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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
NASA NTRS2009

HART-II Acoustic Predictions using a Coupled CFD/CSD Method

This paper documents results to date from the Rotorcraft Acoustic Characterization and Mitigation activity under the NASA Subsonic Rotary Wing Project. The primary goal of this activity is to develop a NASA rotorcraft impulsive noise prediction capability which uses first principles fluid dynamics and structural dynamics. During this effort, elastic blade motion and co-processing capabilities have been included in a recent version of the computational fluid dynamics code (CFD). The CFD code is loosely coupled to computational structural dynamics (CSD) code using new interface codes. The CFD/CSD coupled solution is then used to compute impulsive noise on a plane under the rotor using the Ffowcs Williams-Hawkings solver. This code system is then applied to a range of cases from the Higher Harmonic Aeroacoustic Rotor Test II (HART-II) experiment. For all cases presented, the full experimental configuration (i.e., rotor and wind tunnel sting mount) are used in the coupled CFD/CSD solutions. Results show good correlation between measured and predicted loading and loading time derivative at the only measured radial station. A contributing factor for a typically seen loading mean-value offset between measured data and predictions data is examined. Impulsive noise predictions on the measured microphone plane under the rotor compare favorably with measured mid-frequency noise for all cases. Flow visualization of the BL and MN cases shows that vortex structures generated in the prediction method are consist with measurements. Future application of the prediction method is discussed.

Boyd, D. Douglas, Jr.↗
NASA NTRS1985

Viscoelastic behavior and lifetime (durability) predictions

A method for lifetime or durability predictions for laminated fiber reinforced plastics is given. The procedure is similar to but not the same as the well known time-temperature-superposition principle for polymers. The method is better described as an analytical adaptation of time-stress-super-position methods. The analytical constitutive modeling is based upon a nonlinear viscoelastic constitutive model developed by Schapery. Time dependent failure models are discussed and are related to the constitutive models. Finally, results of an incremental lamination analysis using the constitutive and failure model are compared to experimental results. Favorable results between theory and predictions are presented using data from creep tests of about two months duration.

Brinson, R. F.↗
NASA NTRS1982

Rotorcraft noise

This report is a compilation of papers presented at the NASA/U.S. Helicopter Industry Workshop on Aerodynamic Noise Prediction/Noise Reduction held at Langley Research Center, March 29-31, 1982. Included in the topics presented are papers on noise reduction techniques, scaling laws, empirical noise prediction, and methods for developing and validating noise prediction methods. The results of the working sessions are presented as findings, conclusions, and recommendations.

Helicopters↗
NASA NTRS2013

Advanced Methods for Determining Prediction Uncertainty in Model-Based Prognostics with Application to Planetary Rovers

Prognostics is centered on predicting the time of and time until adverse events in components, subsystems, and systems. It typically involves both a state estimation phase, in which the current health state of a system is identified, and a prediction phase, in which the state is projected forward in time. Since prognostics is mainly a prediction problem, prognostic approaches cannot avoid uncertainty, which arises due to several sources. Prognostics algorithms must both characterize this uncertainty and incorporate it into the predictions so that informed decisions can be made about the system. In this paper, we describe three methods to solve these problems, including Monte Carlo-, unscented transform-, and first-order reliability-based methods. Using a planetary rover as a case study, we demonstrate and compare the different methods in simulation for battery end-of-discharge prediction.

prognosis↗
NASA NTRS2018

Using Machine-Learning Methods and Expert Prediction Probabilities to Forecast Solar Flares

It has long been known that studying connection between solar flares and properties of magnetic field in active regions is very important for understanding the flare physics and developing space weather forecasts. The Helioseismic and Magnetic Imager onboard the Solar Dynamics Observatory (SDO/HMI) obtains tremendous amounts of magnetic field data products. However the operational NOAA Space Weather Prediction Center (SWPC) forecasts of solar flares still represent prediction probabilities issued by the experts. In this research we investigate the possibilities to enhance the daily operational flare forecasts performed at the SWPC by developing a synergy of the expert predictions and physics-based criteria, and by employing machine-learning methods. Among the physics-based criteria we consider the descriptors of the Polarity Inversion Line (PIL) and Space weather HMI Active Region Patches (SHARP), and derive from them daily characteristics of the entire Sun. We also consider the daily descriptors of the GOES Soft X-Ray (SXR) 1-8 Angstroms flux such as the flare history of the previous days and averaged X-Ray flux. We estimate the effectiveness in separation of flaring and non-flaring cases for each characteristic, as well as for the expert prediction probabilities, and find that some PIL, SHARP and SXR descriptors are as effective as the expert prediction probabilities and should be considered to issue the flare forecast. Finally, we train and test several Machine-Learning classification algorithms (Support Vector Classifiers with various kernel functions, k-Nearest Neighbor Classifier, Random Forest Classifier, and Neural Networks) using the most effective descriptors and expert prediction probabilities, and compare the obtained predictions with the current SWPC forecasts.

Machine-Learning↗
NASA NTRS1979

Near-field noise prediction for aircraft in cruising flight: Methods manual

Methods for predicting noise at any point on an aircraft while the aircraft is in a cruise flight regime are presented. Developed for use in laminar flow control (LFC) noise effects analyses, they can be used in any case where aircraft generated noise needs to be evaluated at a location on an aircraft while under high altitude, high speed conditions. For each noise source applicable to the LFC problem, a noise computational procedure is given in algorithm format, suitable for computerization. Three categories of noise sources are covered: (1) propulsion system, (2) airframe, and (3) LFC suction system. In addition, procedures are given for noise modifications due to source soundproofing and the shielding effects of the aircraft structure wherever needed. Sample cases, for each of the individual noise source procedures, are provided to familiarize the user with typical input and computed data.

Tibbetts, J. G.↗
DOE OSTI2024

E min : A First-Principles Thermochemical Descriptor for Predicting Molecular Synthesizability

Predicting the synthesizability of a new molecule remains an unsolved challenge that chemists have long tackled with heuristic approaches. Here, in this study, we report a new method for predicting synthesizability using a simple yet accurate thermochemical descriptor. We introduce E min , the energy difference between a molecule and its lowest energy constitutional isomer, as a synthesizability predictor that is accurate, physically meaningful, and first-principles based. We apply E min to 134,000 molecules in the QM9 data set and find that E min is accurate when used alone and reduces incorrect predictions of "synthesizable" by up to 52% when used to augment commonly used prediction methods. Our work illustrates how first-principles thermochemistry and heuristic approximations for molecular stability are complementary, opening a new direction for synthesizability prediction methods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1992

Method for improved prediction of bone fracture risk using bone mineral density in structural analysis

A non-invasive in-vivo method of analyzing a bone for fracture risk includes obtaining data from the bone such as by computed tomography or projection imaging which data represents a measure of bone material characteristics such as bone mineral density. The distribution of the bone material characteristics is used to generate a finite element method (FEM) mesh from which load capability of the bone can be determined. In determining load capability, the bone is mathematically compressed, and stress, strain force, force/area versus bone material characteristics are determined.

Cann, Christopher E.↗
NASA NTRSDate not supplied

Improving Computational Efficiency of Prognostics Algorithms in Resource-Constrained Settings

The field of prognostics and health management provides quantitative methods for monitoring and predicting the health of physical systems. Prognostics algorithms are useful in that they can be employed to assess the current state of a system, propagate the system state throughout time, and predict potential anomalies or failures that may occur. However, effective prognosis can be challenging to achieve in resource-constrained settings due to computational limitations and high computational latency, leading to obsolete predictions. Thus, computationally efficient and accurate algorithms are necessary for some prognostics applications. In this work, we implement three new algorithmic approaches to prediction (sampling methods, variable prediction time step, variable prediction sample size) with the goal of improving computational efficiency while minimizing decrease in model accuracy. To quantitatively analyze our results, we examine a use-case of degradation of a Lithium-ion battery. Notably, through this work it was found that none of the sampling approaches had a significant impact on computational efficiency or model accuracy in predicting EOD of the battery. However, our results show that prediction accuracy is highly dependent on the time step used, and that an appropriate time step can optimize both model accuracy and simulation efficiency. Finally, implementing a variable sample size also affected prediction, and our results show that tuning both the magnitude and timing of the sample size adjustment in an application-specific manner may prove useful in some applications. Taken together, our findings highlight the challenge of performing prognostics in resource-constrained settings, and illustrate the potential of developing new prediction algorithms to improve computational efficiency of prognosis.

Prognostics↗
NASA NTRS1994

Application of Coupled-Cluster Methods to the Prediction and Interpretation of the Spectra of Molecules of Interest in Atmospheric Chemistry

The quality of fundamental vibrational frequencies determined using the CCSD(T) method (singles and doubles coupled-cluster theory plus a perturbational estimate of the effects of connected triple excitations) is shown to be very good, usually predicting band centers to within +/-8/cm. This approach is applied to several molecules of interest in atmospheric chemistry, including HNO, NO2(+), H2CO, and HOCl. The HNO molecule displays a large and unusual anharmonicity in the H-N stretch. For the calculation of ultraviolet (UV) spectra, the linear response CCSD (LRCCSD) approach (which is equivalent to EOM-CCSD) has been shown to yield vertical excitation energies that are accurate to approximately 0.1 eV for singly excited electronic states. This method together with more approximate methods is used to examine the UV spectra of several molecules important in stratospheric chemistry, including HOCl, Cl2O, ClOOCl, ClOOH, and HOOH.

Lee, Timothy J.↗
NASA NTRS1986

A direct-inverse method for the prediction of transonic and separated flows about airfoils at high angles of attack

A direct-inverse technique and computer program called TAMSEP that can be used for the analysis of the flow about airfoils at subsonic and low transonic freestream velocities is presented. The method is based upon a direct-inverse nonconservative full potential inviscid method, a Thwaites laminar boundary layer technique, and the Barnwell turbulent momentum integral scheme; and it is formulated using Cartesian coordinates. Since the method utilizes inverse boundary conditions in regions of separated flow, it is suitable for predicting the flowfield about airfoils having trailing edge separated flow under high lift conditions. Comparisons with experimental data indicate that the method should be a useful tool for applied aerodynamic analyses.

Carlson, L. A.↗
DOE OSTI2021

Assessment of DFT methods for the prediction of detachment energies and electronic structures of complex and multiply charged anions

Here, in this work, we assess the ability of different density functional theory methods to reproduce the vertical/adiabatic detachment energies (VDEs/ADEs) of a series of 40 anions, including monoanion versus multiply charged anions (MCAs) and covalent versus noncovalent interaction. The statistical analysis of errors is firstly performed by comparing the theoretical values with the experimental benchmark data obtained from the negative ion photoelectron spectroscopy (NIPES). The proposed optimally tuned range-separated (OTRS) functionals are proved to not only well reproduce the experimental VDEs/ADEs, but also simulate experimental NIPES. The result implies a more serious issue of delocalization error for MCAs and a balanced description of electron-rich/- deficient region of anions is necessary. The radius of the spherically symmetric average electron localization function (ELF) region is demonstrated as a useful descriptor for the characterization of electronic structure of anionic systems and a quasilinear fitting model is proposed to efficiently obtain their OTRS parameters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1976

An improved method for the prediction of completely three-dimensional aerodynamic load distributions of configurations with leading edge vortex separation

The application of a higher-order subsonic potential flow panel method to the solution of three-dimensional flow about wing and wing-body combinations with leading-edge vortex separation is presented. The governing equations are the linear flow differential equation and nonlinear boundary conditions which require that the flow be parallel to the wing and body surfaces and that the free vortex sheet, springing from the leading and trailing edges, be aligned with the local flow and support no pressure jump. The vortex core is modeled as a simple line vortex which receives vorticity from the free sheet through a connecting sheet. The Kutta condition is imposed on all appropriate edges of the wing. This set of nonlinear equations is solved by an iterative procedure. The Goethert rule accounts for compressibility. The method has been programmed for the CDC 6600. Delta wings, gothic wings, arrow wings, cambered wings, and wing with body have been analyzed. Initial studies involving variations of panel density, vortex sheet sizing, Jacobian update, and initial geometry demonstrate that the present method generally exhibits good convergence characteristics.

Rubbert, p. E.↗
NASA NTRS2002

High Speed Jet Noise Prediction Using Large Eddy Simulation

Current methods for predicting the noise of high speed jets are largely empirical. These empirical methods are based on the jet noise data gathered by varying primarily the jet flow speed, and jet temperature for a fixed nozzle geometry. Efforts have been made to correlate the noise data of co-annular (multi-stream) jets and for the changes associated with the forward flight within these empirical correlations. But ultimately these emipirical methods fail to provide suitable guidance in the selection of new, low-noise nozzle designs. This motivates the development of a new class of prediction methods which are based on computational simulations, in an attempt to remove the empiricism of the present day noise predictions.

Lele, Sanjiva K.↗
NASA NTRS1982

Applications of system identification methods to the prediction of helicopter stability, control and handling characteristics

A set of results on rotorcraft system identification is described. Flight measurements collected on an experimental Puma helicopter are reviewed and some notable characteristics highlighted. Following a brief review of previous work in rotorcraft system identification, the results of state estimation and model structure estimation processes applied to the Puma data are presented. The results, which were obtained using NASA developed software, are compared with theoretical predictions of roll, yaw and pitching moment derivatives for a 6 degree of freedom model structure. Anomalies are reported. The theoretical methods used are described. A framework for reduced order modelling is outlined.

Padfield, G. D.↗
DOE OSTI2020

An Assessment of Homogeneous Mixture Method Cavitation Models in Predicting Cavitation in Nozzle Flow

The homogeneous mixture method (HMM) is a popular class of models used in the computational prediction of cavitation. Several cavitation models have been developed for use with HMM to govern the development and destruction of vapor in a fluid system. Two models credited to Kunz and Schnerr–Sauer are studied in this paper. The goal of this work is to provide an assessment of the two cavitation submodels in their ability to predict cavitation in nozzle flow. Validation data were obtained via experiments which employ both passive cavitation detection, (PCD) via acoustic sensing and optical cavitation detection (OCD) via camera imaging. The experiments provide quantitative information on cavitation inception and qualitative information on the vapor in the nozzle. The results show that initial vapor formation is not predicted precisely but within reason. A sensitivity analysis of the models to input parameters shows that the Schnerr–Sauer method does not depend upon the estimation of nuclei size and number density. Small changes in the vapor formation rate but not the total vapor volume can be seen when weighting parameters are modified. In contrast, changes to the input parameters for the Kunz model greatly change the final total vapor volume prediction. The assessment also highlights the influence of vapor convection within the method. Finally, the analysis shows that if the fluid and nozzle walls do not support nuclei larger than 40 μm, the methods would still predict cavitation when indeed there would be none in practice.

Engineering↗
NASA NTRS1988

A comparison of numerical methods for the prediction of two-dimensional heat transfer in an electrothermal deicer pad

Transient, numerical simulations of the deicing of composite aircraft components by electrothermal heating have been performed in a 2-D rectangular geometry. Seven numerical schemes and four solution methods were used to find the most efficient numerical procedure for this problem. The phase change in the ice was simulated using the Enthalpy method along with the Method for Assumed States. Numerical solutions illustrating deicer performance for various conditions are presented. Comparisons are made with previous numerical models and with experimental data. The simulation can also be used to solve a variety of other heat conduction problems involving composite bodies.

Deicer↗