Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “corrections”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Surface Corrected Lunar MTF Measurements in MODIS and VIIRS Using the SP Model

Lunar observations have been used for sensor performance assessments for a number of Earth-observing instruments, including the Moderate Resolution Imaging Spectroradiometer (MODIS) on board Terra and Aqua and the Visible Infrared Imaging Radiometer Suite (VIIRS) on board Suomi-NPP (SNPP) and NOAA-20 (N20). While the primary purpose of lunar observations in MODIS and VIIRS is radiometric calibration, these observations have been leveraged for other sensor performance assessments such as spatial registration and deriving the modulation transfer function (MTF). In this work, we will derive the lunar MTF using a knife edge approach similar to previous work. However, to further isolate the edge of the lunar disk when deriving the edge spread function (ESF), we will apply a lunar surface variation correction using a model based on data obtained by the Spectral Profiler (SP) on board the SELENE spacecraft. This model was provided to us by AIST in Japan. To align the measured and modeled data, we developed techniques for projecting the measured lunar surface pixels onto the radiance maps produced by the SP model. We correct the lunar surface variation while preserving the signal of the lunar disk edge in the ESF, and then calculate the MTF results using standard techniques. These results are in good agreement with previously published results from both Moon-based observations in MODIS and VIIRS and from the spectroradiometric calibration assembly (SRCA) on MODIS. With the exception of MODIS bands 1 and 2, the MTF is stable on orbit for the reflective bands in both instruments.

MODIS↗
NASA NTRSDate not supplied

Planning and Execution of the Three Mid-Course Correction Maneuvers for the James Webb Space Telescope

The James Webb Space Telescope (JWST) was successfully launched on December 25, 2021 12:20 UTC on an Ariane 5 rocket out of Kourou, French Guiana on a direct, lower energy manifold transfer out to the Sun Earth-Moon (SEM) L2 point. Three mid-course correction (MCC) maneuvers, designated MCC-1, MCC-1b, and MCC-2, were required to provide the energy necessary to reach L2 due to a purposeful biasing down of the launch vehicle. This paper will document the prelaunch preparation, nominal planning, contingency preparation, and successful execution of the three mid-course correction maneuvers.

Maneuver Planning↗
NASA NTRSDate not supplied

An Investigation of Bluff Body Blockage Corrections Using the NASA/ODU 6-inch MSB

Spheres of different diameters were tested in the NASA/ODU 6-inch MSBS. The objective is to develop an improved understanding of blockage corrections to be made to other bluff-body geometries. Drag coefficients are shown with classical corrections applied, along with wall pressure signatures and base pressure measurements. Anomalous behavior was observed with the largest diameter, thought to be some form of flow breakdown, hence uncorrectable interference.

blunt body↗
NASA NTRSDate not supplied

Planning and Execution of the Three Mid-Course Correction Maneuvers for the James Webb Space Telescope

The James Webb Space Telescope (JWST) was successfully launched on December 25, 2021 12:20 UTC on an Ariane 5 rocket out of Kourou, French Guiana on a direct, lower energy manifold transfer out to the Sun Earth-Moon (SEM) L2 point. Three mid-course correction (MCC) maneuvers, designated MCC-1, MCC-1b, and MCC-2, were required to provide the energy necessary to reach L2 due to a purposeful biasing down of the launch vehicle. This paper will document the prelaunch preparation, nominal planning, contingency preparation, and successful execution of the three mid-course correction maneuvers.

Jeremy Peterson↗
NASA NTRSDate not supplied

Sensitivity of Optimal Midcourse Correction Scheduling for Robust Cislunar Trajectory Design

A new approach to optimal trajectory design is the determination of optimal trajectories that are robust to initial trajectory dispersions, navigation errors, maneuver execution errors, and environment modeling errors. This paper investigates the sensitivity of cislunar robust optimal trajectory design to launch date, duration of navigation measurement passes, and navigation measurement frequency. For a given cislunar trajectory from translunar injection (TLI) to lunar orbit insertion (LOI), the optimal locations of midcourse corrections, also known as trajectory correction maneuvers (TCM) are determined by minimizing the final 3-σ ∆v subject to a final 3-σ position dispersion constraint for a given launch date, specified measurement pass duration prior to each maneuver, and measurement frequency. Optical navigation (OpNav) is assumed, and OpNav field-of-view (FOV) and lighting constraints are employed. These constraints turn out to be important elements of the problem. The sensitivity of the optimal TCM locations are then investigated by varying the launch date, duration of OpNav measurement passes, and the OpNav measurement frequency, and then re-optimizing the locations of the TCMs. Given the problem parameters provided herein, results show that while the optimal TCM locations with respect to TLI vary greatly from one launch date to another, their locations with respect to LOI are nearly invariant over a 2-month launch window. Results also show that in all cases the optimal location of the last TCM is found to be at the point where the OpNav lunar FOV constraint is first violated. For all other TCMs, OpNav measurement pass duration and measurement frequency can have a moderate to large affect on the optimal TCM locations.

Linear Covariance Analysis↗
NASA NTRSDate not supplied

Optimized Trajectory Correction Burn Placement for the NASA Artemis II Mission

The NASA Artemis II mission represents the first time humans plan to return to the lunar vicinity in over 50 years with a crew traveling to the Moon in the Orion spacecraft on a free return trajectory. This first crewed mission of the Artemis program will evaluate human-rated elements of Orion in preparation to sending astronauts to the lunar surface. The selected free-return cislunar trajectory profile that is reminiscent of the Apollo 8 mission that nominally requires no additional translational burns following the trans-lunar injection (TLI) burn. Due to crew activity, maneuver execution errors, navigation uncertainty, orbit insertion errors, disturbance accelerations, and other system limitations; periodic trajectory corrections burns are necessary to ensure proper entry interface (EI) conditions are satisfied for a safe return to Earth. Robust trajectory optimization techniques are utilized to determine the optimized placements for the Artemis II trajectory correction burns that accounts for the crew schedule, both the primary and backup navigation systems, targeting strategies and burn plan configurations, spacecraft venting, thruster selection, and the integrated GN&C performance.

Linear Covariance Analysis↗
NASA NTRS2022

Correction of Path Integrated Attenuation Estimates Considering the Soil Moisture Effect for the Gpm Dual-Frequency Precipitation Radar

Spaceborne precipitation radars, including the Tropical Rainfall Measuring Mission’s Precipitation Radar (PR) and the Global Precipitation Measurement Mission’s Dual-Frequency Precipitation Radar (DPR), measure not only precipitation echoes but surface echoes as well, the latter of which are used to estimate the path-integrated attenuation (PIA) in the surface reference technique (SRT). In our previous study based on analyzing PR measurements, we found that attenuation-free surface backscattering cross sections (denoted by s0e) over land increased in the presence of precipitation. This behavior, called the soil moisture effect, causes an underestimate of the PIA by the SRT as the method does not explicitly consider this effect. In this study, measurements made by Ku-band Precipitation Radar (KuPR) and Ka-band Precipitation Radar (KaPR), which comprise the DPR, were analyzed to examine whether KuPR and KaPR exhibit similar dependencies on the soil moisture as does the PR. For both KuPR and KaPR, an increase in s0e was observed for a large portion of the land area, except for forests and deserts. Results from the Hitschfeld–Bordan (HB) method suggest that s0e increases with the surface precipitation rate for light precipitation events. Meanwhile, for heavy precipitation, owing to the degradation of the HB method, it is difficult to estimate s0e quantitatively. Thus, a correction method for PIA that considers the soil moisture effect was developed and implemented into the DPR standard algorithm. With this correction, the surface precipitation rate estimates increased by approximately 18%for KuPR and 15%for the normal scan of KaPR over land.

Shinta Seto↗
NASA NTRS2022

Precipitation over the U.S. Coastal Land/Water Using Gauge-Corrected Multi-Radar/Multi-Sensor System and Three Satellite Products

The weather and climate over the coastal regions have received increasing attention because of substantial population growth, the rising sea level, and extreme weather. Satellite remote sensing provides global precipitation estimates (including coastal land/ocean). While these datasets have been extensively evaluated over land, they have rarely been assessed over coastal ocean. As precipitation radars cover both coastal land and ocean, we used the Multi-Radar/Multi-Sensor System (MRMS) gauge-corrected precipitation product from 2018 to 2020 to evaluate three widely used satellite-based precipitation products over the U.S. coastal land versus the ocean (and the water over the Great Lakes). These products included the Integrated Multi-satellite Retrievals for GPM (IMERG), Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks (PERSIANN), and Climate Prediction Center Morphing technique (CMORPH). The MRMS data showed a precipitation climatology difference between the coastal land and the ocean that was higher in the winter and lower in the summer and autumn. IMERG and CMORPH performed best over land and water, respectively, while PERSIANN was the most consistent in its performance over land versus water. Heavy precipitation was overestimated by the three products, with larger overestimates over water than over land. These results were not affected by the MRMS uncertainties due to the gauge correction or by the use of different versions.

coastal precipitation↗
NASA NTRSDate not supplied

Dose Error Correction Using Simulation Extrapolation for Community Noise Dose-Response Modeling

The objective of this work is to provide a framework to account and correct for dose error in dose-response modeling due to measurement uncertainty. Error in noise measurements, especially in the case of limited monitoring locations in a community, can lead to an attenuation or misestimation of parameters in dose-response models. This error can result in overpredicted annoyance at lower doses and underpredicted annoyance at higher doses. Simulated data in the present work are based on previous NASA community studies and incorporate a notional design for future studies with the X-59 aircraft. Several populations of different annoyance response sensitivities are included. Simulation extrapolation (SIMEX, Cook and Stefanski 1994) is used to correct for the dose error in a simple, fully pooled logistic regression. Results indicate the negative impact of attenuation is greatly diminished for all amounts of dose error considered, regardless of a population’s annoyance sensitivity. Therefore, SIMEX can help produce a more accurate dose-response relationship.

SIMEX↗
NASA NTRSDate not supplied

Improving Ocean Reanalyses and ENSO Forecasts By Assimilation of Rain Corrected Satellite Sea Surface Salinity Using the GMAO S2S Forecast System

During the past years, we have seen that the La Nina to El Nino transition has had a significant global socio-economic impact and so has been the key focus for improving coupled ocean-atmosphere forecasts. Assimilation of satellite altimetry and subsurface temperature and salinity from (mostly) Argo help to improve the initialization of the thermocline, while satellite Sea Surface Temperature (SST) aids in constraining surface heat-fluxes, leading to improved subseasonal to seasonal forecasts of the coupled system. However, few studies have focused on improving the fresh-water flux and near-surface density and mixing through assimilation of satellite sea surface salinity (SSS). For expediency, the few ocean models that do assimilate SSS bias-correct the satellite SSS data to normalize towards the near-surface Argo data. However, in rainy regions, where buoyant water sits as a fresh lens at the surface, this assumption is likely inadequate. In previous work, we have shown that adjusting SSS data to bulk salinity (Sb) using the Rain Impact Model (RIM) of Santos-Garcia et al., 2014 has improved the near-surface density and mixed layer depth, leading to deeper thermocline and improved the NINO3.4 SST forecasts. Now we utilize the Soil Moisture/Ocean Salinity, Rain Corrected (SMOS_RC) SSS product provided by the Centre Aval de Traitement des données SMOS (CATDS CPDC) to represent the Sb more accurately at first model layer (in our case 5 m). Rather than using a diffusivity model as with RIM, SMOS_RC relies on an observed relationship between the spatial heterogeneity of SMOS SSS and instantaneous rain rate (RR) (Supply et al., 2020). In order to test the impact of SMOS_RC versus SMOS, we compare two reanalyses over the period 2014 to 2021. For both reanalysis experiments, all available along-track absolute dynamic topography and in situ observations are assimilated using the LETKF scheme (Penny et al., 2013). One reanalysis additionally assimilates SMOS SSS data as is (i.e., with the fresh bias), and a separate reanalysis is performed assimilating the SMOS_RC data. We assess the impact for near-surface and subsurface dynamics within ocean reanalyses by validating against observations and explore how SSS assimilation (SMOS versus SMOS_RC) impacts dynamical ENSO forecasts using the NASA GMAO Sub-seasonal to Seasonal coupled forecast system (GEOS S2S-3, Molod et al., 2020, Hackert et al., 2023). We will show that improved SSS estimates and near-surface density and mixing led to more accurate coupled air/sea interaction and better ENSO forecasts.

Eric Hackert↗
NASA NTRSDate not supplied

A NASA Perspective on Quantum AI, Error Correction, and Beyond

Quantum computing is one of the most enticing computational paradigms with the potential to revolutionize diverse areas of future-generation computational systems. While quantum computing hardware has advanced rapidly, from tiny laboratory experiments to quantum chips that can outperform even the largest supercomputers on specialized computational tasks, these noisy-intermediate scale quantum (NISQ) processors are still too small and non-robust to be directly useful for any real-world applications. We discuss the prospects for quantum computing and AI, highlighting advances in algorithms, both near- and longer-term. Quantum error correction is critical to the realization of any such vision. The talk with touch on some recent exciting advanced in quantum error correction, particularly in dynamical codes. The talk will conclude with an example of how the combination of quantum computing and artificial intelligence can help probe fundamental aspect of quantum physics.

quantum optimization algorithms and sampling↗
NASA NTRSDate not supplied

IXPECALCARF: vignetting and aperture corrections for IXPE spectropolarimetric data analysis

We report recent updates to IXPECALCARF, a tool developed by the IXPE Science Operation Center to generate Ancillary Response File (ARF) and Modulation Response File (MRF) for X-ray spectropolarimetric data analysis for IXPE. Using the Crab Nebula as a case study, we demonstrate corrections due to IXPE dithering patterns and off-axis corrections for user-defined regions when analyzing diffuse emissions away from the IXPE optical axis.

IXPE↗