Complex engineered systems evolve, with a tendency toward self-organization, which can, paradoxically, frustrate the aims of those seeking to develop them. The systems engineer, seeking to promote the development in the context of changing and uncertain requirements, is challenged by conceptual gaps that emerge within engineering projects, particularly as they scale up, that inhibit communication among the various stakeholders. Overall optimization, involving multiple criterion, is often expressed in the language of the individual parties, increasing the complexity of the overall situation, subsuming the participants within the evolution of the complex engineered system, conflating the objective and subjective in counter productive or inefficient ways that can arrest healthy development. The conventional pragmatic systems engineering approach to the resolution of such situations is to introduce architectural discipline by way of separation of concerns. In complex engineered systems projects, the crucial interface, at any level of abstraction, is between the technical domain experts and higher level decision makers. Bridging the ensuing conceptual gap requires models and methods that provide communication tools promoting a convergence of the conversation between these parties on a common "common sense" of the underlying reality of the evolving engineered system. In the interest of conceptual clarity, we confine our investigation to a restricted, but important general class of evolving engineered system, information gathering and utilizing systems. Such systems naturally resolve the underlying domain specific measures by reduction into common plausible information measures aimed at an overall sense of informativeness. For concreteness, we further restrict the investigation and the demonstration to a species that is well documented in the open literature: weather radar networks, and in particular to the case of the currently emerging system referred to as CASA. The multiobjective problem of objectively exploring the high dimensionality of the decision space is done using multiobjective genetic algorithms (MOGA), specifically the John Eddy genetic algorithms (JEGA), resulting in well formed Pareto fronts and sets containing Pareto optimal points within 20% of the ideal point. A visualization technique ensures a clear separation of the subjective criterion provided by the decision makers by superficially adding preferences to the objective optimal solutions. To identify the integrative objective functions and test patterns utilized in the MOGA analysis, explorations of networked weather radar technologies and configuration are completed. The explorations identify trends within and between network topologies, and captures both the robustness and fragility of network based measurements. The information oriented measures of fusion accuracy and precision are used to evaluate pairs of networked weather radars against a standardized low order vortex test pattern, resulting in a metrics for characterizing the performance of dual-Doppler weather radar pairs. To define integrative measures, information oriented measures abstracting over sensor estimators and parameters used to estimate the radial velocity and returned signal from distributed targets, specifically precipitation, are shown to capture the single radar predicted performance against standardized test patterns. The methodology bridges the conceptual gap, based on plausible information oriented measures, standardized with test patterns, and objectively applied to a concrete case with high dimensionality, allowed the conversation to converge between the systems engineer, decision makers, and domain experts. The method is an informative objective process that can be generalized to enable expansion within the technology and to other information gathering and utilizing systems and sensor technologies.
| Identifer | oai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:dissertations-6303 |
| Date | 01 January 2011 |
| Creators | Hopf, Anthony P |
| Publisher | ScholarWorks@UMass Amherst |
| Source Sets | University of Massachusetts, Amherst |
| Language | English |
| Detected Language | English |
| Type | text |
| Source | Doctoral Dissertations Available from Proquest |
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