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At least 469 records · Page 26

All sources NASA NTRS DOE OSTI

NASA NTRS2019

A Terrestrial Validation of ICESat Elevation Measurements and Implications for Global Reanalyses

The primary goal of NASA's Ice, Cloud, and land Elevation Satellite (ICESat) mission was to detect centimeter-level changes in global ice sheet elevations at the spatial scale of individual ice streams. Confidence in detecting these small signals requires careful validation over time to characterize the uncertainty and stability of measured elevations. A common validation approach compares altimeter elevations to an independently characterized and stable reference surface. Using a digital elevation model (DEM) from geodetic surveys of one such surface, the salar de Uyuni in Bolivia, we show that ICESat elevations at this location have a 0.0-centimeter bias relative to the WGS84 ellipsoid, 4.0-centimeter (1-sigma) uncertainty overall, and 1.8-centimeter uncertainty under ideal conditions over short (50 kilometer) profiles. We observe no elevation bias between ascending and descending orbits, but we do find that elevations measured immediately after transitions from low to high surface albedo may be negatively biased. Previous studies have reported intercampaign biases (ICBs) between various ICESat observation campaigns, but we find no statistically significant ICBs or ICB trends in our data. We do find a previously unreported 3.1-centimeter bias between ICESat's Laser 2 and Laser 3, and we find even larger interlaser biases in reanalyzed data from other studies. For an altimeter with an exact repeat orbit like ICESat, we also demonstrate that validation results with respect to averaged elevation profiles along a single ground track are comparable to results obtained using reference elevations from an in situ survey.

Laser Ranging↗

NASA NTRS2020

Analytical Redundancy Using Kalman Filters for Rocket Engine Sensor Validation

The use of sensor redundancy is crucial in aerospace systems to maintain safe, reliable operation. While hardware redundancy is more common in application, analytical redundancy can provide a viable alternative in systems where the installation of multiple redundant sensors is not viable. To this end, the use of Kalman filters to analytically validate sensor measurements within rocket engines was explored. First, a dynamic model of the RS 25 engine, a derivative of the Space Shuttle Main Engine (SSME), was reduced to a subset of relations, focused around the main combustion chamber pressure. These relations were used within the Kalman filter algorithm to generate an estimate of sensor measurements to be compared with true measurements for data validation purposes. By using a bank of Kalman filters, the residuals between the estimated and true measurements were used to detect and isolate sensor faults. Through fault simulations, the sensor validation performance of this Kalman filter bank design was compared to a hardware redundancy check. Sensor bias and drift faults of various magnitudes were injected into nominal RS 25 engine test data. Results for both approaches show comparable fault detection with most bias faults found nearly instantaneously by both algorithms. Drift fault detection results show certain cases where one algorithm is faster than the other. The key advantage of the Kalman filter algorithm is shown in fault isolation performance where it can isolate faults between two redundant sensors while the hardware redundancy comparisons cannot.

sensors↗

NASA NTRSDate not supplied

CFD Validation Experiments: Toward a Broader Perspective

The current literature considers a CFD validation experiment synonymously with a particular type of wind tunnel test. By drawing on the experience of the authors, this paper makes a case for broadening the definition to include a more balanced and synergistic exploitation of computational and physical testing techniques. The concept of validation dialog is introduced which, together with technique verification, is considered a key enabler in the pursuit of an improved CFD predictive capability. An outline of a lifecycle for a CFD validation experiment is also proposed to consolidate the thinking. The result, it is reasoned, will encourage improved engagement with a broader range of stakeholders and wider recognition of the value of the outcomes of what might otherwise be considered studies of lesser importance. In turn, this is expected to encourage the adoption of more systematic approaches to complex problems, such that they are more readily broken down into smaller, more focused endeavors, while at the same time making such activities easier to fund.

CFD↗

NASA NTRS2022

Verification and Validation of Hybridspectral Radiometry Obtained from an Unmanned Surface Vessel (USV) in the Open and Coastal Oceans

The hardware and software capabilities of the compact-profiling hybrid instrumentation for radiometry and ecology (C-PHIRE) instruments on an unmanned surface vessel (USV) are evaluated. Both the radiometers and USV are commercial-off-the-shelf (COTS) products, with the latter being only minimally modified to deploy the C-PHIRE instruments. The hybridspectral C-PHIRE instruments consist of an array of 18 multispectral microradiometers with 10 nm wavebands spanning 320–875 nm plus a hyperspectral compact grating spectrometer (CGS) with 2048 pixels spanning 190–1000 nm. The C-PHIRE data were acquired and processed using two architecturally linked software packages, thereby allowing lessons learned in one to be applied to the other. Using standard data products and unbiased statistics, the C-PHIRE data were validated with those from the well-established compact-optical profiling system (C-OPS) and verified with the marine optical buoy (MOBY). Agreement between algorithm variables used to estimate colored dissolved organic matter (CDOM) absorption and chlorophyll a concentration were also validated. Developing and operating novel technologies, such as the C-PHIRE series of instruments, deployed on a USV increase the frequency and coverage of optical observations, which are required to fully support the present and next-generation validation exercises in radiometric remote sensing of aquatic ecosystems.

Hybridspectral↗

NASA NTRS2022

Unifying the Validation of Ambient Solar Wind Models

Progress in space weather research and awareness needs community-wide strategies and procedures to evaluate our modeling assets. Here we present the activities of the Ambient Solar Wind Validation Team embedded in the COSPAR ISWAT initiative. We aim to bridge the gap between model developers and end-users to provide the community with an assessment of the state-of-the-art in solar wind forecasting. To this end, we develop an open online platform for validating solar wind models by comparing their solutions with in situ spacecraft measurements. The online platform will allow the space weather community to test the quality of state-of-the-art solar wind models with unified metrics providing an unbiased assessment of progress over time. In this study, we propose a metadata architecture and recommend community-wide forecasting goals and validation metrics. We conclude with a status update of the online platform and outline future perspectives.

Space weather↗

NASA NTRSDate not supplied

Validation of Gas-Liquid Sharp Interface Model in Loci-Stream for Propellant Tank Self-pressurization under Normal Gravity

Deep space missions require advances in cryogenic fluid management (CFM) for long term storage of propellants. One of the important phenomena is self-pressurization due to heat leakages into the tank. Managing self-pressurization is one of the key technologies for deep space exploration and long-term space missions. The complex interactions involving natural convection, thermal gradients, turbulence, and phase change near the gas-liquid interface cannot be modeled using reduced order or nodal analysis models, and 3-D CFD analyses are necessary to fully characterize the dynamics. CFD analyses pose their own difficulties. The requisite CFD tool to tackle this problem need to be modular with the ability to incorporate various physics models, efficient, and computationally scalable for simulating flight size tanks. In this paper, we discuss modeling approach for self-pressurization in situations where the liquid interface is static and validate NASA MSFC’s Loci-Stream CFD solver for predicting self-pressurization in a test tank in normal gravity. This tank was designed to capture quantifiable and accurate data for understanding various two-phase fluid phenomena and to validate modeling tools. Specifically, we demonstrate the capability of the Loci-Stream solver with a two-phase sharp-interface treatment to predict self-pressurization of a tank with an unperturbed gas-liquid interface. This validation highlights the reliability of our modeling approach and our solver to serve as a design and analysis tool for NASA’s CFM application needs.

cryogenic fluid management↗

NASA NTRSDate not supplied

Validation of Gas-Liquid Sharp Interface Model in Loci-Stream for Propellant Tank Self-pressurization under Normal Gravity

Deep space missions require advances in cryogenic fluid management (CFM) for long term storage of propellants. One of the important phenomena is self-pressurization due to heat leakages into the tank. Managing self-pressurization is one of the key technologies for deep space exploration and long-term space missions. The complex interactions involving natural convection, thermal gradients, turbulence, and phase change near the gas-liquid interface cannot be modeled using reduced order or nodal analysis models, and 3-D CFD analyses are necessary to fully characterize the dynamics. CFD analyses pose their own difficulties. The requisite CFD tool to tackle this problem need to be modular with the ability to incorporate various physics models, efficient, and computationally scalable for simulating flight size tanks. In this paper, we discuss modeling approach for self-pressurization in situations where the liquid interface is static and validate NASA MSFC's Loci-Stream CFD solver for predicting self-pressurization in a test tank in normal gravity. This tank was designed to capture quantifiable and accurate data for understanding various two-phase fluid phenomena and to validate modeling tools. Specifically, we demonstrate the capability of the Loci-Stream solver with a two-phase sharp-interface treatment to predict self-pressurization of a tank with an unperturbed gas-liquid interface. This validation highlights the reliability of our modeling approach and our solver to serve as a design and analysis tool for NASA's CFM application needs.

cryogenic fluid management↗

NASA NTRSDate not supplied

Validation of Two-phase Flow Modeling Techniques in Loci-Stream using Axial Jet Pressure Control and Autogenous Pressurization Experiment

Improvements to computational fluid dynamics modeling of cryogenic fluid management operations are presented with experimental validations. Modeling improvements includes utilizing improved delayed detaches eddy simulation to more effectively model turbulence compared to the Reynolds-averaged Navier Stokes modeling, modeling temperature dependent tank solid properties to capture large variation in thermodynamic properties at cryogenic conditions, modeling real gas equation of state for hydrogen instead of ideal gas behavior, and an on-going effort to improve interface turbulence transport for the volume of fluid method. Two flight-scale ground tests, five K-site tank axial jet pressure control experiments and an Engineering Design Unit tank autogenous pressurization experiment are validated and show the effectiveness of the improved modeling techniques. The successful validation establishes further trust in these models for flight project support and provides a pathway for maturation of in-development interface turbulence damping model for the volume of fluid method for more generalized applications.

CFD↗

NASA NTRSDate not supplied

Validation of Two-Phase Flow Modeling Techniques in Loci-Stream Using Axial Jet Pressure Control and Autogenous Pressurization Experiments

CFD↗

DOE OSTI2021

Validation of Oregon State University High Temperature Test Facility Experiments Using Pronghorn

The OSU High Temperature Test Facility is a quarter-scale diameter, 1/64 scale volume test facility meant to replicate thermophysical phenomena in the prototypical General Atomics Modular High Temperature Gas Reactor. Tests pertaining to conduction cooldown events were performed from 2016-2019, providing a large database by which computational methods that are applicable to different length scales can be validated. One of these codes is Pronghorn, which is a coarse-meshed, porous-based subchannel thermal hydraulics code based on the MOOSE application, with the intention of better capturing the physics of both conduction and convection heat transfer within the OSU HTTF core. The goal of this summer project is to develop the framework by which Pronghorn can perform validation exercises of the HTTF core for benchmarking, by generating a mesh appropriate to the geometry of the HTTF core, developing input decks that accurately capture the initial and boundary conditions, materials, and relevant equations to the physics seen in the HTTF core, and using a postprocessor to compare simulation results to various experimental data. While validation of codes is a multi-year project, a mesh has been generated and tested in Pronghorn that meets mass conservation and basic heat transfer principles. The next step is to accurate depict the fluid inlet and outlet boundary conditions, which will be performed using computational fluid dynamics software.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Conducting Field Validations of Commercial Energy Efficiency Technologies with Underserved Communities: Preprint

Underserved communities in the United States often experience the negative impacts of climate change and environmental degradation but enjoy few of the benefits of technological and environmental advances. The White House has addressed this inequity through the Justice40 initiative, which requires 40% of the benefits of select federal investments to be directed to underserved communities (The White House, 2022). Clean energy and energy efficiency are two highlighted investment categories, so the U.S. Department of Energy will guide implementation of the Justice40 initiative by, among other things, decreasing energy burdens, increasing parity in clean energy technology access and adoption, and increasing energy resiliency. A strategy for reaching these goals is to evaluate and validate new energy efficiency technologies in commercial buildings in underserved communities, where buildings may be older, smaller, and have deferred maintenance due to historical underinvestment. This paper assesses the proficiency of the technologies under these conditions and increases awareness of the benefits to the communities. In addition, historical redlining and past negative experiences with government and large institutions may make residents wary of participating in these field validations. Researchers, therefore, may need to spend more time building relationships and matching technologies to buildings. In this paper, we analyzed technical reports to identify common required and desired field validation building characteristics, and conducted semi-structured expert conversations to identify key stages and major themes of engaging underserved communities. Our results indicate that the benefits to both the community and energy efficiency research justify the effort. The White House. (2022). Justice40. https://www.whitehouse.gov/environmentaljustice/justice40/

ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATION↗

DOE OSTI2024

Verification, Validation, and Calibration Through a Causal Lens

While typical validation and verification approaches focus on identifying the associations between data elements using statistical and machine learning methods, the novel methods in this paper focus instead on identifying causal relationships between data elements. Statistical and machine-learning-based approaches are strictly data-driven, meaning that they provide quantitative comparison measures between data sets without explicitly considering the hypotheses behind them. This can lead to the erroneous conclusion that, if two data sets are close enough, the models that generated them are similar. In addition, when experimental and simulated data differ to an extent that fails to meet the acceptance criteria, calibration techniques are used to tweak simulation model parameters to reduce the gap between the two types of data. This produces the false expectation that a simulation model will match reality. The methods presented in this paper move away from these strictly data-driven methods for validation and calibration toward more robust, model-driven methods based on causal inference. Causal inference aims to identify the possible mechanisms that might have generated data. Thus, this analysis targets the prediction of the effects when one (or more) of the identified mechanisms are altered. There are many approaches to identify, quantify, and illustrate causal relationships. For the scope of this paper, directed graphs are employed as causal models. If the directed graph lacks cycles, it is known as a directed acyclic graph. A node in such a graph represents an observed data element while a directed edge connecting two nodes represents a causal relationship between two variables. The developed causal methods are designed to extract causal models from simulation models and experimental data. Causal models capture the causal relationships between data elements (e.g., simulated and experimental data). In this context, validation and verification are performed by comparing causal models. The proposed approach does not only inform system analysts on how a simulation model matches real-world data, but also identifies elements of the simulation model that should be revised when discrepancies between simulation and experimental data are observed. Through these causal methods, analysts can identify the portion of the model equation(s) that are behind an edge connecting two variables. Hence, once the structural differences between causal models have been determined, model calibration can occur by changing only those model parameters that impact the identified causal relationships.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Validating Mixtures of 233 U, 235 U, and 239 Pu for the Sum-of-Fractions Method

The Sum-of-Fractions method is a technique used to assure that homogeneous mixtures of fissile and fissionable isotopes are below a minimum margin of k eff or reactivity. Current work by Pacific Northwest National Laboratory examines different mixtures of 233 U, 235 U, and 239 Pu to determine critical mass limits for mixtures of transuranic actinides lacking a validation basis. To provide a validation basis for these limits, the work presented here describes the results of a sensitivity and uncertainty analysis of various mixtures of these isotopes in various concentrations moderated and reflected by light water and polyethylene. The TSUNAMI-1D sequence in the SCALE code system was used to generate sensitivity coefficients for three different concentrations of mixtures of 233 U, 235 U, and 239 Pu. The TSUNAMI-IP sequence was then used for similarity assessment (c k ) with critical benchmark experiment sensitivity data files (SDFs) from the Oak Ridge National Laboratory Verified, Archived Library of Inputs and Data and the Nuclear Energy Agency SDF database. The VADER sequence in SCALE was used for statistical testing and to generate upper subcritical limits from the data to develop a basis for validating critical mass limits.

07 ISOTOPE AND RADIATION SOURCES↗

DOE OSTI2024

Modeling and Validation of a Residential Multi-Functional Variable Refrigerant Flow Heat Pump System with Heat Recovery

To bridge the existing gap in modeling the variable refrigerant flow heat pump systems with heat recovery (VRFHR), we developed a suite of dynamic VRFHR system models in Modelica. These models are specifically tailored for residential multi-functional VRFHR (MF-VRFHR) applications, including space conditioning and domestic hot water (DHW) heating, utilizing both the TIL library for HVAC equipment and the Buildings library for thermal load calculations. The development comprises essential component models, including the newly developed heat recovery unit (HRU), along with system models that integrate the heat pump system and building envelope. These system models accommodate various operational modes such as heating-only, cooling-only, and heating-recovery (including heating-dominant and cooling-dominant) modes. Furthermore, we propose an efficient optimization-based model calibration method that identifies critical model parameters while utilizing a small amount of data obtained from either real systems or manufacturer's specifications. We demonstrate the effectiveness of these models and the proposed calibration method for a MF-VRFHR system installed in Richland, WA. The developed models are calibrated and validated using data collected under different operational modes during both heating and cooling seasons. The results show that the models capture the system dynamics and achieve high accuracy, with the coefficient of the variation of the root-mean-square-error less than 15% for variables such as outdoor unit power consumption, compressor speed, space temperature and DHW temperature. The validated models serve as a reliable representation of the MF-VRFHR system, facilitating the development and validation of optimized controls needed to realize the full benefits of integrated heat pump systems. Future research will utilize these models to develop advanced controls and optimize system performance for improved energy efficiency and demand flexibility.

Modeling, Variable refrigerant flow (VRF) systems,↗

DOE OSTI2025

EMT Model Validation of a 2 MVA PV Inverter Using Transient and Frequency-Domain Hardware Testing: Preprint

This paper presents results and new insights gained from a hardware test campaign on a 2 MVA PV inverter for validating its vendor-supplied EMT model. The test campaign was conducted using a 7 MVA grid simulator and a 2 MW PV emulator. It considered both time-domain transient tests and frequency-domain impedance scan tests. The paper highlights the inadequacy of transient tests in capturing all critical resonance modes of the inverter, and the effectiveness of the frequency scan testing in addressing this problem. The paper shows the frequency scan testing as an effective tool for EMT model validation of IBR units which can highlight inaccuracies in the EMT models that are easy to overlook when model validation is performed using only the time-domain transient tests such as voltage ride-through and phase jump tests.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2026

Simulation and Experimental Validation of an Integrated Heat Pump – Thermal Energy Storage Using a Room-Temperature Phase Change Material

As the dependence on electrical heat pumps (HPs) and intermittent renewables increases, grid strains are expected to grow. This necessitates an energy storage system to reduce the mismatch between energy supply and demand. Thus, a proposed dual-mode commercially available 14.1 kW HP was integrated with a single 22°C phase change material (PCM) thermal storage system (TES) to load-shift both cooling and heating loads. The HP-TES system was manufactured and experimentally tested using a novel test matrix based on AHRI 210/240 psychrometric conditions. Furthermore, transient dual-mode system-level HP-TES models were developed in Modelica and validated using the experimental test conditions. Base HP cooling and heating experimental tests at ambient temperatures of 35°C and −8.3°C show that the modified HP-TES maintained the rated system capacity and performance. The HP-TES discharge provided approximately 30% and 50% reductions in cooling and heating demand, respectively. The transient HP-TES models predicted system capacity and total power input for discharge and recharge operating modes within ±4% mean percentage error, and recharge power input within ±2%, with maximum errors occurring at the equipment startup. During system operation, the sources of model deviations are first-order polynomial fits of the PCM digital scanning calorimetry (DSC) data and unaccounted supercooling in the PCM during solidification. Nonetheless, the model predictions agree with the experimental tests, demonstrating the availability of robust, accurate, and validated transient models that can be used for further validation and the development of system controls.

25 ENERGY STORAGE↗

DOE OSTI2021

Ball-on-ring test validation for equibiaxial flexural strength testing of engineered ceramics

The validation of a ball-on-ring, equibiaxial flexural strength method to obtain the transverse rupture strength (TRS) of right cylindrical ceramic specimens was performed in this study. Validation of the test method was achieved using commercially available engineered high purity alumina disks and finite element (FE) model analysis. The validated fixture was then used to obtain the TRS and Weibull statistical analysis of MgO-partially stabilized zirconia (MSZ) and Y 2 O 3 -partially stabilized zirconia (YSZ) ceramic disks. TRS data for alumina, MSZ, and YSZ agreed with the TRS values reported in the literature. A statistically relevant number of samples (N > 30) for each material were tested to allow for a Weibull statistical analysis. Weibull parameters for these materials were within the expected values for engineered ceramics. The characteristic strength for alumina, MSZ, and YSZ were determined to be 289, 786, and 814 MPa, respectively. The Weibull modulus was determined between 10 and 25 for each material, which is typical of engineered ceramics. In addition, FE model results were in close agreement with experimental fracture values for the three ceramic materials tested in this study.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Experimental validation of a Kalman observer using linearized OpenFAST and a fully instrumented 1:70 model

Abstract To enable real‐time monitoring and control strategies for floating offshore wind turbines, accurate information about the state of the system is needed. This paper details the application of a Kalman filter to the UMaine VolturnUS‐S floating wind platform to provide accurate state estimates in real time using minimal system measurements. The midfidelity nonlinear simulation tool OpenFAST was used to generate the underlying linear state‐space model for the Kalman filter. This linear model and its limitations are demonstrated through comparison with experimental data collected on a 1:70 froude‐scaled model of the floating platform and tower. Using a selection of five measurements from the real system, a Kalman filter was developed to provide estimates for the remaining system states and measurements. These estimates were then validated against the experimental values collected from testing of the scale model. Validation of the Kalman filter produced accurate estimates of surge, heave, and tower base bending moment, measurements of which were not available to the Kalman filter. Performance of the Kalman filter was tested and validated over a range of sea conditions from rated wind speed to storm events and demonstrated robustness in the Kalman filter to maintain accuracy across all operating conditions despite significant error in the underlying linear model for extreme conditions.

17 WIND ENERGY↗