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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

A methodology for decay heat characterization in molten salt reactors

Accurate decay heat prediction in molten salt reactors (MSRs) faces dual challenges: complex operational uncertainties and the need for interpretable models compatible with engineering workflows. This work presents a hybrid machine learning and segmented polynomial methodology that addresses both requirements through three key innovations. First, a modular data architecture encodes MSR-specific operational parameters (power density: 1-100 W cm -3 , humidity: 0-0.1 wt %, air ingress: 0-0.1 mol %) with uncertainty-aware temporal discretization spanning 15 orders of magnitude. Second, region-optimized machine learning models achieve 92.3 % root mean square error (RMSE) reduction over conventional polynomials while maintaining physical interpretability through automated piecewise equation generation. Third, dual front-end interfaces accelerate safety analyses — a Jupyter environment enables researchers to explore 10,000+ parameter combinations via interactive widgets, while a Streamlit web application reduces design iteration cycles through production-grade visualization tools. Operational deployment demonstrates prediction times of only a couple hundred milliseconds for 10 4 years decay profiles, enabling real-time optimization of spent fuel container designs.

42 - ENGINEERING↗
DOE OSTI2026

Characterization of Organosulfates and Organonitrates in Vertically Resolved Aerosols over the Southern Great Plains Field Campaign Report

Aerosol is the largest individual source of uncertainty in assessing the Earth’s radiative balance due to poorly understood aerosol processes and aerosol-cloud interactions. Thus, to constrain aerosol’s climate impacts, it is critical to understand aerosol compositions at high elevations. Organic material accounts for about 20-80% of total aerosol mass in the atmosphere and is known to play a key role in aerosol processes and cloud formation. In prior research, characterization of aerosol molecular composition has been mostly carried out at ground level. In these ground-level measurements, total speciated organosulfates and organonitrates may contribute significantly to organic aerosol mass on the order of 10-40%, most of which are from abundant biogenic volatile organic compounds such as isoprene and monoterpenes. Organosulfates and organonitrates have also been shown to be present in substantial amounts in cloud water, suggesting that they can be transported and/or directly formed at high elevations. On the other hand, the less common and more expensive aircraft studies have performed high-altitude measurements, but were often limited in the number of different altitudes sampled and in sample collection under consistent conditions. Therefore, the vertical distributions of key aerosol components such as organosulfates and organonitrates are not well understood and have not been extensively studied. Nevertheless, it is important to understand how organosulfates and organonitrates in aerosols are distributed, transformed, participate in aqueous-phase processes, and interact with high-altitude clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Disentangling the Black Hole Mass Spectrum with Photometric Microlensing Surveys

Abstract From the formation mechanisms of stars and compact objects to nuclear physics, modern astronomy frequently leverages surveys to understand populations of objects to answer fundamental questions. The population of dark and isolated compact objects in the Galaxy contains critical information related to many of these topics, but is only practically accessible via gravitational microlensing. However, photometric microlensing observables are degenerate for different types of lenses, and one can seldom classify an event as involving either a compact object or stellar lens on its own. To address this difficulty, we apply a Bayesian framework that treats lens type probabilistically and jointly with a lens population model. This method allows lens population characteristics to be inferred despite intrinsic uncertainty in the lens class of any single event. We investigate this method’s effectiveness on a simulated ground-based photometric survey in the context of characterizing a hypothetical population of primordial black holes (PBHs) with an average mass of 30 M ⊙ . On simulated data, our method outperforms current black hole (BH) lens identification pipelines and characterizes different subpopulations of lenses while jointly constraining the PBH contribution to dark matter to ≈25%. Key to robust inference, our method can marginalize over population model uncertainty. We find the lower mass cutoff for stellar origin BHs, a key observable in understanding the BH mass gap, particularly difficult to infer in our simulations. This work lays the foundation for cutting-edge PBH abundance constraints to be extracted from current photometric microlensing surveys.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Preliminary Design of Critical Experiments Involving Commercially Available B 4 C Neutron Absorber Plates with Low-Enriched UO 2 Fuel

The International Criticality Safety Benchmark Evaluation Project (ICSBEP) is an initiative to provide high-quality benchmark data in a standardized format for criticality safety analysts to use to validate calculational tools and nuclear data. In the last released 2022 version, the ICSBEP handbook contains over 5,000 critical experiment descriptions, results, and associated models. This paper describes the critical configurations proposed and calculations performed as part of the conceptual design phase of Integral Experiment Request (IER) 554 (IER-554). The goal of IER-554 is to add to the benchmark experiments available to the criticality safety community by designing critical experiments that can analyze how adding commercially available Boralcan plates to an assembly of low-enriched UO2 fuel rods affects the effective neutron multiplication factor (k eff ). Boralcan, a neutron absorber product developed by Rio Tinto, is made of B4C in an Al 1100 matrix and is commonly used for criticality suppression in fuel storage pools. In the current version of the ICSBEP handbook, only a few dated critical experiments involve B4C materials, and none involve Boralcan in a thin plate shape. The experiments designed as part of IER-554 are intended to be performed at the Sandia Pulsed Reactor Facility/Critical Experiments (SPRF/CX) apparatus at Sandia National Laboratories. SPRF/CX is a well-characterized assembly considered trustworthy by the benchmarking community because of the numerous high-quality evaluations with very low experimental uncertainties included in the ICSBEP handbook. Figure 1 illustrates the assembly for a particular configuration from LCT-078, one of the published benchmarks in the ICSBEP handbook. The experiments will be moderated and reflected by light water at ambient atmospheric pressure. Before the plates are inserted in the critical assembly, they will be characterized with x-ray computed tomography (XCT) to identify the sizes and distribution of the B 4 C powder particles inside the plates. The preliminary design calculations were performed with SCALE 6.3.0 using the KENO V.a sequence for the criticality calculations, the CE-TSUNAMI-3D sequence for the sensitivity and uncertainty studies, and the ENDF/B-VII.1 Continuous Energy cross section library. All the calculation results presented have 10 pcm statistical uncertainties. A set of critical experiments with Boralcan plates could increase the confidence of the criticality safety community in its modeling methods when using this type of neutron absorber material. Experiments would also help validate k eff calculations, and the industry could use these validations to change the B loading credit limits from the US Nuclear Regulatory Commission standard review plan for dry cask storage of spent nuclear fuel. This paper summarizes only part of the analysis documented in the preliminary design report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Synchrotron radiography of Richtmyer–Meshkov instability driven by exploding wire arrays

We present a new technique for the investigation of shock-driven hydrodynamic phenomena in gases, liquids, and solids in arbitrary geometries. The technique consists of a pulsed power-driven resistive wire array explosion in combination with multi-MHz synchrotron radiography. Compared to commonly used techniques, it offers multiple advantages: (1) the shockwave geometry can be shaped to the requirements of the experiment, (2) the pressure (P > 300 MPa) generated by the exploding wires enables the use of liquid and solid hydrodynamic targets with well-characterized initial conditions (ICs), (3) the multi-MHz radiography enables data acquisition to occur within a single experiment, eliminating uncertainties regarding repeatability of the ICs and subsequent dynamics, and (4) the radiographic measurements enable estimation of compression ratios from the x-ray attenuation. In addition, the use of a synchrotron x-ray source allows the hydrodynamic samples to be volumetrically characterized at a high spatial resolution with synchrotron-based microtomography. This experimental technique is demonstrated by performing a planar Richtmyer–Meshkov instability (RMI) experiment on an aerogel–water interface characterized by Atwood number A0∼−0.8 and Mach number M∼1.5. The qualitative and quantitative features of the experiment are discussed, including the energy deposition into the exploding wires, shockwave generation, compression of the interface, startup phase of the instability, and asymptotic growth consistent with Richtmyer's impulsive theory. Additional effects unique to liquids and solids—such as cavitation bubbles caused by rarefaction flows or initial jetting due to small perturbations—are observed. It is also demonstrated that the technique is not shape dependent by driving a cylindrically convergent RMI experiment.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Processing Aleatory and Epistemic Uncertainties in Experimental Data From Sparse Replicate Tests of Stochastic Systems for Real-Space Model Validation

This paper presents a practical methodology for propagating and processing uncertainties associated with random measurement and estimation errors (that vary from test-to-test) and systematic measurement and estimation errors (uncertain but similar from test-to-test) in inputs and outputs of replicate tests to characterize response variability of stochastically varying test units. Also treated are test condition control variability from test-to-test and sampling uncertainty due to limited numbers of replicate tests. These aleatory variabilities and epistemic uncertainties result in uncertainty on computed statistics of output response quantities. The methodology was developed in the context of processing experimental data for “real-space” (RS) model validation comparisons against model-predicted statistics and uncertainty thereof. The methodology is flexible and sufficient for many types of experimental and data uncertainty, offering the most extensive data uncertainty quantification (UQ) treatment of any model validation method the authors are aware of. It handles both interval and probabilistic uncertainty descriptions and can be performed with relatively little computational cost through use of simple and effective dimension- and order-adaptive polynomial response surfaces in a Monte Carlo (MC) uncertainty propagation approach. A key feature of the progressively upgraded response surfaces is that they enable estimation of propagation error contributed by the surrogate model. Sensitivity analysis of the relative contributions of the various uncertainty sources to the total uncertainty of statistical estimates is also presented. Finally, the methodologies are demonstrated on real experimental validation data involving all the mentioned sources and types of error and uncertainty in five replicate tests of pressure vessels heated and pressurized to failure. Simple spreadsheet procedures are used for all processing operations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Coal Fired Power Plant Configuration and Operation Impact on Plant Effluent Contaminants and Conditions

The primary objective of this project is to characterize coal contaminants in coal-fired power plant wastewater as a function of coal type, unit configurations, and unit operation profile with uncertainty analysis. This project was in response to the U.S. Department of Energy (DOE) Solicitation DE-FOA-0001842. The project duration was between September 01, 2018, and December 31, 2021 (no-cost extension filed, due to the Covid-19 pandemic restrictions, and approved). Field and lab test program was conducted with the main goal to characterize coal contaminants in coal-fired power plant wastewater as a function of coal type, unit configurations, and unit operation profile with uncertainty analysis. In this project, the team of Lehigh University (prime recipient) and Western Kentucky University identified two suitable Thermoelectric Power Plants (TTPs) firing bituminous and sub-bituminous coals respectively, designed test plans, and performed sample collection. Sampling included coal from each TTPs power generation units, Wet Flue Gas Desulfurization (WFGD) slurry material and waste-water samples taken from the outlet of the water treatment tank prior to discharge and other pertinent locations. Coal samples are dried, crushed, and pulverized according to the American Society for Testing and Materials (ASTM) methods. The prepared coal samples are analyzed for normal proximate and ultimate analysis tests in addition to the toxic metals and anions according to ASTM methods. The FGD slurry materials are analyzed for toxic metals and anions according to Electric Power Research Institute (EPRI) or Environmental Protection Agency (EPA) methods, as appropriate. The wastewater samples from the water treatment tank outlet are analyzed for toxic metals and anions according to EPA methods. The effluent species analyzed include mercury, arsenic, selenium, nitrate/nitrite, bromide, and chlorine. This project provided results of effluent conditions as a function of coal type, unit configuration, and unit operation profile, and identified the levels of uncertainty in the effluent results.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2021

Distribution System State Estimation With High Penetration of Demand Response Enabled Loads

Demand-side operations incentivize utility customers to take part in various grid services. A demand response enabled load (DREL) is a flexible grid asset that schedules electricity consumption in response to a time-of-use (TOU) energy price. Consequently, its energy profile differs from that of a conventional load that is insensitive to price. This difference may cause new challenges for distribution system state estimation (DSSE). It is well known that DSSE often needs to use pseudo-measurements based on historic load profiles to increase system observability. However, historic profiles of conventional loads are not representative of DREL behaviors. Additionally, the inaccuracy impacts DSSE results and other DSSE-dependent operations. In this paper, we propose an online pseudo-measurement generation approach for DSSE with DRELs. We formulate an optimization model to represent DRELs self-adjusting actions. Sampling-based stochastic optimization techniques are proposed to account for uncertainties in DRELs. A set of representative DREL behavior data corresponding to the samples are used to characterize DREL pseudo-measurements. Case studies with modified IEEE 123-bus test system verify the validity of the proposed work.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Characterizing Performance of Freshwater Wetland Methane Models Across Time Scales at FLUXNET-CH 4 Sites Using Wavelet Analyses

Process-based land surface models are important tools for estimating global wetland methane (CH 4 ) emissions and projecting their behavior across space and time. So far there are no performance assessments of model responses to drivers at multiple time scales. In this study, we apply wavelet analysis to identify the dominant time scales contributing to model uncertainty in the frequency domain. We evaluate seven wetland models at 23 eddy covariance tower sites. Our study first characterizes site-level patterns of freshwater wetland CH 4 fluxes (FCH 4 ) at different time scales. A Monte Carlo approach was developed to incorporate flux observation error to avoid misidentification of the time scales that dominate model error. Our results suggest that (a) significant model-observation disagreements are mainly at multi-day time scales (<15 days); (b) most of the models can capture the CH 4 variability at monthly and seasonal time scales (>32 days) for the boreal and Arctic tundra wetland sites but have significant bias in variability at seasonal time scales for temperate and tropical/subtropical sites; (c) model errors exhibit increasing power spectrum as time scale increases, indicating that biases at time scales <5 days could contribute to persistent systematic biases on longer time scales; and (d) differences in error pattern are related to model structure (e.g., proxy of CH 4 production). Our evaluation suggests the need to accurately replicate FCH 4 variability, especially at short time scales, in future wetland CH 4 model developments.

58 GEOSCIENCES↗
DOE OSTI2023

An uncertainty-aware strategy for plasma mechanism reduction with directed weighted graphs

In this work, we present a framework for the analysis and reduction of plasma mechanisms by means of weighted directed graphs, in which reactions and species are both treated as nodes. The methodology consists of two distinct analyses. The first, which is qualitative, relies on graph spatializations via force-directed algorithms to discover the predominant global patterns in the chemical model. The second ranks the reactions based on their shortest paths' lengths from/to the species of interest and their relative contributions to the power balance. Further, this quantitative investigation enables a strategy for mechanism reduction that is fully automatized, as it does not require any expert knowledge, highly effective, as it generates reduced mechanisms that are highly accurate while relying on a small number of processes, and easily interpretable, as the algorithm justifies the importance of the retained reactions by outputting their related chemical pathways. Additionally, the work proposes a methodology extension that employs ensembles of graphs to improve the robustness of the reduced mechanism to reaction parameter uncertainties. The approach, here tested for steady-state predictions of a plasma system characterizing negative hydrogen ion sources, is general and can be used in a wide variety of applications outside the particular nuclear fusion context demonstrated in this work.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Review of High‐Speed Digital Image Correlation: Advancements and Good Practices

This paper reviews the current state of the art in high‐speed (HS) and ultrahigh‐speed (UHS) digital image correlation (DIC) techniques, emphasizing their critical role in experimental research across various scientific domains. HS and UHS DIC have evolved significantly, driven by advancements in camera systems, image processing algorithms and experimental methodologies. These developments have opened new avenues for capturing and analysing dynamic events with unprecedented temporal and spatial detail, but not without introducing challenges such as optical distortions, motion blur and lighting issues that can affect measurement quality. This review advocates for standardized reporting practices in HS/UHS DIC methodologies to improve reproducibility and reliability across studies, drawing on guidelines from the International Digital Image Correlation Society (iDICs). Through a comprehensive analysis of over 150 articles, this review identifies key advancements in imaging technology and their application in six research domains: material characterization, test development, fracture mechanics, model validation, ballistic and explosive phenomena assessment and measurement uncertainties. Distinctions between two‐dimensional (2D) and stereo‐DIC applications are explored, offering insights into their practical implementation and trade‐offs. Good practices for HS/UHS DIC applications are proposed along with suggestions for future directions for this evolving field, highlighting the indispensable role of technological innovation in expanding the capabilities of optical metrology.

experimental mechanics↗
DOE OSTI2023

Binary pseudo-random array (BPRA) for inspection and calibration for cylindrical wavefront interferometry

High-accuracy metrology is vitally important in manufacturing ultra-high-quality free-form mirrors designed to manipulate X-ray light with nanometer-scale wavelengths. However, surface topography measurements are instrument dependent, and without the knowledge of how the instrument performs under the practical usage conditions, the measured data contain some degree of uncertainty. Binary Pseudo Random Array (BPRA) “white noise” artifact are effective and useful for characterizing the Instrument Transfer Function (ITF) of surface topography metrology tools and wavefront measurement instrument. BPRA artifact contains features with all spatial frequencies in the instrument bandpass with equal weight. As a result, power spectral density of the patterns has a deterministic white-noise-like character that allows direct determination of the ITF with uniform sensitivity over the entire spatial frequency range. The application examples include electron microscopes, x-ray microscopes, interferometric microscopes, and large field-of-view Fizeau Interferometers. Furthermore, we will introduce the application of BPRA method to characterizing the ITF of Cylindrical Wavefront Interferometry (CWI), by developing the BPRA artifact which matches the radius of curvature of the cylindrical wavefront. The data acquisition and analysis procedures for different applications of the ITF calibration technique developed are also discussed.

Munechika, K↗
DOE OSTI2020

NASA’s first ground-based Galactic Cosmic Ray Simulator: Enabling a new era in space radiobiology research

With exciting new NASA plans for a sustainable return to the moon, astronauts will once again leave Earth’s protective magnetosphere only to endure higher levels of radiation from galactic cosmic radiation (GCR) and the possibility of a large solar particle event (SPE). Gateway, lunar landers, and surface habitats will be designed to protect crew against SPEs with vehicle optimization, storm shelter concepts, and/or active dosimetry; however, the ever penetrating GCR will continue to pose the most significant health risks especially as lunar missions increase in duration and as NASA sets its aspirations on Mars. The primary risks of concern include carcinogenesis, central nervous system (CNS) effects resulting in potential in-mission cognitive or behavioral impairment and/or late neurological disorders, degenerative tissue effects including circulatory and heart disease, as well as potential immune system decrements impacting multiple aspects of crew health. Characterization and mitigation of these risks requires a significant reduction in the large biological uncertainties of chronic (low-dose rate) heavy-ion exposures and the validation of countermeasures in a relevant space environment. Historically, most research on understanding space radiation-induced health risks has been performed using acute exposures of monoenergetic single-ion beams. However, the space radiation environment consists of a wide variety of ion species over a broad energy range. Using the fast beam switching and controls systems technology recently developed at the NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratory, a new era in radiobiological research is possible. NASA has developed the “GCR Simulator” to generate a spectrum of ion beams that approximates the primary and secondary GCR field experienced at human organ locations within a deep-space vehicle. The majority of the dose is delivered from protons (approximately 65%–75%) and helium ions (approximately 10%–20%) with heavier ions (Z ≥ 3) contributing the remainder. The GCR simulator exposes state-of-the art cellular and animal model systems to 33 sequential beams including 4 proton energies plus degrader, 4 helium energies plus degrader, and the 5 heavy ions of C, O, Si, Ti, and Fe. A polyethylene degrader system is used with the 100 MeV/n H and He beams to provide a nearly continuous distribution of low-energy particles. A 500 mGy exposure, delivering doses from each of the 33 beams, requires approximately 75 minutes. To more closely simulate the low-dose rates found in space, sequential field exposures can be divided into daily fractions over 2 to 6 weeks, with individual beam fractions as low as 0.1 to 0.2 mGy. In the large beam configuration (60 × 60 cm 2 ), 54 special housing cages can accommodate 2 to 3 mice each for an approximately 75 min duration or 15 individually housed rats. On June 15, 2018, the NSRL made a significant achievement by completing the first operational run using the new GCR simulator. This paper discusses NASA’s innovative technology solution for a ground-based GCR simulator at the NSRL to accelerate our understanding and mitigation of health risks faced by astronauts. Ultimately, the GCR simulator will require validation across multiple radiogenic risks, endpoints, doses, and dose rates.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Long-Term Methane Emissions Rate Quantification and Alert System for Natural Gas Storage Wells and Fields

The Department of Energy (DOE) National Energy Technology Laboratory (NETL) and other critical stakeholders (e.g., U.S. Environmental Protection Agency (USEPA), state regulators, and industry) seek to more accurately characterize and quantify methane emissions from natural gas storage wells. These efforts will reduce uncertainties in estimates of these emissions in USEPA’s current Green House Gas Inventory (GHGI) under their Greenhouse Gas Reporting Program (GHGRP; EPA, 2016). Emission factors currently used to estimate methane emissions from gas storage wells are the same factors used for onshore natural gas production wells (USEPA, 2016). This study has developed a robust and representative dataset of emissions from disaggregated gas station wellhead components and related emission factors that will inform future enhancements to the GHGI and GHGRP. Extensive methane emissions measurements and meteorological data were collected from three active storage facilities representing two of the three types of storage facilities (i.e., depleted gas reservoir and salt cavern) to support development of emissions factors specifically for gas storage wells and associated components. Methane emissions were quantified from both above-ground components (e.g., pipe fittings and valves) and seepage from the ground surface in proximity to gas storage wellheads.

03 NATURAL GAS↗
DOE OSTI2020

LA17-V-InverseRadTransportProblem-PD2Kb. Final Project Report

In the inverse radiation transport problem, a radiation signal emanating from an unknown object is used to reconstruct geometric and material parameters of the object , e.g., the mass of special nuclear material (SNM), the isotopic composition of the SNM (e.g., the enrichment of 235U), the thickness of shielding, etc. The inverse radiation transport problem is one of the most fundamental and important in the emergency response mission, and has been addressed in previous NA-22 and NA-42/84 investments by using derivative-free optimization methods. Our project was aimed at (i) consolidating previous work by applying polynomial chaos expansion (PCE) for reducing significantly the number of forward model simulations required by derivative-free optimization methods; (ii) developing a general-purpose framework and stand-alone software for solving the inverse radiation transport problem by applying a new “predictive modeling” methodology (predictive modeling of coupled multi-physics systems, PM_CMPS) which enables the fusing of experimental and computational information; and (iii) developing several benchmarks (for unscattered gamma rays) for demonstrating the quantification of non-Gaussian features (e.g., skewness and kurtosis, which characterize asymmetries and long tails) of response distributions by deterministically and efficiently propagating parameter uncertainties (covariances and higher-order moments, where available) using high-order sensitivities computed by the recently developed comprehensive adjoint sensitivity analysis methodology (C-ASAM). With regard to (i), application of PCE, the most significant accomplishment of this project was an implementation of PCE into INVERSE that significantly reduced computation time for the DiffeRential Evolution Adaptive Metropolis (DREAM) and Differential Evolution (DE) methods. For inverse transport problems with measurements of neutron leakage, neutron multiplication, and neutron-induced gamma-rays, the solution times for the DREAM and DE methods were reduced by factors of 30-300, reducing run times from hours to minutes while maintaining the same accuracy as the standard (non-PCE) DREAM and DE. Speedups were further improved by exploring sparse grid quadrature sets using the Toolkit for Adaptive Stochastic Modeling and Non-Intrusive ApproximatioN (Tasmanian) toolset. An initial exploration of sparse grids indicated that further speedups factors of 5-10 are obtainable. The implementation of PCE in INVERSE is not in a form that users can easily access. With regard to (ii), solving the inverse problem using a predictive modeling paradigm, the most significant accomplishment of this project were the derivation and implementation of adjoint-based second derivatives in neutron and photon transport theory. There are two codes that compute these derivatives. SENSPG computes them for uncollided gamma rays and SENSMG computes them for neutron leakage. SENSMG is open-source code available on github. Other significant accomplishments included a stand-alone code, MULTI-PRED, that implements the predictive modeling paradigm, along with a detailed manual. The code was implemented in the existing INVERSE code for inverse problems, but a head-to-head comparison of inverse methods was not achieved. We also derived and implemented the capability to compute sensitivities for multiplicity measurements into the SENSMG code, and this capability was used in a data assimilation application, but it was not used for solving inverse problems. With regard to (iii), developing benchmarks to demonstrate the importance of high-order sensitivity and uncertainty analysis, the most significant accomplishment of this project were two test problems that showed how important second-order sensitivities are.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2020

Evaluation of Changes to the MTR Fuel Dissolution Flowsheet to Increase the Number of L-Bundles Charged to a Dissolver

Material Test Reactor (MTR) fuels are dissolved in the H-Canyon facility using a Hg-catalyzed, HNO₃ dissolution flowsheet. The flowsheet is based on experimental work in which laboratory-scale experiments were used to provide bounding values for both offgas and H₂ generation rates. The generation of H₂ gas, primarily from the dissolution of Al, is controlled by limiting the surface area exposed to the solution. The number of L-Bundles charged and their submergence level defines the exposed surface area which is directly proportional to the H₂ generation rate. For the MTR fuel dissolution flowsheet, the maximum number of L-Bundles which can be charged to a dissolver was specified as a function of the Al concentration in the solution and the submergence level of the bundle. The MTR fuels are currently dissolved in the 6.1D dissolver. To reach the desired terminal Al concentration, a total of 12 L-Bundles of fuel are dissolved per batch. Depending on the submergence level being used in the dissolver, the 12 bundles are dissolved in three charges of four bundles per charge or in a sequence of three, four, and five bundles. However, if six L-Bundles could be dissolved in the initial charge, a dissolver batch could be completed in two dissolutions instead of three. To assess the feasibility of dissolving six bundles in the first charge, the Savannah River National Laboratory evaluated changes to the MTR flowsheet which increase the number of bundles which can be charged to a dissolver. Since the development of the existing MTR fuel dissolution flowsheet, improved offgas measurement methods have been developed to more accurately calculate the offgas composition and generation rate during laboratory-scale dissolutions. In the first part of this study, improvements in the calibration model for the Raman spectrometer (used for offgas characterization) and a more effective data smoothing routine were applied to existing data. The uncertainty in the offgas composition data used to define the MTR fuel dissolution flowsheet were subsequently re-evaluated which resulted in an approximate 50% reduction in the uncertainty of the H₂ gas concentration measurements. The reduced uncertainty was used in new calculations to define the maximum number of L-Bundles which can be charged to either the 6.1D or 6.4D dissolver as a function of the Al concentration. With the reduced uncertainty in the H₂ concentration measurements, a flowsheet was defined which supported initially charging 6 bundles to a dissolver. This flowsheet is based on the use of 0.002 M Hg, an L-Bundle immersion depth of 54 in., an air sparge/purge flowrate of 40 scfm, an iodine reactor operating temperature of 200 °C, and not exceeding 60% of the H₂ LFL in the dissolver offgas. In the second phase of this study, calculations were performed to assess the impact of changing various operating parameters to increase the number of L-Bundles charged to an H-Canyon dissolver. Applying the improved offgas measurement techniques including the reduced uncertainty in the H₂ concentration measurements to the existing data, the number of bundles of MTR fuel which can be charged to either the 6.1D or 6.4D dissolver were calculated based on varying the bundle immersion depth (44-60 in.), air sparge/purge flowrate (40-60 scfm), iodine reactor operating temperature (150-200 °C), and the percentage of the H₂ LFL which must not be exceeded (60-76%). Qualitatively, the percentage of the LFL had the largest influence on the maximum number of bundles which can be charged to a dissolver followed by the air sparge/purge flowrate, L-Bundle immersion depth, and the iodine reactor operating temperature. During the evaluation of each variable, the other variables were held at the baseline flowsheet conditions.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2026

Influence of Shear Strength Assumptions on BISON Debonding Simulations

Accurately predicting the thermomechanical response of buffer–IPyC debonding in TRISO fuel particles requires reliable mechanical property inputs for each coating layer, particularly the normal and shear strengths that influence interlayer delamination and stress concentrations. Micro tensile testing of AGR-2 fuel particles provided experimentally measured normal strengths for the buffer, IPyC, and buffer–IPyC interface; however, shear strength was not measured. As a result, BISON simulations of interface debonding must rely on assumed shear strength values, typically estimated as 20–40% of the measured ultimate tensile strength. This study evaluates how these assumed shear strength values influence cohesive zone model (CZM) predictions of buffer–IPyC separation in AGR 2 TRISO particles. Using micro tensile data from three AGR 2 compacts (2 1 3, 5 1 3, and 6 3 3), BISON simulations were performed with multiple shear strength assumptions to quantify their effect on radial and tangential stress evolution, debonding, and gap propagation. The results show that shear strength is a high sensitivity parameter: increasing the assumed shear strength significantly alters the stress distribution at the buffer–IPyC junction, shifts the predicted debonding location, and changes the extent of partial gap formation. While normal strength controls the initiation of interface separation, shear strength strongly influences the mode mixity of the failure process and the resulting stress concentrations transmitted to the IPyC and SiC layers. These findings highlight a critical gap in current TRISO mechanical characterization. Without experimentally measured shear strength, BISON simulations must rely on approximations that introduce uncertainty into predictions of coating layer integrity and fission product barrier performance. Future fuel qualification campaigns should therefore consider measurement of shear strength at the interlayer interfaces to reduce model uncertainty and improve the fidelity of TRISO fuel performance simulations.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Network-Cognizant Time-Coupled Aggregate Flexibility of Distribution Systems Under Uncertainties

Increasing integration of distributed energy resources (DERs) within distribution feeders provides unprecedented flexibility at the distribution-transmission interconnection. To exploit this flexibility and to use the capacity potential of aggregate DERs, feasible substation power injection trajectories need to be efficiently characterized. This paper provides an ellipsoidal inner approximation of the set of feasible power injection trajectories at the substation such that for any point in the set, there exists a feasible disaggregation strategy of DERs for any load uncertainty realization. The problem is formulated as one of finding the robust maximum volume ellipsoid inside the flexibility region under uncertainty. Though the problem is NP-hard even in the deterministic case, this paper derives novel approximations of the resulting adaptive robust optimization problem based on optimal second-stage policies. The proposed approach yields less conservative flexibility characterization than existing flexibility region approximation formulations. The efficacy of the proposed method is demonstrated on a realistic distribution feeder.

aggregates↗