Results for “fuel performance simulation” — Page 61

DOE OSTI2021

SCALE 6.3.0 User Manual

SCALE is a comprehensive modeling and simulation suite for nuclear safety analysis and design developed and maintained by Oak Ridge National Laboratory under contract with the U.S. Nuclear Regulatory Commission, U.S. Department of Energy, and the National Nuclear Security Administration to perform reactor physics, criticality safety, radiation shielding, and spent fuel characterization for nuclear facilities and transportation/storage package designs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2023

SCALE 6.3.1 User Manual

SCALE is a comprehensive modeling and simulation suite for nuclear safety analysis and design developed and maintained by Oak Ridge National Laboratory under contract with the U.S. Nuclear Regulatory Commission, U.S. Department of Energy, and the National Nuclear Security Administration to perform reactor physics, criticality safety, radiation shielding, and spent fuel characterization for nuclear facilities and transportation/storage package designs.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

SCALE 6.3.2 User Manual

SCALE is a comprehensive modeling and simulation suite for nuclear safety analysis and design developed and maintained by Oak Ridge National Laboratory under contract with the U.S. Nuclear Regulatory Commission, U.S. Department of Energy, and the National Nuclear Security Administration to perform reactor physics, criticality safety, radiation shielding, and spent fuel characterization for nuclear facilities and transportation/storage package designs. Visit the SCALE website for additional information.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2025

SCALE 6.3.3 User Manual

SCALE is a comprehensive modeling and simulation suite for nuclear safety analysis and design developed and maintained by Oak Ridge National Laboratory under contract with the U.S. Nuclear Regulatory Commission, U.S. Department of Energy, and the National Nuclear Security Administration to perform reactor physics, criticality safety, radiation shielding, and spent fuel characterization for nuclear facilities and transportation/storage package designs.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Flash Diffusivity Measurement of Semi-Porous Insulation Material Intended for Radioisotope Thermoelectric Generators

This research involves the analysis of flash-heating data pursuant to find the thermal diffusivity of a semi-porous insulation material (Min-K) that is being considered for use in a radioisotope thermoelectric generator (RTG). An RTG uses radioactive nuclear fuel to produce electricity through a temperature difference imposed on a bimetallic thermocouple. Insulation is required to protect sensitive equipment from high temperatures and to conserve heat in the fuel. Using flash diffusivity temperature data, various simulations were fitted in order to find the most appropriate heat transfer model for the experiments. Four models were allowed to compete and the standard deviation of the residuals were compared for each model in evaluating model performance. The residuals are simply the difference in temperatures between the measurements and the mathematical models at each measurement point.

McMasters, Robert L.↗

NASA NTRS1972

Pollution measurements of a swirl-can combustor

Pollutant levels of oxides of nitrogen, unburned hydrocarbons, and carbon monoxide were measured for an experimental, annular, swirl can combustor. The combustor was 42 inches in diameter, incorporated 120 modules, and was specifically designed for elevated exit temperature performance. Test conditions included combustor inlet temperatures of 600, 900 and 1050 F, inlet pressures of 5 to 6 atmospheres, reference velocities of 69 to 120 feet per second and fuel-air ratios of 0.014 to 0.0695. Tests were also conducted at a simulated engine idle condition. Results demonstrated that swirl can combustors produce oxides of nitrogen levels substantially lower than conventional combustor designs. These reductions are attributed to reduced dwell times resulting from short combustor length, quick mixing of combustion gases with diluent air, and to uniform fuel distributions resulting from the swirl can approach. Radial staging of fuel at idle conditions resulted in increases in combustion efficiencies and corresponding reductions in pollutant levels.

Niedzwiecki, R. W.↗

NASA NTRS1972

Pollution measurements of a swirl-can combustor.

Pollutant levels of oxides of nitrogen, unburned hydrocarbons, and carbon monoxide were measured for an experimental, annular, swirl-can combustor. The combustor was 42 inches in diameter, incorporated 120 modules, and was specifically designed for elevated exit temperature performance. Test conditions included combustor inlet temperatures of 600, 900 and 1050 F, inlet pressures of 5 to 6 atmospheres, reference velocities of 69 to 120 feet per second, and fuel-air ratios of 0.014 to 0.0695. Tests were also conducted at a simulated engine idle condition. Results demonstrated that swirl-can combustors produce oxides of nitrogen levels substantially lower than conventional combustor designs.

Niedzwiecki, R. W.↗

NASA NTRS1981

Combustion characteristics of hydrogen. Carbon monoxide based gaseous fuels

An experimental rig program was conducted with the objective of evaluating the combuston performance of a family of fuel gases based on a mixture of hydrogen and carbon monoxide. These gases, in addition to being members of a family, were also representative of those secondary fuels that could be produced from coal by various gasification schemes. In particular, simulated Winkler, Lurgi, and Blue-water low and medium energy content gases were used as fuels in the experimental combustor rig. The combustor used was originally designed as a low NOx rich-lean system for burning liquid fuels with high bound nitrogen levels. When used with the above gaseous fuels this combustor was operated in a lean-lean mode with ultra long residence times. The Blue-water gas was also operated in a rich-lean mode. The results of these tests indicate the possibility of the existence of an 'optimum' gas turbine hydrogen - carbon monoxide based secondary fuel. Such a fuel would exhibit NOx and high efficiency over the entire engine operating range. It would also have sufficient stability range to allow normal light-off and engine acceleration. Solar Turbines Incorporated would like to emphasize that the results presented here have been obtained with experimental rig combustors. The technologies generated could, however, be utilized in future commercial gas turbines.

Notardonato, J. J.↗

DOE OSTI2025

Experiment to Investigate the On-set of Transient Fission Gas Release Under Simulated LOCA Conditions

Continuing efforts to better understand the phenomenon of transient fission gas release in irradiated commercial light water reactor fuel undergoing a simulated loss of coolant accident (LOCA) will be discussed in this work. During heating associated with LOCA conditions there is an additional release of fission gas beyond what is typically released during steady state operation. The exact timing of this release could impact the cladding balloon and rupture as the LOCA progresses in an actual accident. Recent experiments performed on the upgraded Severe Accident Test Station at Oak Ridge National Laboratory have expanded the current assessment of transient fission gas release. This system evaluates fission gas release by sweeping fission gas out of the LOCA test furnace and into cryogenically cooled cold traps where radioactive noble gas fission products are measured by gamma spectrometry. Additionally, the sweep gas can be monitored by a gas mass spectrometer to provide additional data on noble gas release and changes in the sweep gas atmosphere during heating. Several different conditions have been evaluated that explored the response of irradiated fuel to different thermal ramp conditions and different overpressure conditions. This further confirmed the impact of an overpressure in suppressing transient fission gas release. Further experiments are planned to evaluate the on-set temperature of transient fission gas release under a known overpressure. This test will progressively step through different temperature conditions while maintaining hydrostatic pressure on the fuel that is representative of high burnup fuel conditions. The available results from this type of testing will be discussed. Post-test microscopy will be compared to other transient fission gas release and standard LOCA tests to further understand the microstructural source of transient fission gas release.

Harp, Jason [ORNL] (ORCID:0000000253458440)↗

NASA NTRS1974

Effect of diffuser bleed on performance of an annular swirl can combustor

A full-scale annular swirl can combustor equipped with diffuser bleed capability was tested at low fuel-air ratio, burning natural gas fuel. Test results show that, by drawing off a small amount of air on the inner or outer diffuser wall, the radial profile of combustor exit temperature could be changed from a strongly tip biased, to a strongly hub biased shape. Furthermore, combustor total pressure loss could be reduced by about one third by using a total bleed rate equal to 6 percent of diffuser inlet flow. At simulated engine idle conditions combustion efficiency was increased from 64 percent to nearly 100 percent by using 3 percent outer wall bleed. Combustor blowout performance was also improved significantly by using this diffuser bleed scheme.

Juhasz, A. J.↗

DOE OSTI2025

PSA 2025 Presentation: "Modeling and Sensitivity Analysis of a Generation IV Pebble Bed Reactor Using MELCOR 2.2"

Accompanying the advancement of reactor technologies is the need for computational modeling and simulation to predict their behavior under normal operating conditions and accident scenarios. New Generation IV reactor designs which employ non-conventional fuel have a particular need for modeling the behavior and release of radionuclides and other material from the fuel. In this work, MELCOR version 2.2, a system-level safety and accident scenario code developed by Sandia National Laboratories, was used to model a 200-MWth pebble bed modular reactor and calculate the inventories of circulating and deposited graphite, metal dust, and elemental components released from the fuel elements. A base case modeling the reactor under standard operating conditions was calculated using MELCOR and the inventories were extrapolated to 30 years of operation time using a logarithmic regression fit. A sensitivity analysis was also performed in which several key parameters for the base case model were modified to explore the effect of these changes on the inventories calculated by MELCOR. A set of transient scenario simulations for a depressurized loss of forced cooling (DLOFC) accident were also performed. The results of the sensitivity analysis and transient simulations are reported and discussed in relation to the modeling techniques used for this study.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2020

Examining Ohmic Losses in Fuel-Cell Catalyst Layers with Different Pt/C Ratios

A model of a fuel-cell cathode with distinct proton conductivities at the agglomerate and electrode scales was used to simulate polarization curves under conditions with facile oxygen transport. Here, the model was applied to electrodes containing agglomerates with different ratios of platinum to carbon in order to examine the hypothesis that intra-agglomerate proton conductivity is substantially lower than ionomer conductivity. The model predicts decreasing performance and increasing sensitivity to Pt/C ratio as intra-agglomerate conductivity declines relative to a constant through-electrode conductivity. Experiments on catalyst layers with Vulcan supports do not show the predicted trend indicating that mesoscale intra-agglomerate conductivity is not orders of magnitude lower than bulk ionomer conductivity.

08 HYDROGEN↗

DOE OSTI2023

Atomic-scale modeling of the dissolution of oxidized platinum nanoparticles in an explicit water environment

Pt nanoparticles (NPs) are currently being investigated for use in fuel cells; however, Pt NP oxidation as a function of size, morphology, and temperature is not well understood or currently quantified. In this study, the stability and dissolution of oxidized platinum NPs is examined via classical molecular dynamics in an explicit water environment. The NPs considered range in size from 1.35 to 2.92 nm in diameter and included five different monolayer (ML) coverages of O*. The simulations were performed at 300, 450, and 600 K with the many-body, reactive third-generation charge-optimized many-body or COMB3 potentials and examine the kinetics of NP dissolution in water. The Pt–O layer, which reduces the kinetic activity for Pt atom dissolution, is projected to make dissolution more favorable for O* MLs smaller than 0.5. The simulations further indicate that the Pt NPs' kinetic rates of dissolution are slowed by an increase in the number of adsorbed species caused by the dissociation of water molecules at the reconstructed facets of the Pt NPs. Furthermore, these findings quantify the effect of oxygen and temperature on the stability and dissolution of oxidized platinum NP in an explicit water environment similar to the conditions in fuel cells and electrocatalysis.

08 HYDROGEN↗

DOE OSTI2022

Integrated Optimization and Control of a Hybrid Gas Turbine/sCO 2 Power System

During phase-I, the project team led by Echogen Power Systems (EPS) had two primary objectives based on investigating the application of gas turbines with supercritical carbon dioxide (sCO 2 ) power cycles. The first objective was to improve the overall efficiency and performance of a hybrid gas turbine/sCO 2 power system through a joint optimization of the two subsystems (gas turbine and sCO 2 power cycle) using non-linear optimization techniques that simultaneously evaluate thermal performance of the combined cycle. The hybrid power system included several points of interaction, including (but not limited to) gas turbine exhaust, fuel heating, inlet chilling and turbine cooling. The second objective was to establish a baseline transient response model of the hybrid power system and a notional microgrid and begin steps to integrate the control systems of the three major elements (gas turbine, sCO 2 cycle and grid controller). The project team established a baseline performance for a combined cycle power plant using a production gas turbine and scaled sCO 2 power cycle only utilizing exhaust heat recovery. Echogen’s non-linear techno-economic optimization code was extended by adding gas turbine component models derived from a in-house developed gas turbine design code. With the two cycles coupled by the gas turbine exhaust, design parameters of both cycles were allowed to vary simultaneously to determine performance opportunity versus isolated designs. Returning to the baseline gas turbine/sCO 2 power cycle transient models: Echogen had in-house developed sCO 2 cycle transient model in GT-Suite system simulation software, and had partnered with Siemens Finspång for gas turbine transient model, and Siemens PTI group to provide micro-grid load profile as well as hybrid power cycle generated load (power and frequency) analysis. The transient model for the SGT-750 Siemens gas turbine was a “black-box” functional mock-up interface (FMI) model developed by Siemens Industrial Turbomachinery in Finspång, Sweden. The SGT-750 is a twin-shaft gas turbine that produces 40 MW electricity with an efficiency of about 40% at ISO conditions. At 100% gas turbine throttle (load), the SGT-750 has average exhaust conditions of 114.6 kg/s and 469.8°C. The transient model for sCO 2 power cycle was developed by Echogen in GT-SUITE 1D system simulation software platform. The basic CO 2 flow circuit has single-shaft turbomachinery with net 11.5 MW electrical power output at design conditions. The power turbine has a double-ended shaft with one end connected to synchronous generator through a fixed-ratio gearbox. The other end of power turbine is connected to the compressor through a continuously variable transmission. The major components of the sCO 2 power cycle modeled include air cooled condenser/cooler, CO 2 compressor, recuperator, two waste heat exchanger coils, power turbine, continuous variable transmission, gearbox and generator. Integration of SGT-750 transient model and sCO 2 power cycle transient model was done in Matlab Simulink. In the integrated model, the gas turbine and sCO 2 power cycle interacted at two points, first one being the gas turbine exhaust gas flow rate and temperature, which were inputs to sCO 2 power cycle model. The second point was the distribution of micro-grid load demand signal between the SGT-750 generator and sCO 2 cycle generator. For a given combined-cycle load demand, the gas turbine load demand was equal to the total demand minus the sCO 2 cycle power generated. In the present study the integrated model was simulated for two cases of grid load demand: (i) for a step change, both positive-step and negative-step, in grid load demand (ii) for a micro-grid load demand curve provided by Siemens PTI group. Finally, the time series plots representing load demand versus integrated system response were presented including the sCO 2 power cycle control system performance plots. The actual generated power and frequency of both the generators, gas turbine and sCO 2 power cycle, was supplied to Siemens PTI group for dynamic grid assessment, results of which are provided in appendices.

03 NATURAL GAS↗

DOE OSTI2024

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

42 ENGINEERING↗

DOE OSTI2024

Integration of Decentralized Graph-Based Multi-Agent Reinforcement Learning with Digital Twin for Traffic Signal Optimization

Machine learning (ML) methods, particularly Reinforcement Learning (RL), have gained widespread attention for optimizing traffic signal control in intelligent transportation systems. However, existing ML approaches often exhibit limitations in scalability and adaptability, particularly within large traffic networks. This paper introduces an innovative solution by integrating decentralized graph-based multi-agent reinforcement learning (DGMARL) with a Digital Twin to enhance traffic signal optimization, targeting the reduction of traffic congestion and network-wide fuel consumption associated with vehicle stops and stop delays. In this approach, DGMARL agents are employed to learn traffic state patterns and make informed decisions regarding traffic signal control. The integration with a Digital Twin module further facilitates this process by simulating and replicating the real-time asymmetric traffic behaviors of a complex traffic network. The evaluation of this proposed methodology utilized PTV-Vissim, a traffic simulation software, which also serves as the simulation engine for the Digital Twin. The study focused on the Martin Luther King (MLK) Smart Corridor in Chattanooga, Tennessee, USA, by considering symmetric and asymmetric road layouts and traffic conditions. Comparative analysis against an actuated signal control baseline approach revealed significant improvements. Experiment results demonstrate a remarkable 55.38% reduction in Eco_PI, a developed performance measure capturing the cumulative impact of stops and penalized stop delays on fuel consumption, over a 24 h scenario. In a PM-peak-hour scenario, the average reduction in Eco_PI reached 38.94%, indicating the substantial improvement achieved in optimizing traffic flow and reducing fuel consumption during high-demand periods. These findings underscore the effectiveness of the integrated DGMARL and Digital Twin approach in optimizing traffic signals, contributing to a more sustainable and efficient traffic management system.

actuated signal control↗

DOE OSTI2022

A Study of Propane Combustion in a Spark-Ignited Cooperative Fuel Research (CFR) Engine

Liquefied petroleum gas (LPG), whose primary composition is propane, is a promising candidate for heavy-duty vehicle applications as a diesel fuel alternative due to its CO 2 reduction potential and high knock resistance. To realize diesel-like efficiencies, spark-ignited LPG engines are proposed to operate near knock-limit over a wide range of operating conditions, which necessitates an investigation of fuel-engine interactions that leads to end-gas autoignition with propane combustion. This work presents both experimental and numerical studies of stoichiometric propane combustion in a sparkignited (SI) cooperative fuel research (CFR) engine. Engine experiments are initially conducted at different compression ratio (CR) values, and the effects of CR on engine combustion are characterized. A three-pressure analysis (TPA) model based on the two-zone combustion concept is developed in GT-Power and validated using test results to estimate in-cylinder wall temperatures, residual gas fraction, etc. This model is further utilized to examine end-gas chemistry by enabling the SI turbulent flame combustion and unburned gas chemical kinetics modules. Finally, a three-dimensional (3D) computational fluid dynamic (CFD) model of the CFR engine is developed in CONVERGE, where the G-equation and SAGE detailed chemical kinetics models are implemented for combustion modeling. Here, a 153 species reduced chemical kinetics mechanism derived from the detailed NUIGMech1.1 mechanism based on the ignition delay and laminar flame speed (LFS) studies is used to generate an LFS lookup table and to describe end-gas autoignition chemistry. Multi-cycle Reynolds-averaged Navier-Stokes (RANS) simulations are then performed for the tested CRs, and the numerical model is shown to be capable of predicting the propane combustion characteristics, particularly the end-gas autoignition behavior.

20 FOSSIL-FUELED POWER PLANTS↗

DOE OSTI2020

Toward Exascale: Overview of Large Eddy Simulations and Direct Numerical Simulations of Nuclear Reactor Flows with the Spectral Element Method in Nek5000

At the beginning of the last decade, Petascale supercomputers (i.e., computers capable of more than 1 petaFLOP) emerged. Now, at the dawn of exascale supercomputing, we provide a review of recent landmark simulations of portions of reactor components with turbulence-resolving techniques that this computational power has made possible. In fact, these simulations have provided invaluable insight into flow dynamics, which is difficult or often impossible to obtain with experiments alone. We focus on simulations performed with the spectral element method, as this method has emerged as a powerful tool to deliver massively parallel calculations at high fidelity by using large eddy simulation or direct numerical simulation. We also limit this paper to constant-property incompressible flow of a Newtonian fluid in the absence of other body or external forces, although the method is by no means limited to this class of flows. We briefly review the fundamentals of the method and the reasons it is compelling for the simulation of nuclear engineering flows. We review in detail a series of Petascale simulations, including the simulations of helical coil steam generators, fuel assemblies, and pebble beds. Even with Petascale computing, however, limitations for nuclear modeling and simulation tools remain. In particular, the size and scope of turbulence-resolving simulations are still limited by computing power and resolution requirements, which scale with the Reynolds number. In the final part of this paper, we discuss the future of the field, including recent advancements in emerging architectures such as GPUbased supercomputers, which are expected to power the next generation of high-performance computers.

computational fluid dynamics↗