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NASA NTRS2016

Status of NASA's Space Launch System

NASA's Space Launch System (SLS) continued to make significant progress in 2015, completing hardware and testing that brings NASA closer to a new era of deep space exploration. The most significant program milestone of the year was completion of Critical Design Review (CDR). A team of independent reviewers concluded that the vehicle design is technically and programmatically ready to move to Design Certification Review (DCR) and launch readiness in 2018. Just four years after program start, every major element has amassed development and flight hardware and completed key tests that will set the stage for a growing schedule of manufacturing and testing in 2016. Key to SLS' rapid progress has been the use of existing technologies adapted to the new launch vehicle. The space shuttle-heritage RS-25 engine is undergoing adaptation tests to prove it can meet SLS requirements and environments with minimal change. The four-segment shuttle-era booster has been modified and updated with an additional propellant segment, new insulation, and new avionics. The Interim Cryogenic Upper Stage is a modified version of an existing upper stage. The first Block I SLS configuration will launch a minimum of 70 metric tons of payload to low Earth orbit (LEO). The vehicle architecture has a clear evolutionary path to more than 100 metric tons and, ultimately, to 130 metric tons. Among the program's major accomplishments in 2015 were the first booster qualification hotfire test, a series of seven RS-25 adaptation hotfire tests, manufacturing of most of the major components for both core stage test articles and first flight tank, delivery of the Pegasus core stage barge, and the upper stage simulator. Renovations to the B-2 test stand for stage green run testing was completed at NASA Stennis Space Center. This year will see the second booster qualification motor hotfire, flight and additional development RS-25 engine tests, and completion of core stage test articles and test stands and several flight article sections. This paper will discuss these and other technical and programmatic successes and challenges over the past year and provide a preview of work ahead before the first flight of this new capability.

Honeycutt, John↗

NASA NTRS2016

Is It Worth It? - the Economics of Reusable Space Transportation

Over the past several decades billions of dollars have been invested by governments and private companies in the pursuit of lower cost access to space through earth-to-orbit (ETO) space transportation systems. Much of that investment has been focused on the development and operation of various forms of reusable transportation systems. From the Space Shuttle to current efforts by private commercial companies, the overarching belief of those making such investments has been that reusing system elements will be cheaper than utilizing expendable systems that involve throwing away costly engines, avionics, and other hardware with each flight. However, the view that reusable systems are ultimately a "better" approach to providing ETO transportation is not held universally by major stakeholders within the space transportation industry. While the technical feasibility of at least some degree of reusability has been demonstrated, there continues to be a sometimes lively debate over the merits and drawbacks of reusable versus expendable systems from an economic perspective. In summary, is it worth it? Based on our many years of direct involvement with the business aspects of several expendable and reusable transportation systems, it appears to us that much of the discussion surrounding reusability is hindered by a failure to clearly define and understand the financial and other metrics by which the financial "goodness" of a reusable or expandable approach is measured. As stakeholders, the different users and suppliers of space transportation have a varied set of criteria for determining the relative economic viability of alternative strategies, including reusability. Many different metrics have been used to measure the affordability of space transportation, such as dollars per payload pound (kilogram) to orbit, cost per flight, life cycle cost, net present value/internal rate of return, and many others. This paper will examine the key considerations that influence stakeholders as they make space transportation investment decisions, including primary metrics by which various stakeholders measure financial goodness and other factors that significantly shape decisions to invest in reusable or expendable systems. It must be noted at the outset that reusable systems take many forms and perform different transportation functions including, but not limited to, ETO payload delivery. The discussion in this paper is limited to the economics of ETO transportation systems.

Webb, Richard↗

NASA NTRS2016

Field Test: Results of Tandem Walk Performance Following Long-Duration Spaceflight

BACKGROUND: Coordinated locomotion has proven to be challenging for many astronauts following long duration spaceflight. As NASA's vision for spaceflight points toward interplanetary travel, we must prepare for unassisted landings, where crewmembers may need to perform mission critical tasks within minutes of landing. Thus, it is vital to develop a knowledge base from which operational guidelines can be written that define when astronauts can be expected to safely perform certain tasks. Data obtained during the Field Test experiment (FT) will add important insight to this knowledge base. Specifically, we aim to develop a recovery timeline of functional sensorimotor performance during the first 24 hours and several days after landing. METHODS: FT is an ongoing study of 30 long-duration ISS crewmembers. Thus far, 9 have completed the full FT (5 U.S. Orbital Segment [USOS] astronauts and 4 Russian cosmonauts) and 4 more consented and launching within the next year. This is in addition to the eighteen crewmembers that participated in the pilot FT (11 USOS and 7 Russian crewmembers). The FT is conducted three times preflight and three times during the first 24 hours after landing. All crewmembers were tested in Kazakhstan in either the medical tent at the Soyuz landing site (~one hour post-landing), or at the airport (~four hours post-landing). The USOS crewmembers were also tested at the refueling stop (~12 hours post-landing) and at the NASA Johnson Space Center (~24 hours post-landing) and a final session 7 days post-landing. Crewmembers are instrumented with 9 inertial measurement unit sensors that measure acceleration and angular displacement (APDM's Emerald Sensors) and foot pressure-sensing insoles that measure force, acceleration, and center of pressure (Moticon GmbH, Munich, Germany) along with heart rate and blood pressure recording instrumentation. The FT consists of 12 tasks, but here we will focus on the most challenging task, the Tandem Walk, which was also performed as part of pilot FT. To perform the Tandem Walk, subjects begin with their feet together, their arms crossed at their chest and eyes closed. When ready, they brought one foot forward and touched the heel of their foot to their toe, repeating with the other foot, and continuing for about 10 steps. Three trials were collected with the eyes closed and a fourth trial was collected with eyes open. There are four metrics which are used to determine the performance level of the Tandem Walk. The first is percent correct steps. For a step to be counted as correct, the foot could not touch the ground while bringing it forward (no side stepping), eyes must stay closed during the eyes closed trials, the heel and toe should be touching, or almost touching (no large gaps) and there shouldn't be more than a three second pause between steps. Three judges score each step and the median of the three scores is kept. The second metric is the average step speed, or the number of steps/time to complete them. Thirdly, the root mean squared (RMS) error in the resultant trunk acceleration is used to determine the amount of upper body instability observed during the task. Finally, the RMS error of the mediolateral center of pressure as measured by the Moticon insoles is used to determine the mediolateral instability at the foot level. These four parameters are combined into a new overall Tandem Walk Parameter. RESULTS: Preliminary results show that crewmembers perform the Tandem Walk significantly worse the first 24 hours after landing as compared to their baseline performance. We find that each of the four performance metrics is significantly worse immediately after landing. We will present the results of tandem walk performance during the FT thus far. We will also combine these with the 18 crewmembers that participated in the pilot FT, concentrating on the level of performance and recovery rate. CONCLUSION: The Tandem Walk data collected as part of the FT experiment will provide invaluable information on the performance capabilities of astronauts during the first 24 hours after returning from long-duration spaceflight that can be used in planning future Mars, or other deep-space missions with unassisted landings. FT will determine the average sensorimotor recovery timeline and inform return-to-duty guidelines for unassisted landings.

Rosenberg, M. J. F.↗

NASA NTRS2016

A New Look at Data Usage by Using Metadata Attributes as Indicators of Data Quality

This study reviews the key metrics (users, distributed volume, and files) in multiple ways to gain an understanding of the significance of the metadata. Characterizing the usability of data by key metadata elements, such as discipline and study area, will assist in understanding how the user needs have evolved over time. The data usage pattern based on product level provides insight into the level of data quality. In addition, the data metrics by various services, such as the Open-source Project for a Network Data Access Protocol (OPeNDAP) and subsets, address how these services have extended the usage of data. Over-all, this study presents the usage of data and metadata by metrics analyses, which may assist data centers in better supporting the needs of the users.

metadata↗

NASA NTRS2016

Trade-Space Analysis Tool for Constellations (TAT-C)

Traditionally, space missions have relied on relatively large and monolithic satellites, but in the past few years, under a changing technological and economic environment, including instrument and spacecraft miniaturization, scalable launchers, secondary launches as well as hosted payloads, there is growing interest in implementing future NASA missions as Distributed Spacecraft Missions (DSM). The objective of our project is to provide a framework that facilitates DSM Pre-Phase A investigations and optimizes DSM designs with respect to a-priori Science goals. In this first version of our Trade-space Analysis Tool for Constellations (TAT-C), we are investigating questions such as: How many spacecraft should be included in the constellation? Which design has the best costrisk value? The main goals of TAT-C are to: Handle multiple spacecraft sharing a mission objective, from SmallSats up through flagships, Explore the variables trade space for pre-defined science, cost and risk goals, and pre-defined metrics Optimize cost and performance across multiple instruments and platforms vs. one at a time.This paper describes the overall architecture of TAT-C including: a User Interface (UI) interacting with multiple users - scientists, missions designers or program managers; an Executive Driver gathering requirements from UI, then formulating Trade-space Search Requests for the Trade-space Search Iterator first with inputs from the Knowledge Base, then, in collaboration with the Orbit Coverage, Reduction Metrics, and Cost Risk modules, generating multiple potential architectures and their associated characteristics. TAT-C leverages the use of the Goddard Mission Analysis Tool (GMAT) to compute coverage and ancillary data, streamlining the computations by modeling orbits in a way that balances accuracy and performance.TAT-C current version includes uniform Walker constellations as well as Ad-Hoc constellations, and its cost model represents an aggregate model consisting of Cost Estimating Relationships (CERs) from widely accepted models. The Knowledge Base supports both analysis and exploration, and the current GUI prototype automatically generates graphics representing metrics such as average revisit time or coverage as a function of cost.

Science Data Processing↗

NASA NTRS2016

Assessing Spontaneous Combustion Instability with Recurrence Quantification Analysis

Spontaneous instabilities can pose a significant challenge to verification of combustion stability, and characterizing its onset is an important avenue of improvement for stability assessments of liquid propellant rocket engines. Recurrence Quantification Analysis (RQA) is used here to explore nonlinear combustion dynamics that might give insight into instability. Multiple types of patterns representative of different dynamical states are identified within fluctuating chamber pressure data, and markers for impending instability are found. A class of metrics which describe these patterns is also calculated. RQA metrics are compared with and interpreted against another metric from nonlinear time series analysis, the Hurst exponent, to help better distinguish between stable and unstable operation.

Eberhart, Chad J.↗

NASA NTRS2017

Examination of a Rotorcraft Noise Prediction Method and Comparison to Flight Test Data

With a view that rotorcraft noise should be included in the preliminary design process, a relatively fast noise prediction method is examined in this paper. A comprehensive rotorcraft analysis is combined with a noise prediction method to compute several noise metrics of interest. These predictions are compared to flight test data. Results show that inclusion of only the main rotor noise will produce results that severely underpredict integrated metrics of interest. Inclusion of the tail rotor frequency content is essential for accurately predicting these integrated noise metrics.

Boyd, D. Douglas, Jr.↗

NASA NTRS2017

Comparison of Commonly-Used Microwave Radiative Transfer Models for Snow Remote Sensing

This paper reviews four commonly-used microwave radiative transfer models that take different electromagnetic approaches to simulate snow brightness temperature (T(sub B)): the Dense Media Radiative Transfer - Multi-Layer model (DMRT-ML), the Dense Media Radiative Transfer - Quasi-Crystalline Approximation Mie scattering of Sticky spheres (DMRT-QMS), the Helsinki University of Technology n-Layers model (HUT-nlayers) and the Microwave Emission Model of Layered Snowpacks (MEMLS). Using the same extensively measured physical snowpack properties, we compared the simulated T(sub B) at 11, 19 and 37 GHz from these four models. The analysis focuses on the impact of using different types of measured snow microstructure metrics in the simulations. In addition to density, snow microstructure is defined for each snow layer by grain optical diameter (Do) and stickiness for DMRT-ML and DMRT-QMS, mean grain geometrical maximum extent (D(sub max)) for HUT n-layers and the exponential correlation length for MEMLS. These metrics were derived from either in-situ measurements of snow specific surface area (SSA) or macrophotos of grain sizes (D(sub max)), assuming non-sticky spheres for the DMRT models. Simulated T(sub B) sensitivity analysis using the same inputs shows relatively consistent T(sub B) behavior as a function of Do and density variations for the vertical polarization (maximum deviation of 18 K and 27 K, respectively), while some divergences appear in simulated variations for the polarization ratio (PR). Comparisons with ground based radiometric measurements show that the simulations based on snow SSA measurements have to be scaled with a model-specific factor of Do in order to minimize the root mean square error (RMSE) between measured and simulated T(sub B). Results using in-situ grain size measurements (SSA or D(sub max), depending on the model) give a mean T(sub B) RMSE (19 and 37 GHz) of the order of 16-26 K, which is similar for all models when the snow microstructure metrics are scaled. However, the MEMLS model converges to better results when driven by the correlation length estimated from in-situ SSA measurements rather than D(sub max) measurements. On a practical level, this paper shows that the SSA parameter, a snow property that is easy to retrieve in-situ, appears to be the most relevant parameter for characterizing snow microstructure, despite the need for a scaling factor.

Snow↗

NASA NTRS2015

JPSS-1 VIIRS Pre-Launch Radiometric Performance

The first Joint Polar Satellite System (JPSS-1 or J1) mission is scheduled to launch in January 2017, and will be very similar to the Suomi-National Polar-orbiting Partnership (SNPP) mission. The Visible Infrared Imaging Radiometer Suite (VIIRS) on board the J1 spacecraft completed its sensor level performance testing in December 2014. VIIRS instrument is expected to provide valuable information about the Earth environment and properties on a daily basis, using a wide-swath (3,040 km) cross-track scanning radiometer. The design covers the wavelength spectrum from reflective to long-wave infrared through 22 spectral bands, from 0.412 m to 12.01 m, and has spatial resolutions of 370 m and 740 m at nadir for imaging and moderate bands, respectively. This paper will provide an overview of pre-launch J1 VIIRS performance testing and methodologies, describing the at-launch baseline radiometric performance as well as the metrics needed to calibrate the instrument once on orbit. Key sensor performance metrics include the sensor signal to noise ratios (SNRs), dynamic range, reflective and emissive bands calibration performance, polarization sensitivity, bands spectral performance, response-vs-scan (RVS), near field response, and stray light rejection. A set of performance metrics generated during the pre-launch testing program will be compared to the sensor requirements and to SNPP VIIRS pre-launch performance.

Oudrari, Hassan↗

NASA NTRS2017

Image Navigation and Registration Performance Assessment Evaluation Tools for GOES-R ABI and GLM

The GOES-R Flight Project has developed an Image Navigation and Registration (INR) Performance Assessment Tool Set (IPATS) for measuring Advanced Baseline Imager (ABI) and Geostationary Lightning Mapper (GLM) INR performance metrics in the post-launch period for performance evaluation and long term monitoring. IPATS utilizes a modular algorithmic design to allow user selection of data processing sequences optimized for generation of each INR metric. This novel modular approach minimizes duplication of common processing elements, thereby maximizing code efficiency and speed. Fast processing is essential given the large number of sub-image registrations required to generate INR metrics for the many images produced over a 24 hour evaluation period. This paper describes the software design and implementation of IPATS and provides preliminary test results.

Image registration↗

NASA NTRS2017

Image Navigation and Registration Performance Assessment Evaluation Tools for GOES-R ABI and GLM

image registration↗

NASA NTRS2015

Quantifying Mapping Orbit Performance in the Vicinity of Primitive Bodies

Predicting and quantifying the capability of mapping orbits in the vicinity of primitive bodies is challenging given the complex orbit geometries that exist and the irregular shape of the bodies themselves. This paper employs various quantitative metrics to characterize the performance and relative effectiveness of various types of mapping orbits including terminator, quasi-terminator, hovering, ping pong, and conic-like trajectories. Metrics of interest include surface area coverage, lighting conditions, and the variety of viewing angles achieved. The metrics discussed in this investigation are intended to enable mission designers and project stakeholders to better characterize candidate mapping orbits during preliminary mission formulation activities. The goal of this investigation is to understand the trade space associated with carrying out remote sensing campaigns at small primitive bodies in the context of a robotic space mission. Specifically, this study seeks to understand the surface viewing geometries, ranges, etc. that are available from several commonly proposed mapping orbits architectures

Pavlak, Thomas A.↗

NASA NTRS2017

Evaluation of a Tactical Surface Metering Tool for Charlotte Douglas International Airport via Human-in-the-Loop Simulation

NASA has been working with the FAA and aviation industry partners to develop and demonstrate new concepts and technologies that integrate arrival, departure, and surface traffic management capabilities. In March 2017, NASA conducted a human-in-the-loop (HITL) simulation for integrated surface and airspace operations, modeling Charlotte Douglas International Airport, to evaluate the operational procedures and information requirements for the tactical surface metering tool, and data exchange elements between the airline controlled ramp and ATC Tower. In this paper, we focus on the calibration of the tactical surface metering tool using various metrics measured from the HITL simulation results. Key performance metrics include gate hold times from pushback advisories, taxi-in-out times, runway throughput, and departure queue size. Subjective metrics presented in this paper include workload, situational awareness, and acceptability of the metering tool and its calibration.

Verma, Savita↗

NASA NTRS2017

Machine Learning Approaches to Increasing Value of Spaceflight Omics Databases

The number of spaceflight bioscience mission opportunities is too small to allow all relevant biological and environmental parameters to be experimentally identified. Simulated spaceflight experiments in ground-based facilities (GBFs), such as clinostats, are each suitable only for particular investigations -- a rotating-wall vessel may be 'simulated microgravity' for cell differentiation (hours), but not DNA repair (seconds) -- and introduce confounding stimuli, such as motor vibration and fluid shear effects. This uncertainty over which biological mechanisms respond to a given form of simulated space radiation or gravity, as well as its side effects, limits our ability to baseline spaceflight data and validate mission science. Machine learning techniques autonomously identify relevant and interdependent factors in a data set given the set of desired metrics to be evaluated: to automatically identify related studies, compare data from related studies, or determine linkages between types of data in the same study. System-of-systems (SoS) machine learning models have the ability to deal with both sparse and heterogeneous data, such as that provided by the small and diverse number of space biosciences flight missions; however, they require appropriate user-defined metrics for any given data set. Although machine learning in bioinformatics is rapidly expanding, the need to combine spaceflight/GBF mission parameters with omics data is unique. This work characterizes the basic requirements for implementing the SoS approach through the System Map (SM) technique, a composite of a dynamic Bayesian network and Gaussian mixture model, in real-world repositories such as the GeneLab Data System and Life Sciences Data Archive. The three primary steps are metadata management for experimental description using open-source ontologies, defining similarity and consistency metrics, and generating testing and validation data sets. Such approaches to spaceflight and GBF omics data may soon enable unique insight into which measured phenomena correlate to biological mechanisms that are truly affected by spaceflight conditions; which are most likely to be confounded by other variables; and which are insufficiently characterized, significantly increasing existing and future science return from ISS and spaceflight missions.

Gentry, Diana↗

NASA NTRS2017

Evaluation of a Tactical Surface Metering Tool for Charlotte Douglas International Airport Via Human-in-the-Loop Simulation

NASA has been working with the FAA and aviation industry partners to develop and demonstrate new concepts and technologies that integrate arrival, departure, and surface traffic management capabilities. In March 2017, NASA conducted a human-in-the-loop (HITL) simulation for integrated surface and airspace operations, modeling Charlotte Douglas International Airport, to evaluate the operational procedures and information requirements for the tactical surface metering tool, and data exchange elements between the airline controlled ramp and ATC Tower. In this paper, we focus on the calibration of the tactical surface metering tool using various metrics measured from the HITL simulation results. Key performance metrics include gate hold times from pushback advisories, taxi-in/out times, runway throughput, and departure queue size. Subjective metrics presented in this paper include workload, situational awareness, and acceptability of the metering tool and its calibration

air traffic management↗

NASA NTRS2017

NASA's Space Launch System: Enabling Exploration and Discovery

As NASA's new Space Launch System (SLS) launch vehicle continues to mature toward its first flight and beyond, so too do the agency's plans for utilization of the rocket. Substantial progress has been made toward the production of the vehicle for the first flight of SLS - an initial "Block 1" configuration capable of delivering more than 70 metric tons (t) to Low Earth Orbit (LEO). That vehicle will be used for an uncrewed integrated test flight, propelling NASA's Orion spacecraft into lunar orbit before it returns safely to Earth. Flight hardware for that launch is being manufactured at facilities around the United States, and, in the case of Orion's service module, beyond. At the same time, production has already begun on the vehicle for the second SLS flight, a more powerful Block 1B configuration capable of delivering more than 105 metric tons to LEO. This configuration will be used for crewed launches of Orion, sending astronauts farther into space than anyone has previously ventured. The 1B configuration will introduce an Exploration Upper Stage, capable of both ascent and in-space propulsion, as well as a Universal Stage Adapter - a payload bay allowing the flight of exploration hardware with Orion - and unprecedentedly large payload fairings that will enable currently impossible spacecraft and mission profiles on uncrewed launches. The Block 1B vehicle will also expand on the initial configuration's ability to deploy CubeSat secondary payloads, creating new opportunities for low-cost access to deep space. Development work is also underway on future upgrades to SLS, which will culminate in about a decade in the Block 2 configuration, capable of delivering 130 metric tons to LEO via the addition of advanced boosters. As the first SLS draws closer to launch, NASA continues to refine plans for the human deep-space exploration it will enable. Planning currently focuses on use of the vehicle to assemble a Deep Space Gateway, which would comprise a habitat in the lunar vicinity allowing astronauts to gain experience living and working in deep space, a testbed for new systems and capabilities needed for exploration beyond, and a departure point for NASA and partners to send missions to other destinations. Assembly of the Gateway would be followed by a Deep Space Transport, which would be a vehicle capable of carrying astronauts farther into our solar system and eventually to Mars. This paper will give an overview of SLS' current status and its capabilities, and discuss current utilization planning.

Robinson, Kimberly F.↗

NASA NTRS2017

Robust Exploration and Commercial Missions to the Moon Using LANTR Propulsion and In-Situ Propellants Derived From Lunar Polar Ice (LPI) Deposits

Since the 1960s, scientists have conjectured that water icecould survive in the cold, permanently shadowed craters located at the Moons poles Clementine (1994), Lunar Prospector (1998),Chandrayaan-1 (2008), and Lunar Reconnaissance Orbiter (LRO) and Lunar CRater Observation and Sensing Satellite(LCROSS) (2009) lunar probes have provided data indicating the existence of large quantities of water ice at the lunar poles The Mini-SAR onboard Chandrayaan-1discovered more than 40 permanently shadowed craters near the lunar north pole that are thought to contain 600 million metric tons of water ice. Using neutron spectrometer data, the Lunar Prospector science team estimated a water ice content (1.5 +-0.8 wt in the regolith) found in the Moons polar cold trap sand estimated the total amount of water at both poles at 2 billion metric tons Using Mini-RF and spectrometry data, the LRO LCROSS science team estimated the water ice content in the regolith in the south polar region to be 5.6 +-2.9 wt. On the basis of the above scientific data, it appears that the water ice content can vary from 1-10 wt and the total quantity of LPI at both poles can range from 600 million to 2 billion metric tons NTP offers significant benefits for lunar missions and can take advantage of the leverage provided from using LDPs when they become available by transitioning to LANTR propulsion. LANTR provides a variablethrust and Isp capability, shortens burn times and extends engine life, and allows bipropellant operation The combination of LANTR and LDP has performance capability equivalent to that of a hypothetical gaseousfuel core NTR (effective Isp 1575 s) and can lead to a robust LTS with unique mission capabilities that include short transit time crewed cargo transports and routine commuter flights to the Moon The biggest challenge to making this vision a reality will be the production of increasing amounts of LDP andthe development of propellant depots in LEO, LLO and LPO. An industry-operated, privately financed venture, with NASA as its initial customer, might provide a possible blueprint for future development and operation With industry interested in developing cislunar space and commerce, and competitive forces at work, the timeline for developing this capability could well be accelerated, quicker than any of us can imagine, and just the beginning of things to come.

Nuclear Thermal Propulsion↗

NASA NTRS2018

Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project: Terminal Operations HITL 1B Primary Results

This presentation provides an overview of the primary results from the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project's second Terminal Operations human-in-the-loop simulation. This talk covers the background of this follow-on experiment, which includes an overview of the first Terminal Operations HITL performed by the project. The primary results include a look at the number and durations of detect and avoid (DAA) alerts issued by the two DAA systems under test. It also includes response time metrics and metrics on the ability of the pilot-in-command (PIC) to maintain sufficient separation. Additional interoperability metrics are included to illustrate how pilots interact with the tower controller. Implications and conclusions are covered at the end.

unmanned aircraft systems↗