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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 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Milestone 1.2.13: Preliminary Measurements of Radiolytic Nitric Acid Formation to Support Predictive Model Validation

Predictive computational models have been developed to support the technical basis for extended dry storage of aluminum-clad spent nuclear fuel (ASNF) in helium-backfilled cannisters. To date, these models have been optimized on a variety of irradiation experiments designed to elucidate the radiation-induced formation of molecular hydrogen gas, a radiolysis product that is potentially problematic for the safe storage of ASNF. However, the yield of nitric acid (HNO3) has not been determined, despite conservative predictions of its formation (300–4000 ppm) in 1% residual air environments irradiated in contact with ASNF. HNO3, another problematic radiolysis product, can lead to enhanced corrosion and potentially compromise storage canister integrity. Thus, to support the validation of predictive computer models, we report the measurement and quantification of HNO3 from the gamma irradiation of aluminum alloy coupons in humid air.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2019

Distribution-Level Phasor Measurement Units Application to Composite Load Model Validation

The paper presents the results of composite load model validation based on the distribution level micro- phasor measurement units (PMU) measurements. The actual micro-PMU measurements from the distribution feeders are collected by Lawrence Berkley National Laboratory (LBNL). The composite load model parameters are initially generated using the load model data tool developed by Pacific Northwest National Laboratory (PNNL). The generated load models are calibrated to match the performances with the micro-PMU measurements using disturbance records “play-in” capabilities available in a GE PSLF simulation package. A trial-and-error approach based on engineering judgement is proposed in this paper to benchmark the generated load model parameters and is implemented in the prototype of load model validation tool, which would be a supplement to the load model data tool.

Liu, Yuan↗
NASA NTRS2012

Method for Pre-Conditioning a Measured Surface Height Map for Model Validation

This software allows one to up-sample or down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. Because the re-sampling of a surface map is accomplished based on the analytical expressions of Zernike-polynomials and a power spectral density model, such re-sampling does not introduce any aliasing and interpolation errors as is done by the conventional interpolation and FFT-based (fast-Fourier-transform-based) spatial-filtering method. Also, this new method automatically eliminates the measurement noise and other measurement errors such as artificial discontinuity. The developmental cycle of an optical system, such as a space telescope, includes, but is not limited to, the following two steps: (1) deriving requirements or specs on the optical quality of individual optics before they are fabricated through optical modeling and simulations, and (2) validating the optical model using the measured surface height maps after all optics are fabricated. There are a number of computational issues related to model validation, one of which is the "pre-conditioning" or pre-processing of the measured surface maps before using them in a model validation software tool. This software addresses the following issues: (1) up- or down-sampling a measured surface map to match it with the gridded data format of a model validation tool, and (2) eliminating the surface measurement noise or measurement errors such that the resulted surface height map is continuous or smoothly-varying. So far, the preferred method used for re-sampling a surface map is two-dimensional interpolation. The main problem of this method is that the same pixel can take different values when the method of interpolation is changed among the different methods such as the "nearest," "linear," "cubic," and "spline" fitting in Matlab. The conventional, FFT-based spatial filtering method used to eliminate the surface measurement noise or measurement errors can also suffer from aliasing effects. During re-sampling of a surface map, this software preserves the low spatial-frequency characteristic of a given surface map through the use of Zernike-polynomial fit coefficients, and maintains mid- and high-spatial-frequency characteristics of the given surface map by the use of a PSD model derived from the two-dimensional PSD data of the mid- and high-spatial-frequency components of the original surface map. Because this new method creates the new surface map in the desired sampling format from analytical expressions only, it does not encounter any aliasing effects and does not cause any discontinuity in the resultant surface map.

Sidick, Erkin↗
NASA NTRS2010

An Overview of Thermal Distortion Modeling, Analysis, and Model Validation for the JWST ISIM Structure

This paper describes thermal distortion modeling, analysis, and model validation activities completed in support of the design and qualification of the JWST ISIM Structure. An overview of the building blocks approach utilized to develop the structural design and modeling capabilities to meet thermal distortion performance requirements will be provided. This effort culminated in a cryogenic (35 K) distortion test of the flight ISIM Structure hardware, the Cryoset Test that both verified the thermal distortion performance and provided data for validation of the structural models. An overview of the modeling, analysis, and model validation development effort will be discussed, and the results of the Cryoset Test and the subsequent model validation will be described.

Johnston, John↗
NASA NTRS2005

Thermal System Verification and Model Validation for NASA's Cryogenic Passively Cooled James Webb Space Telescope (JWST)

A thorough and unique thermal verification and model validation plan has been developed for NASA s James Webb Space Telescope. The JWST observatory consists of a large deployed aperture optical telescope passively cooled to below 50 Kelvin along with a suite of several instruments passively and actively cooled to below 37 Kelvin and 7 Kelvin, respectively. Passive cooling to these extremely low temperatures is made feasible by the use of a large deployed high efficiency sunshield and an orbit location a! !he L2 Lagrange p~in!. Another enabling feature is the scale or size of the observatory that allows for large radiator sizes that are compatible with the expected power dissipation of the instruments and large format Mercury Cadmium Telluride (HgCdTe) detector arrays. This passive cooling concept is simple, reliable, and mission enabling when compared to the alternatives of mechanical coolers and stored cryogens. However, these same large scale observatory features, which make passive cooling viable, also prevent the typical flight configuration fully-deployed thermal balance test that is the keystone to most space missions thermal verification plan. JWST is simply too large in its deployed configuration to be properly thermal balance tested in the facilities that currently exist. This reality, when combined with a mission thermal concept with little to no flight heritage, has necessitated the need for a unique and alternative approach to thermal system verification and model validation. This paper describes the thermal verification and model validation plan that has been developed for JWST.

Parrish, Keith↗
NASA NTRS1999

Uncertainty Modeling Via Frequency Domain Model Validation

Abstract The majority of literature on robust control assumes that a design model is available and that the uncertainty model bounds the actual variations about the nominal model. However, methods for generating accurate design models have not received as much attention in the literature. The influence of the level of accuracy of the uncertainty model on closed loop performance has received even less attention. The research reported herein is an initial step in applying and extending the concept of model validation to the problem of obtaining practical uncertainty models for robust control analysis and design applications. An extension of model validation called 'sequential validation' is presented and applied to a simple spring-mass-damper system to establish the feasibility of the approach and demonstrate the benefits of the new developments.

Waszak, Martin R.↗
DOE OSTI2020

Validated model of a thermoelectric heat pump clothes dryer using secondary pumped loops

The energy associated with clothes drying makes up 4% of the total residential electrical energy consumption in the US. The cost is high since most clothes dryers use electric resistance heating which is inexpensive but also energy inefficient. State-of-the-art vapor-compression heat pump clothes dryers offer significant energy savings but have limited market penetration in the US. Here, a new configuration of clothes dryer was studied that utilizes a solid-state thermoelectric heat pump with pumped secondary water loops and conventional fin-and-tube water-to-air heat exchangers. Experimental results are presented for the thermoelectric dryer prototype with a combined energy factor of 6.89 lb BDW /kWh (specific moisture extraction rate of 1.71 kg w /kWh) and a dry time of 84 min for a standard load size of 8.45 lb (3.83 kg) with 57.5% starting moisture content. This is a 85% energy efficiency improvement over baseline electric resistance dryers. The efficiency and drying time results achieved are similar to vapor compression heat pump dryers. Compared to previous air-based thermoelectric clothes dryers, the energy efficiency has been increased by 6%, but drying time has been reduced by as much as 47% using secondary pumped loops and separate heat exchangers, which represents a significant advancement in the technology. In addition to the experimental prototype, a model was also developed to study the performance. The model was validated against experimental prototype data and used to identify the range of performance (dry time and efficiency) that could be expected of the design.

42 ENGINEERING↗
DOE OSTI2025

Radiation-induced bowing of SiC/SiC composites under neutron flux gradients—integral experimental data for model validation

Here, the radiation-induced swelling of SiC and its composites, including strong dependencies on temperature and dose, can drive significant lateral bowing in the presence of temperature and/or dose gradients. In recent years, simulations have been performed to assess the extent of bowing in SiC composite light-water reactor (LWR) fuel cladding and boiling water reactor (BWR) channel boxes. However, to date, no integral experimental data exist to validate these models. This work provides the first experimental bowing evaluation of three ∼380 mm long SiC composite specimens irradiated under varying neutron dose gradients (∼50°C–60°C, 0.03–0.06 dpa): two tubes (∼9.8 mm diameter) and a miniature BWR channel box (∼30 mm square). The measured radiation-induced length swelling (∼0.3%–0.7% linear) was consistently 10%–21% higher than values obtained from 3D finite element structural analyses with inputs from 3D radiation transport calculations. This discrepancy could be at least partially explained by differences in dose rate (∼10 -8 dpa/s) compared to the literature data (∼10-6 dpa/s) used to establish the dose-to-swelling correlations in the model. Nevertheless, the modeled bowing magnitudes (<2 mm) obtained from finite element analyses and simple analytical equations were within the bounds of the experimental measurements for all specimens. With improved confidence in the ability to predict the structural response and measure the macroscopic deformations, future experiments will target transient bowing under neutron flux gradients at representative LWR temperatures and assess whether grid spacers can mitigate the tens of millimeters of bowing that would otherwise be expected in ∼4 m long LWR components.

bowing↗
NASA NTRS2008

Improved Products for Assimilation and Model Validation from the Atmospheric Infrared Sounder (AIRS) on Aqua

The Atmospheric Infrared Sounder (AIRS) on the EOS Aqua Spacecraft was launched on May 4, 2002. AIRS acquires hyperspectral infrared radiances in the 3.7-15.4 micrometer spectral region with spectral resolution of better than 1200. Key channels from the AIRS Level 1B calibrated radiance product are currently assimilated into operational weather forecasts at NCEP and other international agencies. Additional Level 2 products for assimilation include the AIRS cloud cleared radiances and the geophysical retrieved temperature and water vapor profiles. The AIRS products are also used to validate climate model vertical and horizontal biases and transport of water vapor and key trace gases including Carbon Dioxide and Ozone. The wide variety of products available from the AIRS make it well suited to study processes affecting the interaction of these products.

weather↗
NASA NTRS2016

SOSS ICN Model Validation

Under the NASA-KAIA-KARI ATM research collaboration agreement, SOSS ICN Model has been developed for Incheon International Airport. This presentation describes the model validation work in the project. The presentation will show the results and analysis of the validation.

model validation↗
NASA NTRS2012

Techniques for Down-Sampling a Measured Surface Height Map for Model Validation

This software allows one to down-sample a measured surface map for model validation, not only without introducing any re-sampling errors, but also eliminating the existing measurement noise and measurement errors. The software tool of the current two new techniques can be used in all optical model validation processes involving large space optical surfaces

Sidick, Erkin↗
DOE OSTI2019

A FREQUENCY RESPONSE APPROACH TO MODEL VALIDATION FOR THE COMPACT INTEGRAL EFFECTS TEST FACILITY IN TRANSFORM

One of the key challenges to licensing new reactor designs is validating the integral transient response models of a novel system. This work used a frequency response approach for model validation of the Compact Integral Effects Test (CIET) facility at the University of California, Berkeley. This facility was built as a scaled integral effects test for verifying transient modeling tools for fluoride-salt-cooled hightemperature reactors using Dowtherm A as a simulant fluid for molten salt. The dynamic system model of CIET was created using the Modelica-based TRANSFORM tool developed by Oak Ridge National Laboratory (ORNL). Analysis of the model’s performance as compared with experimental results indicates good agreement under both steady-state and transient conditions. This paper describes the Modelica model creation process using TRANSFORM and the modeling assumptions and methods for matching dynamic behavior with frequency response data. Results, analysis, and a discussion of future work are also presented.

De wet, Dane↗
NASA NTRS2011

An Overview of Thermal Distortion Modeling, Analysis, and Model Validation for the JWST ISIM Structure

The James Webb Space Telescope (JWST) is a large, infrared-optimized space telescope consisting of the following elements: (1) Optical telescope element (OTE) (2) Integrated science instrument module (ISIM) (3) Spacecraft (4) Sunshield The Integrated Science Instrument Module (ISIM) consists of the JWST science instruments (NIRCam, MIRI, NIRSpec), a fine guidance sensor (FGS), the ISIM Structure, and thermal and electrical subsystems. JWST's instruments are designed to work primarily in the infrared range of the electromagnetic spectrum, and the instruments and telescope operate at cryogenic temperatures (approximately 35 K for the instruments). The development and validation of a thermal distortion modeling and analysis capability for the JWST ISIM Structure was successfully completed. The modeling and analysis approach was grounded in initial constituent materials testing and benchmarked to test results at the composite bonded joint, subassembly, and fullscale flight hardware levels. Comparison of analysis predictions and test results from this series of incremental cryogenic thermal distortion tests demonstrates that the model validation goals are achieved.

Johnston, John↗
DOE OSTI2024

Inverter Model Validation and Calibration Using Phasor Measurement Unit Data

As the penetration of inverter-based renewable energy resources increases in the power grid, especially at the distribution and microgrid levels, the need to accurately represent them in planning studies increases as well. However, due to the lack of well-established standard procedures, and vendor reluctance towards the detailed sharing of proprietary models, automated dynamic model validation and parameter calibration tools for inverter based resources (IBRs) remain scarce. This work presents a model validation and parameter calibration platform for representing IBRs with generic phasor-domain models. Phasor measurements of power system events are used for continuous validation using the data playback method, and model parameters are re-calibrated if a significant mismatch between measurements and model response is observed. Unique features of the proposed platform include- (a) an iterative Bayesian optimization approach towards parameter calibration to address a possible mismatch between the structures of generic models implemented in simulation softwares and actual commercial inverters, (b) error metrics designed to account for a possible mismatch between the time resolution of simulation and measurements, and (c) analysis of the measurement-simulation mismatch to provide guidance to engineering personnel regarding model shortcomings. The performance of the platform has been illustrated using both simulated data and field measurements to validate/calibrate inverter models in GridLAB-D.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

Processing Aleatory and Epistemic Uncertainties in Experimental Data From Sparse Replicate Tests of Stochastic Systems for Real-Space Model Validation

This paper presents a practical methodology for propagating and processing uncertainties associated with random measurement and estimation errors (that vary from test-to-test) and systematic measurement and estimation errors (uncertain but similar from test-to-test) in inputs and outputs of replicate tests to characterize response variability of stochastically varying test units. Also treated are test condition control variability from test-to-test and sampling uncertainty due to limited numbers of replicate tests. These aleatory variabilities and epistemic uncertainties result in uncertainty on computed statistics of output response quantities. The methodology was developed in the context of processing experimental data for “real-space” (RS) model validation comparisons against model-predicted statistics and uncertainty thereof. The methodology is flexible and sufficient for many types of experimental and data uncertainty, offering the most extensive data uncertainty quantification (UQ) treatment of any model validation method the authors are aware of. It handles both interval and probabilistic uncertainty descriptions and can be performed with relatively little computational cost through use of simple and effective dimension- and order-adaptive polynomial response surfaces in a Monte Carlo (MC) uncertainty propagation approach. A key feature of the progressively upgraded response surfaces is that they enable estimation of propagation error contributed by the surrogate model. Sensitivity analysis of the relative contributions of the various uncertainty sources to the total uncertainty of statistical estimates is also presented. Finally, the methodologies are demonstrated on real experimental validation data involving all the mentioned sources and types of error and uncertainty in five replicate tests of pressure vessels heated and pressurized to failure. Simple spreadsheet procedures are used for all processing operations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

HYBRID Modeling Validation and Verification Status Matrix

The HYBRID modeling repository is a premier resource for integrated energy systems modeling. HYBRID models have been developed since 2015 to describe the physical operation of tightly coupled thermal systems including power generators, thermal transport systems, thermal storage, thermal-to-electric conversion systems, and other thermal applications. Due to the increased size of the repository, a concise summary matrix of available models is desired. This matrix will consolidate not only the list of available models but also indicate original information sources, publications that have model examples, and level of validation and verification that exists for the models. Validation and verification (V&V) levels begin from simplified algebraic relationship and advance to dynamic data validation. Moving forward, as new models are contributed to HYBRID, their V&V level will be included, updating this matrix.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
NASA NTRS2020

Model Validation for Bigelow Expandable Activity Module (BEAM) with Stowage

The Bigelow Expandable Activity Module (BEAM) was a collaboration between NASA and Bigelow Aerospace to develop an expandable habitat technology that could be used for future space exploration missions such as the Artemis program. On April 26, 2016, the BEAM was launched and berthed to the International Space Station (ISS) on the aft port of Node 3. After the originally planned two-year mission life, BEAM was approved for use as a stowage module for a 109-cargotransfer bag equivalent (CTBE) to alleviate stowage limitations onboard the ISS. The present work builds on the previous 2017 model validation to flight data that demonstrated that BEAM could generally accommodate cargo stowage without adversely affecting BEAM thermal control, primarily for condensation management. Once the stowage was configured in early 2019, model validation efforts resumed. The thermal model revisions included the CTBE stowage and updated CFD-derived heat transfer coefficients for various intra-module ventilation (IMV) flow rates. The coefficients were provided by the Crew and Thermal Systems Division (EC) at NASA JSC and Jacobs Technology. The model is now revalidated and able to predict minimum temperatures with good agreement to flight temperatures (within 1 °C) for both historic and recurring minimum values. Additionally, the model is partially validated for reduced flow rates. With this model, the team was able to provide new flight rule recommendations for condensation and IMV operations management.

Sydney Taylor↗
DOE OSTI2020

Blind Modeling Validation Exercises Using the Horizontal Dry Cask Simulator

The U.S. Department of Energy (DOE) established a need to understand the thermal-hydraulic properties of dry storage systems for commercial spent nuclear fuel (SNF) in response to a shift towards the storage of high-burnup (HBU) fuel (> 45 gigawatt days per metric ton of uranium, or GWd/MTU). This shift raises concerns regarding cladding integrity, which faces increased risk at the higher temperatures within spent fuel assemblies present within HBU fuel compared to low-burnup fuel (≤ 45 GWd/MTU). A dry cask simulator (DCS) was built at Sandia National Laboratories (SNL) in Albuquerque, New Mexico to produce validation-quality data that can be used to test the accuracy of the modeling used to predict cladding temperatures. These temperatures are critical to evaluating cladding integrity throughout the storage cycle of commercial spent nuclear fuel. A model validation exercise was previously carried out for the DCS in a vertical configuration. Lessons learned during the previous validation exercise have been applied to a new, blind study using a horizontal dry cask simulator (HDCS). Three modeling institutions – the Nuclear Regulatory Commission (NRC), Pacific Northwest National Laboratory (PNNL), and Empresa Nacional del Uranio, S.A., S.M.E. (ENUSA) – were granted access to the input parameters from the DCS Handbook, SAND2017-13058R, and results from a limited data set from the horizontal BWR dry cask simulator tests reported in the HDCS update report, SAND2019-11688R. With this information, each institution was tasked to calculate peak cladding temperatures and air mass flow rates for ten HDCS test cases. Axial as well as vertical and horizontal transverse temperature profiles were also calculated. These calculations were done using modeling codes (ANSYS/Fluent, STAR-CCM+, or COBRA-SFS), each with their own unique combination of modeling assumptions and boundary conditions. For this validation study, the ten test cases of the horizontal dry cask simulator were defined by three independent variables – fuel assembly decay heat (0.5 kW, 1 kW, 2.5 W, and 5 kW), internal backfill pressure (100 kPa and 800 kPa), and backfill gas (helium and air). The plots provided in Chapter 3 of this report show the axial, vertical, and horizontal temperature profiles obtained from the dry cask simulator experiments in the horizontal configuration and the corresponding models used to describe the thermal-hydraulic behavior of this system. The tables provided in Chapter 3 illustrate the closeness of fit of the model data to the experiment data through root mean square (RMS) calculations of the error in peak cladding temperatures (PCTs), PCT axial locations, axial temperature profiles, vertical and horizontal temperature profiles at two different axial locations, and air mass flow rates for the ten test cases, normalized by the experimental results. The model results are assigned arbitrary model numbers to retain anonymity. Due to the relatively flat axial temperature profiles, small temperature gradients resulted in large deviations of all models’ PCT axial location from the experimental PCT axial location. When the PCT axial location error is excluded in the calculation of the combined RMS of the normalized errors that considers PCT, the temperature profiles, and the air mass flow rates, the model data fits the experimental data to within 5%. When the vault information is excluded, the model data fits the experimental data to within 2.5%. An error analysis was developed further for one model, using the model and experimental uncertainties in each validation parameter to calculate validation uncertainties. The uncertainties for each parameter were used to define quantifiable validation criteria. For this analysis, the model was considered validated for a given comparison metric if the normalized error in that metric divided by the validation uncertainty was less than or equal to 1. When considering the combined RMS of the normalized errors of all metrics divided by their validation uncertainties, the model was found to have satisfied the criterion for model validation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗