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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 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Development of a Solid-Oxide Fuel Cell/Gas Turbine Hybrid System Model for Aerospace Applications

Recent interest in fuel cell-gas turbine hybrid applications for the aerospace industry has led to the need for accurate computer simulation models to aid in system design and performance evaluation. To meet this requirement, solid oxide fuel cell (SOFC) and fuel processor models have been developed and incorporated into the Numerical Propulsion Systems Simulation (NPSS) software package. The SOFC and reformer models solve systems of equations governing steady-state performance using common theoretical and semi-empirical terms. An example hybrid configuration is presented that demonstrates the new capability as well as the interaction with pre-existing gas turbine and heat exchanger models. Finally, a comparison of calculated SOFC performance with experimental data is presented to demonstrate model validity. Keywords: Solid Oxide Fuel Cell, Reformer, System Model, Aerospace, Hybrid System, NPSS

Freeh, Joshua E.↗
NASA NTRS2008

Heating Augmentation for Short Hypersonic Protuberances

Computational aeroheating analyses of the Space Shuttle Orbiter plug repair models are validated against data collected in the Calspan University of Buffalo Research Center (CUBRC) 48 inch shock tunnel. The comparison shows that the average difference between computed heat transfer results and the data is about 9.5%. Using CFD and Wind Tunnel (WT) data, an empirical correlation for estimating heating augmentation on short hypersonic protuberances (k/delta less than 0.3) is proposed. This proposed correlation is compared with several computed flight simulation cases and good agreement is achieved. Accordingly, this correlation is proposed for further investigation on other short hypersonic protuberances for estimating heating augmentation.

Mazaheri, Ali R.↗
DOE OSTI2022

BISON Validation to In-Situ Cladding Burst Test and High Burnup LOCA Experiments

The process to develop and qualify nuclear fuels for commercial nuclear application requires fundamental material development, characterization, and design; out-of-pile testing on unirradiated materials; integral fuel rod irradiations, testing, and post irradiation examinations (PIEs); and transient analyses. The historical approach depends on the generation of large empirical datasets and series of integral fuel rod irradiations, and this approach ultimately takes approximately 20 years—or sometimes longer—to acquire data through extensive sequential testing. Thus, the qualification and eventual deployment of new fuel systems constitute a long and drawn-out process. However, recent technological advancements have provided researchers the opportunity to perform out-of-cell, in-situ measurements to assess material performance for the duration of the experiment. One such example of this capability is the use of digital image coordination and thermal imaging to assess Zircaloy cladding performance under a simulated loss-of-coolant accident (LOCA) transient condition. In general, the in-situ measurements provide high-fidelity strain, strain rates, and temperature surface maps. This is critical for the United States nuclear industry, which is actively developing a technical basis to support extending the peak rod average burnup from 62 to ~75 GWd/tU and the deployment of accident-tolerant fuel. However, the Nuclear Regulatory Commission, through their research information letter, outlined a number of technical issues for the industry to address before extending burnup. One topic of specific interest is understanding the cladding balloon and rupture geometry during the LOCA heatup phase. Leveraging these advanced in-situ capabilities, this work intends to use insitu data generated from a simulated LOCA in the Severe Accident Test Station at Oak Ridge National Laboratory to better understand high-temperature creep and its impact on Zircaloy balloon and rupture performance. This work used the BISON fuel performance code to compare BISON’s high-temperature creep model predictions to in-situ data and identify limitations and gaps within the model. Additionally, BISON will subsequently be used to simulate relevant high-burnup LOCA tests. The results will be analyzed and compared to the available post-test data in a manner consistent with the approach outlined in the Nuclear Regulatory Commission research information letter.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1993

LOX/hydrocarbon rocket engine analytical design methodology development and validation. Volume 1: Executive summary and technical narrative

During the past three decades, an enormous amount of resources were expended in the design and development of Liquid Oxygen/Hydrocarbon and Hydrogen (LOX/HC and LOX/H2) rocket engines. A significant portion of these resources were used to develop and demonstrate the performance and combustion stability for each new engine. During these efforts, many analytical and empirical models were developed that characterize design parameters and combustion processes that influence performance and stability. Many of these models are suitable as design tools, but they have not been assembled into an industry-wide usable analytical design methodology. The objective of this program was to assemble existing performance and combustion stability models into a usable methodology capable of producing high performing and stable LOX/hydrocarbon and LOX/hydrogen propellant booster engines.

Pieper, Jerry L.↗
DOE OSTI2026

Time-Domain Vortex Induced Vibration Modeling of Reference Dynamic Power Cable for the Gulf of Maine

Vortex-induced vibration (VIV) is a phenomenon known to decrease the fatigue life of dynamic power cables used in floating offshore wind systems through increased bending loading cycles. A variety of modeling solutions have been proposed to study this, but none enable fully-coupled simulations leveraging open-source tools. To address this, a time-domain VIV model has been successfully implemented into the open-source mooring dynamics model MoorDyn. The semi-empirical VIV model describes a lift force acting on segments of a flexible cylinder, making it well suited for implementation into MoorDyn. The new capability successfully predicted the frequencies and magnitudes of strain in both steady and oscillating flows when compared to the original validation results and matched peak spectral response when compared to experimental results, verifying successful implementation. MoorDyn with VIV was then leveraged to simulate a 15 MW floating turbine with a dynamic power cable in the Gulf of Maine using OpenFAST for six return periods of combined wind, wave, and current conditions. Increased curvature and tension fluctuations in higher flow speeds were observed when simulating VIV. Maximum tensions and curvatures also increased, with the 500 year conditions violating the curvature factor of safety of 2.0. These results highlight the importance of considering VIV when designing dynamic power cables for the Gulf of Maine, and indicate that cost effective mitigation strategies should be explored for the area. They also demonstrate the utility of this new modeling capability, which provides the first open-source tool for fully coupled time-domain floating offshore wind simulations with dynamic power cable VIV.

17 WIND ENERGY↗
DOE OSTI2025

Predicting cutoff L-shells of solar protons using the GPPSn particle dataset

Solar energetic protons (SEPs) arriving at the Earth trigger severe radiation storms in the near-Earth space, directly impacting space missions operating at various altitudes. Therefore, monitoring SEP events and predicting the penetration depths of solar protons are critical for aerospace sectors. Building on previous efforts, here we demonstrate the feasibility of using proton measurements from the Global Prompt Proton Sensor network (GPPSn), enabled by Los Alamos National Laboratory developed combined X-ray dosimeters aboard GPS satellites, to characterize and predict the penetration of solar protons into the geomagnetic field. The inclined medium-Earth-orbits (MEOs) of the global GPS constellation offer a unique advantage of allowing simultaneous measurements of penetrating solar protons inside both open- and closed-field line regions. Therefore, the L-profiles of ∼10s–100 MeV solar protons and their associated cutoff L-shells can be determined from the GPPSn dataset, using predefined threshold proton flux values rather than traditional flux ratios. After examining a list of SEP event intervals across solar cycles 23, 24 and 25—including the 2024 Mother’s Day superstorm, we showcase how the latest GPPSn proton dataset (release v1.10), reprocessed and calibrated, can not only be used to monitor solar proton distributions inside the dynamic geomagnetic field for individual events, but also to derive a new empirical model linking cutoff L-shells with several key space weather parameters. This newly developed SEPCL-MEO model demonstrates high predictive performance; for example, predictions for > 30 MeV solar protons yield a correlation coefficient of 0.85 and performance efficiency of 0.67 when validated against GPPSn observations. Results from this pilot study underscores the scientific and operational value of the GPPSn dataset, and this dataset—when paired with machine-learning techniques—can play a critical role in observing and predicting the effects of future incoming SEP events, including extreme ones.

58 GEOSCIENCES↗
NASA NTRS2008

Heating Augmentation for Short Hypersonic Protuberances

Computational aeroheating analyses of the Space Shuttle Orbiter plug repair models are validated against data collected in the Calspan University of Buffalo Research Center (CUBRC) 48 inch shock tunnel. The comparison shows that the average difference between computed heat transfer results and the data is about 9:5%. Using CFD and Wind Tunnel (WT) data, an empirical correlation for estimating heating augmentation on short hyper- sonic protuberances (k/delta < 0.33) is proposed. This proposed correlation is compared with several computed flight simulation cases and good agreement is achieved. Accordingly, this correlation is proposed for further investigation on other short hypersonic protuberances for estimating heating augmentation.

Mazaheri, Alireza R.↗
NASA NTRS2015

Superboom Caustic Analysis and Measurement Program (SCAMP) Final Report

The objectives of the Superboom Caustic Analysis and Measurement (SCAMP) Program were to develop and validate, via flight-test measurements, analytical models for sonic boom signatures in and around focal zones as they are expected to occur during commercial aircraft transition from subsonic to supersonic flight, and to apply these models to focus boom prediction of low-boom aircraft designs. The SCAMP program has successfully investigated sonic boom focusing both analytically and experimentally, while gathering a comprehensive empirical flight test and acoustic dataset, and developing a suite of focused sonic boom prediction tools. An experimental flight and acoustic measurement test was designed during the initial year of the SCAMP program, with execution of the SCAMP flight test occurring in May 2011. The current SCAMP team, led by Wyle, includes partners from the Boeing Company, Pennsylvania State University, Gulfstream Aerospace, Eagle Aeronautics, and Central Washington University. Numerous collaborators have also participated by supporting the experiment with human and equipment resources at their own expense. The experiment involved precision flight of a McDonnell Douglas (now Boeing) F-18B executing different maneuvers that created focused sonic booms. The maneuvers were designed to center on the flight regime expected for commercial supersonic aircraft transonic transition, and also span a range of caustic curvatures in order to provide a variety of conditions for code validations. The SCAMP experiment was designed to capture concurrent F-18B on-board flight instrumentation data, high-fidelity ground-based and airborne acoustic data, and surface and upper air meteorological data. Close coordination with NASA Dryden resulted in the development of new experimental instrumentation and techniques to facilitate the SCAMP flight-test execution, including the development of an F-18B Mach rate cockpit display, TG-14 powered glider in-flight sonic boom measurement instrumentation and "Where's the Focus?" (WTF) software for near-real time way-point computation accounting for local atmospherics. In May 2011, 13 F-18B flights were conducted during 5 flying days over a 2 week period. A densely populated 10,000 ft-long ground acoustic array with 125-ft microphone spacing was designed to capture pre-, focus, and post-focus regions. The ground-based acoustic array was placed in a nominally east-west orientation in the remote Cuddeback lakebed region, north of Edwards AFB. This area was carefully selected to avoid placing focused booms on populated areas or solar power facilities. For the SCAMP measurement campaign, approvals were obtained to temporarily extend the Black Mountain supersonic corridor northward by three miles. The SCAMP flight tests successfully captured 70 boom events, with 61 focus passes, and 9 calibration passes. Seventeen of the focus passes and three of the calibration passes were laterally offset; with the others being centerline flights. Airborne incoming sonic boom wave measurements were measured by the TG-14 for 10 of the F-18B flight passes including one maximum focus signature, several N-u combinations, several overlapped N-u signatures, and several evanescent waves. During the 27-month program, the SCAMP team developed a suite of integrated computer codes with sonic boom focusing predictive capabilities: PCBoom, Lossy Nonlinear Tricomi Equation Method (LNTE) and the Nonlinear Progressive wave Equation (NPE) method. PCBoom propagates the rays through the atmosphere and, in addition to legacy focus signature prediction based on the Gill-Seebass method, provides input source characteristics and propagation parameters to LNTE and NPE. LNTE, a Tricomi solver that incorporates atmospheric losses, computes the focus signature at the focus, and computes the focus signature in the vicinity of the focal zone, including the evanescent and post-focus zones. LNTE signature auralization from low-boom vehicle designs has been demonstrated in the NASA Langley Interior Effects Room (IER). The NPE has also been validated for use in prediction of focused ground boom signatures in sonic boom focal zones. The NPE formulation has the capability to incorporate atmospheric turbulence in the predictions. This has been applied to sonic boom propagation in the past. Prediction of turbulence effects on focal zone signatures was not, however, explored during the SCAMP program.

Page, Juliet↗
DOE OSTI2022

Analysis of contact conditions and microstructure evolution in shear assisted processing and extrusion using smoothed particle hydrodynamics method

Shear assisted processing and extrusion (ShAPE) is a solid-phase processing technique that adds an additional shear force as compared with a conventional extrusion approach. Recently, ShAPE has demonstrated the capability of extruding high-performance aluminum alloy 7075 (AA7075) tubes at speeds up to 12.2 m/min without surface tearing. However, the relationship among the ShAPE processing parameters, thermomechanical conditions, contact conditions, heat generation, and microstructure evolution remains primarily empirical because an insightful understanding of the associated physics is still lacking. To help elucidate these relationships, this work proposes a thermomechanical meshfree model for the first time for ShAPE processing of AA7075 using the smoothed particle hydrodynamics (SPH) method. The meshfree model is first validated thoroughly by experimental data in terms of material flow, die face temperature, and extrusion force with various processing parameters. The validated model is then used to analyze the steady-state contact conditions and heat generation rates during ShAPE processing. Distributions of the average grain size of AA7075 being extruded are calculated using the SPH model output. The meshfree model results reveal that extrusions conducted at lower temperatures and higher strain rates yield more refined grains and possibly higher material strength, which is also consistent with the experimental observations.

36 MATERIALS SCIENCE↗
NASA NTRS1979

Improved prediction of laminar leading edge separation

Research was conducted to provide a definite criterion for the prediction of the bubble burst on airfoils typical of those used for fighter wings. The approach taken was to correlate existing airfoil bubble burst data using various parameters at the laminar separation point. The method due to Weber was modified to provide a continuous analytic solution for the velocity distribution around the airfoil leading edge. Coupling the modified Weber method with the Stratford laminar separation prediction method leads to a universal chart giving the conditions at separation as a function of stagnation location and leading edge radius. Application of the combined method to available two-dimensional airfoil data resulted in an empirical criterion presenting the limiting local velocity gradient at separation as a function of the boundary layer momentum thickness at separation for bubble burst. The correlation leads as well to the qualitative explanation of two types of laminar stall: thin airfoil and leading edge. The validity of the correlation is demonstrated by predicting the lift coefficient and angle of attack for stall on airfoils with leading edge or trailing edge flaps.

Herring, R. N.↗
NASA NTRS1992

Engine Performance and Health Monitoring Models Using Steady State and Transient Prediction Methods

This lecture note discusses the role of computer modelling in the design, development, and validation of a performance monitoring system. The basic requirements of an engine health monitoring system are discussed in the context of the user environment. A form of model based on stage characteristics provides the basis for describing engine measurements. Faults are modelled in accordance with empirical data obtained from tests conducted at the stage level. The model is used to investigate various parameters that provide unambiguous identification of the fault in question. Fault libraries have been developed for field use.

B D MacIsaac↗
NASA NTRS2000

A Catchment-Based Approach to Modeling Land Surface Processes in a GCM: Parameter Estimation and Model Demonstration - Part 2

The viability of a new catchment-based land surface model (LSM) developed for use with general circulation models is demonstrated. First, simple empirical functions -- tractable enough for operational use in the LSM -- are established that faithfully capture the control of topography on the subgrid variability of soil moisture and the surface water budget, as predicted by theory. Next, the full LSM is evaluated offline. Using forcing and validation datasets developed for PILPS Phase 2c, the minimally calibrated model is shown to reproduce observed evaporation and runoff fluxes successfully in the Red-Arkansas River Basin. A complementary idealized study that employs the range of topographic variability seen over North America demonstrates that the simulated surface water budget does vary strongly with topography, which can, by itself, induce variations in annual evaporation as high as 20%.

Ducharne, Agnes↗
NASA NTRS2000

Top-of-Atmosphere Albedo Estimation from Angular Distribution Models using Scene Identification from Satellite Cloud Property Retrievals

The next generation of Earth radiation budget satellite instruments will routinely merge estimates of global top-of-atmosphere radiative fluxes with cloud properties. This information will offer many new opportunities for validating radiative transfer models and cloud parameterizations in climate models. In this study, five months of POLarization and Directionality of the Earth's Reflectances (POLDER) 670 nm radiance measurements are considered in order to examine how satellite cloud property retrievals can be used to define empirical Angular Distribution Models (ADMs) for estimating top-of-atmosphere (TOA) albedo. ADMs are defined for 19 scene types defined by satellite retrievals of cloud fraction and cloud optical depth. Two approaches are used to define the ADM scene types: The first assumes there are no biases in the retrieved cloud properties and defines ADMs for fixed discrete intervals of cloud fraction and cloud optical depth (fixed-tau approach). The second approach involves the same cloud fraction intervals, but uses percentile intervals of cloud optical depth instead (percentile-tau approach). Albedos generated using these methods are compared with albedos inferred directly from the mean observed reflectance field. Albedos based on ADMs that assume cloud properties are unbiased (fixed-tau approach) show a strong systematic dependence on viewing geometry. This dependence becomes more pronounced with increasing solar zenith angle, reaching approximately equals 12% (relative) between near-nadir and oblique viewing zenith angles for solar zenith angles between 60 deg and 70 deg. The cause for this bias is shown to be due to biases in the cloud optical depth retrievals. In contrast, albedos based on ADMs built using percentile intervals of cloud optical depth (percentile-tau approach) show very little viewing zenith angle dependence and are in good agreement with albedos obtained by direct integration of the mean observed reflectance field (less than 1% relative error). When the ADMs are applied separately to populations consisting of only liquid water and ice clouds, significant biases in albedo with viewing geometry are observed (particularly at low sun elevations), highlighting the need to account for cloud phase both in cloud optical depth retrievals and in defining ADM scene types. ADM-derived monthly mean albedos determined for all 5 deg x 5 deg latitude/longitude regions over ocean are in good agreement (regional RMS relative errors less than 2%) with those obtained by direct integration when ADM albedos inferred from specific angular bins are averaged together. Albedos inferred from near-nadir and oblique viewing zenith angles are the least accurate, with regional RMS errors reaching approximately 5-10% (relative). Compared to an earlier study involving ERBE ADMs, regional mean albedos based on the 19 scene types considered here show a factor of 4 reduction in bias error and a factor of 3 reduction in RMS error.

Loeb, N. G.↗
NASA NTRS2008

User's Manual for LEWICE Version 3.2

A research project is underway at NASA Glenn to produce a computer code which can accurately predict ice growth under a wide range of meteorological conditions for any aircraft surface. This report will present a description of the code inputs and outputs from version 3.2 of this software, which is called LEWICE. This version differs from release 2.0 due to the addition of advanced thermal analysis capabilities for de-icing and anti-icing applications using electrothermal heaters or bleed air applications, the addition of automated Navier-Stokes analysis, an empirical model for supercooled large droplets (SLD) and a pneumatic boot option. An extensive effort was also undertaken to compare the results against the database of electrothermal results which have been generated in the NASA Glenn Icing Research Tunnel (IRT) as was performed for the validation effort for version 2.0. This report will primarily describe the features of the software related to the use of the program. Appendix A has been included to list some of the inner workings of the software or the physical models used. This information is also available in the form of several unpublished documents internal to NASA. This report is intended as a replacement for all previous user manuals of LEWICE. In addition to describing the changes and improvements made for this version, information from previous manuals may be duplicated so that the user will not need to consult previous manuals to use this software.

Wright, William↗
NASA NTRS2022

Review of Solar Energetic Particle Models

Solar Energetic Particle (SEP) events are interesting from a scientific perspective as they are the product of a broad set of physical processes from the corona out through the extent of the heliosphere, and provide insight into processes of particle acceleration and transport that are widely applicable in astrophysics. From the operations perspective, SEP events pose a radiation hazard for aviation, electronics in space, and human space exploration, in particular for missions outside of the Earth’s protective magnetosphere including to the Moon and Mars. Thus, it is critical to improve the scientific understanding of SEP events and use this understanding to develop and improve SEP forecasting capabilities to support operations. Many SEP models exist or are in development using a wide variety of approaches and with differing goals. These include computationally intensive physics-based models, fast and light empirical models, machine learning-based models, and mixed-model approaches. The aim of this paper is to summarize all of the SEP models currently developed in the scientific community, including a description of model approach, inputs and outputs, free parameters, and any published validations or comparisons with data.

Kathryn Whitman↗
NASA NTRSDate not supplied

Creating A Consistent Historical NASA POWER Solar Radiation Dataset to Support Renewable Energy, Building Energy Efficiency and Agro-Climatology Decisions

Prediction of Worldwide Energy Resources (POWER) project provides irradiance dataset to support renewable energy, building energy efficiency and agricultural needs. These datasets are derived from Global Energy and Water Cycle Experiment Surface Radiation Budget (GEWEX SRB) and Clouds and the Earth’s Radiant Energy System (CERES SYN1Deg). A systematic bias has been reported between these two datasets for the years with overlapping observations. For obtaining a consistent climate data record spanning the entire time record of observations, it is crucial to understand and remove the bias in the irradiance dataset. Inconsistency in solar radiation data can lead to inaccurate conclusions about solar energy potential and obscure real trends in solar radiation patterns that would impact energy availability assessments. In this study, we adapt quantile mapping approach to remove the systematic bias and to improve reliability of shortwave and longwave irradiance data. We present a validation of the bias corrected data against ground truth. For each 1° latitude and 1° longitude grid box across the globe, we match the CDFs of the reference dataset (CERES SYN1Deg) to that of the SRB dataset, thereby, adjusting the irradiance values to match the empirical distribution of two different measurements. The performance of quantile mapping is evaluated by using the metrics such as Mean Absolute Deviation (MAD). The results indicate that the quantile mapping significantly improves the accuracy and reliability of solar irradiance dataset especially for the weather conditions associated with high cloud cover and extreme irradiance values. The initial range of MAD for the studied sites for daily data was 4 to 19 Wm-2. After correction these reduced to 3 to 7 Wm-2. The findings from this study have important implications for solar energy system design, agricultural planning, and climate modeling community. Reducing the inconsistency and biases in solar irradiance dataset can enable better planning and operation of solar energy systems, leading to increased efficiency and cost-effectiveness. Additionally, this work also contributes to the statistical post-processing techniques in the renewable energy domain and highlights the potential of historical and near-real-time NASA POWER dataset as a valuable resource for solar energy research and applications.

POWER↗
DOE OSTI2022

Squeeze Film Damper Experimental and Numerical Correlation: Test Setup Description and Parameter Identification of Dry System

The process of characterizing a damper involves both experimental techniques and model simulation. Experiments characterize dynamic behavior of a system through empirical modal analysis using impact and shaker testing. The layout of the test setup is crucial for a low-mass, nonlinear system. Physical arrangement, orientation of the system, and instrumentation affect the results that are discussed in this paper. These results can be used to validate a numerical simulation of the same system. With a validated model, important physical input parameters and modeling techniques can be determined and implemented in future designs. In other words, this modeling can be used with confidence to design alternative dampers that may be difficult, costly, and time-consuming to characterize experimentally.

Cook, Jason↗
DOE OSTI2020

A machine learning model for predicting the minimum miscibility pressure of CO 2 and crude oil system based on a support vector machine algorithm approach

CO 2 enhanced oil recovery (EOR) is a potential way for carbon capture, utilization and storage (CCUS). Though, the effect of CO 2 injection is greatly influenced by the reservoir conditions. Typically, Minimum miscible pressure (MMP) is selected as one of the key parameters for the screening and evaluation of prospective CO 2 flooding. Conventional slim tube test is both accurate and widely accepted but it is inefficient. Existing empirical formulas for MMPs are easy to be used but have been proved inaccurate and unreliable. Machine learning-based methods have great advantages in predicting MMP. However, only predication accuracy is discussed for most models without the screening of the main control factors and further validation of the model reliability. In this paper, a new prediction model based on support vector machine (SVM) was developed for pure/impure CO 2 and crude oil system. This study was based on 147 sets of MMP data from the literature with full information on reservoir temperature, oil composition and gas composition. The main control factors were screened by several statistical methods. Unlike the conventional prediction models that verified by only prediction accuracy, learning curve and single factor control variable analysis are further validated to obtain the optimum model.

02 PETROLEUM↗