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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

An Evaluation of the Large‐Scale Atmospheric Circulation and Its Variability in CESM2 and Other CMIP Models

Abstract The Community Earth System Model 2 (CESM2) is the latest Earth System Model developed by the National Center for Atmospheric Research in collaboration with the university community and is significantly advanced in most components compared to its predecessor (CESM1). Here, CESM2's representation of the large‐scale atmospheric circulation and its variability is assessed. Further context is providedthrough comparison to the CESM1 large ensemble and other models from the Coupled Model Intercomparison Project (CMIP5 and CMIP6). This includes an assessment of the representation of jet streams and storm tracks, stationary waves, the global divergent circulation, the annular modes, the North Atlantic Oscillation, and blocking. Compared to CESM1, CESM2 is substantially improved in the representation of the storm tracks, Northern Hemisphere (NH) stationary waves, NH winter blocking and the global divergent circulation. It ranks within the top 10% of CMIP class models in many of these features. Some features of the Southern Hemisphere (SH) circulation have degraded, such as the SH jet strength, stationary waves, and blocking, although the SH jet stream is placed at approximately the correct location. This analysis also highlights systematic deficiencies in these features across the new CMIP6 archive, such as the continued tendency for the SH jet stream to be placed too far equatorward, the North Atlantic westerlies to be too strong over Europe, the storm tracks as measured by low‐level meridional wind variance to be too weak and a lack of blocking in the North Atlantic sector.

Simpson, Isla R.↗
DOE OSTI2025

Inferring Plant Acclimation and Improving Model Generalizability With Differentiable Physics‐Informed Machine Learning of Photosynthesis

Net photosynthesis (A N ) is a key component of the global carbon cycle influencing climate feedback over decadal scales. Although plant acclimation to environmental changes can modify A N , traditional vegetation models in Earth system models (ESMs) often rely on plant functional type (PFT)-specific parameterizations or simplified acclimation assumptions limiting generalizability across time, space, and PFTs. In this study, we developed a differentiable photosynthesis model to learn the environmental dependencies of V c,max25 (maximum carboxylation rate at 25°C, representing photosynthetic capacity), as this genre of hybrid physics-informed machine learning can seamlessly train neural networks and process-based equations together. Compared to PFT-specific parameterization of V c,max25 , learning the environment dependencies of key photosynthetic parameters improved model spatiotemporal generalizability. Applying environmental acclimation to V c,max25 led to substantial variations in global mean A N indicating the need to address acclimation in ESMs. The model effectively captured multivariate observations (V c,max25 , A N , and stomatal conductance (g s )) simultaneously with multivariate constraints, improving generalization across space and PFTs. It also learned sensible acclimation relationships of V c,max25 to different environmental conditions. The model explained more than 54%, 57%, and 62% of the variance of A N , g s , and V c,max25 , respectively, presenting a first global-scale spatial test benchmark of A N and g s . These results highlight the potential for differentiable modeling to enhance process-based modules in ESMs and effectively leverage information from large, multivariate data sets.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2005

Diverse Applications of Occultation Data in Ozone Assimilation

Ozone profiles from solar occultation instruments provide invaluable information that can be used to evaluate the quality of assimilated ozone fields, from case studies to long-term phenomena. Occultation data can also be applied to include physical constraints while developing components of an assimilation system. Conversely, assimilation of occultation data can help in their validation, and it provides a framework for evaluation of the impact of occultation data on constraining global ozone fields within models. We illustrate these diverse applications by a series of examples using the ozone assimilation system at NASA/Goddard. In a case study, low ozone in the lower stratosphere due to transport of air from the Tropics to northern high latitudes that was captured by assimilation of Aura Microwave Limb Sounder (MLS) and Solar Backscatter Ultraviolet (SBUV) data, was found to agree with SAGE III data. For long-term monitoring, the quality of a multi-year SBUV-only assimilation was evaluated using monthly-mean time series of POAM, HALOE, and SAGE I1 data. We found realism in the representation of the annual cycle in ozone and in some aspects of interannual variability. Assimilation of POAM data was shown to improve the representation of lower stratospheric ozone, especially over Antarctica. More recently, we assimilated ILAS II ozone data in order to help in their validation. Solar occultation data are used to estimate parameters in a new model for forecast error variances that is being developed. These examples demonstrate the importance of occultation data for ozone assimilation, and potential of assimilation to increase the impact and the value of occultation data.

Markowitz, A.↗
DOE OSTI2022

Machine Learning of All Mycobacterium tuberculosis H37Rv RNA-seq Data Reveals a Structured Interplay between Metabolism, Stress Response, and Infection

Mycobacterium tuberculosis is one of the most consequential human bacterial pathogens, posing a serious challenge to 21st century medicine. A key feature of its pathogenicity is its ability to adapt its transcriptional response to environmental stresses through its transcriptional regulatory network (TRN). While many studies have sought to characterize specific portions of the M. tuberculosis TRN, and some studies have performed system-level analysis, few have been able to provide a network-based model of the TRN that also provides the relative shifts in transcriptional regulator activity triggered by changing environments. Here, we compiled a compendium of nearly 650 publicly available, high quality M. tuberculosis RNA-sequencing data sets and applied an unsupervised machine learning method to obtain a quantitative, top-down TRN. It consists of 80 independently modulated gene sets known as “iModulons,” 41 of which correspond to known regulons. These iModulons explain 61% of the variance in the organism’s transcriptional response. We show that iModulons (i) reveal the function of poorly characterized regulons, (ii) describe the transcriptional shifts that occur during environmental changes such as shifting carbon sources, oxidative stress, and infection events, and (iii) identify intrinsic clusters of regulons that link several important metabolic systems, including lipid, cholesterol, and sulfur metabolism. This transcriptome-wide analysis of the M. tuberculosis TRN informs future research on effective ways to study and manipulate its transcriptional regulation and presents a knowledge-enhanced database of all published high-quality RNA-seq data for this organism to date.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Improved Infrared Optical Constants from Pressed Pellets: II. Ellipsometric n and k Values for Ammonium Sulfate with Variability Analysis

Infrared spectral imaging is facilitated via the comparison of spectra recorded in situ to a databank of actual or synthetic infrared reflectance spectra. It has recently been shown that reference spectra corresponding to the many different morphological forms of the same chemical can be generated synthetically using the imaginary, k, and real, n, components of the complex refractive index, n~ = n + ik. One method to obtain the n and k vectors is infrared ellipsometry, which measures the changes in amplitude, tan ?, and phase, ?, of polarized light reflected from the sample both as a function of wavenumber and angle of incidence. The method requires specularly reflected light so best results are usually obtained with polished planar samples of large surface area. Due to the difficulties of obtaining such samples, however, we investigate the possibility of pressing powders of neat materials and obtaining the corresponding optical constants from the pellets. In this paper, variability in the sample pellet and preparation method is investigated, as is variability in the fitting procedure for the derived optical constants. The n/k vectors are derived from the measured ellipsometric parameters, tan ? and ?, as they are fit by an oscillator model which yield n(?) and k(?) vectors as a function of wavenumber, ?. Construction of the oscillator model is not automatic and depends on significant input from the analyst as well as the sample’s physical characteristics. For the pellet pressing, the experimental variability was found to be minimized for size-selected powdered samples as gauged by the minimal variance in ? and ? for three different pellets; similarly, the analytical precision for multiple measurements of the same pellet was also quite good, suggesting that a pressed pellet is a viable sample preparation method. The greatest variability came in the analytic fitting procedure with differences up to 20% arising from four different fits to the same data set. The final ellipsometric n/k data are compared to literature values obtained from crystalline (NH4)2SO4 samples as well as single-angle reflectance measurements that also used pressed pellets. Comparison with the previous literature values shows generally good agreement although higher k-values are observed for the independent sets of data derived from pressed pellets. These data are suggested as an improved set of optical constants for (NH4)2SO4.

optical constants, ellipsometry, ammonium sulfate,↗
NASA NTRS2011

Seating Considerations for Spaceflight: The Human to Machine Interface

Seating is one of the most critical components to be considered during design of a spacecraft. Since seats are the final interface between the occupant and the vehicle wherein all launch and landing operations are performed, significant effort must be spent to ensure proper integration of the human to the spacecraft. The importance of seating can be divided into two categories: seat layout and seat design. The layout of the seats drives the overall cabin configuration - from displays and controls, to windows, to stowage, to egress paths. Since the layout of the seats is such a critical design parameter within the crew compartment, it is one of the first design challenges that must be completed in the critical path of the spacecraft design. In consideration of seat layout in the vehicle, it is important for the designers to account for often intangible factors such as safety, operability, contingency performance, crew rescue. Seat layout will lead to definition of the quantity, shape, and posture of the seats. The seats of the craft must restrain and protect the occupant in all seated phases of flight, while allowing for nominal mission performance. In design of a spacecraft seat, the general posture of the occupant and the landing loads to be encountered are the greatest drivers of overall design. Variances, such as upright versus recumbent postures will dictate fit of the seat to the occupant and drive the total envelope of the seat around the occupant. Seat design revolves around applying sound principles of seated occupant protection coupled with the unique environments driven by the seat layout, landing loads, and operational and emergency scenarios.

Gohmert, Dustin M.↗
NASA NTRS2015

Characterization of Machine Variability and Progressive Heat Treatment in Selective Laser Melting of Inconel 718

The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human‐rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30‐sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post‐processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one‐way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future flight programs, NASA and its commercial partners will procure parts from vendors who will use a diverse range of machines to produce parts and, as such, it is essential that the AM community develop a sound understanding of the degree to which machine variability impacts material properties.

Prater, Tracie↗
NASA NTRS1997

Cycle-Powered Short Radius (1.9 m) Centrifuge: Effect of Exercise Versus Passive Acceleration on Heart Rate in Humans

In addition to extensive use of lower extremity physical exercise training as a countermeasure for the work capacity component of spaceflight deconditioning, some form of additional head-to-foot (+Gz) gravitational (orthostatic) stress may be required to further attenuate or prevent the signs and symptoms (nausea, vertigo, instability, fatigue) of the general reentry syndrome (GRS) that can reduce astronaut performance during landing. Orthostatic (head-to-foot) stress can be induced by standing, by lower body negative pressure, and by +Gz acceleration. One important question is whether acceleration training alone or with concurrent leg exercise would provide sufficient additive stimulation to attenuate the GRS. Use of a new human-powered centrifuge may be the answer. Thus, the purpose for this study was to compare heart rate (HR), i.e., a stress response during human-powered acceleration, in four men (35-62 yr) and two women (30-31 yr) during exercise acceleration versus passive acceleration (by an off-board operator) at 100% (maximal acceleration = A(max)), and at 25%, 50%, and 75% of A(max). Mean (+/-SE) A(max) was 43.7 +/- 1.3 rpm (+3.9 +/- 0.2Gz). Mean HR at exercise A(max) was 189 +/- 13 b/min (50-70 sec run time), and 142 +/- 22 b/min at passive A(max) (40-70 sec run time). Regression of mean HR on the various +Gz levels indicated explained variance (correlations squared) of r(exp 2) = 0.88 (exercise) and r(exp 2) = 0.96 (passive): exercise HR of 107 +/- 4 (25%) to 189 +/- 13 (100%) b/min were 43-50 b/min higher (p less than 0.05) than comparable passive HR of 64 +/- 2 to 142 +/- 22 b/min. Thus, exercise adds significant physiological stress during +Gz acceleration. Inflight use of this combined exercise and acceleration countermeasure may maintain work capacity as well as normalize acceleration and orthostatic tolerances which could attenuate or perhaps eliminate the GRS.

Greenleaf, J. E.↗
NASA NTRS2015

Rao-Blackwellization for Adaptive Gaussian Sum Nonlinear Model Propagation

When dealing with imperfect data and general models of dynamic systems, the best estimate is always sought in the presence of uncertainty or unknown parameters. In many cases, as the first attempt, the Extended Kalman filter (EKF) provides sufficient solutions to handling issues arising from nonlinear and non-Gaussian estimation problems. But these issues may lead unacceptable performance and even divergence. In order to accurately capture the nonlinearities of most real-world dynamic systems, advanced filtering methods have been created to reduce filter divergence while enhancing performance. Approaches, such as Gaussian sum filtering, grid based Bayesian methods and particle filters are well-known examples of advanced methods used to represent and recursively reproduce an approximation to the state probability density function (pdf). Some of these filtering methods were conceptually developed years before their widespread uses were realized. Advanced nonlinear filtering methods currently benefit from the computing advancements in computational speeds, memory, and parallel processing. Grid based methods, multiple-model approaches and Gaussian sum filtering are numerical solutions that take advantage of different state coordinates or multiple-model methods that reduced the amount of approximations used. Choosing an efficient grid is very difficult for multi-dimensional state spaces, and oftentimes expensive computations must be done at each point. For the original Gaussian sum filter, a weighted sum of Gaussian density functions approximates the pdf but suffers at the update step for the individual component weight selections. In order to improve upon the original Gaussian sum filter, Ref. [2] introduces a weight update approach at the filter propagation stage instead of the measurement update stage. This weight update is performed by minimizing the integral square difference between the true forecast pdf and its Gaussian sum approximation. By adaptively updating each component weight during the nonlinear propagation stage an approximation of the true pdf can be successfully reconstructed. Particle filtering (PF) methods have gained popularity recently for solving nonlinear estimation problems due to their straightforward approach and the processing capabilities mentioned above. The basic concept behind PF is to represent any pdf as a set of random samples. As the number of samples increases, they will theoretically converge to the exact, equivalent representation of the desired pdf. When the estimated qth moment is needed, the samples are used for its construction allowing further analysis of the pdf characteristics. However, filter performance deteriorates as the dimension of the state vector increases. To overcome this problem Ref. [5] applies a marginalization technique for PF methods, decreasing complexity of the system to one linear and another nonlinear state estimation problem. The marginalization theory was originally developed by Rao and Blackwell independently. According to Ref. [6] it improves any given estimator under every convex loss function. The improvement comes from calculating a conditional expected value, often involving integrating out a supportive statistic. In other words, Rao-Blackwellization allows for smaller but separate computations to be carried out while reaching the main objective of the estimator. In the case of improving an estimator's variance, any supporting statistic can be removed and its variance determined. Next, any other information that dependents on the supporting statistic is found along with its respective variance. A new approach is developed here by utilizing the strengths of the adaptive Gaussian sum propagation in Ref. [2] and a marginalization approach used for PF methods found in Ref. [7]. In the following sections a modified filtering approach is presented based on a special state-space model within nonlinear systems to reduce the dimensionality of the optimization problem in Ref. [2]. First, the adaptive Gaussian sum propagation is explained and then the new marginalized adaptive Gaussian sum propagation is derived. Finally, an example simulation is presented.

state estimation↗
NASA NTRS2015

Characterization of Machine Variability and Progressive Heat Treatment in Selective Laser Melting of Inconel 718

The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human-rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30-sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post-processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one-way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future flight programs, NASA and its commercial partners will procure parts from vendors who will use a diverse range of machines to produce parts and, as such, it is essential that the AM community develop a sound understanding of the degree to which machine variability impacts material properties.

Prater, T.↗
NASA NTRS2023

A Wind-Driven Snow Redistribution Module for Alpine3d V3.3.0: Adaptations Designed for Downscaling Ice Sheet Surface Mass Balance

Ice sheets gain mass via snow accumulation at the ice sheet surface, which is the primary component of surface mass balance. On the Antarctic ice sheet, winds redistribute snow resulting in surface mass balance that is variable in both space and time. Representing wind-driven snow redistribution processes in models is critical for local assessments of surface mass balance, repeat altimetry studies, and interpretation of ice core accumulation records. To this end, we have adapted Alpine3D, an existing distributed snow modeling framework, to downscale Antarctic surface mass balance to horizontal resolutions up to 1 km. In particular, we have introduced a new two-dimensional advection-based wind-driven snow redistribution module that is driven by an offline coupling between WindNinja, a wind downscaling model, and Alpine3D. We then show that large accumulation variability can be at least partially explained by terrain-induced wind speed variations which subsequently redistribute snow around rolling topography. By comparing Alpine3D to airborne-derived snow accumulation measurements within a testing domain over Pine Island Glacier in West Antarctica, we demonstrate that our Alpine3D downscaling approach improves surface mass balance estimates when compared to MERRA-2, a global atmospheric reanalysis which we use as atmospheric forcing. In particular, when compared to MERRA-2, Alpine3D reduces simulated surface mass balance root mean squared error by 23.4 mm w.e.yr−1 (13%) and increases variance explained by 24%. Despite these improvements, Alpine3D still underestimates observed accumulation variability, thus providing an opportunity for future model improvement.

Eric Keenan↗
NASA NTRS2012

Dual-Frequency Observations of 140 Compact, Flat-Spectrum Active Galactic Nuclei for Scintillation-Induced Variability

The 4.9 GHz Micro-Arcsecond Scintillation-Induced Variability (MASIV) Survey detected a drop in Interstellar Scintillation (ISS) for sources at red shifts z > or approx. 2, indicating an apparent increase in angular diameter or a decrease in flux density of the most compact components of these sources, relative to their extended emission. This can result from intrinsic source size effects or scatter broadening in the Intergalactic Medium (IGM) , in excess of the expected (1+z)1/2 angular diameter scaling of brightness temperature limited sources resulting from cosmological expansion. We report here 4.9 GHz and 8.4 GHz observations and data analysis for a sample of 140 compact, fiat-spectrum sources which may allow us to determine the origin of this angular diameter-redshift relation by exploiting their different wavelength dependences. In addition to using ISS as a cosmological probe, the observations provide additional insight into source morphologies and the characteristics of ISS. As in the MASIV Survey, the variability of the sources is found to be significantly correlated with line-of-sight H(alpha) intensities, confirming its link with ISS. For 25 sources, time delays of about 0.15 to 3 days are observed between the scintillation patterns at both frequencies, interpreted as being caused by a shift in core positions when probed at different optical depths. Significant correlation is found between ISS amplitudes and source spectral index; in particular, a large drop in ISS amplitudes is observed at alpha < -0.4 confirming that steep spectrum sources scintillate less. We detect a weakened redshift dependence of ISS at 8.4 GHz over that at 4.9 GHz, with the mean variance at 4-day timescales reduced by a factor of 1.8 in the z > 2 sources relative to the z < 2 sources, as opposed to the factor of 3 decrease observed at 4.9 GHz. This suggests scatter broadening in the IGM, but the interpretation is complicated by subtle selection effects that will be explored further in a follow-up paper.

Koay, J. Y.↗
NASA NTRS1999

Sea Surface Slope Statistics for Intermediate and Shore Scale Ocean Waves Measured Using a Low-Altitude Aircraft

Ocean surface remote sensing techniques often rely on scattering or emission linked to shorter- scale gravity-capillary ocean wavelets. However, it is increasingly apparent that slightly longer wavelengths of O(10 to 500 cm) are vital components in the robust sea surface description needed to link varied global remote sensing data sets. This paper describes a sensor suite developed to examine sea surface slope variations in the field using an aircraft flying at very low altitude (below 30 m) and will also provide preliminary measurements detailing changes in slope characteristics versus sea state and friction velocity. Two-dimensional surface slope is measured using simultaneous range measurements from three compact short-range laser altimeters mounted in an equilateral triangle arrangement with spacing of about 1 m. In addition, all three lasers provide independent wave elevation profiles after GPS-aided correction for aircraft altitude. Laser range precision is 1 cm rms while vertical motion correction is 15 cm rms. The measurements are made along-track at approximately 1 m intervals setting the spatial scale of the measurement to cover waves of intermediate to long scale. Products available for this array then include surface elevation, two-dimensional slope distribution, and the cross- and along-track 1-D slope distributions. To complement the laser, a down-looking mm-wave radar scatterometer is centered within the laser array to measure radar backscatter simultaneously with the laser slope. The radar's footprint is nominally 1 m in diameter. Near-vertical radar backscatter is inversely proportional to the small-scale surface slope variance and to the tilt of the underlying (laser-measured) surface facet. Together the laser and radar data provide information on wave roughness from the longest scales down to about 1 cm. These measurements are complemented by aircraft turbulence probe data that provides robust surface flux information.

Vandemack, Douglas↗
NASA NTRS2006

Diurnal Variability of Vertical Structure from a TRMM Passive Microwave "Virtual Radar" Retrieval

Robust description of the diurnal cycle from TRMM observations is complicated by the limitations of Low Earth Orbit (LEO) sampling; from a 'climatological' perspective, sufficient sampling must exist to control for both spatial and seasonal variability, before tackling an additional diurnal component (e.g., with 8 additional 3-hourly or 24 1-hourly bins). For documentation of vertical structure, the narrow sample swath of the TRMM Precipitation Radar limits the resolution of any of these components. A neural-network based 'virtual radar" retrieval has been trained and internally validated, using multifrequency / multipolarization passive microwave(TM1) brightness temperatures and textures parameters and lightning (LIS) observations, as inputs, and PR volumetric reflectivity as targets (outputs). By training the algorithms (essentially highly multivariate, nonlinear regressions) on a very large sample of high-quality co-located data from the center of the TRMM swath, 3D radar reflectivity and derived parameters (VIL, IWC, Echo Tops, etc.) can be retrieved across the entire TMI swath, good to 8-9% over the dynamic range of parameters. As a step in the retrieval (and as an output of the process), each TMI multifrequency pixel (at 85 GHz resolution) is classified into one of the 25 archetypal radar profile vertical structure "types", previously identified using cluster analysis. The dynamic range of retrieved vertical structure appears to have higher fidelity than the current (Version 6) experimental GPROF hydrometeor vertical structure retrievals. This is attributable to correct representation of the prior probabilities of vertical structure variability in the neural network training data, unlike the GPROF cloud-resolving model training dataset used in the V6 algorithms. The LIS lightning inputs are supplementary inputs, and a separate offline neural network has been trained to impute (predict) LIS lightning from passive-microwave-only data. The virtual radar retrieval is thus, in principle, extensible to Aqua/AMSR-E and NPOESS/CMIS passive microwave instruments. The virtual radar approach yields a threefold increase in effective sampling from the mission, albeit of lower-quality "retrieved" data, reducing the variance of local estimates by one third (or the standard deviation by-0.57). In this talk, the variance reduction is leveraged to more finely resolve global diurnal variability in both space and time (local hour).

Boccippio, Dennis J.↗
DOE OSTI2025

Advancing Development of Emissions Detection (Final Report)

This document is the final report to the U.S. Department of Energy (DOE for contract DE-FE0031873) awarded to Colorado State University (CSU). CSU and partners at Harrisburg University of Science and Technology, University of Texas Arlington, and University of Texas at Austin organized several testing rounds to provide knowledge focused on advancing the detection capabilities of emissions monitoring devices. With this funding opportunity the research group began by establishing the Advancing the Development of Emission Detection (ADED) program, with the goal focused on enhancing the accuracy, reliability, and field applicability of methane detection technologies. This effort aimed to address the critical challenges of identifying and quantifying methane emissions while enabling industry stakeholders to meet regulatory compliance and environmental sustainability goals. The program engaged with industry, government, and technology stakeholders to promote adoption and consensus on testing techniques for methane detection solutions. Methane, a potent greenhouse gas, contributes significantly to global warming, and the oil and natural gas (O&G) sector is a primary source of methane emissions. Regulatory measures such as leak detection and repair (LDAR) programs have been implemented to address emissions. However, traditional LDAR approaches, reliant on handheld and component-level measurements, are resource-intensive. To address these limitations and move with evolving regulations, advanced methane technologies are emerging. These solutions include ground-based sensors, mobile systems (e.g., drones, vehicles, and aircraft), and satellite-based platforms. They offer innovative capabilities for autonomous monitoring, larger spatial coverage, and emission quantification using methods such as tracer gas techniques and inverse modeling with Gaussian plume analysis. The ADED program began with creating protocols for methane controlled release (CR) testing these continuous monitoring (CM) and survey technologies that detect and monitor methane emissions at O&G facilities. The protocols were then implemented throughout testing of CM and survey devices at CSU’s Methane Emissions Technology Evaluation Center (METEC) facility from 2021 through 2024. As apart of the protocol, solutions that tested under the ADED program installed their solutions at METEC, documented their system under test, and provided detection reports to the METEC team for analysis. The METEC team would provide the solutions with analyzed reports of their emissions and ground truth data of the releases conducted during their testing session. Under the ADED program, CMs were also tested at O&G facilities for a six week test run of challenge release (ChR) releases. The findings from the ADED program underscore the critical role of collaborative research and innovation in tackling methane emissions, offering a pathway for the oil and gas sector to achieve significant environmental and economic benefits. Results from METEC testing saw improvement of performance and accuracy across all solutions over the extent of the ADED experiments. The results also showed a variance in CM solution performance between CRs and ChRs. That variance pushed the team to further analyze the differences between CR testing environments and field conditions. With the drive from regulations and that variance in field conditions, the ADED team began designing a new CR testing protocol and additions to the METEC testing facility. The METEC team is furthering the progress made through the ADED program with awarded funding from DE-FE0032276. This funding pushes the development of METEC’s addition with new equipment, allowing for an updated facility layout. METEC still facilitates for traditional facilities, with a legacy pad, while expanding an new design based on how O&G infrastructure has Final Report - Contract Number: DE-FE0031873 been changed over the last decade. Throughout the ADED program the team has also been working with international partners to ensure staying in the trend globally. International partners have been essential in moving the new protocol forward to implement into CR testing at the METEC facility in Spring 2025.

42 ENGINEERING↗
NASA NTRS2011

NASA Tech Briefs, January 2011

The topics include: 1) Distributed Aerodynamic Sensing and Processing Toolbox; 2) Collaborative Supervised Learning for Sensor Networks; 3) Hazard Detection Software for Lunar Landing; 4) Onboard Nonlinear Engine Sensor and Component Fault Diagnosis and Isolation Scheme; 5) Network-Capable Application Process and Wireless Intelligent Sensors for ISHM; 6) Interface Supports Multiple Broadcast Transceivers for Flight Applications; 7) FPGA Sequencer for Radar Altimeter Applications; 8) Miniature Sapphire Acoustic Resonator - MSAR; 9) Process-Hardened, Multi-Analyte Sensor for Characterizing Rocket Plume Constituents; 10) SAD5 Stereo Correlation Line-Striping in an FPGA; 11) Hybrid Composite Cryogenic Tank Structure; 12) Nanoscale Deformable Optics; 13) Reliability-Based Design Optimization of a Composite Airframe Component; 14) Zinc Oxide Nanowire Interphase for Enhanced Lightweight Polymer Fiber Composites; 15) Plasma Igniter for Reliable Ignition of Combustion in Rocket Engines; 16) Wire Test Grip Fixture; 17) A Sub-Hertz, Low-Frequency Vibration Isolation Platform; 18) Carbon Nanofibers Synthesized on Selective Substrates for Nonvolatile Memory and 3D Electronics; 19) Nanoparticle/Polymer Nanocomposite Bond Coat or Coating; 20) High-Resolution Wind Measurements for Offshore Wind Energy Development; 21) Spring Tire; 22) Marsviewer 2008; 23) Mission Services Evolution Center Message Bus; 24) Major Constituents Analysis for the Vehicle Cabin Atmosphere Monitor; 25) Astronaut Health Participant Summary Application; 26) Adaption of the AMDIS Method to Flight Status on the VCAM Instrument; 27) Natural Language Interface for Safety Certification of Safety-Critical Software; 28) Cryogenic Caging for Science Instrumentation; 29) Wide-Range Neutron Detector for Space Nuclear Applications; 30) In Situ Guided Wave Structural Health Monitoring System; 31) Multiplexed Energy Coupler for Rotating Equipment; 32) Attitude Estimation in Fractionated Spacecraft Cluster Systems; 33) Full Piezoelectric Multilayer-Stacked Hybrid Actuation/Transduction Systems; 34) Active Flow Effectors for Noise and Separation Control; 35) Method and System for Temporal Filtering in Video Compression Systems; 36) Apparatus for Measuring Total Emissivity of Small, Low-Emissivity Samples; 37) Multiple-Zone Diffractive Optic Element for Laser Ranging Applications; 38) Simplified Architecture for Precise Aiming of a Deep-Space Communication Laser Transceiver; 39) Two-Photon-Absorption Scheme for Optical Beam Tracking; 40) High-Sensitivity, Broad-Range Vacuum Gauge Using Nanotubes for Micromachined Cavities; 41) Wide-Field Optic for Autonomous Acquisition of Laser Link; 42) Extracting Zero-Gravity Surface Figure of a Mirror; 43) Modeling Electromagnetic Scattering From Complex Inhomogeneous Objects; 44) Visual Object Recognition and Tracking of Tools; 45) Method for Implementing Optical Phase Adjustment; 46) Visual SLAM Using Variance Grid Maps; 47) Rapid Calculation of Spacecraft Trajectories Using Efficient Taylor Series Integration; 48) Efficient Kriging Algorithms; 49) Predicting Spacecraft Trajectories by the WeavEncke Method; 50) An Augmentation of G-Guidance Algorithms; 51) Comparison of Aircraft Icing Growth Assessment Software; 52) Silicon-Germanium Voltage-Controlled Oscillator at 105 GHz; 53) Estimation of Coriolis Force and Torque Acting on Ares-1; 54) Null Lens Assembly for X-Ray Mirror Segments; and 55) High-Precision Pulse Generator.

Source record↗
NASA NTRS2002

Context-specific adaptation of the gain of the oculomotor response to lateral translation using roll and pitch head tilts as contexts

Previous studies established that vestibular and oculomotor behaviors can have two adapted states (e.g., gain) simultaneously, and that a context cue (e.g., vertical eye position) can switch between the two states. The present study examined this phenomenon of context-specific adaptation for the oculomotor response to interaural translation (which we term "linear vestibulo-ocular reflex" or LVOR even though it may have extravestibular components). Subjects sat upright on a linear sled and were translated at 0.7 Hz and 0.3 gpeak acceleration while a visual-vestibular mismatch paradigm was used to adaptively increase (x2) or decrease (x0) the gain of the LVOR. In each experimental session, gain increase was asked for in one context, and gain decrease in another context. Testing in darkness with steps and sines before and after adaptation, in each context, assessed the extent to which the context itself could recall the gain state that was imposed in that context during adaptation. Two different contexts were used: head pitch (26 degrees forward and backward) and head roll (26 degrees or 45 degrees, right and left). Head roll tilt worked well as a context cue: with the head rolled to the right the LVOR could be made to have a higher gain than with the head rolled to the left. Head pitch tilt was less effective as a context cue. This suggests that the more closely related a context cue is to the response being adapted, the more effective it is.

Non-NASA Center↗
DOE OSTI2026

Uncovering hidden bias in neutron diffraction residual strain measurements

When calculating residual strain via neutron or X-ray diffraction, uncertainties propagated from the peak fit are often inadequate to describe the true scatter of measurements about a singular strain state, such as one that should describe a macroscopic continuum. Because diffraction is inherently a selective process, orientation-dependent scatter arises from the sub-sampling of strong microstructure and strain gradients. This paper investigates the appropriateness of propagated uncertainties with reference to their original intention, i.e. noise about a mean value. Thirty-six unique orientations of strain measurements are taken at multiple locations within an additive friction-stir deposition component with fine-scale gradients (∼200 µm) of plastic strain, texture and residual elastic strain. Multiple strain and stress calculation pathways are compared: direct substitution of three measurements into Hooke's law, direct inversion of any six unique orientations into the strain state tensor and thirty-six measurement least-squares estimation. For the last two cases, the appropriateness of the uncertainty interval is statistically evaluated on the basis of a physical constraint: common agreement under the strain transformation law. For this sample, the direct inversion of six measurements retains a conservative estimate of the uncertainty. However, propagated uncertainties in the least-squares solution greatly underestimate the true experimental scatter. A simple pathway to estimate appropriate uncertainty intervals is suggested. These results demonstrate that the interpretation of uncertainty in residual strain is strongly dependent on intrinsic sample-dependent effects, and that oversampling orientations and statistical analysis can give more accurate results with realistic uncertainties.

36 MATERIALS SCIENCE↗