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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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The role of experiment in Computational Fluid Dynamics (CFD) is discussed. Flow modeling of complex physics and determination of accuracy limits (confidence) are two ways in which experimentation can be used to develop CFD. The results of this discussion are presented in viewgraph form.
The dynamics of liquid drops rotating in another liquid were studied experimentally with an oil drop suspended in a neutral buoyancy tank. New stable shapes not predicted by the theory were observed.
Computational fluid dynamics (CFD) tools have been used extensively in the analysis and development of the X-43A Hyper-X Research Vehicle (HXRV). A significant element of this analysis is the prediction of integrated vehicle aero-propulsive performance, which includes an integration of aerodynamic and propulsion flow fields. This paper describes analysis tools used and the methodology for obtaining pre-flight predictions of longitudinal performance increments. The use of higher-fidelity methods to examine flow-field characteristics and scramjet flowpath component performance is also discussed. Limited comparisons with available ground test data are shown to illustrate the approach used to calibrate methods and assess solution accuracy. Inviscid calculations to evaluate lateral-directional stability characteristics are discussed. The methodology behind 3D tip-to-tail calculations is described and the impact of 3D exhaust plume expansion in the afterbody region is illustrated. Finally, future technology development needs in the area of hypersonic propulsion-airframe integration analysis are discussed.
This paper presents viewgraphs of NASA's strategic and fundamental research program at the Office of Biological and Physical Research (OBPR). The topics include: 1) Colloid-Polymer Samples; 2) Pool Boiling Experiment; 3) The Dynamics of Miscible Interfaces: A Space Flight Experiment (MIDAS); and 4) ISS and Ground-based Facilities.
Traditional human reliability analysis (HRA) methods have difficulty dealing with the dynamic nature of factors such as time and rely on static and expert-judgment-based assessments of performance-shaping factors (PSFs) across limited levels. In this study, we introduce a mathematical approach for dynamically evaluating the experience and training PSF. Our proposed method integrates the psychological concept of the “forgetting curve” to evaluate how PSFs are impacted by the number of trainings and the time elapsed since training. To confirm the validity of the model, we provide experimental data fitted by identifying the quantitative relationship between training and human performance. This research enables dynamic and objective assessments, thus reducing reliance on subjective expert judgment and improving the accuracy of HRA.
Predicting the proximity of large-scale dynamic failure is a critical concern in the engineering and geophysical sciences. Here we use evolving contractive, dilatational, and shear strain deformation preceding failure in dynamic X-ray tomography experiments to examine which strain components best predict the proximity to failure. We develop machine learning models to predict the proximity to failure using time series of three-dimensional local incremental strain tensor fields acquired in rock deformation experiments under stress conditions of the upper crust. Three-dimensional scans acquired in situ throughout triaxial compression experiments provide a distribution of density contrasts from which we estimate the three-dimensional incremental strain that accumulates between each scan acquisition. Training machine learning models on multiple experiments of six rock types provides suites of feature importance that indicate the predictive power of each feature. Comparing the average importance of groups of features that include information about each strain component quantifies the ability of the contractive, dilatational and shear strain to predict the proximity of macroscopic failure. A total of 24 models of four machine learning algorithms with six rock types indicate that 1) the dilatational strain provides the best predictive power of the strain components, and 2) the intermediate values (25th-75th percentile) of the strain population provide the best predictive power of the statistics of the strain populations. In addition, the success of the predictions of models trained on one rock type and tested on other rock types quantifies the similarities and differences of the precursory strain accumulation process in the six rock types. These similarities suggest the potential existence of a unified theory of brittle rock deformation for a range of rock types.
The pressure and temperature conditions at which precipitation of diamond occurs from hydrocarbon mixtures is important for modelling the interior dynamics of icy planets. However, there is substantial disagreement from laboratory experiments, with those using dynamic compression techniques finding much more extreme conditions are required than in static compression. Here we report the time-resolved observation of diamond formation from statically compressed polystyrene, (C 8 H 8 ) n , heated using the 4.5 MHz X-ray pulse trains at the European X-ray Free Electron Laser facility. Diamond formation is observed above 2,500 K from 19 GPa to 27 GPa, conditions representative of Uranus’s and Neptune’s shallow interiors, on 30 μs to 40 μs timescales. This is much slower than may be observed during the ~10 ns duration of typical dynamic compression experiments, revealing reaction kinetics to be the reason for the discrepancy. In conclusion, reduced pressure and temperature conditions for diamond formation has implications for icy planetary interiors, where diamond subduction leads to heating and could drive convection in the conductive ice layer that has a role in their magnetic fields.
Ever since computations have been used to simulate aerodynamics the need to ensure that the computations adequately represent real life has followed. Many experiments have been performed specifically for validation and as computational methods have improved, so have the validation experiments. Validation is also a moving target because computational methods improve requiring validation for the new aspect of flow physics that the computations aim to capture. Concurrently, new measurement techniques are being developed that can help capture more detailed flow features pressure sensitive paint (PSP) and particle image velocimetry (PIV) come to mind. This paper will present various wind-tunnel tests the author has been involved with and how they were used for validation of various kinds of CFD. A particular focus is the application of advanced measurement techniques to flow fields (and geometries) that had proven to be difficult to predict computationally. Many of these difficult flow problems arose from engineering and development problems that needed to be solved for a particular vehicle or research program. In some cases the experiments required to solve the engineering problems were refined to provide valuable CFD validation data in addition to the primary engineering data. All of these experiments have provided physical insight and validation data for a wide range of aerodynamic and acoustic phenomena for vehicles ranging from tractor-trailers to crewed spacecraft.
Design of Experiments (DOE) techniques were applied to the Launch Abort System (LAS) of the NASA Crew Exploration Vehicle (CEV) parametric geometry Computational Fluid Dynamics (CFD) study to efficiently identify and rank the primary contributors to the integrated drag over the vehicles ascent trajectory. Typical approaches to these types of activities involve developing all possible combinations of geometries changing one variable at a time, analyzing them with CFD, and predicting the main effects on an aerodynamic parameter, which in this application is integrated drag. The original plan for the LAS study team was to generate and analyze more than1000 geometry configurations to study 7 geometric parameters. By utilizing DOE techniques the number of geometries was strategically reduced to 84. In addition, critical information on interaction effects among the geometric factors were identified that would not have been possible with the traditional technique. Therefore, the study was performed in less time and provided more information on the geometric main effects and interactions impacting drag generated by the LAS. This paper discusses the methods utilized to develop the experimental design, execution, and data analysis.
A computational fluid dynamic (CFD) simulation of the flow past an Aeroassist Flight Experiment (AFE) aerobrake under wind tunnel test conditions has been made. The Navier-Stokes equations in three dimensions were solved numerically using a finite-volume, implicit approach. Comparisons with experimental data include surface pressures and heat transfer rates and aerodynamic coefficients. Agreement with experiment is shown to be excellent. The dependence of the solution on the computational grid is explored. The present work is preliminary to simulation of the flow past the AFE under flight conditions, which at present cannot be duplicated with ground-based experimental facilities.
Due to its numerous practical applications and intriguing phase transformation behavior, shape memory alloys (SMAs) have garnered significant research and development interests. In the past, most studies on the mechanical behavior of SMAs have been conducted under uniaxial stress loadings. Limited research on SMAs under shock loading has not provided conclusive results regarding their transformation behavior and transformation stress under such loading. Additionally, there is a lack of comprehensive understanding regarding the effects of different stress states on transformation behavior. The main objectives of this study are to address these issues. To achieve these objectives, a series of shock wave experiments were designed and conducted. Additionally, quasi-static and dynamic uniaxial stress experiments were carried out to establish a baseline for comparison. The results revealed that the transformation stress under dynamic uniaxial strain shock loading was approximately 1.92 GPa in contrast to 0.5 GPa (quasi-static) to 0.8 GPa (dynamic) observed in uniaxial stress loading. The transformation behavior exhibited noticeable rate sensitivity for both types of loading. There appeared to be a critical strain rate above which the austenite phase was driven to a metastable state. This estimated critical axial strain rate along the loading direction was approximately 2 × 10 3 /s–4 × 10 3 /s for uniaxial stress loading and approximately 2 × 10 6 /s for uniaxial strain loading. The apparent high transformation stress for uniaxial strain loading can likely be attributed to a combination of high-pressure confinement and high strain rate. Furthermore, determining their relative contributions remains an open issue.
Abstract The physical mechanisms governing slow earthquakes remain unknown, as does the relationship between slow and regular earthquakes. To investigate the mechanism(s) of slow earthquakes and related quasi‐dynamic modes of fault slip we performed laboratory experiments on simulated fault gouge in the double direct shear configuration. We reproduced the full spectrum of slip behavior, from slow to fast stick slip, by altering the elastic stiffness of the loading apparatus ( k ) to match the critical rheologic stiffness of fault gouge ( k c ). Our experiments show an evolution from stable sliding, when k > k c , to quasi‐dynamic transients when k ~ k c , to dynamic instabilities when k < k c . To evaluate the microphysical processes of fault weakening we monitored variations of elastic properties. We find systematic changes in P wave velocity ( V p ) for laboratory seismic cycles. During the coseismic stress drop, seismic velocity drops abruptly, consistent with observations on natural faults. In the preparatory phase preceding failure, we find that accelerated fault creep causes a V p reduction for the complete spectrum of slip behaviors. Our results suggest that the mechanics of slow and fast ruptures share key features and that they can occur on same faults, depending on frictional properties. In agreement with seismic surveys on tectonic faults our data show that their state of stress can be monitored by V p changes during the seismic cycle. The observed reduction in V p during the earthquake preparatory phase suggests that if similar mechanisms are confirmed in nature high‐resolution monitoring of fault zone properties may be a promising avenue for reliable detection of earthquake precursors.
A two-phase experiment is proposed which utilizes the Shuttle Orbiter and its unique series of repeated entries into the earth's atmosphere as an airborne in situ aerodynamic testing laboratory. The objective of the experiment is to determine static aerodynamic force coefficients, first of the orbiter, and later of various entry configurations throughout the high speed flight regime, including the transition from free molecule to continuum fluid flow. The objective will be accomplished through analysis of inflight measurements from both shuttle-borne and shuttle-launched instrumented packages. Results are presented to demonstrate the feasibility of such an experiment.
We present results of the studies of dynamics in colloidal crystals performed by pump-probe experiments using an X-ray free-electron laser (XFEL). Colloidal crystals were pumped with an infrared laser at a wavelength of 800 nm with varying power and probed by XFEL pulses at an energy of 8 keV with a time delay up to 1000 ps. The positions of the Bragg peaks, and their radial and azimuthal widths were analyzed as a function of the time delay. The spectral analysis of the data did not reveal significant enhancement of frequencies expected in this experiment. As a result, this allowed us to conclude that the amplitude of vibrational modes excited in colloidal crystals was less than the systematic error caused by the noise level.
Nonlinear acoustic standing waves of high amplitude have been demonstrated by utilizing the effects of resonator shape to prevent the pressure waves from entering saturation. Experimentally, nonlinear acoustic standing waves have been generated by shaking an entire resonating cavity. While this promotes more efficient energy transfer than a piston-driven resonator, it also introduces complicated structural dynamics into the system. Experiments have shown that these dynamics result in resonator forcing functions comprised of a sum of several Fourier modes. However, previous numerical studies of the acoustics generated within the resonator assumed simple sinusoidal waves as the driving force. Using a previously developed numerical code, this paper demonstrates the effects of using a forcing function constructed with a series of harmonic sinusoidal waves on resonating cavities. From these results, a method will be demonstrated which allows the direct numerical analysis of experimentally generated nonlinear acoustic waves in resonators driven by harmonic forcing functions.
NASA possesses a wealth of historical cryogenic experiments that provide valuable insights into the design, troubleshooting, and understanding involved in the complex fluid and thermodynamics of managing cryogenic propellants. One approach to leveraging these historical datasets is by simulating these experiments to validate the accuracy of simulation environments and constituent models. This study focused on simulating a selection of the K site test series for both static and sloshing pressurized liquid methane draining experiments conducted at NASA in the 1970’s, utilizing computational fluid dynamics. The simulations were performed in the ANSYS FLUENT environment using the Volume of Fluid (VOF) numerical approach. A k-omega turbulence model was used with interfacial turbulence damping, and accurately predicted the amount of pressurant needed to maintain the required tank pressure throughout the static drain. The static simulation predicted the temperature stratification in the ullage observed at the end of the drain. During the methane expulsion with sloshing test, many features were successfully captured using the k-omega turbulence model with interfacial turbulence damping included. The rate of phase change and liquid temperature was overpredicted compared to the experimental measurements. The overprediction may be attributed to uncertainties in the vessel geometry, methane pressurant temperature and composition, and methodological differences in how the sloshing frequency was adjusted during the expulsion.
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The Vega balloon experiment, designed to measure the dynamics of the Venus atmosphere, comprised the balloons themselves, their gondolas with on-board sensors and radio transmitters, and the radio telescope network on the earth. The structures and the physical parameters of the balloon probe are described, together with the instruments on the gondola, designed for the measurements of the atmospheric pressure, temperature, and vertical wind flows, and illumination, as well as possible flashes of lightning. Consideration is also given to the formatting of the information flow for the individual parameters measured.