019

The 2008 Mars Phoenix Lander Thermal and Evolved Gas Analyzer (TEGA) Dataset: Placing Easily Interpretable Evolved Gas Data on the Planetary Data System (PDS)

The Phoenix Scout Lander mission investigated the north polar region of Mars in 2008 with the goal to study the history of water, assess the past/present Martian climate, search for organics, and evaluate the potential for past/present microbial habit-ability on Mars. To accomplish this goal, the Phoenix Lander’s Thermal and Evolved-Gas Analyzer (TEGA) instrument assessed the gas composition of the Martian atmosphere and evaluated the mineralogy of the Martian regolith. The TEGA instrument consisted of eight small ovens connected to a 4 channel magnetic sector mass spectrometer. The ovens heated soil samples from ambient to 1000°C where the gases (e.g., H2O, CO2, etc.) evolved from thermal decomposition of mineral phases were analyzed by the mass spectrometer. Minerals thermally decomposed at characteristic temperatures and the evolving gases indicated the presence of perchlorate, carbonate, and hydrated phases in the Phoenix landing site soils.

Garcia, A. H.↗

NASA NTRS2020

Precision Assessment of the HPLC Phytoplankton Pigment Dataset Analyzed by NASA to Quantify Global Variability in Support of Ocean Color Remote Sensing

The ability to generate chlorophyll a (Chl a) assessments from ocean color orbital sensors, such as VIIRS and MODIS, that satisfy the requirements to be climate-quality data record (CDR) quality is contingent in part on the quality of the in situ ground or sea truth observations that serve as datasets for vicarious calibration and algorithm validation activities. NASA has a mandate to collect, analyze, and distribute in situ data of the highest possible quality with documented uncertainties and in keeping with established performance metrics. Using a dataset of over 18,000 HPLC phytoplankton pigment samples representing water collected in all major ocean basins analyzed a central laboratory (Field Support Group (FSG) of the Ocean Ecology Laboratory (OEL) at NASA Goddard Space Flight Center (GSFC)), we performed an assessment of the global precision among sample replicates of Chl a as well as major accessory pigments. We investigated the impacts of filtration volume, water basin, collection technique, pigment concentration, and different filtration volumes for replicate filters on replicate filter precision, as well as investigating any pigment-specific differences. Our results quantify sample variability with the goal of understanding any systemic biases or biogeographic influences.

Thomas, Crystal S.↗

NASA NTRSDate not supplied

In-Situ Reaction Monitoring for Lunar Applications Utilizing a Single Quadrupole Residual Gas Analyzer

With a revived focus to create a permeant presence on the moon and in preparation for future Mars exploration, it is imperative that all re-sources are utilized to their fullest potential. In-Situ Resource Utilization (ISRU) will be critical for future mission success as it would enable independent operation of missions while minimally relying on the complex supply chain created between the Earth, moon and Mars. One of the most critical resources that have been identified for ISRU is the creation of liquid oxygen (O2) for not only breathable air, but also for rocket fuel. On the moon and potentially Mars, one of the most O2 rich resources is in the presence of regolith. Although there are numerous minerals within regolith and various processes to extract O2, this is not the scope of this paper. Since the O2 extraction method can vary, a critical standardized analytical method is needed to verify O2 (or oxygenated precursor compounds) for extraction efficiency and purity. Our group utilizes a modified consumer off-the-shelf (COTS), Residual Gas Analyzer (RGA) Single Quadrupole Mass Spectrometer (QMS). Due to the current field mission requirements, the gas analysis module will need to rely only on mass-to-charge ratios (m/z) and peak intensities to differentiate and quantitate targeted gas-phase reactants or products, i.e. carbon monoxide (CO), carbon dioxide (CO2), methane (CH4) and hydrogen (H2). However, due to solar wind implanted volatiles and various other compounds present in lunar regolith, such as nitrogen (N2), helium (He), and deuterium (D2), deconvolution and quantification of isobaric compounds becomes quite difficult. Specifically, the presence of N2 makes quantification of CO, an oxygenated precursor, difficult due to both compounds having a peak at m/z 28. Approaches to differentiate isobaric components: Initially, the solution to overcome isobaric overlap was to use isotopic ratios, particularly be-tween carbon-13 and nitrogen-15. Although limited literature discuss isotopic composition and attempt to quantify the ratios, variation is particularly high and limited to a few lunar regolith samples. The following were identified as potential approaches to quantify isobaric species, N2 and CO, using our RGA. Threshold Ionization. CO and N2 both have peaks at m/z 28, but only N2 is capable of producing a peak at m/z 7. While a N2 peak at m/z 7 is generally rare, instrument parameters can be optimized in order to maximize the peak intensity. Typically a standard ionization energy of 70 eV is used to monitor a batch process and would produce reliable results for a majority of the reactants or products that we are interested in quantifying. However, to analyze the rare molecular fragment of N2 (N2+ at m/z 7), a different ionization energy may be beneficial. Threshold Ionization Mass Spectrometry (TIMS) will be explored to optimize the N2+ peak at m/z 7 by varying parameters such as ionization energy and pressure. Therefore, a quantitative value at m/z 7 will be used to determine the product gas concentration of N2, which will be subtracted from the total concentration determined at m/z 28 enabling us to approximate the amount of CO. Secondary Detector (infrared gas detector, IR). Another approach to quantitate and differentiate be-tween isobaric components is to leverage alternative modes of detection. Unlike mass spectrometry, which generally uses a separation step prior to analysis (i.e. gas chromatography), IR produces energy that is specifically absorbed depending on the bond and configuration of the molecule. This technique could be leveraged since it is generally only active on non-symmetric molecules, i.e. CO. Utilizing concentrations of CO determined from another detector could help correct concentrations of CO obtained from the QMS. However, the inclusion of another detector adds additional mission requirements, such as power, software changes and avionics updates that add additional cost and schedule requirements.

mass spectrometry↗

NASA NTRSDate not supplied

Using Earth Observations to Analyze Vegetation Phenology and Climatology in Bhutan to Identify Forest Disturbance

Changes in climate in the Himalayan region cause variability in temperature, precipitation, and phenology. It can also impact the health of coniferous forest ecosystems including increased damage due to aggressive forest pests. Forest disturbance from bark beetle is a major concern in Bhutan, sometimes causing extensive tree mortality to pine and spruce forests. Climatological trends and changes in vegetation phenology were analyzed and incorporated into a tool in Google Earth Engine that identified patches of forest disturbance in Bhutan. Preprocessed phenology and meteorological data from the Advanced Very High-Resolution Radiometer (AVHRR) and Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS), along with Climate Hazards Center Infrared Precipitation with Station (CHIRPS), Famine Early Warning System Network Land Data Assimilation System (FLDAS), Sentinel-2 Multispectral Instrument (MSI), and Landsat 5 Thematic Mapper (TM), Landsat 7 Enhanced Thematic Mapper (ETM)+, and Landsat 8 Operational Land Imager (OLI) were used within the tool. Changes in temperature, precipitation, and phenology were analyzed throughout Bhutan, and forest disturbance caused by bark beetle was investigated in two districts of the country

Tashi Choden↗

NASA NTRS2020

Elastic wave analyzer for icy sub-surfaces (EWAIS) in the solar system

The sub-surface structures of water-bearing icy worlds (e.g., Europa, Enceladus, and Titan) and the structures of icy regions on Mars contain critical information about their origin and evolution. These bodies have been identified as high-priority targets in the NRC Planetary Science Decadal Survey, which noted a lack of technology readiness as one impediment to related missions. An Elastic Wave Analyzer for Icy Sub-surfaces (EWAIS) instrument is being developed to acquire data that can provide answers to fundamental science questions related to these bodies. The EWAIS instrument generates and receives elastic waves using an array of piezoelectric transducers capable of operating at temperatures as low as 30K. A developed breadboard acquires reflected signals from discontinuities in the traveled materials’ impedance (the product of wave velocity and density) along the wave path. Analysis of the acquired data can be used to determine the elastic properties, presence of cracks, locations of cavities and other discontinuities, as well as the thicknesses of ice and liquid layers. The EWAIS instrument is being developed with a novel dual-frequency transmitter array that will enable reaching distances of kilometers through ice, as well as resolving smaller acoustic reflectors nearer the EWAIS instrument. The selected dual frequencies correspond to two depth ranges that can be analyzed, with resolutions of tens of centimeters in the region of tens to hundreds of meters and tens of meters on the kilometers scale, respectively. The EWAIS will be applicable for operation from any in-situ platform, including surface assets (e.g., lander and rover) and sub-surface assets (e.g., melting probes).

Bar-Cohen, Y.↗