Trickle flow hydrodynamic multiplicity: Experimental observations and pore-scale capillary mechanism

Trickle bed reactors are encountered throughout the process industry. Considerable attention has been given to the study of the hydrodynamics of this type reactor. It has been identified that, in the trickle flow regime, the hydrodynamic parameters (e.g. pressure drop and liquid holdup) are not unique functions of the operating and system conditions, but depend on the flow history. This study reviews the experimental trends identified in literature on the basis of a limiting cases framework and then evaluates the three-dimensional pore-scale liquid distribution using computed tomography (CT) data. This leads to the identification of 20 phenomenological trends that characterize hydrodynamic multiplicity, including hydrodynamic flow hysteresis as well as the effects of pre-wetting. The CT study yields additional experimental insight into the role of capillary pressure and ultimately leads to the proposal of a capillary gate mechanism based on contact angle hysteresis as the root cause of multiplicity. The mechanism is incorporated into a simple pore-network model. It is shown that the qualitative performance of the model corresponds closely to the majority of phenomenological trends and is capable of explaining the observed experimental behaviour.     

Improving yield and shape in a crushing plant

There is increasing demand to optimise yield and increase capacity of crushing plants. Research in this area has resulted in the development of numerous optimisation tools, and resent research has shown that the economic aspects of production have great influence on the optimisation results. The profitability of a product is influenced by several parameters, and control of all these parameters is necessary to use some sort of optimisation software.In this paper, we present a case study of a typical crushing plant, with the goal of reducing the number of crusher while keeping the plant capacity and quality. By reducing the number of crusher the plant will need less maintenance which will decrease the operating costs. The article presents a method to combine crushing plant simulation and optimisation with quality and economic considerations in order to successfully study alternative configurations of the plant.     

Relating consumer preferences to sensory and physicochemical properties of dry beans (Phaseolus vulgaris)

BACKGROUND: Dry beans (Phaseolus vulgaris) have a range of varieties, colours and sizes. Differences in physicochemical and sensory properties influence consumer choices for beans. This study related consumer preferences to sensory and physico‐chemical properties of selected bean varieties—Jenny, Kranskop, PAN 148, AC Calmont, PAN 150 and Mkuzi—grown in Mpumalanga (MP) and Free State (FS) in South Africa. RESULTS: Significant (P < 0.05) variety, location as well as location × variety interaction effects were found for both physico‐chemical and sensory properties of beans. Jenny‐FS, Mkuzi and PAN 148‐MP beans had relatively long cooking times (>60 min). Some beans (e.g. PAN 150 and Mkuzi beans) were described as bitter, soapy and metallic with a raw‐bean flavour whereas more preferred beans (e.g. Jenny‐MP, Kranskop‐MP) were sweet, soft and with a cooked‐bean flavour. CONCLUSION Apart from small seed size, sensory characteristics such as bitter taste, soapy and metallic mouthfeel and hard texture contributed to consumers' dislike of certain bean varieties. The sweet taste, cooked‐bean flavours, soft and mushy textures of the most accepted varieties seemed to be related to beans with good hydration capacities that facilitated softening during cooking. Copyright © 2007 Society of Chemical Industry     

On-line fan blade damage detection using neural networks

This paper presents a methodology for monitoring the on-line condition of axial-flow fan blades with the use of neural networks. In developing this methodology, the first stage was to utilise neural networks trained on features extracted from on-line blade vibration signals measured on an experimental test structure. Results from a stationary experimental modal analysis of the structure were used for identifying global blade mode shapes and their corresponding frequencies. These in turn were used to assist in identifying vibration-related features suitable for neural network training. The features were extracted from on-line blade vibration and strain signals which were measured using a number of sensors.The second stage in the development of the methodology entails utilising neural networks trained on numerical Frequency Response Function (FRF) features obtained from a Finite Element Model (FEM) of the test structure. Frequency domain features obtained from on-line experimental measurements were used to normalise the numerical FRF features prior to neural network training. Following training, the networks were tested using experimental frequency domain features. This approach makes it unnecessary to damage the structure in order to train the neural networks.The paper shows that it is possible to classify damage for several fan blades by using neural networks with on-line vibration measurements from sensors not necessarily installed on the damaged blades themselves. The significance of this is that it proves the possibility to perform on-line fan blade damage classification using less than one sensor per blade. Even more significant is the demonstration that an on-line damage detection system for a fan can be developed without having to damage the actual structure.     

High efficiency fuel cell based uninterruptible power supply for digital equipment

Eliminating the ac–dc converter (such as a computer's power supply), in a dc system when using a fuel cell based uninterruptible power supply (UPS), serves several primary functions. Firstly, it eliminates the need for a dc–ac inverter, and secondly, it eliminates a usually highly inefficient component—the power supply. Multiple conversions result in multiple inefficiencies. By replacing the computer's ac power supply with a high efficiency dc power supply capable of operating directly from a fuel cell – and thereby eliminating the inverter – the overall efficiency of the UPS can be increased by 50% or more. This is essential considering that the primary function of a fuel cell based UPS is long-term operation of the system, and poor efficiency equates to higher fuel consumption. Furthermore, inefficient systems have greater power demands, and therefore a larger fuel cell stack is needed to power them. At the present cost of fuel cell systems, this is a considerable problem. The easiest way to accomplish a direct dc UPS is to replace the computer's ac–dc power supply with a dc–dc power supply.     

DLTS detection of hole traps in MBE grown ρ-GaAs using schottky barrier diodes

The presence of hole traps has been studied by deep level transient spectroscopy (DLTS) characterization of low carrier densityp-type GaAs grown by MBE on p⁺-GaAs substrates using Al and Co Schottky contacts. The results obtained indicate the presence of several hole traps with energy levels of between 0.06 and 0.65 eV above the valence band in concentrations up to 2 × 10¹²/cm³. Some of these defects,e.g. Cu, are ascribed to system-, source-or substrate-related impurities, but the origin of several other defects is unknown.     

The design of advanced performance high strength low-carbon martensitic armour steels: Microstructural considerations

Neither a higher hardness nor higher mechanical properties (yield strength, ultimate tensile strength, impact energy, and %elongation) appear to be exclusive or even reliable criteria for predicting the ballistic performance of martensitic armour steels, as shown in our previous work [K. Maweja, W.E. Stumpf, Mater. Sci. Eng. A (February), submitted for publication]. An alternative design methodology for tempered martensitic armour steels is, therefore, proposed which is based on the effect of retained austenite on the ratio of the yield to ultimate tensile strength (YS/UTS), the microstructure of the tempered martensite and its martensite start temperature M_s. This approach was developed using 6 mm thick armour plates and later was successfully applied to the design of eight experimental armour steels with plate thicknesses ranging from 4.7 to 5.2 mm and tested by the standard R4 (5.56 mm rounds) ballistic test.