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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

Correlative Analysis of GRBs Detected by Swift and Suzaku- WAM

It is now well known that a complete understanding of the energetics of the prompt phase of gamma-ray bursts (GRBs) requires full knowledge of the spectrum, extending at least as high as the peak energy (Epeak) of the vF(v) spectrum. Since most gamma-ray bursts (GRBs) have Epeak above the energy range (15-150 keV) of the Burst Alert Telescope (BAT) on Swift, a full understanding of the prompt emission from Swift GRBs requires spectral fits over as broad an energy range as possible. This can be completed for bursts which are simultaneously detected by Swift BAT and the Suzaku Wide-band All-Sky Monitor (WAM), which covers the energy range from 50-5000 keV. Between the launch of Suzaku in July 2005 and the end of 2008, there were 44 gamma-ray bursts (GRBs) which triggered both Swift and WAM and an additional 41 bursts which triggered Swift and were detected by WAM, but did not trigger. A joint BAT-WAM team has cross-calibrated the two instruments using GRBs, and we are now able to perform joint fits on these bursts to determine spectral parameters including Epeak. The results of broad spectral fits allows us to understand the distribution of Epeak for Swift bursts and to calibrate Epeak estimators when Epeak is within the BAT energy range. For those bursts with spectroscopic redshifts, we can calculate the isotropic energy and study various correlations between Epeak and other global burst parameters. Here we present the results of joint Swift/BAT-Suzaku/WAM spectral fits for 77 of the bursts jointly detected by the two instruments. We show that the distribution of spectral fit parameters is consistent with distributions from earlier missions and confirm that Swift bursts are consistent with earlier reported relationships between Epeak and isotropic energy. We show through time-resolved spectroscopy that individual burst pulses are also consistent with this relationship.

Krimm, H.A.↗
NASA NTRS2008

Aircraft System Analysis of Technology Benefits to Civil Transport Rotorcraft

An aircraft systems analysis was conducted to evaluate the net benefits of advanced technologies on two conceptual civil transport rotorcraft, to quantify the potential of future civil rotorcraft to become operationally viable and economically competitive, with the ultimate goal of alleviating congestion in our airways, runways and terminals. These questions are three of many that must be resolved for the successful introduction of civil transport rotorcraft: 1) Can civil transport rotorcraft actually relieve current airport congestion and improve overall air traffic and passenger throughput at busy hub airports? What is that operational scenario? 2) Can advanced technology make future civil rotorcraft economically competitive in scheduled passenger transport? What are those enabling technologies? 3) What level of investment is necessary to mature the key enabling technologies? This study addresses the first two questions, and several others, by applying a systems analysis approach to a broad spectrum of potential advanced technologies at a conceptual level of design. The method was to identify those advanced technologies that showed the most promise and to quantify their benefits to the design, development, production, and operation of future civil rotorcraft. Adjustments are made to sizing data by subject matter experts to reflect the introduction of new technologies that offer improved performance, reduced weight, reduced maintenance, or reduced cost. This study used projected benefits from new, advanced technologies, generally based on research results, analysis, or small-scale test data. The technologies are identified, categorized and quantified in the report. The net benefit of selected advanced technologies is quantified for two civil transport rotorcraft concepts, a Single Main Rotor Compound (SMRC) helicopter designed for 250 ktas cruise airspeed and a Civil Tilt Rotor (CTR) designed for 350 ktas cruise airspeed. A baseline design of each concept was sized for a representative civil passenger transport mission, using current technology. Individual advanced technologies are quantified and applied to resize the aircraft, thereby quantifying the net benefit of that technology to the rotorcraft. Estimates of development cost, production cost and operating and support costs are made with a commercial cost estimating program, calibrated to Boeing products with adjustments for future civil production processes. A cost metric of cash direct operating cost per available seat-mile (DOC ASM) is used to compare the cost benefit of the technologies. The same metric is used to compare results with turboprop operating costs. Reduced engine SFC was the most advantageous advanced technology for both rotorcraft concepts. Structural weight reduction was the second most beneficial technology, followed by advanced drive systems and then by technology for rotorcraft performance. Most of the technologies evaluated in this report should apply similarly to conventional helicopters. The implicit assumption is that resources will become available to mature the technologies for fullscale production aircraft. That assumption is certainly the weak link in any forecast of future possibilities. The analysis serves the purpose of identifying which technologies offer the most potential benefit, and thus the ones that should receive the highest priority for continued development. This study directly addressed the following NASA Subsonic Rotary Wing (SRW) subtopics: SR W.4.8.I.J Establish capability for rotorcraft system analysis and SRW. 4.8.I.4 Conduct limited technology benefit assessment on baseline rotorcraft configurations.

Wilkerson, Joseph B.↗
NASA NTRS2019

Deep Learning and Uncertainty Quantification for Climate Resilience

Modeling and monitoring of earth’s processes through physical models and satellite observations at high resolutions is crucial for ensuring society’s ability to adapt to climate change. Deep learning (DL) has been shown to be a valuable tool for generating high resolution data, emulating physical models, and detecting weather patterns which can then be used to inform stakeholders and decision makers. However, both the data and model parameters contain substantial uncertainties that may alter users’ decisions. In this work we present two DL applications on high-resolution climate and satellite datasets using Bayesian neural networks to generate well calibrated uncertainty estimates.

Vandal, Thomas↗
NASA NTRS2002

The StarLight interferometer architecture and operational concepts

The StarLight flight project was designed to demonstrate the key technologies of spacebome long-baseline stellar interferometry and precision formation flying for potential use on the Terrestrial Planet Finder (TPF) and other future astrophysics missions. Interferometer performance validation could be achieved over a 6-12 month period by obtaining several hundred fringe visibility amplitude measurements for stars in the band 600-1000 nm for a variety of stellar visibilities (0.2-1.0), magnitudes (Mv = 2-5), and baselines (B = 30-125 meters). Interferometry could be performed both in a 1 meter fixed-baseline combiner-only mode and in a two-spacecraft formation mode. In formation mode, the combiner spacecraft would remain at the focus of a virtual parabola, while the collector spacecraft assumed various positions along the parabola such that the two arms of the interferometer remained equal over a variety of separations and bearing angles. Challenges to be encountered in flight include high-bandwidth inter-spacecraft stellar and metrology pointing control, alignment and shear correction, delay and delay-rate estimation, visibility calibration, and robust fringe tracking in the presence of local and inter-spacecraft dynamics. This paper is based on the StarLight project design-capture of March 2002 and will describe the StarLight Interferometer System architecture and selected operational concepts (both of which have relevance to the on-going TPF Technology Program).

stellar↗
NASA NTRSDate not supplied

Global Solar Activity Data Portal for Studying 3D Dynamics and Activity of the Sun

The main problems with understanding and predicting solar activity are tightly linked to limitations in describing the global evolution of the Sun from the deep interior to the corona. Because of the complexity of interactions in a wide range of dynamical, turbulent, and spatial scales and dramatic changes in thermodynamic and magnetic field conditions, only physics-based models can provide essential background to generate reliable solar activity forecasts. However, performing accurate model calibration and estimating uncertainties is often challenging due to the unavailability of a long time series of observations. To mitigate these limitations, we have developed the Global Solar Activity (GSA) Data Portal, which enables convenient access to a variety of modern and historical data. The portal supports a dynamic visualization for 1D time series (such as the sunspot number and solar irradiance) and quick-look visualization for 2D datasets (e.g., synoptic magnetograms, the solar internal rotation, and flows). The GSA portal includes a search engine that enables data retrieval from user-specified data sources and time intervals. In this presentation, we will discuss the current and upcoming capabilities of the data portal and its potential applications for space weather studies.

SMD↗
NASA NTRSDate not supplied

Quantification of Design Trade-Offs When Comparing Transonic Truss-Braced Wing to Advanced Tube and Wing Aircraft

Interest in novel aircraft configurations has continued to grow in response to increasing demand for improved fuel efficiency. One such configuration of interest is the Transonic Truss-Braced Wing (TTBW). Because the improvement of the TTBW comes from increased efficiency during cruise, it offers increasing returns as the mission distance increases. As a result, there is often a crossover point which represents the minimum mission range where the TTBW will offer a fuel burn reduction relative to a similar Tube and Wing aircraft with similar component technology levels. Aircraft rarely fly missions at their maximum range, so it is important to investigate not only the maximum benefit, but also the most likely benefit. Design decisions and analysis assumptions that significantly impact this crossover point include whether to put fuel in body tanks, how weight build-up estimation is calibrated, engine technology selection, and flight Mach number. This study, conducted under NASA’s Sustainable Flight Demonstration project and inspired by differing assumptions made by different research teams, details the impacts of changing these design decisions and assumptions.

Carl J Recine↗
NASA NTRSDate not supplied

Quantification of Design Trade-Offs When Comparing Transonic Truss-Braced Wing to Advanced Tube and Wing Aircraft

Interest in novel aircraft configurations has continued to grow in response to increasing demand for improved fuel efficiency. One such configuration of interest is the Transonic Truss-Braced Wing (TTBW). Because the improvement of the TTBW comes from increased efficiency during cruise, it offers increasing returns as the mission distance increases. As a result, there is often a crossover point which represents the minimum mission range where the TTBW will offer a fuel burn reduction relative to a similar Tube and Wing aircraft with similar component technology levels. Aircraft rarely fly missions at their maximum range, so it is important to investigate not only the maximum benefit, but also the most likely benefit. Design decisions and analysis assumptions that significantly impact this crossover point include whether to put fuel in body tanks, how weight build-up estimation is calibrated, engine technology selection, and flight Mach number. This study, conducted under NASA’s Sustainable Flight Demonstration project and inspired by differing assumptions made by different research teams, details the impacts of changing these design decisions and assumptions.

Carl J Recine↗
DOE OSTI2025

Uncertainty based Online Ensemble on Non-Stationary Data for Fusion Science

Machine Learning (ML) is poised to play a pivotal role in the development and operation of next-generation fusion devices. Fusion data shows non-stationary behavior due to drifts in the data. The drifts can arise from both experimental evolution and machine wear-and-tear. ML models assume stationary distribution and fail to maintain performance when encountered with non-stationary data streams.Online learning can be used to continuously adapt the models with new data as it is acquired. However, traditional online learning can suffer from short-term performance degradation, as ground truth are not available before making the prediction. To address this challenge, we propose uncertainty aware ensemble approach for online learning. We use Deep Gaussian Process Approximation (DGPA) technique for calibrated uncertainty estimation and use the uncertainty values to guide a meta-algorithm that produces predictions based on ensemble of learners. Moreover, DGPA also provides uncertainty estimation along with the predictions for decision makers. This paper demonstrates that the proposed method outperforms traditional online learning approach, and a naive ensemble without uncertainty guidance by about 7% and 6%, respectively, on B-coil deflection prediction at DIII-D Fusion Facility.

Rajput, Kishansingh [Thomas Jefferson National Acc↗
DOE OSTI2022

Automatic Calibration of a Geomechanical Model from Sparse Data for Estimating Stress in Deep Geological Formations

Summary In this study, we demonstrate geomechanical modeling with fully automatic parameter calibration to estimate the full geomechanical stress fields of a prospective US carbon dioxide (CO2) storage site, based on sparse measurement data. The goal is to compute full stress tensor field estimates (principal stresses and orientations) that are maximally compatible with observations within the constraints of the model assumptions, thereby extending pointwise, incomplete partial stress measurement to a simulated full formation stress field, as well as a rough assessment of the associated error. We use the Perch site, located in Otsego County, Michigan, USA, as our case study. The input data consist of partial stress tensor information inferred from in-situ borehole tests, geophysical well logs, and processing of seismic data. A static earth model (SEM) of the site was developed, and geomechanical simulation functionality of the open-source MATLAB Reservoir Simulation Toolbox (MRST) was used to model the stress field. Adjoint-based nonlinear optimization was used to adjust boundary conditions and material properties to calibrate simulated results of observations. Results were interpreted through a Bayesian framework. The focus of this paper is to demonstrate how the fully automatic calibration procedure works and discuss the results obtained; it does not attempt a detailed analysis of the stress field in the context of the proposed CO2 storage initiatives. Our work is part of a larger effort to noninvasively determine in-situ stresses in deep formations considered for CO2 storage. Guided by previously published research on geomechanical model calibration, our work presents a novel calibration approach supporting a potentially large number of linear or nonlinear calibration parameters to produce results optimally agreeing with available measurements and thus extend partial pointwise estimates to full tensor fields compatible with the physics of the site.

Engineering↗
DOE OSTI2023

Calibrating Constant Elasticity of Substitution Technologies to Bottom-up Cost Estimates

We propose a method for calibrating an industry-level technology to engineering (bottom-up) estimates with a particular focus on abatement opportunities. As a demonstration, substitution elasticities across inputs are adjusted in the nested cost function for the electricity sector to best fit a target marginal abatement cost (MAC) curve derived from engineering assessments of available technologies. Elasticities are optimized over an entire relevant range of the MAC, whereas current techniques use local point estimates under little or no abatement. In the context of fitting to a given MAC we evaluate alternative nesting structures and find that, while complexity in nesting improves the fit, even relatively simple nesting structures can reasonably approximate the target MAC. In our example, focused on the electricity sector, we find standard elasticities adopted in top-down models moderately overstate abatement costs relative to the engineering targets. In our preferred specification the most important adjustment is to escalate the substitution elasticity between energy and value-added inputs. This is consistent with an argument that the current set of point estimates fail to properly account for new capital-based technologies. These conclusions, however, are sensitive to our assumption about output-intensity abatement and consumer price responsiveness, both of which are not delineated in engineering estimates.

abatement cost↗
NASA NTRS2010

Simplified Vicarious Radiometric Calibration

A measurement-based radiance estimation approach for vicarious radiometric calibration of spaceborne multispectral remote sensing systems has been developed. This simplified process eliminates the use of radiative transfer codes and reduces the number of atmospheric assumptions required to perform sensor calibrations. Like prior approaches, the simplified method involves the collection of ground truth data coincident with the overpass of the remote sensing system being calibrated, but this approach differs from the prior techniques in both the nature of the data collected and the manner in which the data are processed. In traditional vicarious radiometric calibration, ground truth data are gathered using ground-viewing spectroradiometers and one or more sun photometer( s), among other instruments, located at a ground target area. The measured data from the ground-based instruments are used in radiative transfer models to estimate the top-of-atmosphere (TOA) target radiances at the time of satellite overpass. These TOA radiances are compared with the satellite sensor readings to radiometrically calibrate the sensor. Traditional vicarious radiometric calibration methods require that an atmospheric model be defined such that the ground-based observations of solar transmission and diffuse-to-global ratios are in close agreement with the radiative transfer code estimation of these parameters. This process is labor-intensive and complex, and can be prone to errors. The errors can be compounded because of approximations in the model and inaccurate assumptions about the radiative coupling between the atmosphere and the terrain. The errors can increase the uncertainty of the TOA radiance estimates used to perform the radiometric calibration. In comparison, the simplified approach does not use atmospheric radiative transfer models and involves fewer assumptions concerning the radiative transfer properties of the atmosphere. This new technique uses two neighboring uniform ground target areas having different reflectance values. The target areas can be natural or artificial and must be large enough to minimize adjacent-pixel contamination effects. The radiative coupling between the atmosphere and the terrain needs to be approximately the same for the two targets. This condition can be met for relatively uniform backgrounds when the distance between the targets is within a few hundred meters. For each target area, the radiance leaving the ground in the direction of the satellite is measured with a radiometrically calibrated spectroradiometer. Using the radiance measurements from the two targets, atmospheric adjacency and atmospheric scattering effects can be subtracted, thereby eliminating many assumptions about the atmosphere and the radiative interaction between the atmosphere and the terrain. In addition, the radiometrically calibrated spectroradiometer can be used with a known reflectance target to estimate atmospheric transmission and diffuse- to-global ratios without the need for ancillary sun photometers. Several comparisons between the simplified method and traditional techniques were found to agree within a few percent. Hence, the simplified method reduces the overall complexity of performing vicarious calibrations and can serve as a method for validating traditional radiative transfer models

Stanley, Thomas↗
NASA NTRS2012

Heading Toward Launch with the Integrated Multi-Satellite Retrievals for GPM (IMERG)

The Day-l algorithm for computing combined precipitation estimates in GPM is the Integrated Multi-satellitE Retrievals for GPM (IMERG). We plan for the period of record to encompass both the TRMM and GPM eras, and the coverage to extend to fully global as experience is gained in the difficult high-latitude environment. IMERG is being developed as a unified U.S. algorithm that takes advantage of strengths in the three groups that are contributing expertise: 1) the TRMM Multi-satellite Precipitation Analysis (TMPA), which addresses inter-satellite calibration of precipitation estimates and monthly scale combination of satellite and gauge analyses; 2) the CPC Morphing algorithm with Kalman Filtering (KF-CMORPH), which provides quality-weighted time interpolation of precipitation patterns following cloud motion; and 3) the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks using a Cloud Classification System (PERSIANN-CCS), which provides a neural-network-based scheme for generating microwave-calibrated precipitation estimates from geosynchronous infrared brightness temperatures. In this talk we summarize the major building blocks and important design issues driven by user needs and practical data issues. One concept being pioneered by the IMERG team is that the code system should produce estimates for the same time period but at different latencies to support the requirements of different groups of users. Another user requirement is that all these runs must be reprocessed as new IMERG versions are introduced. IMERG's status at meeting time will be summarized, and the processing scenario in the transition from TRMM to GPM will be laid out. Initially, IMERG will be run with TRMM-based calibration, and then a conversion to a GPM-based calibration will be employed after the GPM sensor products are validated. A complete reprocessing will be computed, which will complete the transition from TMPA.

Huffman, George J.↗
NASA NTRS1984

Calibration or inverse regression: Which is appropriate for crop surveys using LANDSAT data?

Calibration and inverse regression estimators of crop proportions are investigated where the auxiliary variable is obtained from binary classification of multivariate LANDSAT data. The appropriate model relating classifier proportions and ground observed proportions for a given crop type is the calibration model. Under this model the inverse regression estimator is superior to the calibration estimator in estimating the crop acreage or proportion for a region of interest.

Chhikara, R. S.↗
NASA NTRS2018

Satellite Remote Sensing Estimation of River Discharge: Application to the Yukon River Alaska

A methodology based on general hydraulic relations for rivers has been developed to estimate the discharge (flow rate) of rivers using satellite remote sensing observations. The estimates of discharge, flow depth, and flow velocity are derived from remotely observed water surface area, water surface slope, and water surface height, and demonstrated for two reaches of the Yukon River in Alaska, at Eagle (reach length 34.7 km) and near Stevens Village (reach length 38.3 km). The method is based on fundamental equations of hydraulic flow resistance in rivers, including the Manning equation and the Prandtl-von Karman universal velocity distribution equation. The method employs some new hydraulic relations to help define flow resistance and height of the zero flow boundary in the channel. Estimates are made both with and without calibration. The water surface area of the river reach is measured by using a provisional version of the U.S. Geological Survey (USGS) Landsat based product named Dynamic Surface Water Extent (DSWE). The water surface height and slope measurements require a self-consistent datum, and are derived from observations from the Jason-2 satellite altimeter mission. At both reach locations, the Jason-2 radar altimeter non-winter heights consistently tracked the stage recorded at USGS streamgages with a standard deviation of differences (error) during the non-winter periods of less than 7%. Part of the error may be due to differences in the gage and altimeter crossing locations with respect to the range of stage change and the response to changes in discharge at the upstream and downstream locations. For the non-winter periods, the radar derived slope estimates (mean = 0.0003) were constant over the mission lifetime, and in agreement with previously measured USGS water surface slopes and slopes determined from USGS topographic maps. The accuracy of the mean of the uncalibrated daily estimates of discharge varied between reaches, ranging from 13% near Stevens Village (N = 90) to −21% at Eagle (N = 246) based on the absolute error, and 5% to −6% based on the error of the log of the estimates. Calibrating to the mean of USGS daily discharge estimates from the streamflow rating for the same period of record at each streamgage resulted in mean absolute errors ranging from 1% to 2%, and log errors ranging from 1% or less. The error pattern of the estimates shows that without calibration, even though the mean is well simulated, the high and low end values over the range of estimates may have significant bias.

Bjerklie, David M.↗
NASA NTRS1995

Summary of OARE flight calibration measurements

To date, the Orbital Acceleration Research Experiment (OARE) has flown on the shuttle orbiter for five missions; namely, STS-40, STS-50, STS-58, STS-62, and STS-65. The OARE instrument system contains a three-axis accelerometer which can resolve accelerations to the nano-g (10(exp -9) g) level and a full calibration station to permit in situ bias and scale factor calibration measurements. This calibration capability eliminates the large uncertainty encountered with accelerometers flown in the past on the orbiter which use ground-based calibrations to provide absolute acceleration measurements. A detailed flight data report presentation is given for the OARE calibration measurements from all missions, along with an estimate of the calibration errors. The main aim is to collect, process, and present the calibration data in one archival report. These calibration data are the necessary key ingredient to produce the absolute acceleration levels from the OARE acceleration flight data.

Blanchard, Robert C.↗
NASA NTRS2002

Fine Sun Sensor Field of View Calibration

The fine Sun sensor (FSS) used on many spacecraft consists of two independent single-axis sensors, nominally mounted perpendicularly, that detect Sun angle across a typical field of view of +/- 32 degrees. The nonlinear function that maps the measured counts into an observed angle is called the transfer function. The FSS transfer function provided by the manufacturer consists of nine parameters for each of the two sensitive axes. An improved transfer function has been previously reported that achieves a significant accuracy improvement across the entire field of view. This new function expands the parameter set to 12 coefficients per axis and includes cross terms combining counts from both axes. To make best use of the FSS for spacecraft attitude determination, it must be calibrated after launch. We are interested in simplifying the postlaunch calibration procedure for estimating improvements to the 24 parameters in the transfer function. This paper discusses how to recombine the terms of the transfer function to reduce their redundancy without decreasing its accuracy and then presents an attitude dependent procedure for estimating the parameters. The end result is a calibration algorithm that is easier to use and does not sacrifice accuracy. Results of calibration using on-orbit data are presented.

Sedlak, Joseph E.↗
NASA NTRS2008

Estimating Software-Development Costs With Greater Accuracy

COCOMOST is a computer program for use in estimating software development costs. The goal in the development of COCOMOST was to increase estimation accuracy in three ways: (1) develop a set of sensitivity software tools that return not only estimates of costs but also the estimation error; (2) using the sensitivity software tools, precisely define the quantities of data needed to adequately tune cost estimation models; and (3) build a repository of software-cost-estimation information that NASA managers can retrieve to improve the estimates of costs of developing software for their project. COCOMOST implements a methodology, called '2cee', in which a unique combination of well-known pre-existing data-mining and software-development- effort-estimation techniques are used to increase the accuracy of estimates. COCOMOST utilizes multiple models to analyze historical data pertaining to software-development projects and performs an exhaustive data-mining search over the space of model parameters to improve the performances of effort-estimation models. Thus, it is possible to both calibrate and generate estimates at the same time. COCOMOST is written in the C language for execution in the UNIX operating system.

Baker, Dan↗