Development and validation of a new method for measuring friction between skin and nonwoven materials.

A new method for measuring the coefficient of friction between nonwoven materials and the curved surface of the volar forearm has been developed and validated. The method was used to measure the coefficient of static friction for three different nonwoven materials on the normal (dry) and over-hydrated volar forearms of five female volunteers (ages 18-44). The method proved simple to run and had good repeatability: the coefficient of variation (standard deviation expressed as a percentage of the mean) for triplets of repeat measurements was usually (80 per cent of the time) less than 10 per cent. Measurements involving the geometrically simpler configuration of pulling a weighted fabric sample horizontally across a quasi-planar area of volar forearm skin proved experimentally more difficult and had poorer repeatability. However, correlations between values of coefficient of static friction derived using the two methods were good (R = 0.81 for normal (dry) skin, and 0.91 for over-hydrated skin). Measurements of the coefficient of static friction for the three nonwovens for normal (dry) and for over-hydrated skin varied in the ranges of about 0.3-0.5 and 0.9-1.3, respectively. In agreement with Amontons' law, coefficients of friction were invariant with normal pressure over the entire experimental range (0.1-8.2 kPa).

Experimental and theoretical comparison between static and dynamic torsional soil tests

The dynamic properties of dry Leighton Buzzard sand have been investigated using a resonant column test apparatus. These data are compared with very low frequency cyclic tests on identical specimens of sand. The comparison indicates that the properties of dry sand are independent of frequency. A simple one-dimensional model of kinematic hardening plasticity is used to predict the dynamic behaviour of the sand. The input parameters for this model are based on the results of static tests. These may be conducted on standard laboratory equipment with only minor modifications. The predictions are in good agreement with the measured data.

Exploring the impacts of the interactions between lifecycles and other dynamics that influence the development of technology-based industries

To address future uncertainty within strategy and innovation, managers extrapolate past patterns and trends into the future. Several disciplines make use of lifecycles, often with a linear sequence of identified phases, to make predictions and address likely uncertainties. Often the aggregation of several cycles is then interpreted as a new cycle - such as product lifecycles into an industry lifecycle. However, frequently different lifecycle terms - technology, product, industry - are used interchangeably and without clear definition. Within the interdisciplinary context of technology management, this juxtaposition of dynamics can create confusion, rather than clarification. This paper explores some typical dynamics associated with technology-based industries, using illustrative examples from the automotive industry. A wide range of dimensions are seen to influence the path of a technology-based industry, and stakeholders need to consider the likely causality and synchronicity of these. Some curves can simply present the aggregation of components; other dynamics incur time lags, rather than being superimposed, but still have a significant impact. To optimise alignment of the important dimensions within any development, and for future strategy decisions, understanding these interactions will be critical. © 2011 IEEE.