Engineering topics
Doyle, Richard
Publications and source records attributed to Doyle, Richard.
Talking Points on Reducing Software Vulnerabilities: Formal Methods
No abstract available
Next Generation Flight Computing: A Joint Investment of NASA and AFRL
No abstract available
Human and Robotic Space Mission Use Cases for High-Performance Spaceflight Computing
Spaceflight computing is a key resource in NASA space missions and a core determining factor of spacecraft capability, with ripple effects throughout the spacecraft, end-to-end system, and the mission; it can be aptly viewed as a "technology multiplier" in that advances in onboard computing provide dramatic improvements in flight functions and capabilities across the NASA mission classes, and will enable new flight capabilities and mission scenarios, increasing science and exploration return per mission-dollar.
Human and Robotic Space Mission Use Cases for High-Performance Spaceflight Computing
Spaceflight computing is a key resource in NASA space missions and a core determining factor of spacecraft capability, with ripple effects throughout the spacecraft, end-to-end system, and mission. Onboard computing can be aptly viewed as a "technology multiplier" in that advances provide direct dramatic improvements in flight functions and capabilities across the NASA mission classes, and enable new flight capabilities and mission scenarios, increasing science and exploration return. Space-qualified computing technology, however, has not advanced significantly in well over ten years and the current state of the practice fails to meet the near- to mid-term needs of NASA missions. Recognizing this gap, the NASA Game Changing Development Program (GCDP), under the auspices of the NASA Space Technology Mission Directorate, commissioned a study on space-based computing needs, looking out 15-20 years. The study resulted in a recommendation to pursue high-performance spaceflight computing (HPSC) for next-generation missions, and a decision to partner with the Air Force Research Lab (AFRL) in this development.
Human and Robotic Space Mission Use Cases for High-Performance Spaceflight Computing (HPSC)
No abstract available
Next Generation Space Processor (NGSP) High Performance Spaceflight Computing (HPSC) Next Steps at NASA and AFRL
No abstract available
Autonomous Onboard Science Data Analysis for Comet Missions
Coming years will bring several comet rendezvous missions. The Rosetta spacecraft arrives at Comet 67P/Churyumov-Gerasimenko in 2014. Subsequent rendezvous might include a mission such as the proposed Comet Hopper with multiple surface landings, as well as Comet Nucleus Sample Return (CNSR) and Coma Rendezvous and Sample Return (CRSR). These encounters will begin to shed light on a population that, despite several previous flybys, remains mysterious and poorly understood. Scientists still have little direct knowledge of interactions between the nucleus and coma, their variation across different comets or their evolution over time. Activity may change on short timescales so it is challenging to characterize with scripted data acquisition. Here we investigate automatic onboard image analysis that could act faster than round-trip light time to capture unexpected outbursts and plume activity. We describe one edge-based method for detect comet nuclei and plumes, and test the approach on an existing catalog of comet images. Finally, we quantify benefits to specific measurement objectives by simulating a basic plume monitoring campaign.
Agile Science Operations: A New Approach for Primitive Exploration Bodies
Primitive body exploration missions such as potential Comet Surface Sample Return or Trojan Tour and Rendezvous would challenge traditional operations practices. Earth-based observations would provide only basic understanding before arrival and many science goals would be defined during the initial rendezvous. It could be necessary to revise trajectories and observation plans to quickly characterize the target for safe, effective observations. Detection of outgassing activity and monitoring of comet surface activity are even more time constrained, with events occurring faster than round-trip light time. "Agile science operations" address these challenges with contingency plans that recognize the intrinsic uncertainty in the operating environment and science objectives. Planning for multiple alternatives can significantly improve the time required to repair and validate spacecraft command sequences. When appropriate, time-critical decisions can be automated and shifted to the spacecraft for immediate access to instrument data. Mirrored planning systems on both sides of the light-time gap permit transfer of authority back and forth as needed. We survey relevant science objectives, identifying time bottlenecks and the techniques that could be used to speed missions' reaction to new science data. Finally, we discuss the results of a trade study simulating agile observations during flyby and comet rendezvous scenarios. These experiments quantify instrument coverage of key surface features as a function of planning turnaround time. Careful application of agile operations techniques can play a significant role in realizing the Decadal Survey plan for primitive body exploration
Enhanced Multi-Modal Access to Planetary Exploration
Tomorrow's Interplanetary Network (IPN) will evolve from JPL's Deep-Space Network (DSN) and provide key capabilities to future investigators, such as simplified acquisition of higher-quality science at remote sites and enriched access to these sites. These capabilities could also be used to foster public interest, e.g., by making it possible for students to explore these environments personally, eventually perhaps interacting with a virtual world whose models could be populated by data obtained continuously from the IPN. Our paper looks at JPL's approach to making this evolution happen, starting from improved communications. Evolving space protocols (e.g., today's CCSDS proximity and file-transfer protocols) will provide the underpinning of such communications in the next decades, just as today's rich web was enabled by progress in Internet Protocols starting from the early 1970's (ARPAnet research). A key architectural thrust of this effort is to deploy persistent infrastructure incrementally, using a layered service model, where later higher-layer capabilities (such as adaptive science planning) are enabled by earlier lower-layer services (such as automated routing of object-based messages). In practice, there is also a mind shift needed from an engineering culture raised on point-to-point single-function communications (command uplink, telemetry downlink), to one in which assets are only indirectly accessed, via well-defined interfaces. We are aiming to foster a 'community of access' both among space assets and the humans who control them. This enables appropriate (perhaps eventually optimized) sharing of services and resources to the greater benefit of all participants. We envision such usage to be as automated in the future as using a cell phone is today - with all the steps in creating the real-time link being automated.
Science-driven Spacecraft Autonomy
In this paper we focus on the use of autonomy to enable and enhance scientific goals for spaceborne missions.
Spacecraft Autonomy in the New Millenium
NASA's New Millenium Program (NMP) is designed to dramatically reduce mission costs and enable new and more frequent exploration missons.
Causal Modeling and Event-driven Simulation for Monitoring of Continous Systems
Monitoring of complex continous physical systems has been traditionally accomplished in computer-based process control software by one or both of the following methods: 1) establishing limit checks for sensors and raising an alarm whenever a sensor's value crosses one of these thresholds, and 2) comparing predicted values from a simulation to actual sensor values and flagging discrepancies.
Causal modeling and event-driven simulation for monitoring of continuous systems
We describe extensions to the traditional techniques for anomaly detection, as well as new anomaly detection techniques based on alternate models of what distinguishes normal from abnormal behavior. Some of these techniques are designed to capture anomalies at individual sensors; some detect anomalies across collections of sensors. To assist in reasoning about complex global behaviors, we construct and simulate a causal model of the physical system being monitored. These techniques have been tested on data from the ECLSS of Space Station Freedom (SSF) and are being applied in advanced monitoring prototypes for the SSF External Active Thermal Control System of SSF and the Environmental Emergency and Consumables Management subsystem of the Space Shuttle.
Sensor placement for diagnosability in space-borne systems - A model-based reasoning approach
This paper presents an approach to evaluating sensor placements on the basis of how well they are able to discriminate between a given fault and normal operating modes and/or other fault modes. In this approach, a model of the system in both normal operations and fault modes is used to evaluate possible sensor placements upon the basis of three criteria. Discriminability measures how much of a divergence in expected sensor readings the two system modes can be expected to produce. Accuracy measures confidence in the particular model predictions. Timeliness measures how long after the fault occurrence the expected divergence will take place. These three metrics then can be used to form a recommendation for a sensor placement. This paper describes how these measures can be computed and illustrated these methods with a brief example.
A model-based reasoning approach to sensor placement for monitorability
An approach is presented to evaluating sensor placements to maximize monitorability of the target system while minimizing the number of sensors. The approach uses a model of the monitored system to score potential sensor placements on the basis of four monitorability criteria. The scores can then be analyzed to produce a recommended sensor set. An example from our NASA application domain is used to illustrate our model-based approach to sensor placement.