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This paper presents an examination of the CCA software in sequential and parallel electromagnetics applications using unstructured adaptive mesh refinement.
Controlling carbon dioxide (CO2) and humidity levels in a spacesuit is critical to ensuring both the safety and comfort of an astronaut during extra-vehicular activity (EVA). Traditionally, this has been accomplished utilizing non-regenerative lithium hydroxide (LiOH) or regenerative metal oxide (MetOx) canisters which pose a significant weight burden. Although such technology enables air revitalization, the volume requirements to store the waste canisters as well as the mass to transport multiple units become prohibitive as mission durations increase. Consequently, motivation exists toward developing a fully regenerative technology for environmental control. The application of solid amine materials with vacuum swing adsorption technology has shown the capacity to control CO2 and concomitantly manage humidity levels through a fully regenerative cycle eliminating mission constraints imposed with non-regenerative technologies. Experimental results for full-size and sub-scale test articles have been collected and are described herein. In order to accelerate the developmental efforts, an axially-dispersed plug ow model with an accompanying energy balance has been established and correlated with the experimental data. The experimental and simulation results display good agreement for a variety of ow rates (110-170 SLM), replicated metabolic challenges (100-590 Watts), and atmosphere pressures under consideration for the spacesuit (248 and 760 mm Hg). The relationship between swing adsorption cycles for an outlet criterion of 6.0 mm Hg of CO2 partial pressure has been established for each metabolic challenge. In addition, variable metabolic profiles were imposed on the test articles in order to assess the ability of the technology to transition to new operational constraints. The advent of the model provides the capacity to apply computer-aided engineering practices to support the ongoing efforts to optimize and mature this technology for future application to space exploration.
Controlling carbon dioxide (CO2) and humidity levels in a spacesuit is critical to ensuring both the safety and comfort of an astronaut during extra-vehicular activity (EVA). Traditionally, this has been accomplished utilizing either non-regenerative lithium hydroxide (LiOH) or regenerative but heavy metal oxide (MetOx) canisters which pose a significant weight burden. Although such technology enables air revitalization, the volume requirements to store the waste canisters as well as the mass to transport multiple units become prohibitive as mission durations increase. Consequently, motivation exists toward developing a fully regenerative technology for spacesuit environmental control. The application of solid amine materials with vacuum swing adsorption technology has shown the capacity to control CO2 while concomitantly managing humidity levels through a fully regenerative cycle eliminating constraints imposed with the traditional technologies. Prototype air revitalization units employing this technology have been fabricated in both a rectangular and cylindrical geometry. Experimental results for these test articles have been collected and are described herein. In order to accelerate the developmental efforts, an axially-dispersed plug flow model with an accompanying energy balance has been established and correlated with the experimental data. The experimental and simulation results display good agreement for a variety of flow rates (110-170 ALM), replicated metabolic challenges (100-590 Watts), and atmosphere pressures under consideration for the spacesuit (248 and 760 mm Hg). The testing and model results lend insight into the operational capabilities of these devices as well as the influence the geometry of the device has on performance. In addition, variable metabolic profiles were imposed on the test articles in order to assess the ability of the technology to transition to new metabolic conditions. The advent of the model provides the capacity to apply computer-aided engineering practices to support the ongoing efforts to optimize and mature this technology for future application to space exploration.
The NEQAIR line-by-line radiation code has been incorporated into the DPLR Navier-Stokes flow solver such that the NEQAIR subroutines are now callable functions of DPLR. The coupled DPLR-NEQAIR code was applied to compute the convective and radiative heating rates over high-mass Mars entry vehicles. Two vehicle geometries were considered - a 15 m diameter 70-degree sphere cone configuration and a slender, mid-L/D vehicle with a diameter of 5 m called an Ellipsled. The entry masses ranged from 100 to 165 metric tons. Solutions were generated for entry velocities ranging from 6.5 to 9.1 km/s. The coupled fluids-radiation solutions were performed at the peak heating location along trajectories generated by the Traj trajectory analysis code. The impact of fluids-radiation coupling is a function of the level of radiative heating and the freestream density and velocity. For the high-mass Mars vehicles examined in this study, coupling effects were greatest for entry velocities above 8.5 km/s where the surface radiative heating was reduced by up 17%. Generally speaking, the Ellipsled geometry experiences a lower peak radiative heating rate but a higher peak turbulent convective heating rate than the MSL-based vehicle.
Three terms, ''Waterman's T-matrix method'', ''extended boundary condition method (EBCM)'', and ''null field method'', have been interchangeable in the literature to indicate a method based on surface integral equations to calculate the T-matrix. Unlike the previous method, the invariant imbedding method (IIM) calculates the T-matrix by the use of a volume integral equation. In addition, the standard separation of variables method (SOV) can be applied to compute the T-matrix of a sphere centered at the origin of the coordinate system and having a maximal radius such that the sphere remains inscribed within a nonspherical particle. This study explores the feasibility of a numerical combination of the IIM and the SOV, hereafter referred to as the IIMþSOV method, for computing the single-scattering properties of nonspherical dielectric particles, which are, in general, inhomogeneous. The IIMþSOV method is shown to be capable of solving light-scattering problems for large nonspherical particles where the standard EBCM fails to converge. The IIMþSOV method is flexible and applicable to inhomogeneous particles and aggregated nonspherical particles (overlapped circumscribed spheres) representing a challenge to the standard superposition T-matrix method. The IIMþSOV computational program, developed in this study, is validated against EBCM simulated spheroid and cylinder cases with excellent numerical agreement (up to four decimal places). In addition, solutions for cylinders with large aspect ratios, inhomogeneous particles, and two-particle systems are compared with results from discrete dipole approximation (DDA) computations, and comparisons with the improved geometric-optics method (IGOM) are found to be quite encouraging.
The main focus of this study is to apply a computational tool for the flow analysis of the engine that has been tested with ice crystal ingestion in the Propulsion Systems Laboratory (PSL) of NASA Glenn Research Center. A data point was selected for analysis during which the engine experienced a full roll back event due to the ice accretion on the blades and flow path of the low pressure compressor. The computational tool consists of the Numerical Propulsion System Simulation (NPSS) engine system thermodynamic cycle code, and an Euler-based compressor flow analysis code, that has an ice particle melt estimation code with the capability of determining the rate of sublimation, melting, and evaporation through the compressor blade rows. Decreasing the performance characteristics of the low pressure compressor (LPC) within the NPSS cycle analysis resulted in matching the overall engine performance parameters measured during testing at data points in short time intervals through the progression of the roll back event. Detailed analysis of the fan-core and LPC with the compressor flow analysis code simulated the effects of ice accretion by increasing the aerodynamic blockage and pressure losses through the low pressure compressor until achieving a match with the NPSS cycle analysis results, at each scan. With the additional blockages and losses in the LPC, the compressor flow analysis code results were able to numerically reproduce the performance that was determined by the NPSS cycle analysis, which was in agreement with the PSL engine test data. The compressor flow analysis indicated that the blockage due to ice accretion in the LPC exit guide vane stators caused the exit guide vane (EGV) to be nearly choked, significantly reducing the air flow rate into the core. This caused the LPC to eventually be in stall due to increasing levels of diffusion in the rotors and high incidence angles in the inlet guide vane (IGV) and EGV stators. The flow analysis indicating compressor stall is substantiated by the video images of the IGV taken during the PSL test, which showed water on the surface of the IGV flowing upstream out of the engine, indicating flow reversal, which is characteristic of a stalled compressor.
The planetary exploration programs demand a totally new examination of data multiplexing, digital communications protocols and data transmission principles for both ground and spacecraft operations. Highly adaptive communications devices on‐board and on the ground must provide the greatest possible transmitted data density between deployed crew personnel, spacecraft and ground control teams. Regarding these requirements, this proposal borrows from research into quantum mechanical computing by applying the concept of a qubit, a single bit that represents 16 states, to radio frequency (RF) communications link design for exploration programs. This concept of placing multiple character values into a single data bit can easily make the evolutionary steps needed to meet exploration mission demands. To move the qubit from the quantum mechanical research laboratory into long distance RF data transmission, this proposal utilizes polarization modulation of the RF carrier signal to represent numbers from zero to fifteen. It introduces the concept of a binary‐to‐hexadecimal converter that quickly chops any data stream into 16‐bit words and connects variously polarized feedhorns to a single‐frequency radio transmitter. Further, the concept relies on development of a receiver that uses low‐noise amplifiers and an antenna array to quickly assess carrier polarity and perform hexadecimal to binary conversion. Early testbed experiments using the International Space Station (ISS) as an operations laboratory can be implemented to provide the most cost‐effective return for research investment. The improvement in signal‐to‐noise ratio while supporting greater baseband data rates that could be achieved through this concept justifies its consideration for long‐distance exploration programs.
Systems and methods for operating autonomous waterborne vessels in a safe manner. The systems include hardware for identifying the locations and motions of other vessels, as well as the locations of stationary objects that represent navigation hazards. By applying a computational method that uses a maritime navigation algorithm for avoiding hazards and obeying COLREGS using Velocity Obstacles to the data obtained, the autonomous vessel computes a safe and effective path to be followed in order to accomplish a desired navigational end result, while operating in a manner so as to avoid hazards and to maintain compliance with standard navigational procedures defined by international agreement. The systems and methods have been successfully demonstrated on water with radar and stereo cameras as the perception sensors, and integrated with a higher level planner for trailing a maneuvering target.
The main focus of this study is to apply a computational tool for the flow analysis of the engine that has been tested with ice crystal ingestion in the Propulsion Systems Laboratory (PSL) of NASA Glenn Research Center. A data point was selected for analysis during which the engine experienced a full roll back event due to the ice accretion on the blades and flow path of the low pressure compressor. The computational tool consists of the Numerical Propulsion System Simulation (NPSS) engine system thermodynamic cycle code, and an Euler-based compressor flow analysis code, that has an ice particle melt estimation code with the capability of determining the rate of sublimation, melting, and evaporation through the compressor blade rows. Decreasing the performance characteristics of the low pressure compressor (LPC) within the NPSS cycle analysis resulted in matching the overall engine performance parameters measured during testing at data points in short time intervals through the progression of the roll back event. Detailed analysis of the fan-core and LPC with the compressor flow analysis code simulated the effects of ice accretion by increasing the aerodynamic blockage and pressure losses through the low pressure compressor until achieving a match with the NPSS cycle analysis results, at each scan. With the additional blockages and losses in the LPC, the compressor flow analysis code results were able to numerically reproduce the performance that was determined by the NPSS cycle analysis, which was in agreement with the PSL engine test data. The compressor flow analysis indicated that the blockage due to ice accretion in the LPC exit guide vane stators caused the exit guide vane (EGV) to be nearly choked, significantly reducing the air flow rate into the core. This caused the LPC to eventually be in stall due to increasing levels of diffusion in the rotors and high incidence angles in the inlet guide vane (IGV) and EGV stators. The flow analysis indicating compressor stall is substantiated by the video images of the IGV taken during the PSL test, which showed water on the surface of the IGV flowing upstream out of the engine, indicating flow reversal, which is characteristic of a stalled compressor.
The main focus of this study is to apply a computational tool for the flow analysis of the turbine engine that has been tested with ice crystal ingestion in the Propulsion Systems Laboratory (PSL) at NASA Glenn Research Center. The PSL has been used to test a highly instrumented Honeywell ALF502R-5A (LF11) turbofan engine at simulated altitude operating conditions. Test data analysis with an engine cycle code and a compressor flow code was conducted to determine the values of key icing parameters, that can indicate the risk of ice accretion, which can lead to engine rollback (un-commanded loss of engine thrust). The full engine aerothermodynamic performance was modeled with the Honeywell Customer Deck specifically created for the ALF502R-5A engine. The mean-line compressor flow analysis code, which includes a code that models the state of the ice crystal, was used to model the air flow through the fan-core and low pressure compressor. The results of the compressor flow analyses included calculations of the ice-water flow rate to air flow rate ratio (IWAR), the local static wet bulb temperature, and the particle melt ratio throughout the flow field. It was found that the assumed particle size had a large effect on the particle melt ratio, and on the local wet bulb temperature. In this study the particle size was varied parametrically to produce a non-zero calculated melt ratio in the exit guide vane (EGV) region of the low pressure compressor (LPC) for the data points that experienced a growth of blockage there, and a subsequent engine called rollback (CRB). At data points where the engine experienced a CRB having the lowest wet bulb temperature of 492 degrees Rankine at the EGV trailing edge, the smallest particle size that produced a non-zero melt ratio (between 3 percent - 4 percent) was on the order of 1 micron. This value of melt ratio was utilized as the target for all other subsequent data points analyzed, while the particle size was varied from 1 micron - 9.5 microns to achieve the target melt ratio. For data points that did not experience a CRB which had static wet bulb temperatures in the EGV region below 492 degrees Rankine, a non-zero melt ratio could not be achieved even with a 1 micron ice particle size. The highest value of static wet bulb temperature for data points that experienced engine CRB was 498 degrees Rankine with a particle size of 9.5 microns. Based on this study of the LF11 engine test data, the range of static wet bulb temperature at the EGV exit for engine CRB was in the narrow range of 492 degrees Rankine - 498 degrees Rankine , while the minimum value of IWAR was 0.002. The rate of blockage growth due to ice accretion and boundary layer growth was estimated by scaling from a known blockage growth rate that was determined in a previous study. These results obtained from the LF11 engine analysis formed the basis of a unique “icing wedge.”
The purpose of the workshop was to invite statisticians, applied mathematicians, computer scientists, data system architects, experts in remote sensing technology, and Climate and Earth System scientists to review, discuss, and plan research on issues related to large-scale, efficient analysis of distributed data using spatial statistical methods. Our motivation in organizing this event was to catalyze interchange among experts on the fast-emerging problem of analysis of distributed data. As part of SAMSI's 2017-2018 Program on Mathematical and Statistical Methods for Climate and the Earth System, a Working Group on Remote Sensing was established to address statistical and mathematical research problems in the analysis of remote sensing data. The Working Group has five subgroups: 1) Spatial Retrieval Methodology (the so-called \Spatial-X" subgroup); 2) Spatial Analysis for Hyperspectral Data (the so-called \Spatial-Y" subgroup); 3) Emulators for Complex Forward Models; 4) Optimization for Remote Sensing Retrievals; and 5) Theory of Data Systems (ToDS). The ToDS subgroup spent the first half of this academic year formulating a framework in which to consider the joint problem of a) optimizing statistical methods for environments where data are distributed and too large to move to a central location, and b) the design of data system infrastructures within which to implement those statistical methods. To x ideas, the Workshop focused on spatial statistical methods. To date there are many new spatial statistical methods designed with massive data sets in mind, in the literature. However, very few have been implemented for remote sensing data, and none have been implemented in operational settings like those used by NASA and NOAA. A major impediment to their use in these cases is that the data are not only massive, but are stored in different physical locations. These data must be brought together in some way in order to estimate spatial covariance functions, but moving data to a central location for analysis is tedious at best and impossible at worst. Some remote data reduction is almost certainly necessary, but how much? What are the consequences for inference? The fundamental issue underlying these questions is how to navigate the trade-space between costs and uncertainty in the estimates or inferences that are ultimately produced.
While low disturbance ("quiet") hypersonic wind tunnels are believed to provide more reliable extrapolation of boundary layer transition behavior from ground to flight, the presently available quiet facilities are limited to Mach 6, moderate Reynolds numbers, low freestream enthalpy, and subscale models. As a result, only conventional ("noisy") wind tunnels can reproduce both Reynolds numbers and enthalpies of hypersonic flight configurations, and must therefore be used for flight vehicle test and evaluation involving high Mach number, high enthalpy, and larger models. This article outlines the recent progress and achievements in the characterization of tunnel noise that have resulted from the coordinated effort within the AVT-240 specialists group on hypersonic boundary layer transition prediction. New Direct Numerical Simulation (DNS) datasets elucidate the physics of noise generation inside the turbulent nozzle wall boundary layer, characterize the spatiotemporal structure of the freestream noise, and account for the propagation and transfer of the freestream disturbances to a pitot-mounted sensor. The new experimental measurements cover a range of conventional wind tunnels with different sizes and Mach numbers from 6 to 14 and extend the database of freestream fluctuations within the spectral range of boundary layer instability waves over commonly tested models. Prospects for applying the computational and measurement datasets for developing mechanism-based transition prediction models are discussed.
The biomechanics of exercise in space is difficult to study and there are unknowns surrounding exercise performance on future space exploration countermeasures systems. These issues are beginning to be addressed through enhanced modeling techniques fueled initially by human-in-the-loop data collections in ground-based environments. The presentation will focus on an effort completed at the University of South Florida to apply the Computer Assisted Rehabilitation Environment (CAREN) system to address a human spaceflight need. The research explored the interaction between a human and a moving platform while exercise was completed.
The NEQAIR line-by-line radiation code has been incorporated into the DPLR Navier-Stokes flow solver such that the NEQAIR subroutines are now callable functions of DPLR. The coupled DPLR-NEQAIR code was applied to compute the convective and radiative heating rates over high-mass Mars entry vehicles. Two vehicle geometries were considered - a 15 m diameter 70-degree sphere cone configuration and a slender, mid-L/D vehicle with a diameter of 5 m called an Ellipsled. The entry masses ranged from 100 to 165 metric tons. Solutions were generated for entry velocities ranging from 6.5 to 9.1 km/s. The coupled fluids-radiation solutions were performed at the peak heating location along trajectories generated by the Traj trajectory analysis code. The impact of fluids-radiation coupling is a function of the level of radiative heating and the freestream density and velocity. For the high-mass Mars vehicles examined in this study, coupling effects were greatest for entry velocities above 8.5 km/s where the surface radiative heating was reduced by up 17%. Generally speaking, the Ellipsled geometry experiences a lower peak radiative heating rate but a higher peak turbulent convective heating rate than the MSL-based vehicle.
A laser-generated plasma acoustic point source is used to directly measure the point spread function (PSF) of a microphone phased array. In beamforming analysis of microphone phased array data, the true acoustic field is convolved with the array's PSF. By directly measuring the PSF, corrections to the array analysis can be computed and applied. The acoustic source is measured in an open-jet aeroacoustic facility to evaluate the effects of sampling rate, microphone installation, source shift, reflections, shear layer refraction and model presence. Results show that measurements exhibit behavior consistent with theory with regard to source shift and shear layer refraction. Application of a measured PSF in beamforming analysis shows the process provides an effective in-situ method for array calibration both with and without flow and allows for corrections to incorporate reflections and scattering. The technique improves the agreement of beamforming results with the true spectrum of a known source, especially in the presence of reflections.
A non-intrusive uncertainty quantification method is applied to computational analysis of supersonic, low-boom aircraft. The mean and standard deviation statistics of the pressure waveforms and loudness metrics are evaluated through use of numerical quadrature. The probability density function (p.d.f.) of these outputs is evaluated via kernel density estimation. The simulations use an inviscid, embedded-boundary Cartesian-mesh flow solver in the nearfield combined with an augmented Burgers’ equation solver for propagation in the farfield. The results show that the p.d.f. of the waveform is bimodal at shocks, which makes the mean and standard deviation statistics inappropriate. Despite this limitation, we show that the moment statistics can provide effective assessment of discrepancies when comparing with experimental data. This is demonstrated by presenting uncertainty analysis of a wind-tunnel test and showing that we significantly improve the predictions when we include the test uncertainties in the simulation. Normal distributions are obtained for the ground signature and loudness metrics, which is primarily due to the careful shaping of the low-boom waveform. Separation of variables and error control are used to reduce computational cost. We demonstrate that this is an efficient approach in the sense of balancing numerical errors in the statistics quadrature with discretization errors in the solvers.
This work presents probabilistic intent models for two typical vehicles in ETM operational environment. Several methods, including analytical methods for approximated solutions and a numerical method for exact solution, are presented and applied to compute the intent conflict probability for ETM operations. A comparison of these methods will be conducted in the final paper. Furthermore, simulations will be performed to verify the probabilistic intent model and verify the results of intent conflict probability from different methods.
This panel identifies the challenges of supporting medical events in deep space using integrated systems software to augment existing capabilities during increasingly Earth-independent missions where an asynchronous communication environment becomes routine. An interdisciplinary team of software designers, physicians, human factors engineers, and computational modelers applied their respective expertise to develop a roadmap for supporting the crew making medical decisions in more autonomous fashion with time-delayed ground support. The first presentation describes predictive modeling implemented to assist medical system design and address risk reduction using robust clinical decision support software. The second presentation details how operational and environmental challenges guide assumptions and, in turn, by what means requirements for medical decision-making in deep space are derived. The third presentation describes and defines the skills and capabilities an exploration spaceflight medical officer will need to perform effectively during extended-duration spaceflight missions. The fourth presentation covers the potential models and function of the software element for supporting clinical decisions. The final presentation covers how these elements may work together with ground support to provide comprehensive care despite deep space travel's extreme challenges and limitations.