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NASA NTRS2008

The NASA MSFC Earth Global Reference Atmospheric Model-2007 Version

Reference or standard atmospheric models have long been used for design and mission planning of various aerospace systems. The NASA/Marshall Space Flight Center (MSFC) Global Reference Atmospheric Model (GRAM) was developed in response to the need for a design reference atmosphere that provides complete global geographical variability, and complete altitude coverage (surface to orbital altitudes) as well as complete seasonal and monthly variability of the thermodynamic variables and wind components. A unique feature of GRAM is that, addition to providing the geographical, height, and monthly variation of the mean atmospheric state, it includes the ability to simulate spatial and temporal perturbations in these atmospheric parameters (e.g. fluctuations due to turbulence and other atmospheric perturbation phenomena). A summary comparing GRAM features to characteristics and features of other reference or standard atmospheric models, can be found Guide to Reference and Standard Atmosphere Models. The original GRAM has undergone a series of improvements over the years with recent additions and changes. The software program is called Earth-GRAM2007 to distinguish it from similar programs for other bodies (e.g. Mars, Venus, Neptune, and Titan). However, in order to make this Technical Memorandum (TM) more readable, the software will be referred to simply as GRAM07 or GRAM unless additional clarity is needed. Section 1 provides an overview of the basic features of GRAM07 including the newly added features. Section 2 provides a more detailed description of GRAM07 and how the model output generated. Section 3 presents sample results. Appendices A and B describe the Global Upper Air Climatic Atlas (GUACA) data and the Global Gridded Air Statistics (GGUAS) database. Appendix C provides instructions for compiling and running GRAM07. Appendix D gives a description of the required NAMELIST format input. Appendix E gives sample output. Appendix F provides a list of available parameters to enable the user to generate special output. Appendix G gives an example and guidance on incorporating GRAM07 as a subroutine in other programs such as trajectory codes or orbital propagation routines.

Leslie, F.W.↗

NASA NTRS2002

North Atlantic Surface Winds Examined as the Source of Warm Advection into Europe in Winter

When from the southwest, North Atlantic ocean surface winds are known to bring warm and moist airmasses into central Europe in winter. By tracing backward trajectories from western Europe, we establish that these airmasses originate in the southwestern North Atlantic, in the very warm regions of the Gulf Stream. Over the eastern North Atlantic, Lt the gateway to Europe, the ocean-surface winds changed directions in the second half of the XXth century, those from the northwest and from the southeast becoming so infrequent, that the direction from the southwest became even more dominant. For the January-to-March period, the strength of south-westerlies in this region, as well as in the source region, shows in the years 1948-1995 a significant increase, above 0.2 m/sec/ decade. Based on the sensitivity of the surface temperature in Europe, slightly more than 1 C for a 1m/sec increase in the southwesterly wind, found in the previous studies, the trend in the warm advection accounts for a large part of the warming in Europe established for this period in several reports. However, for the most recent years, 1996-2001, the positive trend in the southwesterly advection appears to be is broken, which is consistent with unseasonally cold events reported in Europe in those winters. This study had, some bearing on evaluating the respective roles of the North Atlantic Oscillation and the Greenhouse Gas Global warming, GGG, in the strong winter warming observed for about half a century over the northern-latitude continents. Changes in the ocean-surface temperatures induced by GGG may have produced the dominant southwesterly direction of the North Atlantic winds. However, this implies a monotonically (apart from inherent interannual variability) increasing advection, and if the break in the trend which we observe after 1995 persists, this mechanism is counter-indicated. The 1948-1995 trend in the south-westerlies could then be considered to a large degree attributable to the North Atlantic Oscillation.

Otterman, J.↗

DOE OSTI2026

Custom-trained Machine-learning Interatomic Potentials: ZnCl2 Aqueous Solution

This dataset was generated using an iterative active-learning strategy implemented in the ArcaNN software package (https://github.com/arcann-chem/arcann_training) to train machine-learning interatomic potentials for aqueous ZnCl2 solutions. Each active-learning cycle consisted of three stages: training, exploration, and labeling. The initial training set combined configurations generated in this work from enhanced-sampling ab initio molecular dynamics simulations with configurations from a previously reported neural-network-potential study of aqueous ZnCl2. The enhanced-sampling ab initio molecular dynamics simulations involved Zn–Cl separation and the chloride coordination number around Zn²? as collective variables. These configurations served as the seed dataset. Subsequent active-learning cycles expanded the training set by identifying and labeling configurations that were poorly represented by the current models, thereby improving coverage of ion-association states and changes in local coordination and charge-state environments relevant to the solution free-energy landscape. For all selected configurations, single-point calculations of the total energies and atomic forces were performed within density functional theory using the CP2K Quickstep module. Reference calculations employed the revPBE-D3 and r2SCAN exchange-correlation functionals. Motivated by recent work on aqueous Zn²?, the main revPBE calculations omitted D3 dispersion contributions involving Zn²?, while retaining the D3 correction for water and chloride. For comparison, fully dispersion-corrected revPBE-D3 reference calculations were also performed, with D3 applied to all species, including Zn²?. Valence electrons were treated explicitly, while core electrons were represented using norm-conserving Goedecker–Teter–Hutter pseudopotentials. The wave functions were expanded using the mixed Gaussian-and-plane-wave scheme with TZV2P-MOLOPT basis sets for all elements and a 600 Ry auxiliary plane-wave cutoff for the electron density. Self-consistent-field convergence was accelerated using the orbital-transformation and Direct Inversion in the Iterative Subspace algorithms, with a convergence threshold of 10?6. All single-point calculations were performed in periodic orthorhombic cells. The CELL_REF keyword in CP2K was used to define a fixed reference cell with a box length of 25 Å. This treatment ensured a consistent reference for configurations extracted from NpT trajectories with fluctuating cell dimensions. The resulting DFT energies and atomic forces constitute the ground-truth labels used to train the MLIPs. The resulting MLIP was trained for aqueous ZnCl2 solutions spanning concentrations from 0 to 30 molal and a broad pH range, from strongly acidic to strongly basic conditions. Representative examples of configurations included in the MLIP training dataset are provided below. These include 1) Representative configurations from the dataset labeled at the revPBE-D3 level, with D3 dispersion interactions involving Zn2+ excluded (revPBE-wo-D3). 2) Representative configurations from the dataset labeled at the fully dispersion-corrected revPBE-D3 level, with D3 interactions applied to all species, including Zn2+ (revPBE-D3). 3) Representative configurations from the dataset labeled at the r2SCAN level of theory (r2SCAN).

Dinpajooh, Mohammadhasan [Pacific Northwest Nation↗

NASA NTRS2004

Computationally-Efficient Minimum-Time Aircraft Routes in the Presence of Winds

A computationally efficient algorithm for minimizing the flight time of an aircraft in a variable wind field has been invented. The algorithm, referred to as Neighboring Optimal Wind Routing (NOWR), is based upon neighboring-optimal-control (NOC) concepts and achieves minimum-time paths by adjusting aircraft heading according to wind conditions at an arbitrary number of wind measurement points along the flight route. The NOWR algorithm may either be used in a fast-time mode to compute minimum- time routes prior to flight, or may be used in a feedback mode to adjust aircraft heading in real-time. By traveling minimum-time routes instead of direct great-circle (direct) routes, flights across the United States can save an average of about 7 minutes, and as much as one hour of flight time during periods of strong jet-stream winds. The neighboring optimal routes computed via the NOWR technique have been shown to be within 1.5 percent of the absolute minimum-time routes for flights across the continental United States. On a typical 450-MHz Sun Ultra workstation, the NOWR algorithm produces complete minimum-time routes in less than 40 milliseconds. This corresponds to a rate of 25 optimal routes per second. The closest comparable optimization technique runs approximately 10 times slower. Airlines currently use various trial-and-error search techniques to determine which of a set of commonly traveled routes will minimize flight time. These algorithms are too computationally expensive for use in real-time systems, or in systems where many optimal routes need to be computed in a short amount of time. Instead of operating in real-time, airlines will typically plan a trajectory several hours in advance using wind forecasts. If winds change significantly from forecasts, the resulting flights will no longer be minimum-time. The need for a computationally efficient wind-optimal routing algorithm is even greater in the case of new air-traffic-control automation concepts. For air-traffic-control automation, thousands of wind-optimal routes may need to be computed and checked for conflicts in just a few minutes. These factors motivated the need for a more efficient wind-optimal routing algorithm.

Jardin, Matthew R.↗

NASA NTRS2001

Dealing with the Asteroid Impact Hazard

The small fraction of the asteroids with Earth-crossing or Earth-approaching orbits is of special interest to us because many will eventually impact our planet. The time-averaged impact flux as a function of projectile energy can be derived from lunar cratering statistics, although we have little information on the possible variability of this flux over time. The effects of impacts of various energies can be modeled, using data from historic impacts (such as the KT impactor 65 million years ago), nuclear explosive testing, and the observed 1994 bombardment of Jupiter by fragments of comet Shoemaker-Levy 9. It is of particular interest to find from such models that the terrestrial environment is highly vulnerable to perturbation from impacts, so that even such a small event as the KT impact (by a projectile roughly 15 km in diameter) can lead to a mass extinction. Combining the impact flux with estimates of environmental and ecological effects reveals that the greatest contemporary hazard is associated with impactors near one million megatons energy. The current impact hazard is significant relative to other natural hazards, and arguments can be developed to illuminate a variety of public policy issues. These include the relative risk of different impact scenarios and the associated costs and probability of success of countermeasures. It is generally agreed that the first step is to survey and catalogue the thousand-or-so Near Earth Asteroids (NEAs), and we review the status of the Spaceguard NEA Survey. We compare the efficiency of various ground and space-based approaches and consider the challenges of international coordination and the problems and opportunities associated with communicating the results with the press and the public. It is also important to reflect on how the impact hazard might be dealt with by both national governments and international decision-making bodies, and to anticipate ways of mitigating the danger if a NEA were located on an apparent Earth-impact trajectory. As the most extreme known example of a natural hazard with low probability but severe global consequences. the NEA impact hazard calls for the most careful consideration and planning.

Morrison, David↗

NASA NTRS2017

Models of Sector Flows Under Local, Regional and Airport Weather Constraints

Recently, the ATM community has made important progress in collaborative trajectory management through the introduction of a new FAA traffic management initiative called a Collaborative Trajectory Options Program (CTOP). FAA can use CTOPs to manage air traffic under multiple constraints (manifested as flow constrained areas or FCAs) in the system, and it allows flight operators to indicate their preferences for routing and delay options. CTOPs also permits better management of the overall trajectory of flights by considering both routing and departure delay options simultaneously. However, adoption of CTOPs in airspace has been hampered by many factors that include challenges in how to identify constrained areas and how to set rates for the FCAs. Decision support tools providing assistance would be particularly helpful in effective use of CTOPs. Such DSTs tools would need models of demand and capacity in the presence of multiple constraints. This study examines different approaches to using historical data to create and validate models of maximum flows in sectors and other airspace regions in the presence of multiple constraints. A challenge in creating an empirical model of flows under multiple constraints is a lack of sufficient historical data that captures diverse situations involving combinations of multiple constraints especially those with severe weather. The approach taken here to deal with this is two-fold. First, we create a generalized sector model encompassing multiple sectors rather than individual sectors in order to increase the amount of data used for creating the model by an order of magnitude. Secondly, we decompose the problem so that the amount of data needed is reduced. This involves creating a baseline demand model plus a separate weather constrained flow reduction model and then composing these into a single integrated model. A nominal demand model is a flow model (gdem) in the presence of clear local weather. This defines the flow as a function of weather constraints in neighboring regions, airport constraints and weather in locations that can cause re-routes to the location of interest. A weather constrained flow reduction model (fwx-red) is a model of reduction in baseline counts as a function of local weather. Because the number of independent variables associated with each of the two decomposed models is smaller than that with a single model, need for amount of data is reduced. Finally, a composite model that combines these two can be represented as fwx-red (gdem(e), l) where e represents non-local constraints and l represents local weather. The approaches studied to developing these models are divided into three categories: (1) Point estimation models (2) Empirical models (3) Theoretical models. Errors in predictions of these different types of models have been estimated. In situations when there is abundant data, point estimation models tend to be very accurate. In contrast, empirical models do better than theoretical models when there is some data available. The biggest benefit of theoretical models is their general applicability in wider range situations once the degree of accuracy of these has been established.

Kulkarni, Deepak↗

NASA NTRS2017

Models of Sector Aircraft Counts in the Presence of Local, Regional and Airport Constraints

Kulkarni, Deepak↗

NASA NTRS2019

Using Graph Coloring to Compute Total Derivatives More Efficiently in OpenMDAO

When they are applicable, gradient based optimization algorithms are the most efficient way to solve design optimization problems. Although gradient based methods are generally efficient, they can be made significantly more so through the usage of analytic techniques to compute the necessary total derivatives. The traditional forward (direct) and reverse (adjoint) analytic techniques have computational costs that scale linearly with the number of design variables and the number of constraints, respectively. In this work, we present an application of a graph coloring algorithm to the analytic techniques for computing total derivative Jacobians in order to achieve much better computational scaling than the pure analytic methods can provide alone. A detailed theoretical explanation of how coloring algorithms interact with analytic derivative methods is presented that illustrates specific types of sparsity patterns that must be present in total derivative Jacobians in order for this coloring technique to be effective. The new technique has been implemented as a feature in the OpenMDAO framework and the implementation is demonstrated on two example problems. The performance on the example problems up to 50% reduction in compute cost for optimizations with bi-directional coloring compared to traditional constraint aggregation. Additionally, the results show how coloring technique alleviates some of the numerical difficulties that constraint aggregation can cause, leading to the ability to solve larger problems. It is expected that the new method will have wide applicability to multidisciplinary optimization problems, and that its availability in OpenMDAO will offer significant computational savings for users without the need for them to implement the coloring algorithm themselves.

Trajectory↗

NASA NTRS2001

Advanced Power and Propulsion: Insuring Human Survival and Productivity in Deep Space Missions

Dr. Chang-Diaz gave an intriguing presentation of his research in advanced rocket propulsion and its relevance for planning and executing crewed deep space explorations. Though not necessarily exclusively Martian, his thrust looks critically at future Mars missions. Initially Dr. Chang-Diaz showed the time constraints of Mars missions due to orbital mechanics and our present chemically powered rocket technology. Since essentially all the energy required to place current generation spacecraft into a Martian trajectory must be expended in the early minutes of a flight, most of such a mission is spent in free-fall drift, captive to the gravitational forces among Earth, the Sun, and Mars. The simple physics of such chemically powered missions requires nearly a year in transit for each direction of a Mars mission. And the optimal orientations of Earth and Mars for rendezvous require further time on or around Mars to await return. These extensions of mission duration place any crew under a three-fold jeopardy: (1) physiological deconditioning (which in some aspects is still unknown and unpreventable), (2) psychological stress, and (3) ionizing radiation. This latter risk is due to exposure of crew members for extended time to the highly unpredictable and potentially lethal radiations of open space. Any gains in shortening mission duration would reap equivalent or greater benefits for these crew concerns. Dr. Chang-Diaz has applied his training and expertise (Ph.D. from Massachusetts Institute of Technology in applied plasma physics) toward development of continuous rocket propulsion which would offer great time advantages in travel, and also more launch options than are now available. He clearly explained the enormous gains from a relatively low thrust accelerative force applied essentially continuously versus the high, but short-lived propulsion of present chemical rockets. In fact, such spacecraft could be powered throughout the mission, accelerating to approximately the midpoint and decelerating during the latter half. This would not only provide some level of gravity (acceleration) throughout the mission but also allow very high velocities to be achieved, thus saving many months of travel time. In proposing the design of such a spacecraft propulsion system, Dr. Chang-Diaz was quick to acknowledge the need for a large power source, which undoubtedly must be nuclear fueled at the solar distances involved. He calls his system the Variable Specific Impulse Magnetoplasma Rocket (VASIMR). The other major ingredient is a mass (deuterium, which could also function as a radiation shield for crews) for energizing into the ultra hot, high velocity exhaust plasma. He foresees models now functional in the laboratory soon to be tested in space. In fact, some of these concepts have already been tried there. His optimism and determination would have operational rockets in the next decades.

Chang-Diaz, Franklin R.↗

NASA NTRSDate not supplied

Multiple Probe Measurements at Uranus Motivated By Spatial Variability

Motivation: Spatial variations in the temperature field and composition of Uranus' atmosphere demonstrate a need for multiple entry probes to characterize vertical profiles in multiple locations. We will review variation of composition and temperature, which are produced by dynamical processes on a range of scales from global (polar anomalies, zonal bands) to regional (vortices, storms) [1–2]. In particular, the spatial variation of convective activity is not well understood based on existing remote sensing observations [3]. Understanding how these processes operate, and how they modulate variable composition, is key to constraining bulk atmospheric abundances. Abundances in turn provide cosmochemical constraints on planetary origins. Secondary probes at Uranus: Key measurements for secondary probes are temperature-pressure profiles, along with compositional profiles. Radio occultations are limited to shallow levels less than ~2 bar [4]. In situ temperature-pressure measurements (or atmospheric structure measurements) can unambiguously extend these results to deeper levels. Measurements with vertical resolution of at least 2 km are needed to characterize anomalies like the 1.2-bar feature from the Voyager 2 occultation at 2–6° S [4], which supports a range of temperature gradients depending on assumptions of composition. Simultaneous measurements of temperature, pressure, and composition are key to understanding this class of features. Species such as methane, hydrogen sulfide, and ammonia must be measured along a probe descent profile because they vary over several orders of magnitude due to the strong temperature dependence of their saturation vapor pressures [e.g., 5]. Results of these measurements can be interpreted to understand the potential for moist convective activity in the atmosphere. Lessons from the other giant planets: On Jupiter, the Galileo Probe's entry into a meteorologically distinct five-micron hot spot led many to interpret the local composition as column-stretched, so that well-mixed abundances were reached at deeper levels than in surrounding, unperturbed regions [6–8]. Ground-based microwave measurements and Juno data now indicate that the deep depletion of ammonia is a very widespread atmospheric characteristic not limited to 5-µm hot spots [9–11]. But in the absence of multiple probes, we do not know if the other volatiles H2S and H2O behave in the same way. The open questions for the Jupiter case strongly motivate sending multiple probes to Uranus. On Saturn, retrievals of NH3 and PH3 abundances at shallow levels vary with latitude [12], but it is unknown how deep these differences extend, which is why a Saturn probe (or probes) was a mission theme for NASA's New Frontiers 4 and 5 opportunities [13]. Challenges for secondary probes: Cost is an issue due to the perception that it involves sacrifices to other mission elements. Spacecraft trajectories may be constrained by needs for orbit insertion that limit probe deliveries to different latitudes, and additional limitations may be placed on communication windows for probe descent phases (particularly if multiple probes are released from the orbiter simultaneously) [14]. Finally, composition sensors for miniature secondary probes are not at the required technological maturity [15]. Mass spectrometers are typically too large, massive, and powerhungry, while smaller nanosensors are only beginning to be developed for planetary missions. Finally, the need for probe survival heating is most easily met by radioisotope heat sources, but these require regulatory approvals that are even more difficult to satisfy compared to standard environmental reviews [16], unless the secondary probe is designed as a core element of a mission. References: [1] Molter E.M., et al. (2021) PSJ, 2, 3. [2] Rowe-Gurney N., et al. (2021) Icar, 365, 114506. [3] Hueso R., Sánchez-Lavega A. (2019) SSRv, 215, 52. [4] Lindal G.F., et al. (1987) JGR, 92, 14987– 15001. [5] Simon A.A., et al. (2022) RemS, 14, 1518. [6] Atreya, S.K., et al. (1997) in The Three Galileos: The Man, the Spacecraft, the Telescope, pp. 249–260 (C. Barbieri et al., eds.). [7] Showman A.P., Ingersoll A.P. (1998) Icar, 132, 205–220. [8] Friedson A.J. (2005) Icar, 177, 1–17. [9] de Pater I., et al. (2001) Icar, 149, 66–78. [10] Li C., et al. (2017) GeoRL, 44, 5317–5325. [11] de Pater I., et al. (2019) Icar, 322, 168–191. [12] Fletcher L.N., et al. (2009) Icar, 202, 543–564. [13] National Research Council (2011) Vision and Voyages. [14] Sayanagi K.M., et al. (2020) SSRv, 216, 72. [15] Wong M.H. et al. (2021) BAAS, 53, 486. [16] Zide A., Mendoza-Hill A., Cheney D. (2022) COSPAR Abstracts H0.6-0012-22.

Michael H Wong↗

NASA NTRS2011

Orbit Determination of Spacecraft in Earth-Moon L1 and L2 Libration Point Orbits

The ARTEMIS mission, part of the THEMIS extended mission, is the first to fly spacecraft in the Earth-Moon Lissajous regions. In 2009, two of the five THEMIS spacecraft were redeployed from Earth-centered orbits to arrive in Earth-Moon Lissajous orbits in late 2010. Starting in August 2010, the ARTEMIS P1 spacecraft executed numerous stationkeeping maneuvers, initially maintaining a lunar L2 Lissajous orbit before transitioning into a lunar L1 orbit. The ARTEMIS P2 spacecraft entered a L1 Lissajous orbit in October 2010. In April 2011, both ARTEMIS spacecraft will suspend Lissajous stationkeeping and will be maneuvered into lunar orbits. The success of the ARTEMIS mission has allowed the science team to gather unprecedented magnetospheric measurements in the lunar Lissajous regions. In order to effectively perform lunar Lissajous stationkeeping maneuvers, the ARTEMIS operations team has provided orbit determination solutions with typical accuracies on the order of 0.1 km in position and 0.1 cm/s in velocity. The ARTEMIS team utilizes the Goddard Trajectory Determination System (GTDS), using a batch least squares method, to process range and Doppler tracking measurements from the NASA Deep Space Network (DSN), Berkeley Ground Station (BGS), Merritt Island (MILA) station, and United Space Network (USN). The team has also investigated processing of the same tracking data measurements using the Orbit Determination Tool Kit (ODTK) software, which uses an extended Kalman filter and recursive smoother to estimate the orbit. The orbit determination results from each of these methods will be presented and we will discuss the advantages and disadvantages associated with using each method in the lunar Lissajous regions. Orbit determination accuracy is dependent on both the quality and quantity of tracking measurements, fidelity of the orbit force models, and the estimation techniques used. Prior to Lissajous operations, the team determined the appropriate quantity of tracking measurements that would be needed to meet the required orbit determination accuracies. Analysts used the Orbit Determination Error Analysis System (ODEAS) to perform covariance analyses using various tracking data schedules. From this analysis, it was determined that 3.5 hours of DSN TRK-2-34 range and Doppler tracking data every other day would suffice to meet the predictive orbit knowledge accuracies in the Lissajous region. The results of this analysis are presented. Both GTDS and ODTK have high-fidelity environmental orbit force models that allow for very accurate orbit estimation in the lunar Lissajous regime. These models include solar radiation pressure, Earth and Moon gravity models, third body gravitational effects from the Sun, and to a lesser extent third body gravitational effects from Jupiter, Venus, Saturn, and Mars. Increased position and velocity uncertainties following each maneuver, due to small execution performance errors, requires that several days of post-maneuver tracking data be processed to converge on an accurate post-maneuver orbit solution. The effects of maneuvers on orbit determination accuracy will be presented, including a comparison of the batch least squares technique to the extended Kalman filter/smoother technique. We will present the maneuver calibration results derived from processing post-maneuver tracking data. A dominant error in the orbit estimation process is the uncertainty in solar radiation pressure and the resultant force on the spacecraft. An estimation of this value can include many related factors, such as the uncertainty in spacecraft reflectivity and surface area which is a function of spacecraft orientation (spin-axis attitude), uncertainty in spacecraft wet mass, and potential seasonal variability due to the changing direction of the Sun line relative to the Earth-Moon Lissajous reference frame. In addition, each spacecraft occasionally enters into Earth or Moon penumbra or umbra and these shadow crossings reduche solar radiation force for several hours. The effects of these events on orbit determination accuracy will be presented. In order to plan for upcoming stationkeeping maneuvers, the maneuver planning team must take the current orbit estimate, propagate it forward to the planned maneuver time, and determine the optimal maneuver to maintain the Lissajous orbit for one or more revolutions. The propagation is performed using a Runge-Kutta 7/8 integrator and typically the position and velocity uncertainty increases with propagation time, increasing the overall uncertainty of the orbit state at the maneuver execution time. The effect of orbit knowledge uncertainty on stationkeeping operations will be presented.

Woodard, Mark↗

NASA NTRS2009

TRW - Lunar Descent Engine

As we went through the program, what we determined, and what we all agreed on, was that the thrust coefficient (Cf) of the nozzle, after you get past a certain point, is really an engineering parameter. It s not a fundamental parameter that is going to be highly variable. Once we knew what the contour of the nozzle was, and once we knew what its characteristic was out to 2:1, we could calculate what the 48:1 thrust coefficient was going to be. In every case that we made a test, the calculation was precise. We weren't looking for a problem out at 48:1. Once we crushed the nozzle and said, "Yeah, we can land on the boulder," and once we had the thermal profile of that columbium nozzle, we did not require a lot of effort there. The real characterization was done in throttling over the 10:1 with the injector and controlling the mixture ratio on that - the whole head-end assembly - out to 2:1. I think everybody at NASA and Grumman agreed that flying like you test is great, particularly if you are using an aircraft engine. But, in this case, the thrust coefficient of the nozzle was not an issue. We had the tandem configuration of the service module, the command module, and the LEM sitting out there, and we were to fire the LEM. On Apollo 5, we were firing the LEM to show how it would work. There was a problem. I can t remember where the problem was, but something caused a problem before that engine had finished its burn. It was not in the engine, but there was some other problem, and NASA made a controlled shutdown. Then, they came to us and asked, "Hey, we re up there. We want to finish this test program. Is it okay if we restart that engine again in space with this tandem configuration?" We said, "As long as it has been more than forty minutes since you shut down, our analysis says that you will be okay in terms of the thermal characteristics of the inside of that chamber." They restarted it and pushed that system around in orbit on Apollo 5. It turned out, that when it came to Apollo 13, we went back into the record, and said, "Hey, we have pushed this system around up there on Apollo 5, and we have also restarted this tandem configuration." The requirements on Apollo 13 were to put it back into play. The spacecraft was out of free return to the earth at the time of the accident. It would not have come back. NASA said, "Okay, we ll use the descent engine to put the spacecraft in a free trajectory; it will go around the moon and be on free trajectory back to Earth." Then, as it came around the far side of the moon, the guys found out that they had an oxygen problem. As you remember, things were getting pretty bad in there. They said, "We ve got to get it back as fast as we can. Is it okay if we re-fire the engine? Now, we re in a free trajectory, so we want to put as much delta-v (or change in velocity) in as we can. Can we re-fire right now?" We said, "Yes, the data says it has been this period of time." We could re-fire the engine, run the rest of the duty cycle up as far as we needed while preserving enough fluids to make the final correction as the spacecraft got near Earth, and restart the engine. It was pretty fortuitous that we could give them those answers.

Elverum, Gerard W.↗

NASA NTRSDate not supplied

Monitoring Airspace Complexity and Determining Contributing Factors

The national airspace has evolved over many years to accommodate increased traffic demand [1] while simultaneously maintaining one of the safest forms of transportation [2], [3]. One of the reasons for this success is the ability of the system and the operators to adapt and accommodate to situations that routinely disrupt optimal operations. These situations may include: adverse weather, delays, early arrivals, equipment outages, and other factors that are outside the operators ability to control. These factors can lead to states where automation is unable to properly handle these issues and therefore air traffic controllers and pilots have to intervene, ultimately increasing communication between operators resulting in higher workload. As controller workload increases to handle sub-optimal operating conditions this can be viewed as an increase in complexity. The reasoning for this is because humans are now required to make tactical decisions in response to external factors, resulting in a departure from the strategic plan where operations would be more efficiently managed. Human operators control airspace complexity under rigid regulations that are constantly changing. The airspace is divided into sectors and the number of aircraft assigned to each controller is limited for safe handling. There has been past work that devised airspace complexity metrics in commercial aviation and related these metrics to controller workload (e.g., [4],[5]). The upper bounds on the system load are pre-determined. Such bounds on complexity make for a safe system, but the system cannot scale and adapt to autonomous, dense, and heterogeneous traffic, including the many types of Unmanned Aerial Vehicles (UAVs) envisioned to be added to the operations. We hypothesize that, as traffic density and heterogeneity grow, and other key metrics change, there will be phase transitions at which the way traffic should be managed changes significantly [6]. We offer a method for in-time detection of contributing factors that lead to phase transitions, characterized by increased complexity. To the best of our knowledge, there is no tool similar to our proposed effort that identifies such contributing factors or precursor patterns. To define the scope we are proposing to measure complexity from the viewpoint of the Terminal Radar Approach Control Facilities (TRACON) controller’s perspective. In particular we are analyzing arrivals into KSFO. With safety as the top concern for airspace operators, it is important to recognize that as density and heterogeneity grow, the focus of the system will change. Times of the day when the airspace has low density and heterogeneity, the flights will follow more efficient paths where the aircraft move on established routes that are more or less directly to the destination. However, when density and heterogeneity increases, the system will begin changing focus to avoiding conflicts and collisions and route the flights in a more flexible way. Higher flexibility requires more communication and coordination between controllers and pilots which the current automation is unable to handle. This paper proposes a novel approach that monitors airspace complexity at multiple scales, uses a Machine Learning-based tool that predicts when operations will transition to a regime of greater complexity, and identifies actions that can reduce the complexity while still maintaining efficient and safe operations. We demonstrate our proposed approach using data from multiple complementary sources. This includes, but is not limited to: historical aircraft surveillance data from NASA’s Sherlock Data Warehouse [7], METAR weather data, and airport configuration data from Aviation System Performance Metrics (ASPM). The surveillance data flight paths are sampled at a variable sample rate — increasing as the aircraft approaches the airport. This is due to how Sherlock manages flight track stitching between different radar facilities which have different sampling rates. The weather and performance data are logged at defined intervals throughout the day at a courser refresh rate. In addition to the logged data and metrics, we leverage pre-defined Standard Terminal Arrival Routes (STARs) procedures to characterize the path of each flight. Each flight files for one of these routes in the flight plan well before entering the terminal airspace, and approximately follows the route until it leaves the STAR, typically on the final fix of a runway transition. However, most flights do not always fly the full STAR procedure to completion [8], but the majority do adhere to the fixes within the common route of the procedure. Our approach leverages fixes in the common route of each of the STARs to build a reference path to the airport. This allows us to characterize the flight paths in what we are defining as the “maneuvering area” (the airspace between the STAR and before the flight is lined up on the runway’s final approach) to determine how off nominal the flights are to calculate its complexity score. Determining airspace complexity is a concept that does not have a concrete answer. In designing this metric, we consider what increases the workload for the air traffic controllers. Consequently more specialized vectoring maneuvers results in higher workload. Accordingly, we start with a theory: each flight has a direct path it takes from the STAR’s common route to the final approach’s outer marker fix for the flight’s landing runway. It is important to note that the direct path is only used as a reference. If the majority of the flights have a large consistent offset as compared to other routes it does not necessarily mean that those flights have higher complexity. We are merely building a distribution based on this direct path for that particular STAR and runway pair to determine the normal mode of operations for that route. Flights that are in the upper tail of these distributions will result in higher complexity scores and flights that fly in the median will represent the normal mode of operations and therefore will have lower complexity scores. Since flights following each STAR route take different paths to the airport, we have a different distribution for each STAR route and therefore can model these distributions to compute a complexity score from their respective normalized distributions. To evaluate the effectiveness of our proposed airspace complexity metric we will compare against an established approach based on trajectory clustering [9]. This unsupervised learning technique consists of the following steps: (1) identify the general maneuvering areas (waypoints) by performing $\kappa$-means or DBSCAN clustering on locations where aircraft frequently turn based on the surveillance radar track data, (2) map flight trajectories onto sequences of waypoints, and (3) cluster the sequences based on their common subsequences. From a high-level perspective, this baseline model learns nominal operations in the airspace through the sequence of waypoints that are representative of where aircraft change direction and defines deviations from the nominal operations as “complex.” Therefore, more deviations from the nominal operations correspond to higher complexity values. For our validation, we re-implemented this technique and tune model hyper-parameters to correctly detect waypoints for the arrival traffic into the San Francisco bay area. We will compute the complexity measure over a one-year period using our proposed technique as well as the baseline. Our validation will be based on each technique’s ability to detect a set of undesirable outcomes (e.g., go-arounds, holding patterns, average time in the airspace, etc.). Since our current complexity metric is derived from the offset from the direct reference path, it’s important to understand what causes these offsets. In many of the flights with high offset distance, flights performing holding patterns and S turns can be observed. These maneuvering tactics are utilized to add distance between the aircraft and the destination runway to prevent multiple flights from having conflicting arrival times. In order to predict a rise in complexity (or the precursor to complexity), it’s necessary to be able to identify these potential conflicts (which in turn, result in higher offsets). To do this, we define a “representative flight” for each STAR route and runway pair. This flight is approximately the path the flight would take if there was a clear path with no other flights in the airspace — including the time remaining to the airport. We first identify the flights for a given STAR runway pair using the offset to the reference path distributions that fall between the 44-55 percentiles. This yields the flights that conform to the most normal mode of operation. Each of these flights is partitioned based on the percent complete from the entry point into the maneuvering areas from 0\% – 100\% complete. Then for each percent “bin”, we take the median value of the flight’s latitude/longitude coordinates, airspeed, and (non causal) time remaining to the airport to construct a lookup table for each percent complete bin on a given route. As a flight enters the maneuvering area, we can find the estimated arrival time of a flight to the airport by finding the closest point to the representative path’s percent complete bin (relative to the flight’s current position at any snapshot in the airspace) and therefore retrieve the corresponding remaining time left on the “representative path”. We assume that the flight will follow the representative path to completion when deriving these estimates. We can then compare these estimated arrival times against other flights for the same snapshot in time to identify potential conflicts. If more flights are estimated to arrive within a tolerance window than there are runways available, then we have a potential conflict. We can use this derived measure along with other factors expected to add disruption to the operation such as weather and runway configuration changes as an input to machine learning tools to detect precursors that increases in our complexity measure. This novel method will assist in uncovering insights into the contributing factors that lead to increased complexity that may allow for in-time responses to avoid reaching a high complexity state in the airspace.

complexity↗

NASA NTRS2007

Large Solar-Rejection Filter

NASA utilized Image Intensified Video Cameras for ATV data acquisition from a jet flying at 12.8 km. Afterwards the video was digitized and then analyzed with a modified commercial software package, Image Systems Trackeye. Astrometric results were limited by saturation, plate scale, and imposed linear plate solution based on field reference stars. Time-dependent fragment angular trajectories, velocities, accelerations, and luminosities were derived in each video segment. It was evident that individual fragments behave differently. Photometric accuracy was insufficient to confidently assess correlations between luminosity and fragment spatial behavior (velocity, deceleration). Use of high resolution digital video cameras in future should remedy this shortcoming. A scenically accurate description of matter interpreted as a substance made up of corpuscular constituents was established during the course of the 19th century. In this description, atoms--the building blocks of the matter--form molecules. The properties of the molecules were described by chemistry or thermodynamics depending on what characteristics of the matter were investigated. In both theories, the molecules can dissociate to atoms when the kinetic energies of the atoms exceed the strength of the chemical bonds. The number of atoms is always preserved in a closed system. This is not true, however, when the matter takes up much higher energies at relativistic scales. New particles can be produced at the expense of the kinetic energy. The number of particles is no longer preserved. There are other conserved quantities, however, these quantities, the charge, baryon number, lepton number, are associated with particles that are considered elementary today. The properties and behavior of these elementary particles is the subject of Particle Physics or High Energy Physics. Practice Page: A crewmember touching a positively charged surface was thought to be galvanically isolated from the vehicle ground analogous to a bird on a high voltage power wire. Recent analysis confirms that positive floating potentials, ionospheric currents to the EVA suit, can be hazardous. The analysis is wrong in that the ionospheric plasma itself can close the circuit. Parametric analysis of very low voltage exposures (2 to 15 volts) could cause pain and/or involuntary muscle tetani or spinal cord shock. NASA worked with the Naval Health Research Center Detachment Directed Energy Bioeffects Laboratory to examine the affects electrical hazards could have on extravehicular activity using two models. The results of the two computational models were combined to predict areas of the body in which neurons of different diameters would be excited. They predicted that physiologically active current could be conducted across the crew member causing catastrophic hazards. Future work to analyze additional current paths was proposed. The FUSE spectrum of BB Dor, observed in a high state, is modeled with an accretion disk with a very low inclination (possibly lower than 10 degrees). Assuming an average WD mass of 0.8 solar mass leads to a distance of the order of approximately 650pc, consistent with the extremely low galactic reddening in its direction, and a mass accretion rate of 10 (exp -9) solar mass a year. The spectrum presents some broad and deep silicon and sulfur absorption lines, indicating that these elements are over-abundant: silicon is 3 times solar, and sulfur is 20 times solar. The FUSE spectrum of BB Dor, observed in a high state, is modeled with an accretion disk with a very low inclination (possibly lower than 10 degrees). Assuming an average WD mass of 0.8 solar mass leads to a distance of the order of approximately 650pc, consistent with the extremely low galactic reddening in its direction, and a mass accretion rate of 10 (exp -9) solar mass a year. The spectrum presents some broad and deep silicon and sulfur absorption lines, indicating that these elements are over-abundant: silicon is times solar, and sulfur is 20 times solar. From its previously observed optical emission lines, P831-57 (WD 0334 6400 or Ret 1 in A Catalog and Atlas of Cataclysmic Variables: Living Edition) has been suspected to contain an accretion disk associated with a companion star in orbit around a subdwarf star with a temperature T is greater than 21,000K. P831-57 has therefore been classified as a nova-like. However, our present observations show it to be a DA + dMe binary. The analysis of its Far Ultraviolet Spectroscopic Explorer (FUSE) spectrum (continuum and lines) reveal an average mass white dwarf (Log(g) approximately equals 7.8 plus or minus 0.1)with a temperature T approximately equals 37,000 plus or minus 500K, an extremely low projected rotational velocity, and a distance of about 115 plus or minus 5pc. The photosphere contains C, N, Si, and S (at about 1% of solar abundances). The dMe star is seen as a flux excess in near-infrared photometry and appears to show occasional flaring of about one magnitude as seen in the Harvard plates. There is no evidence of periodic variability in the spectroscopic or photometric data. We find no evidence of a an accretion disk, instead we find evidence of wind accretion as the stellar carbon abundance (N(C)/N(H) = 2.5 x 10 (exp -6) is about ten times larger than predicted by radiative levitation for such a gravity and temperature. The power needs and solutions for the space exploration and lunar mobility program are discussed. Long term missions in space and on the lunar surface require high energy batteries. Rechargeable batteries for mobility systems and portable utility pallet are needed for successful exploration missions. Nanomaterial usage increases the energy density of the cells apart from increasing the power density. The symptoms and threats from acute mountain sickness (AMS) are discussed. The underlying assumptions concerning spacecraft atmosphere mean there is a potential risk to astronauts. The baseline worst case scenario is about 25% based on direct ascent to 8.0 psia with 32% O2. The practical mitigation approach is a staged depressurization scheme. Due to the uncertainty about potential AMS risk the flight surgeon should prepare, focused research should proceed, and current analytical efforts should continue. This slide presentation reviews the threat astronauts face from acute mountain sickness (AMS). The incidence of AMS is highly variable and the risk to astronauts is unclear. However, the potential risk is higher than current EAAs suggest and precautions should be implemented. Due to the uncertain nature of the risk flight surgeons should prepare, and focused research should proceed. Quasiparticle tunneling can be understood at low temperatures using a non-equilibrium kinetic theory. Low-temperature tunneling can be suppressed using existing techniques: island-lead gap engineering, lead cooling with SIN junctions, and quasiparticle traps. The slide presentation reviews the science goals and mission planning for the proposed Jupiter System Observer (JSO). The spacecraft would accommodate 9 instruments making the instrument payload more capable than any previously flown to Jupiter. The would-be mission includes study programs for Jupiter's satellites, interior, magnetosphere and atmosphere. The power needs and solutions for the space exploration and lunar mobility program are discussed. Long term missions in space and on the lunar surface require high energy batteries. Rechargeable batteries for mobility systems and portable utility pallet are needed for successful exploration missions. Nanomaterial usage increases the energy density of the cells apart from increasing the power density. This slide presentation reviews the power requirements for the space exploration and the lunar surface mobility programs. It includes information about the specifications for high energy batteries and the power requirements for lunar rovers,

Roberts, William↗