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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.

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NASA NTRS2007

AIRSAR Web-Based Data Processing

The AIRSAR automated, Web-based data processing and distribution system is an integrated, end-to-end synthetic aperture radar (SAR) processing system. Designed to function under limited resources and rigorous demands, AIRSAR eliminates operational errors and provides for paperless archiving. Also, it provides a yearly tune-up of the processor on flight missions, as well as quality assurance with new radar modes and anomalous data compensation. The software fully integrates a Web-based SAR data-user request subsystem, a data processing system to automatically generate co-registered multi-frequency images from both polarimetric and interferometric data collection modes in 80/40/20 MHz bandwidth, an automated verification quality assurance subsystem, and an automatic data distribution system for use in the remote-sensor community. Features include Survey Automation Processing in which the software can automatically generate a quick-look image from an entire 90-GB SAR raw data 32-MB/s tape overnight without operator intervention. Also, the software allows product ordering and distribution via a Web-based user request system. To make AIRSAR more user friendly, it has been designed to let users search by entering the desired mission flight line (Missions Searching), or to search for any mission flight line by entering the desired latitude and longitude (Map Searching). For precision image automation processing, the software generates the products according to each data processing request stored in the database via a Queue management system. Users are able to have automatic generation of coregistered multi-frequency images as the software generates polarimetric and/or interferometric SAR data processing in ground and/or slant projection according to user processing requests for one of the 12 radar modes.

Chu, Anhua↗

NASA NTRS2007

Soft Real-Time PID Control on a VME Computer

microPID (uPID) is a computer program for real-time proportional + integral + derivative (PID) control of a translation stage in a Fourier-transform ultraviolet spectrometer. microPID implements a PID control loop over a position profile at sampling rate of 8 kHz (sampling period 125microseconds). The software runs in a strippeddown Linux operating system on a VersaModule Eurocard (VME) computer operating in real-time priority queue using an embedded controller, a 16-bit digital-to-analog converter (D/A) board, and a laser-positioning board (LPB). microPID consists of three main parts: (1) VME device-driver routines, (2) software that administers a custom protocol for serial communication with a control computer, and (3) a loop section that obtains the current position from an LPB-driver routine, calculates the ideal position from the profile, and calculates a new voltage command by use of an embedded PID routine all within each sampling period. The voltage command is sent to the D/A board to control the stage. microPID uses special kernel headers to obtain microsecond timing resolution. Inasmuch as microPID implements a single-threaded process and all other processes are disabled, the Linux operating system acts as a soft real-time system.

Karayan, Vahag↗

NASA NTRS2010

Incorporating Active Runway Crossings in Airport Departure Scheduling

A mixed integer linear program is presented for deterministically scheduling departure and ar rival aircraft at airport runways. This method addresses different schemes of managing the departure queuing area by treating it as first-in-first-out queues or as a simple par king area where any available aircraft can take-off ir respective of its relative sequence with others. In addition, this method explicitly considers separation criteria between successive aircraft and also incorporates an optional prioritization scheme using time windows. Multiple objectives pertaining to throughput and system delay are used independently. Results indicate improvement over a basic first-come-first-serve rule in both system delay and throughput. Minimizing system delay results in small deviations from optimal throughput, whereas minimizing throughput results in large deviations in system delay. Enhancements for computational efficiency are also presented in the form of reformulating certain constraints and defining additional inequalities for better bounds.

Gupta, Gautam↗

NASA NTRS2011

Contact Graph Routing

Contact Graph Routing (CGR) is a dynamic routing system that computes routes through a time-varying topology of scheduled communication contacts in a network based on the DTN (Delay-Tolerant Networking) architecture. It is designed to enable dynamic selection of data transmission routes in a space network based on DTN. This dynamic responsiveness in route computation should be significantly more effective and less expensive than static routing, increasing total data return while at the same time reducing mission operations cost and risk. The basic strategy of CGR is to take advantage of the fact that, since flight mission communication operations are planned in detail, the communication routes between any pair of bundle agents in a population of nodes that have all been informed of one another's plans can be inferred from those plans rather than discovered via dialogue (which is impractical over long one-way-light-time space links). Messages that convey this planning information are used to construct contact graphs (time-varying models of network connectivity) from which CGR automatically computes efficient routes for bundles. Automatic route selection increases the flexibility and resilience of the space network, simplifying cross-support and reducing mission management costs. Note that there are no routing tables in Contact Graph Routing. The best route for a bundle destined for a given node may routinely be different from the best route for a different bundle destined for the same node, depending on bundle priority, bundle expiration time, and changes in the current lengths of transmission queues for neighboring nodes; routes must be computed individually for each bundle, from the Bundle Protocol agent's current network connectivity model for the bundle s destination node (the contact graph). Clearly this places a premium on optimizing the implementation of the route computation algorithm. The scalability of CGR to very large networks remains a research topic. The information carried by CGR contact plan messages is useful not only for dynamic route computation, but also for the implementation of rate control, congestion forecasting, transmission episode initiation and termination, timeout interval computation, and retransmission timer suspension and resumption.

Burleigh, Scott C.↗

NASA NTRS2011

Asynchronous Message Service Reference Implementation

This software provides a library of middleware functions with a simple application programming interface, enabling implementation of distributed applications in conformance with the CCSDS AMS (Consultative Committee for Space Data Systems Asynchronous Message Service) specification. The AMS service, and its protocols, implement an architectural concept under which the modules of mission systems may be designed as if they were to operate in isolation, each one producing and consuming mission information without explicit awareness of which other modules are currently operating. Communication relationships among such modules are self-configuring; this tends to minimize complexity in the development and operations of modular data systems. A system built on this model is a society of generally autonomous, inter-operating modules that may fluctuate freely over time in response to changing mission objectives, modules functional upgrades, and recovery from individual module failure. The purpose of AMS, then, is to reduce mission cost and risk by providing standard, reusable infrastructure for the exchange of information among data system modules in a manner that is simple to use, highly automated, flexible, robust, scalable, and efficient. The implementation is designed to spawn multiple threads of AMS functionality under the control of an AMS application program. These threads enable all members of an AMS-based, distributed application to discover one another in real time, subscribe to messages on specific topics, and to publish messages on specific topics. The query/reply (client/server) communication model is also supported. Message exchange is optionally subject to encryption (to support confidentiality) and authorization. Fault tolerance measures in the discovery protocol minimize the likelihood of overall application failure due to any single operational error anywhere in the system. The multi-threaded design simplifies processing while enabling application nodes to operate at high speeds; linked lists protected by mutex semaphores and condition variables are used for efficient, inter-thread communication. Applications may use a variety of transport protocols underlying AMS itself, including TCP (Transmission Control Protocol), UDP (User Datagram Protocol), and message queues.

Burleigh, Scott C.↗

NASA NTRS2012

Multi-Angle Implementation of Atmospheric Correction for MODIS (MAIAC). Part 3: Atmospheric Correction

This paper describes the atmospheric correction (AC) component of the Multi-Angle Implementation of Atmospheric Correction algorithm (MAIAC) which introduces a new way to compute parameters of the Ross-Thick Li-Sparse (RTLS) Bi-directional reflectance distribution function (BRDF), spectral surface albedo and bidirectional reflectance factors (BRF) from satellite measurements obtained by the Moderate Resolution Imaging Spectroradiometer (MODIS). MAIAC uses a time series and spatial analysis for cloud detection, aerosol retrievals and atmospheric correction. It implements a moving window of up to 16 days of MODIS data gridded to 1 km resolution in a selected projection. The RTLS parameters are computed directly by fitting the cloud-free MODIS top of atmosphere (TOA) reflectance data stored in the processing queue. The RTLS retrieval is applied when the land surface is stable or changes slowly. In case of rapid or large magnitude change (as for instance caused by disturbance), MAIAC follows the MODIS operational BRDF/albedo algorithm and uses a scaling approach where the BRDF shape is assumed stable but its magnitude is adjusted based on the latest single measurement. To assess the stability of the surface, MAIAC features a change detection algorithm which analyzes relative change of reflectance in the Red and NIR bands during the accumulation period. To adjust for the reflectance variability with the sun-observer geometry and allow comparison among different days (view geometries), the BRFs are normalized to the fixed view geometry using the RTLS model. An empirical analysis of MODIS data suggests that the RTLS inversion remains robust when the relative change of geometry-normalized reflectance stays below 15%. This first of two papers introduces the algorithm, a second, companion paper illustrates its potential by analyzing MODIS data over a tropical rainforest and assessing errors and uncertainties of MAIAC compared to conventional MODIS products.

Lyapustin, A.↗

NASA NTRS2012

NASA Research on an Integrated Concept for Airport Surface Operations Management

Surface operations at airports in the US are based on tactical operations, where departure aircraft primarily queue up and wait at the departure runways. There have been attempts to address the resulting inefficiencies with both strategic and tactical tools for metering departure aircraft. This presentation gives an overview of Spot And Runway Departure Advisor with Collaborative Decision Making (SARDA-CDM): an integrated strategic and tactical system for improving surface operations by metering departure aircraft. SARDA-CDM is the augmentation of ground and local controller advisories through sharing of flight movement and related operations information between airport operators, flight operators and air traffic control at the airport. The goal is to enhance the efficiency of airport surface operations by exchanging information between air traffic control and airline operators, while minimizing adverse effects on stakeholders and passengers. The presentation motivates the need for departure metering, and provides a brief background on the previous work on SARDA. Then, the concept of operations for SARDA-CDM is described. Then the preliminary results from testing the concept in a real-time automated simulation environment are described. Results indicate benefits such as reduction in taxiing delay and fuel consumption. Further, the preliminary implementation of SARDA-CDM seems robust for two minutes delay in gate push-back times.

Gupta, Gautam↗

NASA NTRS2013

Mobile Thread Task Manager

The Mobile Thread Task Manager (MTTM) is being applied to parallelizing existing flight software to understand the benefits and to develop new techniques and architectural concepts for adapting software to multicore architectures. It allocates and load-balances tasks for a group of threads that migrate across processors to improve cache performance. In order to balance-load across threads, the MTTM augments a basic map-reduce strategy to draw jobs from a global queue. In a multicore processor, memory may be "homed" to the cache of a specific processor and must be accessed from that processor. The MTTB architecture wraps access to data with thread management to move threads to the home processor for that data so that the computation follows the data in an attempt to avoid L2 cache misses. Cache homing is also handled by a memory manager that translates identifiers to processor IDs where the data will be homed (according to rules defined by the user). The user can also specify the number of threads and processors separately, which is important for tuning performance for different patterns of computation and memory access. MTTM efficiently processes tasks in parallel on a multiprocessor computer. It also provides an interface to make it easier to adapt existing software to a multiprocessor environment.

Clement, Bradley J.↗

NASA NTRS2013

Performance Evaluation of Individual Aircraft Based Advisory Concept for Surface Management

Surface operations at airports in the US are based on tactical operations, where departure aircraft primarily queue up and wait at the departure runways. NASA's Spot And Runway Departure Advisor (SARDA) tool was developed to address these inefficiencies through Air Traffic Control Tower advisories. The SARDA system is being updated to include collaborative gate hold, either tactically or strategically. This paper presents the results of the human-in-the-loop evaluation of the tactical gate hold version of SARDA in a 360 degree simulated tower setting. The simulations were conducted for the east side of the Dallas/Fort Worth airport. The new system provides gate hold, ground controller and local controller advisories based on a single scheduler. Simulations were conducted with SARDA on and off, the off case reflecting current day operations with no gate hold. Scenarios based on medium (1.2x current levels) and heavy (1.5x current levels) traffic were explored. Data collected from the simulation was analyzed for runway usage, delay for departures and arrivals, and fuel consumption. Further, Traffic Management Initiatives were introduced for a subset of the aircraft. Results indicated that runway usage did not change with the use of SARDA, i.e., there was no loss in runway throughput as compared to baseline. Taxiing delay was significantly reduced with the use of advisory by 45% in medium scenarios and 60% in heavy. Arrival delay was unaffected by the use of advisory. Total fuel consumption was also reduced by 23% in medium traffic and 33% in heavy. TMI compliance appeared unaffected by the advisory

departure metering↗

NASA NTRS2014

Learning Extended Finite State Machines

We present an active learning algorithm for inferring extended finite state machines (EFSM)s, combining data flow and control behavior. Key to our learning technique is a novel learning model based on so-called tree queries. The learning algorithm uses the tree queries to infer symbolic data constraints on parameters, e.g., sequence numbers, time stamps, identifiers, or even simple arithmetic. We describe sufficient conditions for the properties that the symbolic constraints provided by a tree query in general must have to be usable in our learning model. We have evaluated our algorithm in a black-box scenario, where tree queries are realized through (black-box) testing. Our case studies include connection establishment in TCP and a priority queue from the Java Class Library.

NASA NTRS2016

Performance Evaluation of SARDA: An Individual Aircraft-Based Advisory Concept for Surface Management

Surface operations at airports in the US are based on tactical operations, where departure aircraft primarily queue up and wait at the departure runways. NASAs Spot And Runway Departure Advisor (SARDA) tool was developed to address these inefficiencies through Air Traffic Control Tower advisories. The SARDA system is being updated to include collaborative gate hold, either tactically or strategically. This paper presents the results of the human-in-the-loop evaluation of the tactical gate hold version of SARDA in a 360 degree simulated tower setting. The simulations were conducted for the east side of the Dallas-Fort Worth airport. The new system provides gate hold, ground controller and local controller advisories based on a single scheduler. Simulations were conducted with SARDA on and off, the off case reflecting current day operations with no gate hold. Scenarios based on medium (1.2x current levels) and heavy (1.5x current levels) traffic were explored. Data collected from the simulation was analyzed for runway usage, delay for departures and arrivals, and fuel consumption. Further, Traffic Management Initiatives were introduced for a subset of the aircraft. Results indicated that runway usage did not change with the use of SARDA, i.e., there was no loss in runway throughput as compared to baseline. Taxiing delay was significantly reduced with the use of advisory by 45 in medium scenarios and 60 in heavy. Arrival delay was unaffected by the use of advisory. Total fuel consumption was also reduced by 23 in medium traffic and 33 in heavy. TMI compliance appeared unaffected by the advisory.

Yoon Jung↗

NASA NTRS2016

An Integrated Gate Turnaround Management Concept Leveraging Big Data Analytics for NAS Performance Improvements

"Gate Turnaround" plays a key role in the National Air Space (NAS) gate-to-gate performance by receiving aircraft when they reach their destination airport, and delivering aircraft into the NAS upon departing from the gate and subsequent takeoff. The time spent at the gate in meeting the planned departure time is influenced by many factors and often with considerable uncertainties. Uncertainties such as weather, early or late arrivals, disembarking and boarding passengers, unloading/reloading cargo, aircraft logistics/maintenance services and ground handling, traffic in ramp and movement areas for taxi-in and taxi-out, and departure queue management for takeoff are likely encountered on the daily basis. The Integrated Gate Turnaround Management (IGTM) concept is leveraging relevant historical data to support optimization of the gate operations, which include arrival, at the gate, departure based on constraints (e.g., available gates at the arrival, ground crew and equipment for the gate turnaround, and over capacity demand upon departure), and collaborative decision-making. The IGTM concept provides effective information services and decision tools to the stakeholders, such as airline dispatchers, gate agents, airport operators, ramp controllers, and air traffic control (ATC) traffic managers and ground controllers to mitigate uncertainties arising from both nominal and off-nominal airport gate operations. IGTM will provide NAS stakeholders customized decision making tools through a User Interface (UI) by leveraging historical data (Big Data), net-enabled Air Traffic Management (ATM) live data, and analytics according to dependencies among NAS parameters for the stakeholders to manage and optimize the NAS performance in the gate turnaround domain. The application will give stakeholders predictable results based on the past and current NAS performance according to selected decision trees through the UI. The predictable results are generated based on analysis of the unique airport attributes (e.g., runway, taxiway, terminal, and gate configurations and tenants), and combined statistics from past data and live data based on a specific set of ATM concept-of-operations (ConOps) and operational parameters via systems analysis using an analytic network learning model. The IGTM tool will then bound the uncertainties that arise from nominal and off-nominal operational conditions with direct assessment of the gate turnaround status and the impact of a certain operational decision on the NAS performance, and provide a set of recommended actions to optimize the NAS performance by allowing stakeholders to take mitigation actions to reduce uncertainty and time deviation of planned operational events. An IGTM prototype was developed at NASA Ames Simulation Laboratories (SimLabs) to demonstrate the benefits and applicability of the concept. A data network, using the System Wide Information Management (SWIM)-like messaging application using the ActiveMQ message service, was connected to the simulated data warehouse, scheduled flight plans, a fast-time airport simulator, and a graphic UI. A fast-time simulation was integrated with the data warehouse or Big Data/Analytics (BAI), scheduled flight plans from Aeronautical Operational Control AOC, IGTM Controller, and a UI via a SWIM-like data messaging network using the ActiveMQ message service, illustrated in Figure 1, to demonstrate selected use-cases showing the benefits of the IGTM concept on the NAS performance.

Efficent ATM systems↗

NASA NTRS2016

Development of the NASA MCAT Auxiliary Telescope for Orbital Debris Research

The National Aeronautical and Space Administration (NASA) has recently deployed the Meter Class Autonomous Telescope (MCAT) to Ascension Island. MCAT will provide NASA with a dedicated optical sensor for observations of orbital debris with the goal of statistically sampling the orbital and photometric characteristics of the population from low Earth to Geosynchronous orbits. Additionally, a small auxiliary telescope, co-located with MCAT, is being deployed to augment its observations by providing near-simultaneous photometry and astrometry, as well as offloading low priority targets from MCAT's observing queue. It will also be available to provide observational measurements to the Space Surveillance Network for the United States Air Force.

Frith, James↗

NASA NTRS2016

Architecture for Integrated Medical Model Dynamic Probabilistic Risk Assessment

Probabilistic Risk Assessment (PRA) is a modeling tool used to predict potential outcomes of a complex system based on a statistical understanding of many initiating events. Utilizing a Monte Carlo method, thousands of instances of the model are considered and outcomes are collected. PRA is considered static, utilizing probabilities alone to calculate outcomes. Dynamic Probabilistic Risk Assessment (dPRA) is an advanced concept where modeling predicts the outcomes of a complex system based not only on the probabilities of many initiating events, but also on a progression of dependencies brought about by progressing down a time line. Events are placed in a single time line, adding each event to a queue, as managed by a planner. Progression down the time line is guided by rules, as managed by a scheduler. The recently developed Integrated Medical Model (IMM) summarizes astronaut health as governed by the probabilities of medical events and mitigation strategies. Managing the software architecture process provides a systematic means of creating, documenting, and communicating a software design early in the development process. The software architecture process begins with establishing requirements and the design is then derived from the requirements.

Probability Theory↗

NASA NTRS2016

Comparison of Different Control Schemes for Strategic Departure Metering

Airports and their terminal airspaces are key choke points in the air transportation system causing major delays and adding to pollution. A solution aimed at mitigating these chokepoints integrates the scheduling of runway operations, flight release from the gates and ramp into the airport movement area, and merging with other traffic competing for downstream airspace points. Within this integrated concept, we present a simulation-based analysis of the departure metering process, which delays the release of flights into the airport movement area while balancing two competing objectives: (1) maintaining large enough queues at the airport resources to maximize throughput and (2) absorbing excess delays at the gates or in ramp areas to save on fuel consumption, emissions, noise, and passenger discomfort. Three metering strategies are compared which respectively attempt to control the number of flights that (1) left the gate but did not take off, (2) left the ramp but did not take off, and (3) spent their unimpeded transit time to the runway but did not take off. It was observed that under deterministic and demand uncertainty conditions, the first strategy performed better than the other two strategies in terms of maintaining the runway throughput while transferring a significant average delay of two minutes to the gate. On the other hand, under uncertainties of flight transit time and runway service rate, all the strategies struggled to delay flights at the gate without a significant impact on the runway throughput.

air traffic management↗

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

MESA: Message-Based System Analysis Using Runtime Verification

In this paper, we present a novel approach and framework for run-time verication of large, safety critical messaging systems. This work was motivated by verifying the System Wide Information Management (SWIM) project of the Federal Aviation Administration (FAA). SWIM provides live air traffic, site and weather data streams for the whole National Airspace System (NAS), which can easily amount to several hundred messages per second. Such safety critical systems cannot be instrumented, therefore, verification and monitoring has to happen using a nonintrusive approach, by connecting to a variety of network interfaces. Due to a large number of potential properties to check, the verification framework needs to support efficient formulation of properties with a suitable Domain Specific Language (DSL). Our approach is to utilize a distributed system that is geared towards connectivity and scalability and interface it at the message queue level to a powerful verification engine. We implemented our approach in the tool called MESA: Message-Based System Analysis, which leverages the open source projects RACE (Runtime for Airspace Concept Evaluation) and TraceContract. RACE is a platform for instantiating and running highly concurrent and distributed systems and enables connectivity to SWIM and scalability. TraceContract is a runtime verication tool that allows for checking traces against properties specified in a powerful DSL. We applied our approach to verify a SWIM service against several requirements.We found errors such as duplicate and out-of-order messages.

Message-based System↗

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↗