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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

A Potts Model parameter study of particle size, Monte Carlo temperature, and “Particle-Assisted Abnormal Grain Growth”

A Potts Model was proposed to account for temperature and particle heterogeneity-dependent Zener Pinning. This was accomplished by relating the random fluctuations of grain boundary position allowed by the Potts Model switching probability at finite simulation temperature to experimentally observed grain growth stagnation behavior. We assume that these fluctuations arise from random fluctuations in the thermodynamic and kinetic properties of the grain boundaries and/or interfaces as they change with temperature. As an application of this model, the grain growth kinetics of U-10 wt. % Mo nuclear fuels were simulated with the input of microstructural images during different heat treatment processes. Simulated average grain growth behavior is in good agreement with experiments.

Frazier, William E.↗
DOE OSTI2021

Improving the W Coating Uniformity by a COMSOL Model-Based CVD Parameter Study for Denser W f /W Composites

Tungsten (W) has the unique combination of excellent thermal properties, low sputter yield, low hydrogen retention, and acceptable activation. Therefore, W is presently the main candidate for the first wall and armor material for future fusion devices. However, its intrinsic brittleness and its embrittlement during operation bears the risk of a sudden and catastrophic component failure. As a countermeasure, tungsten fiber-reinforced tungsten (W f /W) composites exhibiting extrinsic toughening are being developed. A possible W f /W production route is chemical vapor deposition (CVD) by reducing WF 6 with H 2 on heated W fabrics. The challenge here is that the growing CVD-W can seal gaseous domains leading to strength reducing pores. In previous work, CVD models for W f /W synthesis were developed with COMSOL Multiphysics and validated experimentally. In the present article, these models were applied to conduct a parameter study to optimize the coating uniformity, the relative density, the WF 6 demand, and the process time. A low temperature and a low total pressure increase the process time, but in return lead to very uniform W layers at the micro and macro scales and thus to an optimized relative density of the W f /W composite. High H 2 and low WF 6 gas flow rates lead to a slightly shorter process time and an improved coating uniformity as long as WF 6 is not depleted, which can be avoided by applying the presented reactor model.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Parameter Study of the Running-In Process for the Generic Pebble Bed Reactor (GPBR200)

The run-in period of a pebble bed reactor is complex and difficult to model given significant heterogeneity in core composition, power, and temperature. While it is understood that the initial composition of the core should eventually result in the same equilibrium core composition, the approach to equilibrium can vary significantly depending on factors such as start-up fuel enrichment and power ramp rate. To explore this, a high-fidelity model of the General Pebble Bed Reactor was used to vary power ramp schemes and start-up core compositions. It was found that both the initial core composition and power ramp rate had a significant impact on the flow rate of pebbles during early time steps, with higher ramp rates and low enrichment resulting in non-physical flow rates. Power ramp rate alone was found to dictated maximum pebble power peaking observed during the run-in process, with higher ramp rates resulting in greater peak pebble powers. Start-up fuel enrichment and power ramp were found to both impact total fuel consumption, although the impact of start-up fuel enrichment was generally secondary to ramp rate.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Parameter study of a Kinetic Phase Transition model

We investigate the ability of the two model parameters in the Kinetic Phase Transition (KPT) model of Carl Greeff to describe phase transitions of various types when combined with the tin Equation of states for the phases, SESAME 2162. While the two parameters are correlated, one combination can be associated with the nucleation process giving rise to the hysteresis seen in phase transition paths in pressure-temperature space and another can be associated with the overall timescale of the transition. We acknowledge the desire to have a model where the parameters are more independent of each other for easier model parameter determination.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

An experimental process parameter study on the identification of defects in additively fabricated Al6061 with laser powder bed fusion

Additively fabricated metal parts using laser powder bed fusion (L-PBF) possess sophisticated morphology due to the recurrent use of laser-induced metal powder melting and solidification. The surface and 3D morphology of these parts often include defects in the form of protrusions, depressions, pores, voids, keyholes, or cracks that are known to be influenced by laser scanning paths and layer-to-layer processing. Such inconsistent part quality hampers the extensive adoption of L-PBF. Pores and cracks are detrimental to the fatigue life of the parts and components. Quantifying and controlling part defects and optimizing processing and scanning strategy parameters adaptively in real-time through in situ monitoring systems are highly desired. This study investigates the optimization of experimental process parameters (power, scan velocity, and hatch spacing) and their effects on the cracking and porosity of Al6061 alloy using machine learning techniques. Multi-objective optimization is formulated and conducted to determine the L-PBF parameters that minimize both porosity and crack densities.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Multidimensional Parameter Study of Double Detonation Type Ia Supernovae Originating from Thin Helium Shell White Dwarfs

Despite the importance of Type Ia supernovae (SNe Ia) throughout astronomy, the precise progenitor systems and explosion mechanisms that drive SNe Ia are still unknown. An explosion scenario that has gained traction recently is double detonation, in which an accreted shell of He detonates and triggers a secondary detonation in the underlying white dwarf. Our research presents a number of high-resolution, multidimensional, full-star simulations of thin-He-shell, sub-Chandrasekhar-mass white dwarf progenitors that undergo a double detonation. This suite of thin-shell progenitors incorporates He shells that are thinner than those in previous multidimensional studies. We confirm the viability of the double detonation across a range of He-shell parameter space, as well as present bulk yields and ejecta profiles for each progenitor. The yields obtained are generally consistent with previous works and indicate the likelihood of producing observables that resemble SNe Ia. The dimensionality of our simulations allow us to examine features of the double detonation more closely, including the details of the off-center secondary ignition and asymmetric ejecta. We find considerable differences in the high-velocity extent of postdetonation products across different lines of sight. The data from this work will be used to generate predicted observables and may further support the viability of the double detonation scenario as an SN Ia channel, as well as show how the properties of the progenitor or viewing angle may influence trends in observable characteristics.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Preliminary parameter studies to form pellets of hard materials for optical constants derived via single-angle reflectance spectroscopy

Infrared reflectance spectra can be influenced by many factors: the substrate and the thickness of the layer for liquids and the surface micromorphology, the form (powder, crystal) and the particle size for solids. All these parameters can play a role in the appearance of the measured spectrum. To avoid collecting multitudes of spectra to cover all such scenarios, the optical constants n and k, which are intrinsic properties of a material, can instead be used to model the reflectance spectrum. For solids, two techniques are often used to derive optical constants: ellipsometry and single-angle reflectance spectroscopy. For both methods, best results are usually obtained from single crystals. We have recently demonstrated for ammonium sulfate (a relatively soft material) that by optimizing certain conditions, high quality pellets with specularly reflective surfaces can be used in lieu of crystals. This was confirmed by the excellent agreement between the optical constants derived by these two methods. This work focuses on the possible extension of these methods to harder materials, starting with sodium sulfate. The first goal is to see if high quality pellet surfaces can be obtained as for ammonium sulfate. The reflectance values and the associated optical constants can also be obtained.

Diaz, Emmanuela↗
DOE OSTI2023

Electropolishing parameters study for surface smoothening of low-$\beta$650 MHz five-cell niobium superconducting radio frequency cavity

Electropolishing (EP) is applied to niobium (Nb) superconducting radio frequency (SRF) cavities, which are used in particle accelerators for their surface treatment. The EP process for 1.3 GHz cavities has been extensively studied earlier. In this work, a parametric study on EP of low-β (0.61) 650 MHz Nb SRF cavities (LB650), which will be used in pre-production cryomodule for proton improvement plan-II (PIP-II) linear accelerator, was conducted to determine adequate EP conditions for attaining a smooth surface of the cavities. EP performed with the standard parameters and an initial cathode (cathode-I) having a cathode surface area of ~5% of the cavity surface area yielded a rough equator surface of the cavity. The grain step height on the equator weld position was measured to be ~ 32 μm. The rough surface was attributed to preferential grain etching confirmed by a polarization curve showing a linear relationship between the EP current and voltage and the absence of the current plateau region. The cathode was modified to make its surface area twice that of cathode-I. The modified cathode (cathode-M) provided a current plateau region in the corresponding I-V curves measured at different cavity temperatures. The onset voltage for the plateau was found to be higher at higher cavity temperatures. Here this study revealed that even with cathode-M, the standard 18 V was low for EP of such large-sized cavities when the cavity temperature was 18 °C. EP performed at a higher voltage of 22–24.5 V with cathode-M yielded a smooth surface with a grain step height of only 0.6 μm. The applied EP conditions also improved removal uniformity along the cavity length. In contrast to the cavity treated with cathode-I, the cavities treated with cathode-M achieved a significantly higher accelerating gradient (E acc ) in vertical tests conducted in a cryostat at 2 K. The modified EP was found efficient to produce the cavities that achieved E acc of 22.4 MV/m, required by PIP II project in the baseline RF tests, to qualify for further surface processing used to enhance their quality factors.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

A laser parameter study on enhancing proton generation from microtube foil targets

Abstract The interaction of an intense laser with a solid foil target can drive $$\sim$$ ∼ TV/m electric fields, accelerating ions to MeV energies. In this study, we experimentally observe that structured targets can dramatically enhance proton acceleration in the target normal sheath acceleration regime. At the Texas Petawatt Laser facility, we compared proton acceleration from a $$1\, {\upmu }\hbox {m}$$ 1 μ m flat Ag foil, to a fixed microtube structure 3D printed on the front side of the same foil type. A pulse length (140–450 fs) and intensity ((4–10) $$\times 10^{20}$$ × 10 20 W/cm $$^2$$ 2 ) study found an optimum laser configuration (140 fs, 4 $$\times 10^{20}$$ × 10 20 W/cm $$^2$$ 2 ), in which microtube targets increase the proton cutoff energy by 50% and the yield of highly energetic protons ( $$>10$$ > 10 MeV) by a factor of 8 $$\times$$ × . When the laser intensity reaches $$10^{21}$$ 10 21 W/cm $$^2$$ 2 , the prepulse shutters the microtubes with an overcritical plasma, damping their performance. 2D particle-in-cell simulations are performed, with and without the preplasma profile imported, to better understand the coupling of laser energy to the microtube targets. The simulations are in qualitative agreement with the experimental results, and show that the prepulse is necessary to account for when the laser intensity is sufficiently high.

43 PARTICLE ACCELERATORS↗
DOE OSTI2020

Changing the rotational direction of a wind turbine under veering inflow: a parameter study

All current-day wind-turbine blades rotate in clockwise direction as seen from an upstream perspective. The choice of the rotational direction impacts the wake if the wind profile changes direction with height. Here, we investigate the respective wakes for veering and backing winds in both hemispheres by means of large-eddy simulations. We quantify the sensitivity of the wake to the strength of the wind veer, the wind speed, and the rotational frequency of the rotor in the Northern Hemisphere. A veering wind in combination with counterclockwise-rotating blades results in a larger streamwise velocity output, a larger spanwise wake width, and a larger wake deflection angle at the same downwind distance in comparison to a clockwise-rotating turbine in the Northern Hemisphere. In the Southern Hemisphere, the same wake characteristics occur if the turbine rotates counterclockwise. These downwind differences in the wake result from the amplification or weakening or reversion of the spanwise wind component due to the effect of the superimposed vortex of the rotor rotation on the inflow's shear. An increase in the directional shear or the rotational frequency of the rotor under veering wind conditions increases the difference in the spanwise wake width and the wake deflection angle between clockwise- and counterclockwise-rotating actuators, whereas the wind speed lacks a significant impact.

17 WIND ENERGY↗
DOE OSTI2023

Sensitivity study of parameters important to Molten Salt Reactor Safety

This paper presents a molten salt reactor (MSR) design parameter sensitivity study using a nodal dynamic modelling methodology with explicitly modified point kinetics equation and Mann’s model for heat transfer. Six parameters that can impact MSR safety are evaluated. A MATLAB-Simulink model inspired by Thorcon’s 550MW th MSR is used for parameter evaluations. A safety envelope was formed to encapsulate power, maximum and minimum temperature, and temperature-induced reactivity feedback. The parameters are perturbed by ±30%. The parameters were then ranked by their subsequent impact on the considered safety envelope, which ranks acceptable parameter uncertainty. The model is openly available on GitHub.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2025

Steam generator model design parameter sensitivity study for small modular reactor system

Here, this study focuses on design parameter sensitivity studies pertaining to several Once-Through Steam Generator (OTSG) model cases both with and without a riser using python and advanced risk assessment and optimization tool, i.e. Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), to support a Small Modular Reactor (SMR) system. The presented Steam Generator (SG) python-based model is a mathematical representation of a steam-generating unit for a Pressurized Water Reactor (PWR)-type SMR system, including fluid flow and heat transfer equations, models, and correlations. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system, such as the Heat Transfer Coefficient (HTC), Reynolds number, Nusselt number, and heat transfer performance. Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in the input parameters. By using RAVEN, detailed design parametric sensitivity studies. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (i.e., ±1%, ±5% and ±10 % relative changes) for 600 samples. The analysis results give valuable insights into SG system performance, and provide justification for further research and development such as optimized sensor placement, design verification, validation, and optimization.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2024

Steam Generator Model Design Parameter Sensitivity Study Using Advanced Optimization Tools

This study focuses on design parameter sensitivity studies pertaining to a steam generator (SG) model, using both Python and machine-learning tools. The SG model is a mathematical representation (including fluid flow and heat transfer equations/models/correlations) of a steam-generating unit in a pressurized water reactor (PWR)-type small modular reactor (SMR) system. Design studies involve changing the model’s input design parameters (e.g., temperature, pressure, mass flow rate) to observe the resulting effects on the output of the system (e.g., heat transfer coefficient [HTC], Nusselt number, heat transfer performance). Sensitivity studies analyze the degree to which system output and/or desired parameters (e.g., HTC or heat transfer performance) are sensitive to changes in input parameters. By using machine-learning tools such as the Risk Analysis Virtual Environment (RAVEN) developed at Idaho National Laboratory (INL), detailed design parametric sensitivity studies and model optimization were performed. Six input parameters—namely, the pressure, temperature, and mass flow rate for the inlet of the primary-side (hot fluid) and secondary-side (cold fluid) of the SG—were randomly perturbed via RAVEN’s Monte Carlo Sampler module, using uniform distributions (±1% relative changes). The analysis results give valuable insights into SG system performance and optimization, and provide justification for researching optimized sensor placement to effectively monitor and obtain experimental data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2026

Control Parameter Sensitivity Study for Inverter-Based-Resource Dominated Grids: A Small Signal Stability Approach and Framework

The growing adoption of renewable energy is driving the prevalence of inverter-based resources (IBRs) within power grids. Future power grids will integrate both grid-following IBRs (GFM-IBRs) and grid-forming IBRs (GFL-IBRs) alongside synchronous generators. Therefore, it is crucial to perform stability studies that account for all components and especially control interactions related to IBRs. Extensive research has performed to study the IBR-related stability, however, the sensitivity study of IBRs' control parameters on system stability has not been adequately studied yet, especially from a systematic way. Therefore, this paper conducts a small signal stability analysis for a generic grid with multiple types of resources and develops an analytical framework for assessing the sensitivity of control parameters affecting stability margins. To achieve that, the non-autonomous reduced-order non-linear dynamic model is developed for a generic power system with multiple synchronous generator-based resources (SGBRs), GFM-IBRs, and GFL-IBRs. Based on the analytic model, a systematic framework for parametric sensitivity on systems' asymptotic stability is developed. A parameter sensitivity analysis based on eigenvalue methods is proposed. The impact of the droop controllers of GFM-IBRs, PQ-dispatch and the PLL controller of GFL-IBR on the system asymptotic stability is discussed. This sensitivity study is aiming to provide deep insights on control parameters' impact on system stability, and gives direction for parameter tuning in case of instability.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

304L Can Crush Validation Studies

Accurate prediction of ductile behavior of structural alloys up to and including failure is essential in component or system failure assessment, which is necessary for nuclear weapons alteration and life extensions programs of Sandia National Laboratories. Modeling such behavior requires computational capabilities to robustly capture strong nonlinearities (geometric and material), rate- dependent and temperature-dependent properties, and ductile failure mechanisms. This study's objective is to validate numerical simulations of a high-deformation crush of a stainless steel can. The process consists of identifying a suitable can geometry and loading conditions, conducting the laboratory testing, developing a high-quality Sierra/SM simulation, and then drawing comparisons between model and measurement to assess the fitness of the simulation in regards to material model (plasticity), finite element model construction, and failure model. Following previous material model calibration, a J 2 plasticity model with a microstructural BCJ failure model is employed to model the test specimen made of 304L stainless steel. Simulated results are verified and validated through mesh and mass-scaling convergence studies, parameter sensitivity studies, and a comparison to experimental data. The converged mesh and degree of mass-scaling are the mesh discretization with 140,372 elements, and a mass scaling with a target time increment of 1.0e-6 seconds and time step scale factor of 0.5, respectively. Results from the coupled thermal-mechanical explicit dynamic analysis are comparable to the experimental data. Simulated global force vs displacement (F/D) response predicts key points such as yield, ultimate, and kinks of the experimental F/D response. Furthermore, the final deformed shape of the can and field data predicted from the analysis are similar to that of the deformed can, as measured by 3D optical CMM scans and DIC data from the experiment.

36 MATERIALS SCIENCE↗