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DOE OSTI2025

Using Simulation to Interpret LArS's Results

Scintillation light analysis in liquid argon based neutrino detectors is restrained in capability due to uncertainty in fundamental constants critical to the analysis process. One such property is the Rayleigh scattering length of liquid argon. In the fall of 2023, the TallBo cryostat, located in the Noble Liquid Testing Facility (NLTF) at Fermilab, was used to study the scattering length of liquid argon in the Liquid Argon Scattering (LArS) experiment. Due to systematic errors unknown during measurement analysis, LArS s measurements were quite uncertain. By simulating the LArS experiment, we found that the downturn in detector count rate as a function of liquid argon height at low heights was caused by a misplaced silicon photo multiplier (SiPM). With concentrated effort, we may be able to successfully correct this effect by understanding the relationship between the specified Rayleigh scattering length and the measured attenuation length. With this information and further progression in analysis, we may be able to extract corrected measurements from the LArS data and attain a tangible experimental measurement of the scattering length of liquid argon.

Breaux, Auto D. [Tulane U.]↗

DOE OSTI2025

Identification of the Liquid Argon Scattering Experimental Discrepancies Using Simulation

Scintillation light analysis in liquid argon based neutrino detectors is restrained in capability due to uncertainty in fundamental constants critical to the analysis process. One such property is the Rayleigh scattering length of liquid argon. In the fall of 2023, the TallBo cryostat, located in the Proton Assembly Building at Fermilab, was used to study the scattering length of liquid argon in the Liquid Argon Scattering (LArS) experiment. Due to systematic errors unknown during measurement analysis, LArS’s measurements were quite uncertain. By simulating the LArS experiment, we found that the downturn in detector count rate as a function of liquid argon height at low heights was caused by a misplaced photo multiplier. With concentrated effort, we may be able to successfully correct this effect by understanding the relationship between the specified Rayleigh scattering length and the measured attenuation length. With this information and further progression in analysis, we may be able to extract corrected measurements from the LArS data and attain a tangible experimental measurement of the scattering length of liquid argon.

Breaux, Auto D. [Tulane U.; Fermilab]↗

NASA NTRS1993

A comparative study of multivariable robustness analysis methods as applied to integrated flight and propulsion control

Three multivariable robustness analysis methods are compared and contrasted. The focus of the analysis is on system stability and performance robustness to uncertainty in the coupling dynamics between two interacting subsystems. Of particular interest is interacting airframe and engine subsystems, and an example airframe/engine vehicle configuration is utilized in the demonstration of these approaches. The singular value (SV) and structured singular value (SSV) analysis methods are compared to a method especially well suited for analysis of robustness to uncertainties in subsystem interactions. This approach is referred to here as the interacting subsystem (IS) analysis method. This method has been used previously to analyze airframe/engine systems, emphasizing the study of stability robustness. However, performance robustness is also investigated here, and a new measure of allowable uncertainty for acceptable performance robustness is introduced. The IS methodology does not require plant uncertainty models to measure the robustness of the system, and is shown to yield valuable information regarding the effects of subsystem interactions. In contrast, the SV and SSV methods allow for the evaluation of the robustness of the system to particular models of uncertainty, and do not directly indicate how the airframe (engine) subsystem interacts with the engine (airframe) subsystem.

Schierman, John D.↗

NASA NTRSDate not supplied

Sensitivity Analysis of the Human Research Program’s Impact 1.0 Model

Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Leave One Out (LOO) are methods of conducting sensitivity analysis on non-linear simulation models like the IMPACT Model. The PRCC method estimates the sensitivity using partial correlation of the ranks of the generated input values to each generated output value. The “partial” part is due to the adjustments made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. LOO removes a medical condition from test suite and calculates the change in the outcome. This is used to identify the influence of the condition input in the model The inputs to the sensitivity procedures include the number of occurrences of each of the one hundred plus IMPACT medical conditions generated over the simulations, and the IMPACT outputs from the MEDPRAT mathematical model. The outputs total task time lost (TTL), number of return to definitive care (RTDC), and number of loss of crew lives (LOCL). The IMPACT team will report the results of using PRCC and LOO on IMPACT 1.0. Tornado plots will assist in the visualization of the condition-related input sensitivities to each of the main outcomes. The outcomes of this sensitivity analysis will drive review focus by identifying conditions where changes in uncertainty, and input values could drive changes in overall model output uncertainty. These efforts are an integral part of the overall verification, validation, and credibility review of IMPACT 1.0.

Sensitivity Anaylsis↗

DOE OSTI2020

ECP Software Technology Capability Assessment Report

The Exascale Computing Project Software Technology (ECP ST) focus area represents the key bridge between Exascale systems and the scientists developing applications that will run on those platforms. ECP offers a unique opportunity to build a coherent set of software (often referred to as the "software stack") that will allow application developers to maximize their ability to write highly parallel applications, targeting multiple Exascale architectures with runtime environments that will provide high performance and resilience. But applications are only useful if they can provide scientific insight, and the unprecedented data produced by these applications require a complete analysis work ow that includes new technology to scalably collect, reduce, organize, curate, and analyze the data into actionable decisions. This requires approaching scientific computing in a holistic manner, encompassing the entire user workflow - from conception of a problem, setting up the problem with validated inputs, performing high-fidelity simulations, to the application of uncertainty quantification to the final analysis. The software stack plan defined here aims to address all of these needs by extending current technologies to Exascale where possible, by performing the research required to conceive of new approaches necessary to address unique problems where current approaches will not suffice, and by deploying high-quality and robust software products on the platforms developed in the Exascale systems project. The ECP ST portfolio has established a set of interdependent projects that will allow for the research, development, and delivery of a comprehensive software stack,

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Code and Data for "Quantifying Uncertainties in Greenhouse Gas Savings and Mitigation Costs with Cellulosic Biofuels"

Use of cellulosic biofuels from non-feedstocks are modeled using the BEPAM (Biofuel and Environmental Policy Analysis Model) model to quantifying the uncertainties about induced land use change effects, net greenhouse gas saving potential, and economic costs. The code is in GAMS, general algebraic modeling language. NOTE: Column 3 is titled "BAU" in "merged_BAU.gdx", "merged_RFS.gdx", and "merged_CEM.gdx", but contains "RFS" data in "merged_RFS.gdx" and "CEM" data in "merged_CEM.gdx".

BEPAM↗

NASA NTRS2001

Assessment of the Contribution of the Atmosphere to Uncertainties in Normalized Water-Leaving Radiance: A Combined Modeling and Data Analysis Approach

Our research for the Sensor Intercomparison and Merger for Biological and Interdisciplinary Oceanic Studies (SIMBIOS) program has been focused on modeling and simulation studies as well as the development of atmospheric correction algorithms. Based on our original proposal and discussions at the SIMBIOS team meetings and workshops, the objectives of our research can be summarized as follows: (1) Use our radiative transfer model for the coupled atmosphere-ocean system to simulate the radiation field at arbitrary levels and in any desired direction in the atmosphere and ocean so as to provide a firm connection between the signal received by the satellite sensor and by a sensor looking down into the water column just above the surface and just below it; (2) Use the simulations to quantify the influence of atmospheric aerosols on the water-leaving radiance, and to quantify the error in the water-leaving radiance as a function of uncertainties in the aerosol optical properties, mass loading and vertical extent; (3) Use the model simulations in conjunction with validation measurements taken by other SIMBIOS investigators (for satellite overpasses) to assess our understanding of the radiative transfer process in the coupled atmosphere-ocean column, and to examine the extent to which the model provides a realistic prediction of simultaneously measured in situ water-leaving radiance and the radiance received by the satellite sensor; (4) Modify and improve an existing atmospheric correction algorithm, based on the work above, as needed by constructing new look-up tables that include scattering by ocean particles; and (5) Carry out approaches to developing an atmospheric correction algorithm for ocean color imagery with strongly absorbing aerosols.

Stamnes, Knut↗

NASA NTRS1990

Probabilistic simulation of uncertainties in thermal structures

Development of probabilistic structural analysis methods for hot structures is a major activity at Lewis Research Center. It consists of five program elements: (1) probabilistic loads; (2) probabilistic finite element analysis; (3) probabilistic material behavior; (4) assessment of reliability and risk; and (5) probabilistic structural performance evaluation. Recent progress includes: (1) quantification of the effects of uncertainties for several variables on high pressure fuel turbopump (HPFT) blade temperature, pressure, and torque of the Space Shuttle Main Engine (SSME); (2) the evaluation of the cumulative distribution function for various structural response variables based on assumed uncertainties in primitive structural variables; (3) evaluation of the failure probability; (4) reliability and risk-cost assessment, and (5) an outline of an emerging approach for eventual hot structures certification. Collectively, the results demonstrate that the structural durability/reliability of hot structural components can be effectively evaluated in a formal probabilistic framework. In addition, the approach can be readily extended to computationally simulate certification of hot structures for aerospace environments.

Chamis, Christos C.↗

NASA NTRS1990

Probabilistic simulation of uncertainties in thermal structures

Development of probabilistic structural analysis methods for hot structures is a major activity at NASA-Lewis, and consists of five program elements: (1) probabilistic loads, (2) probabilistic finite element analysis, (3) probabilistic material behavior, (4) assessment of reliability and risk, and (5) probabilistic structural performance evaluation. Attention is given to quantification of the effects of uncertainties for several variables on High Pressure Fuel Turbopump blade temperature, pressure, and torque of the Space Shuttle Main Engine; the evaluation of the cumulative distribution function for various structural response variables based on assumed uncertainties in primitive structural variables; evaluation of the failure probability; reliability and risk-cost assessment; and an outline of an emerging approach for eventual hot structures certification. Collectively, the results demonstrate that the structural durability/reliability of hot structural components can be effectively evaluated in a formal probabilistic framework. In addition, the approach can be readily extended to computationally simulate certification of hot structures for aerospace environments.

Chamis, C. C.↗

DOE OSTI2021

A predictive discrete-continuum multiscale model of plasticity with quantified uncertainty

Multiscale models of materials, consisting of upscaling discrete simulations to continuum models, are unique in their capability to simulate complex materials behavior. The fundamental limitation in multiscale models is the presence of uncertainty in the computational predictions delivered by them. In this work, a sequential multiscale model has been developed, incorporating discrete dislocation dynamics (DDD) simulations and a strain gradient plasticity (SGP) model to predict the size effect in plastic deformations of metallic micro-pillars. The DDD simulations include uniaxial compression of micro-pillars with different sizes and over a wide range of initial dislocation densities and spatial distributions of dislocations. An SGP model is employed at the continuum level that accounts for the size-dependency of flow stress and hardening rate. Sequences of uncertainty analyses have been performed to assess the predictive capability of the multiscale model. The variance-based global sensitivity analysis determines the effect of parameter uncertainty on the SGP model prediction. The multiscale model is then constructed by calibrating the continuum model using the data furnished by the DDD simulations. A Bayesian calibration method is implemented to quantify the uncertainty due to microstructural randomness in discrete dislocation simulations (density and spatial distribution of dislocations) on the macroscopic continuum model prediction (size effect in plastic deformation). Here, the outcomes of this study indicate that the discrete-continuum multiscale model can accurately simulate the plastic deformation of micro-pillars, despite the significant uncertainty in the DDD results. Additionally, depending on the macroscopic features represented by the DDD simulations, the SGP model can reliably predict the size effect in plasticity responses of the micropillars with below 10% of error.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Bayesian analysis of nucleon-nucleon scattering data in pionless effective field theory

We perform Bayesian model calibration of two-nucleon (NN) low-energy constants (LECs) appearing in an NN interaction based on pionless effective field theory (πEFT). The calibration is carried out for potentials constructed using naive dimensional analysis in NN relative momenta (p) up to next-to-leading order [NLO, O(p 2 )] and next-to-next-to-next-to-leading order [N3LO, O(p 4 )]. We consider two classes of pionless πEFT potential: one that acts in all partial waves and another that is dominated by s-wave physics. The two classes produce broadly similar results for calibrations to NN data up to E lab = 5 MeV. Our analysis accounts for the correlated uncertainties that arise from the truncation of the pionless πEFT. We simultaneously estimate both the πEFT LECs and the parameters that quantify the truncation error. This permits the first quantitative estimates of the pionless πEFT breakdown scale, Λ b : the 95% intervals are Λ b ∈[50.11,63.03] MeV at NLO and Λ b ∈[72.27,88.54] MeV at N3LO. Furthermore, invoking naive dimensional analysis for the NN potential, therefore, does not lead to consistent results across orders in pionless πEFT. This exemplifies the possible use of Bayesian tools to identify inconsistencies in a proposed EFT power counting.

Bayesian methods↗

NASA NTRS1983

Thermal-structural analysis of large space structures - An assessment of recent advances

Recent advances in modeling, analyzing, and understanding the thermal-structural responses of large space structures are reviewed, and uncertainties in the thermal-structural analysis are identified. Typical heat-load, thermal, and structural analyses requirements for large space structures are discussed using a design for a future large spacecraft as an example. The current status of heating, thermal, and structural analyses is then reviewed, and computer programs used in research and design are discussed. The need to develop efficient methods for integrating the interdisciplinary analyses is emphasized.

Thornton, E. A.↗

NASA NTRS2012

Changes in Extratropical Storm Track Cloudiness 1983-2008: Observational Support for a Poleward Shift

Climate model simulations suggest that the extratropical storm tracks will shift poleward as a consequence of global warming. In this study the northern and southern hemisphere storm tracks over the Pacific and Atlantic ocean basins are studied using observational data, primarily from the International Satellite Cloud Climatology Project, ISCCP. Potential shifts in the storm tracks are examined using the observed cloud structures as proxies for cyclone activity. Different data analysis methods are employed, with the objective to address difficulties and uncertainties in using ISCCP data for regional trend analysis. In particular, three data filtering techniques are explored; excluding specific problematic regions from the analysis, regressing out a spurious viewing geometry effect, and excluding specific cloud types from the analysis. These adjustments all, to varying degree, moderate the cloud trends in the original data but leave the qualitative aspects of those trends largely unaffected. Therefore, our analysis suggests that ISCCP data can be used to interpret regional trends in cloudiness, provided that data and instrumental artefacts are recognized and accounted for. The variation in magnitude between trends emerging from application of different data correction methods, allows us to estimate possible ranges for the observational changes. It is found that the storm tracks, here represented by the extent of the midlatitude-centered band of maximum cloud cover over the studied ocean basins, experience a poleward shift as well as a narrowing over the 25 year period covered by ISCCP. The observed magnitudes of these effects are larger than in current generation climate models (CMIP3). The magnitude of the shift is particularly large in the northern hemisphere Atlantic. This is also the one of the four regions in which imperfect data primarily prevents us from drawing firm conclusions. The shifted path and reduced extent of the storm track cloudiness is accompanied by a regional reduction in total cloud cover. This decrease in cloudiness can primarily be ascribed to low level clouds, whereas the upper level cloud fraction actually increases, according to ISCCP. Independent satellite observations of radiative fluxes at the top of the atmosphere are consistent with the changes in total cloud cover. The shift in cloudiness is also supported by a shift in central position of the mid-troposphere meridional temperature gradient. We do not find support for aerosols playing a significant role in the satellite observed changes in cloudiness. The observed changes in storm track cloudiness can be related to local cloud-induced changes in radiative forcing, using ERBE and CERES radiative fluxes. The shortwave and the longwave components are found to act together, leading to a positive (warming) net radiative effect in response to the cloud changes in the storm track regions, indicative of positive cloud feedback. Among the CMIP3 models that simulate poleward shifts in all four storm track areas, all but one show decreasing cloud amount on a global mean scale in response to increased CO2 forcing, further consistent with positive cloud feedback. Models with low equilibrium climate sensitivity to a lesser extent than higher-sensitivity models simulate a poleward shift of the storm tracks.

Bender, Frida A-M.↗

NASA NTRS2020

Design and Analysis of Buckling-Critical Large-Scale Sandwich Composite Cylindrical Test Articles

It has long been established in the literature that the buckling response of thin-shell structures can be very sensitive to the presence of small geometric and loading imperfections. The Shell Buckling Knockdown Factor Project (SBKF) was established by the NASA Engineering and Safety Center (NESC) to develop analysis-based shell buckling design recommendations for stiffened-metallic and composite launch-vehicle shell structures. Large-scale buckling tests were used to validate the modeling and analysis methods applied in developing these analysis-based recommendations. Herein, the test article design methodology for 8-ft-diameter, honeycomb-core sandwich composite cylinder validation tests is discussed and cylinder designs are presented. In this methodology, first, the sandwich composite design space was defined using several nondimensional parameters, and the desired test article design space was determined by examining the designs of launch-vehicle cylinder structures. Essentially all test article designs within certain design parameters were generated and then downselected based on simple closed-form failure calculations and the nondimensional design-space parameters. Four of these designs that spanned a significant portion of the design space of interest and had global buckling as the first predicted failure mode were selected and subjected to higher-fidelity finite element analyses (FEAs): shell-element-based analyses, axisymmetric-element-based analyses, and global-local analyses. The analysis flow discussed in this report supported the design objective. As the analysis flow progressed, designs were downselected so the fidelity of the analysis methods, and consequently their computational cost and accuracy, was increased. The selection of the FEA types created an analysis framework where particular methods complemented each other and reduced the uncertainty of the predicted test article responses. The analysis results are illustrated using several designs when the computationally expeditious closed-form analysis stage is discussed. Once this stage is complete, the higher-fidelity FEA types are illustrated using one selected detailed test article design. Both perfect and imperfect test article geometries were considered.

Buckling↗

NASA NTRS2016

Sensitivity Analysis of the Integrated Medical Model for ISS Programs

Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Standardized Rank Regression Coefficient (SRRC) are methods of conducting sensitivity analysis on nonlinear simulation models like the Integrated Medical Model (IMM). The PRCC method estimates the sensitivity using partial correlation of the ranks of the generated input values to each generated output value. The partial part is so named because adjustments are made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. In SRRC, standardized regression-based coefficients measure the sensitivity of each input, adjusted for all the other inputs, on each output. Because the relative ranking of each of the inputs and outputs is used, as opposed to the values themselves, both methods accommodate the nonlinear relationship of the underlying model. As part of the IMM v4.0 validation study, simulations are available that predict 33 person-missions on ISS and 111 person-missions on STS. These simulated data predictions feed the sensitivity analysis procedures. The inputs to the sensitivity procedures include the number occurrences of each of the one hundred IMM medical conditions generated over the simulations and the associated IMM outputs: total quality time lost (QTL), number of evacuations (EVAC), and number of loss of crew lives (LOCL). The IMM team will report the results of using PRCC and SRRC on IMM v4.0 predictions of the ISS and STS missions created as part of the external validation study. Tornado plots will assist in the visualization of the condition-related input sensitivities to each of the main outcomes. The outcomes of this sensitivity analysis will drive review focus by identifying conditions where changes in uncertainty could drive changes in overall model output uncertainty. These efforts are an integral part of the overall verification, validation, and credibility review of IMM v4.0.

medical equipment↗

DOE OSTI2022

Evaluation of the mean excitation energy of liquid argon

Current and future experiments need to know the stopping power of liquid argon. It is used directly in calibration, where commonly the minimum-ionizing portion of muon tracks is used as a standard candle. Similarly, muon range is used as a measure of muon energy. More broadly, the stopping power figures into the simulation of all charged particles, and so uncertainty propagates widely throughout data analysis of all sorts. The main parameter that controls stopping power is the mean excitation energy, or I-value. Experimental information for argon's I-value come primarily from measurements of gaseous argon, with a very limited amount of information from solid argon, and none from liquid argon. These measurements are reviewed, along with a discussion of the difference in central value and uncertainty incurred by the difference of phase. The values newly recommended by this note are $(188 \pm 6)$ eV for gaseous argon and $(197 \pm 8)$ eV for liquid argon (68% C.L. in each case).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2023

Correlated Signal Analysis for Nuclear Emergency Response

In the context of nuclear emergency response (NER) scenarios, the critical task is to quickly identify a "black box" as a potential threat, as failing to do so could have catastrophic consequences. Techniques for passive assay of a “black box” typically include gamma-ray spectroscopy and neutron coincidence/multiplicity counting. However, there are significant challenges associated with these type of measurements. First, the presence of intervening materials can obstruct the detection of relevant signatures. Second, the presence of strong non-fission neutron sources, like (α, n) emitters, can add uncertainties to the neutron multiplicity analysis. In our LDRD-MFR Phase II work, a portable neutron spectrometer, called the Compact Fast Neutron Spectrometer (CFNS), was developed for NER applications. The CFNS system leverages information-rich neutron energy spectra to derive actionable information. This work investigates the use of correlated signals in the CFNS from special nuclear material (SNM) to characterize physical properties, such as intervening shielding material and fission to non-fission neutron contributions. In this report, the Phase II results from bulk SNM measurements at the National Criticality Experiments Research Center (NCERC) are briefly discussed along with the motivation for this work. Afterwards, simulations using the MCNPX-PoliMi transport code are discussed, which were used to expand our correlated signal study. Signal triggered analysis for neutron multiplicity extraction will also be discussed. Lastly, the use neutron-photon correlations for intervening material identification are shown, along with the use of correlated neutron energy spectra for α-ratio extraction.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

NASA NTRS1976

Practical aspects of a maximum likelihood estimation method to extract stability and control derivatives from flight data

A maximum likelihood estimation method was applied to flight data and procedures to facilitate the routine analysis of a large amount of flight data were described. Techniques that can be used to obtain stability and control derivatives from aircraft maneuvers that are less than ideal for this purpose are described. The techniques involve detecting and correcting the effects of dependent or nearly dependent variables, structural vibration, data drift, inadequate instrumentation, and difficulties with the data acquisition system and the mathematical model. The use of uncertainty levels and multiple maneuver analysis also proved to be useful in improving the quality of the estimated coefficients. The procedures used for editing the data and for overall analysis are also discussed.

Iliff, K. W.↗