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NASA NTRS1977

Internal structure and properties of Mars

Theoretical physical models of the Martian interior are presented in the light of recent and revised data and constraints. These models include thermal evolution, densities, and seismic-wave velocities. The interior of Mars appears to be earthlike in many respects. Although thermal models indicate that Mars has passed its peak of evolution, it may still have an asthenosphere and may be moderately active tectonically. Mars has an Fe-FeS core with a radius of 1500-2000 km. The mantle is enriched in FeO with an olivine composition of about Fo75. Theoretically determined seismic-wave velocities are relatively well constrained in the mantle, with upper-mantle P-wave velocities ranging from 7.64 to 7.80 km/sec. However, there are wide variations in P-wave velocity in the core, dependent on composition. The shadow zone due to the core is larger than earth's.

Johnston, D. H.↗

NASA NTRS2012

Macro Scale Independently Homogenized Subcells for Modeling Braided Composites

An analytical method has been developed to analyze the impact response of triaxially braided carbon fiber composites, including the penetration velocity and impact damage patterns. In the analytical model, the triaxial braid architecture is simulated by using four parallel shell elements, each of which is modeled as a laminated composite. Currently, each shell element is considered to be a smeared homogeneous material. The commercial transient dynamic finite element code LS-DYNA is used to conduct the simulations, and a continuum damage mechanics model internal to LS-DYNA is used as the material constitutive model. To determine the stiffness and strength properties required for the constitutive model, a top-down approach for determining the strength properties is merged with a bottom-up approach for determining the stiffness properties. The top-down portion uses global strengths obtained from macro-scale coupon level testing to characterize the material strengths for each subcell. The bottom-up portion uses micro-scale fiber and matrix stiffness properties to characterize the material stiffness for each subcell. Simulations of quasi-static coupon level tests for several representative composites are conducted along with impact simulations.

Blinzler, Brina J.↗

NASA NTRS1993

Numerical modeling of ooid size and the problem of Neoproterozoic giant ooids

Temporal variation in ooid size reflects important changes in physical and chemical characteristics of depositional environments. Two numerical models are used to evaluate the effects of several processes influencing ooid size. The first demonstrates that low supply of new ooid nuclei and high cortex growth rate each promote growth of large ooids. The second model demonstrates that high average water velocity and velocity gradient also enhance ooid growth. Several Neoproterozoic oolites contain unusually large ooids, some reaching diameters of up to 16 mm. While lower nuclei supply and higher ooid growth rate may have prevailed prior to the evolution of carbonate-secreting organisms, neither difference can explain the presence of giant ooids in Neoproterozoic deposits because Archean through Mesoproterozoic ooids rarely exceed 5 mm in diameter. In the presence of lower nuclei supply and higher growth rate, high average water velocity may have allowed growth of such large ooids. Higher average water velocity could have been due to a prevalence of carbonate ramps over rimmed shelves during Neoproterozoic time.

NASA Discipline Exobiology↗

NASA NTRS1989

Non-WKB evolution of solar wind fluctuations - A turbulence modeling approach

Recent observations indicate systematic changes in the interplanetary inertial range velocity-magnetic field correlation with increasing heliocentric distance. Here, a multiple length scale model for the evolution of the small scale fluctuations due to local nonlinear couplings as well as couplings to large scale gradients is outlined, which is similar to that used in turbulence modeling of inhomogeneous shear flows. A simple special case solution is given, indicating that couplings to large scale flow gradients can cause radial evolution of the type seen in observations. The strongest couplings of this type are linear and do not appear in the usual WKB orderings. The relationship of the present approach to WKB theory is not fully understood at present.

Ye, Zou↗

NASA NTRS2015

Simple Scaling of Multi-Stream Jet Plumes for Aeroacoustic Modeling

When creating simplified, semi-empirical models for the noise of simple single-stream jets near surfaces it has proven useful to be able to generalize the geometry of the jet plume. Having a model that collapses the mean and turbulent velocity fields for a range of flows allows the problem to become one of relating the normalized jet field and the surface. However, most jet flows of practical interest involve jets of two or more co-annular flows for which standard models for the plume geometry do not exist. The present paper describes one attempt to relate the mean and turbulent velocity fields of multi-stream jets to that of an equivalent single-stream jet. The normalization of single-stream jets is briefly reviewed, from the functional form of the flow model to the results of the modeling. Next, PIV (Particle Image Velocimetry) data from a number of multi-stream jets is analyzed in a similar fashion. The results of several single-stream approximations of the multi-stream jet plume are demonstrated, with a 'best' approximation determined and the shortcomings of the model highlighted.

Jet Noise↗

DOE OSTI2026

Introduction to and comparison of deep learning and optimization approaches to analytical wake modeling of a tilted wind turbine

This paper introduces innovative optimization and deep learning techniques to enhance the prediction of complex wake dynamics in the downstream wind velocity of tilted wind turbines. Traditional methods for calibrating the Bastankhah wake model often lead to increased errors in wind velocity distribution due to overfitting of the local wake characteristics. To address this issue, we propose an additional global optimization step to reduce errors in wind velocity predictions with respect to various wake parameters. Despite this improvement, the Bastankhah model's axisymmetric Gaussian wake shape limits its accuracy for complex wake structures. Therefore, we also propose a deep learning approach, which demonstrates promising results by accurately modeling complex wake shapes across a broader range of tilt angles with minimal computational cost. The deep learning approach achieves near-identical predictions to high-fidelity large-eddy simulations, representing a promising advancement in wake modeling.

17 WIND ENERGY↗

NASA NTRS1980

A thermalized ion explosion model for high energy sputtering and track registration

A velocity spectrum of neutral sputtered particles as well as a low resolution mass spectrum of sputtered molecular ions was measured for 4.74 MeV F-19(+2) incident of UF4. The velocity spectrum is dramatically different from spectra taken with low energy (keV) bombarding ions, and is shown to be consistent with a hot plasma of atoms in thermal equilibrium inside the target. A thermalized ion explosion model is proposed for high energy sputtering which is expected to describe track formation in dielectric materials. The model is shown to be consistent with the observed total sputtering yield and the dependence of the yield on the primary ionization rate of the incident ion.

Seiberling, L. E.↗

NASA NTRS1991

Analysis of aircraft engine blade subject to ice impact

The ice impact on the engine blade made of layered composite is simulated. The ice piece is modeled as an equivalent spherical object and has the velocity opposite to that of the aircraft with direction parallel to the engine axis. Near the impact region and along the leading edge, the blade is assumed to be fully stressed and undergoes large deflection. A specified portion of the blade around the impact region is modeled. The effect of ice size and velocity on the average leading edge strain are investigated for a modified SR-2 model unswept composite propfan blade. Parametric studies are performed to study the response due to ice impact at various locations along the span. Also, the effects of engine speed on the strain and impact displacements are discussed. It is found that for a given engine speed, a critical ice speed exists that corresponds to the maximum strain and this critical speed increases with increase in the engine speed.

Reddy, E. S.↗

NASA NTRS1992

Analysis of aircraft engine blade subject to ice impact

The ice impact problem on an engine blade made of layered composite is simulated. The ice piece is modeled as an equivalent spherical object and has the velocity opposite to that of the aircraft with direction parallel to the engine axis. Near the impact region and along the leading edge, the blade is assumed to be fully stressed and undergoes large deflection. A specified portion of the blade around the impact region is modeled. The effect of ice size and velocity on the average leading edge strain are investigated for a modified SR-2 model unswept composite propfan blade. Parametric studies are performed to study the response due to ice impact at various locations along the span. Also, the effects of engine speed on the strain and impact displacements are discussed. It is found that for a given engine speed, a critical ice speed exists that corresponds to the maximum strain and this critical speed increases with increase in the engine speed.

Reddy, E. S.↗

DOE OSTI2019

Joint Bayesian Inference for Near-surface Explosion Yield

Geophysical observations of an explosion scale with the yield of the explosion. Guided by the principal of yield-scaling and observed relationships in the data, we defined and parameterized seismoacoustic forward models in Ford et al. [2014]. This work extends the model with additional data features of maximum velocity and positive phase duration for the seismic and acoustic data types, respectively, and a new optic data type. Parameters for the seismoacoustic models are estimated via Bayesian inference. The parameterized models can then be used to infer the yield of a new explosion.

58 GEOSCIENCES↗

NASA NTRS1994

Evaluation of turbulence models in the PARC code for transonic diffuser flows

Flows through a transonic diffuser were investigated with the PARC code using five turbulence models to determine the effects of turbulence model selection on flow prediction. Three of the turbulence models were algebraic models: Thomas (the standard algebraic turbulence model in PARC), Baldwin-Lomax, and Modified Mixing Length-Thomas (MMLT). The other two models were the low Reynolds number k-epsilon models of Chien and Speziale. Three diffuser flows, referred to as the no-shock, weak-shock, and strong-shock cases, were calculated with each model to conduct the evaluation. Pressure distributions, velocity profiles, locations of shocks, and maximum Mach numbers in the duct were the flow quantities compared. Overall, the Chien k-epsilon model was the most accurate of the five models when considering results obtained for all three cases. However, the MMLT model provided solutions as accurate as the Chien model for the no-shock and the weak-shock cases, at a substantially lower computational cost (measured in CPU time required to obtain converged solutions). The strong shock flow, which included a region of shock-induced flow separation, was only predicted well by the two k-epsilon models.

Georgiadis, N. J.↗

NASA NTRSDate not supplied

Mass Inferencing Model Creation and Deployment to the RASSOR Lunar Excavation Robot

The Regolith Advanced Surface Systems Operations Robot (RASSOR) Excavator is a teleoperated mobile robotic platform with a unique space regolith excavation capability. The Intelligent Capabilities Enhanced RASSOR research project developed functionality for inferencing regolith mass ingested during RASSOR operation, enhancing RASSOR’s ability to successfully complete ISRU missions. To teleoperate or run autonomously, it is crucial for the quantity of regolith mass ingested by RASSOR to be available as a system state for efficient operation. For example, during autonomous operation, RASSOR should navigate and move to a processing plant to offload the collected regolith when the drums are full; without knowledge of how much mass is in the drums, this type of high-level planning is not possible. Four distinct modeling approaches were employed in developing a mass inferencing approach that could work on RASSOR. All take in system states, such as arm/drum positions, velocities, currents, voltages, and robot pose, and output a mass prediction for each set of the robot’s bucket drums.1) A neural network model that takes a vector of normalized system states; 2) A model that uses the integrated power consumption of an arm-raise (normalized by velocity); 3) A model that uses average drum current over a variable length interval of the drum disengaged from the surface; and 4) A real-time estimation model that aggregates excavation drum current. The developed models run in real time, outputting predictions for the front and rear drums, timestamp of the last prediction, and total mass in RASSOR’s drums. Further testing is required to validate the arm-raise model (2), though initial tests indicate reasonable performance (<10% mean error) on the hardware. The linear fit of average drum-current model (3) had a front value of r^2=0.99 and a rear value of r^2=0.98 on the validation dataset. This model currently has the best performance on unseen data. The real time model (4) is still in development, though initial results on a small subset of the training data show that it has high accuracy in predicting the increase in mass during excavation. Though work remains to be done with deploying a high-fidelity model to the physical system that makes predictions with error below the desired threshold, the modular architecture for model development allows quick adjustment of parameters to increase model fidelity. This architecture can also be adapted to use lunar excavation data to create models that are reflective of RASSOR’s dynamics when operating on the lunar surface. The results are promising as it has been shown that models can be developed that accurately estimate excavated regolith mass.

rassor↗

NASA NTRS1986

Particle propagation, wave growth and energy dissipation in a flaring flux tube

Wave amplification by downgoing particles in a common flare model is investigated. The flare is assumed to occur at the top of a coronal magnetic flux loop, and results in the heating of plasma in the flaring region. The hot electrons propagate down the legs of the flux tube towards increasing magnetic field. It is simple to demonstrate that the velocity distributions which result in this model are unstable to both beam instabilities and cyclotron maser action. An explanation is presented for the propagation effects on the distribution, and the properties of the resulting amplified waves are explored, concentrating on cyclotron maser action, which has properties (emission in the z mode below the local gyrofrequency) quite different from maser action by other distributions considered in the context of solar flares. The z mode waves will be damped in the coronal plasma surrounding the flaring flux tube and lead to heating there. This process may be important in the overall energy budget of the flare. The downgoing maser is compared with the loss cone maser, which is more likely to produce observable bursts.

White, S. M.↗

NASA NTRS2018

The Magellan Evolution of Galaxies Spectroscopic and Ultraviolet Reference Atlas (MegaSaura). II. Stacked Spectra

We stack the rest-frame ultraviolet spectra of N = 14 highly magnified gravitationally lensed galaxies at redshifts 1.6 < z < 3.6. The resulting new composite spans 900 < lambda rest < 3000 Angstrom, with a peak signal-to-noise ratio of 103 per spectral resolution element (approximately 100 km s (exp -1)). It is the highest signalto-noise ratio, highest spectral resolution composite spectrum of z approximately 2-3 galaxies yet published. The composite reveals numerous weak nebular emission lines and stellar photospheric absorption lines that can serve as new physical diagnostics, particularly at high redshift with the James Webb Space Telescope (JWST). We report equivalent widths to aid in proposing for and interpreting JWST spectra. We examine the velocity profiles of strong absorption features in the composite, and in a matched composite of z approximately 0 COS/HST galaxy spectra. We find remarkable similarity in the velocity profiles at z approximately 0 and z approximately 2, suggesting that similar physical processes control the outflows across cosmic time. While the maximum outflow velocity depends strongly on ionization potential, the absorptionweighted mean velocity does not. As such, the bulk of the high-ionization absorption traces the low-ionization gas, with an additional blueshifted absorption tail extending to at least approximately 2000 km s (exp -1). We interpret this tail as arising from the stellar wind and photospheres of massive stars. Starburst99 models are able to replicate this high-velocity absorption tail. However, these theoretical models poorly reproduce several of the photospheric absorption features, indicating that improvements are needed to match observational constraints on the massive stellar content of star-forming galaxies at z approximately 2. We publicly release our composite spectra.

Rigby, J. R.↗

DOE OSTI2024

Assessment of Machine Learning Wall Modeling Approaches for Large Eddy Simulation of Gas Turbine Film Cooling Flows: An a Priori Study

Here, in this work, a priori analysis of machine learning (ML) strategies is carried out with the goal of data-driven wall modeling for large eddy simulation (LES) of gas turbine film cooling flows. High-fidelity flow datasets are extracted from wall-resolved LES (WRLES) of flow over a flat plate interacting with the coolant flow supplied by a single row of 7-7-7 shaped cooling holes inclined at 30 degrees with the flat plate at different blowing ratios (BR). The WRLES are performed using the high-order Nek5000 spectral element computational fluid dynamics (CFD) solver. Light gradient boosting machine (LightGBM) is employed as the ML algorithm for the data-driven wall model. Parametric tests are conducted to systematically assess the influence of a wide range of input flow features (velocity components, velocity gradients, pressure gradients, and fluid properties) on the accuracy of ML wall model with respect to prediction of wall shear stress. In addition, the use of spatial stencil and time delay is also explored within the ML wall modeling framework. It is shown that features associated with gradients of the streamwise and spanwise velocity components have a major impact on the prediction fidelity of wall model, while the effect of gradients of wall-normal velocity component is found to be negligible. Moreover, adding flow feature information from an x-y-z spatial stencil significantly improves the ML model accuracy and generalizability compared to just using local flow features from the matching location. Overall, highest prediction accuracy is achieved when both spatial stencil and time delay features are incorporated within the data-driven wall modeling paradigm.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS2005

Navier-Stokes Computations With One-Equation Turbulence Model for Flows Along Concave Wall Surfaces

This report presents the use of a time-marching three-dimensional compressible Navier-Stokes equation numerical solver with a one-equation turbulence model to simulate the flow fields developed along concave wall surfaces without and with a downstream extension flat wall surface. The 3-D Navier- Stokes numerical solver came from the NASA Glenn-HT code. The one-equation turbulence model was derived from the Spalart and Allmaras model. The computational approach was first calibrated with the computations of the velocity and Reynolds shear stress profiles of a steady flat plate boundary layer flow. The computational approach was then used to simulate developing boundary layer flows along concave wall surfaces without and with a downstream extension wall. The author investigated the computational results of surface friction factors, near surface velocity components, near wall temperatures, and a turbulent shear stress component in terms of turbulence modeling, computational mesh configurations, inlet turbulence level, and time iteration step. The computational results were compared with existing measurements of skin friction factors, velocity components, and shear stresses of the developing boundary layer flows. With a fine computational mesh and a one-equation model, the computational approach could predict accurately the skin friction factors, near surface velocity and temperature, and shear stress within the flows. The computed velocity components and shear stresses also showed the vortices effect on the velocity variations over a concave wall. The computed eddy viscosities at the near wall locations were also compared with the results from a two equation turbulence modeling technique. The inlet turbulence length scale was found to have little effect on the eddy viscosities at locations near the concave wall surface. The eddy viscosities, from the one-equation and two-equation modeling, were comparable at most stream-wise stations. The present one-equation turbulence model is an effective approach for turbulence modeling in the near solid wall surface region of flow over a concave wall.

Wang, Chi R.↗

DOE OSTI2024

A Green's Function Wind Turbine Induction Model That Incorporates Complex Inflow Conditions

ABSTRACT In this work, we develop a new analytical turbine induction model that can incorporate complex inflow conditions including cases where the wind velocity and temperature profiles can vary as functions of height. This induction model is derived from the linearized Navier–Stokes and leads to a second‐order ODE that can be solved using a Green's function formulation. The corresponding Green's function for several configurations are found including the infinite domain, semi‐infinite domain with ground plane, and a power law velocity inflow profile. The results of this approach are then compared with simulations of the turbine induction field using the AMR‐Wind CFD solver with a uniformly loaded actuator disk model. These comparisons show that the Green's function approach captures the centerline blockage, three‐dimensional blockage flow field, and streamwise velocity slow down, with very good agreement for lower thrust conditions and at larger distances away from rotor disk. The effects of shear on the turbine blockage were also compared using a power law inflow profile, and we show that this approach matches the CFD predictions for the cases considered.

17 WIND ENERGY↗

NASA NTRS2009

Basic Diagnosis and Prediction of Persistent Contrail Occurrence using High-resolution Numerical Weather Analyses/Forecasts and Logistic Regression. Part I: Effects of Random Error

Straightforward application of the Schmidt-Appleman contrail formation criteria to diagnose persistent contrail occurrence from numerical weather prediction data is hindered by significant bias errors in the upper tropospheric humidity. Logistic models of contrail occurrence have been proposed to overcome this problem, but basic questions remain about how random measurement error may affect their accuracy. A set of 5000 synthetic contrail observations is created to study the effects of random error in these probabilistic models. The simulated observations are based on distributions of temperature, humidity, and vertical velocity derived from Advanced Regional Prediction System (ARPS) weather analyses. The logistic models created from the simulated observations were evaluated using two common statistical measures of model accuracy, the percent correct (PC) and the Hanssen-Kuipers discriminant (HKD). To convert the probabilistic results of the logistic models into a dichotomous yes/no choice suitable for the statistical measures, two critical probability thresholds are considered. The HKD scores are higher when the climatological frequency of contrail occurrence is used as the critical threshold, while the PC scores are higher when the critical probability threshold is 0.5. For both thresholds, typical random errors in temperature, relative humidity, and vertical velocity are found to be small enough to allow for accurate logistic models of contrail occurrence. The accuracy of the models developed from synthetic data is over 85 percent for both the prediction of contrail occurrence and non-occurrence, although in practice, larger errors would be anticipated.

Duda, David P.↗