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Thermophysical Property Measurements of Molten Semiconductors in 1-g and Reduced-g Condition

Understanding and controlling the formation kinetics of varieties of crystal imperfections such as point defects, non uniform distribution of doping atoms, and impurity atoms in growing crystals are very important. Theoretical (numerical) modeling of the crystal growth process is an essential step to achieving these objectives. In order to obtain reliable modeling results, input parameters, i.e. various thermophysical parameters, must be accurate. The importance of accurate thermophysical properties of semiconductors in crystal growth cannot be overly emphasized. The total hemispherical emissivity, for instance, has a dramatic impact on the thermal environment. It determines the radiative emission from the surface of the melt which determines to a large extent the profile of the solidified crystal. In order to understand the convection and the turbulence in a melt, viscosity becomes an important parameter. The liquid surface tension determines the shape of the liquid-atmosphere interface near the solid-liquid-atmosphere triple point. Currently used values for these parameters are rather inaccurate, and this program intends to provide more reliable measurements of these thermophysical properties. Thus, the objective of this program is in the accurate measurements of various thermophysical properties which can be reliably used in the modeling of various crystal growth processes. In this program, thermophysical properties of molten semiconductors, such as Si, Ge, Si-Ge, and InSb will be measured as a function of temperature using the High Temperature Electrostatic Levitator at JPL. Each material will be doped by different kinds of impurities at various doping levels. Thermophysical properties which will be measured include: density, thermal expansion coefficient, surface tension, viscosity, specific heat, hemispherical total emissivity, and perhaps electrical and thermal conductivities. Many molten semiconductors are chemically reactive with crucibles. As a result, these dispersed impurities in the melts tend to substantially modify the properties of pure semiconductors. Sample levitation done in a vacuum clearly helps maintain the sample purity. However, in the 1-g environment, all gravity caused effects such as convection, sedimentation and buoyancy are still present in the sample. In addition, large forces needed to levitate a sample in the presence of the gravity can cause additional flows in the melt. The use of the High Temperature Electrostatic Levitator (HTESL) for the present research is a recent development and little is known about the flows induced by the electrostatic forces. In this ground base program, we will define the limits of HTESL technology as various thermophysical properties of molten semiconductors are measured.

Rhim, Won-Kyu↗

Thermodynamic Modeling of a Solid Oxide Fuel Cell to Couple with an Existing Gas Turbine Engine Model

The Controls and Dynamics Technology Branch at NASA Glenn Research Center are interested in combining a solid oxide fuel cell (SOFC) to operate in conjunction with a gas turbine engine. A detailed engine model currently exists in the Matlab/Simulink environment. The idea is to incorporate a SOFC model within the turbine engine simulation and observe the hybrid system's performance. The fuel cell will be heated to its appropriate operating condition by the engine s combustor. Once the fuel cell is operating at its steady-state temperature, the gas burner will back down slowly until the engine is fully operating on the hot gases exhausted from the SOFC. The SOFC code is based on a steady-state model developed by The U.S. Department of Energy (DOE). In its current form, the DOE SOFC model exists in Microsoft Excel and uses Visual Basics to create an I-V (current-voltage) profile. For the project's application, the main issue with this model is that the gas path flow and fuel flow temperatures are used as input parameters instead of outputs. The objective is to create a SOFC model based on the DOE model that inputs the fuel cells flow rates and outputs temperature of the flow streams; therefore, creating a temperature profile as a function of fuel flow rate. This will be done by applying the First Law of Thermodynamics for a flow system to the fuel cell. Validation of this model will be done in two procedures. First, for a given flow rate the exit stream temperature will be calculated and compared to DOE SOFC temperature as a point comparison. Next, an I-V curve and temperature curve will be generated where the I-V curve will be compared with the DOE SOFC I-V curve. Matching I-V curves will suggest validation of the temperature curve because voltage is a function of temperature. Once the temperature profile is created and validated, the model will then be placed into the turbine engine simulation for system analysis.

Brinson, Thomas E.↗

Printing Outside the Box: Additive Manufacturing Processes for Fabrication of Large Aerospace Structures

To achieve NASA's mission of space exploration, innovative manufacturing processes are being applied to the fabrication of propulsion elements. Liquid rocket engines (LREs) are comprised of a thrust chamber and nozzle extension as illustrated in figure 1 for the J2X upper stage engine. Development of the J2X engine, designed for the Ares I launch vehicle, is currently being incorporated on the Space Launch System. A nozzle extension is attached to the combustion chamber to obtain the expansion ratio needed to increase specific impulse. If the nozzle extension could be printed as one piece using free-form additive manufacturing (AM) processes, rather than the current method of forming welded parts, a considerable time savings could be realized. Not only would this provide a more homogenous microstructure than a welded structure, but could also greatly shorten the overall fabrication time. The main objective of this study is to fabricate test specimens using a pulsed arc source and solid wire as shown in figure 2. The mechanical properties of these specimens will be compared with those fabricated using the powder bed, selective laser melting technology at NASA Marshall Space Flight Center. As printed components become larger, maintaining a constant temperature during the build process becomes critical. This predictive capability will require modeling of the moving heat source as illustrated in figure 3. Predictive understanding of the heat profile will allow a constant temperature to be maintained as a function of height from substrate while printing complex shapes. In addition, to avoid slumping, this will also allow better control of the microstructural development and hence the properties. Figure 4 shows a preliminary comparison of the mechanical properties obtained.

Babai, Majid↗

Steps Towards the Integration of Conflict Resolution with Metering and Scheduling

NASA Ames Research Center is developing decision support tool technology for air traffic controllers to improve the efficiency and capacity of National Airspace System. The goal is to provide technology, tools and procedures that result in the highest possible level of user preferred trajectories whenever possible with safe and efficient traffic management when necessary. The work is being conducted under the NASA Advanced Air Transportation Technology Program in cooperation with the FAA through the Inter-Agency Integrated Product Team. The objective is to develop technology and procedures that lead towards a seamless integration of conflict resolution with metering and scheduling for arrival aircraft and en route aircraft that are under metering restrictions. A requirement is that the integration incorporate user preferred trajectories. The ultimate goal is the implementation and validation of the Descent Advisor (DA) concept which provides clearance advisories to a sector controller that simultaneously meet metering constraints, are conflict free, incorporate a user preferred (e.g., minimum fuel) descent profile, and generally require no further corrective clearance as the aircraft transitions from en route cruise into the TRACON. The DA concept may also be applied to en route aircraft under metering constraints, e.g., miles-in-trail. To achieve the DA concept a stepwise development and field evaluation is anticipated. This paper addresses the initial steps towards implementation of the DA. The Traffic Management Advisor (TMA) computes arrival time sequence and required delay information for display to the sector controller during periods when arrivals must be metered due to landing rate restrictions at the airport. The Initial Conflict Probe (ICP) compares trajectory predictions for all aircraft and alerts the controller when any two aircraft are predicted to violate separation standards (5 mi. and 2000 ft. in en route airspace). ICP also includes a trial planning function allowing the controller to develop and check a separate "what if" trajectory for conflict resolution. TMA and ICP currently operate independent of one another and have separate controller displays. The TMA meter list is on the radar controller's plan view display. The ICP is still under development, but the current concept calls for a list of predicted conflicts at the data controller position. The research described herein address two steps towards the implementation of DA. The first is to develop a concept for integrated display of conflict and metering information on a controller's display. The objective is to provide the controller with situational awareness of one problem while he develops a solution to the other. The next step is to expand the concept for display of automated clearance advisories for one problem (e.g., metering) which take into account the other problems (e.g., conflicts). Information to be communicated between TMA and ICP to facilitate' manual or automated advisories is being identified as the concept matures. In order to study the ICP/TMA integration concept the CTAS conflict probe capability has been adapted to Ft. Worth Center. The system is being validated in the laboratory with all-track data and for non -interference with TMA, TMA is already running as a daily use prototype at Ft. Worth Center. A laboratory prototype system has been developed under the CTAS baseline which combines conflict and metering information on a common user interface. Elements of the user interface are shown in Figure 1. In this simple illustration the user sees the simultaneous effect of a trial plan on meter fix delay and conflict status. Delay information is shown in the aircraft flight data block, the meter list, and the TMA timeline. Experience during Descent Advisor development and observations at Ft. Worth Center high and low attitude arrival sectors during metering suggests that manual trial planning will be unworkable during rush periods due to high controller workload.

McNally, B. David↗

A Machine Learning Approach to Improve Air Traffic Management Initiatives

Collaborating closely with commercial air carriers and related organizations, the Federal Aviation Administration(FAA) regulates air traffic and ensures the safety and efficiency of air operations. Air traffic controllers make strategic decisions, such as delaying, rerouting, or canceling flights, partly based on guidance provided by the FAA’s Air TrafficControl System Command Center (ATCSCC). The guidance includes, among other things, control measures known asTraffic Management Initiatives (TMIs) designed to enhance safety and improve operational efficiency. TMIs play a crucial role in managing the demand and capacity within the U.S. National Airspace System (NAS). Two major TMIs that are routinely used (primarily to mitigate the adverse effects of bad weather) are Ground Delay Programs (GDPs) andGround Stops (GSs). In a GDP, flights destined for airports facing thunderstorm activity experience delays at their origin airports. This proactive approach minimizes the risk of routing aircraft through hazardous weather conditions and also replaces (fuel burning) airborne delays with ground delays. In a GS, a temporary restriction is imposed on the departure or arrival of aircraft at a specific airport or within a designated airspace. Although other TMIs (e.g., miles-in-trail) are also implemented as part of (air) traffic flow management in the NAS, the focus of this work is on GDPs and GSs. Since TMIs, by design, lead to flight delays or cancellations, it is crucial to put in place the right set of parameters(e.g., scope and duration of the GDP). For example, when the end time of a GDP extends beyond what is necessary, it imposes unnecessary delays on departing flights. This situation could occur as a result of inaccurate prediction of the(required) duration of the GDP based on the weather forecast. On the other hand, if a GDP ends prematurely before the underlying capacity constraints are resolved at the destination airport, it may result in airborne holding. The delicate balance lies in matching the termination of the GDP precisely with the resolution of capacity constraints, avoiding both the imposition of unnecessary ground delays and the need for airborne holding due to premature program termination.Failing to specify the right parameters for TMIs also leads to flight delays, creating a significant obstacle in managing the increasing traffic volumes causing increased work load for the controllers. To address this issue, we propose the integration of Machine Learning (ML) models in the traffic flow management(TFM) pipeline. In current operations, decisions are made by human experts based on extensive training, historical patterns, available traffic and weather data. Since we have an abundance of data from past events that tell us the likely impact of various TMIs, by ingesting historical data, properly trained ML models can offer valuable insights and aid human decision-making. With the FAA increasingly exploring advanced analytics, ML emerges as a focal point for enhancing TFM within the National Airspace System (NAS). As a first step, this study aims to provide traffic controllers with decision-making support for the issuance and adjustment of TMIs. Data analytics and machine learning have been previously employed to address some of the challenges associated with TMIs. Numerous studies have concentrated on various facets of TMI issuance, exploring factors influencing TMI parameters, including arrival rate, airport capacity, and delay prediction. For example, using weather forecasts, several statistical methods were used to produce probabilistic capacity profiles which in conjunction with deterministic models provided insights into the GDP planning process [1–4]. The downside of using deterministic models is that they rely on fixed inputs and predetermined rules, which lack the ability to account for the inherent uncertainty and variability present in real-world scenarios. In a separate series of studies, researchers aimed to predict the occurrences of GDPs and GSs. The majority of these studies utilized various supervised learning methods, including Decision Trees, Naive Bayes, Support VectorMachines, and Random Forests to analyze the influence of weather conditions and arrival demand on TMI incidents[5–8]. However, these studies primarily focused on predicting the incidence of TMIs without explicitly addressing the scope of TMIs, including their duration and their geographical coverage. Furthermore, the emphasis of these studies was largely on GDPs, given their higher frequency and longer duration when compared to GSs. A limited number of studies focused on predicting the parameters of TMIs, specifically addressing their duration and extent. In one such study focusing on optimizing the TMI parameters at San Francisco International Airport (SFO),the authors utilized a probabilistic forecast of fog [9]. They simulated various capacity scenarios based on the (fog)burn-off forecasts, selecting GDP parameters that minimized airborne and overall ground delays. However, this approach exclusively emphasizes stratus (fog) burn-off as the primary determinant of GDP and GS, neglecting other influential factors like severe weather events, runway closures, lower capacity than traffic demand, and other important variables. Given the complexity of predicting the TMI and determining its scope, we seek a more holistic approach. We aim to consider all significant factors that could impact TMIs and their parameters. What sets this research apart is the fusion of all data sources relevant to the issuance and adjustment of TMIs and it represents the first comprehensive attempt to optimize TMIs in this manner. Since this comprehensive solution involves various aspects, we break down the problem into smaller components and input all parameters into a unified model called the “TMI Adjuster”. Figure 1 shows the overall framework and the list of datasets used in each model. The objective of the TMI Adjuster module is to deliver reliable, consistent and expedited recommendations for the progression, adjustment, and termination of TMIs. The ML solution entails developing a pipeline capable of predicting the necessity of a TMI (e.g., GS or GDP) along with its various parameters. For example, in the case of a GS, this includes the scope of the GS either in terms of distance from the destination airport or based on pre-defined airspace sectors. Here, scope refers to those regions and departing airports that are subject to the GS. In this paper, we concentrate on the issuance of GSs in the three major airports in the New York area — LaGuardia(LGA), John F. Kennedy International (JFK), and Newark Liberty International (EWR). We fuse traffic, weather and other relevant aviation data from years 2017 to 2019 to train and validate the ML models. In particular, we use the following datasets: •Terminal Aerodrome Forecast (TAF): meteorological forecasts specific to each airport, issued four times a day, covering predefined time periods. •TMI data: includes all GSs and GDPs along with their respective parameters. •Aviation System Performance Metrics (ASPM): includes traffic related data such as aircraft delays, arrival, and departure rates. •Notices to Airmen (NOTAMs): utilized to extract runway closure data and manage interdependencies between terminals in close proximity. •Flight cancellation data •Airspace Flow Programs (AFP): includes information on flight airborne holdings caused by TMIs. The data preprocessing entails transforming ASPM, TMI, AFP, NOTAMs, and weather data into an hourly format and consolidating all datasets by merging them based on date and time as the primary key. The TMI Adjuster framework comprises two parallel models: one dedicated to GS and a second model focused on GDP. As previously mentioned, our specific focus is on the GS model as a multi-classification problem. In this framework, each data point of the GS model input summarizes ten hours of data. Specifically, the data loader for the GS model generates the input and output of the model as follows: at a given time step, the input includes the actual traffic, weather, and TMI data from the two-hour window before the time step, alongside the weather forecast and scheduled traffic for the next 8 hours starting from the time step. Based on this information, the output of the GS model for each time interval consists of three dimensions. The first dimension represents a binary decision on whether there should be a GS in place for the next hour or not. The second dimension is related to the scope of the GS in the United States, and the third dimension is related to the scope of the GS in Canada (i.e., to determine if the GS impacts airports in Canada).One of the challenges with TMI modeling is the sparsity of TMI events, particularly regarding its scope. To address this challenge in the scope of the GS model output, we implement grouping. The GS scope for the US region is defined based on a list of centers that should be included when the GS is in place. With 20 centers in the US, we utilized historical data to group them into 4 categories. In particular, we summarized our historical data in a graph format where nodes represent centers, and link weights are defined based on the co-occurrence of centers in the scope parameter ofTMIs. By identified strongly connected components in this graph, we were able to partition the centers into four groups. We consider two model structures for the GS Model. Firstly, a hierarchical classification model [10], where the human decision-making for a GS is of hierarchical nature. The decision-maker first decides whether there is a need fora GS, and if the answer is yes, determines the scope. A hierarchical classification model organizes the problem into a class hierarchy, typically a tree or a Directed Acyclic Graph (DAG) structure, and considers the dependency of the decision in the previous step to the next component [10]. Here, we employ the local classifier per level approach, which involves training one multi-class classifier for each level of the class hierarchy. The second structure is the independent structure. In this setting, as the name suggests, we do not consider the dependency of the decisions in the different dimensions of the output of the model. Instead, for each dimension, we train a multi-class classifier independently. Table 1 summarizes GS model statistics for training, validation and testing. The table documents the effect of limiting data to the time steps when there was actually a TMI in place or when a TMI had just terminated. This resulted in a more balanced distribution of the GS class(GS positive class)versus “No GS”(GS negative class), which might help the training process. While JFK and LGA follow very similar distributions, with 40% and 42% GS positive class respectively, EWR has proportionally fewer GS incidents at 28%. Our subsequent phase involves evaluating the performance of both hierarchical structure and independent structure using different state-of-the-art multi-class classifier models such as Random Forest, Decision Trees, K-nearest Neighbors, and Logistic Regression and forecast the duration and scope of the GSs.

Farzan Masrour Shalmani↗

Optical Sensors for Monitoring Gamma and Neutron Radiation

For safety and efficiency, nuclear reactors must be carefully monitored to provide feedback that enables the fission rate to be held at a constant target level via adjustments in the position of neutron-absorbing rods and moderating coolant flow rates. For automated reactor control, the monitoring system should provide calibrated analog or digital output. The sensors must survive and produce reliable output with minimal drift for at least one to two years, for replacement only during refueling. Small sensor size is preferred to enable more sensors to be placed in the core for more detailed characterization of the local fission rate and fuel consumption, since local deviations from the norm tend to amplify themselves. Currently, reactors are monitored by local power range meters (LPRMs) based on the neutron flux or gamma thermometers based on the gamma flux. LPRMs tend to be bulky, while gamma thermometers are subject to unwanted drift. Both electronic reactor sensors are plagued by electrical noise induced by ionizing radiation near the reactor core. A fiber optic sensor system was developed that is capable of tracking thermal neutron fluence and gamma flux in order to monitor nuclear reactor fission rates. The system provides near-real-time feedback from small- profile probes that are not sensitive to electromagnetic noise. The key novel feature is the practical design of fiber optic radiation sensors. The use of an actinoid element to monitor neutron flux in fiber optic EFPI (extrinsic Fabry-Perot interferometric) sensors is a new use of material. The materials and structure used in the sensor construction can be adjusted to result in a sensor that is sensitive to just thermal, gamma, or neutron stimulus, or any combination of the three. The tested design showed low sensitivity to thermal and gamma stimuli and high sensitivity to neutrons, with a fast response time.

Boyd, Clark D.↗

Experimental Evaluation of Verification and Validation Tools on Martian Rover Software

To achieve its science objectives in deep space exploration, NASA has a need for science platform vehicles to autonomously make control decisions in a time frame that excludes intervention from Earth-based controllers. Round-trip light-time is one significant factor motivating autonomy capability, another factor is the need to reduce ground support operations cost. An unsolved problem potentially impeding the adoption of autonomy capability is the verification and validation of such software systems, which exhibit far more behaviors (and hence distinct execution paths in the software) than is typical in current deepspace platforms. Hence the need for a study to benchmark advanced Verification and Validation (V&V) tools on representative autonomy software. The objective of the study was to access the maturity of different technologies, to provide data indicative of potential synergies between them, and to identify gaps in the technologies with respect to the challenge of autonomy V&V. The study consisted of two parts: first, a set of relatively independent case studies of different tools on the same autonomy code, second a carefully controlled experiment with human participants on a subset of these technologies. This paper describes the second part of the study. Overall, nearly four hundred hours of data on human use of three different advanced V&V tools were accumulated, with a control group that used conventional testing methods. The experiment simulated four independent V&V teams debugging three successive versions of an executive controller for a Martian Rover. Defects were carefully seeded into the three versions based on a profile of defects from CVS logs that occurred in the actual development of the executive controller. The rest of the document is structured a s follows. In section 2 and 3, we respectively describe the tools used in the study and the rover software that was analyzed. In section 4 the methodology for the experiment is described; this includes the code preparation, seeding of defects, participant training and experimental setup. Next we give a qualitative overview of how the experiment went from the point of view of each technology; model checking (section 5), static analysis (section 6), runtime analysis (section 7) and testing (section 8). The find section gives some preliminary quantitative results on how the tools compared.

Brat, Guillaume↗

A Comparison Between Orion Automated and Space Shuttle Rendezvous Techniques

The Orion spacecraft will replace the space shuttle and will be the first human spacecraft since the Apollo program to leave low earth orbit. This vehicle will serve as the cornerstone of a complete space transportation system with a myriad of mission requirements necessitating rendezvous to multiple vehicles in earth orbit, around the moon and eventually beyond . These goals will require a complex and robust vehicle that is, significantly different from both the space shuttle and the command module of the Apollo program. Historically, orbit operations have been accomplished with heavy reliance on ground support and manual crew reconfiguration and monitoring. One major difference with Orion is that automation will be incorporated as a key element of the man-vehicle system. The automated system will consist of software devoted to transitioning between events based on a master timeline. This effectively adds a layer of high level sequencing that moves control of the vehicle from one phase to the next. This type of automated control is not entirely new to spacecraft since the shuttle uses a version of this during ascent and entry operations. During shuttle orbit operations however many of the software modes and hardware switches must be manually configured through the use of printed procedures and instructions voiced from the ground. The goal of the automation scheme on Orion is to extend high level automation to all flight phases. The move towards automation represents a large shift from current space shuttle operations, and so these new systems will be adopted gradually via various safeguards. These include features such as authority-to-proceed, manual down modes, and functional inhibits. This paper describes the contrast between the manual and ground approach of the space shuttle and the proposed automation of the Orion vehicle. I will introduce typical orbit operations that are common to all rendezvous missions and go on to describe the current Orion automation architecture and contrast it with shuttle rendezvous techniques and circumstances. The shuttle rendezvous profile is timed to take approximately 3 days from orbit insertion to docking at the International Space Station (ISS). This process can be divided into 3 phases: far-field, mid-field and proximity operations. The far-field stage is characterized as the most quiescent phase. The spacecraft is usually too far to navigate using relative sensors and uses the Inertial Measurement Units (IMU s) to numerically solve for its position. The maneuvers are infrequent, roughly twice per day, and are larger than other burns in the profile. The shuttle uses this opportunity to take extensive ground based radar updates and keep high fidelity orbit states on the ground. This state is then periodically uplinked to the shuttle computers. The targeting solutions for burn maneuvers are also computed on the ground and uplinked. During the burn the crew is responsible for setting the shuttle attitude and configuring the propulsion system for ignition. Again this entire process is manually driven by both crew and ground activity. The only automatic processes that occur are associated with the real-time execution of the burn. The Orion automated functionality will seek to relieve the workload of both the crew and ground during this phase

Ruiz, Jose O,↗

Behavior of Ullage Bubbles During Blowdown in Low-g Experiment (BUBBLE): Overview of a Cryogenic Tank Depressurization Test

Behavior of Ullage Bubbles during Blowdown in Low-g Experiment (BUBBLE) is a cryogenic tank depressurization drop tower experiment currently being designed at NASA Glenn Research Center. There is a need for liquid level rise data while venting a cryogenic propellant tank below the liquid saturation pressure in a reduced gravity environment. When a cryogenic tank is vented to a vapor pressure below the liquid saturation pressure, bubbles become entrained in the liquid causing the bulk liquid-vapor interface to rise. In reduced gravity, bubble rise velocity is diminished leading to a larger liquid level rise compared to a 1g environment. The purpose of the experiment is to gain further understanding of tank depressurization fluid physics and obtain high-fidelity data for model validation in 1g and reduced gravity environments. On-orbit cryogenic propellant tanks operating at high fill levels must efficiently manage venting operations to avoid the risk of liquid entrainment in the vent line, which could lead to asymmetric control thruster loads, freezing and clogging, and loss of liquid propellant. Validated models could be used to design settling and venting profiles to reduce risk and increase efficiency for cryogenic storage and transfer operations.

tank venting↗

Countermeasures for Mitigation of Sensorimotor Decrements Following Head-Down Bed Rest

BACKGROUND Astronauts experience postflight disturbances in postural and locomotor control due to sensorimotor adaptations during spaceflight. These alterations may have adverse consequences if a rapid egress is required after landing. Although exercise is partially effective for mitigating cardiovascular and muscular deconditioning, additional countermeasures are needed to further preserve sensorimotor function for exploration missions. We have identified proprioceptive training and electrical muscle stimulation (EMS) as promising in-flight countermeasures. Since prolonged head down bed rest (HDBR) is a spaceflight analog for body unloading and causes postural and locomotor control decrements that parallel those observed after spaceflight, it can be used to accelerate the development of these countermeasures. METHODS This study will determine the effects of proprioceptive training and EMS on functional task performance and sensorimotor function following 60 days of 6° HDBR. Subjects will be randomly assigned to one of four groups: 1) an EMS arm, 2) a proprioceptive training arm, 3) an exercise plus proprioceptive training arm, and 4) a control arm. The EMS countermeasure will include daily bilateral stimulation of the quadriceps femoris muscle (30 minutes per session). Proprioceptive training will be performed three days per week (20 minutes per session) consisting of body-loaded postural tasks in the horizontal position on an air bearing sled. Exercise training will mimic current protocols used on the International Space Station, but treadmill aerobic exercise will be replaced with additional cycling aerobic exercise. Primary outcome measures will include pre and post HDBR functional tests that are representative of high priority exploration mission tasks and require high demand for dynamic control of postural stability. Additional measures will be used to identify the key physiological factors contributing to countermeasure benefits. Given the constrained samples size, a Bayesian modelling approach will be used to quantify the probability that there is an effect of a given magnitude. COUNTERMEASURE UPDATES Proprioceptive countermeasure design enhancements and human in the loop pilot testing continued through the Crew Health Countermeasures (CHC) Systems Capability Leadership Team (SCLT). The primary goals of this work were to enhance the visual feedback system’s capabilities and develop a proprioceptive training program for 60 days of HDBR. Six healthy non-astronaut volunteers participated in four pilot training sessions to systematically examine how each training variable (e.g., axial load, foot placement, and software profile) affects the overall proprioceptive challenge. The resulting training program will maintain an appropriate challenge during 60 days of HDBR by progressively decreasing the subject’s base of support, increasing tilt board target distances, and increasing axial loads using both subjective verbal feedback and objective performance data. RELEVANCE The deliverable from this project will be proof-of-concept sensorimotor countermeasure designs for functional task performance with full assessment of efficacy in a spaceflight analog. If the countermeasures are effective, they will be translated for validation with the suite of operationally implemented in-flight countermeasures.

T R Macaulay↗

Resolution of the buoyancy in the 8-foot high temperature tunnel combustor

Currently, the 8-Foot High Temperature Tunnel (8-Ft. HTT) combustor produces a good profile at only one point (2000 psia and 3650 R with oxygen enrichment). Air is enriched with oxygen (liquid) so that the combustor product gas will contain the volumetric amount of oxygen normally found in air. The oxygen enriched air has a large fraction that is not reacted and flows through the outer periphery of the fuel injector. This ring of cold air in addition to the relatively cold walls of the combustor set up buoyancy forces that produce a segregation of relatively cool gases at the bottom of the combustor exit. The basic problem is to produce a test gas that has uniform properties at all combustor conditions. The combustor temperature may be as high as 3700 R or as low as 2000 R. Combustor pressures can be as high as 3500 psia (no oxygen enrichment) and as low as 600 psia. The segregation is most severe with oxygen enriched air, since its temperature is lower and its density is high. The combustor is lined with nickel 201 and can be operated at about 1600 R maximum. A global mixing process is desired that produces an acceptable profile of temperature, species, and velocity at the exit of the combustor. The ultimate goal is a temperature profile with about 100 R variance and about 2 percent variance in oxygen. The exit total temperature must not be lowered significantly by the mixing apparatus or mechanisms employed. If immersed bodies are used, they must also be kept very hot. All combustor wall modifications must be able to survive the heat and structural conditions of the varied operating conditions. Our approach to resolving this issue is being conducted in three stages: (1) Consider mixing exclusively, (2) Resolve the heat transfer concerns resulting from the chosen mixing strategy, and (3) Solve the material and structural problems resulting from stages (1) and (2). Since the 8-Ft. HTT is unavailable for experimentation, the study is conducted exclusively with computational fluid dynamic (CPD) codes (Fluent/Uns and Rampant 3.1) using unstructured grid through body fitted coordinates. Both CFD codes are general purpose Navier-Stokes solution packages that can solve integral conservation equations for conservation of mass, momentum and energy. The governing equations are discretized using a control-volume finite-element method on unstructured triangular 2-D grids. In the interest of time, a 3-D tetrahedral grid was used to check the 2-D results on one mixing strategy and the 2-D results were confirmed. Preliminary results indicate that excellent mixing can be achieved with a body placed in the center of the flowing hot fluid with a minor modification to the combustor wall similar to a model positioned in the test section of a wind tunnel. The concept here, is to create longitudinal vortices strong enough to bring both fluids into intimate contact with each other near the wall where the cold fluid resides. However, there may be a trade-off in the choice of mixing strategy, heat transfer and structural requirements. Currently, we are examining the more promising geometries for heat transfer concerns and developing strategies for the material of construction of the center body.

Loney, Norman W.↗

The SPoRT-WRF: Evaluating the Impact of NASA Datasets on Convective Forecasts

The Short-term Prediction Research and Transition Center (SPoRT) is a collaborative partnership between NASA and operational forecasting entities, including a number of National Weather Service offices. SPoRT transitions real-time NASA products and capabilities to its partners to address specific operational forecast challenges. One challenge that forecasters face is applying convection-allowing numerical models to predict mesoscale convective weather. In order to address this specific forecast challenge, SPoRT produces real-time mesoscale model forecasts using the Weather Research and Forecasting (WRF) model that includes unique NASA products and capabilities. Currently, the SPoRT configuration of the WRF model (SPoRT-WRF) incorporates the 4-km Land Information System (LIS) land surface data, 1-km SPoRT sea surface temperature analysis and 1-km Moderate resolution Imaging Spectroradiometer (MODIS) greenness vegetation fraction (GVF) analysis, and retrieved thermodynamic profiles from the Atmospheric Infrared Sounder (AIRS). The LIS, SST, and GVF data are all integrated into the SPoRT-WRF through adjustments to the initial and boundary conditions, and the AIRS data are assimilated into a 9-hour SPoRT WRF forecast each day at 0900 UTC. This study dissects the overall impact of the NASA datasets and the individual surface and atmospheric component datasets on daily mesoscale forecasts. A case study covering the super tornado outbreak across the Ce ntral and Southeastern United States during 25-27 April 2011 is examined. Three different forecasts are analyzed including the SPoRT-WRF (NASA surface and atmospheric data), the SPoRT WRF without AIRS (NASA surface data only), and the operational National Severe Storms Laboratory (NSSL) WRF (control with no NASA data). The forecasts are compared qualitatively by examining simulated versus observed radar reflectivity. Differences between the simulated reflectivity are further investigated using convective parameters along with model soundings to determine the impacts of the various NASA datasets. Additionally, quantitative evaluation of select meteorological parameters is performed using the Meteorological Evaluation Tools model verification package to compare forecasts to in situ surface and upper air observations.

Zavodsky, Bradley↗

Comparative plasma tails of Venus and comets

A review of current models of solar wind flow in the plasma tails of weakly magnetized bodies is presented. Measurements conducted by the Mariner 5 spacecraft, the Veneras 9 and 10, and the PVO orbiters, in the Venus tail, and with the ICE spacecraft in the tail of Comet Giacobini-Zinner, reveal common plasma properties which suggest that similar physical processes are operative. Most notable is the observation of decreased flow velocities and enhanced plasma temperatures in the vicinity of their plasma tails. In Venus, the measured velocity and temperature fields are consistent with the effects of frictional forces between the mass-loaded ionosheath flow and the ionosphere along the (magnetic) polar regions of the ionopause. It is argued that similar conditions exist at a cometary ionopause and that the distribution of magnetic fluxes in a cometary tail is controlled by the entry of plasma fluxes from the (magnetic) polar regions of the comet's ionospheric obstacle. This question is further addressed in connection with the two-step shape of the magnetic profile measured across the tail of the comet. It is suggested that the low intensity outer increases of the magnetic lobes are associated with the draping of the interplanetary magnetic field lines around the comet's ionospheric obstacle, and that the higher intensity increases seen in the inner regions of the magnetic lobes are due to an additional compression of magnetic fluxes produced by the entry of plasma particles into the tail.

Perezdetejada, H.↗

An Analytical Solution for Yaw Maneuver Optimization on the International Space Station and Other Orbiting Space Vehicles

This paper suggests a new method for optimizing yaw maneuvers on the International Space Station (ISS). Yaw rotations are the most common large maneuvers on the ISS often used for docking and undocking operations, as well as for other activities. When maneuver optimization is used, large maneuvers, which were performed on thrusters, could be performed either using control moment gyroscopes (CMG), or with significantly reduced thruster firings. Maneuver optimization helps to save expensive propellant and reduce structural loads ‐ an important factor for the ISS service life. In addition, optimized maneuvers reduce contamination of the critical elements of the vehicle structure, such as solar arrays. This paper presents an analytical solution for optimizing yaw attitude maneuvers. Equations describing pitch and roll motion needed to counteract the major torques during a yaw maneuver are obtained. A yaw rate profile is proposed. Also the paper describes the physical basis of the suggested optimization approach. In the obtained optimized case, the torques are significantly reduced. This torque reduction was compared to the existing optimization method which utilizes the computational solution. It was shown that the attitude profiles and the torque reduction have a good match for these two methods of optimization. The simulations using the ISS flight software showed similar propellant consumption for both methods. The analytical solution proposed in this paper has major benefits with respect to computational approach. In contrast to the current computational solution, which only can be calculated on the ground, the analytical solution does not require extensive computational resources, and can be implemented in the onboard software, thus, making the maneuver execution automatic. The automatic maneuver significantly simplifies the operations and, if necessary, allows to perform a maneuver without communication with the ground. It also reduces the probability of command errors. The suggested analytical solution provides a new method of maneuver optimization which is less complicated, automatic and more universal. A maneuver optimization approach, presented in this paper, can be used not only for the ISS, but for other orbiting space vehicles.

Dobrinskaya, Tatiana↗

Evaluating Alerting and Guidance Performance of a UAS Detect-And-Avoid System

A key challenge to the routine, safe operation of unmanned aircraft systems (UAS) is the development of detect-and-avoid (DAA) systems to aid the UAS pilot in remaining "well clear" of nearby aircraft. The goal of this study is to investigate the effect of alerting criteria and pilot response delay on the safety and performance of UAS DAA systems in the context of routine civil UAS operations in the National Airspace System (NAS). A NAS-wide fast-time simulation study was conducted to assess UAS DAA system performance with a large number of encounters and a broad set of DAA alerting and guidance system parameters. Three attributes of the DAA system were controlled as independent variables in the study to conduct trade-off analyses: UAS trajectory prediction method (dead-reckoning vs. intent-based), alerting time threshold (related to predicted time to LoWC), and alerting distance threshold (related to predicted Horizontal Miss Distance, or HMD). A set of metrics, such as the percentage of true positive, false positive, and missed alerts, based on signal detection theory and analysis methods utilizing the Receiver Operating Characteristic (ROC) curves were proposed to evaluate the safety and performance of DAA alerting and guidance systems and aid development of DAA system performance standards. The effect of pilot response delay on the performance of DAA systems was evaluated using a DAA alerting and guidance model and a pilot model developed to support this study. A total of 18 fast-time simulations were conducted with nine different DAA alerting threshold settings and two different trajectory prediction methods, using recorded radar traffic from current Visual Flight Rules (VFR) operations, and supplemented with DAA-equipped UAS traffic based on mission profiles modeling future UAS operations. Results indicate DAA alerting distance threshold has a greater effect on DAA system performance than DAA alerting time threshold or ownship trajectory prediction method. Further analysis on the alert lead time (time in advance of predicted loss of well clear at which a DAA alert is first issued) indicated a strong positive correlation between alert lead time and DAA system performance (i.e. the ability of the UAS pilot to maneuver the unmanned aircraft to remain well clear). While bigger distance thresholds had beneficial effects on alert lead time and missed alert rate, it also generated a higher rate of false alerts. In the design and development of DAA alerting and guidance systems, therefore, the positive and negative effects of false alerts and missed alerts should be carefully considered to achieve acceptable alerting system performance by balancing false and missed alerts. The results and methodology presented in this study are expected to help stakeholders, policymakers and standards committees define the appropriate setting of DAA system parameter thresholds for UAS that ensure safety while minimizing operational impacts to the NAS and equipage requirements for its users before DAA operational performance standards can be finalized.

UAS Detect-and-Avoid (DAA) System↗

A Low Cost Spacecraft Architecture for Robotic Lunar Exploration Projects

A program of frequent, capable, but affordable lunar robotic missions prior to return of humans to the moon can contribute to the Vision for Space Exploration (VSE) NASA is tasked to execute. The Lunar Reconnaissance Orbiter (LRO) and its secondary payload are scheduled to orbit the moon, and impact it, respectively, in 2008. It is expected that the sequence of missions occurring for approximately the decade after 2008 will place an increasing emphasis on soft landed payloads. These missions are requited to explore intrinsic characteristics of the moon, such as hydrogen distribution in the regolith, and levitated dust, to demonstrate the ability to access and process in-situ resources, and to demonstrate functions critical to supporting human presence, such as automated precision navigation and landing. Additional factors governing the design of spacecraft to accomplish this diverse set of objectives are: operating within a relatively modest funding profile, the need tb visit multiple sites (both polar and equatorial) repeatedly, and to use the current generation of launch vehicles. In the US, this implies use of the Evolved Expendable Launch Vehicles, or EELVs, although this design philosophy may be extended to launch vehicles of other nations, as well. Many of these factors are seemingly inconsistent with each other. For example, the cost of a spacecraft usually increases with mass; therefore the desire to fly frequent, modestly priced spacecraft seems to imply small spacecraft (< 1 Mt, injected mass). On the other hand, the smallest of the EELVs will inject approx. 3 Mt. on a Trans Lunar Injection (TLI) trajectory md would therefore be wasteful or launching a single, small spacecraft. Increasing the technical capability of a spacecraft (such as autonomous navigation and soft landing) also usually increases cost. A strategy for spacecraft design that meets these conflicting requirements is presented. Taken together, spacecraft structure and propulsion subsystems constitute the majority of spacecraft mass; saving development and integration cost on these elements is critical to controlling cost. Therefore, a low cost, modular design for spacecraft structure and propulsion subsystems is presented which may be easily scaled up or down for either insertion into lunar orbit or braking for landing on the lunar surface. In order to effectively use the approx.3 Mt mass-to-TLI of the EELV, two low cost spacecraft will be manifested on the same launch. One spacecraft will be located on top of the other for launch and the two will have to be released in sequence in order to achieve all mission objectives. The two spacecraft could both be landers, both orbiters, or one lander and one orbiter. In order to achieve mass efficiency, the body of the spacecraft will serve the dual purposes of carrying launch loads and providing attachment points for all the spacecraft subsystems. In order to avoid unaffordable technology development costs, small liquid propulsion components and autonomous, scene-matching navigation cameras may be adapted from military missile programs in order to execute precision soft landings.

Lemke, Lawrence G.↗

Coilgun Acceleration Model Containing Multiple Interacting Coils

A coilgun operates by pulsing current through an axially-arranged series of independently-controlled coils inductively interacting with a small, electrically-conductive, azimuthally-symmetric projectile to accelerate it to high velocities. The electrical circuits are programmed to pulse current through the coils in such a way so as to impart further electromagnetic acceleration in each stage. A method is developed to calculate the mutual inductance between the coils and between each coil and the projectile. These terms are used to write a system of first-order ordinary differential equations governing the projectile velocity and the current flow in each coil. While the inclusion of the electromagnetic interactions between coils significantly complicates the equation set as more coil sets are included in the problem, casting the problem symbolically in mass matrix form permits solution using standard numerical Runge-Kutta techniques. Comparing a projectile with a single-turn to that comprised of nine-turns, the inductance of the former is much smaller, but this leads to a greater induced projectile current. The lower inductance and greater current appear to offset each other with little difference in the acceleration profile for the two cases. For the limited cases studied, coils with a discharge half-cycle equal to the time for a projectile to transit from one coil to the next yield increased efficiency.

Polzin, Kurt A.↗

Measurement of Atmospheric Composition from Geostationary Platforms

Satellite instruments flown since 1970 have had great success in elucidating the processes that control stratospheric ozone. In contrast, space-based data for tropospheric constituents that affect air quality and climate have only recently become available. While these datasets highlight the rapidly advancing capabilities of spacebased tropospheric sensors, they are also pointing to the limitations of sun-synchronous, low-earth orbiting (SSO/LEO) satellite platforms for making such measurements. In our talk we will highlight the science requirements for new missions and the technological and algorithmic approaches that we are developing to meet these requirements. From these studies a clear need for advanced atmospheric composition sensors has emerged that can be put on geostationary (GEO) platforms to provide 5 km horizontal resolution with 15-60 minutes repeat cycle. Such measurements have been high priority in the recently released Decadal Survey report by the US National Research Council. The need for GEO is driven not only by the science requirements to track rapidly changing pollution events but also by the need to provide altitude-resolved information about tropospheric constituents. Currently, with the exception of aerosols, it is not possible to derive profile information about lower tropospheric constituents from satellite measurements. New algorithmic approaches are being developed to obtain this information by combining UV and IR data, by monitoring the spatial and temporal structures of the constituents, and by using low-level clouds to separate boundary layer constituents from free troposphere. All these approaches require better spatial and temporal resolution than that provided by LEO sensors.

Bhartia, P. K.↗