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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Grid-Scale Ternary-Pumped Thermal Electricity Storage for Flexible Operation of Nuclear Power Generation under High Penetration of Renewable Energy Sources

In this work, the integration of a grid-scale ternary-Pumped Thermal Electricity Storage (t-PTES) with a nuclear power generation to enhance operation flexibility is assessed using physics-based models and digital real time simulation. A part of the electricity from the nuclear power generation is delivered to the grid, and the balance is used to power a heat pump that can be augmented by an auxiliary resistive load element to increase the charging rate of the thermal storage. This increases the thermal potential between hot and cold thermal stores (usually solid materials or molten salts inside large storage tanks). The thermal energy is transformed back into electricity by reversing the heat pump cycle. Different transient scenarios including startup, shutdown, and power change for grid-connected operation are simulated to determine the behavior of the hybrid nuclear-t-PTES system operating under variable loads that constitute a departure from conventional, baseload nuclear plant operation schemes. Ternary refers to the three modes operation: (i) heat pump (including heating coil), (ii) heat engine, and (iii) simultaneous operation of heat pump (including heating coil) and heat engine during changeover from pumping to generation or vice-versa. The controllability of t-PTES in the short timescales as a dynamic load is used to demonstrate operational flexibility of hybrid nuclear plants for flexible operation through advanced load management. The integration of t-PTES into nuclear power systems enhances the system flexibility and is an enabler for high penetration of renewable energy resources.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

The scoping, design, and plasma physics optimization of the Eos neutron source stellarator

On the path to a fusion pilot plant, Thea Energy plans to build Eos, a sub-breakeven, deuterium-deuterium, beam-target fusion, stellarator neutron source facility for producing tritium and other valuable radioisotopes. In this paper, a set of 1D plasma physics models are coupled and used to design the operating point of the facility and predict performance. At this foundational stage of the design, analytic and approximate models are sufficient to capture the leading-order effects, and fast enough to run in the inner loop of an optimizer. Higher-fidelity analyses will follow. Models of 1D profile-dependent neutral beam stopping, ion beam slowing down, beam-target fusion, electron-ion classical heat transfer, energy confinement (ISS04), beam pressure, beam heating of ions and electrons, beam-beam fusion fraction, and neutral beam injection and gyrotron heating electrical efficiencies are included. A numerical optimizer is used to determine the minimum required facility electric power to generate tritium at a given rate. A potentially advantageous regime is described in which modern precisely-quasisymmetric stellarators, new high-temperature superconductors, ITER-derived neutral beam injection, and new high-frequency gyrotrons enable a suitible target plasma with hot electrons, cold ions, peaked density and temperature profiles, and high beam-injected ion density. It appears possible at this time for a facility with a medium-scale and medium-strength stellarator whose required facility electric power is less than 40 MW to produce $2.5\times 10^{17}$ neutrons s -1 for the production of radioisotopes. With the addition of a tritium breeding blanket, such a facility could produce 0.2 grams d -1 or 70 grams yr -1 of tritium.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Assessing parallel path cooling tower performance via artificial neural networks

Real-time monitoring of a research nuclear reactor, a system in which all generated power is dissipated to the environment, can be performed via analysis of the heat rejection from the cooling system. Given an inlet water temperature and flow rate, the reactor power can be well-approximated from the outlet water temperature; however, the instrumentation to measure outlet conditions may not be robust or accurate. If we know how a cooling tower performs from historical data, but cannot measure the outlet temperature, a mathematical representation of the system can be inverted to obtain the outlet water temperature that describes the cooling capacity. Unfortunately, model inversion processes are computationally expensive. To address this, an artificial neural network (ANN) is implemented to assess the performance of a multi-cell cooling tower for a nuclear reactor. This approach leverages the Merkel model to obtain an extensive data set describing performance of the cooling tower cells throughout a wide array of potential operating conditions. The Merkel model is expressed as a function of four parameters: the inlet and outlet water temperatures, inlet air wet bulb temperature, and ratio of liquid-to-gas mass flow rates (L/G), which together provide a non-dimensional number indicative of cooling tower performance, called the Merkel integral. Computing a 4-dimensional data structure that describes finite combinations of the Merkel integral, an inverse model is then generated using an ANN to determine the cell outlet water temperature from the other three model parameters along with the computed Merkel integral. Compared to traditional model inversion methods, the ANN reduces the computational time by approximately 4 orders of magnitude, with effectively no sacrifice to solution accuracy, and could be applied for different cooling towers in the event the performance curve is known. Finally, three use cases of the ANN are then reviewed: (1) determining the cell outlet water temperatures when gas flow at rated conditions (GFRC) is known, (2) performing the prior case without knowledge of the GRFC, and (3) assessing performance differences between the individual tower cells.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

Stability and Characteristics of Lower-hybrid Drift Waves: Dependence on Electron Beta and Cross-field Relative Drift

Lower-hybrid drift waves (LHDWs) are frequently observed microinstabilities in both space and laboratory plasmas. Despite decades of study, the relationship between electrostatic (ES-LHDW) and electromagnetic (EM-LHDW) variants and the plasma parameters controlling their stability remains unclear. Here, we systematically examine LHDW behavior by solving the local linear dispersion relation over a wide range of plasma and field conditions. Our results demonstrate that ES-LHDWs and EM-LHDWs are not distinct modes but rather two different regimes of the same drift wave whose character evolves smoothly with electron beta (β e ) and the cross-field electron drift velocity relative to ions, normalized to the ion sound speed (u 0x /C s ). The nature of the waves changes from electrostatic to electromagnetic when β e increases. Growth rates increase with u 0x /C s but decrease with β e , while the most unstable wavelength remains nearly universal, with kρ e ∼ 0.8 (k is the magnitude of the wave vector and ρ e is the electron gyroradius). We further present quasi-linear estimates of nonlinear saturation properties, including energy partition among electric fields, magnetic fields, and particle kinetic responses. We show that ES-LHDWs reach higher electric-field saturation amplitudes, whereas EM-LHDWs generate strong magnetic perturbations and parallel electric fields that may enable efficient particle heating. Comparisons with the classical model reveal that retaining electromagnetic effects is essential for accurate predictions of frequency, growth rate, and the propagation angle. These findings provide a unified framework for understanding LHDWs across diverse collisionless plasma environments, including current sheets of magnetic reconnection, shear layers, collisionless shocks, and boundary regions.

Solar coronal waves↗
DOE OSTI2024

Evidence of non-isentropic release from high residual temperatures in shocked metals measured with ultrafast x-ray diffraction

Shock experiments are widely used to understand the mechanical and electronic properties of matter under extreme conditions. However, after shock loading to a Hugoniot state, a clear description of the post-shock thermal state and its impacts on materials is still lacking. We used diffraction patterns from 100-fs x-ray pulses to investigate the temperature evolution of laser-shocked Al–Zr metal film composites at time delays ranging from 5 to 75 ns driven by a 120-ps short-pulse laser. We found significant heating of both Al and Zr after shock release, which can be attributed to heat generated by inelastic deformation. A conventional hydrodynamic model that employs (i) typical descriptions of Al and Zr mechanical strength and (ii) elevated strength responses (which might be attributed to an unknown strain rate dependence) did not fully account for the measured temperature increase, which suggests that other strength-related mechanisms (such as fine-scale void growth) could play an important role in thermal responses under shock wave loading/unloading cycles. Our results suggest that a significant portion of the total shock energy delivered by lasers becomes heat due to defect-facilitated plastic work, leaving less converted to kinetic energy. This heating effect may be common in laser-shocked experiments but has not been well acknowledged. High post-shock temperatures may induce phase transformation of materials during shock release. Another implication for the study is the preservability of magnetic records from planetary surfaces that have a shock history from frequent impact events.

42 ENGINEERING↗
DOE OSTI2024

Towards Net-Zero: Nuclear-Assisted Waste Biomass to Liquid Fuel in Eastern Idaho

A nuclear assisted carbon negative hybrid energy process that enables production of synthetic bio-crude oil and biochar from Eastern Idaho waste biomass is proposed. The process integrates nuclear powered electricity with high temperature steam electrolysis and biomass hydropyrolysis. The bio-crude oil is of sufficient composition and blended with traditional crude oil at a refinery. Hydrogen from the electrolyzer is pressurized and inserted into the pyrolyzer. Non condensable gases generated in the hydropyrolysis process are burned with oxygen from the electrolyzer to produce heat for the electrolyzer, biomass dryer, and pyrolyzer. The biochar is returned to the soil via fertilizer application and remains there for thousands of years. Since the total process uses nuclear generated electricity, the carbon in the biochar is ultimately sequestered from the atmosphere, thus making the process carbon negative. Using Eastern Idaho wheat or barley straw, this hybrid energy process has the potential to provide an alternative petroleum source. Two options exist for the system design: 1) send electricity from the nuclear plant and straw to a chemical processing plant to produce the bio-crude and biochar, 2) construct the biomass processing facility near the nuclear plant to allow use of nuclear-generated process heat to drive the chemical. Process model description and results are discussed. The process is sized to produce gasoline and diesel at the rate that the INL uses every day for fleet usage.

09 BIOMASS FUELS↗
DOE OSTI2021

Thermal-Mechanical Elastic-Plastic and Ductile Failure Model Calibrations for 304L Stainless Steel Alloy

Numerical simulations of metallic structures undergoing rapid loading into the plastic range require material models that accurately represent the response. In general, the material response can be seen as having four interrelated parts: the baseline response under slow loading, the effect of strain rate, the conversion of plastic work into heat and the effect of temperature. In essence, the material behaves in a thermal-mechanical manner if the loading is fast enough so when heat is generated by plastic deformation it raises the temperature and therefore influences the mechanical response. In these cases, appropriate models that can capture the aspects listed above are necessary. The material of interest here is 304L stainless steel, and the objective of this work is to calibrate thermal-mechanical models: one for the constitutive behavior and another for failure. The work was accomplished by first designing and conducting a material test program to provide data for the calibration of the models. The test program included uniaxial tension tests conducted at room temperature, 150 and 300 C and at strain rates between 10 –4 and 10 3 1/s. It also included notched tension and shear-dominated compression hat tests specifically designed to calibrate the failure model. All test specimens were extracted from a single piece of plate to maintain consistency. The constitutive model adopted was a modular $J_2$ plasticity model with isotropic hardening that included rate and temperature dependence. A criterion for failure initiation based on a critical value of equivalent plastic strain fitted the failure data appropriately and was adopted. Possible ranges of the values of the parameters of the models were determined partially on historical data from calibrations of the same alloy from other lots and are given here. The calibration of the parameters of the models were based on finite element simulations of the various material tests using relatively ne meshes and hexahedral elements. When using the model in structural finite element calculations, however, element formulations and sizes different from those in the calibration are likely to be used. A brief investigation demonstrated that the failure initiation predictions can be particularly sensitive to the element selection and provided an initial guide to compensate for the effect of element size in a specific example.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Next steps in high-repetition-rate laser development for Thomson scattering

Design of a next generation high-rep-rate laser system is underway, aiming for a maximum rep rate of 100 kHz for 1 ms. This will be a "pulse-burst" laser, which is a type of heat-capacity laser. Heat-capacity laser operation is characterized by a burst of pulses of limited duration, with burst length ≤100 ms and pulse rep rate ≥1 kHz. Waste heat accumulates in the laser rod during the burst. This heat is deposited evenly throughout the rod volume, with very little heat removed during the burst, such that temperature rises evenly across the rod radius. Thus beam distortion due to thermal gradients is small. Heat is removed from the rod after the burst, with typically tens of seconds between bursts. Pulse-burst operation of flashlamp pumped Nd:YAG lasers is a cost-effective route to high-rep-rate capability. Pulse-burst laser systems with "fast burst" rep rates in the range of 10–20 kHz have been built for the Thomson scattering diagnostics on MST, NSTX-U, and LHD. For Thomson scattering diagnostic application, the typical requirements are 1064 nm, 1–2 J/pulse, ≤30 ns FWHM pulse, with a top-hat beam profile. A major requirement for this next generation laser system is flexibility in burst sequence programs, ranging from 1 kHz for 100 ms to 100 kHz for 1 ms, and a variety of scenarios in between so that operation can be tailored to plasma experiment requirements. Flashlamp pumping will be used for this next generation laser because it is inexpensive and flexible. A new switch-regulated flashlamp driver will provide improved flashlamp control at lower cost. Additional design issues such as the optimum flashlamp pumping spectrum and optimum Nd doping will be addressed. The use of commercial off-the-shelf components will be maximized in this laser system so that pulse-burst systems can be developed and built by others for new applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Material Selection and Sizing of a Thermoelectric Generator (TEG) for Power Generation in a Self-Powered Heating System

By employing the high temperature heat source to directly generate the electricity needed to power auxiliary systems in a natural gas furnace, boiler or hot water heater, a “self-powered” heating system can provide several benefits. Compared with a traditional furnace, boiler or hot water heater, when overall fuel utilization is kept constant, the self-powered system will have a higher primary energy efficiency, lower operating costs, and dramatically improved building safety and resilience during electric grid outages. Furthermore, a self-powered heating system only has a single utility connection – natural gas, without an electric connection – thus simplifying installation. A thermoelectric generator can be used for direct energy conversion of thermal energy to electricity with no moving parts, which offers a very simple means to provide power for the self-powered heating system, and the operation is without noise or vibration and can thus provide a very long system life. This paper provides an analysis focused on materials selection and the thermal power requirements for a thermoelectric generator (TEG) for use in a self-powered heating system. The dimensionless figure of merit for thermoelectric materials, zT, is used to estimate the optimal efficiency that can be achieved with a TEG to produce the electric power required in such an application. Comparisons of the predicted efficiency, the required heat transfer rate to the TEG and the heat transfer area needed for sustained operation under thermal conditions relevant to the self-powered heating application are made for several potential thermoelectric materials. This analysis was used to develop system requirements for a self-powered hot water heater using a TEG for electric power generation.

Laclair, Tim↗
DOE OSTI2022

Automation of FARM from Alpha Phase to Beta Phase

Integrated energy systems (IES) combine different energy technologies in synergistic ways to achieve a more secure and economical energy supply. The RAVEN-based HYBRID framework and the RAVEN plugin for grid and capacity optimization (HERON) are used to find the optimal installed capacity and the optimal economical dispatch of each component of the IES, by respecting the limits on the production variables and the corresponding rates of variation (explicit constraints). Besides, there are other process variables whose evolution needs to be bounded to avoid damaging the components (e.g., condensers, heat exchangers, steam generators, etc.) or degrading the process efficiency (e.g., electrolysis in the hydrogen production process). To avoid violating these latter limits (implicit constraints), a proof-of-concept HERON validator based on Feasible Actuator Range Modifier (FARM-Alpha) was developed by Argonne National Laboratory in January 2021. This FARM-Alpha validator calculates the evolution of process variables on whom the implicit constraints are placed, and then provides feedback to HERON dispatcher to adjust the power setpoints of three IES components, i.e., Balance of Plant, Secondary Energy Source, and Thermal Energy Storage, so as to meet both the explicit and implicit constraints. FARM-Alpha was designed to assess the performance of FARM as a HERON validator only, i.e., the list of components and implicit operational constraints were hard-coded within the source code. The lack of flexibility of the corresponding software structure does not allow the deployment in production environment. This report describes the development and the implementation of an enhanced version of the FARM-based validator (FARM-Beta), which ensures more flexibility for the end user in modeling multiple IES configurations and scenarios. Several test cases of the power dispatch problem were then selected to demonstrate the capabilities offered by FARM-beta. The test cases illustrate the efficiency of the closed-loop optimization scheme and the capability to calculate set-point trajectories satisfying both explicit and implicit constraints.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

Competitiveness Assessment of Decarbonizing Electricity and Process Heat Supply to a Campus with a Small Nuclear Reactor

This paper analyzes the competitiveness of siting a small nuclear reactor to support decarbonization of sites requiring tens of MW of electricity and/or process heat to support centralized heating and cooling system. This paper focuses on campuses as representative of sites with collections of buildings and research facilities with decarbonization needs represented by buildings heating, and electricity consumption by electrical loads which may include cooling via chilled water (e.g., for air conditioning and to cool down computer clusters). A nuclear reactor can be considered to decarbonize a site’s high-temperature steam generation used mostly for building heating needs, climate control, and hot water, by supplying process heat capabilities, while electricity decarbonization would be achieved mostly by the grid. However, a secondary application can be considered to maximize reactor utilization and avoid ramping down the reactor if the steam demand varies significantly throughout the year. Chilled water generation through steam-driven systems was identified as an attractive secondary option for the site analyzed, due to potential for plant design simplification, while electricity generation could be considered as well to reduce electricity purchases for a wider range of site applications. For a campus with peak 60MW thermal power demand, a small nuclear reactor with similar thermal power rating would almost eliminate CO2 emissions from steam generation and reduce electricity imports for chilled water production. A preliminary techno-economic feasibility study shows that a small nuclear reactor design that is optimized to support process heat can represent an economically feasible option when compared with other decarbonization alternatives.

Stauff, Nicolas E.↗
DOE OSTI2022

Conceptual Design of Pulverized Coal Electricity Generating Units for Flexible Operation

This National Energy Technology Laboratory (NETL) study addresses the conceptual design of greenfield pulverized coal (PC) plants intended for flexible rather than high capacity factor baseload operation. The United States has plentiful, low-cost natural gas resources - studies of aggressive decarbonization scenarios of the US energy sector suggest that the variability of carbon-free power can be economically addressed using dispatchable natural gas-fueled generation. Globally, natural gas resources are not as plentiful or low cost; consequently, some regions of the world are anticipated to continue to rely upon coal generation, even as they pursue decarbonization efforts. To support the increased utilization of variable renewable generation in these coal-dependent regions, plant designs must target low-capacity factor coal plants with increased emphasis on flexibility attributes such as start-up times, ramp rates, minimum load, and part-load heat rates. While much work has been performed on the improvement of the flexibility for existing coal plants originally designed for baseload service, little public literature exists on clean sheet design for flexible operation. This conceptual design study aims to define the features, performance characteristics, and costs for greenfield coal plants intended for flexible operation. Quantifying these characteristics provides critical information required by utility owners, grid planners, energy market modelers, and energy policy decision makers in coal-dependent regions of the world to better understand how coal-fired power plants can support a transition to low carbon generation.

20 FOSSIL-FUELED POWER PLANTS↗
DOE OSTI2022

FY22 Progress on Computational Modeling of the Water-Based NSTF

This report summarizes the system-level modeling effort by Argonne National Laboratory (Argonne) of the Natural convection Shutdown heat removal Test Facility (NSTF) in FY22. As an extension of the effort from FY21, this year’s work focuses primarily on the two-phase modeling of the NSTF using RELAP5-3D, particularly with the inclusion of the cavity model. The results from simulations were used to compare against experimental data for benchmarking purposes of the RELAP5 deck. Additionally, RELAP5 was used as a predictive tool to guide planned test operations and identify expected system behaviors. In the first part of this report, details are provided of the cavity omitted model where heat flux is applied directly as a boundary condition to the risers. The general trend predicted by the RELAP5 model matches that from the experimental data when a single-phase natural circulation flow is first established, followed by an oscillatory two-phase period and finally a stable two-phase flow. However, the onset of oscillations is predicted early by the model due to the smaller thermal mixing region in the tank. However, by expanding the simulated thermal mixing region in the tank, the onset of oscillations predicted by the model is able to match that from the experiment. These oscillations where studied in depth and are deduced to be flashing-induced instability. The model was then modified to simulate an accident scenario case where a representative heat load based on the full-scale Framatome’s 625 MW t SC-HTGR was applied directly to the riser channels. The simulated initial and boundary conditions were identical to those performed experimentally, facilitating direct comparisons between the predicted and experimental results. It was determined that the results showed some discrepancies remain, likely due to the overprediction of vapor generation rate by the computer model. In the second part of this report, the cavity model is re-introduced where it is observed that the RELAP5 prediction is now able to capture the major trends of the observed flow commonly observed during two-phase conditions. However, the onset of oscillations is once again predicted early by the model, possibly caused by the underprediction of heat loss from the heater and cavity. This is likely due to the omission of support structures in the cavity that can act as additional pathways for heat to escape to the environment. To overcome the underprediction of heat loss, part of the insulation surrounding the cavity side panels and the back of the heaters are removed to allow heat to escape directly to the environment, which then improves the RELAP5 prediction. Parametric studies are also performed to investigate the effects of heater power, tank inventory level, and tank gas space pressure on flow behaviors, also in direct comparison to conditions tested experimentally. User option-61 in the RELAP5-3D input deck, which changes the heat transfer coefficient correlations used for calculating the vapor generation, is also investigated where it is found that by enabling the option, the overall duration of oscillations is increased and matches that from the experiment better. The RELAP5 model is further benchmarked with a header inlet- throttling case where it is observed that the prediction from the model fails to capture some major features observed in the experiment. By using a modified loss coefficient curve for the valve, the accuracy of the prediction is improved where most of the major features observed in the experiment are predicted by the model. Lastly, the model is benchmarked with an inventory depletion scenario where it is observed that despite the modeling limitation of RELAP5, the prediction shows good agreement with the experimental data where major trends and features are captured by the model. Future work will see continued development of the current RELAP5-3D input deck of the NSTF to both improve the accuracy of the model’s predictive capability and continuing serving the experimental program. The mutually beneficial relationship between analysis and experimental efforts has become integral to the parent NSTF program, and the greater objective to fully understand and accurately predict the heat removal performance of a full scale RCCS concept.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Calculating Behind-the-Meter Energy Storage Incentives on an Avoided Cost Basis

Behind-the-meter (BTM) energy storage offers the potential for shared investment by utilities and their customers, in which both parties share in the costs and benefits of battery investment. Several utilities and a handful of states have begun providing incentives to help customers purchase BTM energy storage, and in exchange, operate that battery on behalf of the customer to realize grid benefits such as meeting peak capacity needs. But there is wide variation in the value and structure of these incentives, suggesting a lack of clarity on the value of BTM storage to the grid and to non-participating customers who fund the incentives for participating customers. This paper provides an objective framework for establishing BTM energy storage incentives based on the avoided cost of generation from a marginal, gas-fired peaking plant. It also conducts several sensitivity analyses to see how those avoided costs vary with emissions pricing, gas prices, plant heat rates, and utility capital structures. This work may be of use to utilities, regulators, and energy system stakeholders in providing a value-based framework for BTM incentive programs that can be used in the absence of policy guidance.

Twitchell, Jeremy B.↗
DOE OSTI2021

A Transported Livengood–Wu Integral Model for Knock Prediction in Computational Fluid Dynamics Simulation

This work describes the development of a transported Livengood–Wu (L–W) integral model for computational fluid dynamics (CFD) simulation to predict autoignition and engine knock tendency. The currently employed L–W integral model considers both single-stage and two-stage ignition processes, thus can be generally applied to different fuels such as paraffin, olefin, aromatics, and alcohol. The model implementation is first validated in simulations of homogeneous charge compression ignition (HCCI) combustion for three different fuels, showing good accuracy in prediction of autoignition timing for fuels with either single-stage or two-stage ignition characteristics. Then, the L–W integral model is coupled with G-equation model to indicate end-gas autoignition and knock tendency in CFD simulations of a direct-injection spark-ignition engine. This modeling approach is about 10 times more efficient than the ones that based on detailed chemistry calculation and pressure oscillation analysis. Two fuels with same Research Octane Number (RON) but different octane sensitivity are studied, namely, Co-Optima alkylate and Co-Optima E30. Feed-forward neural network model in conjunction with multivariable minimization technique is used to generate fuel surrogates with targets of matched RON, octane sensitivity, and ethanol content. The CFD model is validated against experimental data in terms of pressure traces and heat release rate for both fuels under a wide range of operating conditions. The knock tendency—indicated by the fuel energy contained in the autoignited region—of the two fuels at different load conditions correlates well with the experimental results and the fuel octane sensitivity, implying the current knock modeling approach can capture the octane sensitivity effect and can be applied to further investigation on composition of octane sensitivity.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2020

A transported Livengood-Wu integral model for knock prediction in CFD simulation

This work describes the development of a transported Livengood-Wu (L-W) integral model for computational fluid dynamics (CFD) simulation to predict auto-ignition and engine knock tendency. The currently employed L-W integral model considers both single-stage and two-stage ignition processes, thus can be generally applied to different fuels such as paraffin, olefin, aromatics and alcohol. The model implementation is first validated in simulations of homogeneous charge compression ignition combustion for three different fuels, showing good accuracy in prediction of auto-ignition timing for fuels with either single-stage or two-stage ignition characteristics. Then, the L-W integral model is coupled with G-equation model to indicate end-gas auto-ignition and knock tendency in CFD simulations of a direct injection spark ignition engine. This modeling approach is about 10 times more efficient than the ones that based on detailed chemistry calculation and pressure oscillation analysis. Two fuels with same Research Octane Number (RON) but different octane sensitivity are studied, namely Co-Optima Alkylate and Co-Optima E30. Feed-forward neural network model in conjunction with multi-variable minimization technique is used to generate fuel surrogates with targets of matched RON, octane sensitivity and ethanol content. The CFD model is validated against experimental data in terms of pressure traces and heat release rate for both fuels under a wide range of operating conditions. The knock tendency indicated by the fuel energy contained in the auto-ignited region of the two fuels at different load conditions correlates well with the experimental results and the fuel octane sensitivity, implying the current knock modeling approach can capture the octane sensitivity effect and can be applied to further investigation on composition of octane sensitivity.

Yue, Zongyu↗
DOE OSTI2021

Summary of Previous Mechanical Test Data on ODS Alloys 14YWT and OFRAC up to 1000ºC

The Nanostructured Ferritic Alloys (NFA) 14YWT and OFRAC were developed for future fission and fusion nuclear energy reactors requiring high-temperature mechanical properties that are tolerant to extreme neutron irradiation environments. The NFA contain a high concentration of Ti-, Y- and O-enriched nanoclusters (NC) and ultra-fine grains to achieve high temperature strength and creep properties and high sink strength for trapping irradiation induced point defects to minimize hardening and swelling and transmutated He atoms to form intragranular nano-size bubbles that prevent formation of coarse bubbles on grain boundaries that cause embrittlement. The mechanical properties of 14YWT and OFRAC have been acquired from tensile and creep tests conducted in the past at Oak Ridge National Laboratory. The development of 14YWT started in 2000, resulting in the production of numerous heats. Tensile properties were obtained from eleven heats of 14YWT from room temperature to 800ºC. Tensile data for the SM10 heat of 14YWT was extended to 1,000ºC. Initial development of OFRAC occurred in 2016. Tensile tests conducted from room temperature to 800ºC revealed similar properties of OFRAC with those obtained from the newer generation of 14YWT heats. The creep properties of 14YWT-SM10 evaluated using constant stress tensile and load time-to-failure tests at 800ºC showed low minimum creep rates with stresses of 200 and 100 MPa. The single time-to-failure test of 14YWT-SM10 at 800ºC and 100 MPa was terminated after 20,357 hours with no specimen failure and a low creep strain of ~0.24 %. The creep properties of OFRAC determined from strain-rate jump tests at were similar those of 14YWT-SM10. The stress exponent for 14YWT and OFRAC at 800ºC are similar and are consistent with threshold stress behavior. Since both 14YWT and OFRAC are candidates for fuel cladding in future fast reactors, several fabrication studies were recently conducted and have successfully demonstrated that thin wall tubes can be fabricated from 14YWT and OFRAC by cold pilger rolling and high precision tube rolling. The high temperature mechanical properties and feasibility of fabricating thin wall tubes make 14YWT and OFRAC candidates for application as heat pipes in advanced micro-reactors. The purpose of this report is to summarize the previously obtained tensile and creep data at temperatures up to 1000ºC for NFA 14YWT and OFRAC that have been acquired over the past 20 years at ORNL.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Characterization of Build Parameters and Microstructure in Low Heat Input WAAM of Ni-Based Superalloy Haynes 282

Ni-based superalloy Haynes® 282® is being targeted for various applications in advanced power generation systems for its superior fabricability, weldability, and excellent high temperature creep and corrosion performance. This process optimization study aims to use a low heat-input, high deposition rate, controlled Gas Metal Arc Welding (GMAW) process, Cold Metal Transfer (CMT) by Fronius, attempting to achieve fully dense fabrication and possibly avoid the need for HIP. Twenty-one multilayer blocks (~25x100x40 mm3) were deposited to explore a large set of build parameters variations that focused on varying the travel speed from 14 to 42 inches per minute (ipm) and wire feed speed from 150 to 450 ipm. A strong correlation has been observed between arc energy – controlled primarily by travel and wire feed speed. Initial visual inspection, internal microstructural examination, and computed tomography (CT) have been used to determine the effects of built parameters on evolution of internal porosity and defects. Scanning electron microscopy techniques enabled structural and compositional imaging of heterogeneity and changes in microstructural properties.

additive manufacturing↗