Upgrading automation for nuclear fuel in-core management: from the symbolic generation of configurations to the neural adaptation of heuristics

FUELCON is an expert system in nuclear engineering. Its task is optimized refueling-design, which is crucial to keep down operation costs at a plant. FUELCON proposes sets of alternative configurations of fuel-allocation; the fuel is positioned in a grid representing the core of a reactor. The practitioner of in-core fuel management uses FUELCON to generate a reasonably good configuration for the situation at hand. The domain expert, on the other hand, resorts to the system to test heuristics and discover new ones, for the task described above. Expert use involves a manual phase of revising the ruleset, based on performance during previous iterations in the same session. This paper is concerned with a new phase: the design of a neural component to carry out the revision automatically. Such an automated revision considers previous performance of the system and uses it for adaptation and learning better rules. The neural component is based on a particular schema for a symbolic to recurrent-analogue bridge, called NIPPL, and on the reinforcement learning of neural networks for the adaptation.

Case base adaptation using solution-space metrics

In this paper we propose a generalisation of the k-nearest neighbour (k-NN) retrieval method based on an error function using distance metrics in the solution and problem space. It is an interpolative method which is proposed to be effective for sparse case bases. The method applies equally to nominal, continuous and mixed domains, and does not depend upon an embedding n-dimensional space. In continuous Euclidean problem domains, the method is shown to be a generalisation of the Shepard's Interpolation method. We term the retrieval algorithm the Generalised Shepard Nearest Neighbour (GSNN) method. A novel aspect of GSNN is that it provides a general method for interpolation over nominal solution domains. The performance of the retrieval method is examined with reference to the Iris classification problem,and to a simulated sparse nominal value test problem. The introducion of a solution-space metric is shown to out-perform conventional nearest neighbours methods on sparse case bases.

Case based adaptation using interpolation over nominal values

In this paper we propose a method for interpolation over a set of retrieved cases in the adaptation phase of the case-based reasoning cycle. The method has two advantages over traditional systems: the first is that it can predict “new” instances, not yet present in the case base; the second is that it can predict solutions not present in the retrieval set. The method is a generalisation of Shepard’s Interpolation method, formulated as the minimisation of an error function defined in terms of distance metrics in the solution and problem spaces. We term the retrieval algorithm the Generalised Shepard Nearest Neighbour (GSNN) method. A novel aspect of GSNN is that it provides a general method for interpolation over nominal solution domains. The method is illustrated in the paper with reference to the Irises classification problem. It is evaluated with reference to a simulated nominal value test problem, and to a benchmark case base from the travel domain. The algorithm is shown to out-perform conventional nearest neighbour methods on these problems. Finally, GSNN is shown to improve in efficiency when used in conjunction with a diverse retrieval algorithm.

Exploring adaptation & self-adaptation in autonomic computing systems

This panel paper sets out to discuss what self-adaptation means, and to explore the extent to which current autonomic systems exhibit truly self-adaptive behaviour. Many of the currently cited examples are clearly adaptive, but debate remains as to what extent they are simply following prescribed adaptation rules within preset bounds, and to what extent they have the ability to truly learn new behaviour. Is there a standard test that can be applied to differentiate? Is adaptive behaviour sufficient anyway? Other autonomic computing issues are also discussed.

Simulating one of the CIB W14 round robin test cases using the SMARTFIRE fire field model

Numerical predictions produced by the SMARTFIRE fire field model are compared with experimental data. The predictions consist of gas temperatures at several locations within the compartment over a 60 min period. The test fire, produced by a burning wood crib attained a maximum heat release rate of approximately 11MW. The fire is intended to represent a nonspreading fire (i.e. single fuel source) in a moderately sized ventilated room. The experimental data formed part of the CIB Round Robin test series. Two simulations are produced, one involving a relatively coarse mesh and the other with a finer mesh. While the SMARTFIRE simulations made use of a simple volumetric heat release rate model, both simulations were found capable of reproducing the overall qualitative results. Both simulations tended to overpredict the measured temperatures. However, the finer mesh simulation was better able to reproduce the qualitative features of the experimental data. The maximum recorded experimental temperature (12141C after 39 min) was over-predicted in the fine mesh simulation by 12%. (C) 2001 Elsevier Science Ltd. All rights reserved.

Modeling and experiments on an isothermal fatigue test for solder joints

This paper investigates an isothermal fatigue test for solder joints developed at the NPL. The test specimen is a lap joint between two copper arms. During the test the displacement at the ends of the copper are controlled and the force measured. The modeling results in the paper show that the displacement across the solder joint is not equal to the displacement applied at the end of the specimen. This is due to deformation within the copper arms. A method is described to compensate for this difference. The strain distribution in the solder was determined by finite element analysis and compared to the distribution generated by a theoretical 'ideal' test which generates an almost pure shear mode in the solder. By using a damage-based constitutive law the shape of the crack generated in the specimen has been predicted for both the actual test and the ideal pure shear test. Results from the simulations are also compared with experimental data using SnAgCu solder.

The introduction of social adaptation within evacuation modelling

In recent history, a number of tragic events have borne a consistent message; the social structures that existed prior to and during the evacuation significantly affected the decisions made and the actions adopted by the evacuating population in response to the emergency. This type of influence over behaviour has long been neglected in the modelling community. This paper is an attempt to introduce some of these considerations into evacuation models and to demonstrate their impact. To represent this type of behaviour within evacuation models a mechanism to represent the membership and position within social hierarchies is established. In addition, individuals within the social groupings are given the capacity to communicate relevant pieces of data such as the need to evacuate—impacting the response time—and the location of viable exits—impacting route selection. Furthermore, the perception and response to this information is also affected by the social circumstances in which individuals find themselves. Copyright © 2005 John Wiley & Sons, Ltd.

Assessment of the impact of computed and measured fire environments on building evacuation using bench and real scale test data

This study investigates the use of computer modelled versus directly experimentally determined fire hazard data for assessing survivability within buildings using evacuation models incorporating Fractionally Effective Dose (FED) models. The objective is to establish a link between effluent toxicity, measured using a variety of small and large scale tests, and building evacuation. For the scenarios under consideration, fire simulation is typically used to determine the time non-survivable conditions develop within the enclosure, for example, when smoke or toxic effluent falls below a critical height which is deemed detrimental to evacuation or when the radiative fluxes reach a critical value leading to the onset of flashover. The evacuation calculation would the be used to determine whether people within the structure could evacuate before these critical conditions develop.

Model-based pilot and data power adaptation in psam with periodic delayed feedback

We consider the optimum design of pilot-symbol-assisted modulation (PSAM) schemes with feedback. The received signal is periodically fed back to the transmitter through a noiseless delayed link and the time-varying channel is modeled as a Gauss-Markov process. We optimize a lower bound on the channel capacity which incorporates the PSAM parameters and Kalman-based channel estimation and prediction. The parameters available for the capacity optimization are the data power adaptation strategy, pilot spacing and pilot power ratio, subject to an average power constraint. Compared to the optimized open-loop PSAM (i.e., the case where no feedback is provided from the receiver), our results show that even in the presence of feedback delay, the optimized power adaptation provides higher information rates at low signal-to-noise ratios (SNR) in medium-rate fading channels. However, in fast fading channels, even the presence of modest feedback delay dissipates the advantages of power adaptation.

Marginal adaptation and performance of bioactive dental restorative materials in deciduous and young permanent teeth

Objective: The aim of this study was to investigate the adaptation of different types of restorations towards deciduous and young permanent teeth. Materials and Methods: Class V cavities were prepared in deciduous and young permanent teeth and filled with different materials (a conventional glass-ionomer, a resin-modified glass-ionomer, a poly-acid-modified composite resin and a conventional composite resin). Specimens were aged in artificial saliva for 1, 6, 12 and 18 months, then examined by SEM. Results: The composite resin and the polyacid-modified composite had better marginal adaptation than the glass-ionomers,though microcracks developed in the enamel of the tooth. The glass-ionomers showed inferior marginal quality and durability, but no microcracking of the enamel. The margins of the resin-modified glass-ionomer were slightly superior to the conventional glass-ionomer. Conditioning improved the adaptation of the composite resin, but the type of tooth made little or no difference to the performance of the restorative material. All materials were associated with the formation of crystals in the gaps between the filling and the tooth; the quantity and shape of these crystals varied with the material. Conclusions: Resin-based materials are generally better at forming sound, durable margins in deciduous and young permanent teeth than cements, but are associated with microcracks in the enamel. All fluoride-releasing materials give rise to crystalline deposits.