Pattern formation in weakly damped parametric surface waves driven by two frequency components

A quasi-potential approximation to the Navier-Stokes equation for low viscosity fluids is developed to study pattern formation in parametric surface waves driven by a force that has two frequency components. A bicritical line separating regions of instability to either one of the driving frequencies is explicitly obtained, and compared with experiments involving a frequency ratio of 1/2. The procedure for deriving standing wave amplitude equations valid near onset is outlined for an arbitrary frequency ratio following a multiscale asymptotic expansion of the quasi-potential equations. Explicit results are presented for subharmonic response to a driving force of frequency ratio 1/2, and used to study pattern selection. Even though quadratic terms are prohibited in this case, hexagonal or triangular patterns are found to be stable in a relatively large parameter region, a fact that is in qualitative agreement with experimental results.Comment: LaTeX (Journal of Fluid Mechanics style), 8 figure

Multi-level DEA Approach in Research Evaluation

It is well known that the discrimination power of DEA models will be diminishing if too many inputs or outputs are used. It is a dilemma if the decision makers want to select comprehensive indicators to present a relatively holistic evaluation using DEA. In this work we show that by utilizing hierarchical structures of input-output data DEA can handle quite large numbers of inputs and outputs. We present two approaches in a pilot evaluation of 15 institutes for basic research in Chinese Academy of Sciences using DEA models

Maintenance strategy optimisation for infrastructure assets through cost modelling

In infrastructure asset management, maintenance strategies in terms of cost modelling is normally adopted to achieve two broad strategic objectives: to ensure that sufficient funding is available to maintain the portfolio of assets; and to ensure that a minimum cost is achieved while maintaining safety. The data and information required for carrying out cost modelling are often not sufficient in quantity and quality. Even if the data is available, the uncertainty associated with the data and the assessment of the assets’ condition remain a challenge to be dealt with. We report in this paper that cost modelling can be carried out at the initial stage instead of delaying it due to data insufficiency. Subjective experts’ knowledge is elicited and utilised together with some information which is gathered only for a small sample of assets. Linear Bayes methods is adopted to combine the sample data with the subjective experts’ knowledge to estimate unknown model parameters of the cost model. We use a case study from the rail industry to demonstrate the methods proposed in this paper. The assets are metal girders on bridges from a rail company. The optimal maintenance strategy is obtained via simulation based on estimated model parameters