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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.

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At least 505 records · Page 28
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Miserable Risk Estimation: “Managing” Low-Probability, High-Consequence Risks

As with all bold endeavors, NASA missions must identify and manage their risks. While estimating the consequences of these risks is typically straightforward, it can be challenging to estimate their likelihood. This is especially true for low-probability risks, due both to the lack of operational data and the cognitive biases humans bring to risk estimation. In this talk, I will present both a tongue-in-cheek and “Management Science” approach to estimating low-probability, high-consequence risks. I then summon my Human Factors colleagues to provide NASA mission managers with the gentle guidance needed to avoid common errors in risk assessment

Mary K Kaiser↗
NASA NTRS2003

Upper bounds to error probabilities of coded systems beyond the cutoff rate

A family of upper bounds to error probabilities of coded systems was recently proposed by Divsalar. These bounds are valid for transmission over the additive white Gaussian noise channel, and require only the knowledge of the weight spectrum of the code words. After illustrating these bounds, we extend them to fading channels. Contrary to the union bound, our bounds maintain their effectiveness below the signal-to-noise ratio (SNR)at which the cutoff rate of the channel equals the rate of the code. Some applications are shown. First, we derive upper bounds to the minimum SNR necessary to achieve zero error probability as the code block length increases to infinity. Next, we use our bounds to predict the performance of turbo codes and low-density parity-check codes.

Biglieri, Ezio↗
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↗
NASA NTRS2022

Understanding the Microphysical Control and Spatial-Temporal Variability of Warm Rain Probability Using CloudSat and MODIS Observations

By combining measurements from MODIS and the CloudSat radar, we develop a parameterization scheme to quantify the combined microphysical controls by liquid water path (LWP) and cloud droplet number concentration (CDNC) of the probability of precipitation (PoP) in marine low cloud over tropical oceans. We demonstrate that the spatial-temporal variation of grid-mean in-cloud can be largely explained by the variation of the joint probability density function of LWP and CDNC in the phase space specified by the bivariate PoP (LWP and CDNC) function. Through a series of sensitivity tests guided by this understanding, we find that in the Southeastern Pacific and Atlantic the stratocumulus to cumulus transition of the is mainly due to the variation of CDNC while the annual cycle is mainly due to the variation of LWP. The results of this study provide a viable way to diagnose the root cause of warm rain problems in global climate models.

Zhibo Zhang↗
NASA NTRSDate not supplied

Model Assisted Probability of Detection for NASA Space Missions

Model assisted probability of detection (MAPOD) uses data from simulations to improve a traditional probability of detection (POD) study. This could include extending the parameter space to reduce uncertainty or substituting experimental data with simulated data to reduce the time and cost of a POD study. In the past MAPOD was difficult due to limited computational resources, but recent innovations in simulation tools and high-performance computing have made this type of high-degree-of-freedom modeling possible, and complex structures have made it necessary. This presentation will summarize the work done by the computational nondestructive evaluation (CNDE) specialists within the Nondestructive Evaluation Sciences branch at NASA Langley Research Center (LaRC) to complete a MAPOD study for phased array ultrasound testing (PAUT) of a friction stir welding (FSW) method to be used on Space Launch System (SLS) structures. The three critical needs for a MAPOD study are a validated and verified model of the inspection technique for the structure being inspected, some experimental POD data, and an uncertainty model for both the model and the experimental data. PAUT was simulated using Extende CIVA’s UT module. The model was validated using laboratory inspection data from NASA Marshall Space Flight Center (MSFC) for a Hit/Miss POD for FSW in 2219-T87 aluminum panels representative of those used in the SLS. This model was then used to simulate flaw sizes that were originally omitted from the original POD study. The results of this new MAPOD study will be presented along with a discussion of the methods and processes used to analyze the original data, selected simulation parameters, and development of the uncertainty model used for the statistical analysis. The goal of this effort is not just to improve the POD study but to demonstrate the value of MAPOD and provide a roadmap for application of MAPOD on future projects.

Elizabeth Gregory↗
NASA NTRSDate not supplied

Model Assisted Probability of Detection for NASA Space Missions

Model assisted probability of detection (MAPOD) uses data from simulations to improve a traditional probability of detection (POD) study. This could include extending the parameter space to reduce uncertainty or substituting experimental data with simulated data to reduce the time and cost of a POD study. In the past MAPOD was difficult due to limited computational resources, but recent innovations in simulation tools and high-performance computing have made this type of high-degree-of-freedom modelling possible, and complex structures have made it necessary. This presentation will summarize the work done by the computational nondestructive evaluation (CNDE) group at NASA Langley Research Center (LaRC) to complete a MAPOD study for phased array ultrasound testing (PAUT) of a friction stir welding (FSW) method to be used on Space Launch System (SLS) structures. The three critical needs for a MAPOD study are a validated and verified model of the inspection technique for the structure being inspected, some experimental POD data, and an uncertainty model for both the model and the experimental data. PAUT was simulated using Extende CIVA’s UT module. The model was validated using laboratory inspection data from NASA Marshall Space Flight Center (MSFC) for a Hit/Miss POD for FSW in 2219-T87 aluminum panels representative of those used in the SLS. This model was then used to simulate flaw sizes that were originally omitted from the original POD study. The results of this new MAPOD study will be presented along with a discussion of the methods and processes used to analyze the original data, selected simulation parameters, and development of the uncertainty model used for the statistical analysis. The goal of this effort is not just to improve the POD study but to demonstrate the value of MAPOD and provide a roadmap for application of MAPOD on future projects.

Elizabeth Gregory↗
NASA NTRSDate not supplied

An Eddy Current Case Study using NASA’s Transfer Function and Limited-Sample Probability of Detection Guidebooks

Probability of detection (POD) requirements for NASA fracture-critical human-rated systems can be met by (1) claiming ‘similarity’ to NASA Standard Nondestructive Evaluation (NDE) flaw sizes or (2) by inspector-specific POD demonstration, known as NASA Special NDE. Standard NDE flaw sizes are intended to represent the detection capability of most qualified inspectors, and were primarily based on POD studies in the development of the Space Shuttle Program Orbiter fracture control plan. However, these Standard NDE flaw sizes were based on fatigue cracks in flat panels of one material alloy over a limited range of panel thicknesses. While the POD study was comprehensive, the inspection conditions are relatively narrow. An evaluation of similarity between the Standard NDE POD study and flight component conditions is required to apply Standard NDE to specific flight component inspections. A similarity evaluation may include differences in materials, surface finish, component geometry (e.g., curvature, corners, welds), and inspection access. Similarity is typically based on a qualitative engineering evaluation. Recently, NASA published a quantitative methodology to assess similarity. If similarity is not supported by test and analysis, then the methodology provides a transfer function of flaw size for Special NDE POD demonstration. NASA recommends that Special POD demonstrations use flaws that are flight-like or more difficult to detect than flight component flaws, which are commonly induced fatigue cracks. Often, it is not feasible to induce fatigue cracks in flight component geometry, and therefore, a simpler representative geometry is used, commonly a flat panel, for POD demonstration. Inducing cracks in simple geometry specimens can be time-consuming and expensive, and thus, minimizing the number of flawed specimens is desired. Traditionally, NASA Special NDE demonstration was limited to MIL-HDBK-1823A methods or the binomial point-estimate method (PEM), commonly known as 29/29. Recently, NASA published a limited-sample POD (LS-POD) methodology for signal-response NDE techniques (e.g., eddy current) that provides POD demonstration with fewer specimens than previous approaches. LS-POD suggests a minimum of 10 flawed specimens, compared to 29 in the PEM and the suggested minimum of 40 from MIL-HDBK-1823A. The methodology also includes new guidance on evaluating the probability of false calls. In this presentation, these new transfer function and LS-POD methodologies are described and illustrated through an eddy current detection capability of far-side flaws on thin welded panels. A geometry-based transfer function is developed using electro-discharge machined (EDM) notches in flight component and simple geometry to estimate the Special NDE flaw size that is representative of the critical initial flaw size required by the fracture analysis. Then, fatigue cracks are induced in simple flat panels of the transferred flaw size, and the LS-POD methodology is used for Special NDE demonstration.

P. A. Parker↗
NASA NTRSDate not supplied

Metrics on Predictive Probability of Collision Assessments Reliant on Object State Updates

The probability of collision (Pc) metric is the dominant method of risk charac-terization for evaluating satellite close approaches, and has become of particular interest following major debris production incidents. However, confidence in the use of Pc for actionability has been questioned due in part due to its non-intuitive and often significant corrections following messaging updates. This paper assesses predictively computed probabilities and confidence bounds on Pc values corresponding to orbit determination updates by comparing these predic-tive values to observed operational values. This paper also presents use cases for this methodology in assessing event actionability.

conjunction assessment↗
DOE OSTI2018

Analytic Neutrino Oscillation Probabilities in Matter: Revisited

We summarize our recent paper on neutrino oscillation probabilities in matter, explaining the importance, relevance and need for simple, highly accurate approximations to the neutrino oscillation probabilities in matter.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

GANISP: A GAN-Assisted Importance Splitting Probability Estimator

Designing manufacturing processes with high yield and strong reliability relies on effective methods for rare event estimation. Genealogical importance splitting reduces the variance of rare event probability estimators by iteratively selecting and replicating realizations that are headed towards a rare event. The replication step is difficult when applied to deterministic systems where the initial conditions of the offspring realizations need to be modified. Typically, a random perturbation is applied to the offspring to differentiate their trajectory from the parent realization. However, this random perturbation strategy may be effective for some systems while failing for others, preventing variance reduction in the probability estimate. This work seeks to address this limitation using a generative model such as a Generative Adversarial Network (GAN) to generate perturbations that are consistent with the attractor of the dynamical system. The proposed GAN-assisted Importance SPlitting method (GANISP) improves the variance reduction for the system targeted. An implementation of the method is available in a companion repository (https://github.com/NREL/GANISP).

generative adversarial network↗
DOE OSTI2022

GANISP: A GAN-Assisted Importance Splitting Probability Estimator: Preprint

To reduce the variance of rare event probability estimator, genealogical importance splitting marches towards a rare event by iteratively selecting and replicating realizations that are headed towards a rare event. The replication step is made difficult when applied to deterministic systems as the initial conditions of the offspring realizations need to be modified. Typically, a random perturbation is applied to the offspring to differentiate their trajectory from the parent realization. It is shown that a random perturbation strategy may be effective for some systems but may also fail for others, thereby preventing variance reduction in the probability estimate. To address this limitation, it is proposed to use a generative model such as a Generative Adversarial Network (GAN) to generate perturbations that are consistent with the attractor of the dynamical system. The GAN-assisted Importance SPlitting method (GANISP) improves the variance reduction for the system targeted. An implementation of the method is available in a companion repository (https://github.com/NREL/GANISP).

generative adversarial network↗
DOE OSTI2016

Investigation on Reaction Probabilities for Cyclic Voltammetry of Zirconium in LiCl-KCl Eutectic Molten Salt via Reverse-Engineering Method

This work focuses on a reverse-engineering program design for the cyclic voltammetry (CV) method to help illustrating, enhancing, and providing robustness in detection probability of the reactions during an electrorefining process. Analyzing the reactions from CV plots for 1.07, 2.49, and 4.98 wt% of zirconium chloride (ZrCl{sub 4}) in a LiCl-KCl molten salt at 773 K under different scan rates from Hoover's study has been accomplished. The results provide the current (Amp) versus potential (V) to investigate the optimum probability of the reactions at each peak. All simulations have been done through the commercial software MATLAB by using various experimental values existing in the literature as a first guess (e.g., the diffusion coefficients, and formal potentials). Preliminary results indicate that the zirconium reactions at each peak from cathodic to anodic side for 1.07 wt% are as followed: combination of Zr{sup +2}/Zr and Zr{sup +4}/ Zr{sup +2} at approximately -1.15 V, Zr{sup +2}/Zr at -1.5 V, Zr{sup +4}/Zr at -1.85 V, 70% Zr/Zr{sup +4} and 30% Zr/Zr{sup +2} at -0.5 V, and Zr{sup +2}/ Zr{sup +4} at - 0.25 V. These mentioned peaks are similar for 2.49 wt% at different voltages. In addition, the highest anodic peak for 4.98 wt% is found to be a combination of 30% Zr/Zr{sup +4} and 70% Zr/Zr{sup +2}. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Temperature compensated transfer function for probability of detection (POD) in high temperature ultrasonic NDE using low temperature signals - 249

Ultrasonic piezoelectric based transducers offer the potential for in-coolant NDT measurements and imaging required at high temperature for the safe operation of advanced small modular reactors (SMRs). Current work estimates a significant 97% reduction in the probability of detection (POD) for an artificial flaw size of 2{lambda} due to degradation of the transducer performance at elevated temperature. The source of variability for POD in the current work is the temperature dependence of material matrix of piezoelectric material PZT-5A used in the sensor. The physics based model developed using finite element method quantifies reduction in the scattering amplitude for the side drilled hole (SDH) from 15 C to 195 C. Using model assisted probability of detection (MAPOD) approach, sensor temperature effect on the POD is demonstrated for SDHs in the low carbon steel specimen. Scattering amplitudes for the room temperature simulated data is validated with the experimental data. A temperature correction factor and transfer factors are reported to transform the simulated temperature effect from physics based model to the experimental data for estimation of high temperature POD using low temperature ultrasonic measurements. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2016

Numerical methods for high-dimensional probability density function equations

In this paper we address the problem of computing the numerical solution to kinetic partial differential equations involving many phase variables. These types of equations arise naturally in many different areas of mathematical physics, e.g., in particle systems (Liouville and Boltzmann equations), stochastic dynamical systems (Fokker–Planck and Dostupov–Pugachev equations), random wave theory (Malakhov–Saichev equations) and coarse-grained stochastic systems (Mori–Zwanzig equations). We propose three different classes of new algorithms addressing high-dimensionality: The first one is based on separated series expansions resulting in a sequence of low-dimensional problems that can be solved recursively and in parallel by using alternating direction methods. The second class of algorithms relies on truncation of interaction in low-orders that resembles the Bogoliubov–Born–Green–Kirkwood–Yvon (BBGKY) framework of kinetic gas theory and it yields a hierarchy of coupled probability density function equations. The third class of algorithms is based on high-dimensional model representations, e.g., the ANOVA method and probabilistic collocation methods. A common feature of all these approaches is that they are reducible to the problem of computing the solution to high-dimensional equations via a sequence of low-dimensional problems. The effectiveness of the new algorithms is demonstrated in numerical examples involving nonlinear stochastic dynamical systems and partial differential equations, with up to 120 variables.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2017

Continuation of probability density functions using a generalized Lyapunov approach

Techniques from numerical bifurcation theory are very useful to study transitions between steady fluid flow patterns and the instabilities involved. Here, we provide computational methodology to use parameter continuation in determining probability density functions of systems of stochastic partial differential equations near fixed points, under a small noise approximation. Key innovation is the efficient solution of a generalized Lyapunov equation using an iterative method involving low-rank approximations. We apply and illustrate the capabilities of the method using a problem in physical oceanography, i.e. the occurrence of multiple steady states of the Atlantic Ocean circulation.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2014

Theoretical analysis of integral neutron transport equation using collision probability method with quadratic flux approach

Theoretical analysis of integral neutron transport equation using collision probability (CP) method with quadratic flux approach has been carried out. In general, the solution of the neutron transport using the CP method is performed with the flat flux approach. In this research, the CP method is implemented in the cylindrical nuclear fuel cell with the spatial of mesh being conducted into non flat flux approach. It means that the neutron flux at any point in the nuclear fuel cell are considered different each other followed the distribution pattern of quadratic flux. The result is presented here in the form of quadratic flux that is better understanding of the real condition in the cell calculation and as a starting point to be applied in computational calculation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2014

Review of Literature for Model Assisted Probability of Detection

This is a draft technical letter report for NRC client documenting a literature review of model assisted probability of detection (MAPOD) for potential application to nuclear power plant components for improvement of field NDE performance estimations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗