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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Rejection Sampling with Autodifferentiation -- Case study: Fitting a Hadronization Model

We present an autodifferentiable rejection sampling algorithm termed Rejection Sampling with Autodifferentiation (RSA). In conjunction with reweighting, we show that RSA can be used for efficient parameter estimation and model exploration. Additionally, this approach facilitates the use of unbinned machine-learning-based observables, allowing for more precise, data-driven fits. To showcase these capabilities, we apply an RSA-based parameter fit to a simplified hadronization model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

Adjoint Klein-Nishina Sampling Methods: Efficiency, Speed and Applications

Three new rejection sampling methods for generating samples from the adjoint Klein-Nishina cross section are discussed: the two-branch rejection sampling procedure, the three-branch linear rejection sampling procedure and the three-branch inverse rejection sampling procedure. These methods have all been implemented in the Framework for REsearch in Nuclear ScIence and Engineering (FRENSIE). The efficiency and sample generation rate of each of these methods are evaluated to characterize the methods and to make recommendations regarding their use. The use of these methods in realistic transport simulations is also evaluated by incorporating a scattering function into the sampling process. Furthermore, the results of an infinite medium problem are presented to verify that the sampling procedure can be used in an adjoint Monte Carlo simulation to generate results that are in agreement with an equivalent forward simulation.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Deterministic Linear Time for Maximal Poisson‐Disk Sampling using Chocks without Rejection or Approximation

Abstract We show how to sample uniformly within the three‐sided region bounded by a circle, a radial ray, and a tangent, called a “chock.” By dividing a 2D planar rectangle into a background grid, and subtracting Poisson disks from grid squares, we are able to represent the available region for samples exactly using triangles and chocks. Uniform random samples are generated from chock areas precisely without rejection sampling. This provides the first implemented algorithm for precise maximal Poisson‐disk sampling in deterministic linear time. We prove O(n · M(b) log b), where n is the number of samples, b is the bits of numerical precision and M is the cost of multiplication. Prior methods have higher time complexity, take expected time, are non‐maximal, and/or are not Poisson‐disk distributions in the most precise mathematical sense. We fill this theoretical lacuna.

Mitchell, Scott A.↗
DOE OSTI2024

Evaluation of Naturally Occurring Be-7 Activity on LANL Stack Filter Clumps

Los Alamos National Laboratory (LANL) is responsible for providing solutions to challenging issues through multidisciplinary science, engineering, and technology that impact national security. As part of the Radioactive Air Emissions Management (RAEM) Team, it is our responsibility to ensure LANL operates within the requirements of the Code of Federal Regulations 40 CFR 61, Subpart H, National Emission Standards for Emissions of Radionuclides Other Than Radon From Department of Energy Facilities (Rad-NESHAP). The standard states, “Emissions of radionuclides to the ambient air from Department of Energy facilities shall not exceed those amounts that would cause any member of the public to receive in any year an effective dose equivalent of 10 mrem/yr” (EPA, 2002) During a routine assessment of LANL’s Rad-NESHAP compliance program, an opportunity for improvement was identified that addresses the evaluation of routine stack samples which potentially have naturally occurring radioactive materials (NORM) on the filter media. In the past and based on professional judgment, detections of NORM such as K-40 and Be-7 typically were rejected from the analytical results. The assessment finding suggested developing a technical criterion to ensure that such rejections were justified, comparing actual measured values with anticipated NORM concentrations for various stacks located at LANL. The significance of accepting or rejecting samples as “true” or “NORM” and its impact on the RAEM’s mission and compliance to the regulations is explained later in the document. Additionally, this document will describe the process and calculations for how such results are to be accepted as actual samples “true positive” or rejected as NORM.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2023

Resonance Scattering Treatment with the Windowed Multipole Formalism

A new method for directly sampling the resonance upscattering effect is presented. Alternatives have relied on inefficient rejection sampling techniques or large tabular storage of relative velocities. None of these approaches, which require pointwise energy data, are particularly well suited to the windowed multipole cross-section representation. The new method, called multipole analytic resonance scattering, overcomes these limitations by inverse transform sampling from the target relative velocity distribution where the cross section is expressed in the multipole formalism. The closed-form relative speed distribution contains a novel special function we deem the incomplete Faddeeva function, and we present the first results on its efficient numerical evaluation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

CORRLA-RS

The CORRLA-RS package provides a suite of statistical methods for sampling multidimensional distributions and to conduct sensitivity and correlation analysis of large scale data in the Rust programming language. The software provides a unique solution to multidimensional constrained sampling problems utilizing a combination of parallelized Markov Chain Monte Carlo methods and traditional rejection sampling. The sensitivity and correlation analysis methods are backed by a high performance randomized singular value decomposition implementation which enables datasets larger than the random access memory (RAM) size to be analyzed. Additionally, CORRLA-RS implements the active subspace identification method using a KD-Tree and the randomized singular value decomposition acting in concert.

Gurecky, William [Oak Ridge National Laboratory (O↗
DOE OSTI2023

Adjoint DSMC for nonlinear spatially-homogeneous Boltzmann equation with a general collision model

We derive an adjoint method for the Direct Simulation Monte Carlo (DSMC) method for the spatially homogeneous Boltzmann equation with a general collision law. This generalizes our previous results in Caflisch et al., which was restricted to the case of Maxwell molecules, for which the collision rate is constant. The main difficulty in generalizing the previous results is that a rejection sampling step is required in the DSMC algorithm in order to handle the variable collision rate. We find a new term corresponding to the so-called score function in the adjoint equation and a new adjoint Jacobian matrix capturing the dependence of the collision parameter on the velocities. The new formula works for a much more general class of collision models.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

Hyperparameter Setting for a Marked Multidimensional Hawkes Process with Dissimilar Decays

We provide further details for using Lim, et al.'s marked multidimensional Hawkes processes with dissimilar decays. We first describe what makes these different from other Hawkes processes, then describe each model hyperparameter and how to initialize it informed by the input data and any prior biases. We derived tighter bounds than Lim, et al. for faster convergence of rejection sampling. The resulting hyperparameters and bounds have been helpful against both synthetic and real-world datasets.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

nautilus : boosting Bayesian importance nested sampling with deep learning

ABSTRACT We introduce a novel approach to boost the efficiency of the importance nested sampling (INS) technique for Bayesian posterior and evidence estimation using deep learning. Unlike rejection-based sampling methods such as vanilla nested sampling (NS) or Markov chain Monte Carlo (MCMC) algorithms, importance sampling techniques can use all likelihood evaluations for posterior and evidence estimation. However, for efficient importance sampling, one needs proposal distributions that closely mimic the posterior distributions. We show how to combine INS with deep learning via neural network regression to accomplish this task. We also introduce nautilus, a reference open-source python implementation of this technique for Bayesian posterior and evidence estimation. We compare nautilus against popular NS and MCMC packages, including emcee, dynesty, ultranest, and pocomc, on a variety of challenging synthetic problems and real-world applications in exoplanet detection, galaxy SED fitting and cosmology. In all applications, the sampling efficiency of nautilus is substantially higher than that of all other samplers, often by more than an order of magnitude. Simultaneously, nautilus delivers highly accurate results and needs fewer likelihood evaluations than all other samplers tested. We also show that nautilus has good scaling with the dimensionality of the likelihood and is easily parallelizable to many CPUs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Time-Gated Raman Spectroscopy (Intern Final Report)

Time-gated Raman spectroscopy is a powerful tool for rapid non-destructive analysis of chemical compounds, particularly when combined with other investigative methods. Time-gating the signal obtained from a sample during Raman spectroscopy allows for the removal of background emission and black body radiation, improving clarity and accuracy of scans. The main objectives of this project were to prove the lab’s time-gated Raman spectroscopy system works as proof of concept and to make select improvements to the in-house LabVIEW software used to run the time-gated system. This time-gated system will be added to the CTK’s TAP reactors in the future, but this is out of the scope of this internship project. This research is important, as understanding the mechanisms behind catalysts leads to designing better systems/materials and the perfection of catalysts, and energy-efficient chemical manufacturing is key when designing a greener future. The research for this project was done with samples at both ambient conditions in sample holders and at operando conditions (i.e., high temperature, unsteady-state) inside a small-volume chemical reactor. Numerous spectro-kinetic scans of the catalysts were obtained, but the advanced dynamics of these systems are still being interpreted. There is data that demonstrates that the time-gated system is correctly rejecting emission from samples, and one can observe real-time changes in the signal from the sample, due to coking or changes induced by redox chemistry. Chemical manufacturers and the planet are the main beneficiaries of catalysis research, as better catalysts will reduce carbon emissions.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Performance of reverse osmosis membrane with large feed pressure fluctuations from a wave-driven desalination system

Wave-driven desalination systems are proposed water treatment systems that involve reverse osmosis of seawater powered directly by wave motion. Such a configuration would result in drastic feed pressure fluctuations. For a technology conventionally operated with a constant feed condition, the effect of these variable pressures on membrane integrity and performance is unknown. Here, experiments were conducted with spiral wound membranes coupled to a system capable of producing feed pressure fluctuations of more than 400 psi. Feed composition included 5, 20, and 35 g/L NaCl, and a synthetic seawater at normal and 1.5x concentration. The variable feed conditions included sine-like pressure waves swings of 200-500 and 500-900 psi with frequencies of 1.25, 7.5, and 12 waves/min, and a model-generated random waveform. Between each wave experiment we performed membrane integrity tests at 650 psi and 25 g/L NaCl feed, which showed a 7.4% drop in the membrane's water permeability coefficient, an 18.4% flux decline, and more than 99% salt rejection over 1770 h of cumulative experimental time. Analysis of permeate samples showed high salt rejection. In general, variable feed pressure had no significant deleterious effect on membrane integrity or performance.

16 TIDAL AND WAVE POWER↗
DOE OSTI2021

An Indirect Search for Weakly Interacting Massive Particles in the Sun Using Upward-going Muons in NOvA

I present the first Dark Matter search results using the full data set collected with the upward-going muon trigger in NOvA. Weakly Interactive Massive Particles (WIMPs) are a theoretical non-baryonic form of Dark Matter. The nature of Dark Matter is one of the most exciting open questions in modern physics. Though its existence can be inferred by astrophysical evidence, its properties are not yet understood. If we assume that Dark Matter particles can produce Standard Model particles through their interactions, an indirect search can help shed light on this mystery.The NOvA collaboration has built a 14 kton, fine-grained, low-Z, total absorption tracking calorimeter at an off-axis angle to the NuMI neutrino beam. Even though the detector is optimized to observe electron neutrino appearance from a muon neutrino beam, it has a unique potential for more exotic searches given its excellent granularity and energy resolution and relatively low-energy neutrino thresholds. In fact, with an efficient upward-going muon trigger and sufficient background suppression offline, NOvA is capable of a competitive indirect Dark Matter search for low-mass WIMPs.The idea of the upward-going muon trigger is first to select high-quality muon tracks, then use the timing information of all of the hits of each track to estimate directionality. In this way, the background flux is suppressed by more than a factor of 10^5 at trigger level to a rate of approximately 1 Hz. To further optimize this search, we use only upward-going muons that point to the Sun, so our search occurs at night when the Sun is on the other side of the Earth. This strategy also allows us to use the time when the Sun is above the horizon as a control region to estimate the background. Ultimately, implementation of a cut based and maximum likelihood analysis provides a powerful tool for rejecting background and selecting a sample of neutrino-induced upward-going muons. The overall background rejection power achieved by the analysis is substantial and impressive. Starting with approximately 150,000 events per second, we reduced it to 40 events per year. Since no statistically significant excess was found, a 90\% C.L. upper limit on the expected muon flux of upward-going muons has been set using the upper limit on the number of events given the number of observed events in the signal region. Lastly, by assuming the theory behind the upward-going muon flux, a limit on the WIMP-nucleon spin-dependent cross-section in the Sun was estimated. Although the limits on the spin-dependent cross-section do not appear to be competitive with previous indirect Dark Matter searches, the upward-going muon flux limits are promising. The upward-going muon flux limits could extend these results to a broader class of models that are not specific to the dark matter theory but produce upward-going muons, leading to competitive results.

Principato, Cristiana↗
DOE OSTI2020

Computational Optimization of A 3D Printed Collimator

This contribution describes the computational methodology behind an optimization procedure for a scattered beam collimator. The workflow includes producing a file that can be manufactured via additive methods. A conical collimator, optimized for neutron diffraction experiments in a high pressure clamp cell, is presented as an example. In such a case the scattering from the sample is much smaller than that of the pressure cell. Monte Carlo Ray tracing in MCViNE was used to model scattering from a Si powder sample and the cell. A collimator was inserted into the simulation and the number and size of channels were optimized to maximize the rejection of the parasitic signal coming from the complex sample environment. Constraints, provided by the additive manufacturing process as well as a specific neutron diffractometer, were also included in the optimization. The source code and the tutorials are available in c3dp (Islam (2019)).

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2023

ATLAS flavour-tagging algorithms for the LHC Run 2 $pp$ collision dataset

The flavour-tagging algorithms developed by the ATLAS Collaboration and used to analyse its dataset of $\sqrt{s}$ = 13 TeV $pp$ collisions from Run 2 of the Large Hadron Collider are presented. These new tagging algorithms are based on recurrent and deep neural networks, and their performance is evaluated in simulated collision events. These developments yield considerable improvements over previous jet-flavour identification strategies. At the 77% $b$-jet identification efficiency operating point, light-jet (charm-jet) rejection factors of 170 (5) are achieved in a sample of simulated Standard Model $t\bar{t}$ events; similarly, at a $c$-jet identification efficiency of 30%, a light-jet ($b$-jet) rejection factor of 70 (9) is obtained.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition

Over the past decade, the machine learning security community has developed a myriad of defenses for evasion attacks. An understudied question in that community is: for whom do these defenses defend? This work considers common approaches to defending learned systems and how security defenses result in performance inequities across different sub-populations. We outline appropriate parity metrics for analysis and begin to answer this question through empirical results of the fairness implications of machine learning security methods. We find that many methods that have been proposed can cause direct harm, like false rejection and unequal benefits from robustness training. The framework we propose for measuring defense equality can be applied to robustly trained models, preprocessing-based defenses, and rejection methods. We identify a set of datasets with a user-centered application and a reasonable computational cost suitable for case studies in measuring the equality of defenses. In our case study of speech command recognition, we show how such adversarial training and augmentation have non-equal but complex protections for social subgroups across gender, accent, and age in relation to user coverage. We present a comparison of equality between two rejection-based defenses: randomized smoothing and neural rejection, finding randomized smoothing more equitable due to the sampling mechanism for minority groups. This represents the first work examining the disparity in the adversarial robustness in the speech domain and the fairness evaluation of rejection-based defenses.

• Artificial intelligence (AI) / machine learning ↗
DOE OSTI2021

Ultra low background time projection alpha particle detector ( Phase II Final Scientific/Technical Report)

When alpha particles are emitted into a gas they create an ionization track of gas ions and electrons. In our commercial UltraLo instrument we apply a voltage between a planar sample and an anode, integrate the anode signal as it collects the electrons, and distinguish between alphas emitted from the sample and elsewhere (anode, sidewalls) by the duration and shape of the resultant signal. The major contributors limiting the instrument’s lower detection limit are cosmic rays that pass through the detector close to the sample and Rn decays that produce charge tracks the originate in the gas and end on the sample. In this work we proposed to identify and reject these events by converting the anode into a multi-pixel array and operating in time projection mode. Cosmic rays would be eliminated by generating charge on many pixels, while charge collection asymmetry would distinguish between sample events (Bragg curve up) and Rn events (Bragg curve down). We therefore proposed to modify an UltraLo by pixilating its anode, developing low noise, low power multiplexed electronics to track each pixel’s signal individually, and develop analysis software to make the required discriminations.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗