Fibre reinforced composites constitute a relevant class of materials used chiefly in lightweight constructions for example in fuselages or car bodies. The spatial arrangement of the fibres and in particular their direction distribution have huge impact on macroscopic properties and, thus, its determination is an important topic of material characterisation. The fibre direction distribution is defined on the unit sphere, and it is therefore preferable to work with fully three-dimensional images of the microstructure as obtained, e.g., by computed micro-tomography. A number of recent image analysis algorithms exploit local grey value variations to estimate a preferred direction in each fibre point. Averaging these local results leads estimates of the volume-weighted fibre direction distribution. We show how the thus derived fibre direction distribution is related to quantities commonly used in engineering applications. Furthermore, we discuss four algorithms for local orientation analysis, namely those based on the response of anisotropic Gaussian filters, moments and axes of inertia derived from directed distance transforms, the structure tensor, or the Hessian matrix. Finally, the feasibility of these algorithms is demonstrated for application examples and some advantages and disadvantages of the underlying methods are pointed out.
Among the various properties of fibrous filter media, fiber thickness is one of the important characteristics which should be considered in design and quality assurance of filter media. Automatic analysis of images from scanning electron microscopy (SEM) is a suitable tool in that context. Yet, the accuracy of such image analysis tools cannot be judged based on images of real filter media since their true fiber thickness can never be known accurately. A solution is to employ synthetically generated models for evaluation. To this end, a 3D fiber model is extended to incorporate fiber bundles, which are common in fibrous filter media. The resulting novel stochastic 3D fiber model can generate geometries with good visual resemblance of real filter media. By combining this model with simulation of the SEM imaging process, quantitative evaluation of the fiber thickness measurements becomes feasible.
The authors propose two single amplifier low pass filter topologies achieving a second order roll-off in a transimpedance (i-to-v) configuration. Both topologies are derived with the constraint of fully differential signal processing. A transimpedance configuration finds direct application in scenarios when the input signal is in current domain while the output needs to be a voltage. Output of a current steering DigitalAnalog converter, and output of a down-conversion mixer, are two such examples. The transimpedance active-RC configurations presented here achieve the desired filtering with a single op-amp while eliminating redundant voltage conversion. Thus, immense advantages in terms of noise, linearity and area are obtained. To the best of authors' knowledge, no one has previously reported single amplifier bi-quadratic active-RC topologies in fully differential transimpedance configuration.
A novel direct-conversion RF architecture is proposed that has a current-mode interface between the low noise amplifier (LNA) and the down-conversion mixer, as well as the mixer and the base-band filter. The proposed architecture eliminates the voltage swing at the output of all the radiofrequency blocks. The voltage swing is seen only in the baseband after second order filtering, thus resulting in significant linearity improvements and robustness to adjacent channel interference. The current mode interface between filter and mixer also eliminates a redundant voltage-current conversion, giving significant noise advantages. A prototype wireless local area network (WLAN) receiver was designed and simulated in 0.13µm technology, giving a third-order input-referred intercept point of 5 dBm and a noise figure of 2.7 dB for the receive chain. The circuit (including base-band) consumes 8 mA from a 1.2V supply.
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