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Found 955 dataset(s) matching "ames".
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In summary, this paper lays a simple flight plan optimization strategy based on the particle filtering framework described in [5]. This is meant as a first step in formalizing computationally...
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We report here on first steps towards integrating systems health monitoring with adaptive contingency controls. In the scenario considered, the adaptive controller receives specific information...
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We detail all of the facets of adapting classical model checking to a real aerospace system, in- cluding deriving the formal model and a set of specifications from natural language descriptions....
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The work described herein is aimed to advance prognostic health management solutions for electro-mechanical actuators and, thus, increase their reliability and attractiveness to designers of the...
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In this paper we have focused on fundamental processes that are important for understanding the electrical properties of materials, both single crystal minerals and igneous rocks, both...
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The sample scenarios provided here are competition scenarios from previous DXC competitions. They are identical to the competition data associated with previous years' projects, but also listed...
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This is the DXC Framework for Windows Operating Systems
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We believe our approach to gathering and organizing prognostics V&V information from relevant literature, and then applying it to our specific prognostics application, provides a novel...
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Distributed prognostics architecture design is an enabling step for efficient implementation of health management systems. A major challenge encountered in such design is formulation of optimal...
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Particle filters (PF) have been established as the de facto state of the art in failure prognosis, and particularly in the representation and management of uncertainty in long-term predictions...
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In this paper, a maximum entropy-based general framework for probabilistic fatigue damage prognosis is investigated. The proposed methodology is based on an underlying physics-based crack growth...
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Prognostics and health management (PHM) is a maturing system engineering discipline. As with most maturing disciplines, PHM does not yet have a universally accepted research methodology. As a...
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To advance the field of electronics prognostics, the study of transistor fault modes and their precursors is essential. This paper reports on a platform for the aging, characterization, and...
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In situations where the cost/benefit analysis of using physics-based damage propagation algorithms is not favorable and when sufficient test data are available that map out the damage space, one...
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Uncertainty management has always been the key hurdle faced by diagnostics and prognostics algorithms. A Bayesian treatment of this problem provides an elegant and theoretically sound approach to...
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A prognostic system makes it possible to anticipate loss of functionality before it occurs with sufficient lead time to take actions that mitigate the impact of this loss. We focus on the forms of...
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The application of the Bayesian theory of managing uncertainty and complexity to regression and classification in the form of Relevance Vector Machine (RVM), and to state estimation via Particle...
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This invention develops a mathematical model to describe battery behavior during individual discharge cycles as well as over its cycle life. The basis for the form of the model has been linked to...
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One of the key motivating factors for using particle filters for prognostics is the ability to include model parameters as part of the state vector to be estimated. This performs model adaptation...
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Within the area of systems health management, the task of prognostics centers on predicting when components will fail. Model-based prognostics exploits domain knowledge of the system, its...
