A Multifunctional Aerospace Smart Skin Emerges From Computational Models and Physical Experiments
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The application of a sweeping jet actuator to a circulation control system was initiated by a risk reduction series of experiments to optimize the authority of a single sweeping jet actuator. The sweeping jet design was integrated into the existing Fundamental Aerodynamic Subsonic Transonic- Modular Active Control (FAST-MAC) model by replacing the steady blowing system with an array of thirty-nine sweeping jet cartridges. A constant slot height to wing chord ratio was similar to the steady blowing configuration resulting in each actuator having a unique in size for the sweeping jet configuration. While this paper will describe the scaling and optimization of the actuators for future high Reynolds number applications, the major focus of this effort was to target the transonic flight regime by increasing the amplitude authority of the actuator. This was accomplished by modifying the diffuser of the sweeping jet actuator, and this paper highlights twelve different diffuser designs. The experimental portion of this work was completed in the NASA Langley National Transonic Facility.
Experiments and computations were carried out on the adiabatic laminar boundary layer developing along the surfaces of a two-dimensional supersonic nozzle, consisting of upper and lower contoured nozzle blocks and flat sidewalls. Two- and three-dimensional Navier-Stokes codes, as well as two-dimensional boundary-layer codes were employed. These codes were adapted to the characteristics of a specific wind tunnel nozzle, so that their numerical results could be directly compared with experimental data obtained in the same nozzle. Such comparisons were made for the boundary-layer growth on the nozzle contoured surfaces, and for the boundary-layer growth, surface streamlines and surface shear on the sidewalls. The three-dimensional Navier-Stokes code was found to be the only one to correctly predict the mean laminar boundary-layer flow on both the sidewalls and the contoured surfaces. Theory and experiment both indicated that the sidewall flow is highly three-dimensional, with non-uniform shear, corner vortices and a boundary layer strongly distorted by cross flows induced by lateral pressure gradients.
This experiment investigated the integrity of static computer memory (floppy disk media) when exposed to the environment of low earth orbit. The experiment attempted to record soft-event upsets (bit-flips) in static computer memory. Typical conditions that exist in low earth orbit that may cause soft-event upsets include: cosmic rays, low level background radiation, charged fields, static charges, and the earth's magnetic field. Over the years several spacecraft have been affected by soft-event upsets (bit-flips), and these events have caused a loss of data or affected spacecraft guidance and control. This paper describes a commercial spin-off that is being developed from the experiment.
In this report we describe the testing of a novel scheme for state preparation of trapped ions in a quantum computing setup. This technique optimally would allow for similar precision and speed of state preparation while allowing for individual addressability of single ions in a chain using technology already available in a trapped ion experiment. As quantum computing experiments become more complicated, mid-experiment measurements will become necessary to achieve algorithms such as quantum error correction. Any mid-experiment measurement then requires the measured qubit to be re-prepared to a known quantum state. Currently this involves the protected qubits to be moved a sizeable distance away from the qubit being re-prepared which can be costly in terms of experiment length as well as introducing errors. Theoretical calculations predict that a three-photon process would allow for state preparation without qubit movement with similar efficiencies to current state preparation methods.
Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments— including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers—is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.
National airspace, the management for access and operation of these vehicles is required. This management is being developed under the unmanned aircraft system traffic management system (UTM) program. To determine the aerodynamic characteristics of drones, wind tunnel experiments and computation fluid dynamic (CFD) analysis have been conducted. These experiments and analyses are undertaken to understand the flight capabilities of these vehicles in variable head and cross wind conditions. The results of these investigations will provide metrics for the safe operation of these vehicles in and around civil populations and in urban settings. The focus of this paper is to model a drone installed in a wind tunnel for varying pitch attitudes and rotor rpm settings. Specifically, the IRIS drone is modeled in the NASA-Ames 7x10 ft. W/T. The tunnel mounting hardware and the tunnel enclosure are modeled with the IRIS drone geometry. The rotors of the drone are modeled using two methodologies: a rotor disk model and individual blade representations. The results of the analysis are compared with available experimental data to validate the computational approach.
ABSTRACT Closed-loop HIRF experiments were performed on a fault tolerant flight control computer (FCC) at the NASA Langley Research Center. The FCC used in the experiments was a quad-redundant flight control computer executing B737 Autoland control laws. The FCC was placed in one of the mode-stirred reverberation chambers in the HIRF Laboratory and interfaced to a computer simulation of the B737 flight dynamics, engines, sensors, actuators, and atmosphere in the Closed-Loop Systems Laboratory. Disturbances to the aircraft associated with wind gusts and turbulence were simulated during tests. Electrical isolation between the FCC under test and the simulation computer was achieved via a fiber optic interface for the analog and discrete signals. Closed-loop operation of the FCC enabled flight dynamics and atmospheric disturbances affecting the aircraft to be represented during tests. Upset was induced in the FCC as a result of exposure to HIRF, and the effect of upset on the simulated flight of the aircraft was observed and recorded. This paper presents a description of these closed- loop HIRF experiments, upset data obtained from the FCC during these experiments, and closed-loop effects on the simulated flight of the aircraft.
With the increasing presence of unmanned aircraft systems (UAS), or drones, in the national airspace, the management for access and operation of these vehicles is required. NASA’s management approach is being developed under the unmanned aircraft system traffic management (UTM) program. To determine the aerodynamic characteristics of drones, wind tunnel experiments and computation fluid dynamic (CFD) analysis have been conducted. These experiments and analyses are undertaken to understand the flight capabilities of these vehicles in variable head and cross wind conditions. The results of these investigations will provide metrics for the safe operation of these vehicles in and around civil populations and in urban settings. The focus of this paper is to model a drone installed in a wind tunnel for varying pitch attitudes and rotor rpm settings. Specifically, the IRIS drone is modeled in the NASA-Ames 7x10 ft wind tunnel. The tunnel mounting hardware and the tunnel enclosure are modeled along with the IRIS drone geometry. The rotors of the drone are modeled using two methodologies: a rotor disk model and full rotating rotors with moving grids. The results of the analysis are compared with available experimental data to validate the computational approach.
Residual stress in an aerodynamically shaped Ni-based superalloy airfoil fabricated by laser powder bed fusion was measured by neutron diffraction. The experiment was conducted by considering the complex shape, implementing computer aided experiment planning, and automatic alignment at each rapid measurement. The 3-dimensional (3D) residual stress distribution in the airfoil is presented in this work, which lacks symmetry due to the complex geometry of the airfoil. In conclusion, the results provide theoretical thermal processing models a complete residual stress dataset of simulation validation on 3D shape complex structure.
We present the first machine learning-based autonomous hyperspectral neutron computed tomography experiment performed at the Spallation Neutron Source. Hyperspectral neutron computed tomography allows the characterization of samples by enabling the reconstruction of crystallographic information and elemental/isotopic composition of objects relevant to materials science. High quality reconstructions using traditional algorithms such as the filtered back projection require a high signal-to-noise ratio across a wide wavelength range combined with a large number of projections. This results in scan times of several days to acquire hundreds of hyperspectral projections, during which end users have minimal feedback. To address these challenges, a golden ratio scanning protocol combined with model-based image reconstruction algorithms have been proposed. This novel approach enables high quality real-time reconstructions from streaming experimental data, thus providing feedback to users, while requiring fewer yet a fixed number of projections compared to the filtered back projection method. In this paper, we propose a novel machine learning criterion that can terminate a streaming neutron tomography scan once sufficient information is obtained based on the current set of measurements. Our decision criterion uses a quality score which combines a reference-free image quality metric computed using a pre-trained deep neural network with a metric that measures differences between consecutive reconstructions. The results show that our method can reduce the measurement time by approximately a factor of five compared to a baseline method based on filtered back projection for the samples we studied while automatically terminating the scans.
Progress in modeling external aerodynamic flows achieved by using computations and experiments designed to guide turbulence modeling is presented. The computational procedures emphasize utilization of the Reynolds-averaged Navier-Stokes equations and various statistical modeling approaches. Developments for including the influence of compressibility are provided; they point up some of the complexities involved in modeling high-speed flows. Examples of complementary studies that provide the status, limitations, and future challenges of modeling for transonic, supersonic, and hypersonic flows are given.
A three-component laser velocimeter is used to investigate the flow over a backward-facing step. The backward-facing step had an expansion ratio of 2, a boundary layer height to step height ratio of 0.34 and a Reynolds number based on step height of 19,000. Results from three-component velocimeter surveys of the flow over the backward-facing step are presented with comparisons of the current experiment with previous experiments and computational results. The present results compared well with previous experiments with the exception of the reattachment length. The short reattachment length was due to the short length of the channel downstream. The measurement of the lateral velocity component showed that there is a mean flow in and out of the centerline plane as high as 7 percent of the freestream velocity. However, the shear stresses show no correlation between the lateral fluctuations and the longitudinal and vertical fluctuations, indicating that the flow is 2D in terms of the turbulence quantities.
A floating-shock fitting method for the Euler equations has been developed that uses one-sided spatial differences along and across streamlines. This method has been applied to unsteady shocked flow in a duct with a ramp, to supercritical flow over a circular cylinder, and to transonic flow over airfoils. Compared to methods using coordinate-aligned upwind differencing, the coordinate-invariant upwinding generally required fewer grid points to produce crisp shocks and shears. For transonic airfoils, coordinate-invariant upwind differencing advances the agreement between computations and experiment, and it reduces the grid dependency of the computed results for strong shocks. The computational expenditure is comparable to that of coordinate-aligned upwind methods for the Euler equations.
The Adaptive Instrument Module (AIM) will be the first true demonstration of reconfigurable computing with field-programmable gate arrays (FPGAs) in space, enabling the 'brain' of the system to evolve or adapt to changing requirements. In partnership with NASA Goddard Space Flight Center and the Australian Cooperative Research Centre for Satellite Systems (CRC-SS), APL has built the flight version to be flown on the Australian university-class satellite FEDSAT. The AIM provides satellites the flexibility to adapt to changing mission requirements by reconfiguring standardized processing hardware rather than incurring the large costs associated with new builds. This ability to reconfigure the processing in response to changing mission needs leads to true evolveable computing, wherein the instrument 'brain' can learn from new science data in order to perform state-of-the-art data processing. The development of the AIM is significant in its enormous potential to reduce total life-cycle costs for future space exploration missions. The advent of RAM-based FPGAs whose configuration can be changed at any time has enabled the development of the AIM for processing tasks that could not be performed in software. The use of the AIM enables reconfiguration of the FPGA circuitry while the spacecraft is in flight, with many accompanying advantages. The AIM demonstrates the practicalities of using reconfigurable computing hardware devices by conducting a series of designed experiments. These include the demonstration of implementing data compression, data filtering, and communication message processing and inter-experiment data computation. The second generation is the Adaptive Processing Template (ADAPT) which is further described in this paper. The next step forward is to make the hardware itself adaptable and the ADAPT pursues this challenge by developing a reconfigurable module that will be capable of functioning efficiently in various applications. ADAPT will take advantage of radiation tolerant RAM-based field programmable gate array (FPGA) technology to develop a reconfigurable processor that combines the flexibility of a general purpose processor running software with the performance of application specific processing hardware for a variety of high performance computing applications.
This paper presents computational fluid dynamic studies of the inlet turbulence and wall curvature effects on the flow steadiness at near wall surface locations in boundary layer flows. The time-stepping RANS numerical solver of the NASA Glenn-HT RANS code and a one-equation turbulence model, with a uniform inlet turbulence modeling level of the order of 10 percent of molecular viscosity, were used to perform the numerical computations. The approach was first calibrated for its predictabilities of friction factor, velocity, and temperature at near surface locations within a transitional boundary layer over concave wall. The approach was then used to predict the velocity and friction factor variations in a boundary layer recovering from concave curvature. As time iteration proceeded in the computations, the computed friction factors converged to their values from existing experiments. The computed friction factors, velocity, and static temperatures at near wall surface locations oscillated periodically in terms of time iteration steps and physical locations along the span-wise direction. At the upstream stations, the relationship among the normal and tangential velocities showed vortices effects on the velocity variations. Coherent vortices effect on the velocity components broke down at downstream stations. The computations also predicted the vortices effects on the velocity variations within a boundary layer flow developed along a concave wall surface with a downstream recovery flat wall surface. It was concluded that the computational approach might have the potential to analyze the flow steadiness in a turbine blade flow.
Experiments and computations have been performed under laminar conditions in air on 5-deg blunt cones at velocities of 5 km/s and 6 km/s and at Reynolds numbers of 100,000 and 1 million. The computations were performed using ideal-, equilibrium- and nonequilibrium-chemistry models for air. At the conditions of the tests, the aerodynamic coefficients are sensitive to the real-gas effects present, and both experimental and computational aerodynamic coefficients show real-gas and nonlinear effects. The nonequilibrium computations show that a large amount of oxygen is dissociated in the blunt nose region of the flow and much of the oxygen remains dissociated over the entire length of the body, providing an insight into the source of the observed effects in the aerodynamic coefficients. The experimental and computational shock-shapes are in good agreement.