Surface tension as a controlled variable in mechanical dishwashing

Using a continuous, in-line, nondestructive technique based on the maximum bubble pressure method, the surface tension of the wash water in a mechanical dishwashing machine has been monitored. This technique has enabled surface tension to be used as a controlled variable, providing feedback to regulate the amount of surfactant added. Assuming the mechanical force of the water spray is adequate to remove bound soil from the dish surface, the food soil may be titrated against surfactant, providing an indirect indication as to when the dishes are clean. This technique also could be applied to a recirculated wash solution for in-place cleaning.     

Low-Power VLSI Implementation of the Inner Receiver for OFDM-Based WLAN Systems

In this paper, we propose low-power designs for the synchronizer and channel estimator units of the Inner Receiver in wireless local area network systems. The objective of the work is the optimization, with respect to power, area, and latency, of both the signal processing algorithms themselves and their implementation. Novel circuit design strategies have been employed to realize optimal hardware and power efficient architectures for the fast Fourier transform, arc tangent computation unit, numerically controlled oscillator, and the decimation filters. The use of multiple clock domains and clock gating reduces the power consumption further. These blocks have been integrated into an experimental digital baseband processor for the IEEE 802.11a standard implemented in the 0.25mum- 5-metal layer BiCMOS technology from Institute for High Performance Microelectronics.     

Charting of geoelectric potential signal dynamics via geometrical techniques and its possible relation to significant earthquakes in Western Greece

An exploratory data analysis (EDA) framework was developed in order to investigate the presence of possible correlations in the long-term geoelectric potential (LTGP) signal, prior to significant seismic events in Western Greece. Experimental data, which had been collected continuously within a 6-year period (1998–2003) at the earthquake signal-acquisition center of the University of Patras Seismological Laboratory (UPSL), were studied. The multidimensional scaling (MDS) technique was used to detect putative clustering tendencies in the ensemble of time-series (TS) segments that could indicate the existence of a possible correlation between the geoelectric signal structure and the impending seismic activity. The end result is a 2-dimensional point diagram with the geometry reflecting important signal characteristics, directly related with the underlying seismic events. In addition, the “appending technique”, a well-suited data analysis methodology was incorporated as a means of relating any other TS segment directly with the pre-computed, via the MDS, point diagram. Using the proposed EDA framework, we examined the presence of similar temporal patterns in the recorded geoelectric TS field, 10 days before the occurrence of the major earthquakes. The presented experimental results indicated clearly the validity of the introduced approach and, further, motivated the use of such advanced visualization schemes for charting precursor trends of significance seismicity.     

The hot blow forming of AZ31 Mg sheet: Formability assessment and application development

The hot blow forming of magnesium sheet offers significant opportunity for forming complex, lightweight parts for automotive applications. This paper characterizes the elevated-temperature formability of AZ31 magnesium sheet materials and the effect of processing conditions on the performance of these materials. In addition, magnesium sheet application development at General Motors Corporation is reviewed.     

Numerical simulation of typical contact situations of brake friction materials

In the paper, a model typical for contact situations of automotive brakes is established based on the method of movable cellular automata. The processes taking place at local contacts in an automotive brake system are analysed. Based on microscopic and micro-analytical observations, the following contact situations were simulated: (i) a couple of ferritic steel against pearlitic steel, both covered by an oxide layer mixed with graphite nanoparticles and (ii) the same situation but without oxide layers. The results of calculated mean coefficients of friction of the oxide-on-oxide contact correspond well to expected values for a real braking system, whereas steel-on-steel contact are twice as high. This allows one to make some conclusions; for example, oxide formation will take place more quickly than friction layer elimination, and finally this is responsible for the stabilisation of the coefficient of friction.     

An artificial neural network approach on parametric optimization of laser micro-machining of die-steel

In the present research, laser micro machining (LMM) of tungsten-molybdenum general purpose high speed steel (Rex M2) has been studied. Selection of optimum machining parameter combinations for obtaining higher depth of groove and smaller height of recast layer is a challenging task in LMM due to the presence of a large number of process variables. There is no perfect combination of parameters which can simultaneously result in both the highest depth of groove and lowest height of recast layer. This paper presents an attempt to develop a strategy for predicting the optimum machining parameter setting for the generation of the maximum depth of groove with minimum height of recast layer. A feed forward back-propagation neural network has been developed to model the machining process. The model, after proper training, is capable of predicting the response parameters as a function of four different control parameters. Experimental results demonstrate that the machining model is suitable and the optimization strategy satisfies practical requirements. The developed model has been found to be quite unique, powerful and flexible.