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.

Refueling in nuclear engineering: the FUELCON project

Over a time span of almost a decade, the FUELCON project in nuclear engineering has led to a fully functional expert system and spawned sequel projects. Its task is in-core fuel management, also called `refueling', i.e., good fuel-allocation for reloading the core of a given nuclear reactor, for a given operation cycle. The task is crucial for keeping down operation costs at nuclear power plants. Fuel comes in different types and is positioned in a grid representing the core of a reactor. The tool is useful for practitioners but also helps the expert in the domain to test his or her rules of thumb and to discover new ones.

Guest Editorial. Special Issue: Temporal logic in engineering

Logic-based models are thriving within artificial intelligence. A great number of new logics have been defined, and their theory investigated. Epistemic logics introduce modal operators for knowledge or belief; deontic logics are about norms, and introduce operators of deontic necessity and possibility (i.e., obligation or prohibition). And then we have a much investigated class—temporal logics—to whose application to engineering this special issue is devoted. This kind of formalism deserves increased widespread recognition and application in engineering, a domain where other kinds of temporal models (e.g., Petri nets) are by now a fairly standard part of the modelling toolbox.

The integration of an intelligent knowledge-based system into engineering software using the blackboard structure

Over recent years there has been an increase in the use of generic Computational Fluid Dynamics (CFD) software packages spread across various application fields. This has created the need for the integration of expertise into CFD software. Expertise can be integrated into CFD software in the form of an Intelligent Knowledge-Based System (IKBS). The advantages of integrating intelligence into generic engineering software are discussed with a special view to software engineering considerations. The software modelling cycle of a typical engineering problem is identified and the respective expertise and user control needed for each modelling phase is shown. The requirements of an IKBS for CFD software are discussed and compared to current practice. The blackboard software architecture is presented. This is shown to be appropriate for the integration of an IKBS into an engineering software package. This is demonstrated through the presentation of the prototype CFD software package FLOWES.

Utilising computational fluid dynamics (CFD) for the modelling of granular material in large-scale engineering processes

In this paper, the framework is described for the modelling of granular material by employing Computational Fluid Dynamics (CFD). This is achieved through the use and implementation in the continuum theory of constitutive relations, which are derived in a granular dynamics framework and parametrise particle interactions that occur at the micro-scale level. The simulation of a process often met in bulk solids handling industrial plants involving granular matter, (i.e. filling of a flat-bottomed bin with a binary material mixture through pneumatic conveying-emptying of the bin in core flow mode-pneumatic conveying of the material coming out of a the bin) is presented. The results of the presented simulation demonstrate the capability of the numerical model to represent successfully key granular processes (i.e. segregation/degradation), the prediction of which is of great importance in the process engineering industry.

Fire safety engineering and ship design using advanced fire and evacuation simulation

When designing a new passenger ship or modifying an existing design, how do we ensure that the proposed design and crew emergency procedures are safe from an evacuation resulting from fire or other incident? In the wake of major maritime disasters such as the Scandinavian Star, Herald of Free Enterprise, Estonia and in light of the growth in the number of high density, high-speed ferries and large capacity cruise ships, issues concerning the evacuation of passengers and crew at sea are receiving renewed interest. Fire and evacuation models with features such as the ability to realistically simulate the spread of heat and smoke and the human response to fire as well as the capability to model human performance in heeled orientations linked to a virtual reality environment that produces realistic visualisations of the modelled scenarios are now available and can be used to aid the engineer in assessing ship design and procedures. This paper describes the maritimeEXODUS ship evacuation and the SMARTFIRE fire simulation model and provides an example application demonstrating the use of the models in performing fire and evacuation analysis for a large passenger ship partially based on the requirements of MSC circular 1033

Computational fire engineering - do we have what we need?

This presentation will attempt to address the issue of whether the engineering design community has the knowledge, data and tool sets required to undertake advanced evacuation analysis. In discussing this issue I want to draw on examples not only from the building industry but more widely from where ever people come into contact with an environment fashioned by man. Prescriptive design regulations the world over suggest that if we follow a particular set of essentially configurational regulations concerning travel distances, number of exits, exit widths, etc it should be possible to evacuate a structure within a pre-defined acceptable amount of time. In the U.K. for public buildings this turns out to be 2.5 minutes, internationally in the aviation industry this is 90 seconds, in the UK rail industry this is 90 seconds and the international standard adopted by the maritime industry is 60 minutes. The difficulties and short comings of this approach are well known and so I will not repeat them here, save to say that this approach is usually littered with “magic numbers” that do not stand up to scrutiny. As we are focusing on human behaviour issues, it is also worth noting that more generally, the approach fails to take into account how people actually behave, preferring to adopt an engineer’s view of what people should do in order to make their design work. Examples of the failure of this approach are legion and include the; Manchester Boeing 737 fire, Kings Cross underground station fire, Piper Alpha oil platform explosion, Ladbroke Grove Rail crash and fire, Mont Blanc tunnel fire, Scandinavian Star ferry fire and the Station Nightclub fire.

Engineering emergence for cluster configuration

Distributed applications are being deployed on ever-increasing scale and with ever-increasing functionality. Due to the accompanying increase in behavioural complexity, self-management abilities, such as self-healing, have become core requirements. A key challenge is the smooth embedding of such functionality into our systems. Natural distributed systems such as ant colonies have evolved highly efficient behaviour. These emergent systems achieve high scalability through the use of low complexity communication strategies and are highly robust through large-scale replication of simple, anonymous entities. Ways to engineer this fundamentally non-deterministic behaviour for use in distributed applications are being explored. An emergent, dynamic, cluster management scheme, which forms part of a hierarchical resource management architecture, is presented. Natural biological systems, which embed self-healing behaviour at several levels, have influenced the architecture. The resulting system is a simple, lightweight and highly robust platform on which cluster-based autonomic applications can be deployed.

Scalable and efficient graph colouring in 3 dimensions using emergence engineering principles

This paper describes ways in which emergence engineering principles can be applied to the development of distributed applications. A distributed solution to the graph-colouring problem is used as a vehicle to illustrate some novel techniques. Each node acts autonomously to colour itself based only on its local view of its neighbourhood, and following a simple set of carefully tuned rules. Randomness breaks symmetry and thus enhances stability. The algorithm has been developed to enable self-configuration in wireless sensor networks, and to reflect real-world configurations the algorithm operates with 3 dimensional topologies (reflecting the propagation of radio waves and the placement of sensors in buildings, bridge structures etc.). The algorithm’s performance is evaluated and results presented. It is shown to be simultaneously highly stable and scalable whilst achieving low convergence times. The use of eavesdropping gives rise to low interaction complexity and high efficiency in terms of the communication overheads.

Engineering design knowledge management in de-centralised virtual enterprises

The problems of collaborative engineering design and knowledge management at the conceptual stage in a network of dissimilar enterprises was investigated. This issue in engineering design is a result of the supply chain and virtual enterprise (VE) oriented industry that demands faster time to market and accurate cost/manufacturing analysis from conception. The solution consisted of a de-centralised super-peer net architecture to establish and maintain communications between enterprises in a VE. In the solution outlined below, the enterprises are able to share knowledge in a common format and nomenclature via the building-block shareable super-ontology that can be tailored on a project by project basis, whilst maintaining the common nomenclature of the ‘super-ontology’ eliminating knowledge interpretation issues. The two-tier architecture layout of the solution glues together the peer-peer and super-ontologies to form a coherent system for both internal and virtual enterprise knowledge management and product development.

A framework to integrate design knowledge reuse and requirements management in engineering design

This paper presents a framework to integrate requirements management and design knowledge reuse. The research approach begins with a literature review in design reuse and requirements management to identify appropriate methods within each domain. A framework is proposed based on the identified requirements. The framework is then demonstrated using a case study example: vacuum pump design. Requirements are presented as a component of the integrated design knowledge framework. The proposed framework enables the application of requirements management as a dynamic process, including capture, analysis and recording of requirements. It takes account of the evolving requirements and the dynamic nature of the interaction between requirements and product structure through the various stages of product development.