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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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An overview of the NASA Advanced Air Transport Technology (AATT) Project and interest inboundary layer transition modeling for future aircraft and propulsion systems is presented.
America is home to over 5,000 airports available for public use, yet only 30 of these airports serve over 70% of all travelers.01 Despite this vast network of airports, the majority are underutilized due to air transportation services that have trended towards consolidation by putting more people into fewer, larger aircraft on well-traveled routes. Also, these bigger jet-propelled aircraft can only take off from and land on longer airstrips. Regional Air Mobility (RAM) will fundamentally change how we travel by bringing the convenience, speed, and safety of air travel to all Americans, regardless of their proximity to a travel hub or urban center. We advocate RAM technology investment as complementary to and an accelerator for Advanced Air Mobility (AAM) and other initiatives that aspire to transform the airspace. Through targeted advanced technology investments, such as aircraft automation, enhanced operational models, more efficient aircraft and propulsion systems, and expanded airport renewable energy generation, many of which are already underway, RAM will increase the safety, accessibility, and affordability of regional travel while building on the extensive and underutilized federal, state, and local investment in our nation’s local airports.
The Vehicle Integrated Thermal Management Analysis Code (VITMAC) was further developed to aid the analysis, design, and optimization of propellant and thermal management concepts for advanced propulsion systems. The computational tool is based on engineering level principles and models. A graphical user interface (GUI) provides a simple and straightforward method to assess and evaluate multiple concepts before undertaking more rigorous analysis of candidate systems. The tool incorporates the Chemical Equilibrium and Applications (CEA) program and the RJPA code to permit heat transfer analysis of both rocket and air breathing propulsion systems. Key parts of the code have been validated with experimental data. The tool was specifically tailored to analyze rocket-based combined-cycle (RBCC) propulsion systems being considered for space transportation applications. This report describes the computational tool and its development and verification for NASA GTX RBCC propulsion system applications.
Advanced electric propulsion research activities are currently underway that seek to addresses feasibility issues of a wide range of advanced concepts, and may result in the development of technologies that will enable exciting new missions within our solar system and beyond. Each research activity is described in terms of the present focus and potential future applications. Topics include micro-electric thrusters, electrodynamic tethers, high power plasma thrusters and related applications in materials processing, variable specific impulse plasma thrusters, pulsed inductive thrusters, computational techniques for thruster modeling, and advanced electric propulsion missions and systems studies.
The National PARC (NPARC) Alliance was established by the NASA Lewis Research Center and the Air Force Arnold Engineering Development Center to provide the U.S. aeropropulsion community with a reliable Navier-Stokes code for simulating the nonrotating components of propulsion systems. Recent improvements to the turbulence model capabilities of the NPARC code have significantly improved its capability to simulate turbulent flows. Specifically, the Chien k-epsilon and Wilcox k-omega turbulence models were implemented at Lewis. Lewis researchers installed the Chien k-epsilon model into NPARC to improve the code's ability to calculate turbulent flows with attached wall boundary layers and free shear layers. Calculations with NPARC have demonstrated that the Chien k-epsilon model provides more accurate calculations than those obtained with algebraic models previously available in the code. Grid sensitivity investigations have shown that computational grids must be packed against the solid walls such that the first point off of the wall is placed in the laminar sublayer. In addition, matching the boundary layer and momentum thicknesses entering mixing regions is necessary for an accurate prediction of the free shear-layer growth.
This Lecture Series covers topics of aero-thermodynamic performance prediction methods for gas turbine engines with respect to steady and transient operation. This includes advanced cycle calculation methods, also taking into account variable cycle engine types. A very important objective is the consideration of installation effect, i.e., Reynolds number and inlet distortions, as well as advanced control concepts for increasing engine surge margins. In addition to these topics, individual papers include practical considerations in developing the engine cycle, dynamic simulation, inlet distortion effects in aircraft propulsion system integration, “smart” engines, performance and heal monitoring models. This Lecture Series, sponsored by the Propulsion and Energetics Panel of AGARD and the Consultant and Exchange Programme of AGARD presented on 27th -28th May 1992 in Cambridge, MA, United States, 9th-10th June 1992 in Neubiberg, Germany and 11th-12th June 1992 in Chàtillon/Bagneux (near Paris), France
A previously published real-time simulation algorithm, the matrix stability region placement (MSRP) method, is used to simulate a small perturbation model of the NASA Lewis Mach 2.5 40-60 mixed compression inlet. The model is representative of high-speed internal flow propulsion systems which can be approximated as quasi-one-dimensional flows. The resulting system of equations, which is stiff, is also simulated by the second-order Adam-Bashforth method. It is shown that the MSRP method can be used to simulate small perturbation models of high-speed internal flow propulsion systems in real time.
NASA’s Space Nuclear Propulsion (SNP) program is developing several MagicDraw SysML models to support the development of high performance Nuclear Thermal Rocket Engines (NTRE). Currently, the Demonstration Rocket for Agile Cislunar Operations (DRACO) project is aiming to perform the first ever flight demonstration of an NTRE, and NASA is developing a DRACO Insight Project Model Based Systems Engineering (MBSE) model to capture, define, analyze, and report on the flight and ground test system architecture, functional behavior, requirements, risks, and lessons learned. Additional models are in work for engine component trade trees, fault detection sensor coverage analysis using a Goal Function Tree (GFT) plugin, stakeholder engagement, and technology maturation projects. The GFT plugin is the Galois, Inc. Failure Recovery Instruction Generation using Automata derived from Traditional Engineering models (FRIGATE) tool. A new capability for Jira to MagicDraw data sharing using the OpenPDM collaboration platform is under development with partner Victory Solutions, Inc. to enhance risk impact analysis.
This CP contains the extended abstracts and presentation figures of 36 papers presented at the PPM and Other Propulsion R&T Conference. The focus of the research described in these presentations is on materials and structures technologies that are parts of the various projects within the NASA Aeronautics Propulsion Systems Research and Technology Base Program. These projects include Physics and Process Modeling; Smart, Green Engine; Fast, Quiet Engine; High Temperature Engine Materials Program; and Hybrid Hyperspeed Propulsion. Also presented were research results from the Rotorcraft Systems Program and work supported by the NASA Lewis Director's Discretionary Fund. Authors from NASA Lewis Research Center, industry, and universities conducted research in the following areas: material processing, material characterization, modeling, life, applied life models, design techniques, vibration control, mechanical components, and tribology. Key issues, research accomplishments, and future directions are summarized in this publication.
Analytic modeling and analysis processes employed at NASA-SSC in rocket propulsion systems testing are discussed in this paper with application to test facility propellant supply system design, activation and test of a hybrid rocket motor provided. This paper discusses the analytic model employed, its utilization across project phases and reviews performance results.
Many air-breathing hypersonic aerospacecraft design concepts incorporate an elongated fuselage forebody acting as the aerodynamic compression surface for a hypersonic combustion module, or scram jet. This highly integrated design approach creates the potential for an unprecedented form of aero-propulsive-elastic interaction in which deflections of the vehicle fuselage give rise to propulsion transients, producing force and moment variations that may adversely impact the rigid body flight dynamics and/or further excite the fuselage bending modes. To investigate the potential for such interactions, a math model was developed which included the longitudinal flight dynamics, propulsion system, and first seven elastic modes of a hypersonic air-breathing vehicle. Perturbation time histories from a simulation incorporating this math model are presented that quantify the propulsive force and moment variations resulting from aeroelastic vehicle deflections. Root locus plots are presented to illustrate the effect of feeding the propulsive perturbations back into the aeroelastic model. A concluding section summarizes the implications of the observed effects for highly integrated hypersonic air-breathing vehicle concepts.
In the United States transportation sector, Light-Duty Vehicles (LDVs) are the largest energy consumers and CO 2 emitters. Electrification of LDVs is posed as a potential solution, but SI engines can still contribute to decarbonization. Car manufacturers have turned to unconventional engine operation to increase the efficiency of Spark-Ignition (SI) engines and reduce the carbon emissions of their fleets. Dilute, lean, and stratified-charge engine operation has the potential for engine efficiency improvements at the expense of increased cyclic variability and combustion instability. At such demanding engine conditions, the spark ignition event is key for flame initiation and propagation and for enhanced combustion stability. Reliable and accurate spark ignition models can help design ignition systems that reduce cyclic variability. Multiple computational spark-ignition models exist that perform well under conventional conditions, but the underlying physics needs to be expanded, for unconventional engine operation. In this paper, a hybrid Lagrangian–Eulerian Spark-Ignition (LESI) model is coupled with different turbulent flame propagation models for engine simulations. LESI relies on Lagrangian arc tracking and Eulerian energy deposition. The LESI model is coupled with the Well-Stirred Reactor (WSR), Thickened Flame Model (TFM), and g-equation model and used to simulate several cycles of a Direct-Injection Spark-Ignition (DISI) engine using a commercial Computational Fluid Dynamics (CFD) engine solver. The results showcase the successful coupling of LESI with the combustion models. Global engine metrics, such as pressure and Apparent Heat Release Rate (AHRR), for each simulation setup are compared to experimental engine results, for validation. In addition, results highlight the successful prediction of spark channel movement by comparing simulation images to experimental optical engine images. Finally, the successful coupling of LESI to combustion models, making it a usable model in the engine modeling community, is emphasized and future development details are discussed.
Organizational learning is an umbrella term that covers a variety of topics including; learning curves, productivity, organizational memory, organizational forgetting, knowledge transfer, knowledge sharing and knowledge creation. This treatise will review some of these theories in concert with a model of how organizations learn.
Due to constraints in space and structure as well as other practical limitations in aircraft system, the motor controller or electric motor are often installed far away from each other and interconnected via long cables. This amplifies the transmission line effect excited by the dv/dt PWM voltage and induces high voltage stress on the machine winding. This paper investigates the state-of-art modeling approaches for such systems, identifies several limitations in matching the tested voltage reflection waveform in terms of peak voltage, oscillation frequency and damping speed, and offers several key considerations not well covered in literature or in engineering practice. It then proposes a practical modeling methodology which, as validated by experimental results, truly captures these critical reflection voltage specs. To mitigate the high peak voltage and strong oscillation, dv/dt filter is applied and a parametric design optimization based on widely adopted LC-R topology is illustrated, which not only alleviates the voltage stress but also minimized the power loss of the passive damping resistor.
A Differential Scanning Calorimetry/Thermogravimetric Analysis (DSC/TGA) procedure for determination of Heat of Vaporization (HOV) of fuel and surrogate fuel mixtures has been previously utilized for evaluation of oxygenate impacts on spark ignition fuels. This analysis has been further leveraged with mass spectrometry (MS) to elucidate vapor phase compositional changes during evaporation. In this study we focus on a simple system of three compounds (ethanol, n-hexane, and n-octane) to provide a model-based understanding of the evaporation process under these experimental conditions. An Aspen Plus model was set up to provide liquid and vapor phase concentration predictions during mixture evaporation using the initial mixture composition, and measured temperature and mass loss profiles from DSC/TGA experiments. Agreements between the trends of the MS ion count profiles and model composition predictions provide a degree of validation of this modeling approach that can allow the interpretation and extrapolation of DSC/TGA measurements for more complex fuel mixtures.
Electric vehicles (EVs) are becoming a promising source of grid ancillary services due to the temporal and spatial charging flexibility, quick response and storage capability. Such advantages are increasing with government policy promotion and technology improvement. However, the exploration of EV flexibility requires the coordination of both transmission system operators (TSOs) and distribution system operators (DSOs), to ensure the safe and reliable operation of power network. In this paper, we propose a coordinated evaluation method that determines the optimal utilization of EV temporal flexibility without compromising EV owners’ usage. At the distribution level, DSOs first evaluate EV aggregators’ operational boundaries to exploit distribution level services. At the transmission level, TSOs then determine EV charging schedules and ancillary service capacity simultaneously, taking into account the requirement from DSOs. Here, we validate the model in a case study using the IEEE 123 node test feeder and EV charging sessions obtained from a transportation simulation tool that uses real-world data.
This volume, the first of four volumes, is a collection of 28 unclassified/unlimited-distribution papers which were presented at the Joint Army-Navy-NASA-Air Force (JANNAF) 26th Airbreathing Propulsion Subcommittee (APS) was held jointly with the 38th Combustion Subcommittee (CS), 20th Propulsion Systems Hazards Subcommittee (PSHS), and 2nd Modeling and Simulation Subcommittee. The meeting was held 8-12 April 2002 at the Bayside Inn at The Sandestin Golf & Beach Resort and Eglin Air Force Base, Destin, Florida. Topics covered include: scramjet and ramjet R&D program overviews; tactical propulsion; space access; NASA GTX status; PDE technology; actively cooled engine structures; modeling and simulation of complex hydrocarbon fuels and unsteady processes; and component modeling and simulation.
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