A finite volume unstructured mesh approach to dynamic fluid-structure interaction: an assessment of the challenge of flutter analysis

Computational modelling of dynamic fluid-structure interaction (DFSI) is problematical since conventionally computational fluid dynamics (CFD) is solved using finite volume (FV) methods and computational structural mechanics (CSM) is based entirely on finite element (FE) methods. Hence, progress in modelling the emerging multi-physics problem of dynamic fluid-structure interaction in a consistent manner is frustrated and significant problems in computation convergence may be encountered in transferring and filtering data from one mesh and solution procedure to another, unless the fluid-structure coupling is either one way, very weak or both. This paper sets out the solution procedure for modelling the multi-physics dynamic fluid-structure interaction problem within a single software framework PHYSICA, using finite volume, unstructured mesh (FV-UM) procedures and will focus upon some of the problems and issues that have to be resolved for time accurate closely coupled dynamic fluid-structure flutter analysis.

A generic time and space accurate numerical approach to closely coupled fluid-structure interaction problems

Fluid structure interaction, as applied to flexible structures, has wide application in diverse areas such as flutter in aircraft, flow in elastic pipes and blood vessels and extrusion of metals through dies. However a comprehensive computational model of these multi-physics phenomena is a considerable challenge. Until recently work in this area focused on one phenomenon and represented the behaviour of the other more simply even to the extent in metal forming, for example, that the deformation of the die is totally ignored. More recently, strategies for solving the full coupling between the fluid and soild mechanics behaviour have developed. Conventionally, the computational modelling of fluid structure interaction is problematical since computational fluid dynamics (CFD) is solved using finite volume (FV) methods and computational structural mechanics (CSM) is based entirely on finite element (FE) methods. In the past the concurrent, but rather disparate, development paths for the finite element and finite volume methods have resulted in numerical software tools for CFD and CSM that are different in almost every respect. Hence, progress is frustrated in modelling the emerging multi-physics problem of fluid structure interaction in a consistent manner. Unless the fluid-structure coupling is either one way, very weak or both, transferring and filtering data from one mesh and solution procedure to another may lead to significant problems in computational convergence. Using a novel three phase technique the full interaction between the fluid and the dynamic structural response are represented. The procedure is demonstrated on some challenging applications in complex three dimensional geometries involving aircraft flutter, metal forming and blood flow in arteries.

Multilevel approaches applied to the capacitated clustering problem

This paper presents two multilevel refinement algorithms for the capacitated clustering problem. Multilevel refinement is a collaborative technique capable of significantly aiding the solution process for optimisation problems. The central methodologies of the technique are filtering solutions from the search space and reducing the level of problem detail to be considered at each level of the solution process. The first multilevel algorithm uses a simple tabu search while the other executes a standard local search procedure. Both algorithms demonstrate that the multilevel technique is capable of aiding the solution process for this combinatorial optimisation problem.

Velocity measurement of pneumatically conveyed solids using electrodynamic sensors

Theoretical and experimental studies of cross correlation techniques applied to non-restrictive velocity measurement of pneumatically conveyed solids using ring-shaped electrodynamic flow sensors are presented. In-depth studies of the electrodynamic sensing mechanism, and also of the spatial sensitivity and spatial filtering properties of the sensor are included, together with their relationships to measurement accuracy and the effects of solids' velocity profiles. The experimental evaluation of a 53 mm bore sensing head is described, including trials using a calibrated pneumatic conveyor circulating pulverized fuel and cement. Comparisons of test results with the mathematical models of the sensor are used to identify important aspects of the instrument design. Off-line test results obtained using gravity-fed solids flow show that the system repeatability is within +/-0.5% over the velocity range of 2-4 m s(-1) for volumetric concentrations of solids no greater than 0.2%. Results obtained in the pilot-plant trials demonstrate that the system is capable of achieving repeatability better than +/-2% and linearity within +/-2% over the velocity range 20-40 m s(-1) for volumetric concentrations of solids in the range 0.01-0.44%.

Student Experience of E-Learning (SEEL)

The Student Experience of E-Learning project (SEEL) was an institutional response to the university’s HEA/JISC Benchmarking exercise (Ryan and Kandler, 2007). The study had a social constructivist approach which recognised the importance of listening to the student voice (JISC 2007) within the University of Greenwich context, to interpret the student experience of e-learning. Nearly 1000 students responded to an online survey on their approaches to, and their use of, learning technology. The quantitative and qualitative questions used included identifying study patterns, using specific online tools, within the context of learning and beyond, and student’s attitudes towards using e-learning in their studies. Initially, individual responses to questions were analysed in depth, giving a general indication of the student experience. Further depth was applied through a filtering mechanism, beginning with a cross-slicing of individual student responses to produce cameos. Audio logs and individual interviews were drawn from these cameos. Analysis of the cameos is in progress but has already revealed some unexpected results. There was a mismatch between students’ expectations of the university’s use of technology and their experiences and awareness of its possible use in other contexts. Students recognised the importance of social interaction as a vehicle for learning (Vygotsky 1978, Bruner 2006) but expressed polarised views on the use of social networking sites such as Facebook for e-learning. Their experiences in commercial contexts led them to see the university VLE as unimaginative and the tutors’ use of it as lacking in vision. Whereas analysis of the individual questions provided a limited picture, the cameos gave a truer reflection of the students lived experiences and identified a gulf between the university’s provision and the students’ expectation of e-learning and their customary use of technology. However it is recognised that the very nature of an online survey necessarily excludes students who chose not to engage, either through lack of skills or through disillusionment and this would constitute a separate area for study.