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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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At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

VESIcal: An Open-source Thermodynamic Model Engine for Mixed Volatile (H2O-CO2) Solubility in Silicate Melts

Modeling the solubility of volatiles in silicate melts is fundamental to the interpretation of volcanic systems and has implications for magma dynamics, eruption style, and material transport between the mantle, crust, and atmosphere. Recent advancements in computational capabilities and access to computing tools has outpaced the functionality and extensibility of previously available modeling platforms. Here we present VESIcal (Volatile Equilibria and Saturation Index calculator), the first comprehensive modeling tool for H2O, CO2, and mixed (H2O-CO2) solubility in silicate melts that: a) allows users access to seven popular models, with easy inter-comparison between models; b) provides universal functionality for all models (e.g., functions for calculating saturation pressures, degassing paths, etc.); c) can process large datasets (1,000’s of samples) automatically; d) can output computed data into an Excel spreadsheet or CSV file for post-modeling analysis; e) integrates plotting capabilities directly within the tool; and f) provides all of this within the framework of a python library, making the tool extensible by the user and allowing any of the model functions to be incorporated into any other code capable of calling python.Here we will provide a demonstration of VESIcal and its capabilities with applications to various volcanic processes affected by volatiles. VESIcal represents the first tool capable of directly comparing multiple solubility models and equations of state. We find that commonly used models predict surprisingly different volatile solubilities, particularly for pure CO2 or mixed CO2-H2O fluids. Even for melt compositions that are well represented in the calibration datasets of multiple models (e.g., MORBs), calculated solubilities for pure CO2 and pure H2O can deviate from one another by factors of >2 leading to 2x deviations in calculated saturation pressures (e.g., 5 to 10 kbar). The solubility of CO2 predicted by different rhyolitic models also differs substantially, overwhelming other sources of uncertainty such as analytical errors on measurements of volatile contents or uncertainties in crustal density profiles. This highlights the importance of model choice when drawing geological conclusions based on volatiles in magmas.

Kayla Iacovino↗
NASA NTRS2010

Evaluating the Utility of Remotely-Sensed Soil Moisture Retrievals for Operational Agricultural Drought Monitoring

Soil moisture is a fundamental data source used by the United States Department of Agriculture (USDA) International Production Assessment Division (IPAD) to monitor crop growth stage and condition and subsequently, globally forecast agricultural yields. Currently, the USDA IPAD estimates surface and root-zone soil moisture using a two-layer modified Palmer soil moisture model forced by global precipitation and temperature measurements. However, this approach suffers from well-known errors arising from uncertainty in model forcing data and highly simplified model physics. Here we attempt to correct for these errors by designing and applying an Ensemble Kalman filter (EnKF) data assimilation system to integrate surface soil moisture retrievals from the NASA Advanced Microwave Scanning Radiometer (AMSR-E) into the USDA modified Palmer soil moisture model. An assessment of soil moisture analysis products produced from this assimilation has been completed for a five-year (2002 to 2007) period over the North American continent between 23degN - 50degN and 128degW - 65degW. In particular, a data denial experimental approach is utilized to isolate the added utility of integrating remotely-sensed soil moisture by comparing EnKF soil moisture results obtained using (relatively) low-quality precipitation products obtained from real-time satellite imagery to baseline Palmer model runs forced with higher quality rainfall. An analysis of root-zone anomalies for each model simulation suggests that the assimilation of AMSR-E surface soil moisture retrievals can add significant value to USDA root-zone predictions derived from real-time satellite precipitation products.

Bolten, John D.↗
DOE OSTI2021

Updates to the Regional Seismic Travel Time (RSTT) Model: 2. Path-dependent Travel-time Uncertainty

Abstract The regional seismic travel time (RSTT) model and software were developed to improve travel-time prediction accuracy by accounting for three-dimensional crust and upper mantle structure. Travel-time uncertainty estimates are used in the process of associating seismic phases to events and to accurately calculate location uncertainty bounds (i.e. event location error ellipses). We improve on the current distance-dependent uncertainty parameterization for RSTT using a random effects model to estimate slowness (inverse velocity) uncertainty as a mean squared error for each model parameter. The random effects model separates the error between observed slowness and model predicted slowness into bias and random components. The path-specific travel-time uncertainty is calculated by integrating these mean squared errors along a seismic-phase ray path. We demonstrate that event location error ellipses computed for a 90% coverage ellipse metric (used by the Comprehensive Nuclear-Test-Ban Treaty Organization International Data Centre (IDC)), and using the path-specific travel-time uncertainty approach, are more representative (median 82.5% ellipse percentage) of true location error than error ellipses computed using distance-dependent travel-time uncertainties (median 70.1%). We also demonstrate measurable improvement in location uncertainties using the RSTT method compared to the current station correction approach used at the IDC (median 74.3% coverage ellipse).

58 GEOSCIENCES↗
NASA NTRS2018

Observation Error Specification for Near-Surface Soil Moisture Assimilation: Does It Matter?

The observation error variances assumed in the data assimilation (DA) of remotely sensed near-surface soil moisture observations are known to have unrealistic spatial patterns. The temporal variability in the errors is also typically neglected. Soil moisture errors cannot be directly calculated at large scales, and the globally distributed errors are unknown. We apply several approaches to estimating the observation errors (R matrix) for near-surface soil moisture DA experiments, to establish whether the assumed errors are important to the DA performance, and hence whether uncertainty in the observation error specification is a likely source of uncertainty in soil moisture DA output.

Draper, Clara↗
NASA NTRS2019

Terrestrial Single-Station Analog for Constraining the Martian Core and Deep Interior: Implications for InSight

We used a terrestrial single-station seismometer to quantify the uncertainty of InSight (INterior explorations using Seismic Investigations, Geodesy and Heat Transport) data for determining Martian core size. To mimic Martian seismicity, we formed a catalog using 917 terrestrial earthquakes, from which we randomly selected events. We stacked ScS amplitudes on modeled arrival times and searched for where ScS produced coherent seismic amplitudes. A core detection was defined by a coherent peak with small offset between predicted and user-selected arrival times. Iterating the detection algorithm with varying signal-to-noise (SNR) ranges and quantity of events determined the selection frequency of each model and quantified core depth uncertainty. Increasing the quantity of events reduced core depth uncertainty while increasing the recovery rate, while increasing event SNR had little effect. Including ScS2 multiples increased the recovery rate and reduced core depth uncertainty when we used low quantities of events. The most-frequent core depths varied by back azimuth, suggesting our method is sensitive to the presence of mantle heterogeneities. When we added 1° in source distance errors, core depth uncertainty increased by up to 11 km and recovery rates decreased by <5%. Altering epicentral distances by 25% added ~35 km of uncertainty and reduced recovery rates to <50% in some cases. From these experiments, we estimate that if InSight can detect five events with high location precision (<10% epicentral distance errors), that there is at least an 88% chance of core depth recovery using ScS alone with uncertainty in core depth approaching 18 km and decreasing as more events are located.

Marusiak, Angela G.↗
NASA NTRS2019

Terrestrial Single-Station Analog for Constraining the Martian Core and Deep Interior: Implications for InSight

We used a terrestrial single-station seismometer to quantify the uncertainty of InSight (INterior explorations using Seismic Investigations, Geodesy and Heat Transport) data for determining Martian core size. To mimic Martian seismicity, we formed a catalog using 917 terrestrial earthquakes, from which we randomly selected events. We stacked ScS amplitudes on modeled arrival times and searched for where ScS produced coherent seismic amplitudes. A core detection was defined by a coherent peak with small offset between predicted and user-selected arrival times. Iterating the detection algorithm with varying signal-to-noise (SNR) ranges and quantity of events determined the selection frequency of each model and quantified core depth uncertainty. Increasing the quantity of events reduced core depth uncertainty while increasing the recovery rate, while increasing event SNR had little effect. Including ScS2 multiples increased the recovery rate and reduced core depth uncertainty when we used low quantities of events. The most-frequent core depths varied by back azimuth, suggesting our method is sensitive to the presence of mantle heterogeneities. When we added 1° in source distance errors, core depth uncertainty increased by up to 11 km and recovery rates decreased by <5%. Altering epicentral distances by 25% added ~35 km of uncertainty and reduced recovery rates to <50% in some cases. From these experiments, we estimate that if InSight can detect five events with high location precision (< 10% epicentral distance errors), that there is at least an 88% chance of core depth recovery using ScS alone with uncertainty in core depth approaching 18 km and decreasing as more events are located.

Angela G Marusiak↗
NASA NTRS2021

Sky-Scanning Sun-Tracking Airborne Radiometer (3STAR): Instrument Design, Flight Testing, and Tracking Performance

The Sky-Scanning, Sun-Tracking Airborne Radiometer (3STAR) adapts commercial radiometer technology developed for the ocean color research community to airborne measurement of spectrally resolved solar irradiance and sky radiance. These atmospheric observations are used to derive aerosol optical depth (AOD), supporting localized AOD inputs for atmospheric correction of satellite and airborne data over terrestrial and aquatic (including optically dark) targets. The ability to regionally “tune” atmospheric correction schemes with relevant spatial AOD supports constraining atmospheric correction of remote sensing reflectance. Very wide dynamic range has been achieved for multi-channel band-pass-filter-radiometers originally designed for deployment into the water column. By actively tracking and directly pointing to the Sun, the light attenuation by aerosol particles in the atmospheric column can be quantified. These measurements improve knowledge of atmospheric constituents and the atmospheric corrections required to improve remote sensing capabilities for interpreting reflectance measurements from the Earth surface. 3STAR incorporates a custom Sun-tracking/sky-scanning pointing head, a Sun-tracking camera, and a commercially available, cylindrical, 19-channel radiometer tube assembly. An accurate and responsive mount and tracking system has been developed and certified to NASA and Naval Air Systems Command (NAVAIR) airworthiness standards for deployment into the aircraft slipstream. Ground and flight testing indicate typical tracking errors of less than 0.1 degrees, well within the field of view of the radiometer as required to minimize measurement uncertainty from alignment error. Preliminary AOD measurements compare to within 0.013 with 15 measurements from an Aerosol Robotic Network (AERONET) Cimel instrument at 500 nm wavelength and low solar angle.

Atmosphere↗
DOE OSTI2026

Taylor approximation variance reduction for approximation errors in PDE-constrained Bayesian inverse problems

In numerous applications, surrogate models are used as a replacement for accurate parameter-to-observable mappings when solving large-scale inverse problems governed by partial differential equations (PDEs). The surrogate model may be a computationally cheaper alternative to the accurate parameter-to-observable mappings and/or may ignore additional unknowns or sources of uncertainty. The Bayesian approximation error (BAE) approach provides a means to account for the induced uncertainties and approximation errors, i.e. the errors between the accurate parameter-to-observable mapping and the surrogate. The statistics of these errors are, however, in general unknown a priori, and are thus calculated using Monte Carlo sampling. Although the sampling is typically carried out offline, i.e. before considering the data, the process can still represent a computational bottleneck. In this work, we develop a scalable computational approach for reducing the costs associated with the sampling stage of the BAE approach. Specifically, we consider the Taylor expansion of the accurate and surrogate forward models with respect to the uncertain parameter fields either as a control variate for variance reduction or as a means to directly and efficiently approximate the mean and covariance of the approximation errors. We propose efficient methods for evaluating the expressions for the mean and covariance of the Taylor approximations based on linear(-ized) PDE solves. Furthermore, the proposed approach is independent of the dimension of the uncertain parameter, depending instead on the intrinsic dimension of the data, ensuring scalability to high-dimensional problems. The potential benefits of the proposed approach are demonstrated for two high-dimensional inverse problems governed by PDE examples, namely for the estimation of a distributed Robin boundary coefficient in a linear diffusion problem, and for a coefficient estimation problem governed by a nonlinear diffusion problem.

Bayesian approximation error↗
NASA NTRS2002

Site Distribution and Aliasing Effects in the Inversion for Load Coefficients and Geocenter Motion from GPS Data

Precise GPS measurements of elastic relative site displacements due to surface mass loading offer important constraints on global surface mass transport. We investigate effects of site distribution and aliasing by higher-degree (n greater than or equal 2) loading terms on inversion of GPS data for n = 1 load coefficients and geocenter motion. Covariance and simulation analyses are conducted to assess the sensitivity of the inversion to aliasing and mismodeling errors and possible uncertainties in the n = 1 load coefficient determination. We found that the use of center-of-figure approximation in the inverse formulation could cause 10- 15% errors in the inverted load coefficients. n = 1 load estimates may be contaminated significantly by unknown higher-degree terms, depending on the load scenario and the GPS site distribution. The uncertainty in n = 1 zonal load estimate is at the level of 80 - 95% for two load scenarios.

global positioning system↗
NASA NTRS2002

Site distribution and aliasing effects in the inversion for load coefficients and geocenter motion from GPS data

Precise GPS measurements of elastic relative site displacements due to surface mass loading offer important constraints on global surface mass transport. We investigate effects of site distribution and aliasing by higher- degree (n ≥ 2) loading terms on inversion of GPS data for n = 1 load coefficients and geocenter motion. Covariance and simulation analyses are conducted to assess the sensitivity of the inversion to aliasing and mismodeling errors and possible uncertainties in the n = 1 load coefficient determination. We found that the use of center-of-figure approximation in the inverse formulation could cause 10– 15% errors in the inverted load coefficients. n = 1 load estimates may be contaminated significantly by unknown higher-degree terms, depending on the load scenario and the GPS site distribution. The uncertainty in n = 1 zonal load estimate is at the level of 80–95% for two load scenarios.

Webb, Frank H.↗
NASA NTRS2023

Evaluation of Systematic Errors on Polarization Parameters from POLDER Instrument Data for Use In CLARREO Pathfinder-VIIRS Intercalibration

One of the CLARREO Pathfinder (CPF) mission’s science objectives is to intercalibrate the reflective solar bands of the NOAA-20 VIIRS instrument against high-accuracy CPF measurements utilizing coincident, co-angled, and co-located footprints acquired over diverse Earth targets. To alleviate the effect of high polarization sensitivity of select VIIRS channels on intercalibration analysis, the CPF team will limit the intercalibration footprints over low-polarized scene types, which will be identified based on an empirical estimation of their degree and angle of polarization (DOP and AOP) using POLDER data. This paper describes the methodology for evaluating systematic errors in the estimation of DOP and AOP for Earth-reflected radiances using POLDER’s polarized bands and investigates their potential impact on CPF-VIIRS intercalibration uncertainty. The systematic errors were found to be less than 0.01 for DOP and less than 2.2 deg. for AOP, which will have a negligible impact on CPF-VIIRS intercalibration uncertainty.

polarization↗
NASA NTRS1994

Measurement uncertainty and feasibility study of a flush airdata system for a hypersonic flight experiment

Presented is a feasibility and error analysis for a hypersonic flush airdata system on a hypersonic flight experiment (HYFLITE). HYFLITE heating loads make intrusive airdata measurement impractical. Although this analysis is specifically for the HYFLITE vehicle and trajectory, the problems analyzed are generally applicable to hypersonic vehicles. A layout of the flush-port matrix is shown. Surface pressures are related airdata parameters using a simple aerodynamic model. The model is linearized using small perturbations and inverted using nonlinear least-squares. Effects of various error sources on the overall uncertainty are evaluated using an error simulation. Error sources modeled include boundarylayer/viscous interactions, pneumatic lag, thermal transpiration in the sensor pressure tubing, misalignment in the matrix layout, thermal warping of the vehicle nose, sampling resolution, and transducer error. Using simulated pressure data for input to the estimation algorithm, effects caused by various error sources are analyzed by comparing estimator outputs with the original trajectory. To obtain ensemble averages the simulation is run repeatedly and output statistics are compiled. Output errors resulting from the various error sources are presented as a function of Mach number. Final uncertainties with all modeled error sources included are presented as a function of Mach number.

Whitmore, Stephen A.↗
DOE OSTI2021

Pressure-Driven Fiber-Optic Sensor for Online Corrosion Monitoring

For many industrial applications, corrosion is a life-limiting phenomenon and therefore requires careful consideration and rigorous experimental testing before structural materials can be reliably deployed, particularly in harsh chemical environments. The traditional approach to measuring corrosion requires exposing many samples to the intended environment and then extracting them individually at discrete intervals for postexposure characterization. This approach does not provide a high degree of temporal resolution, nor does it provide any real-time information regarding dynamic changes in corrosion rates. Additionally, developing an online corrosion monitor capable of surviving harsh chemical environments could provide valuable information regarding the structural health of components and changing process conditions that could accelerate corrosion. To this end, a corrosion sensor was developed based on a pressure-driven Fabry-Pérot cavity (FPC). This sensor uses a pressure control system to internally pressurize the FPC formed between the sensor’s housing and a metal-embedded singlemode optical fiber. Simultaneous measurement of the change in FPC length using low-coherence interferometry and the applied pressure enables the calculation of the relative changes in the sensor’s diaphragm thickness due to corrosion on its outer surface. Measurements were made in situ while actively corroding the sensor and were validated against surveillance specimens that were corroded simultaneously. The uncertainties in the measured corrosion were analyzed using error propagation of the uncertainties in the measured pressures and displacements and were found to be <1% of the initial diaphragm thickness.

42 ENGINEERING↗
NASA NTRS1973

LAGEOS mission analyses

Two error sources are found to be compatible and significant for the parameters affecting the LAGEOS mission. The first error source is the uncertainty in the gravity model, and the second error source is the radiation pressure which includes direct radiation, albedo radiation, and earth shine. Retrograde orbits increase the number of passes per day over the tracking stations at the expense of also increasing the number of time gaps when no station is observing. It is shown that relativistic effects are significant and must be included in orbit computation and determination systems for this mission. If station locations are known only to one meter, the error in the satellite orbits is comparable with solar pressure induced errors.

Squires, R. K.↗
NASA NTRS1975

A study of orbit determination accuracies for future earth observatory missions

It is anticipated that global orbital accuracies of 10 meters will be required for future earth observatory missions. Results are presented of a study of the LANDSAT-1 orbit to determine position accuracies obtainable today so as to assess what future advancements are necessary to meet a 10-meter goal. Accuracies of 50 meters were determined to be achievable now from two-day tracking arcs. One-half-day arcs yield accuracies of about 30 meters. The dominant error source was found to be geopotential model uncertainty. All other systematic errors produced less than 10 meters total position error.

Bryant, W. C., Jr.↗
NASA NTRS1982

Topex orbit sustenance maneuver design

A trade-off analysis between maneuver period, execution errors, and orbit determination uncertainties is carried out for the Ocean Topography Experiment spacecraft for a given nodal equatorial constraint. Semimajor axis and eccentricity are controlled with minimum impulse using the linear theory of optimal transfer between close coplanar near-circular orbits. Ellipses of equal minimum and average maneuver periods are presented in the (3 execution error, 3 orbit determination uncertainty) space for different nodal equatorial constraints enabling the determination of the appropriate combination of execution errors and orbit determination uncertainties that guarantees a mission required minimum maneuver period for a given nodal deadband.

Kechichian, J. A.↗
NASA NTRS1975

Error Analysis of the Shuttle Orbital Maneuvering System P-V-T Propellant Gaging Module. Mission Planning, Mission Analysis and Software Formulation

An investigation of the shuttle orbital maneuvering system (OMS) pressure-volume-temperature (P-V-T) propellant gaging module has revealed that the gaging errors due to the combined effects of random instrumentation measurement errors, propellant loading uncertainties, and simplifying assumptions in the software are non-linear over the range of the usable propellant quantity gage (0-100%), with the largest error being at the zero point. When the OMS propellant tanks in the orbiter vehicle pods are filled to contain 100% of the maximum usable propellant, the gaging error at the zero point was determined to be 9.5% for the fuel and 9.5% for the oxidizer. When the OMS propellant tanks initially contain 50% of the maximum usable propellant, the largest gaging error is still 9.5% for the fuel and 9.5% for the oxidizer.

Duhon, D. D.↗
NASA NTRS1985

Robust state estimation with imperfect sensors

Robustness properties of extended Kalman-type filters are investigated for time-varying plants when nonlinearities or linear dynamics are present at the plant input and output. Sufficient conditions for the asymptotic stability (of the state estimation error) in the absence of noise are obtained when the nonlinearities or the linear dynamics are perfectly known. When the nonlinearities are known only within bands of uncertainty, the estimation error is shown to be ultimately bounded under certain conditions. The results obtained highlight the robustness properties of such filters, which are similar to, but not exact duals of those of linear quadratic regulators.

Joshi, S. M.↗