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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1999

Influence of Natural Convection and Thermal Radiation Multi-Component Transport in MOCVD Reactors

The influence of Grashof and Reynolds number in Metal Organic Chemical Vapor (MOCVD) reactors is being investigated under a combined empirical/numerical study. As part of that research, the deposition of Indium Phosphide in an MOCVD reactor is modeled using the computational code CFD-ACE. The model includes the effects of convection, conduction, and radiation as well as multi-component diffusion and multi-step surface/gas phase chemistry. The results of the prediction are compared with experimental data for a commercial reactor and analyzed with respect to the model accuracy.

Lowry, S.↗
NASA NTRS2000

Rapid Model Fabrication and Testing for Aerospace Vehicles

Advanced methods for rapid fabrication and instrumentation of hypersonic wind tunnel models are being developed and evaluated at NASA Langley Research Center. Rapid aeroheating model fabrication and measurement techniques using investment casting of ceramic test models and thermographic phosphors are reviewed. More accurate model casting techniques for fabrication of benchmark metal and ceramic test models are being developed using a combination of rapid prototype patterns and investment casting. White light optical scanning is used for coordinate measurements to evaluate the fabrication process and verify model accuracy to +/- 0.002 inches. Higher-temperature (<210C) luminescent coatings are also being developed for simultaneous pressure and temperature mapping, providing global pressure as well as global aeroheating measurements. Together these techniques will provide a more rapid and complete experimental aerodynamic and aerothermodynamic database for future aerospace vehicles.

Buck, Gregory M.↗
NASA NTRS2000

National Combustion Code: Parallel Implementation and Performance

The National Combustion Code (NCC) is being developed by an industry-government team for the design and analysis of combustion systems. CORSAIR-CCD is the current baseline reacting flow solver for NCC. This is a parallel, unstructured grid code which uses a distributed memory, message passing model for its parallel implementation. The focus of the present effort has been to improve the performance of the NCC flow solver to meet combustor designer requirements for model accuracy and analysis turnaround time. Improving the performance of this code contributes significantly to the overall reduction in time and cost of the combustor design cycle. This paper describes the parallel implementation of the NCC flow solver and summarizes its current parallel performance on an SGI Origin 2000. Earlier parallel performance results on an IBM SP-2 are also included. The performance improvements which have enabled a turnaround of less than 15 hours for a 1.3 million element fully reacting combustion simulation are described.

Quealy, A.↗
NASA NTRS2000

Absorption of Solar Radiation by Clouds: An Overview

This talk provides an overview of the subject of absorption of solar radiation by clouds in the earth's atmosphere. The paper summarizes the available evidence which points to disagreements between theoretical and observed values of cloud absorption (and reflections). The importance of these discrepancies, particularly to remote sensing of clouds as well as to studies of cloud physics and earth radiation budgets, is emphasized. Existing cloud absorption and reflection measurements are reviewed and the persistent differences that exist between calculated and measured near-infrared cloud albedos are highlighted. Various explanations for these reflection and absorption discrepancies are discussed under two separate paths: a theoretician's approach and an experimentalist's approach. Examples for the former approach include model accuracy tests, large-droplet hypothesis, excess absorbing aerosol, enhanced water vapor continuum absorption, and effects of cloud inhomogeneity. The latter approach focuses on discussions of instrumental device, calibration, operational strategy, and signal/noise separation. A recommendation for future activities on this subject will be given.

Tsay, Si-Chee↗
NASA NTRS2001

National Combustion Code: Parallel Performance

This report discusses the National Combustion Code (NCC). The NCC is an integrated system of codes for the design and analysis of combustion systems. The advanced features of the NCC meet designers' requirements for model accuracy and turn-around time. The fundamental features at the inception of the NCC were parallel processing and unstructured mesh. The design and performance of the NCC are discussed.

Babrauckas, Theresa↗
NASA NTRS2002

Validation of International Space Station Electrical Performance Model via On-orbit Telemetry

The first U.S. power module on International Space Station (ISS) was activated in December 2000. Comprised of solar arrays, nickel-hydrogen (NiH2) batteries, and a direct current power management and distribution (PMAD) system, the electric power system (EPS) supplies power to housekeeping and user electrical loads. Modeling EPS performance is needed for several reasons, but primarily to assess near-term planned and off-nominal operations and because the EPS configuration changes over the life of the ISS. The System Power Analysis for Capability Evaluation (SPACE) computer code is used to assess the ISS EPS performance. This paper describes the process of validating the SPACE EPS model via ISS on-orbit telemetry. To accomplish this goal, telemetry was first used to correct assumptions and component models in SPACE. Then on-orbit data was directly input to SPACE to facilitate comparing model predictions to telemetry. It will be shown that SPACE accurately predicts on-orbit component and system performance. For example, battery state-of-charge was predicted to within 0.6 percentage points over a 0 to 100 percent scale and solar array current was predicted to within a root mean square (RMS) error of 5.1 Amps out of a typical maximum of 220 Amps. First, SPACE model predictions are compared to telemetry for the ISS EPS components: solar arrays, NiH2 batteries, and the PMAD system. Second, SPACE predictions for the overall performance of the ISS EPS are compared to telemetry and again demonstrate model accuracy.

Jannette, Anthony G.↗
NASA NTRS2002

Comparison of Engine Cycle Codes for Rocket-Based Combined Cycle Engines

This paper summarizes the results from a one day workshop on Rocket-Based Combined Cycle (RBCC) Engine Cycle Codes held in Monterey CA in November of 2000 at the 2000 JANNAF JPM with the authors as primary participants. The objectives of the workshop were to discuss and compare the merits of existing Rocket-Based Combined Cycle (RBCC) engine cycle codes being used by government and industry to predict RBCC engine performance and interpret experimental results. These merits included physical and chemical modeling, accuracy and user friendliness. The ultimate purpose of the workshop was to identify the best codes for analyzing RBCC engines and to document any potential shortcomings, not to demonstrate the merits or deficiencies of any particular engine design. Five cases representative of the operating regimes of typical RBCC engines were used as the basis of these comparisons. These included Mach 0 sea level static and Mach 1.0 and Mach 2.5 Air-Augmented-Rocket (AAR), Mach 4 subsonic combustion ramjet or dual-mode scramjet, and Mach 8 scramjet operating modes. Specification of a generic RBCC engine geometry and concomitant component operating efficiencies, bypass ratios, fuel/oxidizer/air equivalence ratios and flight dynamic pressures were provided. The engine included an air inlet, isolator duct, axial rocket motor/injector, axial wall fuel injectors, diverging combustor, and exit nozzle. Gaseous hydrogen was used as the fuel with the rocket portion of the system using a gaseous H2/O2 propellant system to avoid cryogenic issues. The results of the workshop, even after post-workshop adjudication of differences, were surprising. They showed that the codes predicted essentially the same performance at the Mach 0 and I conditions, but progressively diverged from a common value (for example, for fuel specific impulse, Isp) as the flight Mach number increased, with the largest differences at Mach 8. The example cases and results are compared and discussed in this paper.

Waltrup, Paul J.↗
NASA NTRS2002

National Combustion Code Parallel Performance Enhancements

The National Combustion Code (NCC) is being developed by an industry-government team for the design and analysis of combustion systems. The unstructured grid, reacting flow code uses a distributed memory, message passing model for its parallel implementation. The focus of the present effort has been to improve the performance of the NCC code to meet combustor designer requirements for model accuracy and analysis turnaround time. Improving the performance of this code contributes significantly to the overall reduction in time and cost of the combustor design cycle. This report describes recent parallel processing modifications to NCC that have improved the parallel scalability of the code, enabling a two hour turnaround for a 1.3 million element fully reacting combustion simulation on an SGI Origin 2000.

Quealy, Angela↗
NASA NTRS2012

NASA Center for Climate Simulation (NCCS) Presentation

The NASA Center for Climate Simulation (NCCS) offers integrated supercomputing, visualization, and data interaction technologies to enhance NASA's weather and climate prediction capabilities. It serves hundreds of users at NASA Goddard Space Flight Center, as well as other NASA centers, laboratories, and universities across the US. Over the past year, NCCS has continued expanding its data-centric computing environment to meet the increasingly data-intensive challenges of climate science. We doubled our Discover supercomputer's peak performance to more than 800 teraflops by adding 7,680 Intel Xeon Sandy Bridge processor-cores and most recently 240 Intel Xeon Phi Many Integrated Core (MIG) co-processors. A supercomputing-class analysis system named Dali gives users rapid access to their data on Discover and high-performance software including the Ultra-scale Visualization Climate Data Analysis Tools (UV-CDAT), with interfaces from user desktops and a 17- by 6-foot visualization wall. NCCS also is exploring highly efficient climate data services and management with a new MapReduce/Hadoop cluster while augmenting its data distribution to the science community. Using NCCS resources, NASA completed its modeling contributions to the Intergovernmental Panel on Climate Change (IPCG) Fifth Assessment Report this summer as part of the ongoing Coupled Modellntercomparison Project Phase 5 (CMIP5). Ensembles of simulations run on Discover reached back to the year 1000 to test model accuracy and projected climate change through the year 2300 based on four different scenarios of greenhouse gases, aerosols, and land use. The data resulting from several thousand IPCC/CMIP5 simulations, as well as a variety of other simulation, reanalysis, and observationdatasets, are available to scientists and decision makers through an enhanced NCCS Earth System Grid Federation Gateway. Worldwide downloads have totaled over 110 terabytes of data.

Webster, William P.↗
NASA NTRS2012

Development Of FIAT-Based Thermal Protection System Mass Estimating Relationships For NASA's Multi-Mission Earth Entry Concept

Mass Estimating Relationships (MERs) have been developed for use in the Program to Optimize Simulated Trajectories II (POST2) as part of NASA's multi-mission Earth Entry Vehicle (MMEEV) concept. MERs have been developed for the thermal protection systems of PICA and of Carbon Phenolic atop Advanced Carbon-Carbon on the forebody and for SIRCA and Acusil II on the backshell. How these MERs were developed, the resulting equations, model limitations, and model accuracy are discussed herein.

Sepka, Steven↗
NASA NTRS2013

Development of FIAT-Based Parametric Thermal Protection System Mass Estimating Relationships for NASA's Multi-Mission Earth Entry Concept

Part of NASAs In-Space Propulsion Technology (ISPT) program is the development of the tradespace to support the design of a family of multi-mission Earth Entry Vehicles (MMEEV) to meet a wide range of mission requirements. An integrated tool called the Multi Mission System Analysis for Planetary Entry Descent and Landing or M-SAPE tool is being developed as part of Entry Vehicle Technology project under In-Space Technology program. The analysis and design of an Earth Entry Vehicle (EEV) is multidisciplinary in nature, requiring the application many disciplines. Part of M-SAPE's application required the development of parametric mass estimating relationships (MERs) to determine the vehicle's required Thermal Protection System (TPS) for safe Earth entry. For this analysis, the heat shield was assumed to be made of a constant thickness TPS. This resulting MERs will then e used to determine the pre-flight mass of the TPS. Two Mers have been developed for the vehicle forebaody. One MER was developed for PICA and the other consisting of Carbon Phenolic atop an Advanced Carbon-Carbon composition. For the the backshell, MERs have been developed for SIRCA, Acusil II, and LI-900. How these MERs were developed, the resulting equations, model limitations, and model accuracy are discussed in this poster.

Sepka, Steven A.↗
NASA NTRS2011

Development of FIAT-based Thermal Protection System Mass Estimating Relationships for NASA's Multi-Mission Earth Entry Concep

Mass Estimating Relationships (MERs) have been developed for use in the Program to Optimize Simulated Trajectories II (POST2) as part of NASA's multi-mission Earth Entry Vehicle (MMEEV) concept. MERs have been developed for the thermal protection systems of PICA and of Carbon Phenolic atop Advanced Carbon-Carbon on the forebody and for SIRCA and Acusil II on the backshell. How these MERs were developed, the resulting equations, model limitations, and model accuracy are discussed herein.

MER↗
NASA NTRS2015

Thermal Protection System Mass Estimating Relationships for Blunt-Body, Earth Entry Spacecraft

System analysis and design of any entry system must balance the level fidelity for each discipline against the project timeline. One way to inject high fidelity analysis earlier in the design effort is to develop surrogate models for the high-fidelity disciplines. Surrogate models for the Thermal Protection System (TPS) are formulated as Mass Estimating Relationships (MERs). The TPS MERs are presented that predict the amount of TPS necessary for safe Earth entry for blunt-body spacecraft using simple correlations that closely match estimates from NASA's high-fidelity ablation modeling tool, the Fully Implicit Ablation and Thermal Analysis Program (FIAT). These MERs provide a first order estimate for rapid feasibility studies. There are 840 different trajectories considered in this study, and each TPS MER has a peak heating limit. MERs for the vehicle forebody include the ablators Phenolic Impregnated Carbon Ablator (PICA) and Carbon Phenolic atop Advanced Carbon-Carbon. For the aftbody, the materials are Silicone Impregnated Reusable Ceramic Ablator (SIRCA), Acusil II, SLA-561V, and LI-900. The MERs are accurate to within 14% (at one standard deviation) of FIAT prediction, and the most any MER under predicts FIAT TPS thickness is 18.7%. This work focuses on the development of these MERs, the resulting equations, model limitations, and model accuracy.

mass estimating relationship (MER)↗
NASA NTRS2015

Thermal Protection System Mass Estimating Relationships For Blunt-Body, Earth Entry Spacecraft

Mass estimating relationships (MERs) are developed to predict the amount of thermal protection system (TPS) necessary for safe Earth entry for blunt-body spacecraft using simple correlations that are non-ITAR and closely match estimates from NASA's highfidelity ablation modeling tool, the Fully Implicit Ablation and Thermal Analysis Program (FIAT). These MERs provide a first order estimate for rapid feasibility studies. There are 840 different trajectories considered in this study, and each TPS MER has a peak heating limit. MERs for the vehicle forebody include the ablators Phenolic Impregnated Carbon Ablator (PICA) and Carbon Phenolic atop Advanced Carbon-Carbon. For the aftbody, the materials are Silicone Impregnated Reusable Ceramic Ablator (SIRCA), Acusil II, SLA- 561V, and LI-900. The MERs are accurate to within 14% (at one standard deviation) of FIAT prediction, and the most any MER can under predict FIAT TPS thickness is 18.7%. This work focuses on the development of these MERs, the resulting equations, model limitations, and model accuracy.

Spacecraft↗
NASA NTRS2018

A Case for High-Fidelity Material Response Modeling

Material response modeling of heatshields for planetary entry vehicles has remained largely unchanged since Aerotherm Corp. introduced the CMA program in 1967. Modern models, like FIAT, have tread the same path, introducing efficiencies and better material property data along the way, but otherwise following the same underlying model paradigm. The CMA approach has worked well for heatshield design up to this point. However, there are three motivations for the material response community to pursue higher fidelity beyond simplified, CMA-derived models. The first motivation is that missions are becoming increasingly demanding and complex and, as they do, confidence in simplified models naturally decreases. Second, reliability of materials is now as much or more of a driving concern for mission designers than thermal response. Third, NASA and other agencies are increasingly interested in flight instrumentation for engineering science. This latter motivation places far stricter requirements on model accuracy in order to meet requirements for flight environment reconstruction.

Barnhardt, Michael D.↗
NASA NTRS2014

Development Of FIAT-Based Parametric Thermal Protection System Mass Estimating Relationships For NASA's Multi-Mission Earth Entry Concept

An integrated tool called the Multi Mission System Analysis for Planetary Entry Descent and Landing (M-SAPE) is being developed as part of NASAs In-Space Propulsion Technology (ISPT) program. Part of M-SAPEs development requires the formulation of mass estimating relationships (MERs) to determine the vehicle's Thermal Protection System (TPS) material and required thickness for safe Earth entry. The objective of this study was to develop MERs using simple correlations that were non-ITAR and matched as accurately as possible NASAs high-fidelity ablation modeling tool, the Fully Implicit Ablation and Thermal Analysis Program (FIAT ). These MERs would be a first-estimate for feasibility studies; it is understood that higher-fidelity modeling like FIAT would be necessary once a proposed trajectory was down-selected. The trajectory space for these MERS consisted of 840 different trajectories, and a materials heating limit was the main constraint for an allowable trajectory. MERs for the vehicle fore body included the ablating materials Phenolic Impregnated Carbon Ablator (PICA ) and Carbon Phenolic atop Advanced Carbon-Carbon. For the backshell the materials were Silicone Impregnated Reusable Ceramic Ablator (SIRCA ), Acusil II, SLA-561V, and LI-900. The MERFIAT ratio indicates MERs are accurate to within 14 percent (at one standard deviation) of FIAT prediction, and the most any MER can under-predict TPS thickness is 18.7 percent of FIAT prediction. This poster focuses on the development of these MERs, the resulting equations, model limitations, and model accuracy.

thermal protection system↗
NASA NTRS2019

Using Machine-Learning to Dynamically Generate Operationally Acceptable Strategic Reroute Options

The newly developed Trajectory Option Set (TOS), a preference-weighted set of alternative routes submitted by flight operators, is a capability in the U.S. traffic flow management system that enables automated trajectory negotiation between flight operators and Air Navigation Service Providers. The objective of this paper is to describe and demonstrate an approach for automatically generating pre-departure and airborne TOSs that have a high probability of operational acceptance. The approach uses hierarchical clustering of historical route data to identify route candidates. The probability of operational acceptance is then estimated using predictors trained on historical flight plan amendment data using supervised machine learning algorithms, allowing the routes with highest probability of operational acceptance to be selected for the TOS. Features used describe historical route usage, difference in flight time and downstream demand to capacity imbalance. A random forest was found to be the best performing algorithm for learning operational acceptability, with a model accuracy of 0.96. The approach is demonstrated for an historical pre-departure flight from Dallas/Fort Worth International Airport to Newark Liberty International Airport.

Evans, Antony↗
NASA NTRS2019

Using Machine-Learning to Dynamically Generate Operationally Acceptable Strategic Reroute Options

The newly developed Trajectory Option Set (TOS), a preference-weighted set of alternative routes submitted by flight operators, is a capability in the U.S. traffic flow management system that enables automated trajectory negotiation between flight operators and Air Navigation Service Providers. The objective of this paper is to describe and demonstrate an approach for automatically generating pre-departure and airborne TOSs that have a high probability of operational acceptance. The approach uses hierarchical clustering of historical route data to identify route candidates. The probability of operational acceptance is then estimated using predictors trained on historical flight plan amendment data using supervised machine learning algorithms, allowing the routes with highest probability of operational acceptance to be selected for the TOS. Features used describe historical route usage, difference in flight time and downstream demand to capacity imbalance. A random forest was found to be the best performing algorithm for learning operational acceptability, with a model accuracy of 0.96. The approach is demonstrated for an historical pre-departure flight from Dallas/Fort Worth International Airport to Newark Liberty International Airport.

Evans, Antony↗