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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Assessment of Heavy-Duty Fueling Methods and Components

Building on the successful commissioning and demonstration of NREL's heavy-duty (HD) fast flow research facility under the Innovating Hydrogen Station's Project, researchers advanced R&D activities to the next phase under a new project titled, Assessment of Heavy-Duty Fueling Methods and Components. This Cooperative Research and Development Agreement (CRADA) is led by NREL in partnership with NextEnergy, Argonne National Laboratory, and Chevron with NextEnergy representing a larger group of industry partners that includes AirLiquide, Hyundai, Nel, Nikola, Shell, and Toyota. The CRADA seeks to develop a comprehensive assessment of HD fuel cell electric vehicle fueling protocols and fueling hardware to understand the effects of fueling protocol architectures on station design, vehicle design, functional safety requirements, and the implications on the total cost of ownership (TCO) and techno economic assessment (TEA).

class 8 truck↗
DOE OSTI2023

Develop and Connect TRISO Failure Analysis and Uncertainty Quantification to Fission Product Release Calculation Capability

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel cycle systems. This program has been providing engineering-scale support for the development of BISON, a high-fidelity and high-resolution fuel performance tool. Stress-based failure probability has been developed and analyzed to assess the integrity of tri-structural isotropic (TRISO) fuel particles during fuel life cycles. While simple, stress-based approaches to failure probability leveraging the Weibull statistical distribution entails a number of drawbacks when stress concentration occurs near crack tips, including finite element mesh size dependency. In this report, we use an interaction integral approach to the computation of stress intensity factors in functionally graded materials (FGM) for axisymmetric models. The inner pyrolytic carbon (IPyC) cracking induced silicon carbide (SiC) failure is one of the dominated failure modes in TRISO failure analysis. In this study, we consider a crack in the IPyC layer perpendicular to the SiC layer. The interface between these two TRISO layers is considered to be porous, which we simulate considering a transition of mechanical properties over the porous length. These aspects are considered in the computation of stress intensity factor (SIF) from a fracture mechanics approach and compared with the known stress-based failure probability approach.

42 ENGINEERING↗
DOE OSTI2025

Analyze the real-time performance of the optimized fiber-PTR instrument

An instrument to perform in-reactor, real-time thermal property measurements of nuclear fuels and materials was recently designed, optimized, and tested at Massachusetts Institute of Technology Research Reactor. It was the second insertion experiments of a total of two rounds. Here we report the collection and analysis of the real-time captured thermal diffusivity data on the preloaded SiC. With the optimized design, the instrument temperature had been successfully raised as we expected. Only one probe (the top one) returned real-time thermal diffusivity in a time span of approximately two days. Measured thermal diffusivity of the preloaded SiC was significantly lower than the literature value at the same temperature, indicating a significant influence from the irradiation induced microstructure damage. Meanwhile, the real-time thermal diffusivity value continuously reduced with time, indicating the dynamic microstructure evolution. The possible reasons of the probes that did not return data were hypothesized. The further optimization of the instrument with the objective to improve the measurement accuracy and instrument survivability is also discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Summary of FY25 activities on the project Realistic Reaction Evaluations for Fission Products Off Stability (RREFPOS)

Applications such nonproliferation, post-detonation forensics, spent-fuel assay, reactor burnup and design, as well as astrophysics, rely on the accurate description of the neutron interaction with unstable fission products. Current neutron-induced cross-section descriptions for these nuclei are either non-existent or based on simplified assumptions, leading to unquantified impacts on predicted cross-sections. The goal of the Realistic Reaction Evaluations for Fission Products Off Stability (RREFPOS) project is to develop a reproducible methodology leading to a more predictive and realistic new set of evaluated nuclear data, improving the reliability of applications involving fission products off stability. The current report documents the activities related to the RREFPOS project in its first year, corresponding to the Fiscal Year of 2025 (FY25).

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2025

INL_Intern_Poster_ColeBailey [Poster]

Understanding the thermophysical properties of molten salts is crucial for the advancement of nuclear fuels. This project presents the design of a custom differential thermal analyzer (DTA) that utilizes non-contact ultrasonic mixing to agitate samples and prevent supercooling. The supercooling effect occurs when a liquid is below its freezing point without solidifying. This can be observed when a liquid in a freezer instantly transitions to its solid phase upon disturbance. By avoiding this effect, accurate transition temperatures of molten salts can be gathered for future applications. Initial mixing results were promising, leading to further refinement of the waveguides using ABAQUS to maximize input energy into the fluid. Future work will focus on integrating both mixing and cooling in conjunctions to observe the avoided effect.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗
DOE OSTI2026

Free-Piston Expander for Hydrogen Cooling

This final report details work done by GTI Energy, in partnership with University of Texas at Austin – Center for Electromechanics (UTCEM), Argonne National Laboratory (ANL), and Quantum Fuel Solutions (Quantum) to successfully design, fabricate, and test a linear free-piston hydrogen expander controlled by linear motors which also generates electrical power during the process.

03 NATURAL GAS↗
DOE OSTI2020

ASNF Engineering Scale Drying Experiment Acceptance Criteria for Fabricated Items

This document specifies the acceptance criteria for items fabricated by Holtec International under the scope of INL Contract # 215725, consistent with the parameters described in INL/EXT-19-56017, Aluminum-clad Spent Nuclear Fuel Engineering Scale Drying Experiment Design. Verification is confirmed with initials (or the need for remediation may be identified) along with the date of inspection for each requirement. Verification may be performed by independent proxy (University of South Carolina participant, under INL Contract Number 207046) or by an INL employee, remotely by camera images.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Co-Optimization of Fuels & Engines: Scientific Innovation for Efficient, Clean, and Affordable Transportation

An overview of the Co-Optimization of Fuels and Engines Initiative that is bringing together top scientists, engineers, and analysts from nine national laboratories with university and industry partners across the country to investigate fuels and engines as dynamic design variables that can work together to boost efficiency and performance, while minimizing emissions.

bioenergy, biofuels, consortium, conversion↗
DOE OSTI2020

BISON High Burnup Structure Modeling Capabilities Validated with a Selection of the Halden IFA-650 Rods

The U.S. Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS)program aims to develop predictive capabilities using computational methods for the analysis and design of advanced reactor and fuel cycle systems. This program has been supporting the development of BISON, a high-fidelity and high-resolution fuel performance tool at the engineering scale. This document continues analysis and refinement of capabilities added to BISON early this calendar year in regards to the incorporation of capabilities applicable to extended burnups in response to industry interest. Details are provided on high burnup thermal conductivity models, a refitting of the high-burnup structure (HBS) porosity formation model to include additional data, the coupling of the HBS volume fraction model to thermal conductivity and fine fragmentation models, and validation activities. The IFA-650.4 and IFA-650.9 loss of coolant accident (LOCA) analyses are revisited with the latest developments in this report. A new validation case, IFA-650.14 has also been added to the BISON test suite.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Review and Assessment of NGNP PIRTs for TRISO and HTGR Technologies

The main objective of this technical report is to ensure that research and development (R&D) needs are identified to address the significant (highly ranked) technical challenges related to TRISO-coated particle fuel, high-temperature gas-reactor (HTGR) technologies, and other TRISO-related advanced designs by recognizing the existing foundation of identified R&D needs and augmenting that foundation with insights drawn from current TRISO-related research results and R&D needs related to novel applications of TRISO-related technologies that extend beyond the traditional HTGR designs.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

ARIES/Flatirons Facility - Hydrogen System Capability Buildout

Under the "Advanced Research on Integrated Energy Systems" (ARIES) initiative, hydrogen system capabilities including a MW-scale electrolyzer, storage system, and MW-scale fuel cell generator will be designed and commissioned at NREL's Flatirons Campus. This hydrogen infrastructure will support H2@Scale goals by enabling integrated systems R&D to study the science of scaling for hydrogen energy systems.The system is designed with flexibility to provide a testbed to demonstrate systems integration, grid services, energy storage, direct renewable hydrogen production, and innovative end use applications (e.g. HD transportation, natural gas blending, etc.).

Advanced Research on Integrated Energy Systems↗
DOE OSTI2023

TMS 2023 - Methodology and Density of PuCl3-NaCl Mixtures

The development of molten salt reactors and their associated components demands reliable and accurate thermophysical property data for design and validation. A candidate fuel salt, PuCl3-NaCl (36 mol% PuCl3) has been synthesized and studied at the Idaho National Laboratory. This study has determined the density of PuCl3-NaCl at multiple compositions and temperatures, providing data for validation of modeling efforts and making improvements on the buoyancy method for density measurements of actinide-bearing molten salts.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Mortar-based Cohesive Zone Model with Application to TRISO Particle Debonding

The U.S. Department of Energy’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel cycle systems. This program has been providing engineering-scale support for the development of BISON, a high-fidelity and high-resolution fuel performance tool. This report outlines work towards the development of an integrated, mortar-based cohesive zone framework with mechanical contact. We model debonding of tri-structural isotropic (TRISO) layers using a mortar approach, extending the framework used for mechanical contact, using weighted quantities. A bilinear mixed mode traction approach, already used in Jiang et al. (2021), is applied analogously herein to model debonding between TRISO particle layers. The examples include the debonding of the inner pyrolytic carbon (IPyC) from the silicon carbide (SiC) layers, as well as partial and full debonding of the buffer from the IPyC layers. Both 2D and 3D examples are utilized to demonstrate the superior numerical performance of the new mortar approach, which allows for modeling arbitrarily meshed interfaces (i.e., non-matching discretizations).

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

"Source Term Modeling for Advanced Gas Micro-Reactors"

Maintaining the safety of the public, environment, and operating personnel is the most important factor in designing, operating, maintaining, and decommissioning nuclear reactors. In recent years, there has been a growing interest in the development of micro-reactors employing TRi-structural ISOtropic (TRISO)-coated particle fuel. In gas reactors, TRISO fuel plays an important role in the safety case for high temperature reactors because of the fission product retention properties of the fuel. This ability enables the use of a functional containment strategy for the reactor where multiple barriers are used to prevent fission product release to the environment. Part of the safety analysis of these advanced reactors is the assessment of radionuclide releases under normal and accident conditions through the multiple credited safety barriers. Using conservative assumptions, a mechanistic analysis can be performed to quantify these releases that combines the probabilistic assessment of failure with analytic solutions to radionuclide transport equations. Source term modeling for TRISO fuel has been performed for previous reactor designs; however, these models are outdated, in many cases proprietary, and need updates to be applied to the current state of TRISO fuel technology and alternative gas reactor core configurations [1]. Currently, the only publicly available source term assessment for gas reactors is an expert-based Monte Carlo simulation based on the effectiveness of the fuel kernel, coating layers, and graphite block in a modular high temperature gas reactor [2]. Thus, there is a need to develop a simple, versatile, and mechanistic model of fission product release and transport in gas reactor cores that could be applied to a variety of reactors through user inputs and reactor-specific radionuclide inventories. The release is calculated by the diffusion of the key safety important fission products through the kernel, silicon carbide (SiC), graphite for both intact and defective TRISO particles based on fuel and graphite temperatures in the reactor under normal operation. These releases from the fuel enter the coolant where they can plate-out on cooler surfaces. A clean-up model is included for designs with a coolant purification system to remove fission gases. This initial distribution of fission products in the reactor serves as an initial condition for potential releases under postulated accident conditions. The model then can calculate the fission product release for any transient temperature profile and fission product releases can then be used to assess radiological dose to the workers and the public using conventional dose tools. Data on the diffusion of fission products is based on historic German TRISO experiments and the more current Department of Energy (DOE) Advanced Gas Reactor (AGR) TRISO fuel development program. The model is coded in python with inputs and outputs in excel spreadsheets, as well as python plotting utilities to aid in the interpretation of the results. References: [1] INL, NGNP Mechanistic Source Term White Paper, INL-10-17997, July 2010. [2] David A. Petti, Richard R. Hobbins, Peter Lowry, Hans Gougar, “Representative Source Terms and The Influence of Reactor Attributes on Functional Containment in Modular High Temperature Gas-cooled Reactors,” Nuclear Technology, Vol. 184, p. 181-197, Nov. 2013.

07 ISOTOPE AND RADIATION SOURCES↗
DOE OSTI2024

Bayesian Analysis of TRISO Fuel: Quantifying Model Inadequacy, Incorporating Lower-Length-Scale Effects, and Developing Parallel Active Learning Capabilities

The U.S. Department of Energy (DOE)’s Nuclear Energy Advanced Modeling and Simulation (NEAMS) program aims to develop predictive capabilities by applying computational methods to the analysis and design of advanced reactor and fuel-cycle systems. This program has been providing engineering-scale support for the continued development of BISON, a high-fidelity, high-resolution fuel performance tool. Fuel behavior in nuclear reactors is governed by a complex network of mechanisms that interact with various other physics aspects in the reactor system. Any model developed to represent fuel behavior will likely be idealized, resulting in uncertainties when comparing their predictions against the observed data. In Fiscal Year (FY)-23, we initiated the Uncertainty Quantification (UQ) work by using Bayesian methods to establish a level of model trustworthiness and further improve it, with a particular emphasis on TRI-Structural isOtropic (TRISO) nuclear fuel. This year, we further expanded on that UQ work by investigating an approach to quantifying model inadequacy and accounting for lower-length scale (LLS) effects in TRISO silver (Ag) release modeling. Furthermore, we are implementing parallel active learning capabilities to reduce the computational cost (i.e., required computational resources and elapsed time) of performing UQ. Specifically, we utilized The Kennedy O’Hagan framework for Bayesian uncertainty quantification (KOH) to account for model inadequacy in TRISO Ag release predictions made by BISON. The KOH framework represents an improvement over the standard Bayesian framework used in FY-23. Explicitly accounting for model inadequacy in the Bayesian framework helps establish the level of experimental noise uncertainty in the Advanced Gas Reactor (AGR) data. We compared the inverse UQ results obtained from both the standard Bayesian and KOH frameworks in light of the AGR-2/3/4 data, and also compared the predictive UQ results obtained from these two frameworks in light of the AGR-1 data. Next, we investigated the impact of considering LLS effects in the Ag release simulations. We developed an expanded database of LLS simulated effective diffusivities for Ag, covering a wide range of microstructures and temperatures. Using this database, we developed a framework for incorporating LLS effects into the engineering-scale Ag release UQ. We developed both parametric and non-parametric approaches for bridging the length scales. We then investigated the inverse UQ results in light of the AGR-2/3/4 data and the predictive UQ results in light of the AGR-1 data, and compared the LLS-informed approach and the Arrhenius equation, which does not include microstructure information. Finally, we discussed implementing parallel active learning capabilities in the Multiphysics Object Oriented Simulation Environment (MOOSE)/BISON to reduce the computational cost (i.e., computational resources and elapsed time) of Bayesian UQ. For verification purposes, we first tested these new capabil ities on a species interaction problem. We then demonstrated them on the TRISO Ag release application, showing that parallel active learning capabilities can enhance the accuracy of UQ while also substantially reducing the computational cost in comparison to the reference methods developed in FY-23.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

A Simplified Numerical Approach to Characterize the Thermal Response of a Moving Bed Solar Reactor

Abstract Concentrated solar thermochemical storage in the form of a zero-emission fuel is a promising option to produce long-duration energy storage. Solar fuel is produced using a cavity reactor that captures concentrated solar radiation from a solar field of heliostats. In this paper, heat transfer model of a tubular plug-flow reactor designed and manufactured for a solar fuel production is presented. Experimental data collected from a fixed bed tubular reactor testing are used for model comparison. The system consists of an externally heated tube with counter-current flowing gas and moving solid particles as the heated media. The proposed model simulates the dynamic behavior of temperature profiles of the tube wall, gas, and particles under various gas flowrates and residence times. The heat transfer between gas–wall, solid particle–wall, and gas–solid particle is numerically studied. The model results are compared with the results of experiments done using a 4 kW furnace with a 150 mm heating zone surrounding a horizontal alumina tube (reactor) with 50.8 mm outer diameter and thickness of 3.175 mm. Solid fixed particles of magnesium manganese oxide (MgMn2O4) with the size of 1 mm are packed within the length of 250 mm at the center of the tube length. Simulation results are assessed with respect to fixed bed experimental data for four different gas flowrates, namely, 5, 10, 15, and 20 standard liters per minute of air, and furnace temperatures in the range of 200–1200 °C. The simulation results showed good agreement with maximum steady state error that is less than 6% of those obtained from the experiments for all runs. The proposed model can be implemented as a low-order physical model for the control of temperature inside plug-flow reactors for thermochemical energy storage applications.

Engineering↗
DOE OSTI2026

Persistent Elevated Soot Emissions Induced by Clustered Stochastic Preignition Events

Stochastic Preignition (SPI) is an abnormal combustion phenomenon that can occur in spark-ignition engines particularly under high-load operation. SPI is characterized by uncontrolled initiation of combustion prior to spark discharge, an abnormal combustion process that can lead to severe knock events and significant engine damage. SPI has been associated with fuel properties, lubricant composition, and engine design and operation. Here, in this work, a single-cylinder test engine with a dry-sump oil system was utilized to study the SPI response of E10 and E25 fuels with a range of Reid Vapor Pressure (RVP). An automated test procedure was employed, consisting of ten square-waved load profile segments, with each segment composed of 5 min of low-load operation followed by 25 min of sustained high-load operation. These tests were replicated across multiple days of testing including a lubricant triple flush between tests, and an online Fuel in Oil diagnostic measurement. Exhaust particulate emissions were continuously measured by an AVL microsoot sensor (MSS). Elevated particulate matter emissions were observed to occur concurrently with SPI events as blooms of soot. Particularly after clustered events (i.e., multiple SPI cycles occurring within 10 consecutive engine cycles), high soot emissions were observed to persist over several days of sequential operation despite daily lubricant changes, a complete warm-up procedure, and sustained low-load operation between test segments. This result implies that the particulate emissions trends may be dominated by deposit-based effects, where higher load operation is needed to alter deposition and formation processes. The observed soot blooms were also found to correspond to a reduction in the engine fueling and the fuel engine oil dilution rate despite the engine exhaust remaining at stoichiometric exhaust operation. These observations suggest that post-SPI events, pathways for lubricant migration and consumption into the combustion chamber may occur until these pathways are closed from deposit formation or ring dynamics during extended operation. These observed sooting propensity persisted with all fuels tests, but a linear correlation was observed between the summation of soot and particulate matter index (PMI) value for each fuel as well as SPI events, proving that PMI is a crucial fuel property for reducing SPI.

Splitter, Derek [Oak Ridge National Laboratory (OR↗
DOE OSTI2024

DNS of ignition and flame stabilization in a simplified gas turbine premixer

With the increasing need for fuel flexibility, mitigation of auto-ignition (AI) inside gas turbine (GT) premixers becomes crucial. They must be designed to yield a sufficiently homogeneous fuel-air mixture to achieve low emissions while at the same time avoiding the occurrence of AI and subsequent flame stabilization. This challenge requires a detailed understanding of turbulent mixing and chemistry interactions. In the present work, a direct numerical simulation (DNS) of an array of jets in crossflow (JICF), representative of an industrial GT premixer, is reported to shed light on these complex phenomena. It is found that AI kernels form in the aft part of the premixer and coalesce into a flame front that then propagates upstream, mainly through the boundary layer, and successively engulfs the jets. This, therefore, suggests a significant role of the jet array pattern on the flame stabilization. It is noted that AI kernels continue to form independently during the whole time of the simulation. To clarify the contribution of AI and diffusion in the ignition kernels and the main flame, chemical explosive mode analysis (CEMA) is employed jointly with a kernel tracking algorithm. It is found that during the initial formation of the flame, many ignition kernels form in mixtures with low scalar dissipation rate and large contribution from AI mode. As they quickly grow, they merge into a single flame front that becomes increasingly more diffusion-assisted over time, balancing the AI mode. Turbulence is shown to have a significant enhancing effect in lean premixed flames, but further analysis is required to fully characterize it. These findings are relevant for the industrial premixer studied, and also for novel micromix concepts that may be used in the next generation of GT combustion systems.

ADVANCED PROPULSION SYSTEMS↗