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At least 1,783 records · Page 99

Generalized Linear Covariance Analysis

This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

Navagation↗

Thermal Inspection of Composite Honeycomb Structures

Composite honeycomb structures continue to be widely used in aerospace applications due to their low weight and high strength advantages. Developing nondestructive evaluation (NDE) inspection methods are essential for their safe performance. Pulsed thermography is a commonly used technique for composite honeycomb structure inspections due to its large area and rapid inspection capability. Pulsed thermography is shown to be sensitive for detection of face sheet impact damage and face sheet to core disbond. Data processing techniques, using principal component analysis to improve the defect contrast, are presented. In addition, limitations to the thermal detection of the core are investigated. Other NDE techniques, such as computed tomography X-ray and ultrasound, are used for comparison to the thermography results.

Zalameda, Joseph N.↗

Generalized Linear Covariance Analysis

This talk presents a comprehensive approach to filter modeling for generalized covariance analysis of both batch least-squares and sequential estimators. We review and extend in two directions the results of prior work that allowed for partitioning of the state space into solve-for'' and consider'' parameters, accounted for differences between the formal values and the true values of the measurement noise, process noise, and textita priori solve-for and consider covariances, and explicitly partitioned the errors into subspaces containing only the influence of the measurement noise, process noise, and solve-for and consider covariances. In this work, we explicitly add sensitivity analysis to this prior work, and relax an implicit assumption that the batch estimator's epoch time occurs prior to the definitive span. We also apply the method to an integrated orbit and attitude problem, in which gyro and accelerometer errors, though not estimated, influence the orbit determination performance. We illustrate our results using two graphical presentations, which we call the variance sandpile'' and the sensitivity mosaic,'' and we compare the linear covariance results to confidence intervals associated with ensemble statistics from a Monte Carlo analysis.

n/a↗

Global Scale Attribution of Anthropogenic and Natural Dust Sources and their Emission Rates Based on MODIS Deep Blue Aerosol Products

Our understanding of the global dust cycle is limited by a dearth of information about dust sources, especially small-scale features which could account for a large fraction of global emissions. Here we present a global-scale high-resolution (0.1 deg) mapping of sources based on Moderate Resolution Imaging Spectroradiometer (MODIS) Deep Blue estimates of dust optical depth in conjunction with other data sets including land use. We ascribe dust sources to natural and anthropogenic (primarily agricultural) origins, calculate their respective contributions to emissions, and extensively compare these products against literature. Natural dust sources globally account for 75% of emissions; anthropogenic sources account for 25%. North Africa accounts for 55% of global dust emissions with only 8% being anthropogenic, mostly from the Sahel. Elsewhere, anthropogenic dust emissions can be much higher (75% in Australia). Hydrologic dust sources (e.g., ephemeral water bodies) account for 31% worldwide; 15% of them are natural while 85% are anthropogenic. Globally, 20% of emissions are from vegetated surfaces, primarily desert shrublands and agricultural lands. Since anthropogenic dust sources are associated with land use and ephemeral water bodies, both in turn linked to the hydrological cycle, their emissions are affected by climate variability. Such changes in dust emissions can impact climate, air quality, and human health. Improved dust emission estimates will require a better mapping of threshold wind velocities, vegetation dynamics, and surface conditions (soil moisture and land use) especially in the sensitive regions identified here, as well as improved ability to address small-scale convective processes producing dust via cold pool (haboob) events frequent in monsoon regimes.

aerosols↗

Analyzing the Impacts of Natural Environments on Launch and Landing Availability for NASA's Exploration Systems Development Programs

The National Aeronautics and Space Administration (NASA) is developing new capabilities for human and scientific exploration beyond Earth orbit. Natural environments information is an important asset for NASA's development of the next generation space transportation system as part of the Exploration Systems Development (ESD) Programs, which includes the Space Launch System (SLS) and Multi-Purpose Crew Vehicle (MPCV) Programs. Natural terrestrial environment conditions - such as wind, lightning and sea states - can affect vehicle safety and performance during multiple mission phases ranging from pre-launch ground processing to landing and recovery operations, including all potential abort scenarios. Space vehicles are particularly sensitive to these environments during the launch/ascent and the entry/landing phases of mission operations. The Marshall Space Flight Center (MSFC) Natural Environments Branch provides engineering design support for NASA space vehicle projects and programs by providing design engineers and mission planners with natural environments definitions as well as performing custom analyses to help characterize the impacts the natural environment may have on vehicle performance. One such analysis involves assessing the impact of natural environments to operational availability. Climatological time series of operational surface weather observations are used to calculate probabilities of meeting/exceeding various sets of hypothetical vehicle-specific parametric constraint thresholds. Outputs are tabulated by month and hour of day to show both seasonal and diurnal variation. This paper will discuss how climate analyses are performed by the MSFC Natural Environments Branch to support the ESD Launch Availability (LA) Technical Performance Measure (TPM), the SLS Launch Availability due to Natural Environments TPM, and several MPCV (Orion) launch and landing availability analyses - including the 2014 Orion Exploration Flight Test 1 (EFT-1) mission.

Altino, Karen M.↗

Analyzing the Impacts of Natural Environments on Launch and Landing Availability for NASA's Eploration Systems Development Programs

NASA is developing new capabilities for human and scientific exploration beyond Earth orbit. Natural environments information is an important asset for NASA's development of the next generation space transportation system as part of the Exploration Systems Development Program, which includes the Space Launch System (SLS) and MultiPurpose Crew Vehicle (MPCV) Programs. Natural terrestrial environment conditions - such as wind, lightning and sea states - can affect vehicle safety and performance during multiple mission phases ranging from prelaunch ground processing to landing and recovery operations, including all potential abort scenarios. Space vehicles are particularly sensitive to these environments during the launch/ascent and the entry/landing phases of mission operations. The Marshall Space Flight Center (MSFC) Natural Environments Branch provides engineering design support for NASA space vehicle projects and programs by providing design engineers and mission planners with natural environments definitions as well as performing custom analyses to help characterize the impacts the natural environment may have on vehicle performance. One such analysis involves assessing the impact of natural environments to operational availability. Climatological time series of operational surface weather observations are used to calculate probabilities of meeting or exceeding various sets of hypothetical vehicle-specific parametric constraint thresholds.

Altino, Karen M.↗

Nondestructive Evaluation (NDE) for Inspection of Composite Sandwich Structures

Composite honeycomb structures are widely used in aerospace applications due to their low weight and high strength advantages. Developing nondestructive evaluation (NDE) inspection methods are essential for their safe performance. Flash thermography is a commonly used technique for composite honeycomb structure inspections due to its large area and rapid inspection capability. Flash thermography is shown to be sensitive for detection of face sheet impact damage and face sheet to core disbond. Data processing techniques, using principal component analysis to improve the defect contrast, are discussed. Limitations to the thermal detection of the core are investigated. In addition to flash thermography, X-ray computed tomography is used. The aluminum honeycomb core provides excellent X-ray contrast compared to the composite face sheet. The X-ray CT technique was used to detect impact damage, core crushing, and skin to core disbonds. Additionally, the X-ray CT technique is used to validate the thermography results.

Zalameda, Joseph N.↗

Understanding Differences in Chemistry Climate Model Projections of Stratospheric Ozone

Chemistry climate models (CCMs) are used to project future evolution of stratospheric ozone as concentrations of ozone-depleting substances (ODSs) decrease and greenhouse gases increase, cooling the stratosphere. CCM projections exhibit not only many common features but also a broad range of values for quantities such as year of ozone return to 1980 and global ozone level at the end of the 21st century. Multiple linear regression is applied to each of 14 CCMs to separate ozone response to ODS concentration change from that due to climate change. We show that the sensitivity of lower stratospheric ozone to chlorine change Delta Ozone/Delta inorganic chlorine is a near-linear function of partitioning of total inorganic chlorine into its reservoirs; both inorganic chlorine and its partitioning are largely controlled by lower stratospheric transport. CCMs with best performance on transport diagnostics agree with observations for chlorine reservoirs and produce similar ozone responses to chlorine change. After 2035, differences in Delta Ozone/Delta inorganic chlorine contribute little to the spread in CCM projections as the anthropogenic contribution to inorganic chlorine becomes unimportant. Differences among upper stratospheric ozone increases due to temperature decreases are explained by differences in ozone sensitivity to temperature change Delta Ozone/Delta T due to different contributions from various ozone loss processes, each with its own temperature dependence. Ozone decrease in the tropical lower stratosphere caused by a projected speedup in the Brewer-Dobson circulation may or may not be balanced by ozone increases in the middle- and high-latitude lower stratosphere and upper troposphere. This balance, or lack thereof, contributes most to the spread in late 21st century projections.

Stratospheric Transport↗

Multi-Wheat-Model Ensemble Responses to Interannual Climate Variability

We compare 27 wheat models' yield responses to interannual climate variability, analyzed at locations in Argentina, Australia, India, and The Netherlands as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Wheat Pilot. Each model simulated 1981e2010 grain yield, and we evaluate results against the interannual variability of growing season temperature, precipitation, and solar radiation. The amount of information used for calibration has only a minor effect on most models' climate response, and even small multi-model ensembles prove beneficial. Wheat model clusters reveal common characteristics of yield response to climate; however models rarely share the same cluster at all four sites indicating substantial independence. Only a weak relationship (R2 0.24) was found between the models' sensitivities to interannual temperature variability and their response to long-termwarming, suggesting that additional processes differentiate climate change impacts from observed climate variability analogs and motivating continuing analysis and model development efforts.

uncertainty↗

Ozone Sensitivity to Varying Greenhouse Gases and Ozone-Depleting Substances in CCMI-1 Simulations

Ozone fields simulated for the first phase of the Chemistry-Climate Model Initiative (CCMI-1) will be used as forcing data in the 6th Coupled Model Intercomparison Project. Here we assess, using reference and sensitivity simulations produced for CCMI-1, the suitability of CCMI-1 model results for this process, investigating the degree of consistency amongst models regarding their responses to variations in individual forcings. We consider the influences of methane, nitrous oxide, a combination of chlorinated or brominated ozone-depleting substances, and a combination of carbon dioxide and other greenhouse gases. We find varying degrees of consistency in the models' responses in ozone to these individual forcings, including some considerable disagreement. In particular, the response of total-column ozone to these forcings is less consistent across the multi-model ensemble than profile comparisons. We analyse how stratospheric age of air, a commonly used diagnostic of stratospheric transport, responds to the forcings. For this diagnostic we find some salient differences in model behaviour, which may explain some of the findings for ozone. The findings imply that the ozone fields derived from CCMI-1 are subject to considerable uncertainties regarding the impacts of these anthropogenic forcings. We offer some thoughts on how to best approach the problem of generating a consensus ozone database from a multi-model ensemble such as CCMI-1.

CCMI↗

Lightning Strike Distance Distribution Beyond a Preexisting Lightning Area

The 45th Weather Squadron (45 WS) asked the Applied Meteorology Unit (AMU) to review the 30-year-old, lightning stand-off distances of 5 nautical miles (nmi) for applicability to today's operations. This was based on the realization that previous lightning strike distance studies did not match how 45 WS issues lightning warnings (Roeder, 2008). The previous lightning distance studies were from the point of origin of the lightning or the average starting location that would tend to be in the core of the thunderstorm. However, the 45 WS issues lightning warnings based on the edge of a preexisting lightning area. Before beginning the AMU project, it took several years to develop a method to calculate a distance distribution beyond a preexisting area (Roeder, 2015). The AMU pulled Lightning Detection and Ranging (LDAR) sensor data from 1/1/2013 to 12/31/2013. This dataset consisted of 37 million individual source data points from the LDAR sensors. Only sources within 50 km north, south, east or west of the LDAR grid center were included in the dataset. This limited the use of LDAR data to that with the greatest accuracy of source detection and increased data processing. Points were grouped into flashes based on spatial and temporal criteria. Based on the sensitivity analysis the AMU performed on the flash clustering algorithm, a time value of 0.3 seconds was found to model flashes adequately. Distance parameters were tested from 1,500 to 7,500 meters (m) in 500 m increments. Distance parameters of both 3,000 m and 4,000 m produced results in the plotting tool that were most representative of the physical behavior of lightning. Thus statistics were gathered for the most representative of these spatial and temporal criteria on the flash size and the polygon expansion distance in order to find the correct data distributions. The best fit curves for the LDAR polygon expansion frequency vs. distances for both the 3 kilometer (km) and 4 km distance threshold values were exponential decay functions and had R2 values of > 0.998, indicating good model fits. The equations of the best fit curves were then used to calculate a desired safety radius of 4 nmi for either 3 km or 4 km distance threshold criteria. The AMU analysis concludes the safe reduction of the 5 nmi lightning warning circles to 4 nmi should improve the operational impact by 36% if based on distance from the center of the property area being protected. If based on the edge of the property being protected, then the reduction is 4.5 nmi to 4 nmi and the operational impact is decreased by 21%. For the 6 nmi lightning warning circles, the recommended 4 nmi stand-off distance will result in a safe reduction of operational impact of 31% if based on the center of the area being protected, or 16% if based on the edge of the property.

Flash clustering algorithm↗

The Effects of CDKN1a/p21 on Oxidative Stress and Mitochondrial Function During Long Duration Spaceflight

Broad tissue degeneration and the failure of normal tissue regenerative processes in microgravity because of mechanical unloading are increasing concerns for sustaining life in space as the duration of future flight missions increases. Work in our laboratory has identified normal adult stem cell-based tissue regenerative processes, such as the formation of new bone, cartilage, and immune cells, as being particularly sensitive to the stresses of mechanical unloading in microgravity. Our studies have also identified the inhibition of differentiation of marrow mesenchymal stem cells and activation of CDKN1ap21-mediated cell cycle arrest in proliferative osteoprecursor cells on the bone surface as potential mechanisms for spaceflight-induced skeletal changes. This finding, in combination with the role of CDKN1ap21 as a suppressor of mammalian tissue regeneration, suggests that this gene could be responsible for suppressing stem cell-based tissue regeneration in response to disuse. In this work, we hypothesized that CDKN1ap21 regulates regenerative bone formation in response to alterations in mechanical load and tested this hypothesis by studying the skeletal phenotype and stem cell regenerative ability of juvenile (4-11 weeks old) and adult (18 weeks-12 months old) p21 (--) knockout (KO) mice. Additionally, we analyzed bone micro-architectural properties, bone formation rates and differentiation capacity of bone marrow stem cells (BMSCs) from male and female KO mice exposed to hindlimb unloading (HU) for 15-30 days. We found that juvenile KO mice exhibited increased femoral trabecular and cortical bone formation, whilst three-point bending of the tibias from KO mice showed decreased bone stiffness. Conversely, adult KO mice exhibited no significant differences in micro-architectural properties compared to WT (wild-type) but woven bone structure was indicative of rapid bone remodeling. Furthermore, cortical bone properties showed similar characteristics to aged bone, including increased cross-sectional area and perimeter, whilst three-point bending showed increased stiffness and toughness. Interestingly, in-vitro, KO mice exhibited increased differentiation and mineralized nodule formation in osteoblastogenesis assays compared to WT. Preliminary results from CDKN1ap21 KO mice subjected to HU suggest altered sensitivity to mechanical unloading resulting in decreased cortical thickness compared to WT mice. However, KO mice subjected to short and long-duration HU show increased in-vitro differentiation potential of BMSCs to from form mature, mineral-forming osteoblasts, indicating maintenance of regenerative potential. Analysis of bone formation rates, cell proliferation rates and key genes of interest are currently underway. These results indicate a novel role for CDKN1ap21 in load-dependent osteoprogenitor proliferation and differentiation and that deletion of CDKN1ap21 results in an age-dependent release of osteoblast proliferation inhibition and increased bone formation and turnover.

Stem Cells↗

IceCube: Spaceflight Demonstration of 883-GHz Cloud Radiometer for Future Science

Cloud ice play important roles in Earth’s climate and weather systems through their interactions with atmospheric radiation, dynamics, energy and precipitation processes. Submillimeter (submm) wave remote sensing at 200-1000 GHz is able to provide the sensitivity not covered by visible (VIS)/infrared (IR) and low-frequency microwave (MW) sensors (10-183 GHz), and measure cloud ice in the middle-to-upper troposphere. The IceCube 883-GHz cloud radiometer is the latest of NASA’s efforts to advance the technology readiness level (TRL) of submm-wave receiver technology for future compact, low-cost implementation of Earth observing systems. Emerging CubeSat opportunities allow a fast-track development and spaceflight demonstration of IceCube on a 3-U CubeSat. Funded by NASA’s In-Space Validation of Earth Science Technologies (InVEST) program and Science Mission Directorate (SMD), IceCube is the first CubeSat developed and flown by Goddard Space Flight Center (GSFC) in 2.5 years, using commercial off-the-shelf (COTS) components and subsystems. It was successfully released from International Space Station (ISS) in May 2017, acquired 15-month science data and produced the first global map of the 883-GHz cloud ice. It achieved all mission objectives and provided a pathway for future cost-effective cloud observations from CubeSat constellation.

Submm-wave remote sensing↗

Performance Impacts to the NASA Artemis II Trajectory Correction Burn Placement

As NASA embarks to return humans to the lunar vicinity with the upcoming Artemis II mission, the selected free return trajectory taking the crew to the Moon in the Orion spacecraft is impacted by the execution of small trajectory correction burns to ensure the spacecraft stays on course for a successful return to Earth. The placement of these nominally zero translational maneuvers must account for the crew schedule, navigation tracking constraints, spacecraft venting, thermal and communication requirements, and a host of other programmatic factors. Understanding the influence the placement of these periodic burn corrections have on the integrated GN\&C performance can provide valuable insight to mission controllers and trajectory planning processes to untangle the complex trade space considered for both baseline and contingency scenarios. This sensitivity information can also be utilized to facilitate the optimized placement of these burns. This paper utilizes several techniques to systematically generate the performance impacts to the NASA Artemis II trajectory correction burn placement and demonstrate how to derive optimized locations that make the system robust to crew activity, maneuver execution errors, navigation uncertainty, orbit insertion errors, disturbance accelerations, and other system limitations.

GN&C↗

Discovering neutrino tridents at the Large Hadron Collider

Neutrino trident production of di-lepton pairs is well recognized as a sensitive probe of both electroweak physics and physics beyond the Standard Model. Although a rare process, it could be significantly boosted by such new physics, and it also allows the electroweak theory to be tested in a new regime. We demonstrate that the forward neutrino physics program at the Large Hadron Collider offers a promising opportunity to measure for the first time, dimuon neutrino tridents with a statistical significance exceeding $5\sigma$. We present predictions for various proposed experiments and outline a specific experimental strategy to identify the signal and mitigate backgrounds, based on "reverse tracking" dimuon pairs in the FASER$\nu$2 detector. We also discuss prospects for constraining beyond Standard Model contributions to neutrino trident rates at high energies.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Online and Offline Data Quality Monitoring for the Mu2e Calorimeter

This thesis presents the design, implementation, and validation of a calorimeter Data Quality Monitoring (DQM) toolchain for the Mu2e experiment at Fermilab. Mu2e searches for charged lepton flavor violation via coherent muon-to-electron conversion in the field of an aluminum nucleus, $\mu^- Al \rightarrow e^-Al$, a process whose observation would constitute clear evidence of physics beyond the Standard Model. Achieving target sensitivity requires stringent control of detector performance and data integrity during acquisition, as subtle issues in readout configuration, data formatting, or electronics behavior can compromise reconstruction and bias downstream analyzes. To address these challenges, this work develops a multi-layer DQM approach spanning both raw data validation and reconstructed digi-level diagnostics. At the low level, a fragment analysis component performs word- and bit-field decoding of calorimeter readout blocks, enabling sanity checks of the expected structure and producing detailed error and integrity statistics useful for commissioning and troubleshooting. At the digi level, the CaloDigiDQM analyzer is implemented within the art framework and transforms each CaloDigiCollection into a structured hierarchy of ROOT histograms designed for fast drill-down diagnostics. The module generates coherent monitoring views at global, disk, board, and channel granularity, including occupancy, waveform-derived features (baseline, RMS, peak amplitude and position), and left-right sensor consistency metrics. Detector-aware channel-to-electronics mapping is performed through the conditions system (CaloDAQMap), ensuring that diagnostics remain aligned with hardware identifiers used in operations. For end-to-end testing without reliance on live DAQ data, a synthetic CaloDigi producer is developed to generate realistic waveforms with controlled noise and pulse shapes. The resulting system supports both offline ROOT-file production and online operation, including optional histogram streaming through otsdaq via ots::HistoSender. This toolchain provides a practical and scalable foundation for calorimeter commissioning and stable data collection, enabling early detection of anomalies and reducing operational risk for Mu2e.

Vakulenko, Mark [Drew U.] (ORCID:0009000276197818)↗

Fabrication of Tunnel Junctions For Direct Detector Arrays With Single-Electron Transistor Readout Using Electron-Beam Lithography

This paper will describe the fabrication of small aluminum tunnel junctions for applications in astronomy. Antenna-coupled superconducting tunnel junctions with integrated single-electron transistor readout have the potential for photon-counting sensitivity at sub-millimeter wavelengths. The junctions for the detector and single-electron transistor can be made with electron-beam lithography and a standard self-aligned double-angle deposition process. However, high yield and uniformity of the junctions is required for large-format detector arrays. This paper will describe how measurement and modification of the sensitivity ratio in the resist bilayer was used to greatly improve the reliability of forming devices with uniform, sub-micron size, low-leakage junctions.

Stevenson, T. R.↗

All-purpose, all-sky photometric redshifts for the Legacy Imaging Surveys Data Release 8

ABSTRACT In this paper, we present photometric redshift (photo-z) estimates for the Dark Energy Spectroscopic Instrument (DESI) Legacy Imaging Surveys, currently the most sensitive optical survey covering the majority of the extragalactic sky. Our photo-z methodology is based on a machine-learning approach, using sparse Gaussian processes augmented with Gaussian mixture models (GMMs) that allow regions of parameter space to be identified and trained separately in a purely data-driven way. The same GMMs are also used to calculate cost-sensitive learning weights that mitigate biases in the spectroscopic training sample. By design, this approach aims to produce reliable and unbiased predictions for all parts of the parameter space present in wide area surveys. Compared to previous literature estimates using the same underlying photometry, our photo-zs are significantly less biased and more accurate at z > 1, with negligible loss in precision or reliability for resolved galaxies at z < 1. Our photo-z estimates offer accurate predictions for rare high-value populations within the parent sample, including optically selected quasars at the highest redshifts (z > 6), as well as X-ray or radio continuum selected populations across a broad range of flux (densities) and redshift. Deriving photo-z estimates for the full Legacy Imaging Surveys Data Release 8, the catalogues provided in this work offer photo-z estimates predicted to be of high quality for ≳9 × 108 galaxies over ${\sim}19\, 400\, \text{deg}^{2}$ and spanning 0 < z ≲ 7, offering one of the most extensive samples of redshift estimates ever produced.

79 ASTRONOMY AND ASTROPHYSICS↗