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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Simulation of natural circulation cartridge loop experiments and application to molten salt reactors

This work uses the TRAC/RELAP Advanced Computational Engine (TRACE) thermal hydraulics (TH) code to model natural circulation cartridge loop experiments previously conducted at Oak Ridge National Laboratory (ORNL) using water and compares the simulated and experimental results. TRACE is also used to characterize natural circulation in the cartridge loop vehicle using FLiNaK as the working fluid. The experimental vehicle is a buoyancy-aided, annular cartridge loop, referred to as a thermosyphon, and is designed to aid in qualifying liquid–fueled and/or liquid–cooled irradiation experiments for the Versatile Test Reactor (VTR), which is currently being designed in the United States. Out-of-pile water experiments have been conducted using the cartridge and the Thermosyphon Test Loop facility at ORNL, and future experiments are anticipated that would use other molten salt surrogates as the working fluid, followed by eventual insertion of a similar cartridge into VTR. Additionally, this work aims to determine how well TRACE can replicate the natural convection conditions that were observed experimentally; this serves as an initial step for validating the modeling tool for design and safety calculations to support future irradiation experiments in VTR. Initial predictions of potential experiments were made using FLiNaK as the natural circulation fluid to demonstrate the relevance of the cartridge design to molten salt reactors (MSRs). Results from this study indicate that TRACE can accurately capture natural convection phenomena in the thermosyphon and that several design changes to the current cartridge vehicle are necessary to achieve hydraulic conditions similar to those expected in MSRs.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

(U) PRAD0697 & PRAD0698: Complex Loading of CeO₂ Powder

Cerium(IV) oxide (CeO₂) powder is shock compressed using the Precision High Energy-density Liner Implosion eXperiment (PHELIX) platform. Experimental results are compared against several modeling approaches. Compaction behavior is best captured with a P-∝ model, which calculates CeO₂ powder bulk densities within 80-99% of experimental values but overpredicts densi cation at the cylindrical target's outer radius and center by up to 20%. Preliminary calculations suggest that accuracy could be increased with the inclusion of a coupled strength model. Several common computational modeling approaches for the shock compression response of granular materials and the magnetohydrodynamic (MHD) force upon the impactor/liner in pulsed power compression experiments are investigated and analyzed for their validity. The Bi-linear Ramp, P-∝ PACXP, and P-∝ Menikoff-Kober continuum compaction models are calibrated to planar impact Hugoniot data for CeO₂ powder and used to predict the powder's shock compaction response under non-planar shock wave compression. MHD calculations of the PHELIX pulsed power driver are performed using an idealized resistor-inductor-capacitor (RLC) circuit calibrated to previous experiments. All simulations are performed using the LANL code FLAG. Two validation experiments are computationally designed using the calibrated compaction and circuit models, executed using the PHELIX platform on CeO₂ targets with initial porous densities of 3.95 and 4.03 g/cm³, measured with proton radiography, and analyzed against the model predictions. The two P-∝ models more accurately describe CeO₂ powder densi cation than the Bi-linear Ramp model. However, the two P-∝ models overpredict bulk density of the shock compressed CeO₂ powder by up to 20% when the appropriate impact velocities are applied. MHD calculations for both validation experiments underpredict liner impact velocities by 4-11% when using the idealized RLC circuit model calibrated to previous experiments. Compensating underpredictions of impact velocity and overpredictions of powder densication lead to a false accuracy in pre-shot calculations compared to experimental data. To improve correlation between simulations and experiments, the following improvements are suggested: 1. A coupled strength model for CeO₂ powder that updates strength as a function of porosity and applied stress. 2. An improved MHD circuit model that more accurately captures the PHELIX machine.

36 MATERIALS SCIENCE↗
DOE OSTI2017

Distributed Workflows for Modeling Experimental Data

Modeling helps explain the fundamental physics hidden behind experimental data. In the case of material modeling, running one simulation rarely results in output that reproduces the experimental data. Often one or more of the force field parameters are not precisely known and must be optimized for the output to match that of the experiment. Since the simulations require high performance computing (HPC) resources and there are usually many simulations to run, a workflow is very useful to prevent errors and assure that the simulations are identical except for the parameters that need to be varied. These workflows are usually distributed because the simulations require HPC, but the optimization and steps to compare the simulation results and experimental data are done on a local workstation. We will present results from force field refinement of data collected at the Spallation Neutron Source using Kepler, Pegasus, and Beam workflows and discuss what we have learned from using these workflows.

Lynch, Vickie E.↗
DOE OSTI2024

Evaluating the Importance of Conformers for Understanding the Vacuum-Ultraviolet Spectra of Oxiranes: Experiment and Theory

Vacuum-ultraviolet (VUV) absorption spectroscopy enables electronic transitions that offer the unambiguous identification of molecules. As target molecules become more complex, multifunctional species present a great challenge to both experimental and computational spectroscopy. This research reports both experimental and theoretical studies of oxiranes. Computationally, the nuclear ensemble approach has been used to accurately predict experimental spectra for a variety of molecules. However, this approach incurs great computational cost, as ensembles generally consist of thousands of geometries. The present study aims to drastically reduce the ensemble by evaluating the significance of the conformers to the predicted spectra. This approach was applied to 11 substituted oxiranes using the Conformer Rotamer Ensemble Sampling Tool (CREST) of Grimme to generate an ensemble of unique conformers determined by their Boltzmann populations. Five TD-DFT functionals (BMK, CAM-B3LYP, M06-2X, MN15, ωB97X-D) and EOM-CCSD were used to simulate the spectrum of each substituted oxirane ensemble. Computed spectra were then compared to the experiment using both qualitative and quantitative metrics. Based on these metrics, it was observed that certain conformers may not be necessary to characterize this set of oxiranes despite the temperature (323 K) of the experiment. A single conformer can then be used with TD-DFT and EOM-CCSD to replicate the experimental spectra of these medium-sized combustion species.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

High-Fidelity Modeling and Experiments to Inform Safety Analysis Codes for Heat Pipe Microreactors

Heat pipe microreactors are reactor designs that primarily use liquid-metal heat pipes to cool the core. The main interest in heat pipes is the fact that they can remove heat passively. This, along with the use of liquid metal, allows the reactor to operate at higher temperatures. Although the use of heat pipes in nuclear reactors is new, liquid-metal heat pipe technology is mature. Nevertheless, experimental data on heat pipes are scarce, and very little is known about their behavior during abnormal operations and close to their thermal limits. Therefore, new experiments and accurate heat pipe simulations are needed to develop reliable closure models. This work describes a joint experimental and numerical investigation into heat pipes that attempts an initial closure of this gap. Further, the numerical and experimental efforts are currently proceeding in parallel, aimed at different aspects of heat pipes. The numerical part is focused on gaps in local closures, and the experiments capture the overall heat pipe behavior.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Dataset documenting reaction-induced changes to five fractured foamed wellbore cement cores during CO2 fluid flow

This dataset consists of reconstructed CT scans for four fractured foamed cement cores, generated in the lab using Portland Class H cement, and associated processed data. The cements were exposed to reactive brines, and CT scans were take at different time points through the experiment. The CT imaging allows for the tracking of dissolution-induced changes to fracture morphology, as well as alteration and dissolution in the cement matrix.

Computed Tomography↗
DOE OSTI2020

Super resolution convolutional neural network for feature extraction in spectroscopic data

Two dimensional (2D) peak finding is a common practice in data analysis for physics experiments, which is typically achieved by computing the local derivatives. However, this method is inherently unstable when the local landscape is complicated or the signal-to-noise ratio of the data is low. In this work, we propose a new method in which the peak tracking task is formalized as an inverse problem, which thus can be solved with a convolutional neural network (CNN). In addition, we show that the underlying physics principle of the experiments can be used to generate the training data. By generalizing the trained neural network on real experimental data, we show that the CNN method can achieve comparable or better results than traditional derivative based methods. This approach can be further generalized in different physics experiments when the physical process is known.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

An Efficient Bayesian Approach to Learning Droplet Collision Kernels: Proof of Concept Using “Cloudy,” a New n -Moment Bulk Microphysics Scheme

The small-scale microphysical processes governing the formation of precipitation particles cannot be resolved explicitly by cloud resolving and climate models. Instead, they are represented by microphysics schemes that are based on a combination of theoretical knowledge, statistical assumptions, and fitting to data (“tuning”). Historically, tuning was done in an ad hoc fashion, leading to parameter choices that are not explainable or repeatable. Recent work has treated it as an inverse problem that can be solved by Bayesian inference. The posterior distribution of the parameters given the data—the solution of Bayesian inference—is found through computationally expensive sampling methods, which require over $\mathcal{O}$(10 5 ) evaluations of the forward model; this is prohibitive for many models. We present a proof of concept of Bayesian learning applied to a new bulk microphysics scheme named “Cloudy,” using the recently developed Calibrate-Emulate-Sample (CES) algorithm. Cloudy models collision-coalescence and collisional breakup of cloud droplets with an adjustable number of prognostic moments and with easily modifiable assumptions for the cloud droplet mass distribution and the collision kernel. The CES algorithm uses machine learning tools to accelerate Bayesian inference by reducing the number of forward evaluations needed to $\mathcal{O}$(10 2 ). It also exhibits a smoothing effect when forward evaluations are polluted by noise. In a suite of perfect-model experiments, we show that CES enables computationally efficient Bayesian inference of parameters in Cloudy from noisy observations of moments of the droplet mass distribution. In an additional imperfect-model experiment, a collision kernel parameter is successfully learned from output generated by a Lagrangian particle-based microphysics model.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Assessment of Existing Transportation Packages for Use with HALEU

Commercial light water reactor operators and fuel vendors in the United States are pursuing changes to fuel that include increased 235 U enrichment. Economic studies generally anticipate maximum near-term fuel assembly designs with up to 8 wt.% 235 U. Many next-generation nuclear reactor designs require high-assay low-enriched uranium (HALEU) (19.75 wt.% > 235 U > 5 wt.%) fuel. One necessary element for the commercial-scale use of HALEU is the ability to safely transport large quantities of enriched fuel material in multiple forms. However, there is uncertainty as to whether subcriticality requirements can be satisfied with existing package designs and whether existing critical benchmark experiment data are sufficient to support criticality safety code validation for HALEU transportation applications. This study assesses the potential to use currently licensed transportation packages for the transportation of increased enrichment unirradiated U fuel forms. The assessment uses selected package designs that represent the five categories of fuel form-boiling water reactor pins and assemblies, pressurized water reactor pins and assemblies, UF 6 , U-metal and tristructural isotropic (TRISO) particles, and UO 2 pellets or powder-and focuses on demonstrating subcriticality and identifying benchmark critical experiments appropriate for use in criticality computer code validation. Key quantities of interest that relate to subcriticality are limiting conditions (e.g., optimum moderation), package or package array k eff , package capacity, and package transportation array size. The SCALE TSUNAMI-3D and TSUNAMI Indices and Parameters codes are used for sensitivity and uncertainty calculations and for identification of candidate critical benchmark experiments for code validation. The primary metric for identifying candidate benchmarks is the similarity coefficient, c k . For each fuel form category, a representative package is evaluated. Results provided for each package evaluation include enrichment and packaging limits (e.g., maximum transportation array size as a function of enrichment) and benchmark critical experiment similarity coefficients. Results indicate that there are viable means for increasing enrichments into the HALEU range across the spectrum of fuel forms with differing increase amounts available for different packages. Sources of subcriticality margin to offset increased enrichment reactivity include reduced transportation array size, reduced fissile mass, burnable absorber credit, and safety analysis margin harvesting. For all packages except the DN-30, numerous critical benchmark experiment candidates for validation were identified.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2017

Enhanced Dual Confocal Measurement System

A measurement instrument utilizing dual, chromatic, confocal, distance sensors has been jointly developed by General Atomics (GA) and Sandia National Laboratories (SNL) for thickness and flatness measurement of target components used in dynamic materials properties (DMP) experiments on the SNL Z-Machine (Z). Compared to previous methods used in production of these types of targets, the tool saves time and yields a 4x reduction in thickness uncertainty which is one of the largest sources of error in equation of state (EOS) measurements critical to supporting the NNSA’s Stockpile Stewardship program and computer modeling of high energy density experiments. It has numerous differences from earlier instruments operating on the dual confocal sensor principle to accommodate DMP components including larger lateral travel, longer working distance, ability to measure flatness in addition to thickness, built-in thickness calibration standards for quickly checking calibration before and after each measurement, and streamlined operation. Thickness and flatness of 0.2mm-3.3mm thick sections of diamond machined copper and aluminum can be measured to “sub-micron” accuracy. Sections up to 6mm thick can be measured with as-yet undermined accuracy. Furthermore, samples must have one surface which is flat to within 300µm, lateral dimensions of no more than 50mm x 50mm, and height less than 40mm.

36 MATERIALS SCIENCE↗
DOE OSTI2025

AGR 1 and 2 Isotopic Depletion Validation

This presentation includes work performed developing a computational benchmark for the AGR 1 and 2 experiments. These experiments involve irradiation of TRISO particle compact in the Advanced Test Reactor (ATR). Many post-irradiation measurements were made from these experiments, including isotopic concentrations of fission products. The benchmark involves a MCNP-ORIGEN coupled model of the ATR and AGR experiment capsules to calculate a comprehensive inventory of fission product and actinide concentrations in the compacts. This presentation describes the experiments, the measurements obtained, the benchmark model, and results of the model evaluation.

97 - MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Electronic excitation spectra of molecular hydrogen in phase I from quantum Monte Carlo and many-body perturbation methods

Here, we study the electronic excitation spectra in solid molecular hydrogen (phase I) at ambient temperature and 5- to 90-GPa pressures using quantum Monte Carlo methods and many-body perturbation theory. In this range, the system changes from a wide-gap molecular insulator to a semiconductor, altering the nature of the excitations from localized to delocalized. Computed gaps and spectra agree with experiments, proving the ability to predict accurately band gaps of many-body systems in the presence of nuclear quantum and thermal effects.

08 HYDROGEN↗
DOE OSTI2019

Investigation of Application Specific k eff Sensitivities to Existing and New Subcritical and Critical Experiments

Integral subcritical and critical experiments are essential in providing validation of computational codes which improve confidence in the predicted k eff results of specific applications. This work discusses the relevance of existing integral subcritical and critical experiments to applications far reaching across the nuclear complex. These applications include Travelling Wave Reactors (TWR), Kilopower Reactor Using Stirling Technology (KRUSTY), and plutonium reflected by tantalum. The primary goal of this work is to improve knowledge of energy-dependent cross-section sensitivities for specific applications, identify nuclear data gaps in existing experiments, enable an optimized design of new experiments to address these gaps, and design practical new experiments that could be executed at the National Criticality Experiments Research Center (NCERC) that have a high-value to these applications.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Importance of Higher Fidelity Model Geometries during Optimization of Critical Experiments

PARADIGM, PARallel Approach of Differential and InteGral Measurements, is a cross-collaborative effort at Los Alamos National Laboratory between nuclear data theorists, differential and integral experimenters, as well as machine learning statisticians to tackle uncertainties in the intermediate region of 239 Pu. In essence, the idea behind PARADIGM is to remove the linear conceptualization of the nuclear data pipeline, shown in Figure 1, and replace it with a far more parallelized approach. The novel approach leverages machine learning to guide which differential measurements and integral experiments will result in the largest decrease in uncertain ties for a nuclide reaction pair in a given energy range. The concept builds off earlier work, EUCLID, which focused on the fast region of 239 Pu. The practical benefit of having evaluation, differential measurement, and integral experiment personnel in collaboration with machine learning is to represent the entire nuclear data in one snapshot. This enable large reduction in the time to deliver improved nuclear data, which using the PARADIGM approach could be done in 3 years. A general outline of PARADIGM and specific topics are available in other papers. The discussion here will pertain directly to the integral experiment design. More specifically, the process of taking a rough design and transforming it into a finalized neutronic model will be discussed.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The influence of random packed column parameters on the liquid holdup and interfacial area

Abstract Carbon dioxide capture via solvent absorption in packed columns has emerged as a potential technology to mitigate coal‐fired power plant CO 2 emissions. Parameters, including packing types, solvent properties, and operating conditions, could potentially affect the packed column CO 2 capture efficiency. To understand the importance of those parameters and help packed column optimization, a design of experiments (DoEs) method was proposed to generate input parameter matrix. Combined with multiphase computational fluid dynamics (CFD), the random packed column parameter influence on the liquid holdup and interfacial area can be efficiently investigated. Surrogate‐based sensitivity analysis shows that the solvent flow rate and contact angle are key factors dictating liquid holdup and interfacial area. On the other hand, solvent viscosity has a marginal impact on the interfacial area. The sensitivity scores were calculated for each input parameter to guide the selection of dimensionless numbers for the liquid holdup and interfacial area correlation development.

42 ENGINEERING↗
DOE OSTI2017

Evaluation of Thin Plate Hydrodynamic Stability through a Combined Numerical Modeling and Experimental Effort

An experimental and computational effort was undertaken in order to evaluate the capability of the fluid-structure interaction (FSI) simulation tools to describe the deflection of a Missouri University Research Reactor (MURR) fuel element plate redesigned for conversion to lowenriched uranium (LEU) fuel due to hydrodynamic forces. Experiments involving both flat plates and curved plates were conducted in a water flow test loop located at the University of Missouri (MU), at conditions and geometries that can be related to the MURR LEU fuel element. A wider channel gap on one side of the test plate, and a narrower on the other represent the differences that could be encountered in a MURR element due to allowed fabrication variability. The difference in the channel gaps leads to a pressure differential across the plate, leading to plate deflection. The induced plate deflection the pressure difference induces in the plate was measured at specified locations using a laser measurement technique. High fidelity 3-D simulations of the experiments were performed at MU using the computational fluid dynamics code STAR-CCM+ coupled with the structural mechanics code ABAQUS. Independent simulations of the experiments were performed at Argonne National Laboratory (ANL) using the STAR-CCM+ code and its built-in structural mechanics solver. The simulation results obtained at MU and ANL were compared with the corresponding measured plate deflections.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Mixed Ionic Electronic Conducting Quaternary Perovskites: Materials by Design for Solar Thermochemical Hydrogen

The innovative research conducted by Arizona State University and Princeton University in the project "Mixed Ionic-Electronic Conducting Quaternary Perovskites: Materials by Design for Solar Thermochemical Hydrogen" marks a significant stride forward in thermochemical water splitting. Through an intricate blend of computational design and experimental validation, the project delved into the promising potential of Mixed Ionic Electronic Conducting (MIEC) perovskites. These complex materials, characterized by their unique redox-active nature and adaptability in stoichiometry, present a promising frontier for efficient solar thermochemical hydrogen production. Firstly, the research enhanced the science by utilizing state-of-the-art computational methodologies to unravel the nuanced chemical potentials of MIEC perovskites. By simulating various off-stoichiometric scenarios and redox conditions, the team was able to predict material behaviors under diverse environmental conditions, a feat unachievable through conventional experimental methodologies alone. This approach not only fast-tracks the material screening process, significantly reducing the time from laboratory re-search to practical application, but also uncovers trends and correlations that are pivotal for future materials innovation. Regarding technical effectiveness, the project stands out in its economic feasibility. Traditional methods of materials discovery are often marred by high costs and extensive timeframes, owing to the iterative nature of experimental processes. However, by employing theoretical computations and validating these findings with targeted experiments, the project introduced a cost-effective paradigm for materials discovery and the first ever prediction, synthesis, and preliminary validation of a material solely from computational and theoretical considerations. This synergy between computation and experimentation expedites the discovery of optimal materials conducive to high-efficiency solar-to-hydrogen conversion processes. Furthermore, the public stands to benefit substantially from this research. The success of MIEC perovskites in solar thermochemical applications heralds a shift towards lower cost and lower electricity input for clean hydrogen production, hence potentially impacting climate and energy resilience. By improving the efficiency of solar-to-hydrogen conversions, the research paves the way for reduced dependency on fossil fuels, addressing the urgent global need for accessible and renewable energy sources. Moreover, the project's advancements contribute to scientific literacy in renewable energy technologies, empowering society through knowledge and spurring future innovations. In essence, this research project demonstrates significant progress in the realm of advanced water splitting through solar thermochemistry. Through its groundbreaking approaches in computational materials science and its implications for real-world applications, it holds the promise of a cleaner, more energy-resilient future.

08 HYDROGEN↗
DOE OSTI2022

Hydrated Anions: From Clusters to Bulk Solution with Quasi-Chemical Theory

The interactions of hydrated ions with molecular and macromolecular solution and interface partners are strong on a chemical energy scale. Here we recount the foremost ab initio theory for the evaluation of the hydration free energies of ions, namely, quasi-chemical theory (QCT). We focus on anions, particularly halides but also the hydroxide anion, because they have been outstanding challenges for all theories. For example, this work supports understanding the high selectivity for F – over Cl – in fluoride-selective ion channels despite the identical charge and the size similarity of these ions. QCT is built by the identification of inner-shell clusters, separate treatment of those clusters, and then the integration of those results into the broader-scale solution environment. Recent work has focused on a close comparison with mass-spectrometric measurements of ion-hydration equilibria. We delineate how ab initio molecular dynamics (AIMD) calculations on ion-hydration clusters, elementary statistical thermodynamics, and electronic structure calculations on cluster structures sampled from the AIMD calculations obtain just the free energies extracted from the cluster experiments. That theory–experiment comparison has not been attempted before the work discussed here, but the agreement is excellent with moderate computational effort. This agreement reinforces both theory and experiment and provides a numerically accurate inner-shell contribution to QCT. The inner-shell complexes involving heavier halides display strikingly asymmetric hydration clusters. Asymmetric hydration structures can be problematic for the evaluation of the QCT outer-shell contribution with the polarizable continuum model (PCM). Nevertheless, QCT provides a favorable setting for the exploitation of PCM when the inner-shell material shields the ion from the outer solution environment. For the more asymmetrically hydrated, and thus less effectively shielded, heavier halide ions clustered with waters, the PCM is less satisfactory. We therefore investigate an inverse procedure in which the inner-shell structures are sampled from readily available AIMD calculations on the bulk solutions. This inverse procedure is a remarkable improvement; our final results are in close agreement with a standard tabulation of hydration free energies, and the final composite results are independent of the coordination number on the chemical energy scale of relevance, as they should be. Finally, a comparison of anion hydration structure in clusters and bulk solutions from AIMD simulations emphasize some differences: the asymmetries of bulk solution inner-shell structures are moderated compared with clusters but are still present, and inner hydration shells fill to slightly higher average coordination numbers in bulk solution than in clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗