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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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DOE OSTI2018

Drone Video Platform—Collision Avoidance, Situational Awareness, and Communications STL-039-17, Year 2 of 2

At the beginning of FY 2018, the collision avoidance task of this project was dropped because it had become a “commercial off-the-shelf” product for rotary drones, but it was still considered a very difficult problem for fixed wing drones. In the second quarter of FY 2018, R. Trainham took over the project and decided to redirect efforts into testing a variety of sensors on a variety of platforms. The core module task was also dropped from the project because it duplicated what was already available commercially. Since last year’s SDRD final review, we have conducted flight tests in Idaho, Montana, Nevada, and Wisconsin. We have flown five different gamma detectors, a chemical detector and sampler, an optical spectrometer, and a point LIDAR on quadcopters, hexcopters, and the fixed wing T-28 and Sandstorm. We have collaborated with H3D, USI, Virginia Tech, and ORNL. In the coming year, we will continue those collaborations, and will add BYU and INL as collaborators.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2019

SCALE/Sampler Sensitivity Indices

The Sampler sequence of the SCALE code system for random sampling–based uncertainty analyses has recently been extended by including a sensitivity analysis. In uncertainty analyses with respect to uncertainties in the nuclear data, the determination of two multiple correlation coefficients—R2 and SPC2—allows for the identification of nuclide reactions that are significantly contributing to the investigated output uncertainty. Individual nuclide reactions are ranked by importance, allowing suggestions for additional measurements and evaluations to significantly reduce the observed output uncertainty. A brief description of the theory is provided herein, followed by application of this analysis to a sodium-cooled fast reactor pin cell.

Bostelmann, Rike↗

DOE OSTI2021

Automated microbial detection and quantification

A method for automated microbial detection includes collecting air particles into a solid-state sampler, the air particles including microbes, charging the air particles using a plasma field generated by propulsion electrodes, focusing the charged air particles toward a sample well of a microfluidic testing cartridge, tagging the charged air particles with a fluorescence marker, and detecting a quantity of the microbes using a fluorescence detector.

Gilbert, James H.↗

DOE OSTI2021

Optimization Of In-field Alpha Spectrometry For Uranium Enrichment Determination In Uranium Hexafluoride

In response to needs identified by the International Atomic Energy Agency (IAEA) research is underway to develop In-Field Alpha Spectrometry (IFAS) as a method to allow IAEA safeguards inspectors to collect samples of uranium hexafluoride (UF6) at processing facilities to assess and verify uranium enrichment. For sample collection, the IFAS method uses Single-Use Destructive Assay (SUDA) samplers, which contain thin zeolite coatings that trap UF6 gas and convert it to the safer, more stable form uranyl fluoride (as a dihydrate, UO2F2·2H2O). For alpha spectrometry, the IFAS instrument employs a large area silicon semiconductor transducer to detect and record alpha particle energy-deposition events. Over the past year optimization work has significantly increased the diameter of useful SUDA samples (from 12.7 mm to 48 mm), improved the manufacturability and reproducibility of SUDA samples, increased the area of the IFAS alpha spectrometer sensor from 1.2 cm to 3.1 cm, and improved source positioning within the IFAS. This paper will report on this optimization work, its impacts on IFAS performance, and future plans for IFAS miniaturization, improvements, and testing.

Chichester, David↗

DOE OSTI2021

Sensor for infrared communication using plant nanobionics

A living plant can function as self-powered auto-samplers and preconcentrators of an analyte within ambient groundwater, detectors of the analyte contained therein. For example, a pair of near infrared (IR) fluorescent sensors embedded within the mesophyll of the plant leaf can be used as detectors of the nitroaromatic molecules, with the first IR channel engineered through CoPhMoRe to recognize analyte via an IR fluorescent emission and the second IR channel including a functionalized nanostructure that acts as an invariant reference signal.

Strano, Michael S.↗

DOE OSTI2023

Design and Operation of a Multi-Bed Catalytic Micro-Reactor for the Study of Co-Processing of Bio-Oils with VGO

An industry wide shift from fossil-based fuel to renewable fuel sources including biomass, municipal waste, and plastics will require new process monitoring methods to minimize transitional risks including off specification product formation and catalyst deactivation. This project aims to provide a machine learning based process monitoring tool composed of online, slipstream mass spectra for use in biomass refineries and co-processing in existing refineries allowing operators to monitor product qualities and adjust process conditions accordingly. In order to maximize the robustness of the tool, large volumes of data must be collected to fine tune model parameters which consists of both micro and pilot scale mass spectral data. Micro-scale data is collected with a multi-tube micro-reactor housing up to six catalysts in horizontal beds, coupled with a molecular beam mass spectrometer. A pyrolizer equipped with an auto-sampler streamlines the micro-scale data collection process. This type of pyrolizer/micro-reactor configuration does not exist on the market, and therefore had to be created for the purposes of this project. The design and commissioning of this reactor will be presented in detail. This reactor set-up is highly flexible and increases throughput of analysis. For catalyst testing, each bed can be individually selected simply by turning valves. For catalyst reduction and regeneration, simultaneous flow through all six beds is used. The reproducibility of the system was first assessed with whole biomass pyrolysis along with pyrolysis of calibration standards. Initial work on this system evaluated two FCC catalysts, equilibrium catalyst (E-cat), and a proprietary catalyst from Johnson Matthey specifically design for co-processing of bio-oil with vacuum gas oil (VGO). This work used model compounds and VGO which illuminated differences in products produced by the catalysts.

biomass↗

DOE OSTI2022

Magnetically coupled loading chamber and apparatus for in situ MAS NMR: operating under either high or low pressure

A sample chamber holder for MAS-NMR capable of operating at both low and high pressures. In one example the sample chamber holder is made up of a sample holder body defining a sample chamber therein, a connector configured to operatively statically hold an in situ rotor within the sample chamber; a coupler configured to operatively connect the sampler holder body to a magnetically coupled rotation member. The magnetically coupled rotation member is configured to engage and rotate a sealing cap from an NMR rotor in such a way so as to allow an NMR cap to be alternatively opened or sealed in-situ while the NMR rotor remains statically positioned in an NMR device.

Hu, Jian Z.↗

DOE OSTI2023

Status of Error Correction Studies in Support of FFA@CEBAF

In this work, we examine the beam correction requirements for the FFA@CEBAF energy upgrade. Both hardware and software diagnostic and corrector components are under investigation; in particular the relationship between hardware and software optimization will be developed. To generate a representative sample of errors---from the machine lattice and other beam properties---we construct a Markov Chain Monte Carlo (MCMC) sampler which considers different probability distributions for different types of errors. This sample is used to investigate the statistical sensitivity of the beam to various diagnostic and corrective schema. Once statistics are acquired, we plan to use a variety of optimization techniques to minimize correction time for the electron beam in the FFA arcs designed for the CEBAF upgrade.

Benesch, J.↗

DOE OSTI2017

Radon Fluxes from an Earthen Barrier Over Uranium Mill Tailings After Two Decades of Service - 17234

Radon (Rn) fluxes were measured at a disposal facility for uranium mill tailings after two decades of service. The facility was closed with an earthen cover vegetated with grasses. Measurements were made on the surface of the Rn barrier and directly on the surface of the tailings. Fluxes were measured using extra small (area = 0.018 m{sup 2}), small (0.071 m{sup 2}), medium (0.59 m{sup 2}), and large (2.32 m{sup 2}) flux chambers to evaluate the impact of measurement scale on Rn flux. Activated carbon (AC) passive collectors and electric radon detectors (RAD7) were used to measure Rn concentrations. Tests were conducted at various locations on each cover representing conditions that can lead to different levels of soil structural development and different water content. Rn fluxes at the surface of the Rn barrier were much lower than Rn fluxes measured at the surface of the tailings, indicating the barrier remained effective for Rn containment. Geometric mean Rn fluxes measured at the surface of the Rn barrier in each test pit were below the regulatory requirement (0.74 Bq/m{sup 2}- s). Rn concentrations measured using AC samplers in the flux chambers were 60% of concentrations measured using the RAD7, on average, and Rn fluxes computed with the AC data were 9% of those computed with the RAD7 data, on average. Size of the flux chamber had no systematic effect on Rn flux, indicating that 20 y of soil forming processes had not created a pore network causing scale-dependent Rn flux. Geometric mean Rn fluxes in the test pits were similar regardless of differences in surface conditions (vegetation, thickness of soil cover) known to influence soil forming processes and soil structure, but were lower in areas where surface conditions promoted higher water content in the Rn barrier. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Experience on Safety Review of Liquid and Gaseous Effluent Monitoring System for Nuclear Power Plants in Korea - 16237

The liquid and gaseous effluent monitoring systems are important components in order to evaluate and minimize the radiation environmental impacts from Nuclear Power Plants (NPPs). Therefore, licensee should install liquid and gaseous effluent monitoring systems and these systems should be reviewed by regulatory body. In Korea, the criteria of liquid and gaseous effluent monitoring systems for NPPs are stipulated in Nuclear Safety Act (NSA) and subordinate statute, and it is stated in 'Regulation on Technical Standards for Nuclear Reactor Facilities, etc.' that 'Instrumentation shall be provided to monitor related variables, including the following, and systems over their anticipated ranges of normal operations, anticipated operational occurrences, and accident conditions'. RG-1.97(Rev. 3, 1983) of US Nuclear Regulatory Commission (NRC) was used as criterion for accident monitoring instrumentations for NPPs in Korea. Licensee, however, started to apply RG-1.97(Rev. 4, 2006) as new criterion for accident monitoring instrumentation of the Construction Permit (CP) of new NPPs (Shin-kori Unit 5 and 6). Licensee submitted the report for type selection criteria and this report shows selection criteria of from 'Type A variables' to 'Type E variables'. Licensee of Korea has plans to submit the validation report regarding the criteria for accident monitoring instrumentation during Operation License (OL) and regulatory body of Korea also will conduct safety review of these reports. A graded approach to establishing a sampling program is required in ANSI/HPS N13.1-1999. Because deaerator release pipe of Shin-kori unit 5, 6 was integrated into condenser vacuum system release pipe, regulatory body reviewed application of a graded approach on this integration. Output of PWR GALE shows that iodine released from turbine building is 0.12% of total iodine release amount and this value is potential impact categories (PICs) 3 in ANSI/HPS N13.1-1999. So, periodic sampler installed in condenser vacuum system release pipe in Shin-kori unit 5, 6 is suitable. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2017

Determination of critical experiment correlations for experiments involving arrays of low-enriched fuel rods

Quantifying correlations among critical experiments has become a topic of interest over the last 10-15 years. Correlations arise from the shared use of fissile material, non-fissile materials, fixtures, and procedures in multiple experiments or multiple experiment series. A Monte-Carlo sampling technique proposed as a viable technical method to evaluate these correlations has been implemented in the SCALE 6.2 Sampler sequence. This paper presents an investigation of the use of this new tool and technique for low-enriched uranium pin array experiments with a thermal neutron energy spectrum. The Nuclear Energy Agency's Expert Group on Uncertainty Analyses for Criticality Safety Assessments has been examining methods of calculating the correlation coefficients among experiments from the LCT-007 and LCT-039 series. Results for two scenarios are presented to demonstrate the impact of pin pitch uncertainty modeling on the correlation coefficients. The convergence of the correlation coefficients is also investigated. Additional studies examine the impact of the stochastic uncertainty and the use of continuous-energy Monte-Carlo for individual realizations on the correlation coefficients. Correlation coefficients are also determined for the LCT-042 experiment series. This experiment series differs from other experiments because unique poison panels and fuel array separation distances may reduce correlation of the individual experiments within the series. The effects of pin pitch uncertainty and stochastic uncertainty are also examined for this series. Comparing the results of the two sets of experiments shows potential conclusions that can be drawn regarding viability of the Monte-Carlo sampling technique for determining critical experiment correlations. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2019

Experiments and Simulation of a Borehole in Salt to Understand Heat, Brine, and Vapor Migration - 19192

Disposition of heat-generating nuclear waste (HGNW) remains a continuing technical and sociopolitical challenge. Numerous concepts for HGNW management have been proposed and examined internationally, including an extensive focus on geologic disposal. One proposed geologic material is salt because of its low permeability and viscoplastic deformation that causes self-repair of damage done to the salt by waste emplacement activities. Evaluating the safety and technical challenges of storing HGNW in a salt repository is an ongoing process involving experiments and supporting numerical simulation. Currently an experiment is underway at the Waste Isolation Pilot Plant (WIPP) to explore how the presence of a heat generating source affects phenomena such as brine migration, vapor transport, and mechanical changes to the bedded salt. A sub-horizontal heated borehole test is in progress in the underground at the WIPP that includes a centrally located 10.2 cm diameter borehole with an adjustable heater surrounded with smaller diameter boreholes instrumented with thermocouples. The central borehole contains an inflatable packer, heating block, brine sampler, and constantly flowing nitrogen gas circulation system. Air-injection tests performed in the central borehole provide pressure measurements that are used to constrain permeability of the system. The steady-state temperatures, as well as the rise and fall of temperature when the heater is cycled on and off, have been measured for up to 60 days. In the borehole, dry nitrogen gas circulation evaporates water and outflows to a desiccant container where water mass is measured daily during the experiment to quantify vapor removal. Although this test is a 'shake-down' for a planned second round of fresh borehole testing, we have gathered a rich dataset. These data allow us to build simulations using the Finite Element Heat and Mass transfer code (FEHM) to evaluate the experimental results, determine field-scale parameters, and identify code improvements to reproduce important physical processes that may not be accounted for at present. A 3-D numerical mesh, built using LaGrit software (lagrit.lanl.gov; Miller et al., 2007), includes increasing resolution around the central borehole. Modeling of the experiment allows for determining the local thermal conductivity and permeability of any damaged bedded salt around the borehole, where damage from drilling may change the permeability, porosity and saturation conditions, by parameter testing and inverse methods. Additionally, assumptions about brine and vapor flow and transport are being tested by comparing measured and simulated results. The combination of experimental data and model results provide additional data to help support the safety case for safe and effective HGNW disposition in bedded salt formations. Initial results from this experiment show that water flow into the borehole is within previous experimental results. Further, we have found that the design of the heater block is restricting energy to flow into the rock salt. Thus, this test has proven useful in design of the next generation experiment where infrared heating may be used to bypass issues caused by air gaps located around the current stainless steel block heater. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2023

Adaptive, Active Learning, and Multifidelity Monte Carlo Methods in the MOOSE Stochastic Tools Module

MOOSE is an open-source computational platform for constructing multi-physics models and executing them in a massively parallel fashion. It has a stochastic tools module (STM) for forward/inverse uncertainty quantification (UQ) and surrogate modeling. This presentation details some recent developments to the STM with respect to the implementation of adaptive, active learning, and multifidelity Monte Carlo methods for forward UQ of computational models. Specifically, the adaptive Monte Carlo methods include Markov Chain Monte Carlo (MCMC)-driven algorithms like adaptive importance sampling and parallelized subset simulation for statistical QoI estimation, rare events analysis, and stochastic gradient-free optimization. The active learning methods include Gaussian Process (GP) surrogates and their training via Adam optimization, design of acquisition functions, and integration with samplers like Monte Carlo, adaptive importance, and parallelized subset simulation. These active learning methods are also designed to work in a batch mode, wherein, the required calls to the full computational model are executed in parallel whenever a user-specified batch size is met. The multifidelity methods in STM are broadly divided into two categories: hierarchical, where a defined hierarchy exists among the low-fidelity models, and peer, where all the low-fidelity models are treated equally. A GP surrogate is used to learn the differences between the low- and high-fidelity models in both multifidelity categories, and acquisition functions from the active learning classes are used to decide whether to rely on a low-fidelity model or call the expensive high-fidelity model. Alongside the software description and usage, applications are also presented to nuclear engineering computational models including a TRISO nuclear fuel particle, a reactor pressure vessel, and a heat-pipe microreactor.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2023

Bayesian Inference with Latent Hamiltonian Neural Networks (L-HNNs)

When sampling for Bayesian inference, one popular approach is to use Hamiltonian Monte Carlo (HMC) and the No-U-Turn Sampler (NUTS). However, HMC and NUTS can require numerous numerical gradients of the target density and can prove slow in practice. We propose Hamiltonian neural networks (HNNs) with HMC and NUTS for solving Bayesian inference problems [1, 2]. Once trained, HNNs do not require gradients of the target density while sampling. Moreover, they satisfy important properties such as perfect time reversibility and Hamiltonian conservation, making them well suited for use within HMC and NUTS because stationarity can be shown. We also propose an HNN extension called latent HNNs (L-HNNs), which predict latent variable outputs. Compared to HNNs, L-HNNs offer improved expressivity and a reduction in integration errors. Finally, we propose employing L-HNNs in NUTS with an online error monitoring scheme to prevent degeneracy of the sampling in regions of low probability density. We demonstrate L-HNNs in NUTS with online error monitoring by using several example cases involving complex, heavy-tailed, and high local curvature probability densities. Overall, L-HNNs in NUTS with online error monitoring satisfactorily inferred these probability densities. Compared to traditional NUTS, L-HNNs in NUTS with online error monitoring improved the effective sample size (ESS) per gradient by an order of magnitude.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Optical encoder devices and systems

Devices, systems and methods for encoding information using optical components are described. An example photonic filtered sampler includes a spectral shaper configured to receive an optical pulse train, a dispersive element positioned to receive an output of the spectral shaper and to expand spectral contents thereof in time, and a modulator configured to receive an output of the dispersive element and a radio frequency (RF) signal, and to produce a modulated output optical signal in accordance with the RF signal. In this configuration, one or more characteristics of the modulated output optical signal is determined based on a spectral shape provided by the spectral shaper and dispersive properties of the dispersive element.

Buckley, Brandon Walter↗

DOE OSTI2021

Optimization of In-Field Alpha Spectrometry for Uranium Enrichment Determination in Uranium Hexafluoride

In response to needs identified by the International Atomic Energy Agency (IAEA) research is underway to develop In-Field Alpha Spectrometry (IFAS) as a method to allow IAEA safeguards inspectors to collect samples of uranium hexafluoride (UF6) at processing facilities to assess and verify uranium enrichment. For sample collection, the IFAS method uses Single-Use Destructive Assay (SUDA) samplers, which contain thin zeolite coatings that trap UF6 gas and convert it to the safer, more stable form uranyl fluoride (UO2F2). For alpha spectrometry, the IFAS instrument employs a large area silicon semiconductor transducer to detect and record alpha particle energy-deposition events. Over the past year optimization work has significantly increased the diameter of useful SUDA samples (from 12.7 mm to 48 mm), improved the manufacturability and reproducibility of SUDA samples, increased the area of the IFAS alpha spectrometer sensor from 1.2 cm to 3.1 cm, and improved source positioning within the IFAS. This paper will report on this optimization work, its impacts on IFAS performance, and future plans for IFAS miniaturization, improvements, and testing.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗