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At least 109 records · Page 6

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NASA NTRS2014

Dissertation Defense Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This paper describes an approach to quantify the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft without the use of test data. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional "validation by test only" mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions. Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computational Fluid Dynamics can be used to verify these requirements; however, the model must be validated by test data. This research includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available and open source solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT, STARCCM+, and OPENFOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid Dynamics model using the methodology found in "Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations". This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions. The method accounts for all uncertainty terms from both numerical and input variables. Objective three is to compile a table of uncertainty parameters that could be used to estimate the error in a Computational Fluid Dynamics model of the Environmental Control System /spacecraft system. Previous studies have looked at the uncertainty in a Computational Fluid Dynamics model for a single output variable at a single point, for example the re-attachment length of a backward facing step. For the flow regime being analyzed (turbulent, three-dimensional, incompressible), the error at a single point can propagate into the solution both via flow physics and numerical methods. Calculating the uncertainty in using Computational Fluid Dynamics to accurately predict airflow speeds around encapsulated spacecraft in is imperative to the success of future missions.

CFD↗

NASA NTRS2014

Dissertation Defense: Computational Fluid Dynamics Uncertainty Analysis for Payload Fairing Spacecraft Environmental Control Systems

Spacecraft thermal protection systems are at risk of being damaged due to airflow produced from Environmental Control Systems. There are inherent uncertainties and errors associated with using Computational Fluid Dynamics to predict the airflow field around a spacecraft from the Environmental Control System. This paper describes an approach to quantify the uncertainty in using Computational Fluid Dynamics to predict airflow speeds around an encapsulated spacecraft without the use of test data. Quantifying the uncertainty in analytical predictions is imperative to the success of any simulation-based product. The method could provide an alternative to traditional validation by test only mentality. This method could be extended to other disciplines and has potential to provide uncertainty for any numerical simulation, thus lowering the cost of performing these verifications while increasing the confidence in those predictions.Spacecraft requirements can include a maximum airflow speed to protect delicate instruments during ground processing. Computational Fluid Dynamics can be used to verify these requirements; however, the model must be validated by test data. This research includes the following three objectives and methods. Objective one is develop, model, and perform a Computational Fluid Dynamics analysis of three (3) generic, non-proprietary, environmental control systems and spacecraft configurations. Several commercially available and open source solvers have the capability to model the turbulent, highly three-dimensional, incompressible flow regime. The proposed method uses FLUENT, STARCCM+, and OPENFOAM. Objective two is to perform an uncertainty analysis of the Computational Fluid Dynamics model using the methodology found in Comprehensive Approach to Verification and Validation of Computational Fluid Dynamics Simulations. This method requires three separate grids and solutions, which quantify the error bars around Computational Fluid Dynamics predictions. The method accounts for all uncertainty terms from both numerical and input variables. Objective three is to compile a table of uncertainty parameters that could be used to estimate the error in a Computational Fluid Dynamics model of the Environmental Control System spacecraft system.Previous studies have looked at the uncertainty in a Computational Fluid Dynamics model for a single output variable at a single point, for example the re-attachment length of a backward facing step. For the flow regime being analyzed (turbulent, three-dimensional, incompressible), the error at a single point can propagate into the solution both via flow physics and numerical methods. Calculating the uncertainty in using Computational Fluid Dynamics to accurately predict airflow speeds around encapsulated spacecraft in is imperative to the success of future missions.

Fluid Dynamics↗

NASA NTRS2014

Validation of the 5th and 95th Percentile Hybrid III Anthropomorphic Test Device Finite Element Model

NASA spacecraft design requirements for occupant protection are a combination of the Brinkley criteria and injury metrics extracted from anthropomorphic test devices (ATD's). For the ATD injury metrics, the requirements specify the use of the 5th percentile female Hybrid III and the 95th percentile male Hybrid III. Furthermore, each of these ATD's is required to be fitted with an articulating pelvis and a straight spine. The articulating pelvis is necessary for the ATD to fit into spacecraft seats, while the straight spine is required as injury metrics for vertical accelerations are better defined for this configuration. The requirements require that physical testing be performed with both ATD's to demonstrate compliance. Before compliance testing can be conducted, extensive modeling and simulation are required to determine appropriate test conditions, simulate conditions not feasible for testing, and assess design features to better ensure compliance testing is successful. While finite element (FE) models are currently available for many of the physical ATD's, currently there are no complete models for either the 5th percentile female or the 95th percentile male Hybrid III with a straight spine and articulating pelvis. The purpose of this work is to assess the accuracy of the existing Livermore Software Technology Corporation's FE models of the 5th and 95th percentile ATD's. To perform this assessment, a series of tests will be performed at Wright Patterson Air Force Research Lab using their horizontal impact accelerator sled test facility. The ATD's will be placed in the Orion seat with a modified-advanced-crew-escape-system (MACES) pressure suit and helmet, and driven with loadings similar to what is expected for the actual Orion vehicle during landing, launch abort, and chute deployment. Test data will be compared to analytical predictions and modelling uncertainty factors will be determined for each injury metric. Additionally, the test data will be used to further improve the FE model, particularly in the areas of the ATD neck components, harness, and suit and helmet effects.

Lawrence, C.↗

NASA NTRS1974

Developing a gas rocket performance prediction technique

A simple, semi-empirical performance correlation/prediction technique applicable to gaseous and liquid propellant rocket engines is presented. Excellent correlations were attained for over 100 test firings by adjusting the computation of the gaseous mixing of an unreactive, coaxial jet using a correlation factor, F, which resulted in prediction of the experimental combustion efficiency for each firing. Static pressure, mean velocity and turbulence intensity in the developing region of non-reactive coaxial jets, typical of those of coaxial injector elements were determined. Detailed profiles were obtained at twelve axial locations (extending from the nozzle exit for a distance of five diameters) downstream from a single element of the Bell Aerospace H2/O2 19-element coaxial injector. These data are compared with analytical predictions made using both eddy viscosity and turbulence kinetic energy mixing models and available computer codes. Comparisons were disappointing, demonstrating the necessity of developing improved turbulence models and computational techniques before detailed predictions of practical coaxial free jet flows are attempted.

Morgenthaler, J. H.↗

NASA NTRS2003

Material Damping Experiments at Cryogenic Temperatures

A unique experimental facility has been designed to measure damping of materials at cryogenic temperatures. The test facility pays special attention to removing other sources of damping in the measurement by avoiding frictional interfaces, decoupling the test specimen from the support system, and by using a non-contacting measurement device; Damping data is obtained for materials (AI, GrEp, Be, Fused Quartz), strain amplitudes (less than 10-6 ppm), frequencies (20Hz-330Hz) and temperatures (20K-293K) relevant to future precision optical space missions. The test data shows a significant decrease in viscous damping at cryogenic temperatures and can be as low as 10-4%, but the amount of the damping decrease is a function of frequency and material. Contrary to the other materials whose damping monotonically decreased with temperature, damping of Fused Quartz increased substantially at cryo, after reaching a minimum at around l50 K. The damping is also shown to be insensitive to strain for low strain levels. At room temperatures, the test data correlates well to the analytical predictions of the Zener damping model. Discrepancies at cryogenic temperatures between the model predictions and the test data are observed.

cryogenic↗

NASA NTRS1984

Shuttle payload bay dynamic environments: Summary and conclusion report for STS flights 1-5 and 9

The vibration, acoustic and low frequency loads data from the first 5 shuttle flights are presented. The engineering analysis of that data is also presented. Vibroacoustic data from STS-9 are also presented because they represent the only data taken on a large payload. Payload dynamic environment predictions developed by the participation of various NASA and industrial centers are presented along with a comparison of analytical loads methodology predictions with flight data, including a brief description of the methodologies employed in developing those predictions for payloads. The review of prediction methodologies illustrates how different centers have approached the problems of developing shuttle dynamic environmental predictions and criteria. Ongoing research activities related to the shuttle dynamic environments are also described. Analytical software recently developed for the prediction of payload acoustic and vibration environments are also described.

Oconnell, M.↗

NASA NTRS2001

In-Flight Characterization of the Electromagnetic Environment Inside an Airliner

In 1995, the NASA Langley Research Center conducted a series of experimental measurements that characterized the electromagnetic environment (EME) inside a Boeing 757 airliner while in flight, Measurements were made of the electromagnetic energy coupled into a commercially configured aircraft as it was flown in close proximity to ground-based radio frequency (RF) transmitters operating at approximately 26, 173. and 430 MHz. The goal of this experiment was to collect data for the verification of analytical predictions of the internal aircraft response to an external stimulus. This paper describes the experiment, presents the data collected by it, and discusses techniques used to compute both the magnitude of the electric field illuminating the aircraft and its direction of propagation relative to a coordinate system fixed to the aircraft. The latter is determined from Global Positioning System (GPS) and aircraft Inertial Reference Unit (IRU) data. The paper concludes with an examination of the shielding effectiveness of the test aircraft. as determined by comparison of' the measured internal EME and computed external EME.

Moeller, Karl J.↗

NASA NTRS2020

Machine Learning-Based Predictive Analytics for Aircraft Engine Conceptual Design

Big data and artificial intelligence/machine learning are transforming the global business environment. Data is now the most valuable asset for enterprises in every industry. Companies are using data-driven insights for competitive advantage. With that, the adoption of machine learning-based data analytics is rapidly taking hold across various industries, producing autonomous systems that support human decision-making. This work explored the application of machine learning to aircraft engine conceptual design. Supervised machine-learning algorithms for regression and classification were employed to study patterns in an existing, open-source database of production and research turbofan engines, and resulting in predictive analytics for use in predicting performance of new turbofan designs. Specifically, the author developed machine learning-based analytics to predict cruise thrust specific fuel consumption (TSFC) and core sizes of high-efficiency turbofan engines, using engine design parameters as the input. The predictive analytics were trained and deployed in Keras, an open-source neural networks application program interface (API) written in Python, with Google’s TensorFlow (an open source library for numerical computation) serving as the backend engine. The promising results of the predictive analytics show that machine-learning techniques merit further exploration for application in aircraft engine conceptual design.

deep-learning↗

NASA NTRS1986

High temperature stress-strain analysis

The objectives of the high-temperature structures program are threefold: to assist in the development of analytical tools needed to improve design analyses and procedures for the efficient and accurate prediction of the nonlinear structural response of hot-section components; to aid in the calibration, validation, and evaluation of the analytical tools by comparing predictions with experimental data; and to evaluate existing as well as advanced temperature and strain measurement instrumentation. As the analytical tools, test methods, tests, instrumentations, as well as data acquisition, management, and analysis methods are developed and evaluated, a proven, integrated analysis and experiment method will result in a more accurate prediction of the cyclic life of hot section components.

Thompson, Robert L.↗

DOE OSTI2023

Measurement of the angle between jet axes in pp collisions at $ \sqrt{s}$ = 5.02 TeV

This article reports measurements of the angle between differently defined jet axes in pp collisions at $\sqrt{s}$ = 5.02 TeV carried out by the ALICE Collaboration. Charged particles at midrapidity are clustered into jets with resolution parameters R = 0.2 and 0.4. The jet axis, before and after Soft Drop grooming, is compared to the jet axis from the Winner-Takes-All (WTA) recombination scheme. The angle between these axes, ΔR axis , probes a wide phase space of the jet formation and evolution, ranging from the initial high-momentum-transfer scattering to the hadronization process. The ΔR axis observable is presented for 20 < $p^{ch jet}_{T}$ < 100 GeV/c, and compared to predictions from the PYTHIA 8 and Herwig 7 event generators. The distributions can also be calculated analytically with a leading hadronization correction related to the non-perturbative component of the Collins-Soper-Sterman (CSS) evolution kernel. Comparisons to analytical predictions at next-to-leading-logarithmic accuracy with leading hadronization correction implemented from experimental extractions of the CSS kernel in Drell-Yan measurements are presented. The analytical predictions describe the measured data within 20% in the perturbative regime, with surprising agreement in the non-perturbative regime as well. These results are compatible with the universality of the CSS kernel in the context of jet substructure.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

SPH modeling of biomass granular flow: Theoretical implementation and experimental validation

The commercialization of biomass-derived energy is impeded by flowability challenges arising from the feeding and handling of granular biomass materials in full-scale biorefineries. To overcome these obstacles, a robust and accurate model to simulate the flow of granular biomass is indispensable. However, conventional mesh-based numerical codes are limited by inherent mesh distortion in simulating large deformation that commonly occurs in granular biomass handling. Here, in this study, we propose a graphics processing unit (GPU)-accelerated meshless Smoothed Particle Hydrodynamics (SPH) code to model the flow of granular biomass materials. A modified void ratio-based mass conversation, a hybrid particle-to-particle/surface frictional boundary treatment, and a hypoplastic constitutive model are implemented. Four numerical examples, an elastic block sliding on inclined planes, sand column collapse, Angle of Repose, and axial compression tests for pine chips, were simulated using the developed SPH code. The results demonstrate good agreement between numerical predictions and analytical and experimental data for all four examples, validating the SPH code and increasing confidence that it can be applied to simulate more complex granular biomass handling processes, such as hopper feeding or auger conveyance.

09 BIOMASS FUELS↗

DOE OSTI2023

Dimensionally reduced machine learning model for predicting single component octanol–water partition coefficients

Abstract MF-LOGP, a new method for determining a single component octanol–water partition coefficients ( $$LogP$$ LogP ) is presented which uses molecular formula as the only input. Octanol–water partition coefficients are useful in many applications, ranging from environmental fate and drug delivery. Currently, partition coefficients are either experimentally measured or predicted as a function of structural fragments, topological descriptors, or thermodynamic properties known or calculated from precise molecular structures. The MF-LOGP method presented here differs from classical methods as it does not require any structural information and uses molecular formula as the sole model input. MF-LOGP is therefore useful for situations in which the structure is unknown or where the use of a low dimensional, easily automatable, and computationally inexpensive calculations is required. MF-LOGP is a random forest algorithm that is trained and tested on 15,377 data points, using 10 features derived from the molecular formula to make $$LogP$$ LogP predictions. Using an independent validation set of 2713 data points, MF-LOGP was found to have an average $$RMSE$$ RMSE = 0.77 ± 0.007, $$MAE$$ MAE = 0.52 ± 0.003, and $${R}^{2}$$ R 2 = 0.83 ± 0.003. This performance fell within the spectrum of performances reported in the published literature for conventional higher dimensional models ( $$RMSE$$ RMSE = 0.42–1.54, $$MAE$$ MAE = 0.09–1.07, and $${R}^{2}$$ R 2 = 0.32–0.95). Compared with existing models, MF-LOGP requires a maximum of ten features and no structural information, thereby providing a practical and yet predictive tool. The development of MF-LOGP provides the groundwork for development of more physical prediction models leveraging big data analytical methods or complex multicomponent mixtures. Graphical Abstract

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Attack Surface Analysis of the Digital Twins interface with Advanced Sensor and Instrumentation Interfaces: Cyber Threat Assessment and Attack Demonstration for Digital Twins in Advanced Reactor Architectures

A digital twin is a virtual representation of a physical system or object using real-time data that can predict and analyze how the system or object performs. This relatively new technology can be applied to the field of nuclear power generation, to aid in the design and development of new nuclear power plants and reduce operation costs using predictive maintenance and other data analytical methods. While there are already companies utilizing simulation software to train operators and technicians in the nuclear industry, some are now transitioning to utilizing their existing technology, software, and methods to develop digital twin solutions for the next generation of nuclear power plants, offering their services to utilities and government organizations around the world.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2024

Novel Hot Gas Components for Gas Turbine Engines Enabled by Materials and Additive Manufacturing Process Development

Additive Manufacturing (AM), also known as 3D printing, has emerged as a manufacturing method that enables new design freedom for gas turbine engine manufacturers. However, the material selection for AM processable high-temperature super alloys is currently limited. Additionally, the heat transfer performance of AM enabled micro-cooling architectures is not yet well understood. Accordingly, in support of advanced manufacturing and engine performance development, Oak Ridge National Laboratory (ORNL)and Solar Turbines (Solar) conducted a multidisciplinary project to generate both AM super alloy material properties data and micro-channel performance data for two AM super alloys. The data supported the design and analysis of an internally cooled turbine hot section AM tip shoe component. This data was used to analytically predict the reduction in operating temperature of a gas turbine tip shoe. The work concluded that the cooling flow required to cool the tip shoe can be tuned to suit the efficiency improvements desired in an industrial gas turbine.

36 MATERIALS SCIENCE↗

NASA NTRS1966

Proceedings of the First Aerospace Mechanisms Symposium

To provide a better opportunity, therefore, for the aerospace mechanisms designer to compare and correlate the specific knowledge gained from a wide variety of important mechanism design efforts, the First Aerospace Mechanisms Symposium was held on 19-20 May 1966. This Symposium, dealing exclusively with aerospace mechanism design and development, was sponsored by the Jet Propulsion Laboratory of the California Institute of Technology, Lockheed Missiles & Space Company, and the University of Santa Clara. The first aerospace symposium with such broad sponsorship, is supplied the first forum for an extensive discussion in depth of ideas, problems, and accomplishments regarding aerospace mechanisms. It stressed the practical aspects, with emphasis on actual flight test data and correlation with analytical predictions. This volume presents the papers offered at the Symposium in order to provide the aerospace mechanisms designer with a useful source of ideas and information and to serve as a stimulant to the continuance of a periodic professional interchange in the field of aerospace mechanisms.

Conference↗

NASA NTRS1972

Applications of optical holography to applied mechanics.

This paper provides a brief summary of applications of optical holography and holographic interferometry to applied solid mechanics. Basic equations commonly used in fringe interpretation are described and used to reduce the data contained on holographic interferograms. A comparison of data obtained holographically with analytical prediction is given wherever possible. Applications contained herein include front surface physics, study of bomb breakup, transverse wave propagation, study of mode shapes of panels at elevated temperatures, nondestructive testing, and vibration analysis.

Aprahamian, R.↗

NASA NTRS1976

Purging of multilayer insulation by gas diffusion

An experimental investigation was conducted to determine the time required to purge a multilayer insulation (MLI) panel with gaseous helium by means of gas diffusion to obtain a condensable (nitrogen) gas concentration of less than 1 percent within the panel. Two flat, rectangular MLI panel configurations, one incorporating a butt joint, were tested. The insulation panels consisted of 15 double-aluminized Mylar radiation shields separated by double silk net spacers. The test results indicated that the rate which the condensable gas concentration at the edge or at the butt joint of an MLI panel was reduced was a significant factor in the total time required to reduce the condensable gas concentration within the panel to less than 1 percent. The experimental data agreed well with analytical predictions made by using a simple, one-dimensional gas diffusion model in which the boundary conditions at the edge of the MLI panel were time dependent.

Sumner, I. E.↗

NASA NTRS1976

Pressure and velocity in a developing coaxial jet

Determinations of static pressure, mean velocity and turbulence intensity in the developing region of coaxial jets are presented. Detailed profiles were obtained at twelve axial locations (extending from the nozzle exit for a distance of 5 diameters) downstream from a single element of the Bell Aerospace H2/O2 19-element coaxial injector. Measurements of mass-flux per unit area (using a constant temperature anemometer), total pressure and local temperature were used in the determination of local static pressure and velocity. These data show a low pressure region exists near the nozzle exit. Although this pressure reduction is small (0.34 psi), it substantially altered the flow development. Comparison of results shows that velocity near the nozzle exit decreases initially (no central velocity core) as a result of both pressure gradients and viscous mixing. These data are compared with analytical predictions made using available computer codes. Results show the need to consider pressure effects in any proposed mathematical model.

Moon, L. F.↗