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Results for “calibration data analysis”

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.

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At least 1,063 records · Page 59
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

SU-F-T-368: Improved HPGe Detector Precise Efficiency Calibration with Monte Carlo Simulations and Radioactive Sources

Purpose: To obtain an improved precise gamma efficiency calibration curve of HPGe (High Purity Germanium) detector with a new comprehensive approach. Methods: Both of radioactive sources and Monte Carlo simulation (CYLTRAN) are used to determine HPGe gamma efficiency for energy range of 0–8 MeV. The HPGe is a GMX coaxial 280 cm{sup 3} N-type 70% gamma detector. Using Momentum Achromat Recoil Spectrometer (MARS) at the K500 superconducting cyclotron of Texas A&M University, the radioactive nucleus {sup 24} Al was produced and separated. This nucleus has positron decays followed by gamma transitions up to 8 MeV from {sup 24} Mg excited states which is used to do HPGe efficiency calibration. Results: With {sup 24} Al gamma energy spectrum up to 8MeV, the efficiency for γ ray 7.07 MeV at 4.9 cm distance away from the radioactive source {sup 24} Al was obtained at a value of 0.194(4)%, by carefully considering various factors such as positron annihilation, peak summing effect, beta detector efficiency and internal conversion effect. The Monte Carlo simulation (CYLTRAN) gave a value of 0.189%, which was in agreement with the experimental measurements. Applying to different energy points, then a precise efficiency calibration curve of HPGe detector up to 7.07 MeV at 4.9 cm distance away from the source {sup 24} Al was obtained. Using the same data analysis procedure, the efficiency for the 7.07 MeV gamma ray at 15.1 cm from the source {sup 24} Al was obtained at a value of 0.0387(6)%. MC simulation got a similar value of 0.0395%. This discrepancy led us to assign an uncertainty of 3% to the efficiency at 15.1 cm up to 7.07 MeV. The MC calculations also reproduced the intensity of observed single-and double-escape peaks, providing that the effects of positron annihilation-in-flight were incorporated. Conclusion: The precision improved gamma efficiency calibration curve provides more accurate radiation detection and dose calculation for cancer radiotherapy treatment.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1984

Landsat-4 MSS and Thematic Mapper data quality and information content analysis

Landsat-4 Thematic Mapper and Multispectral Scanner data were analyzed to obtain information on data quality and information content. Geometric evaluations were performed to test band-to-band registration accuracy. Thematic Mapper overall system resolution was evaluated using scene objects which demonstrated sharp high contrast edge responses. Radiometric evaluation included detector relative calibration, effects of resampling, and coherent noise effects. Information content evaluation was carried out using clustering, principal components, transformed divergence separability measure, and numerous supervised classifiers on data from Iowa and Illinois. A detailed spectral class analysis (multispectral classification) was carried out on data from the Des Moines, IA area to compare the information content of the MSS and TM for a large number of scene classes.

Anuta, P. E.↗
DOE OSTI2024

3D multi-system Bayesian calibration with energy conservation to study rapidity-dependent dynamics of nuclear collisions

Considerable information about the early-stage dynamics of heavy ion collisions is encoded in the rapidity dependence of measurements. To leverage the large amount of experimental data, we perform a systematic analysis using three-dimensional hydrodynamic simulations of multiple collision systems — large and small, symmetric and asymmetric. Specifically, we perform fully 3D multi-stage hydrodynamic simulations initialized by a parameterized model for rapidity-dependent energy deposition, which we calibrate on the hadron multiplicity and anisotropic flow coefficients. We utilize Bayesian inference to constrain properties of the early- and late-time dynamics of the system, and highlight the impact of enforcing global energy conservation in our 3D model.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2020

X-ray Spectra of the Fe-L Complex II: Atomic Data Constraints from the EBIT Experiment and X-Ray Grating Observations of Capella

The Hitomi results for the Perseus cluster have shown that accurate atomic models are essential to the success of X-ray spectroscopic missions and just as important as the store of knowledge on instrumental calibration and astrophysical modeling. Preparing the models requires a multifaceted approach, including theoretical calculations, laboratory measurements, and calibration using real observations. In a previous paper, we presented a calculation of the electron impact cross sections on the transitions forming the Fe-L complex. In the present work, we systematically tested the calculation against cross-sections of ions measured in an electron beam ion trap experiment. A two-dimensional analysis in the electron beam energies and X-ray photon energies was utilized to disentangle radiative channels following dielectronic recombination, direct electron-impact excitation, and resonant excitation processes in the experimental data. The data calibrated through laboratory measurements were further fed into a global modeling of the Chandra grating spectrum of Capella. We investigated and compared the fit quality, as well as the sensitivity of the derived physical parameters to the underlying atomic data and the astrophysical plasma modeling. We further list the potential areas of disagreement between the observations and the present calculations, which, in turn, calls for renewed efforts with regard to theoretical calculations and targeted laboratory measurements.

Liyi Gu↗
NASA NTRS1985

A GPS measurement system for precise satellite tracking and geodesy

NASA is pursuing two key applications of differential positioning with the Global Positioning System (GPS): sub-decimeter tracking of earth satellites and few-centimeter determination of ground-fixed baselines. Key requirements of the two applications include the use of dual-frequency carrier phase data, multiple ground receivers to serve as reference points, simultaneous solution for use position and GPS orbits, and calibration of atmospheric delays using water vapor radiometers. Sub-decimeter tracking will be first demonstrated on the TOPEX oceanographic satellite to be launched in 1991. A GPS flight receiver together with at least six ground receivers will acquire delta range data from the GPS carriers for non-real-time analysis. Altitude accuracies of 5 to 10 cm are expected. For baseline measurements, efforts will be made to obtain precise differential pseudorange by resolving the cycle ambiguity in differential carrier phase. This could lead to accuracies of 2 or 3 cm over a few thousand kilometers. To achieve this, a high-performance receiver is being developed, along with improved calibration and data processing techniques. Demonstrations may begin in 1986.

Yunck, T. P.↗
NASA NTRS2016

Assessment of SNPP VIIRS VIS NIR Radiometric Calibration Stability Using Aqua MODIS and Invariant Surface Targets

The first Visible Infrared Imaging Radiometer Suite (VIIRS) is onboard the Suomi National Polar-orbiting Partnership (SNPP) satellite. As a primary sensor, it collects imagery and radiometric measurements of the land, atmosphere, cryosphere, and oceans in the spectral regions from visible (VIS) to long-wave infrared. NASA's National Polar-orbiting Partnership (NPP) VIIRS Characterization Support Team has been actively involved in the VIIRS radiometric and geometric calibration to support its Science Team Principal Investigators for their independent quality assessment of VIIRS Environmental Data Records. This paper presents the performance assessment of the radiometric calibration stability of the VIIRS VIS and NIR spectral bands using measurements from SNPP VIIRS and Aqua MODIS simultaneous nadir overpasses and over the invariant surface targets at the Libya-4 desert and Antarctic Dome Concordia snow sites. The VIIRS sensor data records (SDRs) used in this paper are reprocessed by the NASA SNPP Land Product Evaluation and Analysis Tool Element. This paper shows that the reprocessed VIIRS SDRs have been consistently calibrated from the beginning of the mission, and the calibration stability is similar to or better than MODIS. Results from different approaches indicate that the calibrations of the VIIRS VIS and NIR spectral bands are maintained to be stable to within 1% over the first three-year mission. The absolute calibration differences between VIIRS and MODIS are within 2%, with an exception for the 0.865-m band, after correction of their spectral response differences.

Wu, Aisheng↗
DOE OSTI2012

A plastic miniature x-ray emission spectrometer based on the cylindrical von Hamos geometry

We present a short working distance miniature x-ray emission spectrometer (miniXES) based on the cylindrical von Hamos geometry. We describe the general design principles for the spectrometer and detail a specific implementation that covers K{beta} and valence level emission from Fe. Large spatial and angular access to the sample region provides compatibility with environmental chambers, microprobe, and pump/probe measurements. The primary spectrometer structure and optic is plastic, printed using a 3-dimensional rapid-prototype machine. The spectrometer is inexpensive to construct and is portable; it can be quickly set up at any focused beamline with a tunable narrow bandwidth monochromator. The sample clearance is over 27 mm, providing compatibility with a variety of environment chambers. An overview is also given of the calibration and data processing procedures, which are implemented by a multiplatform user-friendly software package. Finally, representative measurements are presented. Background levels are below the level of the K{beta}{sub 2,5} valence emission, the weakest diagram line in the system, and photometric analysis of count rates finds that the instrument is performing at the theoretical limit.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
NASA NTRS1985

Calculation of three-dimensional boundary layers on rotating turbine blades

An assessment has been made of the applicability of a three dimensional boundary layer analysis to the calculation of heat transfer and streamline flow patterns on the surfaces of both stationary and rotating turbine passages. In support of this effort, an analysis has been developed to calculate a general nonorthogonal surface coordinate system for arbitrary three dimensional surfaces and also to calculate the boundary layer edge conditions for compressible flow using the surface Euler equations and experimental pressure distributions. Using available experimental data to calibrate the method, calculations are presented for the endwall, and suction surfaces of a stationary cascade and for the pressure surface of a rotating turbine blade. The results strongly indicate that the three dimensional boundary layer analysis can give good predictions of the flow field and heat transfer on the pressure, suction, and endwall surfaces in a gas turbine passage.

Anderson, O. L.↗
DOE OSTI2014

Statistical and systematic errors in the measurement of weak-lensing Minkowski functionals: Application to the Canada-France-Hawaii Lensing Survey

The measurement of cosmic shear using weak gravitational lensing is a challenging task that involves a number of complicated procedures. We study in detail the systematic errors in the measurement of weak-lensing Minkowski Functionals (MFs). Specifically, we focus on systematics associated with galaxy shape measurements, photometric redshift errors, and shear calibration correction. We first generate mock weak-lensing catalogs that directly incorporate the actual observational characteristics of the Canada-France-Hawaii Lensing Survey (CFHTLenS). We then perform a Fisher analysis using the large set of mock catalogs for various cosmological models. We find that the statistical error associated with the observational effects degrades the cosmological parameter constraints by a factor of a few. The Subaru Hyper Suprime-Cam (HSC) survey with a sky coverage of ∼1400 deg{sup 2} will constrain the dark energy equation of the state parameter with an error of Δw {sub 0} ∼ 0.25 by the lensing MFs alone, but biases induced by the systematics can be comparable to the 1σ error. We conclude that the lensing MFs are powerful statistics beyond the two-point statistics only if well-calibrated measurement of both the redshifts and the shapes of source galaxies is performed. Finally, we analyze the CFHTLenS data to explore the ability of the MFs to break degeneracies between a few cosmological parameters. Using a combined analysis of the MFs and the shear correlation function, we derive the matter density Ω{sub m0}=0.256±{sub 0.046}{sup 0.054}.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1976

Interactive analysis of thermal imagery

Necessary knowledge is presented on data acquisition and preparation for analysis of thermal imagery of power plant heated discharges remotely sensed from an aircraft, with special emphasis on analog to digital conversion of analog tapes acquired during scanning and to geometrical scaling. The central element in the interactive analysis of thermal imagery is an interactive graphics computer terminal which allows an interpreter to effectively interact with a large-scale computer, providing decisions or data as computations are carried out. A temperature calibration is performed, which the interpreter may test anywhere on the image. When satisfied that calibration is correct, the portion of the image to be analyzed is outlined. Printed and microfiche analyses of the plume are produced. The flow chart of programs for analysis of thermal imagery is presented and discussed in some detail.

Madding, R. P.↗
DOE OSTI2016

Inter-Disciplinary Collaboration in Support of the Post-Standby TREAT Mission

Although analysis methods have advanced significantly in the last two decades, high fidelity multi- physics methods for reactors systems have been under development for only a few years and are not presently mature nor deployed. Furthermore, very few methods provide the ability to simulate rapid transients in three dimensions. Data for validation of advanced time-dependent multi- physics is sparse; at TREAT, historical data were not collected for the purpose of validating three-dimensional methods, let alone multi-physics simulations. Existing data continues to be collected to attempt to simulate the behavior of experiments and calibration transients, but it will be insufficient for the complete validation of analysis methods used for TREAT transient simulations. Hence, a 2018 restart will most likely occur without the direct application of advanced modeling and simulation methods. At present, the current INL modeling and simulation team plans to work with TREAT operations staff in performing reactor simulations with MAMMOTH, in parallel with the software packages currently being used in preparation for core restart (e.g., MCNP5, RELAP5, ABAQUS). The TREAT team has also requested specific measurements to be performed during startup testing, currently scheduled to run from February to August of 2018. These startup measurements will be crucial in validating the new analysis methods in preparation for ultimate application for TREAT operations and experiment design. This document describes the collaboration between modeling and simulation staff and restart, operations, instrumentation and experiment development teams to be able to effectively interact and achieve successful validation work during restart testing.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Stakeholder analysis for designing an urban air quality data governance ecosystem in smart cities

Cities, the world over, are fuelling economic growth. At the same time, rapid urbanization is a root cause of serious environmental damage. Recent WHO global air pollution guidelines highlight air pollution as a critical environmental threat along with climate change. To address these threats, smart cities and clean air programs are on a rise. In smart cities, data and Information and Communication Technologies (ICT) are major drivers of city transformations. The 4th Industrial Revolution (4IR) technologies such as the Internet of Things (IoT), big data, artificial intelligence (AI), and cloud computing have the potential to accelerate these transformations toward urban resilience. However, the success of smart cities and clean air programs depends on cohesive multi-sector stakeholder contributions. This study conducted interdisciplinary participative stakeholder analysis to understand the data, and sectorial challenges, to outline the technological opportunities to facilitate clean air programs in Indian smart cities. The research highlights gaps due to siloed stakeholder operations, lack of data calibration, non-alignment of smart city and air quality management services, non-availability of health exposure data, and difficulty in translating scientific data into implementable actions. Stakeholders expressed potential ‘fit for the purpose’ use of IoT devices, satellites, smartphones, and mobility data augmented by AI methods in bridging these gaps. In conclusion, the analysis points toward a need to develop an easily accessible and ubiquitous urban data governance ecosystem enabling seamless cross-sector data exchanges to build trusting relationships among the stakeholders across the air quality management value chain.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2026

Ripening of Rh Nanoparticle Catalysts in Reverse Water–Gas Shift via a Data-Driven Model Combining Physics, Theory, and Experiment

Degradation via sintering is an ongoing challenge that impedes the broad commercial success of supported metallic nanoparticle catalysts. To mitigate degradation via informed catalyst design and process operations, here we aim to disambiguate the underlying mechanisms of sintering by combining theory and experiment in a quantitative framework. While mechanistic sintering models exist, they only model a single sintering pathway, even though multiple sintering mechanisms can occur simultaneously or dominate at different stages of the process. Data-driven machine learning models have emerged as a means to represent complex processes through data regression. However, machine learning models have very large data needs and lack mechanistic insights due to their black-box encoding. To develop an interpretive model of catalyst degradation via sintering, we constructed a hybrid model combining mechanistic “physics-based” models and data-driven methods to obtain both reliable predictions and mechanistic insights regarding experimentally observed sintering phenomena. Focusing on nanoparticle sintering in the Rh–TiO 2 catalyst for the reverse water–gas shift (RWGS) reaction, the hybrid model couples a mechanistic term for Ostwald ripening with energy values calculated via density functional theory (DFT) with a parametric, data-driven discrepancy function term for unmodeled mechanisms. The hybrid model is trained using Bayesian inference with data collected from small-angle X-ray scattering (SAXS) in situ experiments wherein average nanoparticle diameter versus time was measured at three relevant operating temperatures. The calibrated hybrid model results show that an Ostwald ripening-only model parameterized with fixed DFT energies does not fully capture the time and temperature dependence of the SAXS-observed sintering kinetics, and that an additional functional contribution, or DFT energy calibration, is required to reconcile simulation and experiment. Analysis of the hybrid-model error confirms that the hybrid model outperforms both the purely mechanistic and purely data-driven alternatives in terms of expected predictive accuracy for time-evolving average particle sizes. Furthermore, the results support the hypothesis that the Ostwald ripening mechanism is less important for explaining the sintering phenomena as operating temperature increases under an assumed fixed DFT parameterization. This could be explained in one of two ways: either latent, unmodeled sintering mechanisms dominate at higher temperatures, or the DFT uncertainty increases with temperature. The proposed modeling approach directly links theory to experiments and simulations via a statistical hybrid modeling framework and can be extended to other catalytic systems to improve predictive models and mechanistic understanding.

Bayesian hybrid modeling↗
DOE OSTI2018

Using the JCC-71 neutron coincidence collar as a benchmark for detector characterization with PTR-32 list mode data acquisition

Augmenting or interchanging current international safeguards shift registerbased data acquisition systems with list mode data acquisition systems gives nondestructive assay (NDA) systems greater versatility. Neutron list mode data analysis offers comparable analytical results to the more widely used shift register analysis in nuclear material quantification applications and offers several diagnostic tools that are specifically beneficial to in-laboratory characterization and calibration measurements. These benefits include identification of non-ideal behavior, optimization of operational parameters from a single measurement, and an improved understanding of the physics-based behavior of NDA systems for a more precise system representation and more confident assay results. In this work the advantages of using list mode data acquisition for detector characterization are demonstrated experimentally. Two commercial-off-the-shelf International Atomic Energy Agency-supported technologies are used for a typical detector characterization procedure and their performance is compared. Specifically, a 3 He-based Canberra Industries JCC-71 Neutron Coincidence Collar is characterized using the Hungarian Institute of Isotopes’ Pulse Train Recorder-32 (PTR-32) list mode data acquisition system, and the results are compared to those obtained using the standard Canberra Industries JSR-15 model shift register. The quantitative results from the two systems are in agreement, which demonstrates that the PTR-32 is a technically viable alternative to conventional shift register electronics for this task. A suitable procedure for full instrument characterization is described, and the added benefits of list mode for characterization and data collection are discussed. Furthermore, this is an important step toward establishing a procedure for the routine use of list mode data acquisition and analysis for neutron NDA system characterization in safeguards field applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2021

Bayesian analysis for estimating statistical parameter distributions of elasto-viscoplastic material models

High temperature design methods rely on constitutive models for inelastic deformation and failure typically calibrated against the mean of experimental data without considering the associated scatter. Variability may arise from the experimental data acquisition process, from heat-to-heat material property variations, or both and need to be accurately captured to predict parameter bounds leading to efficient component design. Applying the Bayesian Markov Chain Monte Carlo (MCMC) method to produce statistical models capturing the underlying uncertainty in the experimental data is an area of ongoing research interest. This work varies aspects of the Bayesian MCMC method and explores their effect on the posterior parameter distributions for a uniaxial elasto-viscoplastic damage model using synthetically generated reference data. From our analysis with the uniaxial inelastic model we determine that an informed prior distribution including different types of test conditions results in more accurate posterior parameter distributions. The parameter posterior distributions, however, do not improve when increasing the number of similar experimental data. Additionally, changing the amount of scatter in the data affects the quality of the posterior distributions, especially for the less sensitive model parameters. Moreover, we perform a sensitivity study of the model parameters against the likelihood function prior to the Bayesian analysis. The results of the sensitivity analysis help to determine the reliability of the posterior distributions and reduce the dimensionality of the problem by fixing the insensitive parameters. The comprehensive study described in this work demonstrates how to efficiently apply the Bayesian MCMC methodology to capture parameter uncertainties in high temperature inelastic material models. Quantifying these uncertainties in inelastic models will improve high temperature engineering design practices and lead to safer, more effective component designs.

42 ENGINEERING↗
DOE OSTI2017

Modeling Total Dissolved Gas for Optimal Operation of Multireservoir Systems

One important environmental issue of hydropower in the Columbia and Snake River Basins (Pacific Northwest region of United States) is elevated total dissolved gas (TDG) downstream of a dam, which has the potential to cause gas bubble disease in affected fish. Gas supersaturation in the Columbia River Basin primarily occurs due to dissolution of bubbles entrained during spill events. This paper presents a physically based TDG model that can be used to optimize spill operations in multireservoir hydropower systems. Independent variables of the model are forebay TDG, tailwater elevation, spillway and powerhouse discharges, project head, and environmental parameters such as temperature and atmospheric pressure. The model contains seven physically meaningful experimental parameters, which were calibrated and validated against TDG data collected downstream of Rock Island Dam (Washington) from 2008 to 2012. In conclusion, a sensitivity analysis was performed to increase the understanding of the relationships between TDG downstream of the dam and processes such as air entrainment, lateral powerhouse flow, and dissolution.

13 HYDRO ENERGY↗
DOE OSTI2025

Sensitivity of an integrated experiment to uncertainty in the high explosive equations of state

Traditionally, hydrodynamics simulations are performed with a single equation-of-state (EOS) to describe each material. These EOSs typically have a physics-informed functional form with adjustable parameters that are calibrated in order to replicate small-scale data. However, because the calibration data have uncertainty and there are typically inherent degeneracies in fitting the EOS, there are actually multiple EOSs that might be consistent with calibration data. In this work, we perform uncertainty quantification (UQ) for the reactant and product equations of state for the high explosive PBX 9501 to yield an ensemble of EOSs that match the uncertain small-scale calibration data. We then simulate an experiment of an explosively formed penetrator repeatedly with different EOSs to both validate the UQ analysis and determine the effects of EOS uncertainty on the prediction of quantities of interest in the experiment. In general, we find good agreement between the simulation predictions and the experimental measurements, and we identify an EOS variable that contributes most directly to the spread in the predictions as the EOSs are varied.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Case Study for the ARRA-funded GSHP Demonstration at University at Albany

High initial costs and lack of public awareness of ground-source heat pump (GSHP) technology are the two major barriers preventing rapid deployment of this energy-saving technology in the United States. Under the American Recovery and Reinvestment Act (ARRA), 26 GSHP projects have been competitively selected and carried out to demonstrate the benefits of GSHP systems and innovative technologies for cost reduction and/or performance improvement. This report highlights the findings of a case study of one of the ARRA-funded GSHP demonstration projects—a distributed GSHP system at a new 500-bed apartment-style student residence hall at the University at Albany. This case study is based on the analysis of detailed design documents, measured performance data, published catalog data of heat pump equipment, and actual construction costs. Simulations with a calibrated computer model are performed for both the demonstrated GSHP system and a baseline heating, ventilation, and air-conditioning (HVAC) system to determine the energy savings and other related benefits achieved by the GSHP system. The evaluated performance metrics include the energy efficiency of the heat pump equipment and the overall GSHP system, as well as the pumping performance, energy savings, carbon emission reductions, and cost-effectiveness of the demonstrated GSHP system compared with the baseline HVAC system. This case study also identifies opportunities for improving the operational efficiency of the demonstrated GSHP system.

15 GEOTHERMAL ENERGY↗