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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 1,657 records · Page 92
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Directional Reflectance Studies in Support of the Radiometric Calibration Test Site (RadCaTS) at Railroad Valley

The Radiometric Calibration Test Site (RadCaTS) is a suite of commercial and custom instruments used to make measurements of the surface reflectance and atmosphere throughout the day at Railroad Valley, Nevada. It was developed in response to the need for daily radiometric calibration data for the vast array of Earth-observing sensors on orbit, which is continuously increasing as more nations and private companies launch individual environmental satellites as well as large constellations. The current suite of instruments at RadCaTS includes five ground-viewing radiometers (GVRs), four of which view the surface in a nadir-viewing configuration. Many sensors such as those on Landsat-7 and Landsat-8 view Railroad Valley within 3° of nadir, while others such as those on Sentinel-2A and -2B, RapidEye, Aqua, Suomi NPP, and Terra can view Railroad Valley at off-nadir angles. Past efforts have shown that the surface bidirectional reflectance distribution function (BRDF) has minimal impact on vicarious calibration uncertainties for views <10°, but the desire to use larger view angles has prompted the effort to develop a BRDF correction for data from RadCaTS. The current work investigates the application of Railroad Valley BRDF data derived from a BRF camera developed at the University of Arizona in the 1990s (but is no longer in use) to the current RadCaTS surface reflectance measurements. Also investigated are early results from directional reflectance studies using a mobile spectro-goniometer system during a round-robin field campaign in 2018. This work describes the preliminary results, the effects on current measurements, and the approach for future measurements.

RadCalNet↗
NASA NTRS2020

Sensitivity of Satellite Ocean Color Data to System Vicarious Calibration of the Long Near Infrared Band

Satellite ocean color missions require accurate (< 1% uncertainties) system vicarious calibrations (SVC) in order to retrieve the relatively small remote sensing reflectance (Rrs, sr-1) from the at-sensor radiance. However, current atmospheric correction and SVC procedures do not include calibration of the “long” near infrared band (NIRL–869nm for MODIS), partially because earlier studies indicated that accuracy in the retrieved Rrsis insensitive to moderate changes in the NIRLvicarious gain (g). However, the sensitivity of ocean color data products to g(NIRL) has not been thoroughly examined. Here, we first derived 10 SVC ‘gain configurations’ (vicarious gains for all visible and NIR bands) for MODIS/Aqua using current operational NASA protocols, each time assuming a different g(869). From these, we derived a suite of ~1.4E6 unique gain configurations with g(869) ranging from 0.85 to 1.2. All MODIS/A data for 25locations within each of five ocean gyres were then processed using each of these gain configurations. Such time series show substantial variability inthe dominant Rrs(547) patterns in response to changes in g(869). Overall gyre mean Rrs(547) generally decreased with increasing g(869), while the standard deviations around those means show gyre-specific minima for 0.97 < g(869) < 1.02. Following these sensitivity analyses, we assess the potential to resolve g(869) using suchtime series, finding g(869) = 1.025 most closely comports with expectations. This approach is broadly applicable to other ocean color sensors, and highlights the importance of rigorous cross-sensor calibration of the NIRLbands, with implications on consistency of merged-sensor datasets.

vicarious calibration↗
NASA NTRS1995

Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) Onboard Calibration System

The AVIRIS instrument uses an onboard calibration system to provide auxiliary calibration data. The system consists of tungsten halogen cycle lamp imaged onto a fiber bundle through an eight position filter wheel. The fiber bundle illuminates the back side of the foreoptics shutter during a pre-run and post-run calibration sequence. The filter wheel contains 2 neutral density filters, 5 spectral filters and blocked position.

spectrometer↗
NASA NTRS2020

Comparison of the MODIS and VIIRS Thermal Emissive Band Radiometric Calibration

Moderate Resolution Imaging Spectroradiometer (MODIS) and Visible Infrared Imaging Radiometer Suite (VIIRS) are major instruments for Earth science observations.Nearly 40 MODIS scientific products and a wide range of VIIRS environmental data records are produced using their global observations. The consistency of the MODIS and VIIRS calibrated data is important for the study of Earth science. This article assesses the calibration consistency of the Aqua MODIS and VIIRS thermal emissive band (TEB) data. To remove the impact of the mismatched relative spectral response (RSR) on the comparisons, the simultaneous nadir observation data from the cross-track infrared sounder (CrIS) and the infrared atmospheric sounding interferometer (IASI) are used as references in two different methods to independently verify the consistency. The comparisons of the MODIS and VIIRS TEB calibrated data show that the brightness temperature (BT) differences for comparable bands between MODIS and VIIRS are in general within 0.2 K for BT larger than 230 K. The differences of all comparable MODIS and VIIRS TEBs are consistent over time. MODIS measurements agree better with N20 VIIRS than with Suomi National Polar-orbiting Partnership (S-NPP) VIIRS. The S-NPP VIIRS measurements are higher than N20 VIIRS, within 0.1 Kfor long-wave infrared (LWIR) bands and 0.3 K for band M13.

Calibration↗
NASA NTRS2019

Lunar calibration and performance assessments of the NOAA-20 VIIRS reflective solar bands

The Moon has played a vital role in the radiometric stability monitoring of NASAs Earth Observing System sensors, such as MODIS on the Terra and Aqua spacecrafts. The lunar calibration methodologies developed for the two MODIS instruments were later extended to apply to the VIIRS instrument on the Suomi-NPP spacecraft. The follow-on VIIRS instrument on the NOAA-20 (N20) spacecraft (previously JPSS-1) has been successfully operating since its launch in November 2017. Fifteen VIIRS spectral bands are in the reflective solar spectral region, covering wavelengths from 0.4 to 2.3 μm. Similar to the previous MODIS and VIIRS instruments, the N20 VIIRS views the Moon via a spacecraft roll maneuver on a near-monthly basis at a confined phase angle range (-51.5° to -50.5°) to facilitate radiometric stability monitoring with reduced uncertainties. In this paper, we briefly present the lunar calibration methodology and also report the derived instrument gain parameters from the regularly scheduled lunar calibrations. The USGS Robotic Lunar Observatory (ROLO) model is used to provide the predicted lunar irradiance for each lunar measurement to account for the variation in the observation geometry. The spatial characterization algorithms using the Moon, previously developed for MODIS and SNPP VIIRS, have also been extended to N20 VIIRS to track its on-orbit band-to-band registration (BBR).

VIIRS↗
NASA NTRS2021

NOAA-20 VIIRS on-Orbit Calibration Improvements

The NOAA-20 (N-20) VIIRS has successfully operated for more than two years since its launch in November 2017. Shortly after completing its initial instrument check-outs and post-launch testing (PLT) activities, the N-20 VIIRS sensor data records (SDR) achieved the beta, provisional, and validated maturity status in January, February, and April 2018, respectively. In this paper, we briefly describe the instrument on-orbit operation and calibration activities, provide an overall assessment of its on-orbit performance, and discuss the methodologies developed to maintain and improve sensor calibration and data quality. As illustrated in this paper, the N-20 VIIRS continues to perform with excellent stability, allowing high-quality environmental data records (EDR) to be generated from its well-calibrated SDR.

NOAA-20↗
NASA NTRSDate not supplied

Evaluation of a Traditional Regression Model Term Selection Process for Balance Calibration Data Sets

Key elements of a traditional regression model term selection process for the analysis of wind tunnel strain-gage balance calibration data are discussed. The traditional process is sometimes applied when regression models of the gage outputs are needed and an analyst does not have access to a term selection algorithm. In principle, the traditional process identifies supported regression model terms of a gage output by combining an analyst's subject- matter knowledge with a visual examination of selected plots of the calibration loads. Twelve empirical rules are listed that may be used to select regression model terms. Data from the manual calibration of a force balance is used to illustrate the application of the traditional term selection process. The data example shows that the traditional process can become very complex. Its successful application highly depends on an analyst's experience and skills. Therefore, it is suggested to replace the traditional term selection process with an automated term selection algorithm. Then, objective metrics are systematically applied during the term selection that make the identification of the regression model more repeatable and less dependent on an analyst's personal skills.

strain-gage balance↗
NASA NTRSDate not supplied

Automated Probabilistic Finite Element Model Calibration Tool Based on Uncertainty Quantification and Machine Learning

Qualification and certification of safety critical parts is a hurdle to the adoption of metallic additively manufactured components for aerospace vehicle applications. Challenges include variability in part properties due to inconsistent defect distribution and microstructure. Understanding of the process through finite element modeling (FEM), and process control through in-situ monitoring, may result in significant improvements; however, solutions useful to manufacturers will require large volumes of data and automated data utilization. Toward this end, a generalizable automated FEM calibration paradigm is developed. This paradigm leverages existing and novel tools from machine learning and uncertainty quantification to enable the automatic calibration of FEMs without requiring prior knowledge of the model performance across input parameter space, including meshing and solver settings, which can require time consuming manual model probing or cause noisy and inconsistent predictions. The result is a probabilistic distribution of calibrated and validated FEM input parameters targeting measured data.

Additive manufacturing model calibration finite el↗
NASA NTRSDate not supplied

Early Results From NOAA-21 (JPSS-2) VIIRS on-Orbit Calibration

Launched on November 10, 2022, the NOAA-21 (N-21) VIIRS has successfully completed its initial post-launch testing (PLT) and intensive calibration and validation (ICV) activities. It is now operated in its nominal configuration and characterized using measurements from its on-board calibrators (OBC) and lunar observations. In this paper, we provide a brief description of N-21 VIIRS on-orbit operation and calibration activities and present results derived from its early mission performance assessments, including examples of its OBC performance, spectral band responses, as well as detector signal to noise characteristics. As shown in this paper, the overall performance of N-21 VIIRS is better than that of its predecessor currently operated on the S-NPP and comparable to the one onboard the N-20, with an exception of relatively large changes in its SWIR band responses.

NOAA-21↗
DOE OSTI2014

Cloud-Based Model Calibration Using OpenStudio: Preprint

OpenStudio is a free, open source Software Development Kit (SDK) and application suite for performing building energy modeling and analysis. The OpenStudio Parametric Analysis Tool has been extended to allow cloud-based simulation of multiple OpenStudio models parametrically related to a baseline model. This paper describes the new cloud-based simulation functionality and presents a model cali-bration case study. Calibration is initiated by entering actual monthly utility bill data into the baseline model. Multiple parameters are then varied over multiple iterations to reduce the difference between actual energy consumption and model simulation results, as calculated and visualized by billing period and by fuel type. Simulations are per-formed in parallel using the Amazon Elastic Cloud service. This paper highlights model parameterizations (measures) used for calibration, but the same multi-nodal computing architecture is available for other purposes, for example, recommending combinations of retrofit energy saving measures using the calibrated model as the new baseline.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2015

AMS Ground Truth Measurements: Calibrations and Test Lines

Airborne gamma spectrometry is one of the primary techniques used to define the extent of ground contamination after a radiological incident. Its usefulness was demonstrated extensively during the response to the Fukushima NPP accident in March-May 2011. To map ground contamination, a set of scintillation detectors is mounted on an airborne platform (airplane or helicopter) and flown over contaminated areas. The acquisition system collects spectral information together with the aircraft position and altitude every second. To provide useful information to decision makers, the count data, expressed in counts per second (cps), need to be converted to a terrestrial component of the exposure rate at 1 meter (m) above ground, or surface activity of the isotopes of concern. This is done using conversion coefficients derived from calibration flights. During a large-scale radiological event, multiple flights may be necessary and may require use of assets from different agencies. However, because production of a single, consistent map product depicting the ground contamination is the primary goal, it is critical to establish a common calibration line very early into the event. Such a line should be flown periodically in order to normalize data collected from different aerial acquisition systems and that are potentially flown at different flight altitudes and speeds. In order to verify and validate individual aerial systems, the calibration line needs to be characterized in terms of ground truth measurements This is especially important if the contamination is due to short-lived radionuclides. The process of establishing such a line, as well as necessary ground truth measurements, is described in this document.

airborne platform↗
DOE OSTI2016

Traceable Pyrgeometer Calibrations

This poster presents the development, implementation, and operation of the Broadband Outdoor Radiometer Calibrations (BORCAL) Longwave (LW) system at the Southern Great Plains Radiometric Calibration Facility for the calibration of pyrgeometers that provide traceability to the World Infrared Standard Group.

14 SOLAR ENERGY↗
DOE OSTI2017

ON-LINE MONITORING OF I&C TRANSMITTERS AND SENSORS FOR CALIBRATION VERIFICATION AND RESPONSE TIME TESTING WAS SUCCESSFULLY IMPLEMENTED AT ATR

The Advanced Test Reactor (ATR) has always had a comprehensive procedure to verify the performance of its critical transmitters and sensors, including RTDs, and pressure, level, and flow transmitters. These transmitters and sensors have been periodically tested for response time and calibration verification to ensure accuracy. With implementation of online monitoring techniques at ATR, the calibration verification and response time testing of these transmitters and sensors are verified remotely, automatically, hands off, include more portions of the system, and can be performed at almost any time during process operations. The work was done under a DOE funded SBIR project carried out by AMS. As a result, ATR is now able to save the manpower that has been spent over the years on manual calibration verification and response time testing of its temperature and pressure sensors and refocus those resources towards more equipment reliability needs. More importantly, implementation of OLM will help enhance the overall availability, safety, and efficiency. Together with equipment reliability programs of ATR, the integration of OLM will also help with I&C aging management goals of the Department of Energy and long-time operation of ATR.

47 OTHER INSTRUMENTATION↗
DOE OSTI2017

Robust Online Monitoring for Calibration Assessment of Transmitters and Instrumentation

Robust online monitoring (OLM) technologies are expected to enable the extension or elimination of periodic sensor calibration intervals in operating and new reactors. These advances in OLM technologies will improve the safety and reliability of current and planned nuclear power systems through improved accuracy and increased reliability of sensors used to monitor key parameters. In this article, we discuss an overview of research being performed within the Nuclear Energy Enabling Technologies (NEET)/Advanced Sensors and Instrumentation (ASI) program, for the development of OLM algorithms to use sensor outputs and, in combination with other available information, 1) determine whether one or more sensors are out of calibration or failing and 2) replace a failing sensor with reliable, accurate sensor outputs. Algorithm development is focused on the following OLM functions: • Signal validation • Virtual sensing • Sensor response-time assessment These algorithms incorporate, at their base, a Gaussian Process-based uncertainty quantification (UQ) method. Various plant models (using kernel regression, GP, or hierarchical models) may be used to predict sensor responses under various plant conditions. These predicted responses can then be applied in fault detection (sensor output and response time) and in computing the correct value (virtual sensing) of a failing physical sensor. The methods being evaluated in this work can compute confidence levels along with the predicted sensor responses, and as a result, may have the potential for compensating for sensor drift in real-time (online recalibration). Evaluation was conducted using data from multiple sources (laboratory flow loops and plant data). Ongoing research in this project is focused on further evaluation of the algorithms, optimization for accuracy and computational efficiency, and integration into a suite of tools for robust OLM that are applicable to monitoring sensor calibration state in nuclear power plants.

fault detection↗
DOE OSTI2018

Bayesian Calibration of Inertial Confinement Fusion Models with Very Expensive Data

Calibrating computer simulations against experimental data is a ubiquitous problem in science and is particularly difficult when experimental data are expensive or diffi- cult to collect. In inertial confinement fusion experiments, where a single data point can cost 10 5 –10 6 USD, calibration of large-scale design calculations is particularly challenging. We present a framework that aims to provide calibrated predictions far from the available data that can be trained using a small number of data points. The approach aims to retain as much of the physics (summarized by the simulation code) as possible and is based on a truncated polynomial chaos expansion in the space of simulation inputs, augmented with a non-parametric correction for higher distribution modes. Due to the difficulty of the problem, understanding the sources of uncertainty in the model is essential; we demonstrate this through an application of our approach to a series of 6 experimental laser shots. As a result, we validate our approach, show that the uncertainties in our predictions of experimental performance are dominated by shot-shot fluctuations and regression uncertainties, and discuss paths towards an improved prediction model.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2013

Statistical modeling support for calibration of a multiphysics model of subcooled boiling flows

Nuclear reactor system analyses rely on multiple complex models which describe the physics of reactor neutronics, thermal hydraulics, structural mechanics, coolant physico-chemistry, etc. Such coupled multiphysics models require extensive calibration and validation before they can be used in practical system safety study and/or design/technology optimization. This paper presents an application of statistical modeling and Bayesian inference in calibrating an example multiphysics model of subcooled boiling flows which is widely used in reactor thermal hydraulic analysis. The presence of complex coupling of physics in such a model together with the large number of model inputs, parameters and multidimensional outputs poses significant challenge to the model calibration method. However, the method proposed in this work is shown to be able to overcome these difficulties while allowing data (observation) uncertainty and model inadequacy to be taken into consideration. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2015

Study of the influence of heat sources on the out-of-pile calibration curve of calorimetric cells used for nuclear energy deposition quantification

At present the Jules Horowitz Reactor is under construction in Cadarache research center of CEA 'French Alternative Energies and Atomic Energy Commission' center located in the south-east of France. This new Material Testing Reactor (MTR) will be operational in late 2019 and will allow the generation of a new experimental potential (up to 20 irradiation devices simultaneously) and new harsh conditions such as higher neutron fluxes (5.10{sup 14} n.cm{sup -2}.s{sup -1} for E≥1 MeV), faster material ageing and higher nuclear heating (up to 20 W/g for nominal capacity of 100 MW). In nuclear research field, the control and the measurement of the nuclear heating (energy deposition rate per mass unit induced by the interactions of radiations with matter) is crucial to carry out accurate studies on ageing of materials and on the behavior of nuclear fuels under irradiation. Several experiments need to know precisely this key parameter in order to establish dedicated thermal conditions. The measurement of the nuclear heating inside MTRs is realized by three kinds of sensors: single-cell calorimeter, differential calorimeter and gamma thermometer. One scientific objective of the IN-CORE program, between CEA and Aix-Marseille University in 2009, is to improve the nuclear heating measurement. In this context a new multi-sensor device, called CARMEN, was made. This device contains in particular a differential calorimeter which was designed to measure the nuclear heating in the periphery of OSIRIS reactor (a MTR located at Saclay, France) up to 2 W/g and tested during two irradiation campaigns. Results obtained during these campaigns showed that temperatures reached inside the calorimeter are higher than ones obtained during the preliminary out-of-pile calibration experiments. For instance for 1.74 W/g, the in-pile temperature of the calorimeter rod is equal to 305 deg. C against 225 deg. C in laboratory conditions by simulating the nuclear heating by Joule Effect inside the calorimeter cell head. This discrepancy is higher than in previous experiments because the calorimeter owns a high sensitivity. Consequently, a new prototype was created and instrumented by other heat sources in order to impose an energy deposition on the calorimetric cell structure (in particular in the base) and to improve the calibration step in out-of-pile conditions. In this paper, on the first part a detailed description of the new calorimetric sensor will be given. On the second part, the experimental response of the sensor obtained for several internal heating conditions will be shown. The influence of these conditions on the calibration curve will be discussed. Then the response of this prototype will be also presented for different external cooling fluid conditions (in particular flow temperature). In this part, the comparison between the in-pile and out-of-pile experimental results will be performed. On the last part, these out-of-pile experiments will be completed by 2D axisymmetrical thermal simulations with the CEA code CAST3M using Finite Elements Method. After a comparison between experimental and numerical works, improvements of the sensor prototype will be studied (new heat sources). (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2017

Robust online monitoring for calibration assessment of transmitters and instrumentation - 260

Robust online monitoring (OLM) technologies are expected to enable the extension or elimination of periodic sensor calibration intervals in operating and new reactors. Advances in OLM technologies will improve the safety and reliability of current and planned nuclear power systems through improved accuracy and increased reliability of sensors used to monitor key parameters. In this paper, we discuss an overview of research being performed within the Nuclear Energy Enabling Technologies (NEET)/Advanced Sensors and Instrumentation (ASI) program, for the development of OLM algorithms to use sensor outputs and, in combination with other available information, 1) determine whether one or more sensors are out of calibration or failing and 2) replace a failing sensor with reliable, accurate sensor outputs. A Gaussian Process (GP)-based uncertainty quantification (UQ) method previously developed for UQ in OLM, was adapted for this purpose. The resulting models are being evaluated for use in high-confidence signal validation for the purpose of detecting and diagnosing sensor faults, and for computing virtual sensor outputs that may be used as a temporary replacement for failing sensors. In addition to assessing sensor drift, approaches for extracting sensor response time in an automated fashion were developed, for monitoring changes in sensor response time in pressure transmitters. Such changes are also indicative of various fault modes. These algorithms were evaluated with existing measurement data from several laboratory-scale flow loops. Ongoing research in this project is focused on further evaluation of the algorithms, optimization for accuracy and computational efficiency, and integration into a suite of tools for robust OLM that are applicable to monitoring sensor calibration state in nuclear power plants. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗