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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 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Flowsheet for the Neutralization of Accelerated Basin De-inventory (ABD) Material

Under the Accelerated Basin De-inventory (ABD) program H-Canyon will be dissolving aluminum spent nuclear fuel (ASNF) and then neutralizing that solution without performing head-end strike or uranium recovery operations. After dissolution in H-Canyon the material will be neutralized to a free hydroxide concentration of either 0.6 M or 1.2 M to meet the waste acceptance criteria for transfer to the SRS Concentration, Storage and Transfer Facility (CSTF). In order to ensure the material could be successfully neutralized and transferred, SRNL completed experiments with simulated H-Canyon dissolver solutions. Two bounding simulants were developed based on the expected compositions of ASNF to be dissolved, one containing only Gd as the neutron poison and one containing Fe as an additional poison.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Sensitivity and uncertainty of the IFR-1 BISON benchmark

The fuel performance code BISON is being used to evaluate metallic fuel for a new fast-spectrum test reactor called the Versatile Test Reactor, which is being considered for adoption by the US Department of Energy. To quantify the accuracy of BISON predictions, researchers at Oak Ridge National Laboratory have been developing a series of benchmarks based on legacy metallic fuel experiments. As part of this effort, the sensitivity of BISON predictions to variations in model inputs and the uncertainties associated with BISON predictions must be established. This paper summarizes efforts to perform a comprehensive sensitivity analysis (SA) and uncertainty quantification (UQ) on a benchmark based on the IFR-1 experiment.For the SA, at least one input was chosen from every BISON model and physics module used in the benchmark. The inputs were varied individually in a series of BISON simulations. Here, the resulting variations in benchmark predictions were normalized to calculate sensitivities. These sensitivities were then used to inform input selections for the UQ.The UQ was performed using the Monte Carlo UQ method. A literature review was conducted to estimate uncertainty distributions for the selected inputs, and values were sampled randomly from each distribution in a series of BISON simulations. Variations in the benchmark predictions were used to estimate uncertainty distributions and confidence intervals. It was found that nearly 100% of the benchmark predictions matched the corresponding legacy values within the confidence intervals. However, this is at least partially because the confidence intervals associated with benchmark predictions were wide. The uncertainty contributions of assumptions in the benchmark, experimental uncertainties, and BISON models were quantified. Some analysis was performed to identify inputs that contributed to the uncertainties. Finally, recommendations are made for future benchmark and future BISON development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2020

BISON Methods and Contact Algorithms

This paper reviews five critical algorithms for BISON’s simulation of nuclear fuel: the burnup model, the coolant channel model, fuel cracking models, mechanical contact, and thermal contact.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

CO 2 and Renewable Electricity into Chemicals: Formic Acid Production from Coal Flue Gas

Formic acid (FA) is an industrial chemical. It is used as a preservative for silage, as a digestive aid for animals, as a fluid for fracking, as a pharmaceutical intermediate and in leather tanning. The global formic acid market is valued at 777.4 million USD in 2020 and is expected to reach 851.8 million USD by the end of 2026. A new major formic acid application is the use of formic acid as a key feedstock for the bioprocessing industry. It has the potential to grow tremendously if we can lower the cost of formic acid production compared with the current fossil-fuel one. Recently, Dioxide Materials has developed a technology that can directly convert CO 2 to pure formic acid with a three-compartment CO 2 electrolyzer. However, the electrolyzer performance needs further improvement for the technology to be commercially viable. The major objective of this project is to develop the electrolyzer technology to enable formic acid as a feedstock for the bioprocessing industry to be economically manufactured from flue gas from a coal fired pilot plant. In particular, the project is to understand how to run the electrolyzer for the conversion of CO 2 into formic acid using flue gas from a coal fired power plant as a source of CO 2 . The work will include characterizing how the performance of the electrolyzer changes with low CO 2 concentration and impurities, developing new cell designs that can still operate with feedstocks with low CO 2 concentrations, testing simulated flue gas in the electrolyzer system and developing filters to remove any impurities that arise.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

CFD modeling of near-wall combustion and unburned methane prediction in natural gas spark ignition engines

Natural gas-powered engines play a critical role in gas drilling, compression, and transmission sectors, but methane (CH 4 ) from engine combustion slip can be significant over their lifespan, contributing to atmospheric pollution and signaling reduced engine efficiency. Here, to address this challenge, computational fluid dynamics (CFD) simulations offer valuable insights into the in-cylinder combustion process, enabling the optimization of combustion strategies and engine designs to minimize unburned CH 4 slip. This study aims to evaluate and improve combustion models for simulating the combustion process and predicting unburned CH 4 concentrations in natural gas spark-ignition (SI) engines, including engines that are part of combined reformer-engine systems. Specifically, the performance of two flamelet-based combustion models—the Extended Coherent Flame Model (ECFM) and the G-equation model—was assessed using experimental engine data collected under varying excess-air ratio (λ) conditions and fuel compositions, including natural gas and syngas blends. In addition, to enhance the predictive capabilities of the G-equation model, a flame-wall interaction (FWI) sub-model was integrated into its framework. The effects of its model parameters, such as quenching and influence distance, on combustion behavior and unburned methane predictions were analyzed in detail. The ECFM tended to predict delayed combustion phasing under diluted mixture conditions, resulting in overprediction of unburned CH 4 concentrations. In contrast, the G-equation model provided reasonable predictions of combustion pressure, while representing higher the CH 4 reduction rate across the operating condition compared to experimental data. Incorporating the FWI sub-model—with the quenching distance calculated based on a pressure-dependent relation (P -0.48 ) and a fixed influence distance of 1.5 mm—further improved the G-equation model’s accuracy in predicting CH 4 reduction rates without compromising its ability to simulate the combustion process.

Combustion model↗
DOE OSTI2024

Constitutive model development of aluminum alloy 1100 for elevated temperature forming process

Commercially pure aluminum alloy, AA1100, presents good electrical and thermal conductivity, high formability, and low cost. Those favorable characteristics have the potential to enable bipolar plates with improved economics and enhanced performance compared to current stainless steel bipolar plates for proton exchange membrane fuel cells. An accurate constitutive model is essential to develop and optimize processing parameters and effectively control the forming process. Here, the objective of this work is to develop a constitutive model of AA1100 that is able to simulate stress-strain relation, formed geometry, and predict the onset of fracture strain to avoid forming failure. Initially, a set of tensile tests at temperature between 300 and 500°C and strain rate between 0.005 and 1.0/s were conducted to examine the deformation behavior. Then, a set of damage-based unified visco-plastic constitutive equations is proposed and calibrated based on the results of stress-strain data. A genetic algorithm optimization method is applied to search for best fitting material constants in constitutive equations. The proposed model shows good predictability of both the stress-strain relation and fracture strain at low strain rate and high temperature conditions. The accuracy of proposed model is also evaluated statistically. A comparison of the proposed model with three popular models (Arrhenius-type mode, Johnson-Cook model and Zerilli-Armstrong model) was made. The proposed model shows the best experimental agreement with correlation coefficient of 0.96 in contrast to 0.25, 0.38 and 0.75 for the popular models, respectively. The proposed model can help to optimize the elevated temperature forming process and guide die design to enable optimal geometric features in the formed components.

08 HYDROGEN↗
DOE OSTI2021

Sensitivity and Uncertainty of the IFR-1 BISON Benchmark

The fuel performance code BISON is being used to evaluate metallic fuel for a new fast-spectrum test reactor called the Versatile Test Reactor, which is being considered by the US Department of Energy. To quantify the accuracy of BISON predictions, researchers at Oak Ridge National Laboratory have been developing a series of benchmarks based on legacy metallic fuel experiments. As part of this effort, the sensitivity of BISON predictions to variations in model inputs and the uncertainties associated with BISON predictions must be established. This report summarizes efforts to perform a comprehensive sensitivity analysis (SA) and uncertainty quantification (UQ) on a benchmark based on the IFR-1 experiment. For the SA, at least one input was chosen from every BISON model and physics module used in the benchmark. The inputs were varied individually in a series of BISON simulations. The resulting variations in benchmark predictions were normalized to calculate sensitivities. The strongest sensitivities were identified and used to inform input selections for the UQ. The UQ was performed using the Monte Carlo UQ method. A literature review was conducted to estimate uncertainty distributions for the selected inputs, and values were sampled randomly from each distribution in a series of BISON simulations. Variations in the benchmark predictions were used to estimate uncertainty distributions and confidence intervals. It was found that nearly 100% of benchmark predictions matched the corresponding legacy values within the confidence intervals. However, this is at least partially because of the wide confidence intervals associated with the benchmark predictions. The uncertainty contributions of assumptions in the benchmark, experimental uncertainties, and BISON models were quantified. Some analysis was performed to identify inputs that contributed to the uncertainties. Finally, recommendations are made for future benchmark development and future BISON development.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Transient Efficiency, Flexibility, and Reliability Optimization of Coal-Fired Power Plants - Final Report

This program developed an advanced model-based monitoring and model-predictive control algorithms for a coal fired power plant (CFPP), and deployed these algorithms in a real-time platform to demonstrate performance benefits for transient flexibility and plant operation efficiency. More specifically, the objectives were successfully achieved through a combination of (i) developing a high-fidelity transient plant model in Apros, which was used as a high-fidelity plant simulation between $100-50\% TMCR$ where TMCR denotes the turbine maximum continuous rating, i.e., baseload, (ii) developing a very fast physics-based reduced-order model (ROM) of the plant, which ran more than $100\times$ faster than real-time, enabling its use as real-time embedded model for model-based estimation (MBE) and model predictive control (MPC) (iii) implementing a real-time MBE based on ROM using a robust unscented Kalman filter (UKF) to continuously tune the ROM to match the measurements from high-fidelity Apros plant model despite significant plant-model mismatch, and thus, obtain a Digital Twin of the plant (iv) designing and implementing a real-time MPC with dual objectives of transient plant load tracking with high ramp rates and minimizing coal consumption, i.e., improving plant efficiency in the baseload-partload operation range of $100-50\% TMCR$. Each key element above was developed and tested individually, and has been reported in corresponding Topical Reports. Finally, all the individual elements were integrated in an overall closed-loop system, that was successfully tested in desktop Simulink test harness simulations with ROM or high-fidelity model as the plant. Thereafter, the Simulink implementation was used to auto-generate C-code and deploy as real-time Docker microservice containers in Linux, and validate that they can run in real-time in the hardware-in-the loop (HIL) setup and produce the same results as in Simulink. The results of the integrated simulation tests in Simulink as well as the real-time HIL deployment are documented in this final report, showing good load tracking for load ramps at $3-4\%/min$ ramp rates, and achieving up to $5.5\%$ reduction in coal relative to baseline operation at $50\% TMCR$ load. The desktop and HIL simulations show successful performance of the overall model based estimation and control solution and achieve the key objectives of the program for flexible, efficient and reliable operation of subcritical coal fired power plants.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2024

Nanoindentation Stress Relaxation to Quantify Dislocation Velocity–Stress Exponent

This work reports a new methodology using indentation stress relaxation to characterize the dislocation velocity–stress exponent. Through the indentation stress relaxation process, the dislocation structure builds up at the rate governed by dislocation velocity, which is a function of the externally applied stress. The relationship between the dislocation velocity and stress can thus be derived from the indentation stress relaxation data of the stress as a function of time. In this study, instrumented nanoindentation stress relaxation experiments were performed on pure aluminum samples, following three different initial displacement rates of 100, 400, and 800 nm/s. Based on the scaling properties of dislocation kinetics, the data were interpreted to derive a dislocation velocity–stress exponent of 2.5 ± 0.5 for room-temperature aluminum. Crystal plasticity finite-element simulations were performed to illustrate the sensitivity of the proposed nanoindentation stress relaxation methodology to the dislocation velocity–stress exponent value.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2022

Parametric Study of Panel PCM–Air Heat Exchanger Designs

Heat exchangers, devices for the transfer of heat between two or more working fluids, are extensively used in cooling applications and heating applications. Heat exchangers in buildings are typically components of space-conditioning systems, as well as of water-heating applications. Heat exchangers are also sometimes used in applications that require storage and release of energy at specific times. Phase change materials (PCMs) enhance these heat-exchange processes, given their ability to melt and solidify at a fixed range of temperatures, absorbing or releasing significant amounts of latent heat. Five different configurations of PCM–air heat exchangers for thermal control in buildings are analyzed in this work. The heat exchangers were fitted with PCM encapsulated in plastic and composite pouches of various shapes, and packaged in stackable panel layers. Three-dimensional computational fluid dynamics (CFD) modeling of coupled incompressible fluid and conjugate heat transfer were performed on the designs. The phase change process was numerically modelled using the apparent heat capacity method. Steady-state CFD simulations provided quantification of pressure drop as a function of air flow velocity. Transient simulation results describe the thermal evolution of PCM in the pouches, helping to determine the best performing configuration with respect to total thermal charging time.

10 SYNTHETIC FUELS↗
DOE OSTI2022

An IIPG-based finite element framework in MOOSE for modeling fiber reinforced composite failure governed by extrinsic cohesive laws

Fiber reinforced composites (FRC) are widely applied to many important engineering structures such as silicon carbide ceramic matrix composite (SiC CMC) of nuclear fuel claddings. Many material and structure failures are initiated at the interface between two distinctive materials, such as the debonding of interfaces of matrix/fiber of composites or bulk matrix/inclusion in metals at micro-scales. Accurate and robust modeling of these interface failures is critical to the development of novel material and structure with improved functionality. This paper presents a discontinuous Galerkin (DG) finite element method based on the Incomplete Interior Penalty scheme and its implementation in MOOSE for modeling material interface behaviors. The proposed method naturally accommodates important extrinsic cohesive zone material models and is capable of modeling the failures of material interfaces across which material properties are highly distinctive. We demonstrate a good performance of the proposed method using single fiber and multiple fiber debonding problems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2024

Characterizing the effects of drive asymmetries, component offsets, and joint gaps in double shell capsule implosions

This work provides a numerical study of how double shell capsule deformations caused by drive asymmetries and fabrication imperfections affect implosion symmetry and neutron yield. Hydrodynamics simulations are performed in two dimensions and focus on low-mode deformations that are caused by corresponding asymmetries in the Hohlraum drive, component offsets, and ablator joint gaps. By providing a parameter study of these features, our goal is to understand the dominant sources for inner shell deformation and yield degradation. The discussed capsules are composed of an aluminum ablator with a chromium inner shell. The latter encloses a carbon-deuterium foam ball that serves as fuel. We find that for clean capsules, even-numbered low-mode asymmetries in the drive are imprinted on the ablator and smoothly transferred to the inner shell during shell collision. The resulting deformation of the inner shell is more pronounced with larger fuel radius, while the yield is inversely proportional to the amplitude of the drive asymmetry and varies by factors ≤4 in comparison with clean simulations. Capsule component offsets in the vertical direction and ablator thickness nonuniformity result in p1-type deformations of the imploding inner shell. Finally, joint gaps have the largest effect in deforming the ablator and inner shell and degrading yield. While small gap widths (1 μm) result in prolate inner shells, larger gap widths (4 μm) cause an oblate deformation. More importantly, capsules with a small outer gap (1 μm) experience a dramatic drop in yield, typically <3% of a clean simulation.

Goodarzi, S. (ORCID:000000018556489X)↗
DOE OSTI2021

Feasibility of full-core pin resolved CFD simulations of small modular reactor with momentum sources

Complex flow structure interactions and heat transfer processes take place in nuclear reactor cores. Given the extreme pressure/temperature and radioactive conditions inside the core, numerical simulations offer an attractive and sometimes more feasible approach to study the related flow and heat transfer phenomena in addition to the experiments. Under the Exascale Computing Project, the full-core simulation of a small modular reactor (SMR) has been pursued coupling Computational Fluid Dynamics (CFD) and neutronics. A key aspect of the modeling of SMR fuel assemblies is the presence of spacer grids and the mixing promoted by mixing vanes or the equivalent. A reduced order methodology is adopted based on momentum sources to mimic the mixing of the vanes. The momentum sources have been carefully calibrated with detailed Large Eddy Simulations (LES) of spacer grids performed with Nek5000. Modeling the spacer grid and mixing vanes (SGMV) effect without body-fitted computational grid avoids the excessive costs in resolving the local geometric details, and thus supports the simulation to be scaled up to the full core. Besides the progress on momentum source modeling, this paper also features the first full-core pin resolved CFD simulation ever performed to the authors' knowledge. This represents a significant advancement in capability for the CFD of nuclear reactors, which will hopefully serve as an inspiration for further integrating high-fidelity numerical simulations in actual engineering designs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Plant Reload Optimization (prlo)

The PRLO framework is built on a modular and extensible architecture that tightly couples advanced evolutionary optimization algorithms with nuclear fuel depletion solvers (i.e., nuclear physics neutronics code). It supports exploring complex, high-dimensional design spaces constrained by user-specified operational, safety, and economic constraints. Objectives such as minimizing fresh fuel enrichment, flattening radial and axial power distributions, and maximizing discharge burnup are evaluated. PRLO’s equilibrium cycle optimization capability enables the identification of core configurations that maintain fuel cycle sustainability over extended planning horizons. Its integration with the RAVEN platform facilitates optimization of loading patterns or fuel shuffling schemes across multiple cycles. The interface with SIMULATE, a licensed industry-standard nodal code developed by Studsvik, ensures accurate neutronic and thermal-hydraulic feedback for reactor core design. PRLO’s automated workflow engine supports iterative design refinement, enabling utilities to streamline core design processes and meet evolving performance and regulatory targets.

Kim, Junyung [Idaho National Laboratory] (00090005↗
DOE OSTI2025

Accelerating Combustion and Surface Chemistry Simulations

Design of modern combustion systems relies on computer models to predict how changes in design will affect performance. These models have largely displaced previous methods that rely on the designer’s intuition or costly and time-consuming physical testing. By using improved models, design cycles can be shortened, and cleaner and more efficient combustion devices can be created. This project aims to improve computer simulations of transportation fuels with the goal of making these simulations faster and more accurate for predicting combustion in vehicles.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Real Fuel Modeling for Gasoline Compression Ignition Engine

Increasing regulatory demand for efficiency has led to development of novel combustion modes such as HCCI, GCI and RCCI for gasoline light duty engines. In order to realize HCCI as a compression ignition combustion mode system, in-cylinder compression temperatures must be elevated to reach the autoignition point of the premixed fuel/air mixture. This should be co-optimized with appropriate fuel formulations that can autoignite at such temperatures. CFD combustion modeling is used to model the auto ignition of gasoline fuel under compression ignition conditions. Using the fully detailed fuel mechanism consisting of thousands of components in the CFD simulations is computationally expensive. To overcome this challenge, the real fuel is represented by few major components of create a surrogate fuel mechanism. In this study, 9 variations of gasoline fuel sets were chosen as candidates to run in HCCI combustion mode. A study detailing the development of the gasoline real fuel model was performed and various surrogates for gasoline fuel were investigated. The gasoline real fuel model will be used in subsequent CFD modelling activities for the development of an advanced mixed mode combustion system as part of the Department of Energy funded project DE-EE0008478.

Gasoline Compression Ignition, real fuel modeling,↗
DOE OSTI2022

High-Fidelity Simulations of Supercritical CO2 Based Oxy-Combustion with Non-Ideal Equation of State

The supercritical carbon dioxide (sCO2) Allam-Fetvedt cycle employs high-temperature oxy-combustion using sCO2 as the working fluid, leading to a unique and challenging environment for materials. In this cycle, pressurized gaseous fuel is combusted in the presence of a hot oxidant flow containing a mixture of CO2 and oxygen and a hot CO2 diluent recycle stream at approximately 300 bar under lean combustion conditions. We present high-fidelity reacting simulations of this oxy-combustor environment and compare the results when performing simulations with ideal and non-ideal equations of state. By doing so, we identify if the combustor behavior at the regime of interest is sensitive enough to the equation of state to justify the added computational cost incurred with a non-ideal equation of state.

equation of state↗
DOE OSTI2025

Evaluating the Impact of Tritium Permeation Membrane Performance and Direct Internal Recycling on Fusion Fuel Cycle Efficiency Using TMAP8

An efficient fuel cycle is vital to sustainable and cost-effective energy generation in fusion systems. Since tritium is not widely available, fusion systems must breed their own tritium for sustainable fusion deuterium-tritium reactions. An inefficient fuel cycle increases the tritium inventory needed for operations, which increases costs, constraints on tritium management systems, and safety concerns. A fuel cycle model is a powerful tool for understanding tritium inventories and flow rates across all systems in the fuel cycle. By simplifying the technical details into time-dependent tritium flow rates and inventories, the model can simulate the entire fuel cycle with high computational efficiency, even for technologies that are still under development. It can therefore quantify the impact of new tritium management technologies on fuel cycle efficiency. To evaluate the impact of key components on reducing tritium inventory, we are using and expanding an existing fuel cycle models based on latest advancements in fuel cycle research. The new model integrates Tritium Permeation Membrane (TPM) and Direct Internal Recycling (DIR) to enhance tritium transport from blanket breeders and plasma exhaust. These fuel cycle models are implemented in TMAP8 (Tritium Migration Analysis Program, version 8), a MOOSE-based open-source application designed to provide cutting-edge capabilities for tritium transport and fuel cycle modeling. The study aims to demonstrate the extensibility of existing fuel cycle modeling capability in TMAP8 and to offer a proof-of-principle design for future fusion plant systems. The presentation will cover the performance of fuel cycle modeling capabilities available in TMAP8, highlight advancements in fuel cycle research, and present a sensitivity analysis of these models. The results underline potential approaches and technology solutions to lower tritium inventory requirements, highlighting their role in shaping the future of fusion energy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗