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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Effect of model selection on combustor performance and stability using ROCCID

The ROCket Combustor Interactive Design (ROCCID) methodology is an interactive computer program that combines previously developed combustion analysis models to calculate the combustion performance and stability of liquid rocket engines. Test data from a 213 kN (48,000 lbf) Liquid Oxygen (LOX)/RP-1 combustor with a O-F-O (oxidizer-fuel-oxidizer) triplet injector were used to characterize the predictive capabilities of the ROCCID analysis models for this injector/propellant configuration. Thirteen combustion performance and stability models have been incorporated into ROCCID, and ten of them, which have options for triplet injectors, were examined in this study. Calculations using different combinations of analysis models, with little or no anchoring, were carried out on a test matrix of operating conditions matching those of the test program. Results of the computer analyses were compared to test data, and the ability of the model combinations to correctly predict combustion stability or instability was determined. For the best model combination(s), sensitivity of the calculations to fuel drop size and mixing efficiency was examined. Error in the stability calculations due to uncertainty in the pressure interaction index (N) was examined. The recommended model combinations for this O-F-O triplet LOX/RP-1 configuration are proposed.

Giuliani, James E.↗
NASA NTRS1980

Midlatitude measurements of the ionospheric electric field during the ALADDIN programme

Three measurements of ionospheric electric field were made during the 24-h ALADDIN rocket program at Wallops Island on June 29-30, 1974. The first of these used a double probe instrument, flown at 1500 Local Solar Time, and the second and third measurements were made by barium cloud releases at evening and morning twilight. These three electric field vectors have been compared with the predictions of a number of models of electric field due to the dynamo effects of various atmospheric tides, and also of a possible magnetospheric origin. On the assumption that the measurements were made at a location equatorward of the afternoon convergence and poleward of the morning divergence in the electric field patterns related to the Sq current system, Stening's (1973) model of the diurnal variation of the electric field induced by the (1, -2) tidal model at the time of the summer solstice correctly predicts the directions of the observed electric field. Forbes and Lindzen's (1976, 1977) model, incorporating the three major propagating tidal modes as well as the evanescent (1, -2) mode, also bears an acceptable relationship to the ALADDIN electric field directions. The ALADDIN E-field magnitudes are comparable with those obtained by ground-based observations from Millstone Hill and from Saint Santin but are about half of Stening's model values, and three times those of Forbes and Lindzen. Saint Santin E-field directions, at the same latitude but 75 deg difference in longitude, are distinctly different from ALADDIN, implying that longitudinal differences are significant.

Rees, D.↗
NASA NTRS1980

Prediction of dominant wave properties ahead of hurricanes

A method is proposed for predicting properties of dominant waves in the forward region of hurricanes where the waves are found to propagate predominantly in the direction of hurricane forward travel. An extended fetch concept is used in which each wave component is exposed to the action of wind over a fetch length that is determined by wave group speed, hurricane forward speed, and location with respect to eye. Maximum extended fetches are found to the right of the eye (with respect to direction of hurricane travel) in the northern hemisphere. The method correctly predicts dominant wave frequencies and significant wave heights. The prediction method utilizes recently developed concepts in wave generation and energy transfer among wave spectral components; the predicted values are compared favorably with observations.

Shemdin, O. H.↗
NASA NTRS1971

Viscoseal performance for rarefied gas sealant.

Viscoseal performance as predicted by three different analytical models is compared with experimental data for a rarefied gas sealant. An experimental investigation has been conducted on two multiple grooved two-inch diameter viscoseals over a wide range of gas densities and shaft speeds up to 30,000 rpm. The two seal geometries considered differ significantly insofar as groove aspect ratio is concerned. Two types of seal performances are presented in the form of net leakage operation and sealing coefficient performance as functions of the degree of gas rarefication. Although the analytical models correctly predict sealing trends, all of the models are shown to have some deficiencies which prevent their indiscriminate application.

Milligan, M. W.↗
DOE OSTI2025

Kinematic flow for cosmological loop integrands

Recently, an interesting pattern was found in the differential equations satisfied by the Feynman integrals describing tree-level correlators of conformally coupled scalars in a power-law FRW cosmology [1, 2]. It was proven that simple and universal graphical rules predict the equations for arbitrary graphs as a flow in kinematic space. In this note, we show that the same rules — with one small addition — also determine the differential equations for loop integrands. We explain that both the basis of master integrals and the singularities of the differential equations can be represented by tubings of marked graphs. An important novelty in the case of loops is that some basis functions can vanish, and we present a graphical rule to identify these vanishing functions. Taking this into account, we then demonstrate that the kinematic flow correctly predicts the differential equations for all loop integrands.

Cosmological models↗
NASA NTRS2002

Experimental Verification of the Theoretical Prediction of the Phase Structure of a Ni-Al-Ti-Cr-Cu Alloy

The Bozzolo-Ferrante-Smith (BFS) method for alloys was applied to the study of NiAl-based materials to assess the effect of alloying additions on structure. Ternary, quaternary and even pentalloys based on NiAl with additions of Ti, Cr and Cu were studied and experimental verification of the theoretical predictions including the phase structure of a Ni-Al-Ti-Cr-Cu alloy is presented. Two approaches were used, Monte Carlo simulations to determine low energy structures, and analytical calculations of the energy of high symmetry configurations which give physical insight into preferred structures. The energetics for site occupancy in ternary and quaternary systems were calculated leading to an indirect determination of solubility limits at 0 K. Precipitate formation with information concerning structure and lattice parameter were also 'observed' computationally and the general characteristics of a Ni-Al-Ti-Cr-Cu alloy were correctly predicted. The results indicate that the BFS method for alloys can be a useful tool for alloy design and can be used to complement experimental alloy design programs.

Wilson, A.↗
NASA NTRSDate not supplied

Machine Learning Approaches for Rare-Earth Silicate Environmental Barrier Coating Thermochemical and Thermomechanical Property Predictions

Environmental barrier coatings (EBCs) are a necessary enabling technology for the transition from superalloys to silicon carbide (SiC) ceramic matrix composites (CMCs) in gas turbine engines for increased efficiency and decreased fuel costs. SiC-based CMCs are prone to oxidation-based degradation in the engine hot section, and rare-earth (RE) silicates are promising candidates for EBCs due to their close thermal expansion match to the composite substrate and oxidation resistance. However, the design of EBCs is hindered by the large chemical space of candidate materials and the difficulty in obtaining material properties for engineering optimization. This is especially difficult as research continues into mixed-cation or “high-entropy” RE silicates. First-principles computational methods such as density functional theory (DFT) are highly effective at calculating material properties to guide coating design but are limited by their computational cost. Atomistic simulations have the potential to both accelerate property calculations and expand the properties able to be calculated due to their lower computational compared to DFT. However, they require interatomic potentials (IAPs) specific to the material system of interest, and, to our knowledge, there are no suitable IAPs for RE silicates. Machine learning (ML) is a promising technique to accelerate material property predictions indirectly by generating IAPs for atomistic simulations or via direct prediction. In this work, we present two ML approaches to accelerate the calculation of RE silicate properties relevant to EBC design: 1) a ML-derived interatomic potential (IAP) for atomistic simulations of yttrium disilicate (Y2Si2O7) from DFT training data, and 2) a neural network (NN) model to directly predict thermochemical properties of RE silicates and oxides directly from easily obtainable unit cell parameters. Classical MD simulations using the IAP yield lattice properties and bond lengths in good agreement with both DFT and experimental results from x-ray diffraction. Thermodynamic properties calculated using the finite-displacement phonon method and quasi-harmonic approximation were orders of magnitude faster than DFT with good agreement to the DFT results. The IAP was also used to calculate properties such as coefficient of thermal expansion (CTE) that require large simulation supercells and are therefore difficult with DFT. The IAP correctly predicted the anisotropic nature of the CTE in three different phases of Y2Si2O7. The NN model predicts constant pressure heat capacity, Cp, orders of magnitude faster than DFT calculations, which can enable its use as a surrogate model for multiscale simulations. The two methods presented in this work demonstrate the utility of ML for accelerating the prediction of RE silicate properties, which can in turn accelerate EBC design and optimization.

machine learning↗
DOE OSTI2026

A buoyancy–shear–drag–scalar-based turbulence model for power-law acceleration-driven Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz mixing

A previously developed phenomenological turbulence model for Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz instability-induced mixing based on a general buoyancy–shear–drag model [O. Schilling, “A buoyancy–shear–drag-based turbulence model for Rayleigh–Taylor, reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz mixing,” Physica D 402, 132238 (2020)] is extended to include active or passive scalar mixing and power-law acceleration-driven Rayleigh–Taylor mixing. The buoyancy–shear–drag equations are coupled to a scalar variance equation that is used to define the molecular mixing parameter θ m , and when the scalar is active, modifies the Rayleigh–Taylor and Kelvin–Helmholtz mixing layer growth parameters to depend on the asymptotic value of this parameter, θ mol . Here, the scalar variance equation is closed by algebraically or differentially modeling the scalar variance dissipation rate. Nonlinear analytical solutions of the model are obtained in the total and separate bubble and spike mixing layer width formulations with the algebraic scalar variance dissipation rate for each instability, which are then used to calibrate the mechanical and scalar equation coefficients to predict specific values of physical observables and molecular mixing parameters. Surrogate mechanical and scalar turbulent fields can be constructed by multiplying a presumed self-similar spatial profile by appropriate functions of the width and its time derivative, and of the scalar obtained by solving the ordinary differential model equations. The explicit modeling and solution of turbulent transport equations are not required. The bubble and spike mixing layer width and scalar variance equations are then solved numerically for constant-acceleration Rayleigh–Taylor, impulsively reshocked Richtmyer–Meshkov, and Kelvin–Helmholtz mixing, confirming that the prescribed level of molecular mixing is correctly predicted and illustrating the spatiotemporal evolution of the scalar fields.

Buoyancy–drag↗
DOE OSTI2024

Accelerating cavity fault prediction using deep learning at Jefferson Laboratory

Abstract Accelerating cavities are an integral part of the continuous electron beam accelerator facility (CEBAF) at Jefferson Laboratory. When any of the over 400 cavities in CEBAF experiences a fault, it disrupts beam delivery to experimental user halls. In this study, we propose the use of a deep learning model to predict slowly developing cavity faults. By utilizing pre-fault signals, we train a long short-term memory-convolutional neural network binary classifier to distinguish between radio-frequency (RF) signals during normal operation and RF signals indicative of impending faults. We optimize the model by adjusting the fault confidence threshold and implementing a multiple consecutive window criterion to identify fault events, ensuring a low false positive rate. Results obtained from analysis of a real dataset collected from the accelerating cavities simulating a deployed scenario demonstrate the model’s ability to identify normal signals with 99.99% accuracy and correctly predict 80% of slowly developing faults. Notably, these achievements were achieved in the context of a highly imbalanced dataset, and fault predictions were made several hundred milliseconds before the onset of the fault. Anticipating faults enables preemptive measures to improve operational efficiency by preventing or mitigating their occurrence.

43 PARTICLE ACCELERATORS↗
NASA NTRSDate not supplied

Predicting Char Yield of High-Temperature Resins

A simulation protocol is developed to predict the char yield of organic resins during high-temperature processing. Such in silico methods can help screen promising new formulations for advanced materials, but previously no chemistry-sensitive technique existed to predict the important experimental value of char yield. The method utilizes a reactive force field (ReaxFF) to model the chemical transformation of precursor monomers into carbonized structures during three processing stages: ramp-up to processing temperatures (~3000 K), pyrolysis, and quenching. Achieving good agreement with experimental char yields requires continuous removal of small byproduct molecules to mimic outgassing, and the application of high pressure to eliminate porosity and encourage graphitization. More than ten different resin chemistries are investigated, including arylacetylenes, cyanate esters, phthalonitriles, and polyimides, representing a diverse group of precursors with respect to initial cyclic content, heteroatoms and reactive groups. The protocol correctly predicts the relative char yield between the investigated chemistries and provides quantitative agreement with experimental values, especially for high char yield resins. The properties of the resins during processing are compared, including outgassing products, morphology of the final chemical configurations, cyclic content and mechanical properties.

polymer simulations, molecular dynamics↗
NASA NTRSDate not supplied

Predicting Char Yield of High-Temperature Resins

A simulation protocol is developed to predict the char yield of organic resins during high-temperature processing. Simulation protocol in silico methods can help screen promising new formulations for advanced materials, but previously no chemistry-sensitive technique existed to predict the important experimental value of char yield. The method utilizes a reactive force field (ReaxFF) to model the chemical transformation of precursor monomers into carbonized structures during three processing stages: ramp-up to processing temperatures (~3000 K), pyrolysis, and quenching. Achieving good agreement with experimental char yields requires continuous removal of small byproduct molecules to mimic outgassing, and the application of high pressure to eliminate porosity and encourage graphitization. More than ten different resin chemistries are investigated, including arylacetylenes, cyanate esters, phthalonitriles, and polyimides, representing a diverse group of precursors with respect to initial cyclic content, heteroatoms and reactive groups. The protocol correctly predicts the relative char yield between the investigated chemistries and provides quantitative agreement with experimental values, especially for high char yield resins. The properties of the resins during processing are compared, including outgassing products, morphology of the final chemical configurations, cyclic content and mechanical properties.

polymer simulations, molecular dynamics↗
NASA NTRS2016

Initial Analysis of and Predictive Model Development for Weather Reroute Advisory Use

In response to severe weather conditions, traffic management coordinators specify reroutes to route air traffic around affected regions of airspace. Providing analysis and recommendations of available reroute options would assist the traffic management coordinators in making more efficient rerouting decisions. These recommendations can be developed by examining historical data to determine which previous reroute options were used in similar weather and traffic conditions. Essentially, using previous information to inform future decisions. This paper describes the initial steps and methodology used towards this goal. A method to extract relevant features from the large volume of weather data to quantify the convective weather scenario during a particular time range is presented. Similar routes are clustered. A description of the algorithm to identify which cluster of reroute advisories were actually followed by pilots is described. Models built for fifteen of the top twenty most frequently used reroute clusters correctly predict the use of the cluster for over 60 of the test examples. Results are preliminary but indicate that the methodology is worth pursuing with modifications based on insight gained from this analysis.

machine learning↗
NASA NTRS1983

A unified mathematical theory of electrophoretic processes

A mathematical theory is presented which shows that each of the four classical electrophoretic modes (zone electrophoresis, moving boundary electrophoresis, isotachophoresis, and isoelectric focusing) is based on the same general principles and can collectively be described in terms of a single set of equations. This model can predict the evolution of the four electrophoretic modes as a function of time. The model system is one-dimensional, neglecting the effects of electroosmosis, temperature gradients, and any bulk flows of liquid. The model is based on equations which express the components' dissociation equilibria, the mass transport due to electromigration and diffusion, electroneutrality, and the conservation of mass and charge. The model consists of a system of coupled partial differential and nonlinear algebraic equations which can be solved numerically by use of a computer. The versatility of this model was verified using an example of a three-component system containing cacodylate, tris hydroxylmethylaminomethane, and histidine. Results show that this model not only correctly predicts the characteristic features of each electrophoretic mode, but also gives details of the concentration, pH, and conductivity profiles not easily amenable to direct experimental measurement.

Bier, M.↗
NASA NTRS2000

Application of Three-Component PIV to a Hovering Rotor Wake

The key to accurate predictions of rotorcraft aerodynamics, acoustics, and dynamics lies in the accurate representation of the rotor wake. The vortical wake computed by rotorcraft CFD analyses typically suffer from numerical dissipation before the first blade passage. With some a priori knowledge of the wake trajectory, grid points can be concentrated along the trajectory to minimize the dissipation. Comprehensive rotorcraft analyses based on lifting-line theory rely on classical vortex models and/or semi-empirical information about the tip vortex structure. Until the location, size, and strength of the trailed tip vortex can be measured over a range of wake ages, the analyses will continue to be adjusted on a trial and error basis in order to correctly predict blade airloads, acoustics, dynamics, and performance. Using the laser light sheet technique, tip vortex location can be acquired in a straightforward manner. Measuring wake velocities and vortex core size, however, has been difficult and tedious using point-measurement techniques such as laser velocimetry. Recently, the Particle Image Velocimetry (PIV) technique has proven to be an efficient method for acquiring velocity measurements over relatively large areas and volumes of a rotor wake. The work reported to date, however, has been restricted to 2-component velocity measurements of the rotor wake. Three-component velocity measurements of a hovering rotor wake were acquired at NASA Ames Research Center in May 1999. This experiment represents a major step toward understanding the detailed structure of a rotor wake. This paper will focus primarily on the experimental technique used in acquiring this data. The accuracy and limitations of the current technique will also be discussed. Representative velocity field measurements will be included.

Yamauchi, Gloria K.↗
NASA NTRS1993

Application of a Reynolds stress model to separating boundary layers

Separating turbulent boundary layers occur in many practical engineering applications. Nonetheless, the physics of separation/reattachment of flows is poorly understood. During the past decade, various turbulence models were proposed and their ability to successfully predict some types of flows was shown. However. prediction of separating/reattaching flows is still a formidable task for model developers. The present study is concerned with the process of separation from a smooth surface. Features of turbulent separating boundary layers that are relevant to modeling include the following: the occurrence of zero wall shear stress, which causes breakdown of the boundary layer approximation; the law of the wall not being satisfied in the mean back flow region; high turbulence levels in the separated region; a significant low-frequency motion in the separation bubble; and the turbulence structure of the separated shear layer being quite different from that of either the mixing layers or the boundary layers. These special characteristics of separating boundary layers make it difficult for simple turbulence models to correctly predict their behavior.

Ko, Sung HO↗
NASA NTRS1994

A Comparison of Density Functional Theory with Ab initio Approaches for Systems Involving First Transition Row Metals

Density functional theory (DFT) is found to give a better description of the geometries and vibrational frequencies of FeL and FeL(sup +) systems than second order Moller Plesset perturbation theory (MP2). Namely, the DFT correctly predicts the shift in the CO vibrational frequency between free CO and the Sigma(sup -) state of FeCO and yields a good result for the Fe-C distance in the quartet states of FeCH4(+) 4 These are properties where the MP2 results are unsatisfactory. Thus DFT appears to be an excellent approach for optimizing the geometries and computing the zero-point energies of systems containing first transition row atoms. Because the DFT approach is biased in favor of the 3d(exp 7) occupation, whereas the more traditional approaches are biased in favor of the 3d(exp 6) occupation, differences are found in the relative ordering of states. It is shown that if the dissociation is computed to the most appropriate atomic asymptote and corrected to the ground state asymptote using the experimental separations, the DFT results are in good agreement with high levels of theory. The energetics at the DFT level are much superior to the MP2 and in most cases in good agreement with high levels of theory.

Ricca, Alessandra↗
NASA NTRS2012

An Assessment of Comprehensive Code Prediction State-of-the-Art Using the HART II International Workshop Data

Despite significant advancements in computational fluid dynamics and their coupling with computational structural dynamics (= CSD, or comprehensive codes) for rotorcraft applications, CSD codes with their engineering level of modeling the rotor blade dynamics, the unsteady sectional aerodynamics and the vortical wake are still the workhorse for the majority of applications. This is especially true when a large number of parameter variations is to be performed and their impact on performance, structural loads, vibration and noise is to be judged in an approximate yet reliable and as accurate as possible manner. In this paper, the capabilities of such codes are evaluated using the HART II Inter- national Workshop data base, focusing on a typical descent operating condition which includes strong blade-vortex interactions. Three cases are of interest: the baseline case and two cases with 3/rev higher harmonic blade root pitch control (HHC) with different control phases employed. One setting is for minimum blade-vortex interaction noise radiation and the other one for minimum vibration generation. The challenge is to correctly predict the wake physics - especially for the cases with HHC - and all the dynamics, aerodynamics, modifications of the wake structure and the aero-acoustics coming with it. It is observed that the comprehensive codes used today have a surprisingly good predictive capability when they appropriately account for all of the physics involved. The minimum requirements to obtain these results are outlined.

vanderWall, Berend G.↗
NASA NTRS2013

The HART II International Workshop: An Assessment of the State-of-the-Art in Comprehensive Code Prediction

Significant advancements in computational fluid dynamics (CFD) and their coupling with computational structural dynamics (CSD, or comprehensive codes) for rotorcraft applications have been achieved recently. Despite this, CSD codes with their engineering level of modeling the rotor blade dynamics, the unsteady sectional aerodynamics and the vortical wake are still the workhorse for the majority of applications. This is especially true when a large number of parameter variations is to be performed and their impact on performance, structural loads, vibration and noise is to be judged in an approximate yet reliable and as accurate as possible manner. In this article, the capabilities of such codes are evaluated using the HART II International Workshop database, focusing on a typical descent operating condition which includes strong blade-vortex interactions. A companion article addresses the CFD/CSD coupled approach. Three cases are of interest: the baseline case and two cases with 3/rev higher harmonic blade root pitch control (HHC) with different control phases employed. One setting is for minimum blade-vortex interaction noise radiation and the other one for minimum vibration generation. The challenge is to correctly predict the wake physics-especially for the cases with HHC-and all the dynamics, aerodynamics, modifications of the wake structure and the aero-acoustics coming with it. It is observed that the comprehensive codes used today have a surprisingly good predictive capability when they appropriately account for all of the physics involved. The minimum requirements to obtain these results are outlined.

vanderWall, Berend G.↗