SEARCH · Search NASA
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Predictive simulations of heat and particle fluxes in the plasma boundary are a critical missing capability for magnetic fusion energy power plant design.
Optimization of critical supply chains to deliver thousands of parts, materials, sub-assemblies, and vehicle structures as needed is vital to the success of the Constellation Program. Thorough analysis needs to be performed on the integrated supply chain processes to plan, source, make, deliver, and return critical items efficiently. Process modeling provides simulation technology-based, predictive solutions for supply chain problems which enable decision makers to reduce costs, accelerate cycle time and improve business performance. For example, United Space Alliance, LLC utilized this approach in late 2006 to build simulation models that recreated shuttle orbiter thruster failures and predicted the potential impact of thruster removals on logistics spare assets. The main objective was the early identification of possible problems in providing thruster spares for the remainder of the Shuttle Flight Manifest. After extensive analysis the model results were used to quantify potential problems and led to improvement actions in the supply chain. Similarly the proper modeling and analysis of Constellation parts, materials, operations, and information flows will help ensure the efficiency of the critical logistics supply chains and the overall success of the program.
The SMall Aspect Ratio Tokamak (SMART) is currently being commissioned at the University of Seville and will be able to compare the performance of positive and negative triangularity plasmas at low aspect ratio. Predictive simulations have been performed for different machine scenarios and heating schemes using the TRANSP code. The objectives of these simulations are to predict the parameters expected in positive triangularity plasmas, to guide diagnostic development, and to validate transport models. Several reduced turbulence models have been used to predict electron and ion temperatures for the operational phase 2. All models provide similar results from approximately mid-radius to the separatrix but important discrepancies are found in the core region. These positive triangularity results are compared with experiments from a similar size machine like GLOBUS-M2. The multi-mode model (MMM) shows the best agreement. Simulations with different boundary conditions have been performed and no strong differences have been observed between them. The impact of neutral beam injection (NBI) on the predicted profiles has also been addressed. Rotation reduces turbulence levels so higher temperatures are achieved when included in the simulations. Studying the different contributions to the thermal diffusivities, it is observed that electron temperature gradient (ETG) turbulence dominates at the plasma core while micro-tearing modes (MTM) dominate at the edge in the electron channel. In the ion channel, the neoclassical contribution is dominant at the core and at the very edge while the Weiland component, which includes ion temperature gradient mode (ITG), trapped electron mode (TEM), kinetic ballooning mode (KBM), peeling mode (PM) and collisionless and collision dominated magnetohydrodynamic (MHD) modes governs the mid-radius region. For phase 3, two plasmas with different electron densities have been studied. The case with lower density matches well a specific discharge of GLOBUS-M2. The higher density plasma shows high performance with β N ≈ 3.8.
The filtering approach (Leonard, 1974) to large eddy simulation is described. Large eddy simulation is then surveyed with reference to subgrid scale models, numerical methods, channel flow, and free shear flows. It is concluded that the premise of LES (i.e., that the small eddies are much easier to model than the large ones) seems to be borne out by computational experience to date. The greatest obstacle in LES at present is the lack of computer power which effectively denies the ability to simulate all the significant eddies in flows of interest.
The Geostationary Operational Environmental Satellite-R program (GOES-R) has launched two of the next generation geostationary weather satellites, both of which are now fully operational. GOES-16 launched in November 2016, and GOES-17 launched in March 2017. In this paper, we present the pointing and pointing stability results of the two spacecraft, with specific focus on aspects of the design related to mitigating jitter. The flight instrument suite includes 6 seismic accelerometers sampled at approximately 2 kilohertz, allowing in-flight verification of pointing stability and comparison back to simulation predictions. This paper compares the observed flight results with the simulation predictions for acceleration and shock response spectrum (SRS) for various operational scenarios and instrument observation modes. Passive isolation of both the reaction wheels and the payload deck have proved to be effective in reducing jitter responses. Active Vibration Damping (AVD) of flexible-body modes attenuates the low frequency motion of the vehicle appendages, improving the low-frequency pointing performance. Knowledge of the instrument scan mirror motion is fed forward to the reaction wheel control, reducing disturbances on the spacecraft bus. Attitude knowledge and rate data are provided to the primary Earth-observing instrument with an accuracy defined by the Integrated Rate Error (IRE) requirements. The data are used to adjust instrument scanning. As we show in this paper, the in-flight performance of the GN&C (Guidance, Navigation and Control) design provides the necessary capabilities to achieve the demanding GOES-R mission objectives while its robustness enabled the simultaneous operation of the Advanced Baseline Imager (ABI) prime and redundant cryocoolers (CCs) to resolve an in-flight cooling anomaly on GOES-17.
To test the ability of WEST-1 to predict blade fatigue load distribution, actual wind signals were fed into the simulator and the response data were recorded and processed in the same manner as actual wind turbine data. The WEST-1 simulator was operated in a stable, unattended mode for six hours. The probability distribution of the cyclic flatwise bending moment for the blade was comparable to that for an actual wind turbine in winds with low turbulence. The input from a stationary anemometer was found to be inadequate for use in the prediction of fatigue load distribution for blade design purposes and modifications are necessary.
Abstract We model the interstellar dust content of the reionization era with a suite of cosmological, fluid-dynamical simulations of galaxies with stellar masses ranging from ∼10 5 to 10 9 M ⊙ in the first 1.2 Gyr of the Universe. We use a post-processing method that accounts for dust creation and destruction processes, allowing us to systematically vary the parameters of these processes to test whether dust-dependent observable quantities of galaxies at these epochs could be useful for placing constraints on dust physics. We then forward model observable properties of these galaxies to compare to existing data. We find that we are unable to simultaneously match existing observational constraints with any one set of model parameters. Specifically, the models that predict the largest dust masses D / Z ≳ 0.1 at z = 5—because of high assumed production yields and/or efficient growth via accretion in the interstellar medium—are preferred by constraints on total dust mass and infrared (IR) luminosities, but these models produce far too much attenuation in the ultraviolet (UV), preventing them from matching observations of β UV . To investigate this discrepancy, we analyze the relative spatial distribution of stars and dust as probed by IR and UV emission, which appear to exhibit overly symmetric morphologies compared to existing data, likely due to the limitations of the stellar feedback model used in the simulations. Our results indicate that the observable properties of the dust distribution in high redshift galaxies are a particularly strong test of stellar feedback.
A study to establish the validity of five predictive models of workload in the context of a controlled helicopter mission, TASKILLAN, is presented. Ten subjects performed simulations involving combinations of a low level flight task with three cognitive side tasks pertaining to navigation, spatial awareness, and computation. It is found that the best predictors of subjective workload are relativly simple models that integrate the total demands of task over time.
As part of the Game Changing Development (GCD) Program, funded by NASA’s Space Technology Mission Directorate (STMD), the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The GCD PSI Project, planned to be accomplished over a four year period, contains a Predictive Simulation Capability (PSC) Element focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~650 Pa) and Lunar (vacuum) ambient environments. In addition to the PSC Element, the PSI Project also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper describes the activities and accomplishments in the past year for the Prediction of Plume Flow in low pressure environments component of the PSI Project. While the Loci/Chem Computational fluid dynamics (CFD) application has been validated and used extensively for simulating launch environments in atmospheric conditions, use of this tool for simulating supersonic plumes at Mars-like ambient pressure requires further validation. CFD simulations of underexpanded jets have been performed using Loci/Chem for Mars-like conditions to predict several metrics for steady laminar, turbulent, and impinging plumes. The CFD results are compared with an experimental data set for low Reynolds number plumes at these conditions in order to evaluate the current capability of the Loci/Chem tool for these types of environments. The CFD validation results to date show reasonable agreement with the experimental data across all of the metrics of interest for the configurations considered. The Loci/Chem-Boltzmann CFD application is a hybrid continuum/rarefied flow solver which extends modeling capabilities to very low pressure environments such as those on the Moon. The Loci/Chem-Boltzmann solver uses a gradient-based continuum breakdown criterion to restrict solution of the computationally expensive Boltzmann equation to only a subset of the domain, while using the Navier-Stokes equations elsewhere. This CFD application is under active development, and current efforts toward establishing production ready capability for evaluating Lunar plume surface interactions are well under way. Initial simulations of an Apollo LEM indicate that several regions of the flow require solving the Boltzmann equations due to extreme rarefaction. Early simulations are promising, indicating reasonable overall computational time for a full 3D human scale lander simulation.
NASA’s Game Changing Development Program, funded by NASA’s Space Technology Mission Directorate, the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The PSI Project, planned to be completed over a four year period, contains a Predictive Simulation Capability (PSC) Element focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~600 Pa) and Lunar (vacuum) ambient environments. In addition to the PSC Element, the PSI Project also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper describes the first Pathfinder three-dimensional, transient simulation of the test configuration used to acquire erosion and cratering test data as part of the Physics Focused Ground Test conducted by the PSI Project in FY2021. This first pathfinder simulation was conducted using the Loci/GGFS (Gas Granular Flow Solver), a computational fluid dynamics tool developed in part with funding provided by the PSI Project. Crater growth and ejecta flow paths from the pathfinder simulation is compared to raw high-speed imagery PFGT results of the crater growth. There is significant similarity of test and simulation to warrant expending resources on a more rigorous quantitative Validation Assessment.
NASA’s Game Changing Development Program, funded by NASA’s Space Technology Mission Directorate, the development of simulation capability for the prediction of extra-terrestrial Plume Surface Interaction (PSI) environments has been undertaken by the Fluid Dynamics Branch at NASA/MSFC. The PSI Project, planned to be completed over a four year period, contains a Predictive Simulation Capability (PSC) Element focused on creating simulation capability for the reliable and accurate prediction of PSI in Martian (~600 Pa) and Lunar (vacuum) ambient environments. In addition to the PSC Element, the PSI Project also contains a companion Ground Testing Element for development of focused datasets for validation of predictive capability as well as a Flight-focused Instrumentation Element. This paper describes the first Pathfinder three-dimensional, transient simulation of the test configuration used to acquire erosion and cratering test data as part of the Physics Focused Ground Test conducted by the PSI Project in FY2021. This first pathfinder simulation was conducted using the Loci/GGFS (Gas Granular Flow Solver), a computational fluid dynamics tool developed in part with funding provided by the PSI Project. Crater growth and ejecta flow paths from the pathfinder simulation is compared to raw high-speed imagery PFGT results of the crater growth. There is significant similarity of test and simulation to warrant expending resources on a more rigorous quantitative Validation Assessment.
Major (regional and global)dust storms dominate weather and climate variability on present-day Mars. Absorption and scattering of visible and IR radiation by dust strongly affect the thermal state of the thin Mars atmosphere, while dust provides condensation nuclei for water and CO2 cloud particles, which also affect radiative fluxes. Global dust storms (GDS) occur ~three times per Mars decade and to date have been observed in only northern fall and winter,when the global circulation is strongest. Tenfold increases in column dust opacity are typical during GDS, with intense vertical motions transporting dust to far higher altitudes than usual. The key processes and feedbacks that produce GDS remain poorly understood, hence current atmospheric models fail to self-consistently simulate observed dust storm activity. This means we have no predictive capability for when GDS may occur, either now or in Mars’s past. And crucially, due to the huge impact of GDS on the atmosphere and surface, our lack of ability to simulate realistic dust storms has major implications for Mars science and exploration: from understanding the present climate (§2.1),to modeling past climates and water cycles (§2.2), to exploring how wind, water, and dust cycles varied over time to interpret geology and assess potential habitability(§2.3), to quantifying and mitigating risks posed to Mars missions (§2.4)
An investigation has been conducted in a 16-foot transonic tunnel to determine the effectiveness of utilizing solid circular cylinders to simulate the jet exhaust plume for a series of eight nacelle-mounted isolated circular-arc afterbodies. This investigation was conducted at Mach numbers from 0.40 to 1.30 at an angle of attack of 0. Plume simulators with simulator diameter to nozzle-exit diameter ratios of 0.82, 0.88, 0.98, and 1.00 were investigated. Results of this investigation indicate that use of one of the larger diameter simulators at all Mach numbers would generally result in pressure-coefficient distributions and drag coefficients useful for preliminary design work.
This high level presentation introduces the Sandia Z machine, dynamic materials properties experiments including the Mach Wave concept, and Alegra magnetohydrodynamic modeling for a technical audience. Alegra models are shown to be highly capable, with predictive capabilities limited only by the quality and accuracy of material models.
The development of a predictive simulation capability for extra-terrestrial Plume Surface Interaction (PSI) environments is undertaken by the Fluid Dynamics Branch at NASA/MSFC under the Game Changing Development (GCD) Program funded by NASA’s Space Technology Mission Directorate (STMD). Predictive simulation capability for propulsive Martian and Lunar landing PSI requires accurate modeling of the complex high-speed plume impingement and resulting gas/particle-cloud and ejecta stream formation. Physics modeling gap analysis during formulation of the PSI project scope identified two particular phenomena of first order importance in gas-particle interactions that lacked existing modeling formulations. The first arises from the lack of models capturing the unsteady drag forces imparted on particles by the rapidly expanding supersonic compressible flow. The second addresses the fluctuating forces and dispersions imparted on both the particle and the fluid resulting from the interference and wake turbulence generated by close proximity particle clouds, dubbed the Particle Turbulent Kinetic Energy(PTKE). Their first order significance has been identified in experiments, but simulation models currently do not exist for either effect. The development of models and the eventual implementation into the Eulerian Gas-Granular Flow Solver (GGFS) simulation tools was constructed as one of four major tasks of the PSI project. In this process, data on particle kinetics and gas-particle interactions are collected from carefully designed experiments of particles embedded in jets. The effects observed in the experiments are then replicated in high-fidelity particle-resolved CFD simulations to inform the formulation of improvements to particle phase drag models for implementations in the more efficient Eulerian-Lagrangian CFD simulations. The resulting models are ultimately ported to the Eulerian-Eulerian models applied for most efficient simulations in PSI production application tools. This paper describes the activities and accomplishments of the past year in the gas-particle interaction modeling task of the PSI project.
Friction stir processing (FSP) is a promising solid-phase microstructural modification technique that can repair and enhance damaged stainless steel surfaces exposed to harsh environments. The quality of the repaired material is closely correlated to the recrystallized grain size in the stir zone (SZ), which is influenced by the thermomechanical conditions dictated by FSP process parameters. Thus, establishing a reliable relationship between these parameters and recrystallized grain size in the SZ is crucial for optimizing repair quality. However, existing experimental approaches often rely on indirect temperatures measured far from the SZ, along with rough strain rate estimations, which are imprecise and time-consuming. Meanwhile, existing mesh-based modeling methods usually face numerical challenges when dealing with the large material deformations inherent in FSP. Here, to address these issues, this study introduces a meshfree process model for FSP based on the smoothed particle hydrodynamics (SPH) method, aimed at predicting process conditions under different parameters. The model is validated using experimental data from 11 combinations of tool traverse and rotation speeds on 316 L stainless steel. Correlations between process parameters, material flow, temperature, strain, strain rate, and recrystallized grain size are revealed through SPH simulations and electron backscatter diffraction (EBSD) imaging. The results show that in situ SZ temperatures range from 1071 to 1322°C, which exceed the tool temperature by over 300°C. Furthermore, SZ temperature, strain rate, and grain size increase monotonically with higher tool temperature and faster traverse speed. A relationship is then established between the model-predicted Zener-Hollomon parameter and the recrystallized grain size based on EBSD data, expressed as ln(d) = -0.364 ln(Z) + 14.673. Finally, this relationship exhibits satisfactory accuracy with errors of less than 26.9% in predicting grain sizes at various SZ locations, which offers valuable insights for optimizing FSP repair processes for 316 L stainless steel.
The "Dynamic Altitude Simulation Prediction Program," DASSPP, is a program to predict the transient response of an engine, test cell, ejector system under engine shutdown conditions. These transients are important to know so that corrective modifications can be adapted to prevent any damage to the engine or test cell. The "Dynamic Altitude System Simulation Prediction Program," DASSPP, is a major rewrite of the existing program "RL-1000" written in BASIC. The RL-1000 program was written to analyze the transients of the RL-10 system only. The new program is written to run in Excell 97 and utilizes the Visual BASIC language in Excell. The program has many added features not included in the original "Rl-1000" program. The program utilizes the ejector models developed during the summer of 1997. The new program is very user friendly and utilizes a dialog box for data input.
We used the CAM5 model to examine how different particle-bound polycyclic aromatic hydrocarbon (PAH) degradation approaches affect the spatial distribution of benzo(a)pyrene (BaP). Three approaches were evaluated: NOA (no effect of OA coatings state on BaP), shielded (viscous OA coatings shield BaP from oxidation under cool and dry conditions) and ROI-T (viscous OA coatings slow BaP oxidation in response to temperature and humidity). Results show that BaP concentrations vary seasonally, influenced by emissions, deposition, transport and degradation approach, all of which are influenced by meteorological conditions. All simulations predict higher population-weighted global average (PWGA) fresh BaP concentrations during December–January–February (DJF) compared to June–July–August (JJA), due to increased emissions from household activities and reduced removal processes during colder months. The shielded and ROI-T approaches, which account for OA coatings, result in 2–6 times higher BaP concentrations in DJF compared to NOA. The shielded simulation predicts the highest PWGA fresh BaP concentration (1.3 ng m −3 ), with 90 % of BaP protected from oxidation. In contrast, the ROI-T approach forecasts lower concentrations in middle to low latitudes, as it assumes less effective OA coatings under warmer, more humid conditions. Evaluations against observed BaP concentrations show the shielded approach performs best, with a normalized mean bias (NMB) within ± 20 %. The combined incremental lifetime cancer risk (ILCR) for both fresh and oxidized PAHs is similar across simulations, emphasizing the importance of considering both forms in health risk assessments. This study highlights the critical role of accurate degradation approaches in PAH modeling.