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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS1986

A two-fluid solar wind model with Alfven waves - Parameter study and application to observations

The effects of Alfven waves from the inner corona on the solar wind density profile, flow velocity and on the random motion of protons are studied. Different base densities, temperatures, and wave velocity amplitudes, as well as different flow geometries, are considered. The model calculations are compared to simultaneous observations of the electron density profile and the resonantly scattered Lyman alpha line. Present observations, out to 4 solar radii, can be used to place limits on the coronal base density and temperature, and put an upper limit on the wave amplitude. It is pointed out that future observations of the electron density and the Lyman alpha line, out to larger heliocentric distances, and of lines from heavier elements, should be used to place more stringent constraints on the amplitudes of MHD waves in the corona.

Esser, R.↗
NASA NTRS1987

On dynamic loads in parallel shaft transmissions. 2: Parameter study

Solutions to the governing equations of a spur gear transmission model, developed in NASA TM-100180 (AVSCOM TM-87-C-2), are presented. Factors affecting the dynamic load are identified. It is found that the dynamic load increases with operating speed up to a system natural frequency. At operating speeds beyond the natural frequency the dynamic load decreases dramatically. Also. it is found that the applied load and shaft inertia have little effect on the dynamic load. Damping and friction decrease the dynamic load. Finally, tooth stiffness has a significant effect on dynamic loading; the higher the stiffness, the lower the dynamic loading. Also, the higher the stiffness the higher the rotating speed required for dynamic response.

Lin, Edward Hsiang-Hsi↗
NASA NTRS1991

Aerodynamic parameter studies and sensitivity analysis for rotor blades in axial flight

The analytical capability is offered for aerodynamic parametric studies and sensitivity analyses of rotary wings in axial flight by using a 3-D undistorted wake model in curved lifting line theory. The governing equations are solved by both the Multhopp Interpolation technique and the Vortex Lattice method. The singularity from the bound vortices is eliminated through the Hadamard's finite part concept. Good numerical agreement between both analytical methods and finite differences methods are found. Parametric studies were made to assess the effects of several shape variables on aerodynamic loads. It is found, e.g., that a rotor blade with out-of-plane and inplane curvature can theoretically increase lift in the inboard and outboard regions respectively without introducing an additional induced drag.

Chiu, Y. Danny↗
NASA NTRS1992

Time-series photometric spot modeling. I - Parameter study and application to HD 17433 = VY Arietis

New UBVRI photometry of the active chromosphere binary HD 17433 (VY) Ari from 1987 through 1991 is presented, and the long-term and short-term spot behavior is studied. A 0.2 mag variation of the mean brightness and a maximum wave amplitude of up to 0.4 mag in 1988 are found. The newly measured photometric period of 16.42 d suggests asynchronous rotation of the primary component by about 30 percent.

Strassmeier, K. G.↗
NASA NTRS2004

Automated Parameter Studies Using a Cartesian Method

Computational Fluid Dynamics (CFD) is now routinely used to analyze isolated points in a design space by performing steady-state computations at fixed flight conditions (Mach number, angle of attack, sideslip), for a fixed geometric configuration of interest. This "point analysis" provides detailed information about the flowfield, which aides an engineer in understanding, or correcting, a design. A point analysis is typically performed using high fidelity methods at a handful of critical design points, e.g. a cruise or landing configuration, or a sample of points along a flight trajectory.

Murman, Scott M.↗
NASA NTRS2005

Parameter Studies, time-dependent simulations and design with automated Cartesian methods

Over the past decade, NASA has made a substantial investment in developing adaptive Cartesian grid methods for aerodynamic simulation. Cartesian-based methods played a key role in both the Space Shuttle Accident Investigation and in NASA's return to flight activities. The talk will provide an overview of recent technological developments focusing on the generation of large-scale aerodynamic databases, automated CAD-based design, and time-dependent simulations with of bodies in relative motion. Automation, scalability and robustness underly all of these applications and research in each of these topics will be presented.

Aftosmis, Michael↗
DOE OSTI2019

A Parameter Study for Improving the Performance of the Production Target for the Muon G-2 Experiment

The target station of the Muon g-2 Experiment is one of the central pieces for the production of secondary pions which eventually will decay to the desired muons. In this paper, we report adjustments made to optimize its perfor-mance. For instance, in the simulation we vary the size of the primary incoming beam and examine its impact on the downstream production. We then compare this with the ac-tual measured beam size upstream of the target. In addition, we examine the sensitivity in performance with the strength of the lithium lens and the distance between lens and target. We compare measured data with simulation results.

43 PARTICLE ACCELERATORS↗
NASA NTRS1972

Tropospheric range error parameters: Further studies

Improved parameters are presented for predicting the tropospheric effect on electromagnetic range measurements from surface meteorological data. Parameters are given for computing the dry component of the zenith radio range effect from surface pressure alone with an rms error of 1 to 2 mm, or the total range effect from the dry and wet components of the surface refractivity, N, and a two-part quartic profile model. The parameters were obtained from meteorological balloon data with improved procedures, including the conversion of the geopotential heights of the balloon data to actual or geometric heights before using the data. The revised values of the parameter k show more latitude variation than is accounted for by the variation of g. This excess variation of k indicates a small latitude variation in the mean molecular weight of air and yields information about the latitude-varying water vapor content of air.

Hopfield, H. S.↗
NASA NTRS1972

Tropospheric range error parameters: Further studies

Improved parameters are presented for predicting the tropospheric effect on electromagnetic range measurements from surface meteorological data. More geographic locations have been added to the earlier list. Parameters are given for computing the dry component of the zenith radio range effect from surface pressure alone with an rms error of 1 to 2 mm, or the total range effect from the dry and wet components of the surface refractivity and a two-part quartic profile model. The new parameters are obtained, as before, from meteorological balloon data but with improved procedures, including the conversion of the geopotential heights of the balloon data to actual or geometric heights before using the data. The revised values of the parameter k (dry component of vertical radio range effect per unit pressure at the surface) show more latitude variation than is accounted for by the variation of g, the acceleration of gravity.

Hopfield, H. S.↗
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↗