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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

An Improved Approach to the Predictability & Reliability of the Onset of Turbulence With Shocks

The construction of numerical schemes for (a) stable and accurate simulation of turbulence with strong shocks, and for (b) obtaining correct propagation speed of discontinuities in the presence of stiff source terms share one important ingredient – minimization of numerical dissipation while maintaining numerical stability. The dual requirements to achieve both numerical stability and minimal numerical dissipation are often conflicting since existing shock capturing schemes were designed mainly to be robust for rapidly developed turbulence-free flows and for shock waves without stiff source term. For the past two decades, Yee and collaborators have focused on an improved understanding of the nonlinear behavior of different high order shock-capturing methods. It was found that even very high order methods without proper nonlinear stability and numerical dissipation control can either numerically smear the onset of turbulence due to excess numerical dissipation, or induce (onset) numerical turbulence that is not physical turbulence due to lack of proper numerical dissipation to improve nonlinear stability for long time integration. Our approach is to combine (I) and (II) below for obtaining the physically correct onset of turbulence with shocks, including problems with stiff source terms: (I) Nonlinear dynamics is utilized to complement the traditional linearized stability theory (Yee & Sweby, Yee et al., Griffiths et al., Lafon & Yee, Yee, Wang et al., Kotov et al. 1990- 2015) in order to (i) Minimize numerically induced false transition to turbulence, (ii) Minimize numerical instability due to long time integration of turbulent flows, (iii) Minimize numerically induced standing wave solutions, and (iv) Minimize wrong propagation of speed of discontinuities due to the presence of stiff source terms. (II) Our recently developed physical preserving (structural preserving) high order methods with improved nonlinear stability & accuracy that are essential in minimizing spurious numerics are used.

HECC↗
NASA NTRS2014

Contra-Rotating Open Rotor Tone Noise Prediction

Reliable prediction of contra-rotating open rotor (CROR) noise is an essential element of any strategy for the development of low-noise open rotor propulsion systems that can meet both the community noise regulations and the cabin noise limits. Since CROR noise spectra typically exhibits a preponderance of tones, significant efforts have been directed towards predicting their tone spectra. To that end, there has been an ongoing effort at NASA to assess various in-house open rotor tone noise prediction tools using a benchmark CROR blade set for which significant aerodynamic and acoustic data had been acquired in wind tunnel tests. In the work presented here, the focus is on the near-field noise of the benchmark open rotor blade set at the cruise condition. Using an analytical CROR tone noise model with input from high-fidelity aerodynamic simulations, detailed tone noise spectral predictions have been generated and compared with the experimental data. Comparisons indicate that the theoretical predictions are in good agreement with the data, especially for the dominant CROR tones and their overall sound pressure level. The results also indicate that, whereas individual rotor tones are well predicted by the linear sources (i.e., thickness and loading), for the interaction tones it is essential that the quadrupole sources be included in the analysis.

Propeller Noise↗
NASA NTRS2014

Contra-Rotating Open Rotor Tone Noise Prediction

Reliable prediction of contra-rotating open rotor (CROR) noise is an essential element of any strategy for the development of low-noise open rotor propulsion systems that can meet both the community noise regulations and cabin noise limits. Since CROR noise spectra exhibit a preponderance of tones, significant efforts have been directed towards predicting their tone content. To that end, there has been an ongoing effort at NASA to assess various in-house open rotor tone noise prediction tools using a benchmark CROR blade set for which significant aerodynamic and acoustic data have been acquired in wind tunnel tests. In the work presented here, the focus is on the nearfield noise of the benchmark open rotor blade set at the cruise condition. Using an analytical CROR tone noise model with input from high-fidelity aerodynamic simulations, tone noise spectra have been predicted and compared with the experimental data. Comparisons indicate that the theoretical predictions are in good agreement with the data, especially for the dominant tones and for the overall sound pressure level of tones. The results also indicate that, whereas the individual rotor tones are well predicted by the combination of the thickness and loading sources, for the interaction tones it is essential that the quadrupole source is also included in the analysis.

Propeller Noise↗
NASA NTRS1983

Design of the hybrid automated reliability predictor

The design of the Hybrid Automated Reliability Predictor (HARP), now under development at Duke University, is presented. The HARP approach to reliability prediction is characterized by a decomposition of the overall model into fault-occurrence and fault-handling sub-models. The fault-occurrence model is a non-homogeneous Markov chain which is solved analytically, while the fault-handling model is a Petri Net which is simulated. HARP provides automated analysis of sensitivity to uncertainties in the input parameters and in the initial state specifications. It then produces a predicted reliability band as a function of mission time, as well as estimates of the improvement (narrowing of the band) to be gained by a specified amount of reduction in uncertainty.

Geist, R.↗
NASA NTRS1977

Measurement, estimation, and prediction of software reliability

Quantitative indices of software reliability are defined, and application of three important indices is indicated: (1) reliability measurement, (2) reliability estimation, and (3) reliability prediction. State of the art techniques for each of these procedures are presented together with considerations of data acquisition. Failure classifications and other documentation for comprehensive software reliability evaluation are described.

Hecht, H.↗
NASA NTRS1991

Using probabilistic analysis to assess the reliability of predicted SRB aft-skirt stresses

Probabilistic failure analysis is a tool to predict the reliability of a part or system. Probabalistic techniques were used to predict critical stresses which occur in the solid rocket booster aft-skirt during main engine buildup, immediately prior to lift-off. More than any other hold down post (HDP) load component, the Z loads are sensitive to variations in strains and calibration constants. Also, predicted aft-skirt stresses are strongly affected by HDP load variations. Therefore, the instrumented HDP are not effective load transducers for Z loads, and, when used with aft skirt stress indicator equations, yield estimates with large uncertainty. Monte Carlo simulation proved to be a straight forward way of studying the overlapping effects of multiple parameters on predicted equipment performance. An advantage of probabilistic analysis is the degree of uncertainty of each parameter as stated explicitly by its probability distribution. It was noted, however, that the choice of parameter distribution had a large effect on the simulation results. Many times these distributions must be assumed. The engineer who is designing the part should be responsible for the choice of parameter distribution.

Richardson, James A.↗
NASA NTRS1991

TranAir applications to transonic flowfield predictions

Reliable methods for predicting external aircraft flowfields are required for airframe/engine and aircraft/store integrations, as well as for predicting store trajectories. Although Euler methods have demonstrated an impressive capability for predicting aircraft flowfields at all speed regimes, the need to generate a separate grid for any new or modified configuration make these methods impractical to use in a preliminary design environment. The PAN AIR and Nielsen programs are considerably easier to use, but are limited to the linear speed regime. The TranAir program uses PAN AIR type geometry inputs and works well in the transonic speed regime. It might be the technique of choice for predicting transonic aircraft flowfields. A study was made of the relative merits of Nielsen, PAN AIR and TranAir for predicting the transonic flowfield about the F-18 aircraft.

Cenko, A.↗
DOE OSTI2020

Combining Three-Dimensional Modeling with Artificial Intelligence to Increase Specificity and Precision in Peptide–MHC Binding Predictions

The reliable prediction of the affinity of candidate peptides for the MHC is important for predicting their potential antigenicity and thus influences medical applications, such as decisions on their inclusion in T cell–based vaccines. In this study, we present a rapid, predictive computational approach that combines a popular, sequence-based artificial neural network method, NetMHCpan 4.0, with three-dimensional structural modeling. We find that the ensembles of bound peptide conformations generated by the programs MODELLER and Rosetta FlexPepDock are less variable in geometry for strong binders than for low-affinity peptides. In tests on 1271 peptide sequences for which the experimental dissociation constants of binding to the well-characterized murine MHC allele H-2D b are known, by applying thresholds for geometric fluctuations the structure-based approach in a standalone manner drastically improves the statistical specificity, reducing the number of false positives. Furthermore, filtering candidates generated with NetMHCpan 4.0 with the structure-based predictor led to an increase in the positive predictive value (PPV) of the peptides correctly predicted to bind very strongly (i.e., Kd < 100 nM) from 40 to 52% (p = 0.027). The combined method also significantly improved the PPV when tested on five human alleles, including some with limited data for training. Overall, an average increase of 10% in the PPV was found over the standalone sequence-based method. The combined method should be useful in the rapid design of effective T cell–based vaccines.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2015

Charge transport model to predict intrinsic reliability for dielectric materials

Several lifetime models, mostly empirical in nature, are used to predict reliability for low-k dielectrics used in integrated circuits. There is a dispute over which model provides the most accurate prediction for device lifetime at operating conditions. As a result, there is a need to transition from the use of these largely empirical models to one built entirely on theory. Therefore, a charge transport model was developed to predict the device lifetime of low-k interconnect systems. The model is based on electron transport and donor-type defect formation. Breakdown occurs when a critical defect concentration accumulates, resulting in electron tunneling and the emptying of positively charged traps. The enhanced local electric field lowers the barrier for electron injection into the dielectric, causing a positive feedforward failure. The charge transport model is able to replicate experimental I-V and I-t curves, capturing the current decay at early stress times and the rapid current increase at failure. The model is based on field-driven and current-driven failure mechanisms and uses a minimal number of parameters. All the parameters have some theoretical basis or have been measured experimentally and are not directly used to fit the slope of the time-to-failure versus applied field curve. Despite this simplicity, the model is able to accurately predict device lifetime for three different sources of experimental data. The simulation's predictions at low fields and very long lifetimes show that the use of a single empirical model can lead to inaccuracies in device reliability.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2007

Prediction of Geomagnetic Activity and Key Parameters in High-Latitude Ionosphere-Basic Elements

Prediction of geomagnetic activity and related events in the Earth's magnetosphere and ionosphere is an important task of the Space Weather program. Prediction reliability is dependent on the prediction method and elements included in the prediction scheme. Two main elements are a suitable geomagnetic activity index and coupling function -- the combination of solar wind parameters providing the best correlation between upstream solar wind data and geomagnetic activity. The appropriate choice of these two elements is imperative for any reliable prediction model. The purpose of this work was to elaborate on these two elements -- the appropriate geomagnetic activity index and the coupling function -- and investigate the opportunity to improve the reliability of the prediction of geomagnetic activity and other events in the Earth's magnetosphere. The new polar magnetic index of geomagnetic activity and the new version of the coupling function lead to a significant increase in the reliability of predicting the geomagnetic activity and some key parameters, such as cross-polar cap voltage and total Joule heating in high-latitude ionosphere, which play a very important role in the development of geomagnetic and other activity in the Earth s magnetosphere, and are widely used as key input parameters in modeling magnetospheric, ionospheric, and thermospheric processes.

Lyatsky, W.↗