Search NASA⌕ Search

SEARCH · Search NASA

Results for “federated algorithm”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Data Science and the Knowledge Discovery Adventure

This talk will cover the important steps involved in the data science and knowledge discovery process: • Initial fact gathering (interview domain experts, review reports, articles, state-of-the-art) • Identify the problem (prediction, classification, statistical analysis, etc.) • Survey supporting data sources • Understand the data (numerical, categorical, text, sampling rate, data quality issues, etc.) • Selecting relevant features and sources • Acquire the data (set up agreements with the data stewards, APIs to download, etc.) • Merge data sources (temporal, spatial, common key, other ontologies...) • Feature Engineering (non linear domain knowledge or physics-based relationships) • Build data processing pipeline (may need to tap into data stream, develop parallel processing algorithm, federated learning etc.) • Build model and test (tune hyper-parameters, cross validation.) • Analyze/Validate results (do the results make sense. Does it answer the original question). • Deploy/Publish (Monitor and assess benefits)

Data science↗
NASA NTRSDate not supplied

Coordination between Federated Scheduling and Conflict Resolution in UAM Operations

This work proposes a federated scheduling algorithm and explores two mechanisms for coordinating federated scheduling and conflict resolution functions - two core traffic management functions in urban air mobility operations. A federated scheduling algorithm is first developed, together with data that needs to be shared among schedulers. Two mechanisms for coordinating scheduling and conflict resolution functions are then introduced and studied as conflicts in high-density operations may not be completely resolved by conflict resolution function alone. The first coordination mechanism is constructed based on the arrival scheduler at the destination and another one utilizes the departure scheduler at the origin. Experiments and trade space studies are conducted to compare these two mechanisms using fast-time traffic simulations. Results show that both mechanisms perform well in coordinating scheduling and conflict resolution functions and helping resolve all potential conflicts. Experiments also show that with proper parameter selection, both mechanisms can achieve better efficiency (less delay) while maintaining zero losses of separation.

Federated scheduling↗
NASA NTRS2021

Coordination between Federated Scheduling and Conflict Resolution in UAM Operations

This work proposes a federated scheduling algorithm and explores two mechanisms for coordinating federated scheduling and conflict resolution functions - two core traffic management functions in urban air mobility operations. A federated scheduling algorithm is first developed, together with data that needs to be shared among schedulers. Two mechanisms for coordinating scheduling and conflict resolution functions are then introduced and studied as conflicts in high-density operations may not be completely resolved by conflict resolution function alone. The first coordination mechanism is constructed based on the arrival scheduler at the destination and another one utilizes the departure scheduler at the origin. Experiments and trade space studies are conducted to compare these two mechanisms using fast-time traffic simulations. Results show that both mechanisms perform well in coordinating scheduling and conflict resolution functions and helping resolve all potential conflicts. Experiments also show that with proper parameter selection, both mechanisms can achieve better efficiency (less delay) while maintaining zero losses of separation.

Federated scheduling↗
NASA NTRSDate not supplied

Parametric Study of Federated Conflict Resolution for UAM Operations

This work presents a federated conflict resolution algorithm and its parametric study for UAM operations. A federated speed-control-based conflict resolution algorithm is introduced first, including its rules of the road, data exchange requirement, and critical parameters. Two experiments were set up for the parametric study. The first investigates five parameters: look ahead time, resolution update interval, maximum allowed speed reduction, traffic flow interval, and crossing angle. The second experiment studies the uncertainty of departure time. Metrics associated with safety, efficiency, and conflict resolution effort were measured for each scenario. A Design Of Experiment (DOE) analysis was used to perform the multi-factor analysis for the first experiment. It revealed that the crossing angle and flow interval were the most critical parameters across all three metrics, followed by maximum allowed speed reduction. Look ahead time and resolution update interval were of minor significance to safety and conflict resolution effort, but had little to no effect on efficiency. The analysis of the second experiment showed that, given a flow rate, the fluctuation in departure time was absorbed by the conflict resolution algorithm, which resulted in a relatively small fluctuation in airborne delay.

Urban air mobility↗
NASA NTRSDate not supplied

Parametric Study of Federated Conflict Resolution for UAM Operations using DOE Analysis

This work presents a federated conflict resolution algorithm and its parametric study for UAM operations. A federated speed-control-based conflict resolution algorithm is introduced first, including its rules of the road, data exchange requirement, and critical parameters. Two experiments were set up for the parametric study. The first investigates five parameters: look ahead time, resolution update interval, maximum allowed speed reduction, traffic flow interval, and crossing angle. The second experiment studies the uncertainty of departure time. Metrics associated with safety, efficiency, and conflict resolution effort were measured for each scenario. A Design Of Experiment (DOE) analysis was used to perform the multi-factor analysis for the first experiment. It revealed that the crossing angle and flow interval were the most critical parameters across all three metrics, followed by maximum allowed speed reduction. Look ahead time and resolution update interval were of minor significance to safety and conflict resolution effort, but had little to no effect on efficiency. The analysis of the second experiment showed that, given a flow rate, the fluctuation in departure time was absorbed by the conflict resolution algorithm, which resulted in a relatively small fluctuation in airborne delay.

Urban air mobility↗
NASA NTRS1985

Analysis of estimation algorithms for CDTI and CAS applications

Estimation algorithms for Cockpit Display of Traffic Information (CDTI) and Collision Avoidance System (CAS) applications were analyzed and/or developed. The algorithms are based on actual or projected operational and performance characteristics of an Enhanced TCAS II traffic sensor developed by Bendix and the Federal Aviation Administration. Three algorithm areas are examined and discussed. These are horizontal x and y, range and altitude estimation algorithms. Raw estimation errors are quantified using Monte Carlo simulations developed for each application; the raw errors are then used to infer impacts on the CDTI and CAS applications. Applications of smoothing algorithms to CDTI problems are also discussed briefly. Technical conclusions are summarized based on the analysis of simulation results.

Goka, T.↗
NASA NTRS1982

Flight-Management Algorithm for Fuel-Conservative Descents

Federal Aviation Administration has developed an automated time-based metering form of air traffic control for arrivals into terminal area called local flow management/profile descent (LFM/PD). LFM/PD saves fuel by matching airplane arrival flow to airport acceptance rate through time-control computations and by allowing pilot to descend at his discretion from cruise altitude to metering fix in an idle-thrust, clean configuration (landing gear up, flaps zero, speed brakes retracted).

Knox, C. E.↗
NASA NTRS1986

Algorithm for Fuel-Conservative Airplane Descents

Federal Aviation Administration implementing automated, time-based metering form of air-traffic control (ATC) with profile-descent procedures for arrivals into terminal area. Measures provide fuel savings by matching arrival of airplanes to airport acceptance rate through time-control computations and allowing pilot to descend at his discretion from cruise altitude to designated metering-fix altitude in idle-thrust clean configuration. Airborne descent algorithm developed compatible with time-based metering and profile-descent procedures and designed to improve accuracy of delivering airplane during fuel-efficient descent to metering fix at time designated by the ATC system.

Knox, C. E.↗
NASA NTRS2012

Design and Implementation of a Lunar Communications Satellite and Server for the 2012 SISO Smackdown

Last year, the Simulation Interoperability Standards Organization (SISO) inaugurated the now annual High Level Architecture (HLA) Smackdown at the Spring Simulation Interoperability Workshop (SIW). A primary objective of the Smackdown event is to provide college students with hands-on experience in the High Level Architecture (HLA). The University of Alabama in Huntsville (UAHuntsville) fielded teams in 2011 and 2012. Both the 2011 and 2012 smackdown scenarios were a lunar resupply mission. The 2012 UAHuntsville fielded four federates: a communications network Federate called Lunar Communications and Navigation Satellite Service (LCANServ) for sending and receiving messages, a Lunar Satellite Constellation (LCANSat) to put in place radios needed by the communications network for Line-Of-Sight communication calculations, and 3D graphical displays of the orbiting satellites and a 3D visualization of the lunar surface activities. This paper concentrates on the first two federates by describing the functions, algorithms, the modular FOM, experiences, lessons learned and recommendations for future Smackdown events.

Bulgatz, Dennis↗
NASA NTRS2014

NASA Unmanned Aircraft (UA) Control and Non-Payload Communication (CNPC) System Waveform Trade Studies

Unmanned Aircraft Systems (UAS) represent a new capability that will provide a variety of services in the government (public) and commercial (civil) aviation sectors. The growth of this potential industry has not yet been realized due to the lack of a common understanding of what is required to safely operate UAS in the National Airspace System (NAS). To address this deficiency, NASA has established a project called UAS Integration in the NAS (UAS in the NAS), under the Integrated Systems Research Program (ISRP) of the Aeronautics Research Mission Directorate (ARMD). This project provides an opportunity to transition concepts, technology, algorithms, and knowledge to the Federal Aviation Administration (FAA) and other stakeholders to help them define the requirements, regulations, and issues for routine UAS access to the NAS. The safe, routine, and efficient integration of UAS into the NAS requires new radio frequency (RF) spectrum allocations and a new data communications system which is both secure and scalable with increasing UAS traffic without adversely impacting the Air Traffic Control (ATC) communication system. These data communications, referred to as Control and Non-Payload Communications (CNPC), whose purpose is to exchange information between the unmanned aircraft and the ground control station to ensure safe, reliable, and effective unmanned aircraft flight operation. A Communications Subproject within the UAS in the NAS Project has been established to address issues related to CNPC development, certification and fielding. The focus of the Communications Subproject is on validating and allocating new RF spectrum and data link communications to enable civil UAS integration into the NAS. The goal is to validate secure, robust data links within the allocated frequency spectrum for UAS. A vision, architectural concepts, and seed requirements for the future commercial UAS CNPC system have been developed by RTCA Special Committee 203 (SC-203) in the process of determining formal recommendations to the FAA in its role provided for under the Federal Advisory Committee Act. NASA intends to conduct its research and development in keeping with this vision and associated architectural concepts. The prototype communication systems developed and tested by NASA will be used to validate and update the initial SC-203 requirements in order to provide a foundation for SC-203's Minimum Aviation System Performance Standards (MASPS).

Aircraft Communications↗
NASA NTRS2012

Three Dimensional Computer Graphics Federates for the 2012 Smackdown Simulation

The Simulation Interoperability Standards Organization (SISO) Smackdown is a two-year old annual event held at the 2012 Spring Simulation Interoperability Workshop (SIW). A primary objective of the Smackdown event is to provide college students with hands-on experience in developing distributed simulations using High Level Architecture (HLA). Participating for the second time, the University of Alabama in Huntsville (UAHuntsville) deployed four federates, two federates simulated a communications server and a lunar communications satellite with a radio. The other two federates generated 3D computer graphics displays for the communication satellite constellation and for the surface based lunar resupply mission. Using the Light-Weight Java Graphics Library, the satellite display federate presented a lunar-texture mapped sphere of the moon and four Telemetry Data Relay Satellites (TDRS), which received object attributes from the lunar communications satellite federate to drive their motion. The surface mission display federate was an enhanced version of the federate developed by ForwardSim, Inc. for the 2011 Smackdown simulation. Enhancements included a dead-reckoning algorithm and a visual indication of which communication satellite was in line of sight of Hadley Rille. This paper concentrates on these two federates by describing the functions, algorithms, HLA object attributes received from other federates, development experiences and recommendations for future, participating Smackdown teams.

Fordyce, Crystal↗
NASA NTRS2016

ASTAR Flight Test: Overview and Spacing Results

The purpose of the NASA Langley Airborne Spacing for Terminal Arrival Routes (ASTAR) research aboard the Boeing ecoDemonstrator aircraft was to demonstrate the use of NASA's ASTAR algorithm using contemporary tools of the Federal Aviation Administration's Next Generation Air Transportation System (NEXTGEN). EcoDemonstrator is a Boeing test program which utilizes advanced experimental equipment to accelerate the science of aerospace and environmentally friendly technologies. The ASTAR Flight Test provided a proof-of-concept flight demonstration that exercised an algorithmic-based application in an actual aircraft. The test aircraft conducted Interval Management operations to provide time-based spacing off a target aircraft in non-simulator wind conditions. Work was conducted as a joint effort between NASA and Boeing to integrate ASTAR in a Boeing supplied B787 test aircraft while using a T-38 aircraft as the target. This demonstration was also used to identify operational risks to future flight trials for the NASA Air Traffic Management Technology Demonstration expected in 2017.

Roper, Roy D.↗
NASA NTRS1993

The gust-front detection and wind-shift algorithms for the Terminal Doppler Weather Radar system

The Federal Aviation Administration's (FAA) Terminal Doppler Weather Radar (TDWR) system was primarily designed to address the operational needs of pilots in the avoidance of low-altitude wind shears upon takeoff and landing at airports. One of the primary methods of wind-shear detection for the TDWR system is the gust-front detection algorithm. The algorithm is designed to detect gust fronts that produce a wind-shear hazard and/or sustained wind shifts. It serves the hazard warning function by providing an estimate of the wind-speed gain for aircraft penetrating the gust front. The gust-front detection and wind-shift algorithms together serve a planning function by providing forecasted gust-front locations and estimates of the horizontal wind vector behind the front, respectively. This information is used by air traffic managers to determine arrival and departure runway configurations and aircraft movements to minimize the impact of wind shifts on airport capacity. This paper describes the gust-front detection and wind-shift algorithms to be fielded in the initial TDWR systems. Results of a quantitative performance evaluation using Doppler radar data collected during TDWR operational demonstrations at the Denver, Kansas City, and Orlando airports are presented. The algorithms were found to be operationally useful by the FAA airport controllers and supervisors.

Hermes, Laurie G.↗
NASA NTRSDate not supplied

Using Federated Learning to Overcome Data Gravity in Space

Humans intend to take longer missions to outer space. Understanding the impact that space has on human health is paramount to the success of these missions. Controlled experiments with model organisms are run to infer the impact of space conditions on human health, but the data these experiments generate are too large to transfer to Earth for building models. The same is true for space-relevant data generated on Earth. Ideally, these datasets should be combined to improve statistical power and model accuracy without having to transfer data. Federated learning is such a method which trains an algorithm across decentralized computing systems, each of which has their own local copy of training and testing data. In this research, made possible by NASA@Work, the AI for Life in Space group at NASA demonstrates the use of federated learning to train an ensemble of causality inference models on a combination of data residing on the International Space Station (ISS) and in the cloud. Our work leverages CRISP, a causal inference platform developed during the 2020 Frontier Development Lab’s “Astronaut Health Challenge.” We also leverage the OpenFL federated learning library which was collaboratively developed at Intel and UPenn. We used publicly available data from the NASA Ames Life Sciences Data Archive to identify features in ionizing radiation experiments as causal of changes in cardiac blood velocity. This research demonstrates, for the first time, the possibility of running machine learning algorithms on datasets separated by astronomical distances. In this experiment, all the data were generated in terra, half of which were transferred to the ISS and analyzed on the Spaceborne Computer. In the future, our research will leverage federated learning on data generated in situ on the ISS with data generated terrestrially to predict the impact of spaceflight on mammalian female reproductive capacity.

James Casaletto↗
NASA NTRS2022

Vision-Based Precision Approach and Landing for Advanced Air Mobility

Advanced Air Mobility (AAM) aircraft require perception systems for precision approach and landing systems (PALS) in urban, suburban, rural, and regional environments. The current state-of-the-art methods approved for automated approach and landing will be difficult to utilize in support of AAM operational concepts. However, there are technology and systems from other applications and lower-TRL research that use vision, IR, radar, and GPS methods to provide baseline perception and sensing requirements for AAM aircraft approach and landing. This paper focuses on vision-based PAL to demonstrate a closed-loop baseline controller while adhering to the Federal Aviation Administration requirements and regulations. The coplanar algorithm determines pose estimation, which feeds into an Extended Kalman filter. Combining IMU with vision creates a sensor fusion navigation solution for GPS-denied environments. The state estimate leads to glideslope and localizer error computations, which will be pertinent for designing and deriving guidance laws and control laws for AAM PALS. The IMU and vision navigation solution provides promising simulation results for AAM PALS, and higher fidelity simulations will include computer graphics rendering and feature correspondence.

Evan Kawamura↗
NASA NTRSDate not supplied

Distributed Sensing and Computer Vision Methods for Advanced Air Mobility Approach and Landing

Advanced Air Mobility (AAM) aircraft require precision approach and landing systems (PALS) in several types of environments such as urban, suburban, and rural. It is difficult to implement current state-of-the-art methods approved for automated approach and landing for AAM operations. However, existing technology and systems that use vision, IR, radar, and GPS methods provide baseline perception and sensing requirements for AAM aircraft approach and landing. This paper focuses on vision-based PAL and computer vision feature correspondence methods to demonstrate a baseline navigation system while adhering to the Federal Aviation Administration requirements and regulations. The coplanar algorithm determines pose estimation, which feeds into an Extended Kalman filter that combines IMU with vision to create a sensor fusion navigation solution for GPS-denied environments. The state estimate leads to glideslope and localizer error computations, which will be pertinent for designing and deriving guidance laws and control laws for AAM PALS. The IMU and vision navigation solution provides promising simulation results for AAM PALS. This paper builds on previous work by incorporating high fidelity simulations with computer graphics rendering to demonstrate a distributed sensor network to track an AAM aircraft during approach and landing to compare with the aircraft's onboard navigation solution.

Evan Kawamura↗
NASA NTRS2006

Software for Simulating Air Traffic

Future Air Traffic Management Concepts Evaluation Tool (FACET) is a system of software for performing computational simulations for evaluating advanced concepts of advanced air-traffic management. FACET includes a program that generates a graphical user interface plus programs and databases that implement computational models of weather, airspace, airports, navigation aids, aircraft performance, and aircraft trajectories. Examples of concepts studied by use of FACET include aircraft self-separation for free flight; prediction of air-traffic-controller workload; decision support for direct routing; integration of spacecraft-launch operations into the U.S. national airspace system; and traffic- flow-management using rerouting, metering, and ground delays. Aircraft can be modeled as flying along either flight-plan routes or great-circle routes as they climb, cruise, and descend according to their individual performance models. The FACET software is modular and is written in the Java and C programming languages. The architecture of FACET strikes a balance between flexibility and fidelity; as a consequence, FACET can be used to model systemwide airspace operations over the contiguous U.S., involving as many as 10,000 aircraft, all on a single desktop or laptop computer running any of a variety of operating systems. Two notable applications of FACET include: (1) reroute conformance monitoring algorithms that have been implemented in one of the Federal Aviation Administration s nationally deployed, real-time, operational systems; and (2) the licensing and integration of FACET with the commercially available Flight Explorer, which is an Internet- based, real-time flight-tracking system.

Sridhar, Banavar↗