It is shown, by compiling data from the literature, that there is a general relationship between the ferrite grain size and the size of the largest carbide particle in mild steels which are simply cooled after austenitization. By using this relationship, a cleavage fracture criterion derived by Smith is shown to predict a grain size dependence for the cleavage fracture stress of mild steel that is in good agreement with the results of many workers. These results indicate a value of 14 J m -2 for the effective surface energy of ferrite.Experimental results are presented showing the variation of the cleavage fracture stress of spheroidized steels with carbide particle radius. These support the suggestion that cleavage in such steels is due to the propagation of penny-shaped crack nuclei prod uced when spheroidal carbide particles crack. If the 95th percentile carbide radius is taken to represent the crack nucleus radius, an effective surface energy value of 14 Jm-2 is found to satisfy the fracture stress results. This value is in agreement with that deduced in the first part of the paper. This paPer comprises two complementary studies of the influence of microstructural variables on the cleavage fracture stress (Jf in plain-carbon steel. The first part is a critical analysis of previous fracture stress values and metallographic observations, to show that it is possible to explain the apparently anomalous result, that the strong dependence of (Jf on ferrite grain size, which is found experimentally, is not predicted by the most rigorous theoretical model available. The second part presents experimental results for the dependence of the fracture stress on carbide diameter in spheroidized steels and demonstrates that this follows the Griffith type of relationship. EFFECT OF FERRITE GRAIN SIZE ON afThere is abundant evidence that cleavage fracture in mild steels occurs when a microcrack in a brittle grain boundary carbide propagates at a critical tensile fracture stress .1-3 Smith 4 has modelled the situation for a nucleus initiated in a grain boundary carbide by a dislocation pile up of length equal to half the grain diameter. Detailed consideration of energy changes enables the critical value of fracture stress (J f to be related to the microstructural parameters of grain size d and carbide thickness Co through the equation:(1)where ri is the lattice friction stress, reff the effective shear stress, y p the effective surface energy of ferrite, E Young's modulus, and v Poisson's ratio. This is a plane strain model, appropriate if the grain boundary carbides are plate-like in form, i.e. long in the direction of the normal to the plane of the two-dimensional configuration analysed.At first sight, eqn.(1) predicts that the fracture stress depends on the ferrite 'grain diameter d. However, if the effective shear stress ref f is written as k~d-l/2, where k~is the gradient of the Hall-Petch (shear) yielding relationship, the fracture criterion reduces to:

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Warm pre-stressing of a cracked body can result in an apparent elevation of its fracture toughness at lower testing temperatures. This effect has been observed in mild steel pre-loaded at room temperature and tested at -150°C, when the apparent toughness elevation can be as great as a factor of two. This toughness elevation is produced both when the pre-load is maintained during cooling and when the pre-load is completely removed prior to cooling.Crack tip stress distributions have been estimated for different warm pre-stressing histories by the superposition of the appropriate monotonic loading stress distributions. The Ritchie, Knott and Rice model of cleavage fracture and its associated fracture criterion have been used in conjunction with the crack tip stress distribution to predict the final fracture load after warm pre-stressing. Predictions so made are seen to be in good agreement with the experimental observations. 0376-9429/81/030335-09500.20/0 Int. Journ. of Fracture, 17 (1981) 335-343

I n recent years, knowledge management has referred to efforts to capture, store, and deploy knowledge using a combination of information technology and business processes. 1-3 More specifically, organizations aim to acquire knowledge from valued individuals and to analyze business activities to learn from successes and failures. Such 42 computer.org/intelligent IEEE INTELLIGENT SYSTEMS K n o w l e d g e M a n a g e m e n t T h e A u t h o r s Alun Preece has worked in the area of knowledge-based systems for 15 years, the last six of which he has spent at the University of Aberdeen, Scotland. His current research interests are in distributed knowledge-based systems and industrial knowledge management. He received his PhD from the University of Wales, Swansea, developing decision support systems for health care planning. He is a member of the IEEE Computer Society, the AAAI, and the British Computer Society Specialist Group on Knowledge-Based Systems and Applied AI. Contact him at