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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 487 records · Page 27
All sourcesNASA NTRSDOE OSTI
NASA NTRS1985

Hypersonic characteristics of an advanced aerospace plane

A series of hypersonic wind-tunnel tests have been conducted in the NASA Langley Hypersonic Facilities Complex to obtain the static longitudinal and lateral-directional aerodynamic characteristics of an advanced aerospace plane. Data were obtained at 0 to 20 deg angles of attack and -3 to 3 deg angles of sideslip at Mach numbers of 6 and 10 in air and 20 in helium. Results show that stable trim capability exists at angles of attack near maximum lift-drag ratio (L/D). Both performance and stability exhibited some Mach number dependency. The vehicle was longitudinally unstable at low angles of attack but stable at angles of attack near and above maximum L/D. It was directionally unstable with positive dihedral effect. The rudder showed an inability to provide lateral-directional control, and removing the vertical tail resulted in increased directional instability. Analytical predictions of the static longitudinal aerodynamic coefficients gave relatively good comparisons with the experimental data.

Mccandless, R. S.↗
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 NTRS2001

Capillary Flow in Containers of Polygonal Section: Theory and Experiment

An improved understanding of the large-length-scale capillary flows arising in a low-gravity environment is critical to that engineering community concerned with the design and analysis of spacecraft fluids management systems. Because a significant portion of liquid behavior in spacecraft is capillary dominated it is natural to consider designs that best exploit the spontaneous character of such flows. In the present work, a recently verified asymptotic analysis is extended to approximate spontaneous capillary flows in a large class of cylindrical containers of irregular polygonal section experiencing a step reduction in gravitational acceleration. Drop tower tests are conducted using partially-filled irregular triangular containers for comparison with the theoretical predictions. The degree to which the experimental data agree with the theory is a testament to the robustness of the basic analytical assumption of predominantly parallel flow. As a result, the closed form analytical expressions presented serve as simple, accurate tools for predicting bulk flow characteristics essential to practical low-g system design and analysis. Equations for predicting corner wetting rates, total container flow rates, and transient surfaces shapes are provided that are relevant also to terrestrial applications such as capillary flow in porous media.

Weislogel, Mark M.↗
DOE OSTI2024

A machine learning approach for determining temperature-dependent bandgap of metal oxides utilizing Allen–Heine–Cardona theory and O’Donnell model parameterization

To evaluate the high temperature sensing properties of metal oxide and perovskite materials suitable for use in combustion environments, it is necessary to understand the temperature dependence of their bandgaps. Although such temperature-driven changes can be calculated via the Allen–Heine–Cardona (AHC) theory, which assesses electron–phonon coupling for the bandgap correction at given temperatures, this approach is computationally demanding. Another approach to predict bandgap temperature-dependence is the O’Donnell model, which uses analytical expressions with multiple fitting parameters that require bandgap information at 0 K. This work employs data-driven Gaussian process regression (GPR) to predict the parameters employed in the O’Donnell model from a set of physical features. We use a sample of 54 metal oxides for which density functional theory has been performed to calculate the bandgap at 0 K, and the AHC calculations have been carried out to determine the shift in the bandgap at non-zero temperatures. As the AHC calculations are impractical for high-throughput screening of materials, the developed GPR model attempts to alleviate this issue by predicting the O'Donnell parameters purely from physical features. To mitigate the reliability issues arising from the very small size of the dataset, we apply a Bayesian technique to improve the generalizability of the data-driven models as well as quantify the uncertainty associated with the predictions. The method captures well the overall trend of the O’Donnell parameters with respect to a reduced feature set obtained by transforming the available physical features. Quantifying the associated uncertainty helps us understand the reliability of the predictions of the O’Donnell parameters and, therefore, the bandgap as a function of temperature for any novel material.

36 MATERIALS SCIENCE↗
NASA NTRS1987

Application of a comprehensive analytical model of rotorcraft aerodynamics and dynamics (CAMRAD) to the McDonnell Douglas AH-64A helicopter

CAMRAD results on main rotor blade natural frequency and structural loads predictions are compared to flight test data and predictions of the Dynamic Analysis Research Tool (DART) and the Rotor/Airframe Comprehensive Aeroelastic Program (RACAP). Consideration is also given to the effects of various analytical options available in CAMRAD including dynamic stall, wake modeling, and the number of bending and torsion degrees of freedom included in the structural analysis. It is concluded that, while several modeling limitations are identified in the CAMRAD structural analyses, the structural loads predictions are as accurate as analysis codes which provide more representative models of the complex geometries and structures of the AH-64A rotor system. However, it is noted that the CAMRAD analysis cannot be considered fully reliable for dynamic predictions for more advanced bearingless rotor designs being proposed for future AH-64 configurations.

Callahan, C.↗
DOE OSTI2020

The Lorentzian inversion formula and the spectrum of the 3d O(2) CFT

We study the spectrum and OPE coefficients of the three-dimensional critical O(2) model, using four-point functions of the leading scalars with charges 0, 1, and 2 ( s , $\phi$, and t ). We obtain numerical predictions for low-twist OPE data in several charge sectors using the extremal functional method. We compare the results to analytical estimates using the Lorentzian inversion formula and a small amount of numerical input. We find agreement between the analytic and numerical predictions. We also give evidence that certain scalar operators lie on double-twist Regge trajectories and obtain estimates for the leading Regge intercepts of the O(2) model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS2018

Towards Design Principles for Visual Analytics in Operations Contexts

Operations engineering teams interact with complex data systems to make technical decisions that ensure the operational efficacy of their missions. To support these decision-making tasks, which may require elastic prioritization of goals dependent on changing conditions, custom analytics tools are often developed. We were asked to develop such a tool by a team at the NASA Jet Propulsion Laboratory, where rover telecom operators make decisions based on models predicting how much data rovers can transfer from the surface of Mars. Through research, design, implementation, and informal evaluation of our new tool, we developed principles to inform the design of visual analytics systems in operations contexts. We offer these principles as a step towards understanding the complex task of designing these systems. The principles we present are applicable to designers and developers tasked with building analytics systems in domains that face complex operations challenges such as scheduling, routing, and logistics.

Lombeyda, Santiago↗
NASA NTRS1987

Thermal barrier coating life prediction model development

The objectives of this program are to increase understanding of thermal barrier coating (TBC) degradation and failure modes, to generate quantitative ceramic failure life data under cyclic thermal conditions which simulate those encountered in gas turbine engine service, and to develop an analytical methodology for prediction of coating life in the engine. Observations of degradation and failure modes in plasma deposited ceramic indicate that spallation failure results from progressive cracking of the ceramic parallel to and adjacent to, but not coincident with the metal-ceramic interface.

Demasi, J. T.↗
DOE OSTI2024

Quantifying Uncertainty in HPC Job Queue Time Predictions

High Performance Computing (HPC) has developed at an unprecedented pace in recent decades. This growth has demanded corresponding development in the area of HPC Operational Data Analytics (ODA), which encompasses a wide range of data analysis techniques, ML/AI efforts, tools, and visualizations. Published studies in ODA offer a variety of practical ways to inform HPC users, administrators, procurement managers, and other stakeholders. Uncertainty analysis, however, is rare in the related published literature. For instance, we identify only 1 out of 14 existing studies focused on job queue time prediction that investigates the uncertainty aspect of their proposed predictions. We recognize the utmost importance uncertainty quantification can have in such predictive analytics solutions, with consequences in how users interpret information they receive, and attempt to bridge this gap. With the goal of improving access to such insights, we develop a process for determining upper and lower bounds of the predicted queue times of a regression model at a specified confidence level. Our current research is focused on the uncertainty in predicting job queue times, yet our approach may be employed in predicting other metrics.

HPC↗
DOE OSTI2020

Evaluation of Graph Analytics Frameworks Using the GAP Benchmark Suite

The analysis of connected data is an increasingly important application in high-performance computing. Such analyses can reveal fraudulent patterns in financial transactions, optimize telecommunications networks, predict information flow in social networks, etc. However, the landscape of graph analytics is highly diverse. Graph algorithms stress processor architectures differently, and no one graph can represent all topologies. Consequently, no single approach or framework is expected to be optimal for all graph analytics problems. To help make sense of this diverse landscape, we evaluated four approaches to graph analytics: GraphBLAS, Galois, BGL17, GraphIt; and compare them against hand-tuned implementations that take advantage of hardware features on our test platform. Graph- BLAS formulates graph analytics as sparse linear algebra. Galois provides syntactic constructs for data parallelism over irregular data structures. BGL17 is a generic C++ template library for implementing graph algorithms. GraphIt provides a domain- specific language to describe and optimize graph algorithms. We use the GAP Benchmark Suite to establish baseline performance and guide the side-by-side evaluation of each framework. GAP consists of 30 tests: six graph analytics algorithms (breadth- first search, single-source shortest path, PageRank, betweenness centrality, connected components, and triangle counting) run on five graphs, each with different topological characteristics (e.g., high diameter, skewed degree distribution, high average degree). High-performance reference implementations are included for each benchmark algorithm. Because a graph can be loaded into memory a number of ways (e.g., flat file on disk, compressed sparse format, data frames, retrieved from SQL or NoSQL databases), our evaluation focused on computational performance rather than I/O. Our results show the relative strengths of each framework.

Graph algorithms, Benchmarking, shared-memory prog↗
NASA NTRS1985

Evaluation of capillary reinforced composites

Anti-icing of the inlet of jet engines is generally performed with high pressure heated air that is directed forward from the compressor through a series of pipes to various manifolds located near the structures to be anti-iced. From these manifolds, the air is directed to all flowpath surfaces that may be susceptible to ice formation. There the anti-icing function may be performed by either heat conduction or film heating. Unfortunately, the prospect of utilizing lighweight, high strength composites for inlet structures of jet engines has been frustrated by the low transverse thermal conductivity of such materials. It was the objective of this program to develop an advanced materials and design concept for anti-icing composite structures. The concept that was evaluated used capillary glass tubes embedded on the surface of a composite structure with heated air ducted through the tubes. An analytical computer program was developed to predict the anti-icing performance of such tubes and a test program was conducted to demonstrate actual performance of this system. Test data and analytical code results were in excellent agreement. Both indicate feasibility of using capillary tubes for surface heating as a means for composite engine structures to combat ice accumulation.

Cahill, J. E.↗
DOE OSTI2023

Video frame prediction of microbial growth with a recurrent neural network

The recent explosion of interest and advances in machine learning technologies has opened the door to new analytical capabilities in microbiology. Using experimental data such as images or videos, machine learning, in particular deep learning with neural networks, can be harnessed to provide insights and predictions for microbial populations. This paper presents such an application in which a Recurrent Neural Network (RNN) was used to perform prediction of microbial growth for a population of two Pseudomonas aeruginosa mutants. The RNN was trained on videos that were acquired previously using fluorescence microscopy and microfluidics. Of the 20 frames that make up each video, 10 were used as inputs to the network which outputs a prediction for the next 10 frames of the video. The accuracy of the network was evaluated by comparing the predicted frames to the original frames, as well as population curves and the number and size of individual colonies extracted from these frames. Overall, the growth predictions are found to be accurate in metrics such as image comparison, colony size, and total population. Yet, limitations exist due to the scarcity of available and comparable data in the literature, indicating a need for more studies. Both the successes and challenges of our approach are discussed.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2018

On the Development of Shell Buckling Knockdown Factors for Stiffened Metallic Launch Vehicle Cylinders

From the 1920s to the early 1970s, many shell buckling experiments were conducted in an effort to understand the complex buckling behavior exhibited by thin-walled cylindrical shells, to provide data to correlate with new shell stability theories, and provide design guidelines. Typically, the experiments yielded buckling loads that were substantially lower than the corresponding analytical predictions, which were based on simplified linear bifurcation analyses of geometrically perfect shells with nominal dimensions and idealized boundary conditions. The seminal works by von Kármán and Tsien, by Donnell and Wan, and by Koiter identified small deviations from the idealized geometry of a shell, known as initial geometric imperfections, as a primary source of the discrepancy between corresponding analytical predictions and experimental results. However, the computational tools and capabilities at that time could not perform the nonlinear analyses needed to assess the effects of these imperfections on the buckling behavior of thin-walled shells. Thus, buckling design allowables were determined by establishing lower bounds to test data. Specifically, empirical design factors, that have become known as knockdown factors, were determined and were to be used in conjunction with linear bifurcation analyses for simply supported shells; that is, these empirical factors were used to "knock down" the value of the unconservative simplified analytical prediction. This approach to shell buckling design has proved satisfactory for most design purposes and remains prominent in industry practice, as evidenced by the extensive use of the NASA space vehicle design criteria and recommendations. Unfortunately, the current design guidelines have not been updated since they were first published in the late 1960s and may not be able to take full advantage of modern materials, precision manufacturing processes, and new structural concepts.

Hilburger, Mark W.↗
DOE OSTI2022

Generalized Analysis of Dynamic Flow Fouling on Heat Transfer Surfaces

Several energy applications involve flow of untreated heat transfer fluids that contain trace amounts of mineral salts, such as calcium carbonate and calcium sulfate, which show reverse solubility with temperature. The gradual accretion of these salts onto the heat transfer surfaces causes fouling that degrades thermal performance over time. While fouling of bare surfaces has been extensively studied, fouling of nonwetting superhydrophobic or liquid-infused surfaces is less understood, especially under dynamic flow conditions. This study presents a systematic experimental analysis to elucidate dynamic flow fouling of calcium carbonate and calcium sulfate on smooth, superhydrophobic and liquid-infused surfaces in a generalized manner. Here, copper tubes with modified inner surface wettability are fabricated and subjected to forced convection at different flow rates and fouling salt concentrations. Fouling characteristics of the two salts on the different surfaces are examined through microstructural analysis, and quantified in terms of asymptotic fouling resistance that measures the total extent of fouling, and a threshold time, which correlates to the onset of significant fouling. Using Taguchi design of experiments, the study reports, for the first time, closed-form analytical relationships for the asymptotic fouling thermal resistance and threshold time on the Reynolds number, dimensionless concentration of fouling agent and dimensionless infused liquid viscosity that represents the different surface types in a unified manner. It is shown that the analytical model accurately predicts the fouling characteristics in up to about 97% of the data, based on which contour maps of optimum surface designs for minimizing fouling resistance are presented. The results provide information on designing surfaces for reduced fouling or for estimating the fouling characteristics for a given surface in applications.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Modeling inclusive electron-nucleus scattering with Bayesian artificial neural networks

We introduce a Bayesian protocol based on artificial neural networks that is suitable for modeling inclusive electron-nucleus scattering on a variety of nuclear targets with quantified uncertainties. Unlike previous applications in the field, which directly parameterize the cross sections, our approach employs artificial neural networks to represent the longitudinal and transverse response functions. In contrast to cross sections, which depend on the incoming energy, scattering angle, and energy transfer, the response functions are determined solely by the energy and momentum transfer to the system, allowing the angular component to be treated analytically. We assess the accuracy and predictive power of our framework against the extensive data in the quasielastic inclusive electron-scattering database. Additionally, we present novel extractions of the longitudinal and transverse response functions and compare them with previous experimental analysis and nuclear ab-initio calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1974

Booster aerodynamic heating: Test support

Several technical areas were encompassed in providing support for booster thermal environment test work. These areas included: (1) cavity flow heating, (2) rarefied flow heating, and (3) impulse operated model research and testing. Cavity flow heating problems were studied with respect to the proposed altitude control motors for the space shuttle. Available literature on this subject was reviewed and analytical predictive methods were summarized for use in planning testing work. Rarefied flow heating data was reviewed and correlated. The study showed the importance of considering rarefied flow conditions in launch thermal environment prediction. Impulse operated model research and testing was conducted to provide a basis for understanding and designing such models for booster thermal environment testing.

Engel, C. D.↗
NASA NTRS1975

Transport of liquid state nitrogen through long length service lines during thermal/vacuum testing

Physical and analytical aspects associated with the transport are presented. Included is a definition of the problems and difficulties imposed by the servicing of a typical solid cryogen system, as well as a discussion of the transport requirements and of the rationale which governed their solution. A successful detailed transport configuration is defined, and the application of established mathematics to the design approach is demonstrated. The significance of head pressure, pressure drop, line friction, heat leak, Reynolds number, and the fundamental equilibrium demands of pressure and temperature were examined as they relate to the achievement of liquid state flow. Performance predictions were made for the transport system, and several analytical quantities are tabulated. These data are analyzed and compared with measured and calculated results obtained while actually servicing a solid cryogen system during thermal/vacuum testing.

Florio, F. A.↗
NASA NTRS1976

Experimental and theoretical investigation of fatigue life in reusable rocket thrust chambers

During a test program to investigate low-cycle thermal fatigue, 13 rocket combustion chambers were fabricated and cyclically test fired to failure. Six oxygen-free, high-conductivity (OFHC) copper and seven Amzirc chambers were tested. The chamber liners were fabricated of copper or copper alloy and contained milled coolant channels. The chambers were completed by means of an electroformed nickel closeout. The oxidant/fuel ratio for the liquid oxygen and gaseous hydrogen propellants was 6.0. The failures in the OFHC copper chambers were not typical fatigue failures but are described as creep rupture enhanced by ratcheting. The coolant channels bulged toward the chamber centerline, resulting in progressive thinning of the wall during each cycle. The failures in the Amzirc alloy chambers were caused by low-cycle thermal fatigue. The lives were much shorter than were predicted by an analytical structural analysis computer program used in conjunction with fatigue life data from isothermal test specimens, due to the uneven distribution of Zr in the chamber material.

Hannum, N. P.↗