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The boundary integral equation (BIE) numerical technique is applied to several practical pressure vessels and piping problems. Axisymmetric and three‐dimensional formulations of the BIE method for linear elastic stress analysis are reviewed. Isoparametric quadratic elements which exhibit excellent modelling capabilities are used to discretize the surfaces. Several three‐dimensional and axisymmetric structures are analysed.

Through the credit they furnish, materials suppliers provide a form of working capital for most construction contractors. This paper considers the implications of this for crediting organizations (i.e. suppliers). It is shown that a supplier's financial turnover movement (or lack of it) can be modelled and predicted with some accuracy by considering a number of characteristics of their credit control department. The models are developed from analysis of data obtained from a survey of 55 UK materials suppliers' credit control and debt collection procedures. The statistical technique of multivariate‐discriminant analysis (MDA) is used. Predictive accuracy of the models is tested on an independent, hold‐out sample of 10 suppliers' characteristics. It is found that ‘risk‐taking’ suppliers who protect themselves from bad debt by using insurance; suppliers who employ a third‐party organization to evaluate potential debtors' creditworthiness; and suppliers who service only one construction trade with materials, achieve significantly greater financial growth than those suppliers who do not exhibit these characteristics.

Today’s growing numbers of contractor selection methodologies reflect the increasing awareness of the construction industry for improving its procurement process and performance. This paper investigates contractor classification methods that link clients’ selection aspirations and contractor performance. Multivariate techniques were used to study the intrinsic link between clients’ selection preferences, i.e. project‐specific criteria (PSC) and their respective levels of importance assigned (LIA), during tender evaluation for modelling contractor classification models in a data set of 68 case studies of UK construction projects. The logistic regression (LR) and multivariate discriminant analysis (MDA) were used. Results revealed that both techniques produced a good prediction on contractor performance and indicated that suitability of the equipment, past performance in cost and time on similar projects, contractor relationship with local authority, and contractor reputation/image are the most predominant PSC in the LR and MDA models among the 34 PSC. Suggests contractor classification models using multivariate techniques could be developed further.