A novel neural/symbolic hybrid approach to heuristically optimized fuel allocation and automated revision of heuristics in nuclear engineering

FUELCON is an expert system for optimized refueling design in nuclear engineering. This task is crucial for keeping down operating costs at a plant without compromising safety. FUELCON proposes sets of alternative configurations of allocation of fuel assemblies that are each positioned in the planar grid of a horizontal section of a reactor core. Results are simulated, and an expert user can also use FUELCON to revise rulesets and improve on his or her heuristics. The successful completion of FUELCON led this research team into undertaking a panoply of sequel projects, of which we provide a meta-architectural comparative formal discussion. In this paper, we demonstrate a novel adaptive technique that learns the optimal allocation heuristic for the various cores. The algorithm is a hybrid of a fine-grained neural network and symbolic computation components. This hybrid architecture is sensitive enough to learn the particular characteristics of the ‘in-core fuel management problem’ at hand, and is powerful enough to use this information fully to automatically revise heuristics, thus improving upon those provided by a human expert.

A Generic Framework for Describing Study Plans for Networked Universities using Meta-Data

This paper presents a generic framework that can be used to describe study plans using meta-data. The context of this research and associated technologies and standards is presented. The approach adopted here has been developed within the mENU project that aims to provide a model for a European Networked University. The methodology for the design of the generic Framework is discussed and the main design requirements are presented. The approach adopted was based on a set of templates containing meta-data required for the description of programs of study and consisting of generic building elements annotated appropriately. The process followed to develop the templates is presented together with a set of evaluation criteria to test the suitability of the approach. The templates structure is presented and example templates are shown. A first evaluation of the approach has shown that the proposed framework can provide a flexible and competent means for the generic description of study plans for the purposes of a networked university.

Ontological considerations of time, meta-predicates and temporal propositions

A natural approach to representing and reasoning about temporal propositions (i.e., statements with time-dependent truth-values) is to associate them with time elements. In the literature, there are three choices regarding the primitive for the ontology of time: (1) instantaneous points, (2) durative intervals and (3) both points and intervals. Problems may arise when one conflates different views of temporal structure and questions whether some certain types of temporal propositions can be validly and meaningfully associated with different time elements. In this paper, we shall summarize an ontological glossary with respect to time elements, and diversify a wider range of meta-predicates for ascribing temporal propositions to time elements. Based on these, we shall also devise a versatile categorization of temporal propositions, which can subsume those representative categories proposed in the literature, including that of Vendler, of McDermott, of Allen, of Shoham, of Galton and of Terenziani and Torasso. It is demonstrated that the new categorization of propositions, together with the proposed range of meta-predicates, provides the expressive power for modeling some typical temporal terms/phenomena, such as starting-instant, stopping-instant, dividing-instant, instigation, termination and intermingling etc.