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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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Cross-Facility Orchestration of Electrochemistry Experiments and Computations
Instrument-computing ecosystems supporting automated electrochemical workflows typically require the integration of disparate instruments such as syringe pump, fraction collector, and potentiostat, all connected to an electrochemical cell. These specialized instruments with custom software and interfaces are not typically designed for network integration and remote automation. We developed a networked ecosystem of these instruments and computing platforms, which includes software to enable automated workflow orchestration from remote computers. Specifically, we developed Python wrappers of APIs and custom Pyro client-server modules to support remote operation of these instruments over the ecosystem network. Herein, we describe a specific workflow for generating and validating voltammogram (I-V) measurements of an electrolyte solution pumped into the electrochemical cell. We demonstrate the orchestration of this workflow which is composed using a Jupyter notebook and executed on a remote computer.
Uniting Experiment and Computational Modeling to Elucidate Structure-Property Relationships of Water Splitting Materials.
Abstract not provided.
Towards Z-Next: The Integration of Theory, Experiments, and Computational Simulation in a Bayesian Data Assimilation Framework
Making reliable predictions in the presence of uncertainty is critical to high-consequence modeling and simulation activities, such as those encountered at Sandia National Laboratories. Surrogate or reduced-order models are often used to mitigate the expense of performing quality uncertainty analyses with high-fidelity, physics-based codes. However, phenomenological surrogate models do not always adhere to important physics and system properties. This project develops surrogate models that integrate physical theory with experimental data through a maximally-informative framework that accounts for the many uncertainties present in computational modeling problems. Correlations between relevant outputs are preserved through the use of multi-output or co-predictive surrogate models; known physical properties (specifically monotoncity) are also preserved; and unknown physics and phenomena are detected using a causal analysis. By endowing surrogate models with key properties of the physical system being studied, their predictive power is arguably enhanced, allowing for reliable simulations and analyses at a reduced computational cost.
Uniting Experiment and Computational Modeling to Elucidate Structure-Property Relationships of Water Splitting Materials.
Abstract not provided.
Magnetized Liner Inertial Fusion: Developing a data-driven understanding of magnetic flux compression from computation through experiment.
Abstract not provided.
CFD Validation at Sandia National Labs: Collaborations Between Experiments and Computations
Provides an overview of recent collaborations between SNLs wind tunnel and CFD teams.
Experiments on computer recognition of con- nected handwritten words
Computer recognition of handwritten words
Experiments on computer recognition of connected handwritten words.
Computer recognition of connected handwritten words by stroke decomposition
Flowfield scaling of a swept compression corner interaction A comparison of experiment and computation
Over the past decade, there has been some important progress in understanding the problems of three-dimensional (3D) shock wave/turbulent boundary layer interactions. However, the problems are by no means solved. The present investigation has the objective to determine the flowfield structure of a swept compression corner interaction and to perform a test of an equation considered by Settles and Bogdonoff (1982). The experimental data obtained in a 20 x 20 cm high Reynolds number supersonic wind tunnel are compared with the predictions of a state-of-the-art numerical solution of the Navier-Stokes equations. It is found that a 3D scaling law for Reynolds number effects, previously established for interaction 'footprints', is equally valid when applied to the present flowfield.
Hypersonic shock-wave turbulent-boundary-layer interaction flows - Experiment and computation
Solutions of the Reynolds-averaged Navier-Stokes equations are presented and compared with experimental surface data for a series of hypersonic shock-wave/turbulent-boundary-layer interaction flows. The turbulence models used include the standard k-epsilon two-equation eddy viscosity model, a two-layer modification to this model, and a third model with several modifications to account for compressibility effects. Both modified models gave significant improvements for all the test flows.
Flow over an all-body hypersonic aircraft - Experiment and computation
The objective of the present investigation is to establish a benchmark experimental data base for a generic hypersonic vehicle shape for validation and/or calibration of advanced computational fluid dynamics computer codes. This paper includes results from the comprehensive test program conducted in the NASA Ames 3.5-ft Hypersonic Wind Tunnel for a generic all-body hypersonic aircraft model. Experimental and computational results on flow visualization, surface pressures, surface convective heat transfer, and pilot-pressure flowfield surveys are presented. Comparisons of the experimental results with computational results from an upwind parabolized Navier-Stokes code developed at NASA Ames demonstrate the capabilities of this code.
Growth Characteristics Downstream of a Shallow Bump: Computation and Experiment
Measurements of the velocity field created by a shallow bump on a wall revealed that an energy peak in the spanwise spectrum associated with the driver decays and an initially small-amplitude secondary mode rapidly grows with distance downstream of the bump. Linear theories could not provide an explanation for this growing mode. The present Navier-Stokes simulation replicates and confirms the experimental results. Insight into the structure of the flow was obtained from a study of the results of the calculations and is presented.
A Sample of NASA Langley Unsteady Pressure Experiments for Computational Aerodynamics Code Evaluation
As computational fluid dynamics methods mature, code development is rapidly transitioning from prediction of steady flowfields to unsteady flows. This change in emphasis offers a number of new challenges to the research community, not the least of which is obtaining detailed, accurate unsteady experimental data with which to evaluate new methods. Researchers at NASA Langley Research Center (LaRC) have been actively measuring unsteady pressure distributions for nearly 40 years. Over the last 20 years, these measurements have focused on developing high-quality datasets for use in code evaluation. This paper provides a sample of unsteady pressure measurements obtained by LaRC and available for government, university, and industry researchers to evaluate new and existing unsteady aerodynamic analysis methods. A number of cases are highlighted and discussed with attention focused on the unique character of the individual datasets and their perceived usefulness for code evaluation. Ongoing LaRC research in this area is also presented.
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.
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.
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.
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.