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At least 127 records · Page 7

Volatile Analyzer for Lunar Polar Missions

One of the major questions remaining for the future exploration of the Moon by humans concerns the presence of volatiles on our nearest neighbor in space. Observational studies, and investigations involving returned lunar samples and using robotic spacecraft infer the existence of volatile compounds particularly water [1]. It seems very likely that a volatile component will be concentrated at the poles in circumstances where low-temperatures exist to provide cryogenic traps. However, the full inventory of species, their concentration and their origin and sources are unknown. Of particular importance is whether abundances are sufficient to act as a resource of consumables for future lunar expeditions especially if a long-term base involving humans is to be established. To address some of these issues requires a lander designed specifically for operation at a high-lunar latitude. A vital part of the payload needs to be a volatile analyzer such as the Gas Analysis Package specifically designed for identification quantification of volatile substances and collecting information which will allow the origin of these volatiles to be identified [1]. The equipment included, particularly the gas analyzer, must be capable of operation in the extreme environmental conditions to be encountered. No accurate information yet exists regarding volatile concentration even for sites closer to the lunar equator (because of contamination). In this respect it will be important to understand (and thus limit) contamination of the lunar surface by extraneous material contributed from a variety of sources. The only data for the concentrations of volatiles at the poles comes from orbiting spacecraft and whilst the levels at high latitudes may be greater than at the equator, the volatile analyzer package under consideration will be designed to operate at the highest specifications possible and in a way that does not compromise the data.

Gibons, Everett K.↗

Mitigating Problems in Measuring Hypergolic Fuels

To monitor hydrazine concentrations accurately and safely, hydrazine is converted into a stable derivative that will be monitored and correlated to the actual hydrazine concentration. The hydrazine's reactivity is harnessed to produce a chemical reaction that will form a stable gas-phase derivative which will not react or decompose before it reaches the detector. Hydrazine, monomethylhydrazine, and unsymmetrical dimethylhydrazine belong to a class of compounds known as hypergolic fuels. These fuels self-ignite upon mixing with hypergolic oxidizer (dinitrogen tetroxide), without need of a spark or other ignition source. The resulting reaction produces thrust with exceptionally high energy, making these compounds particularly useful as rocket propellants. Hydrazines are also highly toxic and corrosive. The combined properties of reactivity, corrosivity, and toxicity present the potential for a leak, a disastrous situation in a hypergol-loaded system. Consequently, leak detection is of the utmost importance in protecting equipment and personnel. Hydrazine vapor quantification presents many challenges in addition to the safety concerns. The reactivity of these compounds causes thermal and catalytic decomposition, which results in significant losses. Further complications arise from the sticky nature of hydrazine. Molecules adsorb irreversibly to virtually any surface they make contact with before detection, which results in instrument drift. These properties make it difficult to accurately quantify hydrazines. Current analytical methods seek to minimize these interactions. After an extensive literature search to determine appropriate chemical reactions, a method was devised to quantify hydrazines, without the limitations of monitoring hydrazines.

Source record↗

Integrated analysis and applications

A select overview is provided of ongoing research focusing on the development and verification of integrated structural analysis and optimal design capabilities for advanced aerospace propulsion and power systems. Subjects discussed include the following: (1) Composites - analytical models (composite mechanics), integrated computational methods, and characterization of composite structural response and durability for resin-, metal-, and ceramic-matrix systems; (2) Advanced inelastic analysis - algorithm/numerical methods for more accurate and efficient analysis; (3) Constitutive modeling - theoretical formulation and characterization of thermoviscoplastic material behavior; (4) Computational simulation - engine structures from components to assembly, and up to an entire engine system subjected to simulated test-stand and mission load histories; (5) Probabilistic structural analysis - quantification of the effects of uncertainty in geometry, material, loads, and boundary conditions on structural response for true reliability assessment; and (6) Interdisciplinary optimization - incorporation of mathematical optimization and multidisciplinary analyses to provide streamlined, autonomous optimal design systems.

Hopkins, Dale A.↗

Instantaneous Wavenumber Estimation for Damage Quantification in Layered Plate Structures

This paper illustrates the application of instantaneous and local wavenumber damage quantification techniques for high frequency guided wave interrogation. The proposed methodologies can be considered as first steps towards a hybrid structural health monitoring/ nondestructive evaluation (SHM/NDE) approach for damage assessment in composites. The challenges and opportunities related to the considered type of interrogation and signal processing are explored through the analysis of numerical data obtained via EFIT simulations of damage in CRFP plates. Realistic damage configurations are modeled from x-ray CT scan data of plates subjected to actual impacts, in order to accurately predict wave-damage interactions in terms of scattering and mode conversions. Simulation data is utilized to enhance the information provided by instantaneous and local wavenumbers and mitigate the complexity related to the multi-modal content of the plate response. Signal processing strategies considered for this purpose include modal decoupling through filtering in the frequency/wavenumber domain, the combination of displacement components, and the exploitation of polarization information for the various modes as evaluated through the dispersion analysis of the considered laminate lay-up sequence. The results presented assess the effectiveness of the proposed wavefield processing techniques as a hybrid SHM/NDE technique for damage detection and quantification in composite, plate-like structures.

Mesnil, Olivier↗

Retinoid quantification by HPLC/MS(n)

Retinoic acid (RA) mediates most of the biological effects of vitamin A that are essential for vertebrate survival. It acts through binding to receptors that belong to the nuclear receptor transcription factor superfamily (Mangelsdorf et al. 1994). It is also a highly potent vertebrate teratogen. To determine the function and effects of endogenous and exogenous RA, it is important to have a highly specific, sensitive, accurate, and precise analytical procedure. Current analyses of RA and other retinoids are labor intensive, of poor sensitivity, have limited specificity, or require compatibility with RA reporter cell lines (Chen et al. 1995. BIOCHEM: Pharmacol. 50: 1257-1264; Creech Kraft et al. 1994. BIOCHEM: J. 301: 111-119; Lanvers et al. 1996. J. Chromatogr. B Biomed. Appl. 685: 233-240; Maden et al. 1998. DEVELOPMENT: 125: 4133-4144; Wagner et al. 1992. DEVELOPMENT: 116: 55-66). This paper describes an HPLC/mass spectrometry/mass spectrometry product ion scan (HPLC/MS(n)) procedure for the analysis of retinoids that employs atmospheric pressure chemical ionization MS. The retinoids are separated by normal-phase column chromatography with a linear hexane-isopropanol-dioxane gradient. Each retinoid is detected by a unique series of MS(n) functions set at optimal collision-induced dissociation energy (30% to 32%) for all MS(n) steps. The scan events are divided into three segments, based on HPLC elution order, to maximize the mass spectrometer duty cycle. The all-trans, 9-cis, and 13-cis RA isomers are separated, if desired, by an isocratic hexane-dioxane-isopropanol mobile phase. This paper describes an HPLC/MS(n) procedure possessing high sensitivity and specificity for retinoids.

NASA Discipline Developmental Biology↗

Voyager orbit determination at Jupiter

This paper summarizes the Voyager 1 and Voyager 2 orbit determination activity extending from encounter minus 60 days to the Jupiter encounter, and includes quantitative results and conclusions derived from mission experiences. The major topics covered include an identification and quantification of the major orbit determination error sources and a review of salient orbit determination results from encounter, with emphasis on the Jupiter approach phase orbit determination. Special attention is paid to the use of combined spacecraft-based optical observations and earth-based radiometric observations to achieve accurate orbit determination during the Jupiter encounter approach phase.

Campbell, J. K.↗

Uncertainty Quantification of Classical Theories of Dendritic Growth Kinetics Applied to Nickel-Based Alloys

The solidification velocity in a model nickel-alloy single crystal during laser spot melting was recently characterized using synchrotron X-ray imaging. The measured solidification velocity was found to exceed the absolute stability threshold predicted by the Kurz-Giovanola-Trivedi (KGT) model. The discrepancies between the model and experiments motivate the further assessment of accurate material properties. This work quantifies the impact material property uncertainty has on model predictions of the absolute stability threshold velocities. Properties from the literature are reviewed and compared to those calculated using computational thermodynamics to provide uncertainty estimates on input properties to the KGT model. Global sensitivity analysis is used to quantify the influence of each uncertain input property on the predicted threshold velocity. This work supports the understanding of the nickel-alloy solidification during powder bed fusion additive manufacturing and identifies the solidification material properties that are the most important to assess from first-principles computations and experiments.

Computational thermodynamics↗

Advanced NASA Earth Science Mission Concept for Vegetation 3D Structure, Biomass and Disturbance

Carbon in forest canopies represents about 85% of the total carbon in the Earth's aboveground biomass (Olson et al., 1983). A major source of uncertainty in global carbon budgets derives from large errors in the current estimates of these carbon stocks (IPCC, 2001). The magnitudes and distributions of terrestrial carbon storage along with changes in sources and sinks for atmospheric C02 due to land use change remain the most significant uncertainties in Earth's carbon budget. These uncertainties severely limit accurate terrestrial carbon accounting; our ability to evaluate terrestrial carbon management schemes; and the veracity of atmospheric C02 projections in response to further fossil fuel combustion and other human activities. Measurements of vegetation three-dimensional (3D) structural characteristics over the Earth's land surface are needed to estimate biomass and carbon stocks and to quantify biomass recovery following disturbance. These measurements include vegetation height, the vertical profile of canopy elements (i.e., leaves, stems, branches), andlor the volume scattering of canopy elements. They are critical for reducing uncertainties in the global carbon budget. Disturbance by natural phenomena, such as fire or wind, as well as by human activities, such as forest harvest, and subsequent recovery, complicate the quantification of carbon storage and release. The resulting spatial and temporal heterogeneity of terrestrial biomass and carbon in vegetation make it very difficult to estimate terrestrial carbon stocks and quantify their dynamics. Vegetation height profiles and disturbance recovery patterns are also required to assess ecosystem health and characterize habitat. The three-dimensional structure of vegetation provides habitats for many species and is a control on biodiversity. Canopy height and structure influence habitat use and specialization, two fundamental processes that modify species richness and abundance across ecosystems. Accurate and consistent 3D measurements of forest structure at the landscape scale are needed for assessing impacts to animal habitats and biodiversity following disturbance.

Ranson, K. Jon↗

Quantification of HCl from high-resolution, ground-based, infrared solar spectra in the 3000 per cm region

Recent ground-based infrared solar spectra at 0.02 per cm resolution in the 3000 per cm region have been analyzed for the atmospheric content of HCl. Nonlinear spectral least-squares fitting applied to spectra obtained at several zenith angles shows little sensitivity of the results to tropospheric HCl but provides an accurate measurement of the total column amount.

Goldman, A.↗

Uncertainty Quantification using Deep Ensembles for Decision Making in Cyber-Physical-Human Systems

In this paper and its companion, Differential Equation Approximation Using Gradient-Boosted Quantile Regression, Robison et al., we examine an approach to quantifying model uncertainty with the aim of increasing the trustworthiness of computational models in human-machine interactions. In Differential Equation Approximation Using Gradient-Boosted Quantile Regression, we focus on gradient-boosted decision trees, while in this one, we give more details about deep ensembles. Uncertainty quantification is crucial for building trustworthy autonomous decision-making agents in human-machine teams. There are two types of uncertainties: aleatoric and epistemic. The former is related to the inherent stochasticity (noise) of the process, whereas the latter is associated with the lack of knowledge or representation capability of models, such as neural networks. By lack of knowledge, we mean the model’s inability to accurately predict outputs for all possible inputs. The aleatory uncertainty can be estimated fairly easily with, for example, filters, whereas epistemic uncertainty is challenging to compute. This paper uses deep ensembles to quantify both aleatory and epistemic uncertainty. It can act as an uncertainty-aware surrogate transition model for decision-making frameworks. "Uncertainty-aware" means that the surrogate transition model should make predictions along with confidence in those predictions. In the context of decision-making, the transition models are ordinary differential equations (ODEs). Since ODEs can be simulated to make one-step or multi-step predictions, a good surrogate model for them should perform reasonably well in both modes. In a multi-step approach, the trajectory sampling method TS∞ was used to propagate uncertainty over multiple steps. The cartpole dynamical system was selected to demonstrate the ability of deep ensembles as good surrogate transition models for decision-making frameworks. The deep ensembles modeled the dynamics of cartpole ODEs and made uncertainty-aware predictions in single-step and multi-step transition modes.

CPH systems↗

Quantifying Methane Leak Emissions by Fused Airborne Imaging Spectroscopy with in Situ Surface Mobile and Airborne Observations of a California Producing Oil Field

Methane (CH4) emission budgets remain uncertain and are projected to grow as oil and gas production from short-lived wells increases and their subsequent transport through aging gas distribution networks. Orders-of-magnitude variations in temporal, spatial, and emission scales present a key challenge to leak detection and quantification. Also, the probability distributions for large and stochastic, leaky systems such as geological reservoirs (by natural migration-seeps) and petroleum production from those reservoirs remain largely unknown, needed to address current approach limitations. The scale of many petroleum systems favors remote sensing, but the sensitivity of such systems often precludes detection of weak emissions. Consequently, an accurate evaluation requires that the relative contribution from the emission "tails" of small leaks also be quantified, which is best carried out using high-sensitivity in situ methods. Fusion of remote sensing and in situ approaches leverages complementary capabilities to address these limitations. We show results from mobile surface (AMOG) and airborne in situ (AJAX) and thermal-infrared (TIR) hyperspectral imaging spectroscopy (Mako) data applied to a producing oil field in the California Central Valley near Bakersfield. AMOG is an automobile-based mobile lab that measures 13 trace gases, aerosol size distributions and vertical profiles, 3D winds and other meteorology, and atmospheric column measurements by solar spectroscopy at highway speeds. AJAX measures 5 trace gases and 3D winds at ~140 m/s. Mako is a broad-area TIR imaging spectrometer that can discriminate multiple gases present in each pixel acquired. In situ-derived, total field emissions were 31±16 Gg/yr CH4. This was compared with Mako-derived emissions from all plumes identified across the study site. We found that super-emitters were not the dominant emissions mode and the spatial pattern of plume locations from production infrastructure was correlated to geological structures.

Leifer, Ira↗

A Model-Based, Bayesian Solution for Characterization of Complex Damage Scenarios in Aerospace Composite Structures

Ultrasonic damage detection and characterization is commonly used in nondestructive evaluation (NDE) of aerospace composite components. In recent years there has been an increased development of guided wave based methods. In real materials and structures, these dispersive waves result in complicated behavior in the presence of complex damage scenarios. Model-based characterization methods utilize accurate three dimensional finite element models (FEMs) of guided wave interaction with realistic damage scenarios to aid in defect identification and classification. This work describes an inverse solution for realistic composite damage characterization by comparing the wavenumber-frequency spectra of experimental and simulated ultrasonic inspections. The composite laminate material properties are first verified through a Bayesian solution (Markov chain Monte Carlo), enabling uncertainty quantification surrounding the characterization. A study is undertaken to assess the efficacy of the proposed damage model and comparative metrics between the experimental and simulated output. The FEM is then parameterized with a damage model capable of describing the typical complex damage created by impact events in composites. The damage is characterized through a transdimensional Markov chain Monte Carlo solution, enabling a flexible damage model capable of adapting to the complex damage geometry investigated here. The posterior probability distributions of the individual delamination petals as well as the overall envelope of the damage site are determined.

H. Reed↗

One-step Tape Casting of Composites via Slurry on Fiber

A process by which metal matrix composites can be made was presented. The process involves putting a powder slurry on fibers to make a precursor green tape. These green tapes are cut, stacked and hot pressed to form the fully dense composite. A computer program was presented which enables complete quantification and control of the process. Once some easily obtained properties of the slurry and its behavior are determined (such as the shrinkage from the wet to green state, and the density of the green tape) modification of the fiber spacing and blade height give the maker precise control of fiber volume fraction, and fiber architecture in the composite. The process was shown to be accurate and flexible through the production of a wide variety of volume fraction fiber composites made from a wide variety of fibers and powders. The most time consuming step of the tape casting process (other than hot pressing) was winding the fiber on the drum. The tape casting techniques developed resulted in high quality metal matrix composites, with ultimate tensile strength in the range of 215 ksi (1477 MPa), a strain at failure of 1.15 percent, and in fatigue at room temperature 0 to 120 ksi, n = 0.3 Hz, a 4-ply Ti-24Al-11Nb/SCS-6, 32 vol% fiber tape cast composite lasted 202,205 cycles with a maximum strain on the 100th cycle of 0.43 percent.

deGroh, Henry C., III↗

Remote Sensing of Dissolved Organic Carbon (DOC) Stocks, Fluxes and Transformations Along the Land-Ocean Aquatic Continuum: Advances, Challenges, and Opportunities

From stream headwaters to the deep ocean, dissolved organic carbon (DOC) is ubiquitous across the world’s aquatic systems, where it fulfills important biogeochemical and ecological functions. Importantly, DOC is a dynamic component of the carbon cycle and represents a global reservoir (mass of carbon) equivalent in size to the atmospheric CO 2 pool. The mobilization, transport, and transformations of DOC along the land-ocean aquatic continuum biogeochemically connect terrestrial landscapes, freshwater and marine ecosystems, and the atmosphere. As a result, DOC budgets are vulnerable to climate- and human-driven changes. Having the ability to quantify DOC stocks, fluxes, and transformations consistently and accurately in aquatic systems is therefore critical to our understanding of DOC’s functions in the environment and of their susceptibility to change. In recent years, optical techniques and synoptic earth observations have opened new doors to achieve this objective on a global scale. In this review, we explore how in situ measurements, earth observations, and the models they inform have facilitated the large-scale quantification of DOC stocks, fluxes, and transformations along the land-ocean aquatic continuum and how they have helped shape our current understanding of the global DOC cycle. The review also explores the limitations and challenges we still face today, and discusses how upcoming and future sensors are expected to provide new insights into our understanding of the global DOC cycle.

Dissolved organic carbon↗

The Impact of Prior Biosphere Models in the Inversion of Global Terrestrial CO2 Fluxes by Assimilating OCO-2 Retrievals

Atmospheric mixing ratios of carbon dioxide (CO2) are largely controlled by anthropogenic emissions and biospheric fluxes. The processes controlling terrestrial biosphere-atmosphere carbon exchange are currently not fully understood, resulting in terrestrial biospheric models having significant differences in the quantification of biospheric CO2 fluxes. Atmospheric transport models assimilating measured (in situ or space-borne) CO2 concentrations to estimate "top-down" fluxes, generally use these biospheric CO2 fluxes as a priori information. Most of the flux inversion estimates result in substantially different spatio-temporal posteriori estimates of regional and global biospheric CO2 fluxes. The Orbiting Carbon Observatory 2 (OCO-2) satellite mission dedicated to accurately measure column CO2 (XCO2) allows for an improved understanding of global biospheric CO2 fluxes. OCO-2 provides much-needed CO2 observations in data-limited regions facilitating better global and regional estimates of "top-down" CO2 fluxes through inversion model simulations. The specific objectives of our research are to: 1) conduct GEOS-Chem 4D-Var assimilation of OCO-2 observations, using several state-of-the-science biospheric CO2 flux models as a priori information, to better constrain terrestrial CO2 fluxes, and 2) quantify the impact of different biospheric model prior fluxes on OCO-2-assimilated a posteriori CO2 flux estimates. Here we present our assessment of the importance of these a priori fluxes by conducting Observing System Simulation Experiments (OSSE) using simulated OCO-2 observations with known "true" fluxes.

Biosphere↗

InSight orbit determination

The InSight mission relied on accurate deep-space navigation for a successful Mars landing on November 26, 2018. In this paper, we discuss the role of the cruise Orbit Determination team, whose responsibilities included determining the spacecraft state, predicting the future trajectory, and quantifying the uncertainty associated with those estimates. In particular, we will focus on spacecraft dynamic modeling, small forces due to attitude control, radiometric tracking data, filter strategies, uncertainty quantification, and responses to unexpected flight situations. We will also provide analysis of reconstructed maneuvers, small forces, and delivery accuracy at Mars arrival.

Seubert, Jill↗

Intracavity absorption with a continuous wave dye laser - Quantification for a narrowband absorber

An experimental investigation of the dependence of intracavity absorption on factors including transition strength, concentration, absorber path length, and pump power is presented for a CW dye laser with a narrow-band absorber (NO2). A Beer-Lambert type relationship is found over a small but useful range of these parameters. Quantitative measurement of intracavity absorption from the dye laser spectral profiles showed enhancements up to 12,000 (for pump powers near lasing threshold) when compared to extracavity measurements. The definition of an intracavity absorption coefficient allowed the determination of accurate transition strength ratios, demonstrating the reliability of the method.

Brobst, William D.↗

Use of satellite imagery for wildland resource evaluation

The author has identified the following significant results. Accurate identification and delineation of crested wheatgrass seedlings has enabled a broad inventory of this resource. The entire state of Nevada is being inventoried for crested wheatgrass seedlings. Irrigated fields and pastures are easily visible from ERTS-1 imagery and were quantified in total acres on 12,500 square miles of the state. Recent fire scars may be monitored and inventoried from satellite-borne imagery. Inventory and quantification of large native meadows of Nevada have been accomplished on one frame of ERTS-1 data. This inventory would not have been economically feasible with any known ground inventory method. The U-2 sequential data taken in the spring revealed several resource management oriented phenological changes in the vegetation. The green-up of grasses and shrubs was detected on the imagery and supplied a good indicator for livestock turn-out dates. Water level manipulations in the Ruby Marsh were readily detected by noting changes in vegetation growth and reflectance.

Tueller, P. T.↗