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At least 199 records · Page 11

Time-Average Measurement of Velocity, Density, Temperature, and Turbulence Using Molecular Rayleigh Scattering

Measurement of time-averaged velocity, density, temperature, and turbulence in gas flows using a nonintrusive, point-wise measurement technique based on molecular Rayleigh scattering is discussed. Subsonic and supersonic flows in a 25.4-mm diameter free jet facility were studied. The developed instrumentation utilizes a Fabry-Perot interferometer to spectrally resolve molecularly scattered light from a laser beam passed through a gas flow. The spectrum of the scattered light contains information about velocity, density, and temperature of the gas. The technique uses a slow scan, low noise 16-bit depth CCD camera to record images of the fringes formed by Rayleigh scattered light passing through the interferometer. A kinetic theory model of the Rayleigh scattered light is used in a nonlinear least squares fitting routine to estimate the unknown parameters from the fringe images. The ability to extract turbulence information from the fringe image data proved to be a challenge since the fringe is broadened by not only turbulence, but also thermal fluctuations and aperture effects from collecting light over a range of scattering angles. Figure 1 illustrates broadening of a Rayleigh spectrum typical of flow conditions observed in this work due to aperture effects and turbulence for a scattering angle, chi(sub s), of 90 degrees, f/3.67 collection optics, mean flow velocity, u(sub k), of 300 m/s, and turbulent velocity fluctuations, sigma (sub uk), of 55 m/s. The greatest difficulty in processing the image data was decoupling the thermal and turbulence broadening in the spectrum. To aid in this endeavor, it was necessary to seed the ambient air with smoke and dust particulates; taking advantage of the turbulence broadening in the Mie scattering component of the spectrum of the collected light (not shown in the figure). The primary jet flow was not seeded due to the difficulty of the task. For measurement points lacking particles, velocity, density, and temperature information could reliably be recovered, however the turbulence estimates contained significant uncertainty. Resulting flow parameter estimates are presented for surveys of Mach 0.6, 0.95, and 1.4 jet flows. Velocity, density, and temperature were determined with accuracies of 5 m/s, 1.5%, and 1%, respectively, in flows with no particles present, and with accuracies of 5 m/s, 1-4%, and 2% in flows with particles. Comparison with hotwire data for the Mach 0.6 condition demonstrated turbulence estimates with accuracies of about 5 m/s outside the jet core where Mie scattering from dust/smoke particulates aided in the estimation of turbulence. Turbulence estimates could not be recovered with any significant accuracy for measurement points where no particles were present.

Mielke, Amy F.↗

Inlet Spillage Drag Predictions Using the AIRPLANE Code

AIRPLANE (Jameson/Baker) is a steady inviscid unstructured Euler flow solver. It has been validated on many HSR geometries. It is implemented as MESHPLANE, an unstructured mesh generator, and FLOPLANE, an iterative flow solver. The surface description from an Intergraph CAD system goes into MESHPLANE as collections of polygonal curves to generate the 3D mesh. The flow solver uses a multistage time stepping scheme with residual averaging to approach steady state, but R is not time accurate. The flow solver was ported from Cray to IBM SP2 by Wu-Sun Cheng (IBM); it could only be run on 4 CPUs at a time because of memory limitations. Meshes for the four cases had about 655,000 points in the flow field, about 3.9 million tetrahedra, about 77,500 points on the surface. The flow solver took about 23 wall seconds per iteration when using 4 CPUs. It took about eight and a half wall hours to run 1,300 iterations at a time (the queue limit is 10 hours). A revised version of FLOPLANE (Thomas) was used on up to 64 CPUs to finish up some calculations at the end. We had to turn on more communication when using more processors to eliminate noise that was contaminating the flow field; this added about 50% to the elapsed wall time per iteration when using 64 CPUs. This study involved computing lift and drag for a wing/body/nacelle configuration at Mach 0.9 and 4 degrees pitch. Four cases were considered, corresponding to four nacelle mass flow conditions.

Thomas, Scott D.↗

Electrostatic Precipitation for Cleaning Mars Atmospheric ISRU Intakes

Future Mars ISRU atmospheric intakes are estimated to ingest several hundred grams of dust over their lifetime. The Electrostatics and Surface Physics Laboratory at NASA's Kennedy Space Center is developing a dust removal system based on a mature terrestrial technology - electrostatic precipitation. In this technology, a high voltage and grounded collection electrode create a corona discharge which charges particles in a dust-laden flow. The resulting electric field between the high voltage and collection electrodes drive the charged particles toward the collection electrode. This paper presents the design of the electrostatic precipitator and preliminary results.

Precipitator↗

Data processing of solar EUV instruments on the METEOR satellite

The Multiple Experiment Transporter into Earth Orbit and Return-Solar EUV Experiment (METEOR-SEE) project will take daily extreme ultraviolet (EUV) irradiance spectra starting in the summer of 1995. The METEOR-SEE package consists of an EUV grating spectrograph (EGS) and a cluster of 5 soft x-ray photometers (XP's). Both these instruments have flown previously on NASA sounding rockets. Because of the scope of the project, new data processing algorithms had to be developed for the SEE instruments onboard the METEOR satellite. An overview of the data flow describes how satellite data are collected and processed. Detailed descriptions of specific routines will show what data processing entails.

Brown, Hipook↗

Dynamic Flow Management Problems in Air Transportation

In 1995, over six hundred thousand licensed pilots flew nearly thirty-five million flights into over eighteen thousand U.S. airports, logging more than 519 billion passenger miles. Since demand for air travel has increased by more than 50% in the last decade while capacity has stagnated, congestion is a problem of undeniable practical significance. In this thesis, we will develop optimization techniques that reduce the impact of congestion on the national airspace. We start by determining the optimal release times for flights into the airspace and the optimal speed adjustment while airborne taking into account the capacitated airspace. This is called the Air Traffic Flow Management Problem (TFMP). We address the complexity, showing that it is NP-hard. We build an integer programming formulation that is quite strong as some of the proposed inequalities are facet defining for the convex hull of solutions. For practical problems, the solutions of the LP relaxation of the TFMP are very often integral. In essence, we reduce the problem to efficiently solving large scale linear programming problems. Thus, the computation times are reasonably small for large scale, practical problems involving thousands of flights. Next, we address the problem of determining how to reroute aircraft in the airspace system when faced with dynamically changing weather conditions. This is called the Air Traffic Flow Management Rerouting Problem (TFMRP) We present an integrated mathematical programming approach for the TFMRP, which utilizes several methodologies, in order to minimize delay costs. In order to address the high dimensionality, we present an aggregate model, in which we formulate the TFMRP as a multicommodity, integer, dynamic network flow problem with certain side constraints. Using Lagrangian relaxation, we generate aggregate flows that are decomposed into a collection of flight paths using a randomized rounding heuristic. This collection of paths is used in a packing integer programming formulation, the solution of which generates feasible and near-optimal routes for individual flights. The algorithm, termed the Lagrangian Generation Algorithm, is used to solve practical problems in the southwestern portion of United States in which the solutions are within 1% of the corresponding lower bounds.

Patterson, Sarah Stock↗

Development of a Whole Blood Staining Device for use During Space Shuttle Flights

Exposure to microgravity during space flight results in profound physiologic changes. Numerous studies have shown changes in circulating populations of peripheral blood immune cells immediately after space flight. It is currently unknown if these changes result from exposure to microgravity or are caused by the stress of reentry and readaptation to gravity. We have developed the whole blood staining device as a system for the staining of whole blood collected during space flight for subsequent flow cytometric analysis, This device contains all liquids to address safety issues concerned with space flight and also moves the cells through the staining, lyse/fixation and dilution steps.

Sams, Clarence F.↗

Stereo Imaging Velocimetry

Stereo imaging velocimetry (SIV) will permit the collection of quantitative, three-dimensional flow data from any optically transparent fluid that can be seeded with tracer particles. This includes such diverse experiments as the study of multiphase flow, bubble nucleation and migration, pool combustion, and crystal growth. This technique will be useful to the microgravity science community as our investigations of fluid behavior in reduced-gravity environments enhance our knowledge of heat transfer, surface tension, concentration-gradient-driven anomalies, and residual effects from g-jitter. In its proposed configuration, the NASA Lewis Research Center's Stereo Imaging Velocimeter will consist of at least two charged coupled device (CCD) cameras, oriented at some relative angle with respect to each other. The cameras will observe a fluid experiment that has been seeded with tracer particles that are neutrally buoyant to permit accurate flow tracking. Except for the tracer particles, this measurement technique will be nonintrusive. Velocity accuracies will be on the order of 1 to 5 percent of full field. Each camera will make a two-dimensional record of the motion of the seed particles in the observation volume. Three-dimensional data will be obtained by computationally combining the two-dimensional information.

Source record↗

Atmospheric Processing Module for Mars Propellant Production

The multi-NASA center Mars Atmosphere and Regolith COllector/PrOcessor for Lander Operations (MARCO POLO) project was established to build and demonstrate a methane/oxygen propellant production system in a Mars analog environment. Work at the Kennedy Space Center (KSC) Applied Chemistry Laboratory is focused on the Atmospheric Processing Module (APM). The purpose of the APM is to freeze carbon dioxide from a simulated Martian atmosphere containing the minor components nitrogen, argon, carbon monoxide, and water vapor at Martian pressures (approx.8 torr) by using dual cryocoolers with alternating cycles of freezing and sublimation. The resulting pressurized CO2 is fed to a methanation subsystem where it is catalytically combined with hydrogen in a Sabatier reactor supplied by the Johnson Space Center (JSC) to make methane and water vapor. We first used a simplified once-through setup and later employed a HiCO2 recycling system to improve process efficiency. This presentation and paper will cover (1) the design and selection of major hardware items, such as the cryocoolers, pumps, tanks, chillers, and membrane separators, (2) the determination of the optimal cold head design and flow rates needed to meet the collection requirement of 88 g CO2/hr for 14 hr, (3) the testing of the CO2 freezer subsystem, and (4) the integration and testing of the two subsystems to verify the desired production rate of 31.7 g CH4/hr and 71.3 g H2O/hr along with verification of their purity. The resulting 2.22 kg of CH4/O2 propellant per 14 hr day (including O2 from electrolysis of water recovered from regolith, which also supplies the H2 for methanation) is of the scale needed for a Mars Sample Return mission. In addition, the significance of the project to NASA's new Mars exploration plans will be discussed.

Muscatello, Anthony↗

Atmospheric Processing Module for Mars Propellant Production

The multi-NASA center Mars Atmosphere and Regolith COllector/PrOcessor for Lander Operations (MARCO POLO) project was established to build and demonstrate a methane/oxygen propellant production system in a Mars analog environment. Work at the Kennedy Space Center (KSC) Applied Chemistry Laboratory is focused on the Atmospheric Processing Module (APM). The purpose of the APM is to freeze carbon dioxide from a simulated Martian atmosphere containing the minor components nitrogen, argon, carbon monoxide, and water vapor at Martian pressures (~8 torr) by using dual cryocoolers with alternating cycles of freezing and sublimation. The resulting pressurized CO2 is fed to a methanation subsystem where it is catalytically combined with hydrogen in a Sabatier reactor supplied by the Johnson Space Center (JSC) to make methane and water vapor. We first used a simplified once-through setup and later employed a HiCO2 recycling system to improve process efficiency. This presentation and paper will cover (1) the design and selection of major hardware items, such as the cryocoolers, pumps, tanks, chillers, and membrane separators, (2) the determination of the optimal cold head design and flow rates needed to meet the collection requirement of 88 g CO2/hr for 14 hr, (3) the testing of the CO2 freezer subsystem, and (4) the integration and testing of the two subsystems to verify the desired production rate of 31.7 g CH4/hr and 71.3 g H20/hr along with verification of their purity. The resulting 2.22 kg of CH4/O2 propellant per 14 hr day (including O2 from electrolysis of water recovered from regolith, which also supplies the H2 for methanation) is of the scale needed for a Mars Sample Return mission. In addition, the significance of the project to NASA's new Mars exploration plans will be discussed.

Muscatello, Anthony↗

Atmospheric Processing Module for Mars Propellant Production

The multi-NASA center Mars Atmosphere and Regolith COllectorPrOcessor for Lander Operations (MARCO POLO) project was established to build and demonstrate a methaneoxygen propellant production system in a Mars analog environment. Work at the Kennedy Space Center (KSC) Applied Chemistry Laboratory is focused on the Atmospheric Processing Module (APM). The purpose of the APM is to freeze carbon dioxide from a simulated Martian atmosphere containing the minor components nitrogen, argon, carbon monoxide, and water vapor at Martian pressures (8 torr) by using dual cryocoolers with alternating cycles of freezing and sublimation. The resulting pressurized CO(sub 2) is fed to a methanation subsystem where it is catalytically combined with hydrogen in a Sabatier reactor supplied by the Johnson Space Center (JSC) to make methane and water vapor. We first used a simplified once-through setup and later employed a H(sub 2)CO(sub 2) recycling system to improve process efficiency. This presentation and paper will cover (1) the design and selection of major hardware items, such as the cryocoolers, pumps, tanks, chillers, and membrane separators, (2) the determination of the optimal cold head design and flow rates needed to meet the collection requirement of 88 g CO(sub 2) hr for 14 hr, (3) the testing of the CO(sub 2) freezer subsystem, and (4) the integration and testing of the two subsystems to verify the desired production rate of 31.7 g CH(sub 4) hr and 71.3 g H(sub 2)O hr along with verification of their purity. The resulting 2.22 kg of CH(sub 2)O(sub 2) propellant per 14 hr day (including O(sub 2) from electrolysis of water recovered from regolith, which also supplies the H(sub 2) for methanation) is of the scale needed for a Mars Sample Return mission. In addition, the significance of the project to NASAs new Mars exploration plans will be discussed.

waste treatment↗

Atmospheric Processing Module for Mars Propellant Production

The multi-NASA center Mars Atmosphere and Regolith COllector/PrOcessor for Lander Operations (MARCO POLO) project was established to build and demonstrate a methaneoxygen propellant production system in a Mars analog environment. Work at the Kennedy Space Center (KSC) Applied Chemistry Laboratory is focused on the Atmospheric Processing Module (APM). The purpose of the APM is to freeze carbon dioxide from a simulated Martian atmosphere containing the minor components nitrogen, argon, carbon monoxide, and water vapor at Martian pressures (approx. 8 torr) by using dual cryocoolers with alternating cycles of freezing and sublimation. The resulting pressurized CO(sub 2) is fed to a methanation subsystem where it is catalytically combined with hydrogen in a Sabatier reactor supplied by the Johnson Space Center (JSC) to make methane and water vapor. We first used a simplified once-through setup and later employed a H(sub 2)CO(sub 2) recycling system to improve process efficiency. This presentation and paper will cover (1) the design and selection of major hardware items, such as the cryocoolers, pumps, tanks, chillers, and membrane separators, (2) the determination of the optimal cold head design and flow rates needed to meet the collection requirement of 88 g CO(sub 2) hr for 14 hr, (3) the testing of the CO(sub 2) freezer subsystem, and (4) the integration and testing of the two subsystems to verify the desired production rate of 31.7 g CH(sub 4) hr and 71.3 g H(sub 2)O hr along with verification of their purity. The resulting 2.22 kg of CH(sub 2)O(sub 2) propellant per 14 hr day (including O(sub 2) from electrolysis of water recovered from regolith, which also supplies the H(sub 2) for methanation) is of the scale needed for a Mars Sample Return mission. In addition, the significance of the project to NASAs new Mars exploration plans will be discussed.

hydrocarbon fuel production↗

ICE-RASSOR: Intelligent Capabilities Enhanced Regolith Advanced Surface Systems Operations Robot

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU)processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from a reduced sensor payload. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and prototype state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗

ICE-RASSOR: Intelligent Capabilities Enhanced

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RAS-SOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar sur-face, RASSOR software and sensory systems need to be robust and maximize the information extracted from on-board sensing. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and proto-type state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗

ICE-RASSOR: Intelligent Capabilities Enhanced Regolith Advanced Surface Systems Operations Robot

NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for In-Situ Resource Utilization (ISRU) processing. RASSOR’s design enables it to efficiently collect and deposit regolith, return collected material for processing, and myriad related ISRU activities. To reliably perform these operations on the lunar surface, RASSOR software and sensory systems need to be robust and maximize the information extracted from on-board sensory. Herein, we present preliminary findings from the Intelligent Capabilities Enhanced RASSOR project. We apply supervised learning using real data to estimate the soil mass collected without the need for mass flow rate monitors or other explicate sensing techniques. We also create a reduced-order simulation environment to develop autonomous trenching controllers via reinforcement learning and proto-type state estimation architectures. Our initial results suggest that excavated regolith mass can be inferred within 2.9% RMS error of full scale, and reinforcement learning for autonomous operations has learned viable trenching strategies and helped identify desirable sensing capabilities, arrangements, and considerations. Future work includes regolith mass estimation during dynamic operation, expanding our simulation to more complex environments, and transfer learning from simulation to hardware.

machine learning↗

Validation of Shadowgraph Spectral Analysis using an SLS Block 2 Wind-Tunnel Model

A flow quantification method has previously been developed that uses high-speed shadowgraph images to extract frequency content of a transonic flow field around a wind-tunnel model. In this method, a classical spectral analysis is performed on a set of shadowgraph image pixels to identify their intensity fluctuation frequencies. The spatial change of the image intensity is related to the second derivative of the density gradient. Examining the change of the density gradient as a function of time can be used to understand the flow field pressure fluctuations. Pressure measurements collected during a Booster Obsolescence Life Extension Forward Attachment Structure Trade Study Test are used to calibrate the shadowgraph-based measurements. The test was performed at the NASA Ames Research Center Unitary Plan Wind Tunnel 11- by 11-foot test section and investigated aerodynamic environment downstream of various booster forward attachment hardware geometries of the Space Launch System Block 2 Cargo configuration. Time-correlated shadowgraph video and model surface pressure measurements were acquired during the test and served as an ideal opportunity to calibrate and validate the shadowgraph image intensity method.

Shadowgraph↗

Design of an Acoustic Shielding Flap Concept with Prediction and Validation

As part of a NATO task group, NASA has designed a noise reduction technology called a Shielding Flap for application to a hybrid wing body aircraft concept. The design drivers and objectives for this technology are outlined in this paper. Design parameters are defined, and recently-developed NASA software for prediction of acoustic scattering is used to investigate the expected performance of the technology for a range of parameter values. Detailed scattering computational results are presented for several simulated noise sources and for many variations of the shielding flap concept. A selection of computational results is compared with experimental data collected in the NASA Langley Quiet Flow Facility. Overall, the results indicate that the Shielding Flap has strong potential to reduce aft-radiated noise, which was a primary design objective, by shielding sound from the simulated sources while also shielding sound that is scattered from the main airframe.

Propulsion Airframe Aeroacoustics↗

Electron collection theory for a D-region subsonic blunt electrostatic probe

Blunt probe theory for subsonic flow in a weakly ionized and collisional gas is reviewed, and an electron collection theory for the relatively unexplored case, Deybye length approximately 1, which occurs in the lower ionosphere (D-region), is developed. It is found that the dimensionless Debye length is no longer an electric field screening parameter, and the space charge field effect can be negelected. For ion collection, Hoult-Sonin theory is recognized as a correct description of the thin, ion density-perturbed layer adjacent the blunt probe surface. The large volume with electron density perturbed by a positively biased probe renders the usual thin boundary layer analysis inapplicable. Theories relating free stream conditions to the electron collection rate for both stationary and moving blunt probes are obtained. A model based on experimental nonlinear electron drift velocity data is proposed. For a subsonically moving probe, it is found that the perturbed region can be divided into four regions with distinct collection mechanisms.

Wai-Kwong Lai, T.↗

A Novel Method for Breath Capture Inside a Space Suit

Any non-robotic mission to the Mars surface will need to rely on various life support technologies. The large metabolic generation rate and low tolerance to elevated levels of carbon dioxide (CO2) in the Mars atmosphere make CO2 removal one of the preeminent tasks in this domain. In addition, these same features provide a strong impetus for using regenerable CO2 removal technologies. In the past, many of these regenerable technologies have relied on the low partial pressure CO2 surrounding the vehicle to provide an ultimate sink for removing this gas contaminant, however any Mars mission will have to overcome the presence of the Mars atmosphere. This paper describes the investigation of methods to capture the exhaled CO2 from a suited crewmember before it becomes diluted with the high volumetric air flow present within the space suit. Typical expired air contains CO2 partial pressures in the range of 20-35 mm Hg. This research investigated methods to capture this high partial pressure CO2 prior to its dilution with the low partial pressure CO2 ventilation flow. Specifically the research looked at potential designs for a collection cup for use inside the space suit helmet. This collection cup should not be considered the same as a breathing mask typical of that worn by firefighters, etc. Instead, the collection cup is a non-contact device that makes use of detailed analyses of the ventilation flow environment within the helmet. The research used a detailed Computational Fluid Dynamic (CFD) code called Fluent to provide modeling of the various gas species (CO2, water vapor, O2) as they pass through a helmet. This same model was used to numerically evaluate several different collection cup designs for this same CO2 segregation effort.

Paul, Heather↗