Fracture response of fibre-reinforced materials with macro/microcrack damage using the Boundary Element Technique

The Boundary Element Method (BEM) incorporating the Embedded Cell Approach (ECA) has been used to analyse the effects of constituent material properties, fibre spatial distribution and microcrack damage on the localised behaviour of transversely fractured, unidirectional fibre-reinforced composites. Three specific composites, i.e., glass fibre reinforced polyester, carbon fibre reinforced epoxy and a glass-carbon hybrid, are considered. The geometrical structures examined were perfectly periodic, uniformly spaced fibre arrangements in square and hexagonal embedded cells. In addition, numerical simulations were also conducted using embedded cells containing randomly distributed fibres. The models involve both elastic fibres and matrix, with the interfaces between the different phases being fully bonded. The results indicate that the constituent material properties (two phase composite) and spatial distribution have a significant effect on the localised stress distributions around the primary crack tip. However, the strain energy release rate associated with crack propagation is predominantly influenced by the material composition. The three-phase hybrid composite exhibited an apparent intermediate fracture toughness value, compared to the all-glass and all-carbon models. Furthermore, the strain energy release rate for the macrocrack lowers as it enters a zone of localised damage (microcracking). The presence of microcracks relaxes the stress field, which can result in a significant reduction in the energetics of the primary crack.     

Nanoscale Crystallization in Amorphous Fe–P–Mn Alloys

Mössbauer effect measurements and physicochemical analysis demonstrate that annealing of amorphous Fe–P–Mn alloys leads to the formation of a nanocrystalline structure.     

TEM Studies of High Temperature Corrosion Behaviour of TiAl Intermetallics with Surface Modifications

The oxidation/sulphidation behaviour of a Ti‐46.7Al‐1.9W‐0.5Si alloy with a TiAl₃ diffusion coating was studied in an environment of H₂/H₂S/H₂O at 850^oC. The kinetic results demonstrate that the TiAl₃ coating significantly increased the high temperature corrosion resistance of Ti‐46.7Al‐1.9W‐0.5Si. The SEM, EDX, XRD and TEM analysis reveals that the formation of an Al₂O₃ scale on the surface of the TiAl₃‐coated sample was responsible for the enhancement of the corroison resistance. The Ti‐46.7Al‐1.9W‐0.5Si alloy was also modified by Nb ion implantation. The Nb ion implanted and as received sampels were subjected to cyclic oxidation in an open air at 800^oC. The Nb ion implantation not only increased the oxidation resistance but also substantially improved the adhesion of scale to the substrate.     

Surface effects in nanocrystalline silicon

Exposure to ammonia (NH₃) increases the dark current (DC) in nanocrystalline silicon. Light soaking (LS) for short periods also enhances the dark current, which remains at a high value for a long time. Pumping alone is unable to restore the initial annealed state, but annealing brings it back. The final state obtained by LS and NH₃ exposure depends on the order in which they are performed. Evaporated selenium (Se) deposited on nanocrystalline silicon decreases the DC. These effects cannot be explained entirely by the presence of a-Si : H alone, in our sample. DC and photoluminescence (PL) measurements indicate the presence of two types of center in our sample, which behave differently when exposed to NH₃.     

An introduction of the condition class space with continuous value discretization and rough set theory

The granularity of an information system has an incumbent effect on the efficacy of the analysis from many machine learning algorithms. An information system contains a universe of objects characterized and categorized by condition and decision attributes. To manage the concomitant granularity, a level of continuous value discretization (CVD) is often undertaken. In the case of the rough set theory (RST) methodology for object classification, the granularity contributes to the grouping of objects into condition classes with the same condition attribute values. This article exposits the effect of a level of CVD on the subsequent condition classes constructed, with the introduction of the condition class space—the domain within which the condition classes exist. This domain elucidates the association of the condition classes to the related decision outcomes—reflecting the inexactness incumbent when a level of CVD is undertaken. A series of measures is defined that quantify this association. Throughout this study and without loss of generality, the findings are made through the RST methodology. This further offers a novel exposition of the relationship between all the condition attributes and the RST‐related reducts (subsets of condition attributes). © 2006 Wiley Periodicals, Inc. Int J Int Syst 21: 173–191, 2006.     

Fault detection for control of wastewater treatment plants.

Interest in real-time model-based control is increasing as more and more facilities are being asked to meet stricter effluent requirements while at the same time minimizing costs. It has been identified that biological process models and automated process control technologies are being used at wastewater treatments plants throughout the world and that great potential for optimising biotreatment may exist with the integration of these two technology areas. According to our experience, wastewater treatment plants are indeed looking for ways to successfully integrate their modelling knowledge into their process control structure; however, there are practical aspects of this integration that must be addressed if the benefits of this integration are to be realised. This paper discusses the practical aspects of monitoring, filtering and analysing real sensor data with an aim to produce a reliable real-time data stream that might be used within a model-based control structure. Several real case study examples are briefly discussed in this paper.     

Comparison of total and faecal coliforms as faecal indicator in eutrophicated surface water.

The aim of this study was to evaluate the use of total coliforms (TC) and faecal coliforms (FC) using a membrane filtration method for precise monitoring of faecal pollution in Korean surface water. The samples were collected in Korea from both main rivers and their tributaries. Presumptive TC * FC were enumerated. The ratios of presumptive FC to TC were not constant, but varied widely, and TC were difficult to enumerate because of overgrowth by background colonies. For FC this was not the case. Seven hundred and three purified strains of presumptive TC * FC and their background colonies were biotyped using API 20E. Among 272 presumptive TC, non-faecal related species, Aeromonas hydrophila dominated (34.6%) and E. coli accounted for only 5.1%. In contrast, E. coli made up 89% of the 209 presumptive FC. Furthermore, of 164 background colonies on Endo Agar LES, 54.9% was A. hydrophila, while background colonies on m-FC Agar were few (58 strains), and despite their atypical colony appearance, most of them were biotyped as enteric bacteria. These results reveal that the detection of FC rather than TC using m-FC Agar is more appropriate for faecal pollution monitoring in eutrophicated surface water located in a temperate region.     

Parameter Uncertainty and Policy Intensity: Some Extensions and Suggestions for Further Work

The effects of parameter uncertainty on optimal policy have been a matter of interest for academics, and even for some policymakers, for a long time. Two lines of literature have developed analytical results on this matter. The first line uses static models and the second dynamic models. In this dynamic line most of the results are confined to models with a single state and a single control variable. In this paper we want to encourage the analysis of more general dynamic cases. To do so, the results in the dynamic line are extended from one-state and one-control finite horizon models to models with a pair of control variables. We then discuss some of the hurdles which must be surmounted for the results to be made more general and suggests some lines for further research. JEL classification: C61; E61