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Clancy, Daniel

Publications and source records attributed to Clancy, Daniel.

At least 37 records · Page 2

Simulating "Mars on Earth"

By now, everyone who's heard of the Haughton-Mars Project knows that we travel to Devon Island to learn how people will live and work on Mars. But how do we learn about Mars operations from what happens in the Arctic? We must document our experience--traverses, life in the hab, instrument deployment, communications, and so on. Then we must analyze and formally model what happens. In short, while most scientists are studying the crater, other scientists must be studying the expedition itself. That's what I have done in the past four field seasons. I study field science, both as it naturally occurs at Haughton (unconstrained by a "Mars Sam") and as a constrained experiment using the Flashline Mars Arctic Research Station. During the second week of July 2001, I lived and worked in the hab as part of the Phase 2 crew of six. Besides participating in all activities, I took many photographs and time lapse video. The result of my work will be a computer simulation of how we lived and worked in the hab. It won't be a model of particular people or even my own phase per se, but a pastiche that demonstrates (a proof of concept) that we have appropriate tools for simulating the layout of the hab and daily routines followed by the group and individual scientists. Activities-how people spend their time-are the focus of my observations for building such a simulation model.

Clancey, William J.

Gyro-based Maximum-Likelihood Thruster Fault Detection and Identification

When building smaller, less expensive spacecraft, there is a need for intelligent fault tolerance vs. increased hardware redundancy. If fault tolerance can be achieved using existing navigation sensors, cost and vehicle complexity can be reduced. A maximum likelihood-based approach to thruster fault detection and identification (FDI) for spacecraft is developed here and applied in simulation to the X-38 space vehicle. The system uses only gyro signals to detect and identify hard, abrupt, single and multiple jet on- and off-failures. Faults are detected within one second and identified within one to five accords,

Wilson, Edward

Simulating Activities: Relating Motives, Deliberation and Attentive Coordination

Activities are located behaviors, taking time, conceived as socially meaningful, and usually involving interaction with tools and the environment. In modeling human cognition as a form of problem solving (goal-directed search and operator sequencing), cognitive science researchers have not adequately studied "off-task" activities (e.g., waiting), non-intellectual motives (e.g., hunger), sustaining a goal state (e.g., playful interaction), and coupled perceptual-motor dynamics (e.g., following someone). These aspects of human behavior have been considered in bits and pieces in past research, identified as scripts, human factors, behavior settings, ensemble, flow experience, and situated action. More broadly, activity theory provides a comprehensive framework relating motives, goals, and operations. This paper ties these ideas together, using examples from work life in a Canadian High Arctic research station. The emphasis is on simulating human behavior as it naturally occurs, such that "working" is understood as an aspect of living. The result is a synthesis of previously unrelated analytic perspectives and a broader appreciation of the nature of human cognition. Simulating activities in this comprehensive way is useful for understanding work practice, promoting learning, and designing better tools, including human-robot systems.

Clancey, William J.

Software Construction and Analysis Tools for Future Space Missions

NASA and its international partners will increasingly depend on software-based systems to implement advanced functions for future space missions, such as Martian rovers that autonomously navigate long distances exploring geographic features formed by surface water early in the planet's history. The software-based functions for these missions will need to be robust and highly reliable, raising significant challenges in the context of recent Mars mission failures attributed to software faults. After reviewing these challenges, this paper describes tools that have been developed at NASA Ames that could contribute to meeting these challenges; 1) Program synthesis tools based on automated inference that generate documentation for manual review and annotations for automated certification. 2) Model-checking tools for concurrent object-oriented software that achieve memorability through synergy with program abstraction and static analysis tools.

Lowry, Michael R.

High Resolution Soil Water from Regional Databases and Satellite Images

This viewgraph presentation provides information on the ways in which plant growth can be inferred from satellite data and can then be used to infer soil water. There are several steps in this process, the first of which is the acquisition of data from satellite observations and relevant information databases such as the State Soil Geographic Database (STATSGO). Then probabilistic analysis and inversion with the Bayes' theorem reveals sources of uncertainty. The Markov chain Monte Carlo method is also used.

Morris, Robin D.

New Boundary Constraints for Elliptic Systems used in Grid Generation Problems

This paper discusses new boundary constraints for elliptic partial differential equations as used in grid generation problems in generalized curvilinear coordinate systems. These constraints, based on the principle of local conservation of thermal energy in the vicinity of the boundaries, are derived using the Green's Theorem. They uniquely determine the so called decay parameters in the source terms of these elliptic systems. These constraints' are designed for boundary clustered grids where large gradients in physical quantities need to be resolved adequately. It is observed that the present formulation also works satisfactorily for mild clustering. Therefore, a closure for the decay parameter specification for elliptic grid generation problems has been provided resulting in a fully automated elliptic grid generation technique. Thus, there is no need for a parametric study of these decay parameters since the new constraints fix them uniquely. It is also shown that for Neumann type boundary conditions, these boundary constraints uniquely determine the solution to the internal elliptic problem thus eliminating the non-uniqueness of the solution of an internal Neumann boundary value grid generation problem.

Kaul, Upender K.

The NASA Integrated Vehicle Health Management Technology Experiment for X-37

The NASA Integrated Vehicle Health Management (IVHM) Technology Experiment for X-37 was intended to run IVHM software on-board the X-37 spacecraft. The X-37 is intended to be an unpiloted vehicle that would orbit the Earth for up to 21 days before landing on a runway. The objectives of the experiment were to demonstrate the benefits of in-flight IVHM to the operation of a Reusable Launch Vehicle, to advance the Technology Readiness Level of this IVHM technology within a flight environment, and to demonstrate that the IVHM software could operate on the Vehicle Management Computer. The scope of the experiment was to perform real-time fault detection and isolation for X-37's electrical power system and electro-mechanical actuators. The experiment used Livingstone, a software system that performs diagnosis using a qualitative, model-based reasoning approach that searches system-wide interactions to detect and isolate failures. Two of the challenges we faced were to make this research software more efficient so that it would fit within the limited computational resources that were available to us on the X-37 spacecraft, and to modify it so that it satisfied the X-37's software safety requirements. Although the experiment is currently unfunded, the development effort had value in that it resulted in major improvements in Livingstone's efficiency and safety. This paper reviews some of the details of the modeling and integration efforts, and some of the lessons that were learned.

Schwabacher, Mark

Synthesizing Monitors for Safety Properties

The problem of testing a linear temporal logic (LTL) formula on a finite execution trace of events, generated by an executing program, occurs naturally in time analysis of software. An algorithm which takes a past time LTL formula and generates an efficient dynamic programming algorithm is presented. The generated algorithm tests whether the formula is satisfied by a finite trace of events given as input and runs in linear time, its constant depending on the size of the LTL formula. The memory needed is constant, also depending on the size of the formula. Further optimizations of the algorithm are suggested. Past time operators suitable for writing succinct specifications axe introduced and shown definitionally equivalent to the standard operators. This work is part of the PathExplorer project, the objective of which it is to construct a flexible framework for monitoring and analyzing program executions.

Havelund, Klaus

Solving and Learning Soft Temporal Constraints: Experimental Setting and Results

Soft temporal constraints problems allow to describe in a natural way scenarios where events happen over time and preferences are associated to event distances and durations. However, sometimes such local preferences are difficult to set, and it may be easier instead to associate preferences to some complete solutions of the problem. Machine learning techniques can be useful in this respect. In this paper we describe two solvers (one more general and the other one more efficient) for tractable subclasses of soft temporal problems, and we show some experimental results. The random generator used to build the problems on which tests are performed is also described. We also compare the two solvers highlighting the tradeoff between performance and representational power. Finally, we present a learning module and we show its behavior on randomly-generated examples.

Rossi, F.

Evolutionary Optimization of a Quadrifilar Helical Antenna

Automated antenna synthesis via evolutionary design has recently garnered much attention in the research literature. Evolutionary algorithms show promise because, among search algorithms, they are able to effectively search large, unknown design spaces. NASA's Mars Odyssey spacecraft is due to reach final Martian orbit insertion in January, 2002. Onboard the spacecraft is a quadrifilar helical antenna that provides telecommunications in the UHF band with landed assets, such as robotic rovers. Each helix is driven by the same signal which is phase-delayed in 90 deg increments. A small ground plane is provided at the base. It is designed to operate in the frequency band of 400-438 MHz. Based on encouraging previous results in automated antenna design using evolutionary search, we wanted to see whether such techniques could improve upon Mars Odyssey antenna design. Specifically, a co-evolutionary genetic algorithm is applied to optimize the gain and size of the quadrifilar helical antenna. The optimization was performed in-situ in the presence of a neighboring spacecraft structure. On the spacecraft, a large aluminum fuel tank is adjacent to the antenna. Since this fuel tank can dramatically affect the antenna's performance, we leave it to the evolutionary process to see if it can exploit the fuel tank's properties advantageously. Optimizing in the presence of surrounding structures would be quite difficult for human antenna designers, and thus the actual antenna was designed for free space (with a small ground plane). In fact, when flying on the spacecraft, surrounding structures that are moveable (e.g., solar panels) may be moved during the mission in order to improve the antenna's performance.

Lohn, Jason D.

What is a Question?

A given question can be defined in terms of the set of statements or assertions that answer it. Application of the logic of inference to this set of assertions allows one to derive the logic of inquiry among questions. There are interesting symmetries between the logics of inference and inquiry; where probability describes the degree to which a premise implies an assertion, there exists an analogous quantity that describes the bearing or relevance that a question has on an outstanding issue. These have been extended to suggest that the logic of inquiry results in functional relationships analogous to, although more general than, those found in information theory. Employing lattice theory, I examine in greater detail the structure of the space of assertions and questions demonstrating that the symmetries between the logical relations in each of the spaces derive directly from the lattice structure. Furthermore, I show that while symmetries between the spaces exist, the two lattices are not isomorphic. The lattice of assertions is described by a Boolean lattice 2(sup N) whereas the lattice of real questions is shown to be a sublattice of the free distributive lattice FD(N) = 2(sup 2(sup N)). Thus there does not exist a one-to-one mapping of assertions to questions, there is no reflection symmetry between the two spaces, and questions in general do not possess unique complements. Last, with these lattice structures in mind, I discuss the relationship between probability, relevance and entropy.

Knuth, Kevin H.

Hierarchies of Models: Toward Understanding Planetary Nebulae

Stars like our sun (initial masses between 0.8 to 8 solar masses) end their lives as swollen red giants surrounded by cool extended atmospheres. The nuclear reactions in their cores create carbon, nitrogen and oxygen, which are transported by convection to the outer envelope of the stellar atmosphere. As the star finally collapses to become a white dwarf, this envelope is expelled from the star to form a planetary nebula (PN) rich in organic molecules. The physics, dynamics, and chemistry of these nebulae are poorly understood and have implications not only for our understanding of the stellar life cycle but also for organic astrochemistry and the creation of prebiotic molecules in interstellar space. We are working toward generating three-dimensional models of planetary nebulae (PNe), which include the size, orientation, shape, expansion rate and mass distribution of the nebula. Such a reconstruction of a PN is a challenging problem for several reasons. First, the data consist of images obtained over time from the Hubble Space Telescope (HST) and spectra obtained from Kitt Peak National Observatory (KPNO) and Cerro Tololo Inter-American Observatory (CTIO). These images are of course taken from a single viewpoint in space, which amounts to a very challenging tomographic reconstruction. Second, the fact that we have two disparate and orthogonal data types requires that we utilize a method that allows these data to be used together to obtain a solution. To address these first two challenges we employ Bayesian model estimation using a parameterized physical model that incorporates much prior information about the known physics of the PN. In our previous works we have found that the forward problem of the comprehensive model is extremely time consuming. To address this challenge, we explore the use of a set of hierarchical models, which allow us to estimate increasingly more detailed sets of model parameters. These hierarchical models of increasing complexity are akin to scientific theories of increasing sophistication, with each new model/theory being a refinement of a previous one by either incorporating additional prior information or by introducing a new set of parameters to model an entirely new phenomenon. We apply these models to both a simulated and a real ellipsoidal PN to initially estimate the position, angular size, and orientation of the nebula as a two-dimensional object and use these estimates to later examine its three-dimensional properties. The efficiency/accuracy tradeoffs of the techniques are studied to determine the advantages and disadvantages of employing a set of hierarchical models over a single comprehensive model.

Knuth, Kevin H.

Failure Mode Identification Through Clustering Analysis

Research has shown that nearly 80% of the costs and problems are created in product development and that cost and quality are essentially designed into products in the conceptual stage. Currently, failure identification procedures (such as FMEA (Failure Modes and Effects Analysis), FMECA (Failure Modes, Effects and Criticality Analysis) and FTA (Fault Tree Analysis)) and design of experiments are being used for quality control and for the detection of potential failure modes during the detail design stage or post-product launch. Though all of these methods have their own advantages, they do not give information as to what are the predominant failures that a designer should focus on while designing a product. This work uses a functional approach to identify failure modes, which hypothesizes that similarities exist between different failure modes based on the functionality of the product/component. In this paper, a statistical clustering procedure is proposed to retrieve information on the set of predominant failures that a function experiences. The various stages of the methodology are illustrated using a hypothetical design example.

Arunajadai, Srikesh G.

Application of Function-Failure Similarity Method to Rotorcraft Component Design

Performance and safety are the top concerns of high-risk aerospace applications at NASA. Eliminating or reducing performance and safety problems can be achieved with a thorough understanding of potential failure modes in the designs that lead to these problems. The majority of techniques use prior knowledge and experience as well as Failure Modes and Effects as methods to determine potential failure modes of aircraft. During the design of aircraft, a general technique is needed to ensure that every potential failure mode is considered, while avoiding spending time on improbable failure modes. In this work, this is accomplished by mapping failure modes to specific components, which are described by their functionality. The failure modes are then linked to the basic functions that are carried within the components of the aircraft. Using this technique, designers can examine the basic functions, and select appropriate analyses to eliminate or design out the potential failure modes. The fundamentals of this method were previously introduced for a simple rotating machine test rig with basic functions that are common to a rotorcraft. In this paper, this technique is applied to the engine and power train of a rotorcraft, using failures and functions obtained from accident reports and engineering drawings.

Roberts, Rory A.

Classification of Aircraft Maneuvers for Fault Detection

Automated fault detection is an increasingly important problem in aircraft maintenance and operation. Standard methods of fault detection assume the availability of either data produced during all possible faulty operation modes or a clearly-defined means to determine whether the data is a reasonable match to known examples of proper operation. In our domain of fault detection in aircraft, the first assumption is unreasonable and the second is difficult to determine. We envision a system for online fault detection in aircraft, one part of which is a classifier that predicts the maneuver being performed by the aircraft as a function of vibration data and other available data. We explain where this subsystem fits into our envisioned fault detection system as well its experiments showing the promise of this classification subsystem.

Oza, Nikunj C.

Molnets: An Artificial Chemistry Based on Neural Networks

The fundamental problem in the evolution of matter is to understand how structure-function relationships are formed and increase in complexity from the molecular level all the way to a genetic system. We have created a system where structure-function relationships arise naturally and without the need of ad hoc function assignments to given structures. The idea was inspired by neural networks, where the structure of the net embodies specific computational properties. In this system networks interact with other networks to create connections between the inputs of one net and the outputs of another. The newly created net then recomputes its own synaptic weights, based on anti-hebbian rules. As a result some connections may be cut, and multiple nets can emerge as products of a 'reaction'. The idea is to study emergent reaction behaviors, based on simple rules that constitute a pseudophysics of the system. These simple rules are parameterized to produce behaviors that emulate chemical reactions. We find that these simple rules show a gradual increase in the size and complexity of molecules. We have been building a virtual artificial chemistry laboratory for discovering interesting reactions and for testing further ideas on the evolution of primitive molecules. Some of these ideas include the potential effect of membranes and selective diffusion according to molecular size.

Colombano, Silvano

Robosphere1: Building A Self-Sustaining Robotic Ecology for Mars Exploration

Robotic exploration of Mars has been a "one shot" approach where each surface mission is planned typically with a rover that will perform a series of experiments for a few weeks or months, until the robot becomes unable to operate in the harsh Mars conditions and simply "dies". It would clearly be desirable to have robots on Mars that can last for much longer periods of time, I propose that there is an approach to sustained robotic exploration that can also pave the way to future human presence. The idea is to continue building a robotic infrastructure with every mission we send. The approach is to built a team of modular robots that could repair individual members when they break down. We could "seed" areas of interest with sturdy power stations (solar, chemical) that teams of robots could use to recharge themselves. We could also seed parts and modules the robots could access for self-repair. No mission could really "fail" if we simply keep adding to and maintaining the existing infrastructure. Simply landing a package of parts will be a success. In time we create a loose infrastructure that can be controlled and augmented from earth on a continuing basis, and which could eventually pave the way for human exploration. I propose that we could begin to build this infrastructure from relatively simple modular robots. Imagine 2 "spider-like" robots built out of small modular snap-in pieces, a bin of these pieces and a bin of snap-in end effectors. One of the spiders breaks down, i.e. one of its modules needs to be replaced. The second spider comes to the rescue and helps the first one replace the broken module. Assuming the input of fresh modules, this process can continue indefinetly. Now start separating robotic explorers from robotic "mechanics", start adding, a category of mechanics that are able to fix at least some of the broken modules (and which in turn can be fixed by the original mechanics), The need for a fresh influx of modules is thus reduced. I submit that we could bootstrap a robotic ecology until it needs very little material from earth and can rely mostly on in-situ resources., We can experiment with this concept in an earthbound facility that can also simulate Mars conditions. I propose that we call this facility Robosphere1.

Colombano, Silvano P.

Decomposition-Based Failure Mode Identification Method for Risk-Free Design of Large Systems

When designing products, it is crucial to assure failure and risk-free operation in the intended operating environment. Failures are typically studied and eliminated as much as possible during the early stages of design. The few failures that go undetected result in unacceptable damage and losses in high-risk applications where public safety is of concern. Published NASA and NTSB accident reports point to a variety of components identified as sources of failures in the reported cases. In previous work, data from these reports were processed and placed in matrix form for all the system components and failure modes encountered, and then manipulated using matrix methods to determine similarities between the different components and failure modes. In this paper, these matrices are represented in the form of a linear combination of failures modes, mathematically formed using Principal Components Analysis (PCA) decomposition. The PCA decomposition results in a low-dimensionality representation of all failure modes and components of interest, represented in a transformed coordinate system. Such a representation opens the way for efficient pattern analysis and prediction of failure modes with highest potential risks on the final product, rather than making decisions based on the large space of component and failure mode data. The mathematics of the proposed method are explained first using a simple example problem. The method is then applied to component failure data gathered from helicopter, accident reports to demonstrate its potential.

Tumer, Irem Y.