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DOE OSTI2024

Implicit neural representations for experimental steering of advanced experiments

Scattering measurements using electrons, neutrons, or photons are essential for obtaining microscopic insights into materials. However, limited facility availability and high-dimensional scattering data necessitate more efficient experimental steering techniques. Here, we report a machine learning method that guides scattering data collection and facilitates real-time estimation of model parameters, given a reliable forward model to simulate experimental signals. We employ implicit neural representations as efficient surrogates that link model parameters with simulated spectroscopies. This enables a Bayesian optimal experimental design framework to estimate the probability distributions of parameters from high-dimensional scattering data. We demonstrate the proposed method using inelastic neutron scattering with simulated and real experimental data, highlighting the method’s ability to provide real-time parameter estimation with quantified uncertainties and to deliver informed experimental guidance that reduces experimental time while maximizing scientific output. This approach paves the way for accelerated discoveries in condensed matter through scattering measurements.

36 MATERIALS SCIENCE↗

NASA NTRSDate not supplied

Battery Design and Orbital Debris Mitigation

This presentation reviews four typical spacecraft battery designs and discusses the benefits and drawbacks of each with respect to the NASA Orbital Debris Mitigation Requirements. These requirements address, among other things, accidental explosion probability while on orbit and reentry ground casualty risk. These probabilities, except for post-mission explosion, must be evaluated against quantitative thresholds. Ground casualty risk resulting from reentry can be assessed quantitatively using reentry demisability models. Some missions establish compliance with explosion probability limits using typical component or assembly reliability figures, while others cite more-restrictive certifications or similarity with past successful projects. NASA encourages – and seeks – standards and information exchange to aid end-users in estimating the probability of accidental explosion.

C Ostrom↗

NASA NTRS2015

Probability of Loss of Crew Achievability Studies for NASA's Exploration Systems Development

Over the last few years, NASA has been evaluating various vehicle designs for multiple proposed design reference missions (DRM) beyond low Earth orbit in support of its Exploration Systems Development (ESD) programs. This paper addresses several of the proposed missions and the analysis techniques used to assess the key risk metric, probability of loss of crew (LOC). Probability of LOC is a metric used to assess the safety risk as well as a design requirement. These assessments or studies were categorized as LOC achievability studies to help inform NASA management as to what "ball park" estimates of probability of LOC could be achieved for each DRM and were eventually used to establish the corresponding LOC requirements. Given that details of the vehicles and mission are not well known at this time, the ground rules, assumptions, and consistency across the programs become the important basis of the assessments as well as for the decision makers to understand.

Boyer, Roger L.↗

NASA NTRS2011

Space Radiation Cancer, Circulatory Disease and CNS Risks for Near Earth Asteroid and Mars Missions: Uncertainty Estimates for Never-Smokers

The uncertainties in estimating the health risks from galactic cosmic rays (GCR) and solar particle events (SPE) are a major limitation to the length of space missions and the evaluation of potential risk mitigation approaches. NASA limits astronaut exposures to a 3% risk of exposure induced cancer death (REID), and protects against uncertainties in risks projections using an assessment of 95% confidence intervals after propagating the error from all model factors (environment and organ exposure, risk coefficients, dose-rate modifiers, and quality factors). Because there are potentially significant late mortality risks from diseases of the circulatory system and central nervous system (CNS) which are less well defined than cancer risks, the cancer REID limit is not necessarily conservative. In this report, we discuss estimates of lifetime risks from space radiation and new estimates of model uncertainties are described. The key updates to the NASA risk projection model are: 1) Revised values for low LET risk coefficients for tissue specific cancer incidence, with incidence rates transported to an average U.S. population to estimate the probability of Risk of Exposure Induced Cancer (REIC) and REID. 2) An analysis of smoking attributable cancer risks for never-smokers that shows significantly reduced lung cancer risk as well as overall cancer risks from radiation compared to risk estimated for the average U.S. population. 3) Derivation of track structure based quality functions depends on particle fluence, charge number, Z and kinetic energy, E. 4) The assignment of a smaller maximum in quality function for leukemia than for solid cancers. 5) The use of the ICRP tissue weights is shown to over-estimate cancer risks from SPEs by a factor of 2 or more. Summing cancer risks for each tissue is recommended as a more accurate approach to estimate SPE cancer risks. 6) Additional considerations on circulatory and CNS disease risks. Our analysis shows that an individual s history of smoking exposure has a larger impact on GCR risk estimates than amounts of radiation shielding or age at exposure (amongst adults). Risks for never-smokers compared to the average U.S. population are estimated to be reduced between 30% and 60% dependent on model assumptions. Lung cancer is the major contributor to the reduction for never-smokers, with additional contributions from circulatory diseases and cancers of the stomach, liver, bladder, oral cavity and esophagus, and leukemia. The relative contribution of CNS risks to the overall space radiation detriment is potentially increased for never-smokers such as most astronauts. Problems in estimating risks for former smokers and the influence of second-hand smoke are discussed. Compared to the LET approximation, the new track structure derived radiation quality functions lead to a reduced risk for relativistic energy particles and increased risks for intermediate energy particles. Revised estimates for the number of safe days in space at solar minimum for heavy shielding conditions are described for never-smokers and the average U.S. population. Results show that missions to near Earth asteroids (NEA) or Mars violate NASA's radiation safety standards with the current levels of uncertainties. Greater improvements in risk estimates for never-smokers are possible, and would be dependent on improved understanding of risk transfer models, and elucidating the role of space radiation on the various stages of disease formation (e.g. initiation, promotion, and progression).

Cucinotta, Francis A.↗

NASA NTRS1979

Magnetic field directional discontinuities. 1: Minimum variance errors

Errors associated with the minimum variance analysis of directional discontinuity normal components were investigated using both computer simulation of discontinuities with controlled properties and the examination of current sheets observed by the Mariner 10 spacecraft. The simulated discontinuities were created by adding fluctuations, represented by isotropic noise, to exactly known but varying (in a plane) magnetic field components. An empirical expression for the magnitude of the error in an estimated discontinuity normal component, relative to the total field across the discontinuity, was derived, as well as other relevant statistical properties. Use of the empirical relation in the analysis of 644 discontinuities observed by Mariner 10 provides a more precise, but probably conservative, estimate of an upper bound on the relative normal component value for tangential discontinuities that can be used to separate rotational from tangential discontinuities in studies using only magnetic field data from a single spacecraft, at least for the interplanetary region of space considered.

Lepping, R. P.↗

NASA NTRS2017

A Probabilistic Method of Assessing Carbon Accumulation Rate at Imnavait Creek Peatland, Arctic Long Term Ecological Research Station, Alaska

Arctic peatlands are an important part of the global carbon cycle, accumulating atmospheric carbon as organic matter since the Late glacial. Current methods for understanding the changing efficiency of the peatland carbon sink rely on peatlands with an undisturbed stratigraphy. Here we present a method of estimating primary carbon accumulation rate from a site where permafrost processes have either vertically or horizontally translocated nearby carbon-rich sediment out of stratigraphic order. Briefly, our new algorithm estimates the probability of the age of deposition of a random increment of sediment in the core. The method assumes that if sediment age is measured at even depth increments, dates are more likely to occur during intervals of higher accumulation rate and vice versa. Multiplying estimated sedimentation rate by measured carbon density yields carbon accumulation rate. We perform this analysis at the Imnavait Creek Peatland, near the Arctic Long Term Ecological Research network site at Toolik Lake, Alaska. Using classical radiocarbon age modeling, we find unreasonably high rates of carbon accumulation at various Holocene intervals. With our new method, we find accumulation rate changes that are in improved agreement within the context of other sites throughout Alaska and the rest of the Circum-Arctic region.

carbon accumulation;Imnavait;peatlands;permafrost;↗

DOE OSTI2024

Estimating coccidioidomycosis endemicity while accounting for imperfect detection using spatio - temporal occupancy modeling

Coccidioidomycosis, or Valley fever, is an infectious disease caused by inhaling Coccidioides fungal spores. Incidence has risen in recent years, and it is believed the endemic region for Coccidioides is expanding in response to climate change. While Valley fever case data can help us understand trends in disease risk, using case data as a proxy for Coccidioides endemicity is not ideal because case data suffers from imperfect detection, including false positives (e.g., travel-related cases reported outside of endemic area) and false negatives (e.g., misdiagnosis or underreporting). Here we proposed a Bayesian, spatio-temporal occupancy model to relate monthly, county-level presence/absence data on Valley fever cases to latent endemicity of Coccidioides, accounting for imperfect detection. We used our model to estimate endemicity in the western United States. We estimated high probability of endemicity in southern California, Arizona, and New Mexico, but also in regions without mandated reporting, including western Texas, eastern Colorado, and southeastern Washington. We also quantified spatio-temporal variability in detectability of Valley fever, given an area is endemic to Coccidioides. We estimated an inverse relationship between lagged 3- and 9-month precipitation and case detection, and a positive association with agriculture. This work can help inform public health surveillance needs and identify areas that would benefit from mandatory case reporting.

60 APPLIED LIFE SCIENCES↗

NASA NTRS2008

An Investigation of the Electrical Short Circuit Characteristics of Tin Whiskers

Existing risk simulations make the assumption that when a free tin whisker has bridged two adjacent exposed electrical conductors, the result is an electrical short circuit. This conservative assumption is made because shorting is a random event that has a currently unknown probability associated with it. Due to contact resistance electrical shorts may not occur at lower voltage levels. In this experiment, we study the effect of varying voltage on the breakdown of the contact resistance which leads to a short circuit. From this data we can estimate the probability of an electrical short, as a function of voltage, given that a free tin whisker has bridged two adjacent exposed electrical conductors. Also, three tin whiskers grown from the same Space Shuttle Orbiter card guide used in the aforementioned experiment were cross-sectioned and studied using a focused ion beam (FIB). The rare polycrystalline structure seen in the FIB cross section was confirmed using transmission electron microscopy (TEM). The FIB was also used to cross section two card guides to facilitate the measurement of the grain size to determine that the tin plating on the card guides had a bright finish.

Courey, Karim J.↗

NASA NTRS2008

An Investigation of the Electrical Short Circuit Characteristics of Tin Whiskers

Courey, Karim J.↗

NASA NTRS2007

Tin Whisker Electrical Short Circuit Characteristics Part 2

Existing risk simulations make the assumption that when a free tin whisker has bridged two adjacent exposed electrical conductors, the result is an electrical short circuit. This conservative assumption is made because shorting is a random event that has a currently unknown probability associated with it. Due to contact resistance electrical shorts may not occur at lower voltage levels. In this experiment, we study the effect of varying voltage on the breakdown of the contact resistance which leads to a short circuit. From this data we can estimate the probability of an electrical short, as a function of voltage, given that a free tin whisker has bridged two adjacent exposed electrical conductors. In addition, three tin whiskers grown from the same Space Shuttle Orbiter card guide used in the aforementioned experiment were cross-sectioned and studied using a focused ion beam (FIB).

Courey, Karim J.↗

NASA NTRS2015

A Fast Goal Recognition Technique Based on Interaction Estimates

Goal Recognition is the task of inferring an actor's goals given some or all of the actor's observed actions. There is considerable interest in Goal Recognition for use in intelligent personal assistants, smart environments, intelligent tutoring systems, and monitoring user's needs. In much of this work, the actor's observed actions are compared against a generated library of plans. Recent work by Ramirez and Geffner makes use of AI planning to determine how closely a sequence of observed actions matches plans for each possible goal. For each goal, this is done by comparing the cost of a plan for that goal with the cost of a plan for that goal that includes the observed actions. This approach yields useful rankings, but is impractical for real-time goal recognition in large domains because of the computational expense of constructing plans for each possible goal. In this paper, we introduce an approach that propagates cost and interaction information in a plan graph, and uses this information to estimate goal probabilities. We show that this approach is much faster, but still yields high quality results.

gola recognition↗

NASA NTRS1989

Probabilities and statistics for backscatter estimates obtained by a scatterometer

Methods for the recovery of winds near the surface of the ocean from measurements of the normalized radar backscattering cross section must recognize and make use of the statistics (i.e., the sampling variability) of the backscatter measurements. Radar backscatter values from a scatterometer are random variables with expected values given by a model. A model relates backscatter to properties of the waves on the ocean, which are in turn generated by the winds in the atmospheric marine boundary layer. The effective wind speed and direction at a known height for a neutrally stratified atmosphere are the values to be recovered from the model. The probability density function for the backscatter values is a normal probability distribution with the notable feature that the variance is a known function of the expected value. The sources of signal variability, the effects of this variability on the wind speed estimation, and criteria for the acceptance or rejection of models are discussed. A modified maximum likelihood method for estimating wind vectors is described. Ways to make corrections for the kinds of errors found for the Seasat SASS model function are described, and applications to a new scatterometer are given.

Pierson, Willard J., Jr.↗

DOE OSTI2023

Efficient Subset Simulation using Hamiltonian Neural Network enhanced Markov Chain Monte Carlo Methods

The Monte Carlo method delivers an unbiased estimate of the probability of failure. However, the variance of the estimate depends on the number of evaluated samples. This number must be very large for estimations of a low probability of failure. If the evaluation of each sample is computationally expensive, the crude Monte Carlo simulation strategy is impracticable. Therefore, subset simulations are used to reduce the required number of evaluations. Subset simulations require a Markov Chain Monte Carlo sampler, such as the random walk Metropolis-Hastings algorithm. The algorithm, however, struggles with sampling in low-probability regions, especially if they are narrow. As a consequence, advanced Markov Chain Monte Carlo simulations have been developed. In particular, the Hamiltonian Monte Carlo method explores the target distribution rapidly. Driven by the idea of Hamiltonian dynamics, this sampler provides a non-random walk through the target distribution. The incorporation of subset simulation and Hamiltonian Monte Carlo methods has shown promising results for reliability analysis. One downside of the Hamiltonian Monte Carlo method is that gradient evaluations are computationally expensive, especially when dealing with high-dimensional problems and evaluating long trajectories. We show that integrating Hamiltonian neural networks in Hamiltonian Monte Carlo simulations significantly speeds up the sampling task. Furthermore, the enhancement of adaptive trajectory length within the Hamiltonian Monte Carlo results in the efficient proposal of the following states. Based on this recent enhancement, we provide a fast sampling strategy for subset simulations using Hamiltonian neural networks to replace the evaluation of the gradient and significantly speed up the Hamiltonian Monte Carlo simulation.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2021

A Bayesian nonparametric analysis for zero-inflated multivariate count data with application to microbiome study

High-throughput sequencing technology has enabled researchers to profile microbial communities from a variety of environments, but analysis of multivariate taxon count data remains challenging. Here, we develop a Bayesian nonparametric (BNP) regression model with zero inflation to analyse multivariate count data from microbiome studies. A BNP approach flexibly models microbial associations with covariates, such as environmental factors and clinical characteristics. The model produces estimates for probability distributions which relate microbial diversity and differential abundance to covariates, and facilitates community comparisons beyond those provided by simple statistical tests. We compare the model to simpler models and popular alternatives in simulation studies, showing, in addition to these additional community-level insights, it yields superior parameter estimates and model fit in various settings. The model's utility is demonstrated by applying it to a chronic wound microbiome data set and a Human Microbiome Project data set, where it is used to compare microbial communities present in different environments.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

NASA NTRS2014

Probability of Loss of Crew Achievability Studies for NASA's Exploration Systems Development

Over the last few years, NASA has been evaluating various vehicle designs for multiple proposed design reference missions (DRM) beyond low Earth orbit in support of its Exploration Systems Development (ESD) programs. This paper addresses several of the proposed missions and the analysis techniques used to assess the key risk metric, probability of loss of crew (LOC). Probability of LOC is a metric used to assess the safety risk as well as a design requirement. These risk assessments typically cover the concept phase of a DRM, i.e. when little more than a general idea of the mission is known and are used to help establish "best estimates" for proposed program and agency level risk requirements. These assessments or studies were categorized as LOC achievability studies to help inform NASA management as to what "ball park" estimates of probability of LOC could be achieved for each DRM and were eventually used to establish the corresponding LOC requirements. Given that details of the vehicles and mission are not well known at this time, the ground rules, assumptions, and consistency across the programs become the important basis of the assessments as well as for the decision makers to understand.

Boyer, Roger L.↗

NASA NTRS2015

Probability of Loss of Crew Achievability Studies for NASA's Exploration Systems Development

Over the last few years, NASA has been evaluating various vehicle designs for multiple proposed design reference missions (DRM) beyond low Earth orbit in support of its Exploration Systems Development (ESD) programs. This paper addresses several of the proposed missions and the analysis techniques used to assess the key risk metric, probability of loss of crew (LOC). Probability of LOC is a metric used to assess the safety risk as well as a design requirement. These risk assessments typically cover the concept phase of a DRM, i.e. when little more than a general idea of the mission is known and are used to help establish "best estimates" for proposed program and agency level risk requirements. These assessments or studies were categorized as LOC achievability studies to help inform NASA management as to what "ball park" estimates of probability of LOC could be achieved for each DRM and were eventually used to establish the corresponding LOC requirements. Given that details of the vehicles and mission are not well known at this time, the ground rules, assumptions, and consistency across the programs become the important basis of the assessments as well as for the decision makers to understand.

Boyer, Roger L.↗

NASA NTRS2015

Probability of Loss of Crew Achievability Studies for NASA's Exploration Systems Development

Over the last few years, NASA has been evaluating various vehicle designs for multiple proposed design reference missions (DRM) beyond low Earth orbit in support of its Exploration Systems Development (ESD) programs. This paper addresses several of the proposed missions and the analysis techniques used to assess the key risk metric, probability of loss of crew (LOC). Probability of LOC is a metric used to assess the safety risk as well as a design requirement. These risk assessments typically cover the concept phase of a DRM, i.e. when little more than a general idea of the mission is known and are used to help establish "best estimates" for proposed program and agency level risk requirements. These assessments or studies were categorized as LOC achievability studies to help inform NASA management as to what "ball park" estimates of probability of LOC could be achieved for each DRM and were eventually used to establish the corresponding LOC requirements. Given that details of the vehicles and mission are not well known at this time, the ground rules, assumptions, and consistency across the programs become the important basis of the assessments as well as for the decision makers to understand.

Boyer, Roger L.↗

NASA NTRS2000

Lightning Strike Peak Current Probabilities as Related to Space Shuttle Operations

A summary is presented of basic lightning characteristics/criteria applicable to current and future aerospace vehicles. The paper provides estimates on the probability of occurrence of a 200 kA peak lightning return current, should lightning strike an aerospace vehicle in various operational phases, i.e., roll-out, on-pad, launch, reenter/land, and return-to-launch site. A literature search was conducted for previous work concerning occurrence and measurement of peak lighting currents, modeling, and estimating the probabilities of launch vehicles/objects being struck by lightning. This paper presents a summary of these results.

Johnson, Dale L.↗