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Design Guidelines for Swirl-Venturi Fuel-Air Mixers for Lean Direct Injection Combustors

Design guidelines for aircraft gas turbine combustors are provided based on the swirl-venturi lean direction injection (SVLDI) scheme. The guidelines are developed through a combination of literature review and internal research at NASA GRC that sought to develop an understanding of how LDI geometry affects NOx emissions, minimum stable f/a, and combustion dynamics. Key objectives are to improve low power operability by reducing the fuel/air ratio achievable with the SV-LDI concept and to reduce NOx emissions for both the subsonic landing-takeoff cycle and supersonic cruise conditions. The design of any combustion system will be a set of compromises between flame stability and decreasing combustion emissions. This document is to serve as a guide for selecting the best options given the overall mission. This document is organized as follows. In section 1, we introduce and describe the SV-LDI concept as a way to reduce NOx emissions. Section 2 provides descriptions of the individual components that make up a single swirl-venturi LDI element — the venturi, swirler, and fuel injector and their primary purposes. Considerable focus is applied to how changes on the air side components affect the flow field. Section 3 examines variations within a single SV-LDI element swirler: blade thickness, presence of a diffuser section, position of fuel nozzle, et cetera. We include examples from the literature to emphasize key aspects of these changes. In Section 4 we consider the interaction of a single element with the combustion chamber and with neighboring elements. In Section 5, we look at fuel staging effects on emissions, combustion efficiency, and combustion dynamics. Throughout these sections, we will highlight any findings we consider universal, and in Section 6 we consolidate those findings to provide guidelines for use in SV-LDI designs.

gas turbine combustion↗

Multi-agent planning and scheduling, execution monitoring and incremental rescheduling: Application to motorway traffic

This article describes a planning method applicable to agents with great perception and decision-making capabilities and the ability to communicate with other agents. Each agent has a task to fulfill allowing for the actions of other agents in its vicinity. Certain simultaneous actions may cause conflicts because they require the same resource. The agent plans each of its actions and simultaneously transmits these to its neighbors. In a similar way, it receives plans from the other agents and must take account of these plans. The planning method allows us to build a distributed scheduling system. Here, these agents are robot vehicles on a highway communicating by radio. In this environment, conflicts between agents concern the allocation of space in time and are connected with the inertia of the vehicles. Each vehicle made a temporal, spatial, and situated reasoning in order to drive without collision. The flexibility and reactivity of the method presented here allows the agent to generate its plan based on assumptions concerning the other agents and then check these assumptions progressively as plans are received from the other agents. A multi-agent execution monitoring of these plans can be done, using data generated during planning and the multi-agent decision-making algorithm described here. A selective backtrack allows us to perform incremental rescheduling.

Mourou, Pascal↗

Space Product Development of Commercial NLO Materials

Growth on selected substrates under various processing conditions have been useful for preparing highly oriented and otherwise promising films of organic compounds for optical thin films and waveguides. The significance of processing conditions to uniformity in thickness, degree of orientation, film quality, and optical properties for a specific processing technique is the general focus of work in this area. A study on the effect of processing conditions relevant to thin-film deposition by various techniques is particularly difficult because of the possibility that convection may play a major role in some cases. It is a goal of some researchers to produce good quality anisotropic films, therefore, an important, yet understudied, requirement should be to assess the role of gravity during certain processing methods. This may be particularly true for the vapor deposition of diacetylenes where subsequent polymerization in the crystal is topochemical and occurs readily only when neighboring monomer molecules are sufficiently close and suitably oriented. Likewise, this requirement is equally viable for the vapor deposition of certain materials such as Pcs in view of the results of microgravity experiments by 3M Corporation involving the preparation of thin films of copper Pc (CuPc). Microgravity-grown CuPc had several desirable features which indicate that the vapor growth of organic films in low-g may result in better quality films for optical and electrical applications. Indeed, other materials vapor deposited onto specific substrates in microgravity produce films potentially beneficial for electro-optic applications. A novel technique, recently discovered, for growing polydiacetylene thin films involves exposing a transparent substrate, in contact with diacetylene monomer solution, to ultraviolet (LTV) light. A polymer film deposits on the side of the substrate in contact with monomer in solution, and there are distinct gravitational effects, which influence film quality. Good quality thin films elude growth from solutions absent of uniform flow fields and homogeneous temperature distributions near the substrate surfaces. The flow fields and temperature distributions during the polymerization process by exposure to UV light details the nature of gravitational influences on this process.

Frazier, Donald O.↗

Wall to membrane linkers, stretch activated channels, and the detection of tension, voltage, temperature, auxin, and pH

Introduction. The higher plant is a heterogeneous, mechanically prestressed structure continually subject to shifting forces. When a cell grows in a plant at gravitropic equilibrium, it must create localized maxima of shear in walls of neighboring cells. Such mechanical stress and strain are likely detected in a variety of ways. However, tension-sensitive ion channels are of particular interest because it appears that they are elaborately evolved for sensory function. We hypothesize that 1) the patchy patterns of high shear are focused via wall-to-membrane linkers onto the plasma membrane, where 2) they are translated by mechanosensory cation channels into corresponding patterns of high cytosolic Ca2+, which 3) initiate local enhancement of wall expansion. Further, we hypothesize that the local promotion of enhancement is achieved at least in part by local intensification of auxin transport across the plasma membrane. By implication, when an organ is asymmetrically pressed, rubbed, or bent or when it is displaced in the gravitational field, the net asymmetry of shear stress occurring across the organ would lead to asymmetric redistribution of auxin and corrective asymmetric growth. We shall describe a representative mechanosensitive Ca(2+) -selective cation channel (MCaC) with susceptibilities to xenobiotics implicating it as a force transducer in thigmo- and gravitropism. Then, we shall consider whether a putative wall-to-membrane linker (WML) could be a key feature of the molecular architecture permitting the stress distributed in the wall system to be focused on the channels.

NASA Discipline Number 40-50↗

Soft x ray window encapsulant for HgI2 detectors

HgI2 is an excellent semiconductor material for a low energy, room temperature x-ray spectrometer. The high values of the atomic numbers for its constituent elements gives high x-ray and gamma ray stopping power. The band gap of HgI2 is significantly higher than other commonly used semiconductors. Owing to the large value band gap, the leakage current for HgI2 devices is smaller, thus allowing low noise performance. Devices fabricated from HgI2 crystals have demonstrated energy resolution sufficient to distinguish the x-ray emission from the neighboring elements on the periodic table. Also the power requirements of HgI2 are very low. These characteristics make a HgI2 spectrometer an ideal component in a satellite based detection system. Unfortunately, HgI2 crystals tend to deteriorate with time, even if protected by standard semiconductor encapsulants. This degradation ruins the performance of the device in terms of its energy resolution and pulse amplitude. The degrading mechanism is believed to be material loss occurring from below the electrodes, due to high vapor pressure of HgI2 at room temperature. To address this major obstacle to rapid expansion of HgI2 technology, a research program aimed at improving device stability by encapsulation with inert polymeric materials was carried out. The program focused specifically on optimizing the encapsulant materials and their deposition techniques. The principal objectives for this program were device encapsulation, device testing, and accelerated testing to ensure very long term stability of these high resolution sensors. A variety of encapsulants were investigated with the selection criteria based on their chemical diffusion barrier properties, mechanical stability, reactivity, and morphology of encapsulant films. The investigation covered different classes of encapsulants including solvent based encapsulants, vapor deposited encapsulants, and plasma polymerized encapsulants. A variety of characterization techniques were employed to examine their effectiveness in stabilizing HgI2 devices; these included permeability evaluation, vacuum and heat testing, scanning electron microscopy (SEM) as well as studying the detector performance of coated detectors. The plasma polymerized films appear to have entirely solved the HgI2 degradation problem. Another achievement of this program was the development of an accelerated testing technique which correlates extremely well with long term tesing.

Entine, G.↗

Automatic Event Detection in Search for Inter-Moss Loops in IRIS Si IV Slit-Jaw Images

The high-resolution capabilities of the Interface Region Imaging Spectrometer (IRIS) mission have allowed the exploration of the finer details of the solar magnetic structure from the chromosphere to the lower corona that have previously been unresolved. Of particular interest to us are the relatively short-lived, low-lying magnetic loops that have foot points in neighboring moss regions. These inter-moss loops have also appeared in several AIA pass bands, which are generally associated with temperatures that are at least an order of magnitude higher than that of the Si IV emission seen in the 1400 angstrom pass band of IRIS. While the emission lines seen in these pass bands can be associated with a range of temperatures, the simultaneous appearance of these loops in IRIS 1400 and AIA 171, 193, and 211 suggest that they are not in ionization equilibrium. To study these structures in detail, we have developed a series of algorithms to automatically detect signal brightening or events on a pixel-by-pixel basis and group them together as structures for each of the above data sets. These algorithms have successfully picked out all activity fitting certain adjustable criteria. The resulting groups of events are then statistically analyzed to determine which characteristics can be used to distinguish the inter-moss loops from all other structures. While a few characteristic histograms reveal that manually selected inter-moss loops lie outside the norm, a combination of several characteristics will need to be used to determine the statistical likelihood that a group of events be categorized automatically as a loop of interest. The goal of this project is to be able to automatically pick out inter-moss loops from an entire data set and calculate the characteristics that have previously been determined manually, such as length, intensity, and lifetime. We will discuss the algorithms, preliminary results, and current progress of automatic characterization.

loops↗

Wind-Driven Erosion and Exposure Potential at Mars 2020 Rover Candidate-Landing Sites

Abstract Aeolian processes have likely been the predominant geomorphic agent for most of Mars' history and have the potential to produce relatively young exposure ages for geologic units. Thus, identifying local evidence for aeolian erosion is highly relevant to the selection of landing sites for future missions, such as the Mars 2020 Rover mission that aims to explore astrobiologically relevant ancient environments. Here we investigate wind-driven activity at eight Mars 2020 candidate-landing sites to constrain erosion potential at these locations. To demonstrate our methods, we found that contemporary dune-derived abrasion rates were in agreement with rover-derived exhumation rates at Gale crater and could be employed elsewhere. The Holden crater candidate site was interpreted to have low contemporary erosion rates, based on the presence of a thick sand coverage of static ripples. Active ripples at the Eberswalde and southwest Melas sites may account for local erosion and the dearth of small craters. Moderate-flux regional dunes near Mawrth Vallis were deemed unrepresentative of the candidate site, which is interpreted to currently be experiencing low levels of erosion. The Nili Fossae site displayed the most unambiguous evidence for local sand transport and erosion, likely yielding relatively young exposure ages. The downselected Jezero crater and northeast Syrtis sites had high-flux neighboring dunes and exhibited substantial evidence for sediment pathways across their ellipses. Both sites had relatively high estimated abrasion rates, which would yield young exposure ages. The downselected Columbia Hills site lacked evidence for sand movement, and contemporary local erosion rates are estimated to be relatively low. Plain Language Summary Wind-blown dune sand can wear away the Martian surface and uncover

Rover↗

Planetesimal Formation in the Protoplanetary Nebula

In this talk we will address two distinct phases of planetesimal formation, each of which is fundamentally dependent upon the coupled interactions of particles and turbulent nebula gas. It has been shown both numerically and experimentally that 3-D (three dimensional) turbulence concentrates aerodynamically size-selected particles by orders of magnitude. In a previous review chapter we illustrated the initial predictions of Turbulent Concentration (TC) as applied to the solar nebula. We predicted the particle size which will be most effectively concentrated by turbulence; it is the particle which has a gas drag stopping time equal to the overturn time of the smallest (Kolmogorov scale) eddy. The primary uncertainty is the level of nebula turbulence, or Reynolds number Re, which can be expressed in terms of the standard nebula eddy viscosity parameter alpha = Rev(sub m)/cH, where v(sub m) is molecular viscosity, c is sound speed, and H is vertical scale height. Several studies, and observed lifetimes of circumstellar disks, have suggested that the level of nebula turbulence can be described by alpha = 10(exp -2) - 10(exp -4). There is some recent concern about how energy is provided to maintain this turbulence, but the issue remains open. We adopt a canonical minimum mass nebula with a range of alpha is greater than 0. We originally showed that chondrule-sized particles are selected for concentration in the terrestrial planet region if alpha = 10(exp -3) - 10(exp -4). In addition, Paque and Cuzzi found that the size distribution of chondrules is an excellent match for theoretical predictions. One then asks by what concentration factor C these particles can be concentrated; our early numerical results indicated an increase of C with alpha, and were supported by simple scaling arguments, but the extrapolation range was quite large and the predictions (C is approximately equal to 10(exp 5) - 10(exp 6) not unlikely) uncertain. The work presented here, which makes use of our recent demonstration that the particle density field is a multifractal with flow-independent properties provides a far more secure ground for such predictions. We also indicate how fine-grained dust rims on chondrules might enter into constraining the situation. Once large particles (meter-size mass equivalent) reach the midplane, perhaps in the form of dense aggregates of the sort formed in 3D turbulence, they remain stable against gravitational instability but might grow rapidly by accretion of their drifting neighbors, depending on the level of global turbulence.

Cuzzi, Jeffrey N.↗

Shape-dependent control of cell growth, differentiation, and apoptosis: switching between attractors in cell regulatory networks

Development of characteristic tissue patterns requires that individual cells be switched locally between different phenotypes or "fates;" while one cell may proliferate, its neighbors may differentiate or die. Recent studies have revealed that local switching between these different gene programs is controlled through interplay between soluble growth factors, insoluble extracellular matrix molecules, and mechanical forces which produce cell shape distortion. Although the precise molecular basis remains unknown, shape-dependent control of cell growth and function appears to be mediated by tension-dependent changes in the actin cytoskeleton. However, the question remains: how can a generalized physical stimulus, such as cell distortion, activate the same set of genes and signaling proteins that are triggered by molecules which bind to specific cell surface receptors. In this article, we use computer simulations based on dynamic Boolean networks to show that the different cell fates that a particular cell can exhibit may represent a preprogrammed set of common end programs or "attractors" which self-organize within the cell's regulatory networks. In this type of dynamic network model of information processing, generalized stimuli (e.g., mechanical forces) and specific molecular cues elicit signals which follow different trajectories, but eventually converge onto one of a small set of common end programs (growth, quiescence, differentiation, apoptosis, etc.). In other words, if cells use this type of information processing system, then control of cell function would involve selection of preexisting (latent) behavioral modes of the cell, rather than instruction by specific binding molecules. Importantly, the results of the computer simulation closely mimic experimental data obtained with living endothelial cells. The major implication of this finding is that current methods used for analysis of cell function that rely on characterization of linear signaling pathways or clusters of genes with common activity profiles may overlook the most critical features of cellular information processing which normally determine how signal specificity is established and maintained in living cells. Copyright 2000 Academic Press.

Review↗

Modeling the Variability of the BL Lacertae Object PKS 2155-304

The bright X-ray-selected BL Lacertae object PKS 2155-304 has been the target of two intense multi-wavelength campaigns in 1991 November and in 1994 May. Although the spectral energy distributions at both epochs were quite similar, the source exhibited two very distinct variability patterns that cannot be easily reconciled with homogeneous one-zone C7 jet models. During the first epoch the variability was almost achromatic in amplitude, with a time lag between X-rays and ultraviolet radiation (UV) of approximately three hours, while during the second epoch the variability amplitude increased as a function of wavelength with the EUV flare peaking approximately one day after the X-ray flare. We model the source using a time-dependent inhomogeneous accelerating jet model. We reproduce the general characteristics of the different variability signatures by assuming that plasma disturbances with different physical properties propagate downstream in an underlying jet characterized by the same set of physical parameters at both epochs. A time delay of approximately one day between the hardening of the UV spectral index and the UV flux present at both epochs is modeled with stochastic fluctuations in the particle acceleration manifested through small variations of the maximum energy of the injected electrons. We predict that similar time delays will be present in future observations even in the absence of strong variability event. We stress the importance of observations at neighboring frequencies as a diagnostic tool for the structure of the quiescent jet in blazars especially in the seemingly dull case in which strong variability is absent.

Georganopuolos, Markos↗

Long-Lived Venus Lander Conceptual Design: How To Keep It Cool

Surprisingly little is known about Venus, our neighboring sister planet in the solar system, due to the challenges of operating in its extremely hot, corrosive, and dense environment. For example, after over two dozen missions to the planet, the longest-lived lander was the Soviet Venera 13, and it only survived two hours on the surface. Several conceptual Venus mission studies have been formulated in the past two decades proposing lander architectures that potentially extend lander lifetime. Most recently, the Venus Science and Technology Definition Team (STDT) was commissioned by NASA to study a Venus Flagship Mission potentially launching in the 2020- 2025 time-frame; the reference lander of this study is designed to survive for only a few hours more than Venera 13 launched back in 1981! Since Cytherean mission planners lack a viable approach to a long-lived surface architecture, specific scientific objectives outlined in the National Science Foundation Decadal Survey and Venus Exploration Advisory Group final report cannot be completed. These include: mapping the mineralogy and composition of the surface on a planetary scale determining the age of various rock samples on Venus, searching for evidence of changes in interior dynamics (seismometry) and its impact on climate and many other key observations that benefit with time scales of at least a full Venus day (Le. daylight/night cycle). This report reviews those studies and recommends a hybrid lander architecture that can survive for at least one Venus day (243 Earth days) by incorporating selective Stirling multi-stage active cooling and hybrid thermoacoustic power.

Dyson, Ridger W.↗

Recommendations for Technology Development and Validation Activities in Support of the Origins Program

The Office of Space Science (OSS) has initiated mission concept studies and associated technology roadmapping activities for future large space optical systems. The scientific motivation for these systems is the study of the origins of galaxies, stars, planetary systems and, ultimately, life. Collectively, these studies are part of the 'Astronomical Search for Origins and Planetary Systems Program' or 'Origins Program'. A series of at least three science missions and associated technology validation flights is currently envisioned in the time frame between the year 1999 and approximately 2020. These would be the Space Interferometry Mission (SIM), a 10-meter baseline Michelson stellar interferometer; the Next Generation Space Telescope (NGST), a space-based infrared optimized telescope with aperture diameter larger than four meters; and the Terrestrial Planet Finder (TPF), an 80-meter baseline-nulling Michelson interferometer described in the Exploration of Neighboring Planetary Systems (ExNPS) Study. While all of these missions include significant technological challenges, preliminary studies indicate that the technological requirements are achievable. However, immediate and aggressive technology development is needed. The Office of Space Access and Technology (OSAT) is the primary sponsor of NASA-unique technology for missions such as the Origins series. For some time, the OSAT Space Technology Program has been developing technologies for large space optical systems, including both interferometers and large-aperture telescopes. In addition, technology investments have been made by other NASA programs, including OSS; other government agencies, particularly the Department of Defense; and by the aerospace industrial community. This basis of prior technology investment provides much of the rationale for confidence in the feasibility of the advanced Origins missions. In response to the enhanced interest of both the user community and senior NASA management in large space optics, OSAT is moving to improve the focus of its sensor, spacecraft, and interferometer/telescope technology programs on the specific additional needs of the OSS Origins Program. To better define Origins mission technology and facilitate its development, OSAT and OSS called for a series of workshops with broad participation from industry, academia and the national laboratory community to address these issues. Responsibility for workshop implementation was assigned jointly to the two NASA field centers with primary Origins mission responsibility, the Goddard Space Flight Center and the Jet Propulsion Laboratory. The Origins Technology Workshop, held at Dana Point, California between June 4 and 6, 1996 was the first in the series of comprehensive workshops aimed at addressing the broad technological needs of the Origins Program. It was attended by 64 individuals selected to provide technical expertise relevant to the technology challenges of the Origins missions. This report summarizes the results of that meeting. A higher level executive summary was considered inappropriate because of the potential loss of important context for the recommendations. Subsequent to the Origins Technology Workshop and prior to publication of this report, NASA Headquarters reorganized the activities of the Of fice of Space Access and Technology. It appears likely that responsibility for the technology programs recommended in this document will move to the Office of Space Science.

Capps, Richard W.↗

Radiation and Nuclear Technology in Planetary Cave Environments

Many technological and environmental challenges must be resolved to enable successful lunar habitation and exploration, and to maximize scientific return. This presentation is intended as a preliminary discussion on three such areas of interest with the intent to identify likely areas of mutual benefit for collaboration and data sharing between the space nuclear and radiological disciplines with the planetary cave community. First is the previously identified and studied possible application of lunar lava tubes or pits to reduce the solar and cosmic radiation environment burden on crew health and hardware reliability. This is an area of continued interest, and should be kept in the forefront of discussion during the selection of sites for potential exploration or long-term habitation. In theory, the prospect of using existing morphology presents an enticing opportunity to reduce the requirements on landed mass or construction while also reducing dose or fluence of harmful natural radiation. However, such discussions should also include the practical implications of relocating habitation hardware and personnel from a landing site to a subsurface location. Inherent risks associated with landing in proximity to the relevant terrain must also be considered and weighed against those imposed by the natural radiation environment. Second is a discussion on the means by which a long-term habitation module or base of operations may be powered throughout the lunar day-night cycle. Fission surface power presents an opportunity to establish round-the-clock power in any lunar surface environment, including permanently shadowed regions where solar panels cannot operate, or in any other non-polar region where solar radiation is available for no more than two weeks per four-week cycle. Among the drawbacks of fission surface power is the need to either land and co-locate a heavy shield to minimize radiological consequences to personnel or equipment, land and operate construction equipment capable of restructuring the in-situ regolith to provide appropriate shielding, or to make use of existing topology features (e.g. craters or pits) to serve as pre-formed radiation barriers. A realistic assessment of the practicality of this third option should involve the selection of candidate features from existing surveys, and assess the effectiveness of the approach using modern radiation transport methodologies. Consideration must be made for the needs to reject waste heat in the thermal power conversion process, which typically requires the use of large area radiators. Energy must be exchanged from the reactor and power conversion system to such radiators, and the impacts on thermal efficiency and secondary scatter of nuclear radiation must be considered. Further consideration should be made for the implications of placement of a power source such that it does not sacrifice valuable scientific opportunity. Placement of a reactor is likely to thereafter prevent personnel access within that feature. Third is a discussion on the use of portable radioisotope power systems (RPS) within confined spaces, both with respect to the dose effects of emitted nuclear radiation and also performance associated with emitted thermal radiation. Radioisotope power systems provide a unique capability to power objects with no reliance upon solar radiance. However, their useable power production relies upon the flow of heat from ‘hot side’ (decaying radioisotope) to ‘cold side’ (radiators emitting heat to space). In the case of a confined volume in vacuum such as a lunar lava tube, that radiated energy will absorb into the wall, which is already above the ‘cold background’ temperature of dark space, and then gradually rises in temperature. That temperature rise, and its implications on availability of useable electrical power, will depend upon factors such as enclosure volume, thermal emissivity/absorptivity, and thermal conductivity through the depth of absorbing media. The advantages of nuclear technology may prove to enable unique scientific exploration opportunities, both above the lunar surface and below. In turn, the unique advantages of lunar lava tubes or pits may present unique opportunities to enhance the application of these technologies and to mitigate the effects of radiation from both natural and technological sources. A discussion on these pairings may prove to be valuable to all, in our endeavor to explore our neighboring worlds.

Radiation↗

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↗