Results for “control framework” — Page 60

NASA NTRS2016

Analysis of the Ability of United States and Russian Trace Contaminant Control Systems to Meet U.S. 180-Day and Russian 360-Day Spacecraft Maximum Allowable Concentrations

As the Space Station Freedom program transitioned to become the International Space Station (ISS), uncertainty existed concerning the performance capabilities for U.S.- and Russian-provided trace contaminant control (TCC) equipment. In preparation for the first dialogue between NASA and Russian Space Agency personnel in Moscow, Russia, in late April 1994, an engineering analysis was conducted to serve as a basis for discussing TCC equipment engineering assumptions as well as relevant assumptions on equipment offgassing and cabin air quality standards. The analysis presented was conducted as part of the efforts to integrate Russia into the ISS program via the early ISS Multilateral Medical Operations Panel's Air Quality Subgroup deliberations. This analysis, served as a basis for technical deliberations that established a framework for TCC system design and operations among the ISS program's international partners that has been instrumental in successfully managing the ISS common cabin environment.

Perry, J. L.↗

NASA NTRS1999

The evolution of Crew Resource Management training in commercial aviation

In this study, we describe changes in the nature of Crew Resource Management (CRM) training in commercial aviation, including its shift from cockpit to crew resource management. Validation of the impact of CRM is discussed. Limitations of CRM, including lack of cross-cultural generality are considered. An overarching framework that stresses error management to increase acceptance of CRM concepts is presented. The error management approach defines behavioral strategies taught in CRM as error countermeasures that are employed to avoid error, to trap errors committed, and to mitigate the consequences of error.

Non-NASA Center↗

NASA NTRSDate not supplied

Softening the Gap between Wöhler and Paris – New Approaches for Fatigue Analysis –

Fatigue analysis tools can vary across industries. For example, automotive engineers often use the Wöhler (S-N) approach to design for safe-life, while aerospace engineers prioritize damage tolerance and inspection intervals, relying instead on crack growth models such as Paris’ law. Although both approaches may deal with the control of cracks in similar materials, their analysis tools and material characterizations are fundamentally distinct. This divide mirrors the classic split between stress-based strength analysis and linear elastic fracture mechanics. However, modern nonlinear models that incorporate material softening, such as cohesive laws, blur this boundary and capture fracture behaviors across scales. This presentation describes the CF23 fatigue model, which uses cohesive softening to link S-N crack initiation with crack propagation rates. CF23 spans the full fatigue spectrum, from initial propagation transients to steady-state growth and threshold conditions, offering a unified framework that bridges Wöhler and Paris-based methodologies. Example applications include fatigue crack propagation transients in adhesive interfaces and skin/stiffener separation.

cohesive elements↗

NASA NTRS1991

Communications and control for electric power systems

The first section of the report describes the AbNET system, a hardware and software communications system designed for distribution automation (it can also find application in substation monitoring and control). The topology of the power system fixes the topology of the communications network, which can therefore be expected to include a larger number of branch points, tap points, and interconnections. These features make this communications network unlike any other. The network operating software has to solve the problem of communicating to all the nodes of a very complex network in as reliable a way as possible even if the network is damaged, and it has to do so with minimum transmission delays and at minimum cost. The design of the operating protocols is described within the framework of the seven-layer Open System Interconnection hierarchy of the International Standards Organization. Section 2 of the report describes the development and testing of a high voltage sensor based on an electro-optic polymer. The theory of operation is reviewed. Bulk fabrication of the polymer is discussed, as well as results of testing of the electro-optic coefficient of the material. Fabrication of a complete prototype sensor suitable for use in the range 1-20 kV is described. The electro-optic polymer is shown to be an important material for fiber optic sensing applications. Appendix A is theoretical support for this work. The third section of the report presents the application of an artificial neural network, Kohonen's self-organizing feature map, for the classification of power system states. This classifier maps vectors of an N-dimensional space to a 2-dimensional neural net in a nonlinear way preserving the topological order of the input vectors. These mappings are studied using a nonlinear power system model.

Kirkham, H.↗

NASA NTRSDate not supplied

Assimilation of SMAP Observations Over Land Improves the Simulation and Prediction of Tropical Cyclone Idai

This work is focused on the role of soil moisture in the prediction of tropical cyclones (TCs) approaching land and after landfall. Soil moisture conditions can impact the circulation and structure of an existing tropical cyclone (TC) when part or all of the circulation is over land. For example, dry land surface conditions may lead to faster dissipation of a TC over land (often associated with changes in precipitation structure), whereas very wet conditions may help sustain or in rare cases re-intensify a TC. Moreover, the presence of strong soil moisture gradients may affect the symmetry and development of the TC circulation leading to changes in its over-land track. While the link between soil moisture conditions and TC evolution in proximity to land is relatively well understood in theory, applications of these findings in the context of numerical weather prediction (NWP) have been limited. Here we present a case study that explores the potential of improving TC predictions through an improved soil moisture initialization in an NWP framework. Specifically, we examine the impact of assimilating observations from the NASA Soil Moisture Active Passive (SMAP) mission into the NASA Goddard Earth Observing System (GEOS) global weather model on the prediction of South-West Indian Ocean TC Idai (2019). SMAP provides accurate L-band (1.4 GHz) brightness temperatures (Tb) observations that are sensitive to soil moisture globally and at high revisit times of 2-3 days. It has previously been shown that the assimilation of SMAP Tb observations significantly improves modeled land surface states. Thus, it is expected that SMAP can be used to constrain land surface initial conditions and potentially benefit TC forecasts. Here we present two sets of retrospective forecasts of TC Idai that are compared in an Observing System Experiment framework at ¼ degree resolution: (i) forecasts initialized from an analysis that is comparable to the GEOS operational analysis (without SMAP Tb assimilation) and (ii) forecasts initialized from an analysis that additionally assimilates SMAP brightness temperature observations over land using a weakly-coupled land analysis. We find that the assimilation of SMAP meaningfully improves the representation of TC Idai’s structure as well as the prediction of its intensity and track. The analyzed TC size, as measured by the wind speed radius, is improved by up to 18% in the analysis with SMAP assimilation relative to the control run. The forecast intensity error, measured against the observed intensity, is reduced by up to 23%. At the 1/4-degree resolution used here, GEOS unavoidably under-estimates TC intensity and over-estimates TC size. The SMAP assimilation therefore corrects the model in the right direction, leading to a storm that is more energetic and more compact. Furthermore, we find that the along-track forecast error is reduced by up to 34%, indicating a more accurate propagation speed, which is consistent with the fact that TC speed over land is strongly affected by surface processes. The impact of SMAP assimilation on the forecast cross-track error is neutral. Across the TC forecast skill metrics used here, the improvements from SMAP DA are largest at lead times of 36 to 72 hours, suggesting that the predictability of forecasts at shorter lead times may be dominated by short-term convective processes, while the land and its longer memory gains in importance as a source of predictability on a 2-3 day timescale. We further investigated the underlying mechanisms leading to the skill improvements from SMAP data assimilation by isolating the land areas that directly influence TC Idai using a back trajectory analysis. We find that the assimilation of SMAP leads to wetter soil moisture conditions that cause an increased latent heat flux, which ultimately results in TC analyzed representation that has higher column-integrated total moisture content and total energy compared to the analysis in the control run without SMAP assimilation. Overall, the results highlight that the assimilation of SMAP observations into a global numerical weather prediction model can lead to pronounced improvements of TC predictions. This is a crucial step towards a better mitigation of the socio-economic impact of landfalling TCs and thus safeguarding human lives. Finally, our study presents an event-based approach that assesses the impact of land data assimilation for a particular weather event rather than by globally averaging differences in skill. We argue that global skill assessments – while necessary – can mute the impact of land data assimilation, because the land’s influence on the atmosphere is constrained to certain locations and certain times. Instead, the event-based approach better highlights the true potential of land data assimilation in the context of NWP, especially for extreme events when accurate predictions are critical.

Jana Kolassa↗

NASA NTRSDate not supplied

Assimilation of SMAP Observations Over Land Improves the Simulation and Prediction of Tropical Cyclone Idai

This work is focused on the role of soil moisture in the prediction of tropical cyclones (TCs) approaching land and after landfall. Soil moisture conditions can impact the circulation and structure of an existing tropical cyclone (TC) when part or all of the circulation is over land. For example, dry land surface conditions may lead to faster dissipation of a TC over land (often associated with changes in precipitation structure), whereas very wet conditions may help sustain or in rare cases re-intensify a TC. Moreover, the presence of strong soil moisture gradients may affect the symmetry and development of the TC circulation leading to changes in its over-land track. While the link between soil moisture conditions and TC evolution in proximity to land is relatively well understood in theory, applications of these findings in the context of numerical weather prediction (NWP) have been limited. Here we present a case study that explores the potential of improving TC predictions through an improved soil moisture initialization in an NWP framework. Specifically, we examine the impact of assimilating observations from the NASA Soil Moisture Active Passive (SMAP) mission into the NASA Goddard Earth Observing System (GEOS) global weather model on the prediction of South-West Indian Ocean TC Idai (2019). SMAP provides accurate L-band (1.4 GHz) brightness temperatures (Tb) observations that are sensitive to soil moisture globally and at high revisit times of 2-3 days. It has previously been shown that the assimilation of SMAP Tb observations significantly improves modeled land surface states. Thus, it is expected that SMAP can be used to constrain land surface initial conditions and potentially benefit TC forecasts. Here we present two sets of retrospective forecasts of TC Idai that are compared in an Observing System Experiment framework at ¼ degree resolution: (i) forecasts initialized from an analysis that is comparable to the GEOS operational analysis (without SMAP Tb assimilation) and (ii) forecasts initialized from an analysis that additionally assimilates SMAP brightness temperature observations over land using a weakly-coupled land analysis. We find that the assimilation of SMAP meaningfully improves the representation of TC Idai’s structure as well as the prediction of its intensity and track. The analyzed TC size, as measured by the wind speed radius, is improved by up to 18% in the analysis with SMAP assimilation relative to the control run. The forecast intensity error, measured against the observed intensity, is reduced by up to 23%. At the 1/4-degree resolution used here, GEOS unavoidably under-estimates TC intensity and over-estimates TC size. The SMAP assimilation therefore corrects the model in the right direction, leading to a storm that is more energetic and more compact. Furthermore, we find that the along-track forecast error is reduced by up to 34%, indicating a more accurate propagation speed, which is consistent with the fact that TC speed over land is strongly affected by surface processes. The impact of SMAP assimilation on the forecast cross-track error is neutral. Across the TC forecast skill metrics used here, the improvements from SMAP DA are largest at lead times of 36 to 72 hours, suggesting that the predictability of forecasts at shorter lead times may be dominated by short-term convective processes, while the land and its longer memory gains in importance as a source of predictability on a 2-3 day timescale. We further investigated the underlying mechanisms leading to the skill improvements from SMAP data assimilation by isolating the land areas that directly influence TC Idai using a back trajectory analysis. We find that the assimilation of SMAP leads to wetter soil moisture conditions that cause an increased latent heat flux, which ultimately results in TC analyzed representation that has higher column-integrated total moisture content and total energy compared to the analysis in the control run without SMAP assimilation. Overall, the results highlight that the assimilation of SMAP observations into a global numerical weather prediction model can lead to pronounced improvements of TC predictions. This is a crucial step towards a better mitigation of the socio-economic impact of landfalling TCs and thus safeguarding human lives. Finally, our study presents an event-based approach that assesses the impact of land data assimilation for a particular weather event rather than by globally averaging differences in skill. We argue that global skill assessments – while necessary – can mute the impact of land data assimilation, because the land’s influence on the atmosphere is constrained to certain locations and certain times. Instead, the event-based approach better highlights the true potential of land data assimilation in the context of NWP, especially for extreme events when accurate predictions are critical.

Jana Kolassa↗

NASA NTRS1999

Bubble Generation in a Flowing Liquid Medium and Resulting Two-Phase Flow in Microgravity

The present investigation reports a study of bubble generation under reduced gravity conditions, using both a co-flow and a cross-flow configuration. This study may be used in the conceptual design of a space-based thermal management system. Ensuing two-phase flow void fraction can be accurately monitored using a single nozzle gas injection system within a continuous liquid flow conduit, as utilized in the present investigation. Accurate monitoring of void fraction leads to precise control of heat and mass transfer coefficients related to a thermal management system; hence providing an efficient and highly effective means of removing heat aboard spacecraft or space stations. Our experiments are performed in parabolic flight aboard the modified DC-9 Reduced Gravity Research Aircraft at NASA Lewis Research Center, using an air-water system. For the purpose of bubble dispersion in a flowing liquid, we use both a co-flow and a cross-flow configuration. In the co-flow geometry, air is introduced through a nozzle in the same direction with the liquid flow. On the other hand, in the cross-flow configuration, air is injected perpendicular to the direction of water flow, via a nozzle protruding inside the two-phase flow conduit. Three different flow conduit (pipe) diameters are used, namely, 1.27 cm, 1.9 cm and 2.54 cm. Two different ratios of nozzle to pipe diameter (D(sub N))sup * are considered, namely (D(sub N))sup * = 0.1 and 0.2, while superficial liquid velocities are varied from 8 to 70 cm/s depending on flow conduit diameter. It is experimentally observed that by holding all other flow conditions and geometry constant, generated bubbles decrease in size with increase in superficial liquid velocity. Detached bubble diameter is shown to increase with air injection nozzle diameter. Likewise, generated bubbles grow in size with increasing pipe diameter. Along the same lines, it is shown that bubble frequency of formation increases and hence the time to detachment of a forming bubble decreases, as the superficial liquid velocity is in-creased. Furthermore, it is shown that the void fraction of the resulting two-phase flow increases with volumetric gas flow rate Q(sub d), pipe diameter and gas injection nozzle diameter, while they decrease with surrounding liquid flow. The important role played by flowing liquid in detaching bubbles in a reduced gravity environment is thus emphasized. We observe that the void fraction can be accurately controlled by using single nozzle gas injection, rather than by employing multiple port injection, since the later system gives rise to unpredictable coalescence of adjacent bubbles. It is of interest to note that empirical bubble size and corresponding void fraction are somewhat smaller for the co-flow geometry than the cross-flow configuration at similar flow conditions with similar pipe and nozzle diameters. In order to supplement the empirical data, a theoretical model is employed to study single bubble generation in the dynamic (Q(sub d) = 1 - 1000 cu cm/s) and bubbly flow regime within the framework of the co-flow configuration. This theoretical model is based on an overall force balance acting on the bubble during the two stages of generation, namely the expansion and the detachment stage. Two sets of forces, one aiding and the other inhibiting bubble detachment are identified. Under conditions of reduced gravity, gas momentum flux enhances, while the surface tension force at the air injection nozzle tip inhibits bubble detachment. In parallel, liquid drag and inertia can act as both attaching and detaching forces, depending on the relative velocity of the bubble with respect to the surrounding liquid. Predictions of the theoretical model compare well with our experimental results. However, at higher superficial liquid velocities, as the bubble loses its spherical form, empirical bubble size no longer matches the theoretical predictions. In summary, we have developed a combined experimental and theoretical work, which describes the complex process of bubble generation and resulting two-phase flow in a microgravity environment. Results of the present study can be used in a wide range of space-based applications, such as thermal energy and power generation, propulsion, cryogenic storage and long duration life support systems, necessary for programs such as NASA's Human Exploration for the Development of Space (HEDS).

Pais, S. C.↗

NASA NTRS2004

Exploring New Pathways in Precipitation Assimilation

Precipitation assimilation poses a special challenge in that the forward model for rain in a global forecast system is based on parameterized physics, which can have large systematic errors that must be rectified to use precipitation data effectively within a standard statistical analysis framework. We examine some key issues in precipitation assimilation and describe several exploratory studies in assimilating rainfall and latent heating information in NASA's global data assimilation systems using the forecast model as a weak constraint. We present results from two research activities. The first is the assimilation of surface rainfall data using a time-continuous variational assimilation based on a column model of the full moist physics. The second is the assimilation of convective and stratiform latent heating retrievals from microwave sensors using a variational technique with physical parameters in the moist physics schemes as a control variable. We will show the impact of assimilating these data on analyses and forecasts. Among the lessons learned are (1) that the time-continuous application of moisture/temperature tendency corrections to mitigate model deficiencies offers an effective strategy for assimilating precipitation information, and (2) that the model prognostic variables must be allowed to directly respond to an improved rain and latent heating field within an analysis cycle to reap the full benefit of assimilating precipitation information. of microwave radiances versus retrieval information in raining areas, and initial efforts in developing ensemble techniques such as Kalman filter/smoother for precipitation assimilation. Looking to the future, we discuss new research directions including the assimilation

Hou, Arthur↗

NASA NTRS1993

Spacecraft materials: Comparison between flight results obtained on LDEF and MIR

Two flight experiments dedicated to the study of the performance of materials in space have been carried out. Material samples have been exposed passively to low-Earth orbit (LEO) environment, then retrieved for laboratory study. The first experiment was conducted in the framework of the FRECOPA project and was flown on the trailing edge of the Long Duration Exposure Facility (LDEF) (exposure to vacuum and ultraviolet (UV) radiation for 5.5 years). The experiment COMES was installed outside of the MIR space station during an extravehicular activity; it was exposed to vacuum, O-atoms, and UV radiation for 1.1 year; and it was brought back to Earth by cosmonauts. The difference in exposure conditions and the use of transparent filters protecting some samples of COMES enable to differentiate the effects of UV radiation and oxygen atoms. The degradations of several thermal control coatings (paints, metalized polymeric films with and without ITO), structural materials, and optical components have been observed, measured, and compared after these two flight experiments. This paper summarizes various 'lessons learned' that can be used to identify aspects of space aging, to orient future research in this field, and to assist in spacecraft design.

Guillaumon, Jean-Claude↗

NASA NTRS2024

System Engineering & Integration (SE&I) In-Situ Resource Utilization (ISRU) Modeling and Analysis (SIMA)

NASA developed a flexible system modeling framework of integrated ISRU and ISRU related subsystem models: MAIT (Mission Analysis & Integration Tool) that enables point solutions, optimization, and/or parametric studies at the system level to predict mission architecture mass, power, and volume and provides accessible consolidated database that categorizes specific ISRU and ISRU related subsystem variables common between NASA & industry. Directly and indirectly addresses multiple STMD shortfalls: - ISRU-581 - ‘ISRU System Modeling’: Establish a modular end-to-end ISRU system modeling & analysis capability by leveraging and evolving prior, on-going, and future investments - More than an ISRU system modeling tool, MAIT integrates power, excavation, Environmental Control & Life Support System (ECLSS), Cryogenic Fluid Management (CFM) liquification, & compares surface ops & environments, to assist in the closure of other related ISRU shortfalls Adheres to governing NASA procedures for Models & Simulations (NASA-HDBK-7009) & AIAA standards for Mass Properties Control for Space Systems.

Modeling↗

NASA NTRS2001

The CE/SE Method: a CFD Framework for the Challenges of the New Millennium

The space-time conservation element and solution element (CE/SE) method, which was originated and is continuously being developed at NASA Glenn Research Center, is a high-resolution, genuinely multidimensional and unstructured-mesh compatible numerical method for solving conservation laws. Since its inception in 1991, the CE/SE method has been used to obtain highly accurate numerical solutions for 1D, 2D and 3D flow problems involving shocks, contact discontinuities, acoustic waves, vortices, shock/acoustic waves/vortices interactions, shock/boundary layers interactions and chemical reactions. Without the aid of preconditioning or other special techniques, it has been applied to both steady and unsteady flows with speeds ranging from Mach number = 0.00288 to 10. In addition, the method has unique features that allow for (i) the use of very simple non-reflecting boundary conditions, and (ii) a unified wall boundary treatment for viscous and inviscid flows. The CE/SE method was developed with the conviction that, with a solid foundation in physics, a robust, coherent and accurate numerical framework can be built without involving overly complex mathematics. As a result, the method was constructed using a set of design principles that facilitate simplicity, robustness and accuracy. The most important among them are: (i) enforcing both local and global flux conservation in space and time, with flux evaluation at an interface being an integral part of the solution procedure and requiring no interpolation or extrapolation; (ii) unifying space and time and treating them as a single entity; and (iii) requiring that a numerical scheme be built from a nondissipative core scheme such that the numerical dissipation can be effectively controlled and, as a result, will not overwhelm the physical dissipation. Part I of the workshop will be devoted to a discussion of these principles along with a description of how the ID, 2D and 3D CE/SE schemes are constructed. In Part II, various applications of the CE/SE method, particularly those involving chemical reactions and acoustics, will be presented. The workshop will be concluded with a sketch of the future research directions.

Chang, Sin-Chung↗

NASA NTRS2026

Benchmarking Bayesian Optimization Frameworks and Acquisition Strategies for Materials Discovery and Autonomous Laboratories

Bayesian optimization (BO) can accelerate materials discovery by guiding expensive experiments toward the most promising processing conditions. We systematically compare five BO surrogate and framework combinations (Gaussian processes in Ax, Gaussian processes and Monte-Carlo neural networks in BayBE, random forests in Lolopy, and tree-structured Parzen (TPE) estimators in Hyperopt) on three benchmarks that mimic common materials design tasks (a discrete solid-electrolyte composition space, a hybrid discrete/continuous laminate-composite design problem solved with micromechanics modeling, and the continuous Ishigami analytic function which is a standard optimization benchmark). Each BO surrogate is paired with posterior mean, probability of improvement, and expected improvement acquisition functions and run for 100 trials from randomized initial samples with uniform random search providing a control. Across five random seeds per setting, BayBE’s Gaussian-process surrogate with expected improvement consistently reached ≥95 % of the known optimum in the fewest evaluations, while Lolopy’s random forest matched or exceeded GP performance on purely categorical or mixed spaces at a higher computational cost. Posterior mean alone often stagnated at local optima, underscoring the need for exploration, whereas probability and expected improvement balanced exploration and exploitation leading to better optimization in fewer trials. Execution times ranged from milliseconds for TPE to minutes for neural-network and random-forest surrogates. These results establish baseline expectations for BO in automated materials laboratories and highlight expected improvement with Gaussian processes as a reliable first choice, with random forests offering a strong alternative when categorical variables dominate. The benchmark suite and code are released to facilitate future surrogate, acquisition, and constraint-handling research in data-driven materials optimization.

Bayesian optimization↗

NASA NTRS2008

Proven and Robust Ground Support Systems - GSFC Success and Lessons Learned

Over the past fifteen years, Goddard Space Flight Center has developed several successful science missions in-house: the Wilkinson Microwave Anisotropy Probe (WMAP), the Imager for Magnetopause-to-Aurora Global Exploration (IMAGE), the Earth Observing 1 (EO-1) [1], and the Space Technology 5 (ST-5)[2] missions, several Small Explorers, and several balloon missions. Currently in development are the Solar Dynamics Observatory (SDO) [3] and the Lunar Reconnaissance Orbiter (LRO)[4]. What is not well known is that these missions have been supported during spacecraft and/or instrument integration and test, flight software development, and mission operations by two in house satellite Telemetry and Command (T & C) Systems, the Integrated Test and Operations System (ITOS) and the Advanced Spacecraft Integration and System Test (ASIST). The advantages of an in-house satellite Telemetry and Command system are primarily in the flexibility of management and maintenance - the developers are considered a part of the mission team, get involved early in the development process of the spacecraft and mission operations-control center, and provide on-site, on-call support that goes beyond Help Desk and simple software fixes. On the other hand, care must be taken to ensure that the system remains generic enough for cost effective re-use from one mission to the next. The software is designed such that many features are user-configurable. Where user-configurable options were impractical, features were designed so as to be easy for the development team to modify. Adding support for a new ground message header, for example, is a one-day effort because of the software framework on which that code rests. This paper will discuss the many features of the Goddard satellite Telemetry and Command systems that have contributed to the success of the missions listed above. These features include flexible user interfaces, distributed parallel commanding and telemetry decommutation, a procedure language, the interfaces and tools needed for a high degree of automation, and instantly accessible archives of spacecraft telemetry. It will discuss some of the problems overcome during development, including secure commanding over networks or the Internet, constellation support for the three satellites that comprise the ST-5 mission, and geographically distributed telemetry end users.

Pfarr, Barbara↗

NASA NTRS2021

Predicting Arrival and Departure Runway Assignments with Machine Learning

Runway assignments at major airports are made by air traffic controllers subject to various constraints, and to achieve various objectives. In this research, we describe our efforts training machine learning (ML) models to predict both departure and arrival runway assignments using an entirely data-driven approach. This approach is compared to existing rule-based approaches developed in previous research using input from Subject Matter Experts. The models have features derived from various FAA data feeds, and leverage multiple machine learning algorithms. Results for models trained for nine major U.S. airports are described and compared to one another across various important dimensions. Particular attention was paid to developing a repeatable framework for training these models so the approach could be scaled to other airports, and to developing models that are useful in a real-time environment. In addition, the models were designed to be functional in a real-time environment to support NASA’s ATD-2 project, as part of an ML-powered shadow system to compare against the performance of the fielded system.

machine learning↗

NASA NTRS2021

Predicting Arrival and Departure Runway Assignments with Machine Learning

Runway assignments at major airports are made by air traffic controllers subject to various constraints, and to achieve various objectives. In this research, we describe our efforts training machine learning (ML) models to predict both departure and arrival runway assignments using an entirely data-driven approach. This approach is compared to existing rule-based approaches developed in previous research using input from Subject Matter Experts. The models have features derived from various FAA data feeds, and leverage multiple machine learning algorithms. Results for models trained for nine major U.S. airports are described and compared to one another across various important dimensions. Particular attention was paid to developing a repeatable framework for training these models so the approach could be scaled to other airports, and to developing models that are useful in a real-time environment. In addition, the models were designed to be functional in a real-time environment to support NASA’s ATD-2 project, as part of an ML-powered shadow system to compare against the performance of the fielded system.

machine learning↗

NASA NTRS1999

Co-evolution for Problem Simplification

This paper explores a co-evolutionary approach applicable to difficult problems with limited failure/success performance feedback. Like familiar "predator-prey" frameworks this algorithm evolves two populations of individuals - the solutions (predators) and the problems (prey). The approach extends previous work by rewarding only the problems that match their difficulty to the level of solut,ion competence. In complex problem domains with limited feedback, this "tractability constraint" helps provide an adaptive fitness gradient that, effectively differentiates the candidate solutions. The algorithm generates selective pressure toward the evolution of increasingly competent solutions by rewarding solution generality and uniqueness and problem tractability and difficulty. Relative (inverse-fitness) and absolute (static objective function) approaches to evaluating problem difficulty are explored and discussed. On a simple control task, this co-evolutionary algorithm was found to have significant advantages over a genetic algorithm with either a static fitness function or a fitness function that changes on a hand-tuned schedule.

Haith, Gary L.↗

NASA NTRSDate not supplied

Optimal Sensor Mobility Design for Target Tracking with Distributed Sensing, Communication and Computing Infrastructure

The paper presents an airborne target tracking approach with data fusion from distributed stationary and mobile sensor network transmitted through a wireless/wired communication network and using a distributed computing infrastructure. To obtain high quality measurements, sensor flight platforms' positions and orientations are optimized with respect to the available target's position and velocity estimates, and a formation control strategy is applied to derive desired trajectories for the flight platforms. As sensors move, the communication network topology switching is determined using the worst-case approach to handle uncertainties in the target's and sensors' positions, which alters communication delays for sensors' data transmission to computing centers. An optimal data migration algorithm is periodically applied to determine these communication delays for each sensor and the optimal location with minimum end-to-end latency for the target tracking algorithm execution, which is based on adaptive information fusion from multi-modal mobile and stationary sensors inside an Extended Kalman Filter framework. The approach is validated in a desktop simulation environment using synthetic sensor data generated for a simulated target's flight.

Distributed sensing↗

NASA NTRS1997

Research in Satellite-Fiber Network Interoperability

This four part report evaluated the performance of high data rate transmission links using the ACTS satellite, and to provide a preparatory test framework for two of the space science applications that have been approved for tests and demonstrations as part of the overall ACTS program. The test plan will provide guidance and information necessary to find the optimal values of the transmission parameters and then apply these parameters to specific applications. The first part will focus on the satellite-to-earth link. The second part is a set of tests to study the performance of ATM on the ACTS channel. The third and fourth parts of the test plan will cover the space science applications, Global Climate Modeling and Keck Telescope Acquisition Modeling and Control.

Edelson, Burt↗