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NASA NTRS2003

Robust and Simple Non-Reflecting Boundary Conditions for the Euler Equations: A New Approach Based on the Space-Time CE/SE Method

This paper reports on a significant advance in the area of non-reflecting boundary conditions (NRBCs) for unsteady flow computations. As a part of the development of the space-time conservation element and solution element (CE/SE) method, sets of NRBCs for 1D Euler problems are developed without using any characteristics-based techniques. These conditions are much simpler than those commonly reported in the literature, yet so robust that they are applicable to subsonic, transonic and supersonic flows even in the presence of discontinuities. In addition, the straightforward multidimensional extensions of the present 1D NRBCs have been shown numerically to be equally simple and robust. The paper details the theoretical underpinning of these NRBCs, and explains their unique robustness and accuracy in terms of the conservation of space-time fluxes. Some numerical results for an extended Sod's shock-tube problem, illustrating the effectiveness of the present NRBCs are included, together with an associated simple Fortran computer program. As a preliminary to the present development, a review of the basic CE/SE schemes is also included.

Chang, Sin-Chung↗

NASA NTRS1990

Time-dependent boundary conditions for hyperbolic systems. II

A general boundary condition formalism is developed for all types of boundary conditions to which hyperbolic systems are subject; the formalism makes possible a 'cookbook' approach to boundary conditions, by means of which novel boundary 'recipes' may be derived and previously devised ones may be consulted as required. Numerous useful conditions are derived for such CFD problems as subsonic and supersonic inflows and outflows, nonreflecting boundaries, force-free boundaries, constant pressure boundaries, and constant mass flux. Attention is given to the computation and integration of time derivatives.

Thompson, Kevin W.↗

NASA NTRS2002

Ground Operations of the ISS GNC Babb-Mueller Atmospheric Density Model

The ISS GNC system was updated recently with a new software release that provides onboard state determination capability. Prior to this release, only the Russian segment maintained and propagated the onboard state, which was periodically updated through Russian ground tracking. The new software gives the US segment the capability for maintaining the onboard state, and includes new GPS and state vector propagation capabilities. Part of this software package is an atmospheric density model based on the Babb-Mueller algorithm. Babb-Mueller efficiently mimics a full analytical density model, such as the Jacchia model. While lacchia is very robust and is used in the Mission Control Center, it is too computationally intensive for use onboard. Thus, Babb-Mueller was chosen as an alternative. The onboard model depends on a set of calibration coefficients that produce a curve fit to the lacchia model. The ISS GNC system only maintains one set of coefficients onboard, so a new set must be uplinked by controllers when the atmospheric conditions change. The onboard density model provides a real-time density value, which is used to calculate the drag experienced by the ISS. This drag value is then incorporated into the onboard propagation of the state vector. The propagation of the state vector, and therefore operation of the BabbMueller algorithm, will be most critical when GPS updates and secondary state vector sources fail. When GPS is active, the onboard state vector will be updated every ten seconds, so the propagation error is irrelevant. When GPS is inactive, the state vector must be updated at least every 24 hours, based on current protocol. Therefore, the Babb-Mueller coefficients must be accurate enough to fulfill the state vector accuracy requirements for at least one day. A ground operations concept was needed in order to manage both the on board Babb-Mueller density model and the onboard state quality. The Babb-Mueller coefficients can be determined operationally in two ways. The first method is to calibrate the coefficients in real-time, where a set of custom coefficients is generated for the real-time atmospheric conditions. The second approach is to generate pre-canned sets of coefficients that encompass the expected atmospheric conditions over the lifetime of the vehicle. These predetermined sets are known as occurrences. Even though a particular occurrence will not match the true atmospheric conditions, the error will be constrained by limiting the breadth of each occurrence. Both methods were investigated and the advantages and disadvantages of each were considered. The choice between these implementations was a trade-off between the additional accuracy of the real-time calibration and the simpler development for the approach using occurrences. The operations concept for the frequency of updates was also explored, and depends on the deviation in solar flux that still achieves the necessary accuracy of the coefficients. This was determined based on historical solar flux trends. This analysis resulted in an accurate and reliable implementation of the Babb-Mueller coefficients and how flight controllers use them during realtime operations.

Brogan, Jonathan↗

NASA NTRS1986

Simulation of cosmic irradiation conditions in thick target arrangements

One approach to simulate 2-pi irradiation conditions of planetary surfaces which has been widely applied in the past are bombardments of so called thick targets. A very large thick target was exposed recently to 2.1 GeV protons at the Bevatron-Bevalac in Berkeley. In a 100x100x180 cm steel-surrounded granodiorite target radioactive medium and high energy spallation products of the incident primary and of secondary particles were analyzed along the beam axis down to depths of 140 g/cm(2) in targets such as Cu, Ni, Co, Fe, T, Si, SiO2 and Al. Activities of these nuclides were exclusively determined via instrumental gamma-ray spectroscopy. Relative yields of neutron capture and spallation products induced in Co and Cu targets during the thick target bombardment are shown as a function of depth. The majority of the medium energy products such as Co-58 from Co targets exhibit a maximum at shallow depths of 40-60 g/cm(2) and then decrease exponentially. In a comparable 600 MeV proton bombarded thick target such a slight maximum for medium energy products was not observed. Rather, Co-58 activities in Co decreased steadily with the highest activity at the surface. The activities of the n-capture product Co-60 increase steadily starting at the surface. This indicates the rapidly growing flux of low energy neutrons within the target.

Theis, S.↗

NASA NTRSDate not supplied

Overlapping Conditions in IMPACT

Introduction The IMPACT 1.0 model assumes independence of 119 different medical conditions. That is, it is assumed that one medical event maps to a single medical condition. However, it is often the case that a single medical event may lead to several different concurrent conditions (e.g., a single accident resulting in multiple fractures, chest/abdominal trauma, and sepsis). There is a significant overlap between many of the conditions in ICL 1.0. For example, depression and anxiety are two separate conditions but often co-exist. This overlap may lead to an overestimation in the incidence calculation. In future iterations of the model, we plan to address progression of medical conditions. Methods There are two possible methods to approach progression of a medical condition. The first is to take any medical condition in ICL, calculate its incidence and determine its outcomes no matter what sequelae occur. For example, calculate the incidence of prostatitis and determine its metrics (e.g., loss of crew life, risk of medical evacuation or task time affected) no matter what the sequelae might be (sepsis, hydronephrosis, renal failure, etc.). The second approach is to take any medical condition in the ICL and calculate the outcomes based on transitions to any other condition. For example, calculate the incidence of nephrolithiasis and determine the incidence of each possible transition (e.g., hydronephrosis, renal failure, UTI, pyelonephritis, sepsis) and then determine its metrics. With perfectly informative evidence, the answers should be the same using either method. The question is which approach best reduces the opportunity for overlapping. Results The team identified 31 conditions that were the most likely to transition to a secondary condition such as sepsis and respiratory failure. It was felt that the first approach, as described above, would be the easiest to implement and would have the greatest reduction in overlapping conditions. The identified conditions were primarily infectious conditions, like UTI and pneumonia (which could lead to both respiratory failure and sepsis), toxic inhalations, cardiac arrest, seizures, and trauma. Once these conditions were identified, the conditions were divided between the four clinicians on the team to identify those that were not consistent with the others in way they were approached. There were 13 conditions that were found to be problematic. Some condition definitions needed to be changed to eliminate references to transitions or to update them in cases where the definitions were out of date. Some conditions required new evidence to correct the loss of crew life, and one condition was felt to have so much overlap that it was recommended for elimination. A second effort required modification of the sepsis incidence calculation to prevent double counting of the conditions, such as prostatitis, that could progress to sepsis. Conclusion The team made significant progress in clarifying the method for dealing with transitions from one medical condition to another. In addition, errors were found and corrected in definitions, incidence, and loss of crew life as well as a condition in which reference was made to a CLiFF that was no longer included. These modifications will provide greater fidelity in the IMPACT model and reduce overlap.

Arian Anderson↗

NASA NTRS2012

Synthetic and Enhanced Vision Systems for NextGen (SEVS) Simulation and Flight Test Performance Evaluation

The Synthetic and Enhanced Vision Systems for NextGen (SEVS) simulation and flight tests are jointly sponsored by NASA's Aviation Safety Program, Vehicle Systems Safety Technology project and the Federal Aviation Administration (FAA). The flight tests were conducted by a team of Honeywell, Gulfstream Aerospace Corporation and NASA personnel with the goal of obtaining pilot-in-the-loop test data for flight validation, verification, and demonstration of selected SEVS operational and system-level performance capabilities. Nine test flights (38 flight hours) were conducted over the summer and fall of 2011. The evaluations were flown in Gulfstream.s G450 flight test aircraft outfitted with the SEVS technology under very low visibility instrument meteorological conditions. Evaluation pilots flew 108 approaches in low visibility weather conditions (600 ft to 2400 ft visibility) into various airports from Louisiana to Maine. In-situ flight performance and subjective workload and acceptability data were collected in collaboration with ground simulation studies at LaRC.s Research Flight Deck simulator.

Shelton, Kevin J.↗

NASA NTRS2014

Visual Advantage of Enhanced Flight Vision System During NextGen Flight Test Evaluation

Synthetic Vision Systems and Enhanced Flight Vision System (SVS/EFVS) technologies have the potential to provide additional margins of safety for aircrew performance and enable operational improvements for low visibility operations in the terminal area environment. Simulation and flight tests were jointly sponsored by NASA's Aviation Safety Program, Vehicle Systems Safety Technology project and the Federal Aviation Administration (FAA) to evaluate potential safety and operational benefits of SVS/EFVS technologies in low visibility Next Generation Air Transportation System (NextGen) operations. The flight tests were conducted by a team of Honeywell, Gulfstream Aerospace Corporation and NASA personnel with the goal of obtaining pilot-in-the-loop test data for flight validation, verification, and demonstration of selected SVS/EFVS operational and system-level performance capabilities. Nine test flights were flown in Gulfstream's G450 flight test aircraft outfitted with the SVS/EFVS technologies under low visibility instrument meteorological conditions. Evaluation pilots flew 108 approaches in low visibility weather conditions (600 feet to 3600 feet reported visibility) under different obscurants (mist, fog, drizzle fog, frozen fog) and sky cover (broken, overcast). Flight test videos were evaluated at three different altitudes (decision altitude, 100 feet radar altitude, and touchdown) to determine the visual advantage afforded to the pilot using the EFVS/Forward-Looking InfraRed (FLIR) imagery compared to natural vision. Results indicate the EFVS provided a visual advantage of two to three times over that of the out-the-window (OTW) view. The EFVS allowed pilots to view the runway environment, specifically runway lights, before they would be able to OTW with natural vision.

Kramer, Lynda J.↗

NASA NTRS2005

Flow Visualization at Cryogenic Conditions Using a Modified Pressure Sensitive Paint Approach

A modification to the Pressure Sensitive Paint (PSP) method was used to visualize streamlines on a Blended Wing Body (BWB) model at full-scale flight Reynolds numbers. In order to achieve these conditions, the tests were carried out in the National Transonic Facility operating under cryogenic conditions in a nitrogen environment. Oxygen is required for conventional PSP measurements, and several tests have been successfully completed in nitrogen environments by injecting small amounts (typically < 3000 ppm) of oxygen into the flow. A similar technique was employed here, except that air was purged through pressure tap orifices already existent on the model surface, resulting in changes in the PSP wherever oxygen was present. The results agree quite well with predicted results obtained through computational fluid dynamics analysis (CFD), which show this to be a viable technique for visualizing flows without resorting to more invasive procedures such as oil flow or minitufts.

Watkins, A. Neal↗

NASA NTRS1986

Control and display requirements for decelerating approach and landing of fixed- and rotary-wing VSTOL aircraft

This paper reviews the results of several simulation investigations of rotary-wing and fixed-wing VSTOL aircraft performing terminal-area operations that include decelerating approaches under instrument conditions and recovery to either fixed landing pads or a ship. By concentrating on instrument decelerating approaches and the hover and landing, it is possible to compare directly the control and display requirements for similar tasks for aircraft with and without vectored thrust capability. Collectively, the results from these experiments, together with other simulator and flight experiments and operational experience, provide a consistent view of control and display complexity required for similar operational capability in adverse weather for the two types of VSTOL configurations. Some initial data showing influence of the transition corridor on flying qualities during transition are pesented and lead to a general discussion of the problem of operating margin definition.

Lebacqz, J. V.↗

NASA NTRS1941

Flight Investigation of Wing-gun Fairings on a Fighter Type Airplane

Description is given of flight tests conducted on gun fairings, designed to correct the detrimental effects of the projecting and submerged wing guns on an F4F-3 fighter. It was found that the installation of unfaired guns on a clean wing resulted in a premature stall that increased the stalling speed in the carrier-approach and landing conditions of flight by suitably fairing the guns, it was possible to reduce the stalling speeds to values approaching very nearly the clean-wing values.

LOOPING - GROUND↗

NASA NTRS1998

XV-15 Tiltrotor Low Noise Terminal Area Operations

Acoustic data have been acquired for the XV-15 tiltrotor aircraft performing a variety of terminal area operating procedures. This joint NASA/Bell/Army test program was conducted in two phases. During Phase 1 the XV-15 was flown over a linear array of microphones, deployed perpendicular to the flight path, at a number of fixed operating conditions. This documented the relative noise differences between the various conditions. During Phase 2 the microphone array was deployed over a large area to directly measure the noise footprint produced during realistic approach and departure procedures. The XV-15 flew approach profiles that culminated in IGE hover over a landing pad, then takeoffs from the hover condition back out over the microphone array. Results from Phase 1 identify noise differences between selected operating conditions, while those from Phase 2 identify differences in noise footprints between takeoff and approach conditions and changes in noise footprint due to variation in approach procedures.

Conner, David A.↗

NASA NTRS2019

Atmospheric Chemistry Modeling Using Machine Learning

Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (milli-seconds for O1D to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a chemistry model. We have investigated a machine learning approach to emulate the chemistry instead of solving the differential equations numerically. From a one-month simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry. This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, etc. We discuss speed and accuracy of our approach, and highlight some potential future directions for improving it.

Keller, Christoph A.↗

NASA NTRS2019

Machine Learning Application to Atmospheric Chemistry Modeling

Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (milli-seconds for O (sup 1) D (Deuterium) to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a chemistry model. We have investigated a machine learning approach to emulate the chemistry instead of solving the differential equations numerically. From a one-month simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry. This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, etc. We discuss speed and accuracy of our approach, and highlight some potential future directions for improving it.

Keller, Christoph A.↗

NASA NTRS2019

Atmospheric Chemistry Modeling and Air Quality Forecasting Using Machine Learning

Atmospheric chemistry models are a central tool to study the impact of chemical constituents on the environment, vegetation and human health. These models split the atmosphere in a large number of grid-boxes and consider the emission of compounds into these boxes and their subsequent transport, deposition, and chemical processing. The chemistry is represented through a series of simultaneous ordinary differential equations, one for each compound. Given the difference in life-times between the chemical compounds (milli-seconds for O1D to years for CH4) these equations are numerically stiff and solving them consists of a significant fraction of the computational burden of a chemistry model.We have investigated a machine learning approach to emulate the chemistry instead of solving the differential equations numerically. From a one-month simulation of the GEOS-Chem model we have produced a training dataset consisting of the concentration of compounds before and after the differential equations are solved, together with some key physical parameters for every grid-box and time-step. From this dataset we have trained a machine learning algorithm (regression forest) to be able to predict the concentration of the compounds after the integration step based on the concentrations and physical state at the beginning of the time step. We have then included this algorithm back into the GEOS-Chem model, bypassing the need to integrate the chemistry.This machine learning approach shows many of the characteristics of the full simulation and has the potential to be substantially faster. There are a wide range of application for such an approach - generating boundary conditions, for use in air quality forecasts, chemical data assimilation systems, etc. We discuss speed and accuracy of our approach, and highlight some potential future directions for improving it.

Keller, Christoph A.↗

NASA NTRS1987

Space vehicle approach velocity judgments under simulated visual space conditions

Thirty-five volunteers responded when they first perceived an increase in apparent size of a collimated, 2-D image of an Orbiter vehicle. The test variables of interest included the presence of a fixed angular reticle within the field of view (FOV); three initial Orbiter distances; three constant Orbiter approach velocities corresponding to 1.6, 0.8, and 0.4 percent of the initial distance per second; and two background starfield velocities. It was found that: (1) at each initial range, increasing approach velocity led to a larger distance between the eye and Orbiter image at threshold; (2) including the fixed reticle in the FOV produced a smaller distance between the eye and Orbiter image at threshold; and (3) increasing background star velocity during this judgment led to a smaller distance between the eye and Orbiter image at threshold. The last two findings suggest that other detail within the FOV may compete for available attention which otherwise would be available for judging image expansion; thus, the target has to approach the observer nearer than otherwise if these details were present. These findings are discussed in relation to previous research and possible underlying mechanisms.

Haines, Richard F.↗

NASA NTRS1987

Space vehicle approach velocity judgments under simulated visual space conditions

Haines, Richard F.↗

NASA NTRS1991

Control concept for maneuvering in hypersonic flight

This research investigates an approach to provide precise, coordinated maneuver control during excursions from a hypersonic cruise flight path while observing the necessary flight condition constraints. The approach achieves specified guidance commands by resolving altitude and cross-range errors into a load factor and bank angle command through a coordinate transformation which acts as an interface between outer loop guidance controls and inner loop flight controls. This interface, referred to as a 'resolver', applies constraints on angle-of-attack and dynamic pressure perturbations while prioritizing altitude regulation over crossrange. An unpiloted test simulation, in which the resolver was used to drive inner-loop flight controls, produced time histories of responses to guidance commands at Mach numbers of 6, 10, 15, and 20. It is shown that angle-of-attack and throttle perturbation constraints, combined with high-speed flight effects and the desire to maintain constant dynamic pressure, significantly impact the maneuver envelope for a hypersonic vehicle. Turn rate, climb rate, and descent rate limits are expressed in terms of these constraints.

Raney, David L.↗

NASA NTRS1992

Control integration concept for hypersonic cruise-turn maneuvers

Piloting difficulties associated with conducting aircraft maneuvers in hypersonic flight are caused in part by the nonintuitive nature of the aircraft response and the stringent constraints anticipated on allowable angle of attack and dynamic pressure variations. An approach is documented that provides precise, coordinated maneuver control during excursions from a hypersonic cruise flight path and the necessary flight condition constraints. The approach is to achieve specified guidance commands by resolving altitude and cross range errors into a load factor and bank angle command by using a coordinate transformation that acts as an interface between outer and inner loop flight controls. This interface, referred to as a 'resolver', applies constraints on angle of attack and dynamic pressure perturbations while prioritizing altitude regulation over cross range. An unpiloted test simulation, in which the resolver was used to drive inner loop flight controls, produced time histories of responses to guidance commands and atmospheric disturbances at Mach numbers of 6, 10, 15, and 20. Angle of attack and throttle perturbation constraints, combined with high speed flight effects and the desire to maintain constant dynamic pressure, significantly impact the maneuver envelope for a hypersonic vehicle.

Raney, David L.↗