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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 1,225 records · Page 68
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

An investigation of design optimization using a 2-D viscous flow code with multigrid

Computational fluid dynamics (CFD) codes have advanced to the point where they are effective analytical tools for solving flow fields around complex geometries. There is also a need for their use as a design tool to find optimum aerodynamic shapes. In the area of design, however, a difficulty arises due to the large amount of computer resources required by these codes. It is desired to streamline the design process so that a large number of design options and constraints can be investigated without overloading the system. There are several techniques which have been proposed to help streamline the design process. The feasibility of one of these techniques is investigated. The technique under consideration is the interaction of the geometry change with the flow calculation. The problem of finding the value of camber which maximizes the ratio of lift over drag for a particular airfoil is considered. In order to test out this technique, a particular optimization problem was tried. A NACA 0012 airfoil was considered at free stream Mach number of 0.5 with a zero angle of attack. Camber was added to the mean line of the airfoil. The goal was to find the value of camber for which the ratio of lift over drag is a maximum. The flow code used was FLOMGE which is a two dimensional viscous flow solver which uses multigrid to speed up convergence. A hyperbolic grid generation program was used to construct the grid for each value of camber.

Doria, Michael L.↗
NASA NTRS2016

Development and Use of Engineering Standards for Computational Fluid Dynamics for Complex Aerospace Systems

Computational fluid dynamics (CFD) and other advanced modeling and simulation (M&S) methods are increasingly relied on for predictive performance, reliability and safety of engineering systems. Analysts, designers, decision makers, and project managers, who must depend on simulation, need practical techniques and methods for assessing simulation credibility. The AIAA Guide for Verification and Validation of Computational Fluid Dynamics Simulations (AIAA G-077-1998 (2002)), originally published in 1998, was the first engineering standards document available to the engineering community for verification and validation (V&V) of simulations. Much progress has been made in these areas since 1998. The AIAA Committee on Standards for CFD is currently updating this Guide to incorporate in it the important developments that have taken place in V&V concepts, methods, and practices, particularly with regard to the broader context of predictive capability and uncertainty quantification (UQ) methods and approaches. This paper will provide an overview of the changes and extensions currently underway to update the AIAA Guide. Specifically, a framework for predictive capability will be described for incorporating a wide range of error and uncertainty sources identified during the modeling, verification, and validation processes, with the goal of estimating the total prediction uncertainty of the simulation. The Guide's goal is to provide a foundation for understanding and addressing major issues and concepts in predictive CFD. However, this Guide will not recommend specific approaches in these areas as the field is rapidly evolving. It is hoped that the guidelines provided in this paper, and explained in more detail in the Guide, will aid in the research, development, and use of CFD in engineering decision-making.

Lee, Hyung B.↗
NASA NTRS2003

Aerosciences, Aero-Propulsion and Flight Mechanics Technology Development for NASA's Next Generation Launch Technology Program

The Next Generation Launch Technology (NGLT) program, Vehicle Systems Research and Technology (VSR&T) project is pursuing technology advancements in aerothermodynamics, aeropropulsion and flight mechanics to enable development of future reusable launch vehicle (RLV) systems. The current design trade space includes rocket-propelled, hypersonic airbreathing and hybrid systems in two-stage and single-stage configurations. Aerothermodynamics technologies include experimental and computational databases to evaluate stage separation of two-stage vehicles as well as computational and trajectory simulation tools for this problem. Additionally, advancements in high-fidelity computational tools and measurement techniques are being pursued along with the study of flow physics phenomena, such as boundary-layer transition. Aero-propulsion technology development includes scramjet flowpath development and integration, with a current emphasis on hypervelocity (Mach 10 and above) operation, as well as the study of aero-propulsive interactions and the impact on overall vehicle performance. Flight mechanics technology development is focused on advanced guidance, navigation and control (GN&C) algorithms and adaptive flight control systems for both rocket-propelled and airbreathing vehicles.

Cockrell, Charles E., Jr.↗
NASA NTRS2003

Changing the Paradigm: Preparing Students for the Computing Profession in the 21st Century

The dramatic technological developments of the past decade have led to a tremendous growth in the demand for computer science professionals well-versed in advanced technology and techniques. NASA, traditionally a haven for cutting-edge innovators, is now competing with every industrial and government sector for computer science talent. The computer science program at University of Texas at San Antonio (UTSA) faces challenges beyond those intrinsically presented by rapid technological change, because a significant number of UTSA students come from low-income families with no Internet or computer access at home. An examination of enrollment statistics for the computer science program at UTSA showed that very few students who entered as freshmen successfully graduated. The upper division courses appeared to be populated by graduate students removing deficiencies and by transfer students. The faculty was also concerned that the students who did graduate from the program did not have the strong technical and programming skills that the CS program had been noted for in the community during the 1980's.

Robbins, Kay A.↗
NASA NTRS1993

Computation of flows in a turn-around duct and a turbine cascade using advanced turbulence models

Numerical investigation has been carried out to evaluate the capability of the Algebraic Reynolds Stress Model (ARSM) and the Nonlinear Stress Model (NLSM) to predict strongly curved turbulent flow in a turn-around duct (TAD). The ARSM includes the near-wall damping term of pressure-strain correlation phi(sub ij,w), which enables accurate prediction of individual Reynolds stress components in wall flows. The TAD mean flow quantities are reasonably well predicted by various turbulence models. The ARSM yields better predictions for both the mean flow and the turbulence quantities than the NLSM and the k-epsilon (k = turbulent kinetic energy, epsilon = dissipation rate of k) model. The NLSM also shows slight improvement over the k-epsilon model. However, all the models fail to capture the recovery of the flow from strong curvature effects. The formulation for phi(sub ij,w) appears to be incorrect near the concave surface. The hybrid k-epsilon/ARSM, Chien's k-epsilon model, and Coakley's q-omega (q = the square root of k, omega = epsilon/k) model have also been employed to compute the aerodynamics and heat transfer of a transonic turbine cascade. The surface pressure distributions and the wake profiles are predicted well by all the models. The k-epsilon model and the k-epsilon/ARSM model provide better predictions of heat transfer than the q-omega model. The k-epsilon/ARSM solutions show significant differences in the predicted skin friction coefficients, heat transfer rates and the cascade performance parameters, as compared to the k-epsilon model. The k-epsilon/ARSM model appears to capture, qualitatively, the anisotropy associated with by-pass transition.

Lakshminarayana, B.↗
NASA NTRS2022

A Robust Machine Learning Schema for Developing, Maintaining, and Disseminating Machine Learning Models

Recent advances in the development of machine learning (ML) algorithms have enabled the creation of predictive models that can improve decision making, decrease computational cost, and improve efficiency in a variety of fields. As an organization begins to develop and implement such models, the data used in the training, validation, and testing of ML models, the model parameters, and the use cases or limitations of the models must be properly stored to ensure models are both fully traceable and used correctly. In the context of predicting material behavior, advances in computationally intense, physics-based modeling of material behavior at various length scales and the emergence of Integrated Computational Materials Engineering (ICME) have driven the need for developing data-driven surrogate models of the physics-based simulation tools using ML techniques. Surrogate model development allows for accurate material behavior prediction at a fraction of the cost of its physics-based counterpart, allowing for multiscale simulations of real-world applications, further enabling the ability to design fit-for-purpose materials for a reasonable computational investment. However, training such models requires extensive data, and thus, effective data management is necessary to reach the full potential that ML can offer to material design and ICME. This paper proposes a generalized, robust schema that allows organizations to store both real (experimental) and virtual (simulation) data used to train ML models and the defining model parameters and architectures within the Granta MI Platform. The developed schema allows for various types of data inputs and outputs, including single point values, time-series data, and images that can be used in the prediction of material behavior, while following outlined best practices for effective data management. An effective schema for ML data and models can help prevent the recreation of virtual/real training data and surrogate models, help reduce the time to create new models similar to existing ones by offering a starting point in the hyperparameter determination stages, minimize resources devoted to verification and validation (V&V) and certification of models, and ensure that data and surrogate models are not misused due to full traceability of both the data and ML model. It also allows organizations access to models that have already been developed, such that they can be used in the design of new materials, enabling the overall goals of ICME.

Brandon L. Hearley↗
NASA NTRSDate not supplied

Predicting Fiber Failure of Plain Weave Fabric with Recursive Multiscale Micromechanics

Recent advances in the development of machine learning (ML) algorithms have enabled the creation of predictive models that can improve decision making, decrease computational cost, and improve efficiency in a variety of fields. As an organization begins to develop and implement such models, the data used in the training, validation, and testing of machine learning models, the model parameters, and the use cases or limitations of the models must be properly stored to ensure models are both fully traceable and used correctly. In the context of predicting material behavior, advances in computationally intense, physics-based, modeling of material behavior at various length scales, and the emergence of Integrated Computational Materials Engineering (ICME) have driven the need for developing data-driven surrogate models of the physics-based simulation tools using machine learning (ML) techniques. Surrogate model development allows for accurate material behavior prediction at a fraction of the cost of its physics-based counterpart, allowing for multiscale simulations of real-world applications, further enabling the ability to design fit-for-purpose materials for a reasonable computational investment. However, training such models requires extensive data, and thus effective data management is necessary to reach the full potential that ML can offer to material design and ICME. This paper proposes a generalized, robust schema that allows organizations to store both real (experimental) and virtual (simulation) data used to train machine learning models and the defining model parameters and architectures. The developed schema allows for various types of data inputs and outputs, including single point values, time-series data, and images that can be used in for various types of machine learning models while following outlined best practices for effective data management. An effective schema for machine learning data and models can help prevent the recreation of virtual/real training data and surrogate models, can help reduce the time to create new models similar to existing ones by offering a starting point in the hyperparameter determination stages, minimize resources devoted to verification and validation (V&V) and certification of models, and ensure that data and surrogate models are not misused due to full traceability of both the data and ML model. It also allows organizations access to models that have already been developed, such that they can be used in the design of new materials, enabling the overall goals of ICME.

Failure↗
NASA NTRS1991

ISE advanced technology

Information on Space Station Freedom scheduling problems and techniques are presented in viewgraph form. Topics covered include automated scheduling systems, user interface standards, benefits of interactive scheduling systems, incremental scheduling, software engineering, computer graphics interface, distributed resource management, and advanced applications.

Fox, Barry R.↗
NASA NTRS2023

Distributed Quantum Processing via Integrated Regional Quantum Networks Using Free-Space Optical Links

The landscape for quantum computing is rapidly evolving with the development of quantum computers and the emergence of future science enabling applications being pursued in many areas, such as distributed quantum computing, hybrid computing scenarios that require cooperatively networked quantum and classical computing assets and more. Quantum networking is also advancing with multiple regional quantum networks and testbeds maturing across the nation. These quantum networking testbeds typically include multiple access points with a heterogeneous mixture of capabilities interconnected by fiber spanning anywhere from tens to hundreds of kilometers; many such networks incorporate a classical networking framework. Alongside these connectivity advancements in the infrastructure, there is quantum sensing device and component technology maturation that is serving to expand the body of quantum networking scenarios that are presently possible and redefining the quantum- enabled future. Bridging the present collective progress in quantum computing and quantum networking will enable the next era of purposeful advancements for national priority use-cases for the benefit of science. One such use-case is enabling future quantum computing applications via integrated regional quantum networking infrastructure in neighboring locations like New York and Maryland, both states are home to robust classical and quantum networking capabilities. To enable near-term distributed quantum computing applications via the practical integration of regional quantum networking infrastructure, free-space optical links via satellite communications will be essential to avoid the exponential loss commonly observed with fiber implementations. There is both an urgent need and a practical justification for pursuing such space-based integration scope now.

Harry Shaw↗
NASA NTRS1992

Advanced large scale GaAs monolithic IF switch matrix subsystem

Attention is given to a novel chip design and packaging technique to overcome the limitations due to the high signal isolation requirements of advanced communications systems. A hermetically sealed 6 x 6 monolithic GaAs switch matrix subsystem with integral control electronics based on this technique is presented. An 0-dB insertion loss and 60-dB crosspoint isolation over a 3.5-to-6-GHz band were achieved. The internal controller portion of the switching subsystem provides crosspoint control via a standard RS-232 computer interface and can be synchronized with an external systems control computer. The measured performance of this advanced switching subsystem is fully compatible with relatively static 'switchboard' as well as dynamic TDMA modes of operation.

Ch'en, D. R.↗
NASA NTRS1992

A probabilistic approach to the evaluation of fatigue damage in a space propulsion system injector element

The fatigue damage of a space propulsion system component is computed using probabilistic structural analysis methods. The analysis takes into account the variations in static and dynamic loads, the uncertainty in structural damping, and the scatter in material fatigue resistance. The key elements of the probabilistic approach include: (1) a numerical engine model for describing the global component interface loads consistent with engine balance, (2) models for computing the local mode boundary conditions on the component, (3) a static structural analysis model that captures the strains at a damage critical location as a function of engine performance variables, (4) a finite element model for assessment of the random amplitude stress response due to random base and pressure excitations with uncertain power and correlation length, and (5) advanced first order reliability methods for computing the probabilities associated with the fatigue damage.

Rajagopal, K. R.↗
NASA NTRS2016

Boeing Smart Rotor Full-scale Wind Tunnel Test Data Report

A full-scale helicopter smart material actuated rotor technology (SMART) rotor test was conducted in the USAF National Full-Scale Aerodynamics Complex 40- by 80-Foot Wind Tunnel at NASA Ames. The SMART rotor system is a five-bladed MD 902 bearingless rotor with active trailing-edge flaps. The flaps are actuated using piezoelectric actuators. Rotor performance, structural loads, and acoustic data were obtained over a wide range of rotor shaft angles of attack, thrust, and airspeeds. The primary test objective was to acquire unique validation data for the high-performance computing analyses developed under the Defense Advanced Research Project Agency (DARPA) Helicopter Quieting Program (HQP). Other research objectives included quantifying the ability of the on-blade flaps to achieve vibration reduction, rotor smoothing, and performance improvements. This data set of rotor performance and structural loads can be used for analytical and experimental comparison studies with other full-scale rotor systems and for analytical validation of computer simulation models. The purpose of this final data report is to document a comprehensive, highquality data set that includes only data points where the flap was actively controlled and each of the five flaps behaved in a similar manner.

Full-Scale Wind Tunnel↗
NASA NTRS1984

Inlet flowfield investigation. Part 2: Computation of the flow about a supercruise forebody at supersonic speeds

A numerical procedure which solves the parabolized Navier-Stokes (PNS) equations on a body fitted mesh was used to compute the flow about the forebody of an advanced tactical supercruise fighter configuration in an effort to explore the use of a PNS method for design of supersonic cruise forebody geometries. Forebody flow fields were computed at Mach numbers of 1.5, 2.0, and 2.5, and at angles-of-attack of 0 deg, 4 deg, and 8 deg. at each Mach number. Computed results are presented at several body stations and include contour plots of Mach number, total pressure, upwash angle, sidewash angle and cross-plane velocity. The computational analysis procedure was found reliable for evaluating forebody flow fields of advanced aircraft configurations for flight conditions where the vortex shed from the wing leading edge is not a dominant flow phenomenon. Static pressure distributions and boundary layer profiles on the forebody and wing were surveyed in a wind tunnel test, and the analytical results are compared to the data. The current status of the parabolized flow flow field code is described along with desirable improvements in the code.

Paynter, G. C.↗
NASA NTRS1984

Space systems computer-aided design technology

The interactive Design and Evaluation of Advanced Spacecraft (IDEAS) system is described, together with planned capability increases in the IDEAS system. The system's disciplines consist of interactive graphics and interactive computing. A single user at an interactive terminal can create, design, analyze, and conduct parametric studies of earth-orbiting satellites, which represents a timely and cost-effective method during the conceptual design phase where various missions and spacecraft options require evaluation. Spacecraft concepts evaluated include microwave radiometer satellites, communication satellite systems, solar-powered lasers, power platforms, and orbiting space stations.

Garrett, L. B.↗
NASA NTRS2003

Enhancement and Extension of Porosity Model in the FDNS-500 Code to Provide Enhanced Simulations of Rocket Engine Components

In the past, the design of rocket engines has primarily relied on the cold flow/hot fire test, and the empirical correlations developed based on the database from previous designs. However, it is very costly to fabricate and test various hardware designs during the design cycle, whereas the empirical model becomes unreliable in designing the advanced rocket engine where its operating conditions exceed the range of the database. The main goal of the 2nd Generation Reusable Launching Vehicle (GEN-II RLV) is to reduce the cost per payload and to extend the life of the hardware, which poses a great challenge to the rocket engine design. Hence, understanding the flow characteristics in each engine components is thus critical to the engine design. In the last few decades, the methodology of computational fluid dynamics (CFD) has been advanced to be a mature tool of analyzing various engine components. Therefore, it is important for the CFD design tool to be able to properly simulate the hot flow environment near the liquid injector, and thus to accurately predict the heat load to the injector faceplate. However, to date it is still not feasible to conduct CFD simulations of the detailed flowfield with very complicated geometries such as fluid flow and heat transfer in an injector assembly and through a porous plate, which requires gigantic computer memories and power to resolve the detailed geometry. The rigimesh (a sintered metal material), utilized to reduce the heat load to the faceplate, is one of the design concepts for the injector faceplate of the GEN-II RLV. In addition, the injector assembly is designed to distribute propellants into the combustion chamber of the liquid rocket engine. A porosity mode thus becomes a necessity for the CFD code in order to efficiently simulate the flow and heat transfer in these porous media, and maintain good accuracy in describing the flow fields. Currently, the FDNS (Finite Difference Navier-Stakes) code is one of the CFD codes which are most widely used by research engineers at NASA Marshall Space Flight Center (MSFC) to simulate various flow problems related to rocket engines. The objective of this research work during the 10-week summer faculty fellowship program was to 1) debug the framework of the porosity model in the current FDNS code, and 2) validate the porosity model by simulating flows through various porous media such as tube banks and porous plate.

Cheng, Gary↗
NASA NTRS1991

Conjugate Gradient Algorithms For Manipulator Simulation

Report discusses applicability of conjugate-gradient algorithms to computation of forward dynamics of robotic manipulators. Rapid computation of forward dynamics essential to teleoperation and other advanced robotic applications. Part of continuing effort to find algorithms meeting requirements for increased computational efficiency and speed. Method used for iterative solution of systems of linear equations.

Fijany, Amir↗
NASA NTRS1999

Overview on NASA's Advanced Electric Propulsion Concepts Activities

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.

Frisbee, Robert H.↗
NASA NTRS1991

Computational fluid dynamics studies of nuclear rocket performance

A CFD analysis of a low pressure nuclear rocket concept is presented with the use of an advanced chemical kinetics, Navier-Stokes code. The computations describe the flow field in detail,including gas dynamic, thermodynamic and chemical properties, as well as global performance quantities such as specific impulse. Computational studies of several rocket nozzle shapes are conducted in an attempt to maximize hydrogen recombination. These Navier-Stokes calculations, which include real gas and viscous effects, predict lower performance values than have been reported heretofore.

Stubbs, Robert M.↗