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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 163 records · Page 9
All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Rocket Engine Turbine Blade Surface Pressure Distributions Experiment and Computations

Understanding the unsteady aspects of turbine rotor flow fields is critical to successful future turbine designs. A technology program was conducted at NASA's Marshall Space Flight Center to increase the understanding of unsteady environments for rocket engine turbines. The experimental program involved instrumenting turbine rotor blades with miniature surface mounted high frequency response pressure transducers. The turbine model was then tested to measure the unsteady pressures on the rotor blades. The data obtained from the experimental program is unique in two respects. First, much more unsteady data was obtained (several minutes per set point) than has been possible in the past. Also, an extensive steady performance database existed for the turbine model. This allowed an evaluation of the effect of the on-blade instrumentation on the turbine's performance. A three-dimensional unsteady Navier-Stokes analysis was also used to blindly predict the unsteady flow field in the turbine at the design operating conditions and at +15 degrees relative incidence to the first-stage rotor. The predicted time-averaged and unsteady pressure distributions show good agreement with the experimental data. This unique data set, the lessons learned for acquiring this type of data, and the improvements made to the data analysis and prediction tools are contributing significantly to current Space Launch Initiative turbine airflow test and blade surface pressure prediction efforts.

Hudson, Susan T.↗
DOE OSTI2020

From Atom to Engine: Understanding Fundamental Effects of Structure on Combustion Using Tandem Experiment and Computation

The ability to tie structural features to a fuel candidate’s ignition properties provides a path for rational design of advantaged fuels that facilitate higher-efficiency, lower-emitting combustion in engines. The time evolution of a fuel’s radical population directly correlates with global combustion parameters, and because the generated radicals depend on the initial structure and reaction pathways of the fuel molecule, it follows that the molecular structure of a fuel has a direct impact on this cascade, and therefore salient ignition-tied fuel properties. This work aims to understand the impact of structural features in the context of global combustion properties for direct application to emerging engine technologies. Specifically, we highlight the ability to identify potential fuel blendstocks for specific engine strategies by examining and elucidating the radical cascade tied to ignition. A representative subset of alcohols possessing a variety of structural features (e.g. branching, chain length) was selected for study using a robust combination of experimental and computational methods. The approach begins with identifying short-lived radicals and likely abstraction sites upon pyrolysis in a microreactor coupled with photoionization mass spectrometry for direct detection of product species. In tandem, electronic structure calculations were performed to calculate the relevant potential energy surfaces for fuel pyrolysis as well as the subsequent O2 addition-isomerization reactions, which govern ignition behavior. Furthermore, the theoretical energetic and ro-vibrational data are used to calculate rate constants for direct ignition modeling to explore how structural effects impact NTC behavior. The microreactor data combined with electronic structure theory calculations provide a well-informed picture of the reactions relevant to ignition for each fuel in this study, as well as the most likely radicals generated under engine conditions. This thorough fundamental picture of fuel decomposition and ignition chemistry is used to correlate the observed ignition behavior to molecular structural effects.

advanced biofuels↗
NASA NTRS1995

Sensitivity Analysis and Optimization of Enclosure Radiation with Applications to Crystal Growth

In engineering, simulation software is often used as a convenient means for carrying out experiments to evaluate physical systems. The benefit of using simulations as 'numerical' experiments is that the experimental conditions can be easily modified and repeated at much lower cost than the comparable physical experiment. The goal of these experiments is to 'improve' the process or result of the experiment. In most cases, the computational experiments employ the same trial and error approach as their physical counterparts. When using this approach for complex systems, the cause and effect relationship of the system may never be fully understood and efficient strategies for improvement never utilized. However, it is possible when running simulations to accurately and efficiently determine the sensitivity of the system results with respect to simulation to accurately and efficiently determine the sensitivity of the system results with respect to simulation parameters (e.g., initial conditions, boundary conditions, and material properties) by manipulating the underlying computations. This results in a better understanding of the system dynamics and gives us efficient means to improve processing conditions. We begin by discussing the steps involved in performing simulations. Then we consider how sensitivity information about simulation results can be obtained and ways this information may be used to improve the process or result of the experiment. Next, we discuss optimization and the efficient algorithms which use sensitivity information. We draw on all this information to propose a generalized approach for integrating simulation and optimization, with an emphasis on software programming issues. After discussing our approach to simulation and optimization we consider an application involving crystal growth. This application is interesting because it includes radiative heat transfer. We discuss the computation of radiative new factors and the impact this mode of heat transfer has on our approach. Finally, we will demonstrate the results of our optimization.

Tiller, Michael M.↗
NASA NTRS1988

Flowfield visualization for SSME hot gas manifold

The objective of this research, as defined by NASA-Marshall Space Flight Center, was two-fold: (1) to numerically simulate viscous subsonic flow in a proposed elliptical two-duct version of the fuel side Hot Gas Manifold (HGM) for the Space Shuttle Main Engine (SSME), and (2) to provide analytical support for SSME related numerical computational experiments, being performed by the Computational Fluid Dynamics staff in the Aerophysics Division of the Structures and Dynamics Laboratory at NASA-MSFC. Numerical results of HGM were calculations to complement both water flow visualization experiments and air flow visualization experiments and air experiments in two-duct geometries performed at NASA-MSFC and Rocketdyne. In addition, code modification and improvement efforts were to strengthen the CFD capabilities of NASA-MSFC for producing reliable predictions of flow environments within the SSME.

Roger, Robert P.↗
DOE OSTI2019

Probabilistic Perturbations in Flexible Production Systems

In formulating the engineering principles for flexible production systems, the probabilistic perturbations of their operation must be taken into account. A set of computational experiments based on a special computer application is described. The place of the proposed method in the overall predesign sequence is established.

42 ENGINEERING↗
DOE OSTI2024

Unifying Quantum Materials Modeling and Experiments: The Role of Machine Learning Interatomic Potentials

Computational experiments have emerged as a powerful complement to traditional experiments in the design of new materials. The development of machine learning (ML) and deep learning techniques, combined with database construction and data mining, has significantly enhanced traditional quantum mechanical methods. This synergy enables the rapid development of structure-property relationships. In this talk, I will discuss our recent efforts in applying Machine Learning Interatomic Potentials (MLIAPs) to accelerate materials modeling across various material classes and challenging applications where traditional methods fall short. First, I will highlight the success of MLIAPs in accurately modeling the melting behavior of complex materials. Our results demonstrate high fidelity with experimental observations and also with calculated reference melting temperatures. In the second application, I will discuss how MLIAPs are trained and applied to elucidate the interplay between segregation tendencies and surface reconstructions in CuNi alloys under oxidizing conditions. A key factor in the success of these MLIAP applications is the design of minimalistic yet flexible datasets along with a computational framework for training MLIAPs.

Saidi, Wissam↗
NASA NTRS1978

Man/terminal interaction evaluation of computer operating system command and control service concepts

The Experiment Computer Operating System (ECOS) of the Spacelab will allow the onboard Payload Specialist to command experiment devices and display information relative to the performance of experiments. Three candidate ECOS command and control service concepts were reviewed and laboratory data on operator performance was taken for each concept. The command and control service concepts evaluated included a dedicated operator's menu display from which all command inputs were issued, a dedicated command key concept with which command inputs could be issued from any display, and a multi-display concept in which command inputs were issued from several dedicated function displays. Advantages and disadvantages are discussed in terms of training, operational errors, task performance time, and subjective comments of system operators.

Dodson, D. W.↗
NASA NTRS1991

Scaling analysis applied to the NORVEX code development and thermal energy flight experiment

A scaling analysis is used to study the dominant flow processes that occur in molten phase change material (PCM) under 1 g and microgravity conditions. Results of the scaling analysis are applied to the development of the NORVEX (NASA Oak Ridge Void Experiment) computer program and the preparation of the Thermal Energy Storage (TES) flight experiment. The NORVEX computer program which is being developed to predict melting and freezing with void formation in a 1 g or microgravity environment of the PCM is described. NORVEX predictions are compared with the scaling and similarity results. The approach to be used to validate NORVEX with TES flight data is also discussed. Similarity and scaling show that the inertial terms must be included as part of the momentum equation in either the 1 g or microgravity environment (a creeping flow assumption is invalid). A 10(exp -4) environment was found to be a suitable microgravity environment for the proposed PCM.

Skarda, J. Raymond Lee↗
NASA NTRS1991

Scaling analysis applied to the NORVEX code development and thermal energy flight experiment

A scaling analysis is used to study the dominant flow processes that occur in molten phase change material (PCM) under 1 g and microgravity conditions. Results of the scaling analysis are applied to the development of the NORVEX (NASA Oak Ridge Void Experiment) computer program and the preparation of the Thermal Energy Storage (TES) flight experiment. The NORVEX computer program which is being developed to predict melting and freezing with void formation in a 1 g or microgravity environment of the PCM is described. NORVEX predictions are compared with the scaling and similarity results. The approach to be used to validate NORVEX with TES flight data is also discussed. Similarity and scaling show that the inertial terms must be included as part of the momentum equation in either the 1 g or microgravity environment (a creeping flow assumption is invalid). A 10(exp -4) environment was found to be a suitable microgravity environment for the proposed PCM.

Skarda, J. R. L.↗
NASA NTRS1997

Quelling Cabin Noise in Turboprop Aircraft via Active Control

Cabin noise in turboprop aircraft causes passenger discomfort, airframe fatigue, and employee scheduling constraints due to OSHA standards for exposure to high levels of noise. The noise levels in the cabins of turboprop aircraft are typically 10 to 30 decibels louder than commercial jet noise levels. However. unlike jet noise the turboprop noise spectrum is dominated by a few low frequency tones. Active structural acoustic control is a method in which the control inputs (used to reduce interior noise) are applied directly to a vibrating structural acoustic system. The control concept modeled in this work is the application of in-plane force inputs to piezoceramic patches bonded to the wall of a vibrating cylinder. The goal is to determine the force inputs and locations for the piezoceramic actuators so that: (1) the interior noise is effectively damped; (2) the level of vibration of the cylinder shell is not increased; and (3) the power requirements needed to drive the actuators are not excessive. Computational experiments for data taken from a computer generated model and from a laboratory test article at NASA Langley Research Center are provided.

Kincaid, Rex K.↗
NASA NTRS1989

Transonic Symposium: Theory, Application and Experiment, volume 2

Papers presented at the Transonic Symposium are compiled. The following subject areas are covered: National Transonic Facility status; transonic aerodynamics of slender wing-body configuration; laminar flow flight experiments; laminar flow wind tunnel experiments; computational support of X-29A flight experiment; transition location on a clean-up glove installed on a F-14 aircraft; and design studies for a laminar glove for the X-29 aircraft.

Foughner, Jerome T., Jr.↗
DOE OSTI2025

Bayesian D‐Optimal Designs for Gaussian Process Surrogate Models

Computer experiments often employ space-filling strategies to create surrogate models with strong predictive performance. The impact of model parameter estimation for Gaussian process surrogates, however, is often overlooked. Obtaining a better initial estimate of the covariance lengthscale parameter, θ, can greatly improve the resulting Gaussian process fit through more effective sequential acquisitions during active learning. In this work, we propose a novel initial design maximizing the Bayesian D-optimality criterion of the Gaussian process lengthscale parameter. Previously published results have shown the emphasis on lengthscale estimation to be promising, but relied on an empirically driven design creation process. Our Bayesian D-optimal designs are rooted in information theory and lead to more informative sequential acquisitions by improving lengthscale estimation. In many cases, these gains eventually result in better surrogates than those seeded with space-filling initial designs. Furthermore, Bayesian D-optimal designs can be tailored to either isotropic or anisotropic covariance structures, and the Bayesian framework enables the inclusion of prior knowledge in the design process, offering greater flexibility and adaptability. Through several simulation studies, we demonstrate the advantages of Bayesian D-optimal designs in terms of both lengthscale estimation accuracy and predictive performance during active learning.

Bayesian experimental design↗
DOE OSTI2019

Decomposing the Train-Scheduling Problem into Integer-Optimal Polytopes

This paper presents conditions for which the linear relaxation for the train-scheduling problem is integer optimal. These conditions are then used to identify how to partition a general problem’s feasible region into integer-optimal polytopes. Such an approach yields an extended formulation that contains far fewer binary variables. Our computational experiments show that this approach results in significant computational savings. Moreover, this approach scales well when the train-scheduling problem is modeled using smaller time increments, allowing for higher fidelity models to be solved without significantly increasing the required computational time.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1978

Space Transportation System/Spacelab accommodations

A description is provided of the capabilities offered by the Spacelab design for doing research in space. The Spacelab flight vehicle consists of two basic elements including the habitable pressurized compartments and the unpressurized equipment mounting platforms. Spacelab services to payloads are considered, taking into account payload mass, electrical power and energy, heat rejection for Spacelab and payload, aspects of Spacelab data handling, and the extended flight capability. Attention is also given to the Spacelab structure, crew station and habitability, the electrical power distribution subsystem, the command and data management subsystem, the experiment computer operating system, the environmental control subsystem, the experiment vent assembly, the common payload support equipment, the instrument pointing subsystem, and details concerning the utilization of Spacelab.

De Sanctis, C. E.↗
NASA NTRS1993

The middeck 0-gravity dynamics experiment

The Middeck 0-Gravity Dynamics Experiment (MODE), flown onboard the Shuttle STS-48 Mission, consists of three major elements: the Experiment Support Module, a dynamics test bed providing computer experiment control, analog signal conditioning, power conditioning, an operator interface consisting of a keypad and display, experiment electrical and thermal control, and archival data storage: the Fluid Test Article assembly, used to investigate the dynamics of fluid-structure interaction in 0-gravity; and the Structural Test Article for investigating the open-loop dynamics of structures in 0-gravity. Deployable, erectable, and rotary modules were assembled to form three one- and two-dimensional structures, in which variations in bracing wire and rotary joint preload could be introduced. Change in linear modal parameters as well as the change in nonlinear nature of the response is examined. Trends in modal parameters are presented as a function of force amplitude, joint preload, and ambient gravity. An experimental study of the lateral slosh behavior of contained fluids is also presented. A comparison of the measured earth and space results identifies and highlights the effects of gravity on the linear and nonlinear slosh behavior of these fluids.

Crawley, Edward F.↗