No abstract

This paper examines the sample size of the experimental datasets in calibrating the Weibull parameters for the modified three‐parameter Weibull stress framework, so as to enhance the experimental strategy for cleavage assessment of ferritic steels based on a local approach. The present work generates a large number of random and independent subsets from the ‘Euro steel’ fracture toughness database for the calibration procedure. The calibration of the Weibull parameters utilizes a subset of high‐constraint specimens and a subset of low‐constraint specimens from the Euro steel database to resolve the uniqueness issue in the calibration procedure reported in previous studies. This investigation reveals strong dependence of the calibrated Weibull modulus on both the constraint differences between the high‐constraint subset and the low‐constraint subset and the size of the selected subsets. The scale fracture toughness value, however, does not exhibit significant dependence on the constraint difference between the two subsets of specimens. The confidence level of the scale fracture toughness, nevertheless, still exhibits strong dependence on the sample size of the experimental data.

Productivity has long been considered highly important in Singapore. In 2015, a national strategy considering skills, innovation and productivity as the basis for sustaining economic growth involving all sectors, was replaced with one seeking to move the economy from a “value-adding” to a “value-creating” one. In Singapore, construction productivity is mainly measured by: value added per person employed; and m2 of floor area completed per manday. By the economic measure, construction usually has the lowest annual growth rate among sectors, but the physical measure shows consistent improvement. This discrepancy has led to debate on the appropriate measure. The construction productivity programme in Singapore has included: promoting mechanisation, standardisation and prefabrication; training; procurement arrangements; regulatory requirements; and application of information and communication technology. Part of the findings of a study commissioned by two trade associations is presented. The aim was to derive findings which would help construction companies to improve productivity, and government to devise better policies and programmes. The study is based on interviews and focus group discussions with senior practitioners in Singapore. The questions included: level of construction productivity; how it is measured; firms’ policies on productivity; obstacles to, and enablers of, productivity measurement and improvement; the productivity development programme; and how productivity could be improved. The study found that construction firms could systematically develop their productivity-enhancing capabilities. It proposed measures for government and industry to improve construction productivity performance.