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NASA NTRSDate not supplied

Component-level Performance and Mass Sensitivity Analysis of NEP MW-class Power System

Nuclear electric propulsion (NEP) is a promising option towards enabling missions to Mars and is an area of interest for NASA’s Space Nuclear Propulsion project. This project is currently investigating technology development opportunities for an NEP vehicle. Physics-based modeling can be used in the early stages of technology development to gain understanding of the effects of technology and performance assumptions on the system performance and mass. This information can then inform technology maturation planning for near term development. By using a Brayton power conversion model and vehicle mass model for megawatt class NEP applications, a sensitivity analysis is performed to assess the impact of individual components’ performance on the power conversion system performance and system mass. A Monte Carlo simulation is also used to determine the variability in system mass based on uncertainty within the modeling parameters. The sensitivity analysis shows a high sensitivity to power conversion inlet temperature, compressor inlet temperature, and recuperator performance. A Monte Carlo analysis suggests a range of -10% to +15% for a 90% confidence interval on system mass based on the uncertainties in the model inputs.

Nuclear electric propulsion↗
NASA NTRS2019

Bayesian Inference and the Effects of Varying Uncertainty Models in Charring Ablator Calibration and Uncertainty Quantification Problems

The Mars Science Laboratory (MSL) vehicle utilized a heat shield constructed from NASA’s Phenolic-Impregnated Carbon Ablator (PICA) material to protect the main structure from the high enthalpy environment encountered during hypersonic atmospheric entry. During the vehicle’s descent through Martian atmosphere, multiple thermocouples embedded within the heat shield captured in-depth material temperature data that allow for studies to be conducted on current material response reconstruction tools. In the present work, material temperature data obtained from thermocouples within the MISP-4 plug (MEDLI (Mars Science Laboratory Entry, Descent, and Landing Instrument) Integrated Sensor Plug) are utilized in the calibration of Theoretical Ablative Composite for Open Testing (TACOT) model parameters in conjunction with NASA’s Porous material Analysis Toolbox (PATO) through Bayesian inference where uncertainty due to parametric, modeling, and experimental sources is simultaneously quantified. Prior to the study, a sensitivity analysis is performed through computation of the robust Sobol indices in an effort to study the relationship between input space and model response and to reduce the dimensionality of the statistical inverse problem. The Bayesian inference methodology necessitates an a-priori choice to be made for the uncertainty model for which numerous possibilities are available. Across most works, however, only basic additive or multiplicative models are utilized with pre-defined magnitudes of uncertainty based on a-priori knowledge or to-be-calibrated multipliers of static covariance matrix structures. The present effort explores the effects of informed uncertainty models, ones with temporal dependence that are simultaneously calibrated through Bayesian inference, on calibrated results for parameters that make up the uncertain input space.

Sensitivity Analysis↗
NASA NTRS2022

Assimilation of Sea Ice Thickness Derived from Cryosat-2 Along-Track Freeboard Measurements into the Met Office's Forecast Ocean Assimilation Model (FOAM)

The feasibility of assimilating sea ice thickness (SIT) observations derived from CryoSat-2 along-track measurements of sea ice freeboard is successfully demonstrated using a 3D-Var assimilation scheme, NEMOVAR, within the Met Office's global, coupled ocean–sea-ice model, Forecast Ocean Assimilation Model (FOAM). The CryoSat-2 Arctic freeboard measurements are produced by the Centre for Polar Observation and Modelling (CPOM) and are converted to SIT within FOAM using modelled snow depth. This is the first time along-track observations of SIT have been used in this way, with other centres assimilating gridded and temporally averaged observations. The assimilation leads to improvements in the SIT analysis and forecast fields generated by FOAM, particularly in the Canadian Arctic. Arctic-wide observation-minus-background assimilation statistics for 2015–2017 show improvements of 0.75 m mean difference and 0.41 m root-mean-square difference (RMSD) in the freeze-up period and 0.46 m mean difference and 0.33 m RMSD in the ice break-up period. Validation of the SIT analysis against independent springtime in situ SIT observations from NASA Operation IceBridge (OIB) shows improvement in the SIT analysis of 0.61 m mean difference (0.42 m RMSD) compared to a control without SIT assimilation. Similar improvements are seen in the FOAM 5 d SIT forecast. Validation of the SIT assimilation with independent Beaufort Gyre Exploration Project (BGEP) sea ice draft observations does not show an improvement, since the assimilated CryoSat-2 observations compare similarly to the model without assimilation in this region. Comparison with airborne electromagnetic induction (Air-EM) combined measurements of SIT and snow depth shows poorer results for the assimilation compared to the control, despite covering similar locations to the OIB and BGEP datasets. This may be evidence of sampling uncertainty in the matchups with the Air-EM validation dataset, owing to the limited number of observations available over the time period of interest. This may also be evidence of noise in the SIT analysis or uncertainties in the modelled snow depth, in the assimilated SIT observations, or in the data used for validation. The SIT analysis could be improved by upgrading the observation uncertainties used in the assimilation. Despite the lack of CryoSat-2 SIT observations available for assimilation over the summer due to the detrimental effect of melt ponds on retrievals, it is shown that the model is able to retain improvements to the SIT field throughout the summer months due to prior, wintertime SIT assimilation. This also results in regional improvements to the July modelled sea ice concentration (SIC) of 5 % RMSD in the European sector, due to slower melt of the thicker sea ice.

Emma K. Fiedler↗
NASA NTRS1984

Utilization of SAGE aerosol profiles in the analysis of Mauna Loa stratospheric lidar data

A systematic approach to analyzing lidar data collected at NOAA's Mauna Loa Observatory (MLO) was developed which relies on parameters derived from SAGE satellite extinction profile measurements to verify boundary conditions applied to analysis. The approach also provides a means of assessing the uncertainties associated with the various inputs, so that the accuracy of the analysis of the MLO lidar data is available. The stratosphere during the 1980 to 1981 period was only mildly perturbed and could be easily represented by the SAMII/SAGE background aerosol model. The MLO lidar observations collected during this period provided stratospheric optical depths with uncertainties ranging between 15% and 25%. Uncertainties in the aerosol optical model contribute errors of 3% to 4% in the computed optical depths. Most of the optical depth uncertainty is associated with the calibration assumption in which no marked improvement can be expected.

Fernald, F. G.↗
NASA NTRS1989

Pulse modulated control synthesis for a flexible spacecraft

The describing function method is employed for the nonlinear control analysis and design of a flexible spacecraft equipped with pulse modulated reaction jets. The method provides a means of characterizing the pulse modulator in terms of its gain and phase for structural mode limit cycle analysis. Although the describing function method is inherently inexact and is not widely used in practice, a new way of utilizing it for practical control design problems is presented. It is shown that the approximations inherent in the method can be accounted as a modeling uncertainty for the nonlinear control robustness analysis. The pulse modulated control system of the Intelsat 5 spacecraft is used as an example to illustrate the concept and methodology developed in the paper. The nonlinear stability margins predicted by the describing function analysis are verified from nonlinear simulations.

Anthony, Tobin C.↗
DOE OSTI2022

Reducing Uncertainty of Fielded Photovoltaic Performance (Final Technical Report)

Improved analysis and reporting of photovoltaic (PV) field performance increases the certainty of owners and financiers that systems will perform as expected. Advanced module technologies (e.g., PERC, HJT, and bifacial) introduce new degradation mechanisms and performance characteristics. The FY19-21 Reducing Uncertainty project leveraged data from the ever-increasing PV fleet to develop models and understanding of the field performance of existing and new technologies. Specifically, we accomplished: report on field performance and degradation rates for high-efficiency silicon (HJT, PERC, IBC) and more conventional technologies; developed automated analysis techniques to quantify system performance (performance ratio, energy yield) and production shortfalls (soiling, degradation, availability); refined the RdTools software toolkit to bring standard, validated analysis techniques to bear on third-party data; analyzed and reported on large datasets including Treasury data and Lawrence Berkeley National Laboratory's Utility-Scale dataset to expand the high-quality degradation-rate histogram published previously; worked with industry partners and the DuraMAT data hub to enable private parties to share and aggregate PV production data anonymously, leveraging cloud-based data analysis infrastructure and publishing on US fleet-scale performance comprising over 7GW of operating systems. (https://www.nrel.gov/pv/fleet-performance-data-initiative.html). Through our industry collaborations we have engaged in NDA-covered data transfer with twelve PV fleet owners as of January 2022, with more agreements in negotiation. Our scalable cloud-based time series database contains over 30 billion rows (20TB) of PV time series data, representing over 1700 commercial and utility-scale systems, and over 7.2 GW of DC capacity (Fig 1). Initial field performance results have been distributed in several public reports. Because our fleet composition and data quality methods are continually improving, annual updates to these results are published to our PV Fleet webpage [ https://www.nrel.gov/pv/fleet-performance-data-initiative.html ] and DuraMAT data hub [DOI: 10.21948/1842958]. Another existing dissemination channel used for observed soiling losses is a map we maintain for soiling losses. Additional products developed include a report detailing fleet-wide performance index, availability, startup loss and snow loss factors, a detailed report on the 1603 grant dataset comprising over 100,000 PV systems with failure and performance details and a utility-scale report coauthored with LBNL on 31 GW of system performance.

14 SOLAR ENERGY↗
DOE OSTI2022

Analysis of SCALE Criticality and Sensitivity Calculations for Reflected HEU Cylinders [Slides]

The SCALE code package offers multiple nuclear data libraries supporting Monte Carlo transport, with sensitivity and uncertainty methods derived from MC transport solutions. Several libraries are multigroup, which introduce bias differing by system. Previous work has shown poor S/U results in several reflector materials: ICSBEP benchmark HMF-084 was selected to analyze biases and S/U method applicability to a variety of reflectors. Prior and ongoing work found inaccuracies in CSAS and TSUNAMI results, which were further investigated utilizing the HEU-MET-FAST-084 ICSBEP critical benchmark, chosen for its geometrical simplicity and variety of reflector materials. Perturbation of reflector thickness across various reflector materials allowed for an assortment of materials is to be tested swiftly for each sequence and method. Observation was an increasing bias of MG $k_{eff}$ relative to CE, in both direction and magnitude. IFP produced extremely reliable results. >85% of CLUTCH cases were found satisfactory.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Differential methods for assessing sensitivity in biological models

Differential sensitivity analysis is indispensable in fitting parameters, understanding uncertainty, and forecasting the results of both thought and lab experiments. Although there are many methods currently available for performing differential sensitivity analysis of biological models, it can be difficult to determine which method is best suited for a particular model. In this paper, we explain a variety of differential sensitivity methods and assess their value in some typical biological models. First, we explain the mathematical basis for three numerical methods: adjoint sensitivity analysis, complex perturbation sensitivity analysis, and forward mode sensitivity analysis. We then carry out four instructive case studies. (a) The CARRGO model for tumor-immune interaction highlights the additional information that differential sensitivity analysis provides beyond traditional naive sensitivity methods, (b) the deterministic SIR model demonstrates the value of using second-order sensitivity in refining model predictions, (c) the stochastic SIR model shows how differential sensitivity can be attacked in stochastic modeling, and (d) a discrete birth-death-migration model illustrates how the complex perturbation method of differential sensitivity can be generalized to a broader range of biological models. Finally, we compare the speed, accuracy, and ease of use of these methods. We find that forward mode automatic differentiation has the quickest computational time, while the complex perturbation method is the simplest to implement and the most generalizable.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Consistent Nuclear Data Evaluations for Criticality Safety

Evaluations of nuclear data are based on statistical analysis of available experimental data and their uncertainties plus model calculations and their uncertainties. As the models are currently rather limited, the evaluations are heavily biassed toward experimental data, with the caveat that a thorough analysis is also required to understand possible discrepancies between data sets. Hence, as new experimental data become available, they are incorporated into the evaluation procedure. Recent measurements of the 233 U capture to fission cross section ratio at the Los Alamos Neutron Science Center have prompted a re-evaluation of the capture cross section in the resonance and fast regions up to 250 keV. We will discuss the challenges of including the new fast neutron experimental data in an evaluation that is consistent with the resonance region. We will also discuss our consistent evaluation procedure based on the Hauser-Feshbach statistical model for nuclear reactions and its application to the evaluations of 239 Pu and 139 La neutron-induced reactions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2004

The Mass of the Central Black Hole in the Seyfert Galaxy NGC 3783

Improved analysis of ultraviolet and optical monitoring data on the Seyfert 1 galaxy NGC 3783 provides evidence for the existence of a supermassive, (8.7 +/- 1.1) x 10(exp 6) solar mass, black hole in this galaxy. By using recalibrated spectra from the International Ultraviolet Explorer satellite and ground-based optical data, as well as refined techniques of reverberation mapping analysis, we have reduced the statistical uncertainties in the response of the emission lines to variations in the ionizing continuum. The different time lags in the emission-line responses indicate a stratification in the ionization structure of the broad-line region and are consistent with the virial relationship suggested by the analysis of similar active galaxies.

Onken, Christopher A.↗
DOE OSTI2023

Deep neural network uncertainty quantification for LArTPC reconstruction

We evaluate uncertainty quantification (UQ) methods for deep learning applied to liquid argon time projection chamber (LArTPC) physics analysis tasks. As deep learning applications enter widespread usage among physics data analysis, neural networks with reliable estimates of prediction uncertainty and robust performance against overconfidence and out-of-distribution (OOD) samples are critical for their full deployment in analyzing experimental data. While numerous UQ methods have been tested on simple datasets, performance evaluations for more complex tasks and datasets are scarce. Here we assess the application of selected deep learning UQ methods on the task of particle classification using the PiLArNet monte carlo 3D LArTPC point cloud dataset. We observe that UQ methods not only allow for better rejection of prediction mistakes and OOD detection, but also generally achieve higher overall accuracy across different task settings. We assess the precision of uncertainty quantification using different evaluation metrics, such as distributional separation of prediction entropy across correctly and incorrectly identified samples, receiver operating characteristic curves (ROCs), and expected calibration error from observed empirical accuracy. We conclude that ensembling methods can obtain well calibrated classification probabilities and generally perform better than other existing methods in deep learning UQ literature.

47 OTHER INSTRUMENTATION↗
NASA NTRS2008

Analysis of System Margins on Missions Utilizing Solar Electric Propulsion

NASA's Jet Propulsion Laboratory has conducted a study focused on the analysis of appropriate margins for deep space missions using solar electric propulsion (SEP). The purpose of this study is to understand the links between disparate system margins (power, mass, thermal, etc.) and their impact on overall mission performance and robustness. It is determined that the various sources of uncertainty and risk associated with electric propulsion mission design can be summarized into three relatively independent parameters 1) EP Power Margin, 2) Propellant Margin and 3) Duty Cycle Margin. The overall relationship between these parameters and other major sources of uncertainty is presented. A detailed trajectory analysis is conducted to examine the impact that various assumptions related to power, duty cycle, destination, and thruster performance including missed thrust periods have on overall performance. Recommendations are presented for system margins for deep space missions utilizing solar electric propulsion.

Systems Engineering↗
DOE OSTI2024

Polynomial chaos expansions on principal geodesic Grassmannian submanifolds for surrogate modeling and uncertainty quantification

In this work we introduce a manifold learning-based surrogate modeling framework for uncertainty quantification in high-dimensional stochastic systems. Our first goal is to perform data mining on the available simulation data to identify a set of low-dimensional (latent) descriptors that efficiently parameterize the response of the high-dimensional computational model. To this end, we employ Principal Geodesic Analysis on the Grassmann manifold of the response to identify a set of disjoint principal geodesic submanifolds, of possibly different dimension, that captures the variation in the data. Since operations on the Grassmann require the data to be concentrated, we propose an adaptive algorithm based on Riemannian K-means and the minimization of the sample Fréchet variance on the Grassmann manifold to identify “local” principal geodesic submanifolds that represent different system behavior across the parameter space. Polynomial chaos expansion is then used to construct a mapping between the random input parameters and the projection of the response on these local principal geodesic submanifolds. Here, the method is demonstrated on four test cases, a toy-example that involves points on a hypersphere, a Lotka-Volterra dynamical system, a continuous-flow stirred-tank chemical reactor system, and a two-dimensional Rayleigh-Bénard convection problem.

42 ENGINEERING↗
NASA NTRS1984

Reliability considerations for the total strain range version of strainrange partitioning

A proposed total strainrange version of strainrange partitioning (SRP) to enhance the manner in which SRP is applied to life prediction is considered with emphasis on how advanced reliability technology can be applied to perform risk analysis and to derive safety check expressions. Uncertainties existing in the design factors associated with life prediction of a component which experiences the combined effects of creep and fatigue can be identified. Examples illustrate how reliability analyses of such a component can be performed when all design factors in the SRP model are random variables reflecting these uncertainties. The Rackwitz-Fiessler and Wu algorithms are used and estimates of the safety index and the probablity of failure are demonstrated for a SRP problem. Methods of analysis of creep-fatigue data with emphasis on procedures for producing synoptic statistics are presented. An attempt to demonstrate the importance of the contribution of the uncertainties associated with small sample sizes (fatique data) to risk estimates is discussed. The procedure for deriving a safety check expression for possible use in a design criteria document is presented.

Wirsching, P. H.↗
NASA NTRS2004

Mars Exploration Rovers Entry, Descent, and Landing Trajectory Analysis

The Mars Exploration Rover mission successfully landed two rovers "Spirit" and "Opportunity" on Mars on January 4th and 25th of 2004, respectively. The trajectory analysis performed to define the entry, descent, and landing (EDL) scenario is described. The entry requirements and constraints are presented, as well as uncertainties used in a Monte Carlo dispersion analysis to statistically assess the robustness of the entry design to off-nominal conditions. In the analysis, six-degree-of-freedom and three-degree-of-freedom trajectory results are compared to assess the entry characteristics of the capsule. Comparison of the preentry results to preliminary post-landing reconstruction data shows that all EDL parameters were within the requirements. In addition, the final landing position for both "Spirit" and "Opportunity" were within 15 km of the predicted landing location.

Desai, Prasun N.↗
NASA NTRS2009

Aerodynamic Challenges for the Mars Science Laboratory Entry, Descent and Landing

An overview of several important aerodynamics challenges new to the Mars Science Laboratory (MSL) entry vehicle are presented. The MSL entry capsule is a 70 degree sphere cone-based on the original Mars Viking entry capsule. Due to payload and landing accuracy requirements, MSL will be flying at the highest lift-to-drag ratio of any capsule sent to Mars (L/D = 0.24). The capsule will also be flying a guided entry, performing bank maneuvers, a first for Mars entry. The system's mechanical design and increased performance requirements require an expansion of the MSL flight envelope beyond those of historical missions. In certain areas, the experience gained by Viking and other recent Mars missions can no longer be claimed as heritage information. New analysis and testing is re1quired to ensure the safe flight of the MSL entry vehicle. The challenge topics include: hypersonic gas chemistry and laminar-versus-turbulent flow effects on trim angle, a general risk assessment of flying at greater angles-of-attack than Viking, quantifying the aerodynamic interactions induced by a new reaction control system and a risk assessment of recontact of a series of masses jettisoned prior to parachute deploy. An overview of the analysis and tests being conducted to understand and reduce risk in each of these areas is presented. The need for proper modeling and implementation of uncertainties for use in trajectory simulation has resulted in a revision of prior models and additional analysis for the MSL entry vehicle. The six degree-of-freedom uncertainty model and new analysis to quantify roll torque dispersions are presented.

Schoenenberger, Mark↗
DOE OSTI2021

Rigorous constraints on three-nucleon forces in chiral effective field theory from fast and accurate calculations of few-body observables

We explore the constraints on the three-nucleon force (3NF) of chiral effective field theory (χ EFT) that are provided by bound-state observables in the A = 3 and A = 4 sectors. Our statistically rigorous analysis incorporates experimental error, computational method uncertainty, and the uncertainty due to truncation of the χ EFT expansion at next-to-next-to-leading order. A consistent solution for the 3 H binding energy, the 4 He binding energy and radius, and the 3 H β-decay rate can only be obtained if χ EFT truncation errors are included in the analysis. Here, the β-decay rate is the only one of these that yields a nondegenerate constraint on the 3NF low-energy constants, which makes it crucial for the parameter estimation. We use eigenvector continuation for fast and accurate emulation of no-core shell model calculations of the few-nucleon observables. This facilitates sampling of the posterior probability distribution, allowing us to also determine the distributions of the parameters that quantify the truncation error. We find a χ EFT expansion parameter of Q = 0.33 ± 0.06 for these observables.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
NASA NTRS2019

Modeling and Simulation Techniques for the NASA SLS Service Module Panel Separation Event; from Loosely-Coupled Euler to Fully-Coupled 6-DOF, Time-Accurate, Navier-Stokes Methodologies

An aerodynamic database has been generated for use by the Orion Multi-Purpose Crew Vehicle (MPCV) Program to analyze Service Module (SM) panel jettison from the NASA SLS vehicle. The database is a combination of CFD data for the panel aerodynamic coefficients, and MATLAB code written to query the CFD data. The Cart3D inviscid CFD flow solver was used to generate the panel aerodynamic coefficients for static panel orientations and free stream conditions that can occur during the jettison event. The MATLAB code performs the multivariate interpolation to obtain aerodynamic coefficients. The MATLAB code uses input for SM panel parameters and returns the SM panel aerodynamic force and moment coefficients for use with a Six-Degree-of-Freedom (6-DOF) motion solver to model the jettison event. This paper examines the accuracy of the sequential-static database approach by modeling the panel jettison event with a fully-coupled, time-dependent, viscous, moving-body CFD simulation. The fully-coupled simulation is obtained using the Loci/Chem unstructured Navier-Stokes CFD solver. The results show that the fully-coupled approach agrees well with the loosely-coupled database/6-DOF approach, indicating that unsteady effects are minimal for the panel jettison event. These results suggest that the database/6-DOF approach is sufficient. In addition, this paper presents the development of an uncertainty model for use in Monte Carlo analysis of the panel jettison event. Here viscous CFD simulations are obtained with Loci/Chem and compared to the inviscid CFD forces and moments. An uncertainty model based on model-form error and numerical error is presented.

Hall, Leslie H.↗