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At least 649 records · Page 36

Overview and Initial Results of SAND-E: Semi-Autonomous Navigation for Detrital Environments

Unmanned aerial systems (UAS) and automated terrain analysis for science and navigation are new technologies for planetary exploration. The Mars Helicopter will fly with the Mars2020 rover, the Dragonfly quadcopter will explore Titan, and Soil Properties and Object Classification (SPOC) software will be used for path planning and navigation on the Mars2020 rover. Using an Argo J5 rover instrumented with stereo cameras and Autonomous Soil Assessment System (ASAS) software, and an off the shelf quadcopter, SAND-E tested the use of automated terrain analysis and UAS data for science operations in a Mars-analog environment in Iceland during July of 2019. Scientifically, we sought to determine changes in the physical and chemical properties of sediments along a glacial-fluvial-aeolian transport pathway. Operationally, we tested rover mission-like scenarios that included UAS images and classified terrain images. Here, we present the initial results for both the operations and science elements of the study. Site Selection: A goal of SAND-E is examine sorting and alteration of sediments in fluvial and aeolian environments in both mineral-dominated and glass-dominated basaltic settings. During the first year of the project we focused on a mineral-dominated environment. Selection of the location was based on prior publications that indicated our selected region had a greater abundance of crystalline sediments than other areas fluvial-aeolian settings in Iceland. Other criteria included the presence of both fluvial and aeolian landforms along a transport pathway such that the sediments in transport could be linked to their source rocks. We chose the Skjaldbreidauhraun glacial outwash plain, which sits at the base of Thórisjökull glacier. The site is 30 km north of Thingvellir National Park and ~2 hours from Reykjavik. The outwash plain is fed by two small catchments that drain from the base of the glacier and cut through hyaloclastite and shield volcano bedrock. The drainage progresses from steep alluvial fans near the glacier into a low-sloping fluvial braidplain that becomes confined by the Skjaldbreidur shield volcano and creates a shallow canyon cut into lava bedrock. The fluvial system was a typical braided alluvial environment composed pebble- and cobble-bedded longitudinal bars and sandy channel beds. The river remained active and fluctuated in response to diurnal runoff cycles near the glacier before disappearing into the sandy substrate downstream. The high concentration of suspended sediment in the river was evident by the cloudy water and the silt and clay-sized sediments that draped the channel beds after abandonment and created playas in the lowest sloping areas of the catchment. The entire fluvial system was affected by the winds generated by frontal systems and katabatic flows descending the glacier. This resulted in the formation of aeolian lag deposits and a wind-deflation plain where the fluvial system was not active. Wind ripples and drifts formed in abandoned fluvial channels from aeolian reworking of the sand-sized fluvial sediments. The silt- and clay-sized sediments found in fluvial channels, bar tops, and playas generated dust plumes during high wind events. Our operation sought to capture the variability in this system by sampling from the range of fluvial and aeolian features 6.3 km (proximal), 11.3 km (medial), and 14.4 km (distal) along the river from its origin at the base of glacier.

Ewing, R. C.↗

Potential Applications of Active Antenna Technologies for Emerging NASA Space Communications Scenarios

Abstract—The National Aeronautics and Space Administration (NASA) is presently embarking on the implementation of far-reaching changes within the framework of both space and aeronautics communications architectures. For example, near earth relays are looking to transition from the traditional few large geostationary satellites to satellite constellations consisting of thousands of small low earth orbiting satellites while lunar space communications will require the need to relay data from many assets distributed on the lunar surface back to earth. Furthermore, within the aeronautics realm, satellite communications for beyond line of sight (BLOS) links are being investigated in tandem with the proliferation of unmanned aerial systems (UAS) within the urban air mobility (UAM) environment. In all of these scenarios, future communications architectures will demand the need to connect and quickly transition between many nodes for large data volume transport. As such, NASA Glenn Research Center (GRC) has been heavily investigating the development of low cost phased array technologies that can readily address these various scenario conditions. In particular, GRC is presently exploring 5G-based beamformer technologies to leverage commercial timescale and volume production cycles which have heretofore not existed within the frequency allocations utilized for NASA applications. In this paper, an overview of the potential future applications of phased arrays being envisioned by NASA are discussed, along with technology feasibility demonstrations being conducted by GRC implementing low cost, 5G based beamformer technologies.

Nessel, James A.↗

Autonomous Assessment and Predictive Capabilities for Low-Altitude Urban Flight Operations

The integration of unmanned aerial vehicles in the national airspace will introduce new vehicle types, technologies, and operational paradigms for which safety must be maintained and hazards mitigated. One approach is to attempt to design for possible hazards and unsafe incidents that can occur at different phases of flight (pre-flight, in-flight, and post-flight) and during ground operations. Another is to mitigate safety incidents by implementing changes to policies, procedures, regulations, and design to cover personnel, equipment, and aircraft during operations. These and other techniques, not described herein, are typically conservative or adhoc in that they reduce the likelihood of risk after safety incidents have occurred. In this work, the goal is to develop a more predictive capability to monitor and mitigate risk and hazards to safety “in-time” enough for decisions to be made. In line with NASA’s Aeronautics Mission Directorate Strategic Thrust 5 [1] (In-Time System-Wide Safety Assurance), the System-Wide Safety (SWS) project under which this work falls, is developing and demonstrating innovative and safety-oriented solutions that enable modernization and aviation transformation. To that effect, this work will detail data-driven efforts on the SWS project to develop a number of safety-critical services for in-time monitoring and mitigation of hazards to low-altitude flight operations. First, hazards to these operations are identified based on previous work by NASA [2,3] and others in the aerospace industry. These hazards include (i) unsafe proximity to other vehicles, property, and people on the ground, (ii) critical system failures such as communication signal/GPS loss, unexpected propulsion system degradation, engine/power failure, and (iii) operational/environmental issues such as severe weather and gusty winds. For these hazards, safety metrics, which can be quantified and assessed are defined, models to monitor and predict them are developed, and flight test data is generated to develop, validate, and test these models, considering the complex interplay of the different hazards that define them [4-6]. In addition, the uncertainty in the non-deterministic effects that cannot be modeled nor predicted and unknown unknowns that arise after design/testing and during operations must be handled in rigorous manner. As a result, for each of the developed safety metrics, their dependencies on one another are characterized and a framework for handling the uncertainties inherent in the modeling, algorithms, and measurements required for prediction is also developed [7]. To that effect, this presentation will describe the safety metrics and services already developed and underway under the System-Wide Safety project that utilize data-driven techniques for the identification of anomalies, precursors, and trends (APTs) to monitor and mitigate hazards to safety, in-time, for urban flight operations in low-altitude airspace.

Okolo, Wendy A.↗

Auralization of Air Vehicle Noise for Community Noise Assessment

This paper serves as an introduction to air vehicle noise auralization and documents the current state-of-the-art. Auralization of flyover noise considers the source, path, and receiver as part of a time marching simulation. Two approaches are offered; a time domain approach performs synthesis followed by propagation, while a frequency domain approach performs propagation followed by synthesis. Source noise description methods are offered for isolated and installed propulsion system and airframe noise sources for a wide range of air vehicles. Methods for synthesis of broadband, discrete tones, steady and unsteady periodic, and a periodic sources are presented, and propagation methods and receiver considerations are discussed. Auralizations applied to vehicles ranging from large transport aircraft to small unmanned aerial systems demonstrate current capabilities.

Rizzi, Stephen A.↗

On the Use of Acoustic Wind Tunnel Data for the Simulation of sUAS Flyover Noise

Acoustic measurements of a small, unmanned aerial system were recently acquired during a ground test campaign. The purposes of the ground test, conducted in the NASA Langley Low Speed Aeroacoustic Wind Tunnel, were to characterize the source noise in terms of its tonal and broadband content, and to identify conditions under which multirotor and rotor-airframe interactions are present. The focus of this work is to assess the effectiveness of using those data for the simulation of flyover noise at a ground observer. The assessment is made at two levels of fidelity using different sets of tools. In the first, 1/3 octave band spectra at a ground receiver will be simulated in a frequency domain approach using the NASA Aircraft NOise Prediction Program. In the second, the pressure time history at a ground receiver is simulated in a time domain approach using the NASA Auralization Framework. Various objective measures are used to verify the simulation process. Acoustic wind tunnel and flight test data are used to gain insight into perceptually important effects.

Rizzi, Stephen A.↗

Distributed Consensus to Enable Merging and Spacing of UAS in an Urban Environment

This paper presents a novel approach to enable multiple Unmanned Aerial Systems approaching a common intersection to independently schedule their arrival time while maintaining a safe separation. Aircraft merging at a common intersection are grouped into a network and each aircraft broadcasts its arrival time interval to the network. A distributed consensus algorithm elects a leader among the aircraft approaching the intersection and helps synchronize the information received by each aircraft. The consensus algorithm ensures that each aircraft computes a schedule with the same input information. The elected leader also dictates when a schedule must be computed, which may be triggered when a new aircraft joins the network. Preliminary results illustrating the collaborative behavior of the vehicles are presented.

Balachandran, Swee↗

Safe2Ditch Steer-To-Clear Development and Flight Testing

This paper describes a series of small unmanned aerial system (sUAS) flights performed at NASA Langley Research Center in April and May of 2019 to test a newly added Steer-to-Clear feature for the Safe2Ditch (S2D) prototype system. S2D is an autonomous crash management system for sUAS. Its function is to detect the onset of an emergency for an autonomous vehicle, and to enable that vehicle in distress to execute safe landings to avoid injuring people on the ground or damaging property. Flight tests were conducted at the City Environment Range for Testing Autonomous Integrated Navigation (CERTAIN) range at NASA Langley. Prior testing of S2D focused on rerouting to an alternate ditch site when an occupant was detected in the primary ditch site. For Steer-to-Clear testing, S2D was limited to a single ditch site option to force engagement of the Steer-to-Clear mode. The implementation of Steer-to-Clear for the flight prototype used a simple method to divide the target ditch site into four quadrants. An RC car was driven in circles in one quadrant to simulate an occupant in that ditch site. A simple implementation of Steer-to- Clear was programmed to land in the opposite quadrant to maximize distance to the occupant’s quadrant. A successful mission was tallied when this occurred. Out of nineteen flights, thirteen resulted in successful missions. Data logs from the flight vehicle and the RC car indicated that unsuccessful missions were due to geolocation error between the actual location of the RC car and the derived location of it by the Vision Assisted Landing component of S2D on the flight vehicle. Video data indicated that while the Vision Assisted Landing component reliably identified the location of the ditch site occupant in the image frame, the conversion of the occupant’s location to earth coordinates was sometimes adversely impacted by errors in sensor data needed to perform the transformation. Logged sensor data was analyzed to attempt to identify the primary error sources and their impact on the geolocation accuracy. Three trends were observed in the data evaluation phase. In one trend, errors in geolocation were relatively large at the flight vehicle’s cruise altitude, but reduced as the vehicle descended. This was the expected behavior and was attributed to sensor errors of the inertial measurement unit (IMU). The second trend showed distinct sinusoidal error for the entire descent that did not always reduce with altitude. The third trend showed high scatter in the data, which did not correlate well with altitude. Possible sources of observed error and compensation techniques are discussed.

Petty, Bryan J.↗

Provably Correct Floating-Point Implementation of a Point-In-Polygon Algorithm

The problem of determining whether or not a point lies inside a given polygon occurs in many applications. In air traffic management concepts, a correct solution to the point-in-polygon problem is critical to geofencing systems for Unmanned Aerial Vehicles and in weather avoidance applications. Many mathematical methods can be used to solve the point-in-polygon problem. Unfortunately, a straightforward floating- point implementation of these methods can lead to incorrect results due to round-off errors. In particular, these errors may cause the control flow of the program to diverge with respect to the ideal real-number algorithm. This divergence potentially results in an incorrect point-in- polygon determination even when the point is far from the edges of the polygon. This paper presents a provably correct implementation of a point-in-polygon method that is based on the computation of the winding number. This implementation is mechanically generated from a source- to-source transformation of the ideal real-number specification of the algorithm. The correctness of this implementation is formally verified within the Frama-C analyzer, where the proof obligations are discharged using the Prototype Verification System (PVS).

Moscato, Mariano M.↗

Search and Rescue under the Forest Canopy using Multiple UAS

We consider the problem of multi-robot search and rescue under the forest canopy. Forest is a particularly challenging environment for collaborative mapping and exploration, mainly due to the existence of severe perceptual aliasing, which hinders reliable mutual localization and map fusion. Our proposed system features unmanned aerial vehicles (UAVs) with onboard sensing and autonomy. Each UAV runs a lightweight filtering algorithm for local state estimation, and a dynamic-aware frontier selection algorithm for fast exploration. The essential and computationally intensive task of collaborative simultaneous localization and mapping (CSLAM) is performed at a central ground station. To handle perceptual aliasing, we make use of stable landmarks extracted from trees, which significantly improve precision and recall during place recognition. Furthermore, to recover from incorrect pairwise data associations during loop closure, we propose a novel procedure for global data association based on recently developed techniques on cycle consistent multiway matching. Our algorithm returns a global data association that is guaranteed to be cycle consistent, and is shown to significantly improve precision compared to the input pairwise associations. The overall multi-UAV system is extensively validated during real-world collaborative exploration missions in a forest at NASA Langley Research Center.

Multi-robot systems↗

Runtime Analysis with R2U2: A Tool Exhibition Report

We present R2U2 (Realizable, Responsive, Unobtrusive Unit), a hardware- supported tool and framework for the continuous monitoring of safetycritical and embedded cyber-physical systems.With the widespread advent of autonomous systems such as Unmanned Aerial Systems (UAS), satellites, rovers, and cars, real-time, on-board decision making requires unobtrusive monitoring of properties for safety, performance, security, and system health. R2U2 models combine past-time and future-time Metric Temporal Logic, “mission time” Linear Temporal Logic, probabilistic reasoning with Bayesian Networks, and modelbased prognostics. The R2U2 monitoring engine can be instantiated as a hardware solution, running on an FPGA, or as a software component. The FPGA realization enables R2U2 to monitor complex cyber-physical systems without any overhead or instrumentation of the flight software. In this tool exhibition report, we present R2U2 and demonstrate applications on system runtime monitoring, diagnostics, software health management, and security monitoring for a UAS. Our tool demonstration uses a hardware-based processor-in-the-loop “iron-bird” configuration.

Johann Martin Schumann↗

Durability Characterization of Low Ice Adhesion and Impact Resistance Coatings

Glaze, rime and mixed icing conditions can cause significant variation in aerodynamic performance, fuel efficiency, and flight safety. For commercial aircraft, active icing mitigation strategies are utilized to enable safe flight within icing conditions according to the FAR Part 25/29 Appendix C icing envelope. For general aviation and unmanned aerial vehicles that cannot support active anti-icing technologies, avoidance is the only recourse. Passive approaches have been investigated to reduce weight and energy consumption for active systems and to expand the operational envelope for smaller aircraft. Coatings are one passive method to reduce or mitigate ice accretion on frontal surfaces of commercial aircraft with the greatest region of interest being wing leading edges. Aircraft wing leading edges represent an extreme environment. Durability must be considered for any material to be applied as a coating in this area. Currently, there are no specifications regarding coating durability of a low ice adhesion material applied on the wing leading edge. Therefore, a reasonable starting point is to use the durability specifications put forth for an aircraft external coating. Besides the tests called out in these specifications, others were included such as Taber abrasion to simulate wear and erosion. Beyond durability, performance metrics with regards to adhesion strength of accreted in-flight (i.e., impact) icing are central to determine coating usefulness. Determination of this property though is particularly challenging and only a few facilities have the capability to quantify this. An instrument at NASA Langley Research Center [Adverse Environment Rotary Test Stand Jr., (AERTS Jr.)], based on the AERTS system at The Pennsylvania State University, allows for screening numerous coatings subjected to the icing environment. To establish a benchmark for comparison with research coatings, a state-of-the-art (SOA) commercial aircraft coating was subjected to an array of salient durability and performance experiments. The same tests were conducted using a baseline epoxy (BE) resin formulation that demonstrated some initial promising results for comparison. Results from this initial screening will be discussed herein.

Miranda L Beaudry↗

TPSAS-NF1676L-13523-DND

Access to the National Airspace System entails policy, architectural and certification challenges for Unmanned Aerial Systems (UAS) as they are being developed. This talk identifies these challenges, builds upon past architectural change successes, and proposes a roadmap to allow small UAS (< 50lb vehicles) to operate in an airspace underlay experiment. The intent is to demonstrate robust operations that can be scaled up to more complex systems and airspace.

Dan Williams↗

TPSAS-NF1676L-14834-DND

A recent spin-off from flight deck adaptive automation research at NASA Langley Research Center is a biocybernetic invention referred to informally as MindShift. When using the MindShift technology, a person is able to play off-the-shelf Nintendo Wii games enhanced with biofeedback, which is used to improve self-regulation of physiological functioning. Therefore, the user experiences the challenge of regulating their physiological responses during gameplay in addition to the intended challenges presented in the video game. The research projects being conducted under the supervision of Dr. Alan Pope and Chad Stephens at NASA Langley Research Center examine the effects of interacting with the MindShift invention technology on subjects' self-regulation of heart rate and brainwave activity, performance in the games, performance on cognitive tasks, and subjective experience of effort (i.e., workload). The MindShift invention's effects are being compared to the effects of interacting with the games without the MindShift technology and to the effects of interacting with commercial-off-the-shelf (COTS) brain-computer interface (BCI) technology, specifically the Mattel Mind Flex and the Uncle Milton Star Wars Force Trainer. A 32-channel electroencephalograph system is used to record subjects' brainwave and electrocardiographic activity. The potential for biofeedback game system applications is wide-ranging - from a more engaging form of clinical biofeedback training to a new challenge for avid gamers. Consequently, research needs to be conducted to fully understand the effects that these new games have on a person's physiological and psychological functioning. Biocybernetic technology like MindShift developed from the idea that operators of critical systems such as aerospace systems could hone their stress management and attention skills in biofeedback-augmented leisure activities while off-the-job in order to positively affect their on-the-job performance. This human performance enhancement technology is applicable to skill training on manually controlled critical tasks, such as unmanned aerial vehicle teleoperation, thus enabling the training of cognitive skills to be concurrent with manual skills. Furthermore, this type of technology can apply to medical and clinical uses of biofeedback by serving as an additional form of clinical biofeedback training that may be particularly useful for those with ADHD.

Brittany N Neilson↗

The NASA Applied Sciences Program: Volcanic Ash Observations and Applications

Since 2000, the NASA Applied Sciences Program has been actively transitioning observations and research to operations. Particular success has been achieved in developing applications for NASA Earth Observing Satellite (EOS) sensors, integrated observing systems, and operational models for volcanic ash detection, characterization, and transport. While other observations and applications remain to be developed for the current constellation of NASA EOS sensors and integrated with observing and forecast systems, future requirements and capabilities for volcanic ash observations and applications are also being developed. Many of these are based on technologies currently being tested on NASA aircraft, Unmanned Aerial Systems (UAS) and balloons. All of these efforts and the potential advances that will be realized by integrating them are shared in this presentation.

John J Murray↗

Demonstration of Two Extended Visual Line of Sight Methods for Urban UAV Operations

This report describes two extended visual line of sight (EVLOS) methods developed and utilized during two flight campaigns over the campus of NASA Langley Research Center (LaRC): a chase vehicle method and a radio controlled (RC) pilot handoff method. These campaigns were performed to (a) evaluate small unmanned aerial system (sUAS) flight beyond the visual line of sight (BVLOS) of the ground control station operator and (b) test technologies under development to enable a transition from EVLOS to BVLOS operations. While an autonomous waypoint-based operational approach enabled minimal pilot intervention in both methods, range containment was enforced (a) manually via continual pilot visual monitoring and (b) autonomously via on-board contingency landing autonomy triggerable at the boundary of stay-in geofences. In the thirty-nine flights which utilized the chase vehicle, the pilot followed the sUAS flying a 1.2 km path at 40m altitude over urban streets. In the fifteen flights which utilized pilot handoff, a pilot at one end of a 1.5 km path initiated the flight at 120m altitude over buildings and trees, and at the midway point of the path transferred radio control to a pilot at the other end. In comparison, the chase vehicle method requires less ground crew and simpler avionics, while the pilot handoff method avoids schedule risk arising from street traffic congestion but better replicates actual direct routing for BVLOS flights. Collision risk with another aircraft was introduced in both campaigns and mitigated with the same manual and autonomous methods. Results from these campaigns serve as a basis for planned BVLOS operations at NASA LaRC.

Nicholas Rymer↗

Risk Assessment of Obstacle Collision for UAVs under off-nominal conditions

Enabling operations of unmanned aerial vehicles (UAVs) in low-altitude airspace, demands the need of robust risk monitoring framework for assessing the safety of airspace, ground-structures and people. As widespread applications emerge, the need of risk assessment becomes increasingly important for UAV flights beyond visual line-of-sight, especially subjected to off-nominal conditions introduced by component failures, degraded controllability or environmental disturbances such as wind gusts in an urban canyon. From a safety perspective, collision with obstacles can be detrimental not only to the vehicle and payload, but also to the structure and people on ground. Although it is safe to assume that approved UAVs would be equipped with collision avoidance systems, risk of collision which can be predicted for a flight trajectory even before the UAV encounters any obstacle is beneficial to resolve contingencies in its decision-making under off-nominal conditions. In this paper, a framework is presented for computing the risk of collision with obstacle based on a UAV's predicted trajectory, proximity to static and dynamic obstacles, sub-system state-of-health and external wind conditions. The conditional probability of trajectory deviation is generated using a Bayesian Belief Network (BBN) based on on-board sensor measurements. Further, a kinematic 3-DOF model is implemented to compute deviation in UAV's trajectory subjected to one case study of off-nominal condition i.e. wind gusts. Finally, the integrated risk factor is demonstrated on real data from experimental flights of an octocopter at NASA Langley Research Center, in presence of simulated obstacles and wind conditions. The proposed approach would enable risk-informed decision making process for timely mitigation of current and future unsafe events.

Portia Banerjee↗

Fire Front Detection and Tracking for Autonomous sUAS in STEReO

The Scalable Traffic Management Emergency Response Operations (STEReO) project aims to incorporate unmanned aerial systems (UAS) into wildfire incident response to safely quicken response times, improve operator awareness, and scale-up aircraft operations.Autonomous UAS can be used to relieve human operators of dull, dirty, and dangerous tasks such as checking for re-ignitions and geo-locating fires. To geo-locate fires, the UAS must be able to detect whether a fire is present and also have the necessary information to stamp a location. Furthermore, the UAS should be able to track the fire front to determine the extent of the fire. This study presents a fire front detection and tracking methodology for an autonomous small UAS (sUAS). The methodology is evaluated in simulation.

Autonomous UAV,Wildfire,Detection,Tracking↗

A Distributed Simulation-to-Flight Framework to Support Investigating Trust/Trustworthiness in Multi-Agent Systems

As autonomous systems continue to grow both in use and complexity, the necessity for robust and extensible simulation-to-flight frameworks is paramount for establishing an effective architecture for autonomous systems. Hardware test flights are time-consuming and cost prohibitive during early system design and development. Simulation environments can be useful tools to accelerate algorithm development and testing. However, transitions from simulation to flight (sim-to-flight) can be challenging, unless systems are designed with this transition in mind and with the necessary capabilities built into the architecture and framework. One of the objectives of Autonomy Teaming and TRAjectories for Complex Trusted Operational Reliability (ATTRACTOR) was to design and develop a distributed mixed-reality simulation environment to begin establishing a basis for certification of autonomous systems via research into trust and trustworthiness. ATTRACTOR’s objective was to construct computational concepts of trustworthiness and justifiable trust in multi-agent autonomous teams, to inform future certification of safety-critical and time-critical autonomous systems in aviation. In this paper, we present an autonomous systems architecture and development framework paired with a persistent distributed modeling and simulation (ModSim) environment for test and evaluation of autonomous systems. They were designed under ATTRACTOR in order to measure and establish trustworthiness and trust in single-and multi-agent human-machine systems whether these machines are fixed-wing general aviation, rotary-wing Unmanned Aerial Vehicles (UAVs), ground rovers, or even spacecraft. The Autonomous Entity Operational Network (AEON) framework enables autonomous system development with an easily extensible collection of libraries and plug-n-play nodes facilitated by the Data Distribution Service (DDS) communication protocol standard. The Baseline Environment for Autonomous Modeling (BEAM) simulation environment is a distributed mixed-reality Unity™-based environment built around the same DDS communication paradigm allowing for easy integration with AEON-based autonomous applications, enabling sim-to-flight with minimal configuration changes. Using AEON and BEAM, source code that runs in simulation ports directly to hardware and has successfully flown in the National Airspace System (NAS) at NASA LaRC many times over the lifetime of ATTRACTOR.

Benjamin N Kelley↗