The mobile arm support project as a test-bed for design research at the Cambridge EDC

A host of methods and tools to support designing are being developed in Cambridge EDC. These range from tools for design management to those for the generation and selection of design ideas, layouts, materials and production processes. A project, to develop a device to improve arm mobility of muscular dystrophy sufferers, is undertaken as a test-bed to evaluate and improve these methods and tools as well as to observe and modify its design and management processes. This paper presents the difficulties and advantages of using design methods and tools within this rehabilitation design context, with special focus on the evolution of the designs, tools, and management processes.

CFD modeling of single-phase flow in a packed bed with MRI validation

Computational fluid dynamics (CFD) simulations are becoming increasingly widespread with the advent of more powerful computers and more sophisticated software. The aim of these developments is to facilitate more accurate reactor design and optimization methods compared to traditional lumped-parameter models. However, in order for CFD to be a trusted method, it must be validated using experimental data acquired at sufficiently high spatial resolution. This article validates an in-house CFD code by comparison with flow-field data obtained using magnetic resonance imaging (MRI) for a packed bed with a particle-to-column diameter ratio of 2. Flows characterized by inlet Reynolds numbers, based on particle diameter, of 27, 55, 111, and 216 are considered. The code used employs preconditioning to directly solve for pressure in low-velocity flow regimes. Excellent agreement was found between the MRI and CFD data with relative error between the experimentally determined and numerically predicted flow-fields being in the range of 3-9%. © 2012 American Institute of Chemical Engineers (AIChE).

Metal-polymer composite sensors for volatile organic compounds: Part 1. Flow-through chemi-resistors

A new type of chemi-resistor based on a novel metal-polymer composite is described. The composite contains nickel particles with sharp nano-scale surface features, which are intimately coated by the polymer matrix so that they do not come into direct physical contact. No conductive chains of filler particles are formed even at loadings above the percolation threshold and the composite is intrinsically insulating. However, when subjected to compression the composite becomes conductive, with sample resistance falling from ≥ 1012 Ω to < 0.01 Ω. The composite can be formed into insulating granules, which display similar properties to the bulk form. A bed of granules compressed between permeable frits provides a porous structure with a start resistance set by the degree of compression while the granules are free to swell when exposed to volatile organic compounds (VOCs). The granular bed presents a large surface area for the adsorption of VOCs from the gas stream flowing through it. The response of this system to a variety of vapours has been studied for two different sizes of the granular bed and for different matrix polymers. Large responses, ΔR/R0 ≥ 10^7, are observed when saturated vapours are passed through the chemi-resistor. Rapid response allows real time sensing of VOCs and the initial state is recovered in a few seconds by purging with an inert gas stream. The variation in response as a function of VOC concentration is determined.

Adapting data processing to compare model and experiment accurately: A discrete element model and magnetic resonance measurements of a 3d cylindrical fluidized bed

Discrete element modeling is being used increasingly to simulate flow in fluidized beds. These models require complex measurement techniques to provide validation for the approximations inherent in the model. This paper introduces the idea of modeling the experiment to ensure that the validation is accurate. Specifically, a 3D, cylindrical gas-fluidized bed was simulated using a discrete element model (DEM) for particle motion coupled with computational fluid dynamics (CFD) to describe the flow of gas. The results for time-averaged, axial velocity during bubbling fluidization were compared with those from magnetic resonance (MR) experiments made on the bed. The DEM-CFD data were postprocessed with various methods to produce time-averaged velocity maps for comparison with the MR results, including a method which closely matched the pulse sequence and data processing procedure used in the MR experiments. The DEM-CFD results processed with the MR-type time-averaging closely matched experimental MR results, validating the DEM-CFD model. Analysis of different averaging procedures confirmed that MR time-averages of dynamic systems correspond to particle-weighted averaging, rather than frame-weighted averaging, and also demonstrated that the use of Gaussian slices in MR imaging of dynamic systems is valid. © 2013 American Chemical Society.