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At least 415 records · Page 23

Blackbird: Object-Oriented Planning, Simulation, and Sequencing Framework Used by Multiple Missions

Every JPL flight mission relies on activity planning and sequence generation software to perform operations. Most such tools in use at JPL and elsewhere use attribute-based schemas or domain-specific languages (DSLs) to define activities. This reliance poses user training, software maintenance, performance, and other challenges. To solve this problem for future missions, a new software called Blackbird was developed which allows engineers to specify behavior in standard Java. The new code base has over an order of magnitude fewer lines of code than other JPL planning software, since no DSL or schema interpreter is needed. The use of Java for defining activities also allows mission adapters to debug their code in an integrated development environment, seamlessly call external libraries, and set up truly multimission models. These efficiency gains have significantly reduced the amount of development effort required to support the software. This paper discusses Blackbird’s design, principles, and use cases.

Lawler, Christopher↗

Flight Deck Surface Trajectory-Based Operations (STBO): A Four-Dimensional Trajectory (4DT) Simulation

Within human factors there is burgeoning interest in the Human-Autonomy Teaming (HAT) concept as away to address the challenges of interacting with complex, increasingly autonomous systems. The HAT concept comes out of an aspiration to interact with increasingly autonomous automation as a team member, rather than simply use automation as a tool. The authors, and others, have proposed core tenets for HAT that include bi-directional communication, automation and system transparency, and advanced coordination between human and automated teammates via predefined, dynamic task sequences known as plays (Shively et al., 2017). It is believed that, with proper implementation, HAT should foster appropriate teamwork, thus increasing trust and reliance on the system, which in turn will reduce workload, increase situation awareness, and improve performance. To this end, HAT has been demonstrated and/or studied in multiple applications including search and rescue operations (Nourbakhsh et al., 2005), healthcare and medicine (Tsui Yanco, 2007), autonomous vehicles (Parasuraman, Barnes, Cosenzo, Mulgund, 2007), photography (Lachter, Brandt, Sadler, Shively, in press), and aviation (Shively et al., in press). The current paper presents one such effort to apply HAT. It details the design of a R-HAT Agent developed as part of a NASA Research Agreement awarded to Human-Autonomy Teaming Solutions Inc. (HATS Inc), and developed in collaboration with the Human-Autonomy Teaming Laboratory at NASA Ames Research Center. The role of this Agent is to mediate interaction between the automation and the human operator of an advanced ground dispatch station, with this mediation based upon previously mentioned core tenets for HAT and the many lessons learned from the HAT research literature. This dispatch station was developed to support a NASA project investigating a concept called Reduced Crew Operations (RCO; Lachter, Brandt, Battiste, Matessa, Johnson, in press). Part of the RCO concept involves a ground operator providing enhanced support to a large number of aircraft with a single pilot on the flight deck. When assisted by the Agent, operators can monitor and support or manage a large number of aircraft and use plays to respond in real-time to complicated, workload-intensive events (e.g., an airport closure). A play is a plan that encapsulates goals, tasks, and a task allocation strategy appropriate for a particular situation. In the current implementation, when a play is initiated by a user, the Agent determines what tasks need to be done and has the ability to autonomously execute them (e.g., determining diversion options and uplinking new routes to aircraft) when it is safe and appropriate. The R-HAT Agent has been designed to both support end users and research in RCO and HAT. Additionally, the Agent and its underlying architecture were developed with generalizability in mind as a modular piece of software applicable outside of RCO aviation in domains such as those mentioned above. This paper will also discuss future further development and testing of the R-HAT Agent.

Bakowski, Deborah L.↗

Multitemporal and Multiscaled Fractal Analysis of Landsat Satellite Data Using the Image Characterization and Modeling System (ICAMS)

The Image Characterization And Modeling System (ICAMS) is a public domain software package that is designed to provide scientists with innovative spatial analytical tools to visualize, measure, and characterize landscape patterns so that environmental conditions or processes can be assessed and monitored more effectively. In this study ICAMS has been used to evaluate how changes in fractal dimension, as a landscape characterization index, and resolution, are related to differences in Landsat images collected at different dates for the same area. Landsat Thematic Mapper (TM) data obtained in May and August 1993 over a portion of the Great Basin Desert in eastern Nevada were used for analysis. These data represent contrasting periods of peak "green-up" and "dry-down" for the study area. The TM data sets were converted into Normalized Difference Vegetation Index (NDVI) images to expedite analysis of differences in fractal dimension between the two dates. These NDVI images were also resampled to resolutions of 60, 120, 240, 480, and 960 meters from the original 30 meter pixel size, to permit an assessment of how fractal dimension varies with spatial resolution. Tests of fractal dimension for two dates at various pixel resolutions show that the D values in the August image become increasingly more complex as pixel size increases to 480 meters. The D values in the May image show an even more complex relationship to pixel size than that expressed in the August image. Fractal dimension for a difference image computed for the May and August dates increase with pixel size up to a resolution of 120 meters, and then decline with increasing pixel size. This means that the greatest complexity in the difference images occur around a resolution of 120 meters, which is analogous to the operational domain of changes in vegetation and snow cover that constitute differences between the two dates.

Quattrochi, Dale A.↗

Active control of a flexible structure using a modal positive position feedback controller

The feasibility of a new Modal Positive Position Feedback (MPPF) strategy in controlling the vibration of a complex flexible structure using a single piezo-electric active structural member is demonstrated. The control strategy generates its control forces by manipulating only the modal position signals of the structure to provide a damping action to undamped modes. This is in contrast to conventional modal controllers that rely in their operation on negative feedback of both the modal position and velocity. The proposed strategy is very simple to design and implement as it designs the controller at the uncoupled modal level and utilizes simple first order filters to achieve the Positive Position Feedback effect. The performance of the new strategy is enhanced by augmenting it with a time sharing strategy to share a small number of actuators between larger number of modes. The effectiveness of the new strategy is validated experimentally on a flexible box-type structure that has four bays and its first two bending modes are 2.015 and 6.535 Hz respectively. A single piezo-electric actuator is utilized as an active structural member to control several transverse bending modes of the structure. The performance of the active control system is determined in the time and the frequency domains. The results are compared with those obtained when using the Independent Modal Space Control (IMSC) of Meirovitch. The experimental results suggest the potential of the proposed strategy as a viable means for controlling the vibration of large flexible structures in real time.

Poh, S.↗

Active control of a flexible structure using a modal positive position feedback controller

The feasibility of a new Modal Positive Position Feedback (MPPF) strategy in controlling the vibration of a complex flexible structure using a single piezo-electric active structural member is demonstrated. The control strategy generates its control forces by manipulating only the modal position signals of the structure to provide a damping action to undamped modes. This is in contrast to conventional modal controllers that rely in their operation on negative feedback of both the modal position and velocity. The proposed strategy is very simple to design and implement as it designs the controller at the uncoupled modal level and utilizes simple first order filters to achieve the Positive Position Feedback effect. The performance of the new strategy is enhanced by augmenting it with a time sharing strategy to share a small number of actuators between larger number of modes. The effectiveness of the new strategy is validated experimentally on a flexible box-type structure that has four bays and its first two bending modes are 2.015 and 6.535 Hz, respectively. A single piezo-electric actuator is utilized as an active structural member to control several transverse bending modes of the structure. The performance of the active control system is determined in the time and the frequency domains. The results are compared with those obtained when using the Independent Modal Space Control (IMSC) of Meirovitch. The experimental results suggest the potential of the proposed strategy as a viable means for controlling the vibration of large flexible structures in real time.

Poh, S.↗

Deep Learning Method for Detecting Precursors to Adverse Events

With the recent advancements in Deep Learning methods, the ability to model large complex heterogeneous data sets are fundamentally changing industry and research. Coupled with hardware improvements, and ease of implementation, a wide variety of deep neural network architectures can quickly be developed to solve a sweeping range of problems such as: object detection in images, automatic healthcare diagnosis using heterogenous data sources, real time language translating and sentence prediction, upscaling low resolution images, and forecasting of multivariate timeseries. Generally, many of these architectures outperform classical machine learning approaches in their respective tasks, however, this typically comes at a cost of interpretability. These black box algorithms generally suffer from lack of transparency in both model complexity as well as the rationale behind the prediction. This lack of comprehension, is driving an emerging area of interest in “Explainable AI”. An algorithm called: “Deep Temporal Multiple Instance Learning”1 was a recently developed to identify precursors to adverse events and has been applied in the aviation domain. The deep learning architecture is designed to capture the evolution of the probability of the outcome over the time preceding the adverse event using a multiple instance learning approach as illustrated in Figure 1. Precursors are defined when the probability of the event has exceeded a threshold at some point in the timeseries, at which point, a sensitivity analysis is performed to determine contributing factors. The contributing factors are used to explain and define the precursor during the periods where the probability score is high. The identified contributing factors are then presented to subject matter experts to provide objective insights into the leading factors associated with the particular adverse event. The algorithm has been tested on flight data from a commercial airline and has the ability to discover precursors to known adverse events that take the form of safety critical operations, such as unstable approach events on final approach. Apart from detecting precursors to adverse events, the converse can also be leveraged to discover corrective actions. These positive actions manifest themselves as periods in the timeseries when the precursor score has been lowered from an elevated state; meaning that if the system had been left uncorrected, it would have eventually reached the adverse event state. Characterizing these state changes can help identify successful interventions that may not have been known before. Policy makers and procedure designers can use this additional knowledge to craft more safety and efficient resilient procedures for future operations and therefore improve the overall performance of the National Airspace.

Matthews, Bryan L.↗

Intelligent Observation Strategies for Geosynchronous Remote Sensing for Natural Hazards

Geosynchronous satellites offer a unique perspective for monitoring environmental factors important to understanding natural hazards and supporting the disasters management life cycle, namely forecast, detection, response, recovery and mitigation. In the NASA decadal survey for Earth science, the GEO-CAPE mission was proposed to address coastal and air pollution events in geosynchronous orbit, complementing similar initiatives in Asia by the South Koreans and by ESA in Europe, thereby covering the northern hemisphere. In addition to analyzing the challenges of identifying instrument capabilities to meet the science requirements, and the implications of hosting the instrument payloads on commercial geosynchronous satellites, the GEO-CAPE mission design team conducted a short study to explore strategies to optimize the science return for the coastal imaging instrument. The study focused on intelligent scheduling strategies that took into account cloud avoidance techniques as well as onboard processing methods to reduce the data storage and transmission loads. This paper expands the findings of that study to address the use of intelligent scheduling techniques and near-real time data product acquisition of both the coastal water and air pollution events. The topics include the use of onboard processing to refine and execute schedules, to detect cloud contamination in observations, and to reduce data handling operations. Analysis of state of the art flight computing capabilities will be presented, along with an assessment of cloud detection algorithms and their performance characteristics. Tools developed to illustrate operational concepts will be described, including their applicability to environmental monitoring domains with an eye to the future. In the geostationary configuration, the payload becomes a networked thing with enough connectivity to exchange data seamlessly with users. This allows the full field of view to be sensed at very high rate under the control of ground infrastructure, resulting in improved efficiencies, accuracy and science benefits. Hence a remote sensing payload and its data may become one of millions of connected objects in the emerging Internet of Things (IoT), and be as easily accessible by a users smart phone as any other smart appliance.

Norton-Thevenin Receptance Coupling (NTRC) as a Payload Analysis Tool

The NASA Engineering and Safety Center (NESC) has funded a study of a new method formulated by NASA Engineers called Norton-Thevenin Receptance Coupling (NTRC) to perform coupled loads analysis (CLA). The problem that NTRC attempts to solve is the dependency of the payload organization to high CLA costs, long schedules, lack of standard capabilities to evaluate multiple configurations and unavailability of loads when needed. NTRC solves the problem by providing a tool that payload developers can use to obtain loads at a fraction of the cost of a CLA at any time that it is required. While NTRC is not intended to replace the formal load cycles performed by the launch vehicle (LV) provider, it will provide the ability to reduce the conservatism in defining preliminary design loads, assess the impact of design changes between formal load cycles, perform trade studies and perform parametric loads analysis where many different design configurations can be evaluated with a minimum amount of data required from the LV provider. NTRC condenses all the necessary information into the launch vehicle to payload/s connection points or boundary degrees of freedom (BD). The launch vehicle model is represented by its impedance at its BDs; its forcing functions are represented by the acceleration at those BDs when the payload is absent and the latter is represented by its impedance at the same BDs. Payload responses are represented by transfer functions of selected response to interface BDs. The methodology has contributed to the Loads and Dynamics discipline advancement and successfully passed Peer Reviews. NTRC is exact in the frequency domain. Time domain replication and accuracy is outstanding. A second phase is envisioned to benchmark the whole set of CLA events for the Agency's most utilized Launch Vehicles, and ready it for operational deployment at NASA.

Kaufman, Daniel↗

The application of artificial intelligence to astronomical scheduling problems

Efficient utilization of expensive space- and ground-based observatories is an important goal for the astronomical community; the cost of modern observing facilities is enormous, and the available observing time is much less than the demand from astronomers around the world. The complexity and variety of scheduling constraints and goals has led several groups to investigate how artificial intelligence (AI) techniques might help solve these kinds of problems. The earliest and most successful of these projects was started at Space Telescope Science Institute in 1987 and has led to the development of the Spike scheduling system to support the scheduling of Hubble Space Telescope (HST). The aim of Spike at STScI is to allocate observations to timescales of days to a week observing all scheduling constraints and maximizing preferences that help ensure that observations are made at optimal times. Spike has been in use operationally for HST since shortly after the observatory was launched in Apr. 1990. Although developed specifically for HST scheduling, Spike was carefully designed to provide a general framework for similar (activity-based) scheduling problems. In particular, the tasks to be scheduled are defined in the system in general terms, and no assumptions about the scheduling timescale are built in. The mechanisms for describing, combining, and propagating temporal and other constraints and preferences are quite general. The success of this approach has been demonstrated by the application of Spike to the scheduling of other satellite observatories: changes to the system are required only in the specific constraints that apply, and not in the framework itself. In particular, the Spike framework is sufficiently flexible to handle both long-term and short-term scheduling, on timescales of years down to minutes or less. This talk will discuss recent progress made in scheduling search techniques, the lessons learned from early HST operations, the application of Spike to other problem domains, and plans for the future evolution of the system.

Johnston, Mark D.↗

Accelerating the Design of Space Vehicles

One of NASA's key goals is to increase the safety and reduce the cost of space transportation. Thus, a key element of NASA's new Integrated Space Transportation Plan is to develop new propulsion, structures, and operations for future generations of reusable launch vehicles (RLVs). As part of this effort to develop the next RLV, the ClCT Program's Computing, Networking, and Information Systems (CNIS) Project is developing and demonstrating collaborative software technologies that use the collective power of the NASA Grid to accelerate spacecraft design. One of these technologies, called AeroDB, automates the execution and monitoring of computational fluid dynamics (CFD) parameter studies on the NASA Grid. About the NASA Grid The NASA Grid, or Information Power Grid,. is being developed to leverage the distributed resources of NASA's many computers. instruments, simulators, and data storage systems. The goal is to use these combined resources to sdve difficult NASA challenges, such as iimulating the entire flight of a space vehicle from ascent to descent.To realize the vision of the NASA Grid, the CNIS Project is developing the software framework and protocols for building domain-specific environments and interfaces, new Grid services based on emerging industry standards, and advanced networking and computing testbeds to support new Grid-based applications such as AeroDB.

Laufenberg, Larry↗

The Arctic Regional Communications Small SATellite (ARCSAT)

Traditional satellite missions are extremely complex and expensive to design, build, test, launch and operate. Consequently many complementary operational, exploration and research satellite missions are being formulated as a growing part of the future space community capabilities using formations of small, distributed, simple to launch and inexpensive highly capable small scale satellites. The Arctic Regional Communications small SATellite (ARCSAT) initiative would launch a Mini-Satellite "Mothership" into Polar or Sun Sync low-earth-orbit (LEO). Once on orbit, the Mothership would perform orbital insertion of four internally stored independently maneuverable nanosatellites, each containing electronically steerable antennas and reconfigurable software-defined radios. Unlike the traditional geostationary larger complex satellite communication systems, this LEO communications system will be comprised of initially a five small satellite formation that can be later incrementally increased in the total number of satellites for additional data coverage. ARCSAT will provide significant enabling capabilities in the Arctic for autonomous voice and data communications relay, Maritime Domain Awareness (MDA), data-extraction from unattended sensors, and terrestrial Search & Rescue (SAR) beacon detection missions throughout the "data starved desert" of the Arctic Region.

Casas, Joseph↗

Kinetic Model Development of the Carbon Vapor Deposition Reactor to Predict Performance Versus Design

To enable complete closure of a Sabatier-based atmosphere revitalization system where oxygen recovery is predicated by carbon dioxide reduction to methane and water, there must be a means of recovering the hydrogen from the byproduct methane. Honeywell’s carbon vapor deposition (CVD) reactor is a potential technology that provides a thermochemical means by which methane decomposes at high temperatures (> 1,000 °C) into hydrogen, solid carbon, and a small percentage of hydrocarbons. This advanced methane pyrolysis reactor utilizes a carbon fiber substrate to capture and immobilize the solid pyrolytic carbon rather than allowing continuation toward undesirable soot. The CVD reactor is a highly dynamic system whose characteristic geometry changes while operating. The reactor model was developed to provide predictive performance assessment capabilities at different operating conditions, geometries, and configurations to aid in technology development. Modeling of the CVD reactor considered the multitude of simultaneous and interdependent physicochemical processes that are entailed, including: (1) the homogeneous gas-phase pyrolysis reactions, (2) the heterogeneous deposition reactions, and (3) the transport of gaseous species in the reactor domains. A 1-D CVD reactor model was developed based on a general packed-bed, axial-dispersion plug flow reactor model with a solid substrate balance to account for carbon deposition. The model includes 59 species and 243 reactions constituting the methane pyrolysis reaction network, carbon deposition, and interconversions of oxygenate species. The reactor model was compared to brassboard test data, where it was shown to be able to capture the pertinent physicochemical phenomena as evidenced by its agreement with short-duration run data (i.e., looking at different temperature and flow rate conditions), as well as trend agreement with the brassboard reactor’s long-duration test data. Recommendations are provided on further model development steps as well as its use cases.

Air Revitalization↗

Human Systems Integration (HSI) Practitioner's Guide

The NASA/SP-2015-3709, Human Systems Integration (HSI) Practitioner's Guide, also known as the "HSIPG," provides a tool for implementing HSI activities within the NASA systems engineering framework. The HSIPG is written to aid the HSI practitioner engaged in a program or project (P/P), and serves as a knowledge base to allow the practitioner to step into an HSI lead or team member role for NASA missions. Additionally, this HSIPG is written to address the role of HSI in the P/P management and systems engineering communities and aid their understanding of the value added by incorporating good HSI practices into their programs and projects. Through helping to build a community of knowledgeable HSI practitioners, this document also hopes to build advocacy across the Agency for establishing strong, consistent HSI policies and practices. Human Systems Integration (HSI) has been successfully adopted (and adapted) by several federal agencies-most notably the U.S. Department of Defense (DoD) and the Nuclear Regulatory Commission (NRC)-as a methodology for reducing system life cycle costs (LCCs). These cost savings manifest themselves due to reductions in required numbers of personnel, the practice of human-centered design, decreased reliance on specialized skills for operations, shortened training time, efficient logistics and maintenance, and fewer safety-related risks and mishaps due to unintended human/system interactions. The HSI process for NASA establishes how cost savings and mission success can be realized through systems engineering. Every program or project has unique attributes. This HSIPG is not intended to provide one-size-fits-all recommendations for HSI implementation. Rather, HSI processes should be tailored to the size, scope, and goals of individual situations. The instructions and processes identified here are best used as a starting point for implementing human-centered system concepts and designs across programs and projects of varying types, including manned and unmanned, human spaceflight, aviation, robotics, and environmental science missions. The practitioner using this guide should have expertise in Systems Engineering or other disciplines involved in producing systems with anticipated human interactions. (See section 1.6 of this guide for further discussion on HSI discipline domains.) The HSIPG provides an "HSI layer" to the NASA Systems Engineering Engine (SEE), detailed in NASA Procedural Requirement (NPR) 7123.1B, NASA Systems Engineering Processes and Requirements, and further explained in NASA/SP-2007-6105, Systems Engineering Handbook (see HSIPG Table 2.2-1, NASA Documents with HSI Content, for specific references and document versions).

Zumbado, Jennifer Rochlis↗

Modeling a Packed Bed Reactor Utilizing the Sabatier Process

A numerical model is being developed using Python which characterizes the conversion and temperature profiles of a packed bed reactor (PBR) that utilizes the Sabatier process; the reaction produces methane and water from carbon dioxide and hydrogen. While the specific kinetics of the Sabatier reaction on the RuAl2O3 catalyst pellets are unknown, an empirical reaction rate equation1 is used for the overall reaction. As this reaction is highly exothermic, proper thermal control is of the utmost importance to ensure maximum conversion and to avoid reactor runaway. It is therefore necessary to determine what wall temperature profile will ensure safe and efficient operation of the reactor. This wall temperature will be maintained by active thermal controls on the outer surface of the reactor. Two cylindrical PBRs are currently being tested experimentally and will be used for validation of the Python model. They are similar in design except one of them is larger and incorporates a preheat loop by feeding the reactant gas through a pipe along the center of the catalyst bed. The further complexity of adding a preheat pipe to the model to mimic the larger reactor is yet to be implemented and validated; preliminary validation is done using the smaller PBR with no reactant preheating. When mapping experimental values of the wall temperature from the smaller PBR into the Python model, a good approximation of the total conversion and temperature profile has been achieved. A separate CFD model incorporates more complex three-dimensional effects by including the solid catalyst pellets within the domain. The goal is to improve the Python model to the point where the results of other reactor geometry can be reasonably predicted relatively quickly when compared to the much more computationally expensive CFD approach. Once a reactor size is narrowed down using the Python approach, CFD will be used to generate a more thorough prediction of the reactors performance.

Reactor↗

STAR-X: Survey and Time-domain Astrophysical Research eXplorer

STAR-X is a MIDEX mission proposed to NASA in December 2021. Comprising an X-ray telescope (XRT) provided by GSFC and MIT, a UV telescope (UVT) provided by the University of Colorado, and a spacecraft (SC) provided by Ball Aerospace, STAR-X is designed to conduct time-domain survey and to respond rapidly to transient events discovered by other observatories such as LIGO, Rubin LSST, Roman WFIRST, and SKA. The key features of the XRT are its excellent PSF (2.5 arc-seconds half-power diameter), large effective area (1,800 cm2 at 1 keV), and large field of view (1 deg2), making it more than an order of magnitude more capable and more sensitive than Chandra and Swift/XRT to conduct survey and to find and study transient sources. The UVT has a 30-cm aperture with 5 filters covering the 160nm to 340nm band, providing simultaneous spectral coverage with the XRT and enabling reverberation mapping of accretion disk geometries around black holes. The SC is highly autonomous and is capable of fast slewing, enabling efficient raster scans and time-domain surveys. In particular, in combination with a state-of-the-art mission operations center at the University of Colorado, the SC can respond to targets of opportunity within 2 hours 90% of the time. With its nearly equatorial low-earth orbit, STAR-X’s telescopes will have low particle background, enabling them to have unprecedented sensitivity for measuring faint diffuse emissions from clusters of galaxies. STAR-X is a timely response to Astro2020’s recommendation for a space-based, sustaining time-domain and multi-messenger program.

William W. Zhang↗

An X-Band Radar Terrain Feature Detection Method for Low-Altitude SVS Operations and Calibration Using LiDAR

To enable safe use of Synthetic Vision Systems at low altitudes, real-time range-to-terrain measurements may be required to ensure the integrity of terrain models stored in the system. This paper reviews and extends previous work describing the application of x-band radar to terrain model integrity monitoring. A method of terrain feature extraction and a transformation of the features to a common reference domain are proposed. Expected error distributions for the extracted features are required to establish appropriate thresholds whereby a consistency-checking function can trigger an alert. A calibration-based approach is presented that can be used to obtain these distributions. To verify the approach, NASA's DC-8 airborne science platform was used to collect data from two mapping sensors. An Airborne Laser Terrain Mapping (ALTM) sensor was installed in the cargo bay of the DC-8. After processing, the ALTM produced a reference terrain model with a vertical accuracy of less than one meter. Also installed was a commercial-off-the-shelf x-band radar in the nose radome of the DC-8. Although primarily designed to measure precipitation, the radar also provides estimates of terrain reflectivity at low altitudes. Using the ALTM data as the reference, errors in features extracted from the radar are estimated. A method to estimate errors in features extracted from the terrain model is also presented.

Young, Steve↗

Performance comparison of token ring protocols for hard-real-time communication

The ability to guarantee the deadlines of synchronous messages while maintaining a good aggregate throughput is an important consideration in the design of distributed real-time systems. In this paper, we study two token ring protocols, the priority driven protocol and the timed token protocol, for their suitability for hard real-time systems. Both these protocols use a token to control access to the transmission medium. In a priority driven protocol, messages are assigned priorities and the protocol ensures that messages are transmitted in the order of their priorities. Timed token protocols do not provide for priority arbitration but ensure that the maximum access delay for a station is bounded. For both protocols, we first derive the schedulability conditions under which the transmission deadlines of a given set of synchronous messages can be guaranteed. Subsequently, we use these schedulability conditions to quantitatively compare the average case behavior of the protocols. This comparison demonstrates that each of the protocols has its domain of superior performance and neither dominates the other for the entire range of operating conditions.

Kamat, Sanjay↗

Human Performance of Novice Schedulers for Complex Spaceflight Operations Timelines

Objective: Investigate the effects on human performance as a function of scheduling task complexity for novice schedulers creating spaceflight timelines. Background: Future astronauts will be expected to self-schedule, yet will not be experts in creating timelines that meet complex constraints inherent to spaceflight operations. Method: Conducted a within-subject experiment to measure scheduling efficiency, effectiveness, workload and situation awareness while varying scheduling task complexity factors, namely number of constraints and types of constraints. Results: Fifteen participants completed various scheduling problems. Performance differences were identified between the independent variables. There was a main effect due to the number of constraints and type of constraint for efficiency, effectiveness, and workload. Significant interactions were observed in situation awareness and workload for certain types of constraints. Results also suggest that a lower number of constraints may be manageable by novice schedulers when compared to scheduling activities without constraints. Conclusion: Results suggest that novice schedulers performance decreases with high number of constraints and future scheduling aids may have to be targeted to type of constraint. Application: Knowledge on the effect of scheduling task complexity will help design scheduling systems that will enable self-scheduling for future astronauts. It will also inform other domains that conduct complex scheduling, such as nursing and manufacturing.

scheduling↗