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Five years of particle impact data obtained from Pioneer 8 and 9 have established reliable frequency levels for the near ecliptic region covered. This analysis is concerned with obtaining a multiplier which permits an estimate of the particle flux through a 1-A.U. sphere centered at the sun.
This report presents the methodology used for receiving, processing, and analyzing flight data from the Space Transportation System at NASA Langley Research Center (LaRC) on a near real time basis. The task was performed in October 1993 during the STS-58 mission using data from the Orbital Acceleration Research Experiment (OARE). The transmitting and receiving of OARE data on a near real time basis at LaRC were highly successful. The time to receive and record the data from the payload tape recorder required 20 to 30 minutes. Payload tape recorder data were downlinked at intervals of 4 to 6 hours rather than continuously. The quality check of the data at LaRC required 2 minutes. Four to 5 minutes of time was required to obtain preliminary acceleration levels of the Orbiter that are within 1 micro-g of the absolute accelerations This demonstration has shown that, with operational modifications LaRC has the capability to serve as a User Operation Center for receiving and processing flight data from the Space Shuttle and Space Station.
Development of the wind turbine sound prediction code began as part of an effort understand and reduce the noise generated by Mod-1. Tone sound levels predicted with this code are in good agreement with measured data taken in the vicinity Mod-1 wind turbine (less than 2 rotor diameters). Comparison in the far field indicates that propagation effects due to terrain and atmospheric conditions may amplify the actual sound levels by 6 dB. Parametric analysis using the code shows that the predominant contributors to Mod-1 rotor noise are (1) the velocity deficit in the wake of the support tower, (2) the high rotor speed, and (3) off-optimum operation.
The test procedures required to evaluate the performance of the Space Lab Bus Interface Unit (SL/BIU) are described. This level of testing involves the design evaluation of signal levels, timing, and signal-to-noise (S/N) performance. The tests are to be comprehensive in order to provide data on the operational characteristics of the SL/BIU. The evluation tests are designed to accomplish the following determinations as a minimum for component level testing of the SL/BIU: (1) the baseline operation parameters for comparison to ICD 2-05301 requirements; (2) the influence of serial data line parameter variation on the operation of SL/BIU; (3) the effects of noise on discrete and serial data lines (S/N ratio); and (4) the effects of cable length variation.
This study models the transition of CO 2 -enhanced oil recovery (CO 2 -EOR) fields to dedicated carbon storage using a generalized reservoir model informed by real field data, SACROC. Through scenario-based simulations, the work evaluates how reservoir depletion levels, boundary conditions, fluid properties, and domain size affect pressure buildup, CO 2 plume migration, and long-term containment performance. The results inform practices for repurposing oil fields into reliable CO 2 storage sites.
Variation of the cosmic ray intensity as a function away from the sun and its radial derivative is studied by plotting satellite cosmic ray measurements against sea level neutron monitor data. Results show that the solar modulation cavity extends well beyond 2 AU and that irregularities in the sun's magnetic field are carried outward radially by the solar wind, thus sweeping low energy cosmic rays out of the solar system and at the same time cooling cosmic rays reaching the earth.
Surface topography is an important variable in the performance of many industrial components and is normally measured with diamond-tip profilometry over a small area or using optical scattering methods for larger area measurement. This article shows quantitative surface topography profiles as obtained using only high-frequency focused air-coupled ultrasonic pulses. The profiles were obtained using a profiling system developed by NASA Glenn Research Center and Sonix, Inc (via a formal cooperative agreement). (The air transducers are available as off-the-shelf items from several companies.) The method is simple and reproducible because it relies mainly on knowledge and constancy of the sound velocity through the air. The air transducer is scanned across the surface and sends pulses to the sample surface where they are reflected back from the surface along the same path as the incident wave. Time-of-flight images of the sample surface are acquired and converted to depth/surface profile images using the simple relation (d = V*t/2) between distance (d), time-of-flight (t), and the velocity of sound in air (V). The system has the ability to resolve surface depression variations as small as 25 microns, is useable over a 1.4 mm vertical depth range, and can profile large areas only limited by the scan limits of the particular ultrasonic system. (Best-case depth resolution is 0.25 microns which may be achievable with improved isolation from vibration and air currents.) The method using an optimized configuration is reasonably rapid and has all quantitative analysis facilities on-line including 2-D and 3-D visualization capability, extreme value filtering (for faulty data), and leveling capability. Air-coupled surface profilometry is applicable to plate-like and curved samples. In this article, results are shown for several proof-of-concept samples, plastic samples burned in microgravity on the STS-54 space shuttle mission, and a partially-coated cylindrical ceramic composite sample. Impressive results were obtained for all samples when compared with diamond-tip profiles and measurements from micrometers. The method is completely nondestructive, noninvasive, non-contact and does not require light-reflective surfaces.
A Navier-Stokes computation is performed for a ducted-fan configuration with the goal of predicting rotor-stator noise generation without having to re- to heuristic modeling. The calculated pressure field in the inlet region is decomposed into classical infinite-duct, modes, which are then used in either a hybrid finite-element /Kirchhoff surface method or boundary integral equation method to calculate the far field noise. Comparisons with experimental data are presented, including rotor wake surveys and far field sound pressure levels for 2 blade passage frequency (BPF) tones.
We have successfully demonstrated significant improvements in the high contrast detection limit of the Well-Corrected Subaperture (WCS) using the Autonomous Phase Retrieval Calibration (APRC) software package developed at the Jet Propulsion Laboratory (JPL) for the Palomar adaptive optics instrument (PALAO). APRC utilizes the Modified Gerchberg-Saxton (MGS) wavefront sensing algorithm, also developed at JPL. The WCS delivers such excellent correction of the atmosphere that non-common path (NCP) wavefront errors not sensed by PALAO but present at the coronagraphic image plane begin to factor heavily as a limit to contrast. We have implemented the APRC program to reduce these NCP wavefront errors from 110 nm to 35 nm (rms) in the lab, and we have extended these exceptional results to targets on the sky for the first time, leading to a significant suppression of speckle noise. Consequently we now report a contrast level of very nearly 1x10(exp -4) at separations of 2 lambda/D before the data is post processed. We describe here the major components of our instrument, the work done to improve the NCP wavefront errors, and the ensuing excellent on sky results, including the detection of the three exoplanets orbiting the star HR8799.
This is a video replay of system data that was generated from the UAS Traffic Management (UTM) Technical Capability Level (TCL) 2 flight demonstration in Nevada and rendered in Google Earth. What is depicted in the replay is a particular set of flights conducted as part of what was referred to as the Ocean scenario. The test range and surrounding area are presented followed by an overview of operational volumes. System messaging is also displayed as well as a replay of all of the five test flights as they occurred.
Meteorological data from the United Kingdom Meteorological Office (UKMO) and constituent data from the Upper Atmospheric Research Satellite (UARS) are used to construct yearly zonal mean dynamical fields for the 1990s for use in the GSFC 2-D chemistry and transport model. This allows for interannual dynamical variability to be included in the model constituent simulations. In this study, we focus on the tropical stratosphere. We find that the phase of quasi-biennial oscillation (QBO) signals in equatorial CH4, and profile and total column 03 data is resolved quite well using this empirically- based 2-D model transport framework. However. the QBO amplitudes in the model constituents are systematically underestimated relative to the observations at most levels. This deficiency is probably due in part to the limited vertical resolutions of the 2-D model and the UKMO and UARS input data sets. We find that using different heating rate calculations in the model affects the interannual and QBO amplitudes in the constituent fields, but has little impact on the phase. Sensitivity tests reveal that the QBO in transport dominates the ozone interannual variability in the lower stratosphere. with the effect of the temperature QBO being dominant in the tipper stratosphere via the strong temperature dependence of the ozone loss reaction rates. We also find that the QBO in odd nitrogen radicals, which is caused by the QBO modulated transport of NOy, plays a significant but not dominant role in determining the ozone QBO variability in the middle stratosphere. The model mean age of air is in good overall agreement with that determined from tropical lower,middle stratospheric OMS balloon observations of SF6 and CO2. The interannual variability of tile equatorial mean age in the model increases with altitude and maximizes near 40 km, with a range, of 4-5 years over the 1993-2000 time period.
A-train sensors such as MODIS, MISR, and CALIPSO are used to determine aerosol properties, and in the process a means of estimating aerosol type (e.g. smoke vs. dust). Correct classification of aerosol type is important for climate assessment, air quality applications, and for comparisons and analysis with aerosol transport models. The Aerosols-Clouds-Ecosystems (ACE) satellite mission proposed in the NRC Decadal Survey describes a next generation aerosol and cloud suite similar to the current A-train, including a lidar. The future ACE lidar must be able to determine aerosol type effectively in conjunction with modeling activities to achieve ACE objectives. Here we examine the current capabilities of CALIPSO and the NASA Goddard Earth Observing System general circulation model and data assimilation system (GEOS-5), to place future ACE needs in context. The CALIPSO level 2 feature mask includes vertical profiles of aerosol layers classified by type. GEOS-5 provides global 3D aerosol mass for sulfate, sea salt, dust, and black and organic carbon. A GEOS aerosol scene classification algorithm has been developed to provide estimates of aerosol mixtures and extinction profiles along the CALIPSO orbit track. In previous work, initial comparisons between GEOS-5 derived aerosol mixtures and CALIPSO derived aerosol types were presented for July 2007. In general, the results showed that model and lidar derived aerosol types did not agree well in the boundary layer. Agreement was poor over Europe, where CALIPSO indicated the presence of dust and pollution mixtures yet GEOS-5 was dominated by pollution with little dust. Over the ocean in the tropics, the model appeared to contain less sea salt than detected by CALIPSO, yet at high latitudes the situation was reserved. Agreement between CALIPSO and GEOS-5, aerosol types improved above the boundary layer, primarily in dust and smoke dominated regions. At higher altitudes (> 5 km), the model contained aerosol layers not detected by CALIPSO. Here we present new results for a full year study using the new Version 3 CALIPSO data and most recent GEOS-5 model results.
The forest above-ground biomass (AGB) and spatial distribution of vegetation elements have profound effects on the productivity and biodiversity of terrestrial ecosystems. In this paper, we evaluated biomass estimation from L-band Synthetic Aperture Radar (SAR) data acquired by National Aeronautics and Space Administration (NASA) Uninhabited Aerial Vehicle SAR (UAVSAR) and the improvement of accuracy by adding canopy height information derived from stereo imagery acquired by Japan Aerospace Exploration Agency (JAXA) Panchromatic Remote Sensing Instrument for Stereo Mapping (PRISM) on-board the Advanced Land Observing Satellite (ALOS). Various models for prediction of forest biomass from UAVSAR data were investigated at pixel sizes of 1/4 ha (50 m x 50 m) and 1 ha. The variance inflation factor (VIF) was calculated for each of the explanatory variables in multivariable regression models to assess the multi-collinearity between explanatory variables. In addition, the t-and p-values were used to interpret the significance of the coefficients of each explanatory variables. The R(exp. 2), Root Mean Square Error (RMSE), bias and Akaike information criterion (AIC), and leave-one-out cross-validation (LOOCV) and bootstrapping were used to validate models. At 1/4-ha scale, the R(exp. 2) and RMSE of biomass estimation from a model using a single track of polarimetric UAVSAR data were 0.59 and 52.08 Mg/ha. With canopy height from PRISM as additional independent variable, R(exp. 2) increased to 0.76 and RMSE decreased to 39.74 Mg/ha (28.24%). At 1-ha scale, the RMSE of biomass estimation based on UAVSAR data of a single track was 39.42 Mg/ha with a R(exp. 2) of 0.77. With the canopy height from PRISM, R(exp. 2) increased to 0.86 and RMSE decreased to 29.47 Mg/ha (20.18%). The models using UAVSAR data alone underestimated biomass at levels above approximately 150 Mg/ha showing the saturation phenomenon. Adding canopy height from PRISM stereo imagery significantly improved the biomass estimation and elevated the saturation level in estimating biomass. Combined use of UAVSAR data acquired from opposite directions (odd and even tracks) slightly improved the biomass estimation.Combined use of UAVSAR data acquired from opposite directions (odd and even tracks) slightly improved the biomass estimation at 1/4-ha scale, R(exp. 2) increased from 0.59 to 0.66 and RMSE reduced from 52.08 to 48.57 Mg/ha. Averaging multiple acquisitions of UAVSAR data from the same look azimuth direction did not improve biomass estimation. A biomass map derived from NASA's LVIS (Laser Vegetation Imaging System) wave-form data was used as a reference for evaluation of the biomass maps from these models. The study has also shown that the errors decreased when deciduous, evergreen, and mixed forests were modeled separately but the improvement was not significant
Introduction: In 1997 NASA’S Discovery Program selected the Genesis mission proposal to return solar wind samples to Earth for laboratory analyses. Principal Investigator Donald S. Burnett and the science team defined the purity of collector materials and ability to analyze solar wind composition to the precision required for planetary science. As a small mission, focused on a well-defined science goal, yet needing careful attention to engineering details, the communication among scientists and engineers, nurtured by Don Burnett, was exceptional. Genesis Mission and Curation Legacy: Genesis, as the first U. S. spacecraft to return astromaterial samples since Apollo, not only integrated the mission planning and flight teams, but also the science and sample curation teams during the mission development period. Since Genesis is a sample return mission, the Science Team was essential in certifying the collectors (sample containers for solar atoms). From inception, Genesis established mission funding for returned sample curation. JSC was lead in contamination control during mission preparation, including establishment of an ISO 4 cleanroom facility and use of ultrapure water (UPW) for cleaning flight hardware (and, as it turned out, for cleaning collectors after the mishap). Reliable, fast communication among scientists, engineers and curators at the hands-on level established deep respect among team members and efficient decision-making. JSC’s 50-years of astromaterial sample curation provided experienced sample processors onsite during recovery in Utah (a deep bench for emergency response). Post-recovery curation included iterative collaboration with science sample users to clean or verify cleanliness of samples. The science legacy from Genesis is addressed by Burnett and Jurewicz, this volume. In The Beginning: After Apollo sample return, Burnett and Marcia Neugebauer at JPL began discussing a solar wind sample return, with Neugebauer arguing that separate collection of solar wind regimes was essential science. By 1992 a solar wind sample return mission was presented at a workshop, and by 1994 a mission was proposed named Suess-Urey. The mission was re-proposed under a new name GENESIS and selected in 1997. Susan Niebur captured the Genesis mission history and stories, from high level management documents and from many interviews with participants [2]. Her account lets readers glimpse personality of participants in quotations from interviews. Need and Scope for Detailed Technical Timeline: A timeline constructed from lower level task documents has been initiated to document the resources and skills actually used, as well as task sequence or concurrency. Timelines for high level mission events are captured in two documents [1] [2] and for detailed re-entry events in [3]. A detailed technical timeline for Genesis mission and curation activities will provide data points for lower level tasks, such as ISO 4 curation facility construction time, preparation for nominal sample field recovery, mishap recovery, and UPW expansion. Changes in technology context 1990-2024: Semiconductor technologies were easily accessible in the U.S.A. (1990-1999), and the Genesis team used those resources for cleanroom design and UPW system expansion. Image documentation was changing from film to digital during cleanroom construction and payload cleaning (1997-2001). Engineering design was done using computer aided design proprietary software, making more difficult the archiving of payload configuration and materials. Email of documents, tracked delivery service and virtual meeting capability greatly improved communication efficiency. Information sources – Pre-launch mission preparation: Examples of mission science, engineering and contamination control are collector purity testing, payload design/fabrication and ISO 4 cleanroom construction. Information on timing of these activities comes from facility readiness reviews, management reviews, shipping documents, procurement documents, test reports, travel documents, laboratory logs, Quality Assurance documents, dates on images, participant notebooks and emails. Information sources – Sample return re-entry and field recovery activities: Information comes from event timelines produced by Mid-Air Recovery team, Lockheed team lead notes and from chase video, JPL Quality Assurance. Information also comes from images and logbooks from UTTR cleanroom operations and from curatorial documents. Information sources – Resulting science and sample cleaning processes: Agendas from the annual gatherings of the science team initially trace testing for collector purity/cleanliness, and after sample recovery, include collector cleaning and cleanliness assessment. Post-recovery documents include curatorial orders and procedures, sample allocation documents and LPSC abstracts. Timeline Objectives: A simple spreadsheet timeline with headers DATE, EVENT, PEOPLE, COMMENT, INFORMATION SOURCE has been initiated and currently has over 90 entries. While this is not definitive historical research, it is a quick look at the evolution of Genesis curation with pointers to documents or people with information. Engineers for future missions may find useful points of comparison for development of facilities. References:[1] Genesis Mission Reference Document, (2011) JPL D-62382.[2] Niebur S. M., edited by Brown D. W. (2023) NASA’s Discovery Program: The First 20 Years of Competitive Planetary Exploration, NASA-SP-2023-4238.[3] Genesis Mishap Investigation Board Report, Vol. 1 (July 2005).
Cosmic-ray scatterings on the cosmic neutrino background induce a flux of gamma-rays and X-rays from boosted meson decays and charged lepton processes. Here we present the first estimate of this flux and its cumulative cosmological contribution. Confronting expectations with Fermi-LAT diffuse gamma-ray data, we find a limit on the cosmic neutrino background overdensity at the level of $η\lesssim 2 \times 10^{4}$ for a lightest neutrino mass of $m_ν\gtrsim0.1$ eV, orders of magnitude stronger than current direct laboratory probes, and comparable to constraints on the cosmic neutrino background obtained with IceCube. We further show that X-ray synchrotron emission from cascade electron-positron pairs in intergalactic magnetic fields provides a complementary, albeit weaker, constraint. We discuss how anisotropic signatures and future gamma-ray data from CTA could further improve bounds on the relic neutrino overdensity, approaching in sensitivity the $Λ$CDM expected density.
I participated to the 2019 Fermilab Italian Student Program under the supervision of Anadi Canepa and Lorenzo Uplegger. I worked with the Fermilab research group that is involved with the R&D of the CMS Outer Tracker. The Compact Muon Solenoid (CMS) is a a general-purpose detector located at the Large Hadron Collider (LHC), the world's most powerful particle accelerator. In the next years LHC will undergo the High-Luminosity LHC upgrade, which will bring its luminosity from 1 × 10 34 cm -2 s -1 to 1.5 × 10 34 cm -2 s -1 . This increase in luminosity will require an upgrade of CMS as well, in order to comply with the augmented rate of particles which will cross the detector. The CMS tracker is a detector, composed of various modules made of silicon pixel trackers and silicon strip trackers, whose aim is to reconstruct the trajectories of the particles produced by the collisions in LHC. The tracker is ideally divided in Inner Tracker and Outer Tracker. The HL-LHC upgrade put important challenges in the designing of the tracker. It will have to withstand the irradiation of a large fluence of particles, without suffering a too severe deterioration of its performance. In addition to this, in order to comply with the increased rate of events that CMS will need to detect, the tracker will be exploited for triggering at the fully hardware Level 1 Trigger, in contrast to the current tracker, whose data are only used for the software High-Level Trigger. This feature is managed by the "stub logic", which will be explained in chapter 2. During the months of August and September at Fermilab I carried out the data analysis of three test beam runs performed in the last two years on the 2S Outer Tracker Minimules. The 2S Minimoule consists of two silicon strip trackers placed one upon the other with the strips kept parallel.
With hundreds of SARS-CoV-2 lineages circulating in the global population, there is an ongoing need for predicting and forecasting lineage frequencies and thus identifying rapidly expanding lineages. Accurate prediction would allow for more focused experimental efforts to understand pathogenicity of future dominating lineages and characterize the extent of their immune escape. Here, we first show that the inherent noise and biases in lineage frequency data make a commonly-used regression-based approach unreliable. To address this weakness, we constructed a machine learning model for SARS-CoV-2 lineage frequency forecasting, called CovTransformer, based on the transformer architecture. We designed our model to navigate challenges such as a limited amount of data with high levels of noise and bias. We first trained and tested the model using data from the UK and the USA, and then tested the generalization ability of the model to many other countries and US states. Remarkably, the trained model makes accurate predictions two months into the future with high levels of accuracy both globally (in 31 countries with high levels of sequencing effort) and at the US-state level. Our model performed substantially better than a widely used forecasting tool, the multinomial regression model implemented in Nextstrain, demonstrating its utility in SARS-CoV-2 monitoring. Assuming a newly emerged lineage is identified and assigned, our test using retrospective data shows that our model is able to identify the dominating lineages 7 weeks in advance on average before they became dominant. Overall, our work demonstrates that transformer models represent a promising approach for SARS-CoV-2 forecasting and pandemic monitoring.
The NASA Langley Research Center (LaRC) has recently completed development of the Aerosol Wind Profiler (AWP) airborne Doppler wind lidar (DWL) instrument. AWP was supported by the NASA Earth Science Technology Office and the Earth Science Division, a project that adapted the Wind-Space Pathfinder (Wind-SP) DWL transceiver onto a structure for flight aboard a variety of NASA research aircraft. AWP demonstrates many technologies required for a space DWL mission, including a coherent-detection, optical heterodyne laser transmitter with high pulse energy (up to ~55 mJ) and repetition rate (200 Hz), electronic control of the beam path allowing for multiple viewing angles (allowing vector wind measurements) with no moving parts, compact highly-stable and tunable reference lasers allowing for high-precision measurement of velocity at long ranges while mitigating the impact of satellite platform velocity, and many others. AWP represents NASA’s only currently operational airborne 3-D wind profiling sensor. NASA LaRC was selected by the NOAA Joint Venture (JV) program to conduct a suborbital 3-D Wind measurement campaign demonstrate how data from a coherent-detection DWL like AWP could serve NOAA’s weather analysis and forecasting needs. The NOAA JV program is designed to work with the private sector, academia and other federal agencies to explore the feasibility and capability of emerging technologies spacecraft and other mission-specific tools to meet NOAA’s mission requirements. AWP was initially demonstrated on the NASA DC-8 within this JV program in October 2023, piggybacking on the NASA EcoDemonstrator mission focused on in-situ sampling of jet aircraft emissions and contrail formation from Everett, Washington. The in-situ sampling resulted in very frequent and rapid aircraft attitude changes which unfortunately degraded AWP data quality. But, during times with level flight and AVAPS dropsonde operations, AWP demonstrated excellent precision (< 2 m/s RMS) with high vertical (< 100 meter) resolution and 2 km spacing between profiles. AWP will be flown again on the NASA LaRC Gulfstream-3 from mid-September to mid-October 2024 out of Hampton, VA to complete the NOAA JV 3-D wind demonstration. Additional AWP flights will occur in early November from southern California during the NASA Active-Passive Profiling Experiment (APEX), focused on underflights of the NASA ER-2 equipped with many atmospheric profiling sensors. This presentation will summarize AWP measurements collected during these two fall 2024 flight campaigns, and how the AWP data compares with AVAPS dropsonde, NOAA weather prediction model, and GOES atmospheric motion vector data.