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NASA NTRSDate not supplied

Overview of Plume-Surface Interaction Data from Subscale Inert Gas Testing at NASA MSFC Test Stand 300 Vacuum Facilities

Maturation and validation of predictive modeling capabilities for plume-surface interaction, and the effects caused by the impingement of rocket engine exhaust on surface regolith, require relevant, highly characterized ground test data. The multi-phase nature of this problem poses challenges to ground testing across physical scaling, test environments and techniques, and diagnostics. NASA has developed a Physics Focused Ground Test (PFGT) of plume-surface interaction to address this need. The PFGT is a subscale, inert-gas experiment at Mars- and Lunar-relevant ambient pressure conditions that will provide critical data for model validation of cratering, ejecta, and plume physics. In this test, the ambient pressure in a vacuum chamber will be varied, along with the height of a supersonic nozzle above a surface, and the mass flow rate through the nozzle. Testing will be performed on a range of regolith simulants of varying composition and will also include instrumented impingement plate tests in place of regolith simulant to characterize gas-only plume physics. Novel high-speed visual diagnostics will capture temporal data on crater formation and ejecta dynamics, and planar laser-induced fluorescence diagnostics will capture plume structure and behavior. This paper will present an overview of the data collected during this test – for both the cratering and ejecta testing and the gas-only plume physics testing. Emphasis will be placed on trends, effects, and interactions observed in the data across the test parameter space.

Chad J. Eberhart↗

NASA NTRSDate not supplied

Validation of CFD Model Prediction of Flow Boiling Regime Transitions during LN2 Line Chilldown

Propellant storage and transfer during future long-duration missions will involve fuel depot operations in which a donor depot tank is used to fill a receiver spacecraft tank with a cryogenic propellant. Prior to the on-Orbit filling operation both the receiver tank and the transfer line must be cooled. The line chilldown process involves transition between boiling regimes in microgravity that will be quite different from their 1g ground-based counterparts. Since the cryogenic propellant itself will be used to perform the chilldown process, the time constants to cool the wall and the amount of fuel that will be used become important design considerations. In this light, the focus of the present work is to understand the flow boiling characteristics of a cryogenic fluid, namely, liquid nitrogen, during the chill-down of a transfer line using CFD modelling and simulations. The cryogenic chill-down process involves different flow boiling regimes: film boiling, transition boiling and nucleate boiling. The prediction of transition between these regimes in a CFD framework is new and challenging. The present work addresses this challenge by employing a volume-of-fluid (VOF) based methodology with Lee phase change model to predict the film boiling regime of the chill-down process in ANSYS Fluent®. The transition and nucleate boiling regimes are predicted by incorporating a sub-grid model developed by Craft Tech that accounts for bubble nucleation, growth, shedding frequency, and departure diameter. The sub-grid model is implemented into Fluent via a user-defined function for wall-fluid heat flux calculations. The sub-grid model is similar in formulation to the well-known Rensselaer Polytechnic Institute (RPI) boiling model. The model constants are tested for different operating conditions and designated values are reported. The CFD model is validated against published experimental data for liquid nitrogen chill-down of a heated stainless-steel pipe in 1g. Predicted results showing good agreement of wall temperature, rewetting temperature, and transition between film and nucleate boiling with the experimental measurements are presented and discussed.

Boiling regimes↗

NASA NTRSDate not supplied

BioSentinel: Leading the Way for Deep Space CubeSat Missions

Flagship science missions are not alone in Deep Space thanks to BioSentinel, a 6U spacecraft launched on Artemis-1. BioSentinel is one of the longest operating CubeSats beyond cislunar space. The subsystems and COTS components of the BioSentinel bus are a template for future deep space missions, and the lessons learned from over a year of operations will enable improved performance for the next missions. BioSentinel achieved its unprecedented performance for an SLS secondary payload due to preparation, planning, and a robust design. Pre-launch antenna and interface testing with both DSN and ESA confirmed command and data pathways and allowed for operational flexibility in the critical early hours post-deployment. Mission Operations simulations prior to launch identified potential risks and primed operators to respond in flight, preparing the team to react quickly to successfully detumble the spacecraft and enter a power-positive state. The spacecraft would not have survived without the inclusion of the trailblazing 3D-printed composite cold gas propulsion system. The non-standard tank geometry enabled efficient use of the limited space available in the CubeSat, as well as the capability to detumble the spacecraft and manage momentum, while providing sufficient margin to execute potential delta-V maneuvers. The Iris radio has operated for over 18 months with no significant issues. Initial Iris performance estimates have been accurate throughout the mission. BioSentinel continues to collect data on thermal conditions and to validate our performance models with real-world knowledge. We have received exemplary support from our DSN partners. Following the conclusion of the primary science mission, the Linear Energy Transfer (LET) Spectrometer continued to collect solar and galactic radiation data from its location in heliocentric orbit. The free space dataset offered by the BioSentinel LET is a valuable source of data for model validation and future mission planning. As the spacecraft travels farther from Earth it is poised to provide longitudinally distributed measurements of solar particle events during solar maximum. The lessons learned from BioSentinel suggest key areas to enhance performance. The ability to upload modified flight software can increase the stability of memory management. Additional heaters in the propulsion system design have already proven successful on the Starling mission. Streamlining mission operations can reduce costs, increase data return, and better utilize DSN time. Enhancements such as these will facilitate reliable, long-duration deep space exploration using the proven BioSentinel 6U CubeSat bus.

BioSentinel↗

NASA NTRS2017

Model-Based Thermal System Design Optimization for the James Webb Space Telescope

Spacecraft thermal model validation is normally performed by comparing model predictions with thermal test data and reducing their discrepancies to meet the mission requirements. Based on thermal engineering expertise, the model input parameters are adjusted to tune the model output response to the test data. The end result is not guaranteed to be the best solution in terms of reduced discrepancy and the process requires months to complete. A model-based methodology was developed to perform the validation process in a fully automated fashion and provide mathematical bases to the search for the optimal parameter set that minimizes the discrepancies between model and data. The methodology was successfully applied to several thermal subsystems of the James Webb Space Telescope (JWST). Global or quasiglobal optimal solutions were found and the total execution time of the model validation process was reduced to about two weeks. The model sensitivities to the parameters, which are required to solve the optimization problem, can be calculated automatically before the test begins and provide a library for sensitivity studies. This methodology represents a crucial commodity when testing complex, large-scale systems under time and budget constraints. Here, results for the JWST Core thermal system will be presented in detail.

Cataldo, Giuseppe↗

NASA NTRS2018

ST7 Disturbance Reduction System (DRS) Colloid Micronewton Thruster Performance and Control Algorithm Model Simulation Validation in Flight

Colloid Micronewton Thrusters (CMNT) were flight demonstrated for the first time on the ST7Disturbance Reduction System (DRS) payload on the European Space Agency (ESA) Laser Interferometer Space Antenna (LISA) Pathfinder spacecraft for attitude and drag-free spacecraft control. LISA Pathfinder was a technology demonstration mission for ESA’s LISA gravitational wave observatory, currently in Phase A with a launch date of 2034. The DRS included the Integrated Avionics Unit (IAU), eight Colloid Micronewton Thrusters (CMNT), Dynamic Control Software (DCS) and Flight Software (FSW). The CMNT technology met performance requirements operating at 5-30 µN of thrust with ≤0.1 µN resolution and ≤0.1 µN/Hz thrust noise to deliver the required nanometer-level precision spacecraft control measured by the gravitational reference sensor (GRS) in the ESA LISA Technology Package (LTP). The performance of seven of the CMNT in flight was consistent with ground test results. The colloid thruster performance model of thrust and thrust noise as a function of operational parameters (i.e. beam current, voltage, temperature, etc.) was validated in flight over a wide range of conditions. A model and simulation of the thruster control algorithm was developed and validated with flight data to predict thrust noise. This capability is important because it is considered to be a significant source of position noise on the spacecraft and, therefore, the acceleration noise on the test masses, which provide the gravity wave measurements. The CMNT thruster model data and validation with LISA Pathfinder/ST7-DRS flight experiments are discussed in this paper.

Hruby, Vlad↗

NASA NTRS2008

Similarity Metrics for Closed Loop Dynamic Systems

To what extent and in what ways can two closed-loop dynamic systems be said to be "similar?" This question arises in a wide range of dynamic systems modeling and control system design applications. For example, bounds on error models are fundamental to the controller optimization with modern control design methods. Metrics such as the structured singular value are direct measures of the degree to which properties such as stability or performance are maintained in the presence of specified uncertainties or variations in the plant model. Similarly, controls-related areas such as system identification, model reduction, and experimental model validation employ measures of similarity between multiple realizations of a dynamic system. Each area has its tools and approaches, with each tool more or less suited for one application or the other. Similarity in the context of closed-loop model validation via flight test is subtly different from error measures in the typical controls oriented application. Whereas similarity in a robust control context relates to plant variation and the attendant affect on stability and performance, in this context similarity metrics are sought that assess the relevance of a dynamic system test for the purpose of validating the stability and performance of a "similar" dynamic system. Similarity in the context of system identification is much more relevant than are robust control analogies in that errors between one dynamic system (the test article) and another (the nominal "design" model) are sought for the purpose of bounding the validity of a model for control design and analysis. Yet system identification typically involves open-loop plant models which are independent of the control system (with the exception of limited developments in closed-loop system identification which is nonetheless focused on obtaining open-loop plant models from closed-loop data). Moreover the objectives of system identification are not the same as a flight test and hence system identification error metrics are not directly relevant. In applications such as launch vehicles where the open loop plant is unstable it is similarity of the closed-loop system dynamics of a flight test that are relevant.

Whorton, Mark S.↗

NASA NTRSDate not supplied

Aeroacoustic Simulations of the High-Lift Common Research Model and Validation with Experiment

Aerodynamic and acoustic data from unsteady numerical simulations of the High-Lift Common Research Model are compared with experimental measurements from an open-jet wind tunnel test of a 10\-scale model. Time-averaged surface pressure data is in good agreement for all of the configurations evaluated during the test. Unsteady surface pressure spectra from the leading-edge slat and the nose of the main element are presented, demonstrating that the highest levels are associated with the wakes of slat brackets. At these locations the simulations and experiment match reasonably well at low enough frequencies (f < 10 kHz based on the model scale) before excessive numerical dissipation leads to a rapid roll off in the predicted frequency spectra. The agreement is inconsistent at other locations on the slat and main-element surfaces, where the pressure fluctuation levels are lower. Noise predictions using a synthetic microphone array are compared with equivalent experimental results, and the changes in levels predicted between three configurations are similar to those measured. However, some details of the noise predictions are inconsistent with the experiment, and the use of solid- instead of porous-surface data for the acoustic processing of the simulations likely contributes to the discrepancies. All of the simulations were completed before the test, and, despite some shortcomings, they provided valuable insight into the aeroacoustic performance of the model that greatly aided test planning and execution. Hence, the post-test comparisons presented here allow an assessment of the predictive methodology in the context of a realistic high-lift configuration.

High-lift↗

DOE OSTI2019

Modeling and Validation of Irradiation Damage in Ni-based Alloys for Long-Term LWR Applications (Final Report)

As light water reactor (LWR) plant lives are extended, the need for predictive modeling tools for materials degradation increase in order to ensure safe operation and plan for component replacements. The Grizzly code, which is built on the MOOSE multi-physics simulation environment, is being developed for exactly this purpose. To extend Grizzly to include capabilities for modeling Ni-based alloys, we propose a US/UK integrated program to address thermal and irradiation-induced transformations mechanisms of Alloys 690 and 625. Alloy 690 is widely used in existing LWR plants due to its superior stress corrosion cracking (SCC) resistance compared to Alloy 600. Alloy 625 is used in more limited applications but offers the benefits of both high strength (in the aged condition) and corrosion/SCC resistance. Research has shown that both alloys can undergo phase changes due to thermal or irradiation exposure. In the precipitation-hardened condition, Alloy 625 “softens” during neutron irradiation as the strengthening precipitates decompose and metastable precipitates form. However, the nature and rates of these transformations as a function of exposure conditions are not well understood. Similarly, the effects of these thermal and irradiation-induced microstructural changes on mechanical properties require evaluation. The proposed program combines thermal and irradiation experiments, mechanical testing, microstructural characterization using state-of-the art analytical techniques, atomistic modeling, micro-and macro-scale modeling via Grizzly. This multi-pronged approach yields several benefits: 1) atomistic scale models capture the physics of the mechanisms of phase transformations, which can be generalized to other systems, 2) the modeling results (from atomistic to continuum) will be validated experimentally to ensure the predictive aspect, 3) the microstructure/property relationships captured with mechanical testing provides information at the engineering scale that is needed to validate the integration of the proposed new capability into Grizzly

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2017

PyForecastTools

This package provides a basic toolkit for model validation and forecast verification, implemented in Python. The code is designed to aid model validation tasks for users of the standard scientific python stack. Functions and classes are provided to calculate a broad range of metrics for continuous and categorical predictions.

Morley, Steven↗

NASA NTRS1992

Reactant conversion in homogeneous turbulence: Mathematical modeling, computational validations and practical applications

Closed form analytical expressions are obtained for predicting the limited rate of reactant conversion in a binary reaction of the type F + rO yields (1 + r) Product in unpremixed homogeneous turbulence. These relations are obtained by means of a single point Probability Density Function (PDF) method based on the Amplitude Mapping Closure. It is demonstrated that with this model, the maximum rate of the reactants' decay can be conveniently expressed in terms of definite integrals of the Parabolic Cylinder Functions. For the cases with complete initial segregation, it is shown that the results agree very closely with those predicted by employing a Beta density of the first kind for an appropriately defined Shvab-Zeldovich scalar variable. With this assumption, the final results can also be expressed in terms of closed form analytical expressions which are based on the Incomplete Beta Functions. With both models, the dependence of the results on the stoichiometric coefficient and the equivalence ratio can be expressed in an explicit manner. For a stoichiometric mixture, the analytical results simplify significantly. In the mapping closure, these results are expressed in terms of simple trigonometric functions. For the Beta density model, they are in the form of Gamma Functions. In all the cases considered, the results are shown to agree well with data generated by Direct Numerical Simulations (DNS). Due to the simplicity of these expressions and because of nice mathematical features of the Parabolic Cylinder and the Incomplete Beta Functions, these models are recommended for estimating the limiting rate of reactant conversion in homogeneous reacting flows. These results also provide useful insights in assessing the extent of validity of turbulence closures in the modeling of unpremixed reacting flows. Some discussions are provided on the extension of the model for treating more complicated reacting systems including realistic kinetics schemes and multi-scalar mixing with finite rate chemical reactions in more complex configurations.

Madnia, C. K.↗

NASA NTRS1974

Modifications to the steady-state 41-node thermoregulatory model including validation of the respiratory and diffusional water loss equations

After the simplified version of the 41-Node Stolwijk Metabolic Man Model was implemented on the Sigma 3 and UNIVAC 1110 computers in batch mode, it became desirable to make certain revisions. First, the availability of time-sharing terminals makes it possible to provide the capability and flexibility of conversational interaction between user and model. Secondly, recent physiological studies show the need to revise certain parameter values contained in the model. Thirdly, it was desired to make quantitative and accurate predictions of evaporative water loss for humans in an orbiting space station. The result of the first phase of this effort are reported.

Source record↗

NASA NTRS2018

Melt Pond Conditions on Declining Arctic Sea Ice Over 1979-2016: Model Development, Validation, and Results

A melt pond (MP) distribution equation has been developed and incorporated into the Marginal Ice-Zone Modeling and Assimilation System to simulate Arctic MPs and sea ice over 1979-2016. The equation differs from previous MP models and yet benefits from previous studies for MP parameterizations as well as a range of observations for model calibration. Model results show higher magnitude of MP volume per unit ice area and area fraction in most of the Canada Basin and the East Siberian Sea and lower magnitude in the central Arctic. This is consistent with Moderate Resolution Imaging Spectroradiometer observations, evaluated with Measurements of Earth Data for Environmental Analysis (MEDEA) data, and closely related to top ice melt per unit ice area. The model simulates a decrease in the total Arctic sea ice volume and area, owing to a strong increase in bottom and lateral ice melt. The sea ice decline leads to a strong decrease in the total MP volume and area. However, the Arctic-averaged MP volume per unit ice area and area fraction show weak, statistically insignificant downward trends, which is linked to the fact that MP water drainage per unit ice area is increasing. It is also linked to the fact that MP volume and area decrease relatively faster than ice area. This suggests that overall the actual MP conditions on ice have changed little in the past decades as the ice cover is retreating in response to Arctic warming, thus consistent with the Moderate Resolution Imaging Spectroradiometer observations that show no clear trend in MP area fraction over 2000-2011.

sea ice↗

DOE OSTI2018

Updated Verification and Validation Assessment for VERA

The Virtual Environment for Reactor Applications (VERA) code suite is assessed in terms of capability and credibility against the Consortium for Advanced Simulation of Light Water Reactors (CASL) Verification and Validation Plan (presented herein) in the context of three selected challenge problems: CRUD-Induced Power Shift (CIPS), Departure from Nucleate Boiling (DNB), and Pellet-Clad Interaction (PCI). Capability refers to evidence of required functionality for capturing phenomena of interest while credibility refers to the evidence that provides confidence in the calculated results. For this assessment, each challenge problem defines a set of phenomenological requirements against which the VERA software is assessed. This approach, in turn, enables the focused assessment of only those capabilities relevant to the challenge problem. The evaluation of VERA against the challenge problem requirements represents a capability assessment. The mechanism for assessment is the Sandia-developed Predictive Capability Maturity Model (PCMM) that, for this assessment, evaluates VERA on 8 major criteria: (1) Representation and Geometric Fidelity, (2) Physics and Material Model Fidelity, (3) Software Quality Assurance and Engineering, (4) Code Verification, (5) Solution Verification, (6) Separate Effects Model Validation, (7) Integral Effects Model Validation, and (8) Uncertainty Quantification. For each attribute, a maturity score from zero to three is assigned in the context of each challenge problem. The evaluation of these eight elements constitutes the credibility assessment for VERA.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2019

Updated Verification and Validation Assessment for VERA

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Non-Equilibrium Law-of-the-wall Modeling for Improved Heat Transfer Predictions: Model Development and Validation.

Abstract not provided.

Perini, Federico↗

NASA NTRS2005

Linear Multivariable Regression Models for Prediction of Eddy Dissipation Rate from Available Meteorological Data

Linear multivariable regression models for predicting day and night Eddy Dissipation Rate (EDR) from available meteorological data sources are defined and validated. Model definition is based on a combination of 1997-2000 Dallas/Fort Worth (DFW) data sources, EDR from Aircraft Vortex Spacing System (AVOSS) deployment data, and regression variables primarily from corresponding Automated Surface Observation System (ASOS) data. Model validation is accomplished through EDR predictions on a similar combination of 1994-1995 Memphis (MEM) AVOSS and ASOS data. Model forms include an intercept plus a single term of fixed optimal power for each of these regression variables; 30-minute forward averaged mean and variance of near-surface wind speed and temperature, variance of wind direction, and a discrete cloud cover metric. Distinct day and night models, regressing on EDR and the natural log of EDR respectively, yield best performance and avoid model discontinuity over day/night data boundaries.

MCKissick, Burnell T.↗

DOE OSTI2021

Dispersive shell pellet injection modeling and validation for DIII-D disruption mitigation

Dispersive shell pellet injection for disruption mitigation on the DIII-D tokamak is modeled with the 3D MHD code NIMROD. The simulations attempt to reproduce as closely as possible a pellet velocity scan that was performed on the DIII-D tokamak [Hollmann, et al., Phys. Rev. Lett. 122, 65001 (2019)]. This scan involved injecting a hollow diamond shell filled with boron dust that is released in the core of the plasma. Trends that are reproduced in the simulation include improved mitigation, reduced plasma current spike amplitude, and increased likelihood of hot-tail runaway electron production with increased pellet speed. The simulations provide additional physics insight into these findings. Limitations of the present model and requirements for a predictive model are discussed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2005

The contribution of CEOP data to the understanding and modeling of monsoon systems

CEOP has contributed and will continue to provide integrated data sets from diverse platforms for better understanding of the water and energy cycles, and for validating models. In this talk, I will show examples of how CEOP has contributed to the formulation of a strategy for the study of the monsoon as a system. The CEOP data concept has led to the development of the CEOP Inter-Monsoon Studies (CIMS), which focuses on the identification of model bias, and improvement of model physics such as the diurnal and annual cycles. A multi-model validation project focusing on diurnal variability of the East Asian monsoon, and using CEOP reference site data, as well as CEOP integrated satellite data is now ongoing. Similar validation projects in other monsoon regions are being started. Preliminary studies show that climate models have difficulties in simulating the diurnal signals of total rainfall, rainfall intensity and frequency of occurrence, which have different peak hours, depending on locations. Further more model diurnal cycle of rainfall in monsoon regions tend to lead the observed by about 2-3 hours. These model bias offer insight into lack of, or poor representation of key components of the convective,and stratiform rainfall. The CEOP data also stimulated studies to compare and contrasts monsoon variability in different parts of the world. It was found that seasonal wind reversal, orographic effects, monsoon depressions, meso-scale convective complexes, SST and land surface land influences are common features in all monsoon regions. Strong intraseasonal variability is present in all monsoon regions. While there is a clear demarcation of onset, breaks and withdrawal in the Asian and Australian monsoon region associated with climatological intraseasonal variability, it is less clear in the American and Africa monsoon regions. The examination of satellite and reference site data in monsoon has led to preliminary model experiments to study the impact of aerosol on monsoon variability. I will show examples of how the study of the dynamics of aerosol-water cycle interactions in the monsoon region, can be best achieved using the CEOP data and modeling strategy.

Lau, William K. M.↗