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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Key Reliability Drivers of Liquid Propulsion Engines and A Reliability Model for Sensitivity Analysis

This paper is to address the in-flight reliability of a liquid propulsion engine system for a launch vehicle. We first establish a comprehensive list of system and sub-system reliability drivers for any liquid propulsion engine system. We then build a reliability model to parametrically analyze the impact of some reliability parameters. We present sensitivity analysis results for a selected subset of the key reliability drivers using the model. Reliability drivers identified include: number of engines for the liquid propulsion stage, single engine total reliability, engine operation duration, engine thrust size, reusability, engine de-rating or up-rating, engine-out design (including engine-out switching reliability, catastrophic fraction, preventable failure fraction, unnecessary shutdown fraction), propellant specific hazards, engine start and cutoff transient hazards, engine combustion cycles, vehicle and engine interface and interaction hazards, engine health management system, engine modification, engine ground start hold down with launch commit criteria, engine altitude start (1 in. start), Multiple altitude restart (less than 1 restart), component, subsystem and system design, manufacturing/ground operation support/pre and post flight check outs and inspection, extensiveness of the development program. We present some sensitivity analysis results for the following subset of the drivers: number of engines for the propulsion stage, single engine total reliability, engine operation duration, engine de-rating or up-rating requirements, engine-out design, catastrophic fraction, preventable failure fraction, unnecessary shutdown fraction, and engine health management system implementation (basic redlines and more advanced health management systems).

Huang, Zhao-Feng↗
DOE OSTI2023

Sensitivity-Driven Experimental Design to Facilitate Control of Dynamical Systems

Control of nonlinear dynamical systems is a complex and multifaceted process. Essential elements of many engineering systems include high-fidelity physics-based modeling, offline trajectory planning, feedback control design, and data acquisition strategies to reduce uncertainties. Here this article proposes an optimization-centric perspective which couples these elements in a cohesive framework. We introduce a novel use of hyper-differential sensitivity analysis to understand the sensitivity of feedback controllers to parametric uncertainty in physics-based models used for trajectory planning. These sensitivities provide a foundation to define an optimal experimental design which seeks to acquire data most relevant in reducing demand on the feedback controller. Our proposed framework is illustrated on the Zermelo navigation problem and a hypersonic trajectory control problem using data from NASA’s X-43 hypersonic flight tests.

42 ENGINEERING↗
DOE OSTI2024

PDF DECODER ANALYSIS CODE

SF-24-038"PDFdecoder", as a new application to explore parametrizations of parton distribution functions (PDFs) of the proton or other hadrons. The PDFs are fundamental quantities in particle physics which are necessary inputs to precise theoretical predictions for experiments at the Large Hadron Collider (LHC) and other facilities. As such, understanding how the PDFs are parametrized and associated uncertainties is a pressing need. The specific problem PDFdecoder confronts is the need of having a tractable and interpretably machine-learning (ML) framework to parametrize the PDFs and their uncertainties so as to understand how a given preferred parametrization is obtained. This problem has not been significantly addressed in the current literature. While other groups have used ML-based approaches to parametrize PDFs in the form of feed-forward neural networks, the question of tractability has not been explored in a PDF context. Our solution makes significant progress in this problem by using an array of encoder-decoder (essentially, autoencoder) architectures with varying constraints to the intermediate latent spaces based on interpretable physics. As a consequence, the trained models can be used as generative networks to produce interpretable predictions for the PDFs in a way that can be refined and studied further.

Hobbs, Timothy↗
NASA NTRS1997

Sensitivity Analysis and Optimization of Aerodynamic Configurations with Blend Surfaces

A novel (geometrical) parametrization procedure using solutions to a suitably chosen fourth order partial differential equation is used to define a class of airplane configurations. Inclusive in this definition are surface grids, volume grids, and grid sensitivity. The general airplane configuration has wing, fuselage, vertical tail and horizontal tail. The design variables are incorporated into the boundary conditions, and the solution is expressed as a Fourier series. The fuselage has circular cross section, and the radius is an algebraic function of four design parameters and an independent computational variable. Volume grids are obtained through an application of the Control Point Form method. A graphic interface software is developed which dynamically changes the surface of the airplane configuration with the change in input design variable. The software is made user friendly and is targeted towards the initial conceptual development of any aerodynamic configurations. Grid sensitivity with respect to surface design parameters and aerodynamic sensitivity coefficients based on potential flow is obtained using an Automatic Differentiation precompiler software tool ADIFOR. Aerodynamic shape optimization of the complete aircraft with twenty four design variables is performed. Unstructured and structured volume grids and Euler solutions are obtained with standard software to demonstrate the feasibility of the new surface definition.

Thomas, A. M.↗
NASA NTRS1996

Dynamic Analysis of Spur Gear Transmissions (DANST). PC Version 3.00 User Manual

DANST is a FORTRAN computer program for static and dynamic analysis of spur gear systems. The program can be used for parametric studies to predict the static transmission error, dynamic load, tooth bending stress and other properties of spur gears as they are influenced by operating speed, torque, stiffness, damping, inertia, and tooth profile. DANST performs geometric modeling and dynamic analysis for low- or high-contact-ratio spur gears. DANST can simulate gear systems with contact ratios ranging from one to three. It was designed to be easy to use and it is extensively documented in several previous reports and by comments in the source code. This report describes installing and using a new PC version of DANST, covers input data requirements and presents examples.

Oswald, Fred B.↗
NASA NTRS1992

Hi-alpha forebody design. Part 1: Methodology base and initial parametrics

The use of Computational Fluid Dynamics (CFD) has been investigated for the analysis and design of aircraft forebodies at high angle of attack combined with sideslip. The results of the investigation show that CFD has reached a level of development where computational methods can be used for high angle of attack aerodynamic design. The classic wind tunnel experiment for the F-5A forebody directional stability has been reproduced computationally over an angle of attack range from 10 degrees to 45 degrees, and good agreement with experimental data was obtained. Computations have also been made at combined angle of attack and sideslip over a chine forebody, demonstrating the qualitative features of the flow, although not producing good agreement with measured experimental pressure distributions. The computations were performed using the code known as cfl3D for both the Euler equations and the Reynolds equations using a form of the Baldwin-Lomax turbulence model. To study the relation between forebody shape and directional stability characteristics, a generic parametric forebody model has been defined which provides a simple analytic math model with flexibility to capture the key shape characteristics of the entire range of forebodies of interest, including chines.

Mason, William H.↗
NASA NTRS2019

Benchmarking Mixed Mode Failure in Progressive Damage and Failure Analysis Methods

The verification and validation of progressive-damage-analysis finite element methods are difficult but critical tasks to undertake during their development. Verification exercises assess whether a predictive analysis tool produces results that are consistent with the fundamental concepts and assumptions of the tool under evaluation. Ideally, closed-form analytical solutions can be derived for which method verification results can be compared. Problems selected for computational tool verification are often simple and isolate individual features of the tool. In the case of progressive damage finite element methods, verifications should be performed to evaluate the ability of the model to predict the initiation of damage and its growth through the finite element mesh under a variety of conditions. Mabson et al. proposed a test case of a unidirectional, fiber-reinforced plate with a center crack subjected to tensile loads to evaluate matrix crack propagation predictions. The problem was modeled using the Abaqus Hashin continuum damage mechanics (CDM) model for fiber-reinforced composites. Different combinations of matrix strengths and element sizes were used in the simulations, and the results were compared to a closed-form solution based on linear elastic fracture mechanics (LEFM). It was determined that the Abaqus CDM model could predict the LEFM solution of Mode I cracks only when the finite element mesh density met specific requirements based on the material properties. This paper presents closed-form LEFM solutions for a center notch mixed mode (CNMM) verification problem. Parametric finite element analyses were developed using progressive damage analysis methods of both the Discrete Damage Mechanics (DDM) and CDM classes. The progressive damage analysis methods applied in the analyses of the CNMM problem include CompDam and the Floating Node Method. Analyses were conducted with various mode mixities and element sizes to verify that the damage models were working as intended and to identify any limits of applicability.

Leone, Frank↗
NASA NTRS1982

Quantiles, parametric-select density estimation, and bi-information parameter estimators

A quantile-based approach to statistical analysis and probability modeling of data is presented which formulates statistical inference problems as functional inference problems in which the parameters to be estimated are density functions. Density estimators can be non-parametric (computed independently of model identified) or parametric-select (approximated by finite parametric models that can provide standard models whose fit can be tested). Exponential models and autoregressive models are approximating densities which can be justified as maximum entropy for respectively the entropy of a probability density and the entropy of a quantile density. Applications of these ideas are outlined to the problems of modeling: (1) univariate data; (2) bivariate data and tests for independence; and (3) two samples and likelihood ratios. It is proposed that bi-information estimation of a density function can be developed by analogy to the problem of identification of regression models.

Parzen, E.↗
NASA NTRS1953

An analysis of turbojet-engine-inlet matching

A method of presenting turbojet-engine air-flow requirements and inlet-system air-flow capacities in identical though independent parametric terms is developed. The application of the air-flow representation technique to the analysis of engine-inlet matching conditions is demonstrated. Several examples are presented to illustrate the application of the method to the explicit determination of inlet geometric variations required to improve the power-plant performance of supersonic airplanes.

Wyatt, Demarquis↗
NASA NTRSDate not supplied

An Initial Electric Motor Rotor Vibration Model

Ongoing integration of outrunner brushless electric motors into drones and Advanced Air Mobility aircraft presents a need for accurate acoustic predictions derived from prediction of the motor rotor vibrations. In outrunner motors, the external rotor vibrates and drives the acoustic field. At resonant frequencies of the rotor, the rotor displacements will be the largest. The vibrations can lead to acoustic tones that are relevant to the overall acoustic design of these types of vehicles. This study performs a finite element analysis to assess the modes in two electric motor rotors. This model is then refined into a simple parameterized geometry that can make the same predictions for motors of the same class. A parametric sweep and least-squares-curve fit to the finite element analysis data results in a series of simple curves that can predict the mode shapes and frequencies that are likely to appear in this class of motors without the need for any simulation. The simulations are validated by comparison to acoustic and experimental modal-analysis data.

Electric Motor Noise↗
NASA NTRSDate not supplied

An Initial Electric Motor Rotor Vibration Model

Ongoing integration of outrunner brushless electric motors into drones and Advanced Air Mobility aircraft presents a need for accurate acoustic predictions derived from prediction of the motor rotor vibrations. In outrunner motors, the external rotor vibrates and drives the acoustic field. At resonant frequencies of the rotor, the rotor displacements will be the largest. The vibrations can lead to acoustic tones that are relevant to the overall acoustic design of these types of vehicles. This study performs a finite element analysis to assess the modes in two electric motor rotors. This model is then refined into a simple parameterized geometry that can make the same predictions for motors of the same class. A parametric sweep and least-squares-curve fit to the finite element analysis data results in a series of simple curves that can predict the mode shapes and frequencies that are likely to appear in this class of motors without the need for any simulation. The simulations are validated by comparison to acoustic and experimental modal-analysis data.

Electric Motor Noise↗
DOE OSTI2024

3D high-fidelity automated neutronics guided optimization of fusion blanket designs

The compact Fusion Pilot Plant (FPP) is defined in the recent National Academies of Sciences, Engineering, and Medicine report as the next step of fusion energy demonstration with a $50$ MWe peak net electricity production, $Q_e$ greater than $1$, and at least $3$ hours of continuous operation. This fusion pilot plant will be a test bed enabling materials, designs, and fuel management assessment, and it will represent an engineering challenge because of its high-fusion power and compact design targets. Previous reactor data is limited to experiments operating in different design space ranges. Therefore, design iterations and assessments should rely on high-fidelity first-principle theoretical and computational models. The high-fidelity integrated modeling of the plasma is a fundamental part of fusion energy research. However, the whole device modeling is often neglected, utilizing low-fidelity, system-level analysis. Recently, the need for high-fidelity multi-physics modeling was recognized, resulting in a selection of integrated tools. Further, autonomous design optimization requires a streamlined framework that perturbs the design point, reruns the analysis, and examines the outputs. However, high-fidelity analysis requires complex geometry specification that is difficult to perturb. This work presents the parametric CAD generation tool TRACER and a new neutronic workflow. TRACER allows the perturbation of the geometry representation, creating geometry files ready for further analysis. The streamlined neutronic workflow allows efficient and accurate calculations. The two new tools coupled together were used to perform a 3D high-fidelity multi-objective, multi-input optimization of an "ARC Class" compact tokamak design. The workflow was driven by an optimization driver for full automation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
NASA NTRS1985

Optical analysis of parabolic dish concentrators for solar dynamic power systems in space

An optical analysis of a parabolic solar collection system operating in Earth orbit was performed using ray tracing techniques. The analysis included the effects of: (1) solar limb darkening, (2) parametric variation of mirror surface error, (3) parametric variation of mirror rim angle, and (4) parametric variation of alignment and pointing error. This ray tracing technique used numerical integration to combine the effects of rays emanating from different parts of the sun at different intensities with the effects of normally distributed mirror-surface errors to compute the angular intensity distribution of rays leaving the mirror surface. A second numerical integration was then performed over the surface of the parabolic mirror to compute the radial distribution of brightness at the mirror focus. Major results of the analysis included: (1) solar energy can be collected at high temperatures with high efficiency, (2) higher absorber temperatures can be achieved at lower efficiencies, or higher efficiencies can be achieved at lower temperatures, and (3) collection efficiency is near its maximum level across a broad plateau of rim angles from 40 deg to 70 deg.

Jefferies, K. S.↗
DOE OSTI2020

Non-Gaussianity in the weak lensing correlation function likelihood – implications for cosmological parameter biases

ABSTRACT We study the significance of non-Gaussianity in the likelihood of weak lensing shear two-point correlation functions, detecting significantly non-zero skewness and kurtosis in 1D marginal distributions of shear two-point correlation functions in simulated weak lensing data. We examine the implications in the context of future surveys, in particular LSST, with derivations of how the non-Gaussianity scales with survey area. We show that there is no significant bias in 1D posteriors of Ωm and σ8 due to the non-Gaussian likelihood distributions of shear correlations functions using the mock data (100 deg2). We also present a systematic approach to constructing approximate multivariate likelihoods with 1D parametric functions by assuming independence or more flexible non-parametric multivariate methods after decorrelating the data points using principal component analysis (PCA). While the use of PCA does not modify the non-Gaussianity of the multivariate likelihood, we find empirically that the 1D marginal sampling distributions of the PCA components exhibit less skewness and kurtosis than the original shear correlation functions. Modelling the likelihood with marginal parametric functions based on the assumption of independence between PCA components thus gives a lower limit for the biases. We further demonstrate that the difference in cosmological parameter constraints between the multivariate Gaussian likelihood model and more complex non-Gaussian likelihood models would be even smaller for an LSST-like survey. In addition, the PCA approach automatically serves as a data compression method, enabling the retention of the majority of the cosmological information while reducing the dimensionality of the data vector by a factor of ∼5.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

A multi‐variable framework for selecting WRF physics configurations at convection‐permitting scales: An Amazon wet‐season case study

Tropical convection over rainforests modulates atmospheric circulation and the energy and hydrological cycles across multiple scales. However, the scarcity of observations still limits our understanding of these processes. Although numerical models are utilized to investigate atmospheric physical processes, their performance depends on the choice of parameterizations and grid resolution. Here, in this work, we introduce and apply a multi‐variable, multi‐physics framework to evaluate and rank the Advanced Research Weather Research and Forecasting (WRF–ARW) configurations at 1‐km resolution over the central Amazon during the wet season. A 48‐member ensemble combines three land‐surface models (LSMs), four planetary boundary layer (PBL), and four microphysics (MP) schemes. Model performance for seven convection‐related near‐surface and boundary‐layer variables is assessed using Taylor diagrams and the Taylor skill score (TSS), analysis of variance (ANOVA)‐based sensitivity metrics, and non‐parametric rank tests. We then construct a combined, weighted TSS to identify configurations that are comparatively robust across variables. Results showed that most configurations reproduce near‐surface temperature, sensible and latent heat fluxes, and boundary‐layer height reasonably well, whereas humidity and rainfall remain challenging. LSM choice has the strongest impact on the surface fluxes and a secondary influence on near‐surface temperature and humidity, PBL schemes dominate boundary‐layer height, and MP schemes exert the largest control on rainfall. No single configuration is optimal for all variables, but the combination of Noah (LSM), Yonsei University (PBL), and Morrison (MP) emerges as the most robust configuration for this case, with the WRF single‐moment six‐class scheme (WSM6) providing a competitive, computationally cheaper MP alternative. The framework is general and can be applied to other regions, seasons, and convective regimes.

Amazon rainforest↗
DOE OSTI2020

Nonlinear Spectroscopy of Collective Modes in an Excitonic Insulator

The nonlinear optical response of an excitonic insulator coupled to lattice degrees of freedom is shown to depend in strong and characteristic ways on whether the insulating behavior originates primarily from electron-electron or electron-lattice interactions. Linear response optical signatures of the massive phase mode and the amplitude (Higgs) mode are identified. Upon nonlinear excitation resonant to the phase mode, a new in-gap mode at twice the phase mode frequency is induced, leading to a huge second harmonic response. Excitation of in-gap phonon modes leads to different and much smaller effects. A Landau-Ginzburg theory analysis explains these different behaviors and reveals that a parametric resonance of the strongly excited phase mode is the origin of the photoinduced mode in the electron-dominant case. Here, the difference in the nonlinear optical response serves as a measure of the dominant mechanism of the ordered phase.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1976

Technical feasibility of a modular dish solar electric system

The paper presents the technical feasibility of generating electricity by using a gas turbine in conjunction with a paraboloid of revolution (dish) solar concentrator. A conceptual design of a dish concentrator is obtained by parametrically examining the significant optical parameters. The optical performance analysis was conducted using a Monte Carlo ray-trace simulation program. The performance of four candidate thermodynamic cycles utilizing two working fluids was analyzed; the cycles were the regenerative and nonregenerative Brayton cycles of both open and closed type. Air and helium were the working fluids for the open and closed type respectively. Heat transfer from the solar radiation to the gas flowing in metal tubes at the receiver was also analyzed. A paraboloid of revolution dish with a cavity receiver using an open air regenerative Brayton cycle turbine emerged as a technically feasible concept in the power range from 30 to 100 KWth per module.

Gupta, B. P.↗