SEARCH · Engineering Papers

Results for “uncertainty propagation”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

SourceResearch connectionFrom yearThrough year

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 649 records · Page 36

All sources NASA NTRS DOE OSTI

DOE OSTI2025

Probabilistic Predictions for Fastener Failure in the Sandia Mechanics Challenge Using the Discrete-Direct Uncertainty Quantification Approach

This paper documents the blind and post-blind analysis predictions for the 2023 Sandia Mechanics Challenge (SMC), which involved predicting the behavior of a threaded fastener joint structure subjected to shock loading. Utilizing repeat sets of fastener calibration data from various experimental configurations including tension, double shear, and joint tension, we developed a library of calibrated models which were propagated through the application model using the Discrete-Direct (DD) uncertainty quantification (UQ) approach. Although the initial blind predictions did not incorporate spare-sample processing to quantify fastener failure probabilities, the analyses yielded reasonable conclusions aligned with experimental results. In the post-blind analysis phase, we focused on enhancing the fidelity of the aluminum constitutive model and innovating the DD approach to obtain probabilistic predictions for fastener failure, particularly when quantities of interest (QoIs) approach their bounds. The improved aluminum model captures the behavior of the cantilever under shock loading more accurately, predicting both partial and complete cracks, although it tends to underpredict failure propagation. The enhanced DD approach facilitates probabilistic predictions that reflect the interdependent failure mechanisms of the fasteners and the cantilever, revealing that while certain fasteners are more likely to fail, the failure does not necessarily follow a progressive pattern. Overall, the post-blind analyses significantly improved the predictive capabilities of the model, providing valuable insights into the SMC application and establishing a robust foundation for informed engineering decisions. The methodology demonstrates a cost-effective and extensible approach suitable for a wide range of applications, highlighting the importance of uncertainty quantification to provide context for engineering decision making.

42 ENGINEERING↗

NASA NTRS1971

L-/S-band calibration error analysis.

Results of a statistical error analysis performed to determine the degree of uncertainty encountered when calibrating steerable receiving antennas with the solar calibration method. The analysis considers the propagation of precision error indices. It is shown that a worst-case one-sigma (1 sigma) uncertainty of plus or minus 0.8 dB in system noise temperature occurs for a solar calibration at L-band. Somewhat better precision can be achieved by monitoring the antenna gain-to-noise temperature ratio at a station; a worst-case uncertainty of plus or minus 0.5 dB (1 sigma) can be realized. An error analysis is made of a method to determine absolute antenna gain based upon solar flux density. The uncertainty in this type of measurement is plus or minus 0.7 dB (1 sigma) at L- and S-band frequencies.

Taylor, R. E.↗

NASA NTRS2007

Non-Parametric Collision Probability for Low-Velocity Encounters

An implicit, but not necessarily obvious, assumption in all of the current techniques for assessing satellite collision probability is that the relative position uncertainty is perfectly correlated in time. If there is any mis-modeling of the dynamics in the propagation of the relative position error covariance matrix, time-wise de-correlation of the uncertainty will increase the probability of collision over a given time interval. The paper gives some examples that illustrate this point. This paper argues that, for the present, Monte Carlo analysis is the best available tool for handling low-velocity encounters, and suggests some techniques for addressing the issues just described. One proposal is for the use of a non-parametric technique that is widely used in actuarial and medical studies. The other suggestion is that accurate process noise models be used in the Monte Carlo trials to which the non-parametric estimate is applied. A further contribution of this paper is a description of how the time-wise decorrelation of uncertainty increases the probability of collision.

Carpenter, J. Russell↗

DOE OSTI2025

Systematic study of the validity of the eikonal model including uncertainties

Nuclear reactions at intermediate beam energies are often interpreted using the eikonal model. In the analysis of complex reaction probes, where few-body reaction methods are needed, the eikonal method may be used as an efficient way for describing the fragment-target reaction process. In this work, we perform a systematic study to test the validity of the eikonal approximation for nucleon-nucleus reactions. We also quantify uncertainties due to the nucleon optical potential on reaction observables. We inspect the validity of the eikonal model and its semiclassical correction by comparing it to exact solutions (obtained from solving the optical-model equation with a finite-differences method) for a wide range of reactions. We also study the effect of relativistic corrections, both kinematic and dynamic, by effectively incorporating the relativistic effects at intermediate energies. The uncertainties from a Bayesian global optical potential (KDUQ) are propagated to the observables of interest. Our study includes neutron and proton reactions on 27 Al , 40 Ca , 90 Zr , and 208 Pb , for a wide range of energies 𝐸 lab = 0–400 MeV. We calculate neutron-total cross sections (elastic and reactions) as well as proton-absorption cross sections as a function of beam energy, using the eikonal model, the eikonal model with a semiclassical correction, and the exact solution. Here, we also compute angular distributions for the methods above. Our results show that for the proton-absorption cross section, the eikonal model can be used down to around 60 MeV and the semiclassical correction extends its use to 30 MeV. However, the validity of the eikonal model for the neutron-total cross section only goes down to ≈120 MeV, a range extended to ≈ 50 MeV when using the semiclassical correction. We find the semiclassical correction to the eikonal model to be less effective in describing the angular distributions. The 1⁢𝜎 uncertainty intervals on the observables we studied is less than 5% for most of the energies considered, but increases rapidly for higher energies, namely energies outside the range of KDUQ (𝐸 lab > 200MeV).

Cluster models↗

DOE OSTI2021

An extended polynomial chaos expansion for PDF characterization and variation with aleatory and epistemic uncertainties

This paper presents an extended polynomial chaos formalism for epistemic uncertainties and a new framework for evaluating sensitivities and variations of output probability density functions (PDF) to uncertainty in probabilistic models of input variables. An ”extended” polynomial chaos expansion (PCE) approach is developed that accounts for both aleatory and epistemic uncertainties, modeled as random variables, thus allowing a unified treatment of both types of uncertainty. We explore in particular epistemic uncertainty associated with the choice of prior probabilistic models for input parameters. A PCE-based Kernel Density (KDE) construction provides a composite map from the PCE coefficients and germ to the PDF of quantities of interest (QoI). Here, the sensitivities of these PDF with respect to the input parameters are then evaluated. Input parameters of the probabilistic models are considered. By sampling over the epistemic random variable, a family of PDFs is generated and the failure probability is itself estimated as a random variable with its own PCE. Integrating epistemic uncertainties within the PCE framework results in a computationally efficient paradigm for propagation and sensitivity evaluation. Two typical illustrative examples are used to demonstrate the proposed approach.

Aleatory uncertainty↗

DOE OSTI2022

Nuclear data uncertainty quantification for the nuclide inventory of a Calvert Cliffs spent fuel sample

The impact of nuclear data cross section uncertainties and covariance matrices on the nuclide vector of spent nuclear fuel was investigated; This exercise was carried out for the Calvert Cliffs fuel assembly D047 benchmark available in the SFCOMPO database. Sample P irradiated in rod MKP109 for 4 cycles up to a burnup of approximately 44 GWd/MTU was selected for the analysis. Nuclear data uncertainties were taken from the most recent libraries released by evaluation projects JEFF, ENDF/B and JENDL, and were propagated using the SANDY code via a stochastic sampling approach. This paper provides a quantification of the uncertainty on the concentration of several actinides and fission products relevant for spent fuel management. Uncertainties generally below 5 % were predicted for the concentrations of most of the uranium, neptunium and plutonium isotopes relevant for SNF applications. Curium isotopes carry larger uncertainties that might exceed 10 %. The contribution of cross section uncertainties on the concentrations of fission products was found to be marginal with the exception of a few nuclides. These results can be significantly affected by the lack of evaluated covariance matrices for the capture cross section of several fission products. Burnup tracers such as {sup 148}Nd and {sup 137}Cs have negligible uncertainties because of the power normalisation imposed in every stochastic calculation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2022

Characterizing and quantifying uncertainty in projections of climate change impacts on air quality

Climate change can aggravate air pollution, with important public health and environmental consequences. While major sources of uncertainty in climate change projections - greenhouse gas (GHG) emissions scenario, model response, and internal variability - have been investigated extensively, their propagation to estimates of air quality impacts has not been systematically assessed. Here, we compare these uncertainties using a coupled modeling framework that includes a human activity model, an Earth system model of intermediate complexity, and a global atmospheric chemistry model. Uncertainties in projections of U.S. air quality under 21st century climate change are quantified based on a climate-chemistry ensemble that includes multiple initializations, representations of climate sensitivity, and climate policy scenarios, under constant air pollution emissions. We find that climate-related uncertainties are comparable at mid-century, making it difficult to distinguish the impact of variations in GHG emissions on ozone and particulate matter pollution. While GHG emissions scenario eventually becomes the dominant uncertainty based on the scenarios considered, all sources of uncertainty are significant through the end of the century. The results provide insights into intrinsically different uncertainties in projections of air pollution impacts and the potential for large ensembles to better capture them.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Development and demonstration of a rolling ball viscometer for molten salts with near-minimum liquidus NaCl–KCl

The thermophysical characterization of molten chloride and fluoride salts is a key interest for the development of advanced molten salt nuclear reactors. Viscosity is one thermophysical property of interest; a high-accuracy understanding of this property is necessary for modeling the thermal energy transfer and mass flow rate for a given molten salt system. Only a few methods have consistently been used to measure the viscosity of molten chloride and fluoride salt systems, and large discrepancies have been observed in the literature between independent studies of nearly identical salt systems. As such, exploration of novel measurement methods or implementations may allow for further validation, improved measurement accuracy, and overall improved understanding about optimal approaches for measuring molten salt viscosity. Here, in this study, a novel implementation of the rolling ball viscometry method was used to measure the viscosity of a 44/56 mol % mixture of NaCl–KCl within a temperature range of 714–838 °C, with the intent to demonstrate the feasibility of this technique for molten salt viscosity measurement cross-validation. The purity of this salt was confirmed through laser-induced breakdown spectroscopy. Measured viscosities were approximately 1.3–1.0 cP within this temperature range, and the overall uncertainty was 10.8%, which was determined through Gaussian error propagation. The results agree reasonably well with measured viscosities of similar NaCl–KCl mixtures in the literature (within 2%–20% depending on the temperature and study), although the experimental error in some of these comparative studies may be significant.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Localizing Transformations of the Galaxy-Galaxy Lensing Observable

Modern cosmological analyses of galaxy-galaxy lensing face a theoretical systematic effect arising from the nonlocality of the observed galaxy-galaxy lensing signal. Because the predicted tangential shear signal at a given separation depends on the physical modeling on all scales internal to that separation, systematic uncertainties in the modeling of nonlinear small scales are propagated outward to larger scales. Even in the absence of other limiting factors, this systematic effect alone can necessitate conservative small-scale cuts, resulting in significant losses of information in the tangential shear data vector. We develop a simple linear transformation of the standard galaxy-galaxy observable that removes this nonlocality, which ensures that the cosmological signal contained within the transformed observable is exclusively drawn from well-understood physical scales. This new observable, through its robustness against nonlocality, also enables a significant extension in the range of usable scales in galaxy-galaxy lensing compared to the standard approach in current cosmological analyses.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2025

Improving Trustworthiness of Data-Driven Power Grid Contingency Analysis With Bayesian Residual Graph Neural Networks

The evolving energy landscape requires novel tools to efficiently perform contingency analysis and reliability assessment of power grids, potentially in real-time. The high computational cost of traditional power flow solvers limits their applicability in practice. Machine learning (ML) surrogates such as deep neural networks (NNs) accelerate power flow solvers computations, enabling high-order contingency analysis and real-time decision-making by learning highly nonlinear functions and integrating grid topology via graph architectures. However, (graph) NNs lack predictive power away from training data and do not provide predictive confidence estimates. Here, we present a Bayesian residual graph NN that integrates knowledge from low-fidelity data via residual training and embeds granular quantification of uncertainties, improving trustworthiness critical for high-consequence decision-making. Applying Bayesian concepts to NNs is challenging due to the high-dimensionality of both the parameter space, complicating derivation of a meaningful prior, and the output space in large grid systems, requiring enhanced techniques to assess the predicted high-dimensional uncertainties. Our contributions include: (1) Deriving a prior for fully connected and graph NNs that leverages low-fidelity data to guide mean predictions and appropriately control prior predictive uncertainty. (2) Integrating this prior within an ensembling with anchoring scheme for efficient approximate posterior inference. (3) Deriving enhanced metrics to assess accuracy of both the mean and uncertainty predictions in high dimensions, appropriately accounting for correlations propagated through graph layers. The resulting Bayesian residual graph NN is tested on a contingency analysis task for 14-bus and 118-bus grids.

24 - POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Evaluations for neutron-induced activation cross sections for Y and Zr isotopes

Activation cross sections are an important input for evaluating results of radiochemical analyses, both for basic science and programmatic applications. We present an update on cross sections for a select set of Y and Zr target isotopes, including several isomers. This effort will focus on a methodology to obtain uncertainty quantified systematic trends for reaction model parameters and propagate them to cross sections. We discuss our results in the context of previous calculations.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

NASA NTRS1987

Commit your works to the Lord, and your thoughts shall be established (Prov. 16:3). Inter-stable control systems

Algebraic structures are discussed for control systems that maintain stability in the presence of resonance uncertainties. Dual algebraic operations serve as elementary connections that propagate the stability of inter-stable subsystems. Frequency responses within complex half-planes define different types of inter-stability. Dominance between incompatible types is discussed. Inter-stability produces sufficient but unnecessary stability conditions, except for conservative systems where the conditions become also necessary. Multivariable systems, colocation of actuator and sensor, and virtual colocation are treated. Instead of passivity, inter-stability relates stability to the mapping of poles and zeros by transfer functions and transfer matrices. Inter-stability determines stability on the subsystem level, is less complex even for multivariable systems, adds design flexibility, and relaxes the dynamic data problem of large systems such as space stations.

Vonpragenau, George L.↗

NASA NTRS1995

A case study of view-factor rectification procedures for diffuse-gray radiation enclosure computations

The view factors which are used in diffuse-gray radiation enclosure calculations are often computed by approximate numerical integrations. These approximately calculated view factors will usually not satisfy the important physical constraints of reciprocity and closure. In this paper several view-factor rectification algorithms are reviewed and a rectification algorithm based on a least-squares numerical filtering scheme is proposed with both weighted and unweighted classes. A Monte-Carlo investigation is undertaken to study the propagation of view-factor and surface-area uncertainties into the heat transfer results of the diffuse-gray enclosure calculations. It is found that the weighted least-squares algorithm is vastly superior to the other rectification schemes for the reduction of the heat-flux sensitivities to view-factor uncertainties. In a sample problem, which has proven to be very sensitive to uncertainties in view factor, the heat transfer calculations with weighted least-squares rectified view factors are very good with an original view-factor matrix computed to only one-digit accuracy. All of the algorithms had roughly equivalent effects on the reduction in sensitivity to area uncertainty in this case study.

Taylor, Robert P.↗

NASA NTRSDate not supplied

Probability Bounds Analysis Applied to Multi-Purpose Crew Vehicle Nonlinearity

The Multi-Purpose Crew Vehicle (MPCV) Program Orion vehicle finite element model (FEM) was updated based on a modal test performed by Lockheed Martin. Due to nonlinearity observed in the test results, linear low force level (LL) and high force level (HL) FEMs were developed for use during various Space Launch System (SLS) flight regimes depending on expected forcing levels. Uncertainty models were derived for the combined MPCV and MPCV Stage Adaptor LL and HL Hurty/Craig-Bampton (HCB) components based on the MPCV structural test article Configuration 4 modal test-analysis correlation results. Subsequently, system-level uncertainty quantification analyses were performed using both models for various SLS flight configurations to determine the impact of the nonlinearity on important system metrics. The system metrics included both transfer functions associated with attitude control and dynamic loads associated with aerodynamic buffeting during ascent. In each case, an independent Monte Carlo (MC) analysis was performed, and no attempt was made to combine the results. The Hybrid Parametric Variation (HPV) method was used to develop the LL and HL MPCV HCB uncertainty models. The HPV method provides both parametric and non-parametric components of uncertainty. The non-parametric uncertainty accounts for the difference in model-form between the linearized analytical model and the corresponding linearized component test results in the form of mode shapes and frequencies at that force level. This linear model-form uncertainty is implemented in the HPV method using random matrix theory. However, the HPV uncertainty models developed for the linear LL and HL MPCV components do not account for the nonlinearity in the MPCV. With respect to the linearized models, this nonlinearity is also an uncertainty in model form, but in this case, it must be treated independently as an epistemic uncertainty. It represents a lack of knowledge, in contrast to an aleatory uncertainty due to the randomness of a variable. In the case of an epistemic variable, the true value is unknown, only the interval within which it lies is known. Epistemic uncertainty can be reduced with increased knowledge, while in general, aleatory uncertainty cannot. This work combines the epistemic uncertainty due to the MPCV nonlinearity with the parametric and non-parametric uncertainty within the HPV method using a second order propagation approach. The LL and HL test data is augmented with surrogate test data derived from a nonlinear MPCV representation. The impact of the MPCV nonlinearity on system response statistics is determined using a series of cumulative distribution functions in the form of a horsetail plot, or p-box. This results in an interval of probabilities for a specific response value, or an interval of response values at a specific probability.

Daniel C Kammer↗

DOE OSTI2023

Godiva-IV Dosimetry Exercise 2022 Preliminary Results

Integral Experiment Request (IER) 538 is part of a series of dose characterization and nuclear accident dosimetry (NAD) exercises performed under the Department of Energy (DOE) Nuclear Criticality Safety Program (NCSP). This is the second NAD exercise using the Godiva-IV critical assembly and the third NAD exercise overall. The participating laboratories provided their own dosimeters that were mounted on the Lawrence Livermore National Laboratory (LLNL) BOttle Manikin ABsorption (BOMAB) phantoms and aluminum plates. The BOMABs and plates were placed at two, three, and four meters away from the center of Godiva. Alongside the NADs, there was a LLNL Passive Neutron Spectrometer (PNS), Atomic Weapons Establishment (AWE) PNS, and Y-12 Sphere present to measure the neutron dose from Godiva. Two irradiations were conducted to test the NAD performance from each laboratory and assesses their performance to the DOE-STD-1098-2017 part 515 criteria. Neutron and gamma doses were measured prior to this exercise. This work presents a model for the neutron and gamma dose respectively to serve as the reference value. A code written in C/C++/ROOT was used to fit the measured neutron and gamma dose with the new models. It was assumed that the neutron and gamma doses are proportional to the change in temperature of Godiva after a burst irradiation. Uncertainties for the reference values were calculated using error propagation of the model’s parameters. Preliminary results (within twenty-four hours) and final results were compared for each laboratory. On average of all the participating laboratories, 32% of neutron doses and 78% of gamma doses were outside the DOE standards. One laboratory did not report their dose readings and were not included in this average. There is a bias for a lower neutron dose and a higher gamma dose based on the distribution of results. In comparison with the past Godiva-IV NAD exercise, there is an improvement in neutron dose readings by 20%.

BOttle Manikin ABsorption (BOMAB)↗

NASA NTRS2006

Adapting Covariance Propagation to Account for the Presence of Modeled and Unmodeled Maneuvers

This paper explores techniques that can be used to adapt the standard linearized propagation of an orbital covariance matrix to the case where there is a maneuver and an associated execution uncertainty. A Monte Carlo technique is used to construct a final orbital covariance matrix for a 'prop-burn-prop' process that takes into account initial state uncertainty and execution uncertainties in the maneuver magnitude. This final orbital covariance matrix is regarded as 'truth' and comparisons are made with three methods using modified linearized covariance propagation. The first method accounts for the maneuver by modeling its nominal effect within the state transition matrix but excludes the execution uncertainty by omitting a process noise matrix from the computation. The second method does not model the maneuver but includes a process noise matrix to account for the uncertainty in its magnitude. The third method, which is essentially a hybrid of the first two, includes the nominal portion of the maneuver via the state transition matrix and uses a process noise matrix to account for the magnitude uncertainty. The first method is unable to produce the final orbit covariance except in the case of zero maneuver uncertainty. The second method yields good accuracy for the final covariance matrix but fails to model the final orbital state accurately. Agreement between the simulated covariance data produced by this method and the Monte Carlo truth data fell within 0.5-2.5 percent over a range of maneuver sizes that span two orders of magnitude (0.1-20 m/s). The third method, which yields a combination of good accuracy in the computation of the final covariance matrix and correct accounting for the presence of the maneuver in the nominal orbit, is the best method for applications involving the computation of times of closest approach and the corresponding probability of collision, PC. However, applications for the two other methods exist and are briefly discussed. Although the process model ("prop-burn-prop") that was studied is very simple - point-mass gravitational effects due to the Earth combined with an impulsive delta-V in the velocity direction for the maneuver - generalizations to more complex scenarios, including high fidelity force models, finite duration maneuvers, and maneuver pointing errors, are straightforward and are discussed in the conclusion.

Schiff, Conrad↗

DOE OSTI2022

Inferring the temperature profile of the radiative shock in the COAX experiment with shock radiography, Dante, and spectral temperature diagnostics

Predicting and modeling the behavior of experiments with radiation waves propagating through low-density foams require a detailed quantification of the numerous uncertainties present. In regimes where a prominent radiative shock is produced, key dynamical features include the shock position, temperature, and curvature and the spatial distribution and temperature of the corresponding supersonic radiation wave. The COAX experimental platform is designed to constrain numerical models of such a radiative shock propagating through a low-density foam by employing radiography for spatial and shock information, Dante for characterizing the x-ray flux from the indirectly driven target, and a novel spectral diagnostic designed to probe the temperature profile of the wave. In this work, we model COAX with parameterized 2D simulations and a Hohlraum-laser modeling package to study uncertainties in diagnosing the experiment. The inferred temperature profile of the COAX radiation transport experiments has been shown to differ from simulations more than expected from drive uncertainties that have been constrained by simultaneous soft x-ray flux and radiography measurements.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1971

Vhf/uhf stellar calibration error analysis.

Results of a statistical error analysis performed to determine the degree of uncertainty encountered when calibrating steerable vhf/uhf receiving antennas with the stellar calibration method. The analysis considers the propagation of precision error indices. It is shown that an antenna gain calibration by the stellar method has a one-sigma (1 sigma) uncertainty of plus or minus 0.65 dB at 1440 MHz (L-band), and plus or minus 0.8 dB (1 sigma) at 136 MHz (vhf). Somewhat increased precision can be achieved by monitoring the antenna gain-to-noise temperature ratio at a station; a worst-case uncertainty of plus or minus 0.4 dB (1 sigma) can be realized at both L-band and vhf. Finally, field test measurements of antenna gain, obtained at 136 MHz in the NASA space tracking and data acquisition network, demonstrate an uncertainty of plus or minus 1.0 dB or less, which effectively confirms the analytical result.

Taylor, R. E.↗