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Faculty of Engineering and Built Environment

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    Crash modeling of a light composite aircraft
    (2014) Moletsane, Moeletsi Augustinus; Jonson, David
    ABSTRACT The study presented here was focused on the crash analysis of light composite aircraft on relatively survivable accidents. The crash analysis approach was based on the numerical simulation using the finite element software (MSC.Dytran). The aircraft crash environment, impact terrain, impact angles and material properties were identified, and later introduced into the aircraft crash model. The background on composite materials is discussed and more focus was given to their response at high strain rates. The modeling methodology is also discussed with more emphasis on the finite element analysis approach and the failure theories behind composite materials. The failure criteria are based on assumptions considered for the classical lamination theory, and each of the failure theories in MSC.Dytran were evaluated before being introduced into the crash model. The Tsai-Wu failure criterion was found to be capable of predicting the progressive ply failure of the composite lamina. The Ravin 500 light composite aircraft model was used for the purpose of this study and four crash scenarios of impacting the aircraft onto the soil model were considered. The aircraft was impacted at the same crash velocity but different flight path angles were considered. The 10⁰, 15⁰, 20⁰ and 30⁰ crash angles together with a crash velocity of 22m/s were used. The impact approach was influenced by the previous literature; it shows that the structural damage of an aircraft during crash accident is affected largely by the crash angle. The results of each crash scenario are presented and mainly focused on the failure response of the aircraft structure. The conclusion on the crashworthiness of the Ravin 500 light composite aircraft is also drawn based on the numerical work. Details regarding the future work or recommendations for the design philosophy and means of improving the crashworthiness of the light composite aircraft are also presented. In addition, more emphasis is focused in the occupant’s space within the aircraft.
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    Cleaner technology systems for surface finishing : evaporative coolers for close circuiting low temperature plating process
    (Elsevier, 2013-12-10) Munsamy, Megashnee; Telukdarie, Arnesh; Zhang, W.
    In the electroplating process, the rinse system generates large quantities of wastewater requiring treatment prior to disposal to municipal systems. The use of conventional water treatment systems is a challenge due to the presence of hazardous components. In addition, this does not solve the problem of the generation of rinse wastewater, but only treats it. Thus the focus was on point-source reduction technologies, specifically the application of a three-stage low flow counter current rinse for recovery of the rinse water in the plating bath, enabling close circuiting of the plating bath rinse system. However, recovery of the rinse water into the plating bath is impeded by the low rates of evaporation, especially in the low temperature plating baths. Alternative methodologies to heating were investigated to facilitate evaporation, with evaporative cooling being identified as the most feasible option. Evaporative cooling facilitates evaporation, whilst maintaining the plating bath temperature within the operational limits. For the recovery of the rinse water in the plating bath, the rate of evaporation in the plating bath must be equivalent to the fresh make-up water requirements of the rinse tanks. The Closed Circuit Plating System (CCPS) model was developed to enable the proper design and/or implementation of an evapo-rative cooler; whereby the user specified inputs are evaluated in achieving the required evaporation rates for the recovery of the rinse water in the plating bath. The key characteristic of the CCPS model is the minimum requirement of proprietary plating solution specific information. The inputs for the model are chemical composition of the plating solution, flowrates, temperature and height of the cooling tower. The outputs from the model are evaporation rates and equilibrium temperatures of the plating bath and cooling tower. The primary limitation of the CCPS model is that it is based on an airewater system. Single and multiple variable sensitivity analyses were performed on the plating plant operational pa-rameters to determine their influence on close circuiting of the rinse plating system: plating solution composition and operational temperature; ambient air temperature; air flow rate and the surface area of the packing in the cooling tower. The results from the model indicated the upper limit plating solution opera-tional temperature, high air flow rates, low ambient air temperature and large surface area of packing facilitated water evaporation rates and lower equilibrium temperatures in the plating bath and cooling tower. The sensitivity analyses will allow the electroplater to optimise the operating conditions to achieve the required evaporation rates for recovery of the rinse water into the plating bath, while simultaneously maintaining the outputs of the electroplating plant and reducing the rinse wastewater generation to almost zero.
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    Neural network modelling and prediction of the flotation deinking behaviour of industrial paper recycling processes
    (Nordic Pulp & Paper Research Journal, 2014) Pauck, Walter James; Venditti, Richard; Pocock, Jon; Andrew, Jerome Edward
    The removal of ink from recovered papers by flotation deinking is considered to be the “heart” of the paper recycling process. Attempts to model the deinking flotation process from first principles has resulted in complex and not readily usable models. Artificial neural networks are adept at modelling complex and poorly understood phenomena. Based on data generated in a laboratory, artificial neural network models were developed for the flotation deinking process. Representative samples of recycled newsprint, magazines and fine papers were pulped and deinked by flotation in the laboratory, under a wide variety of practical conditions. The brightness, residual ink concentration and the yield were measured and used to train artificial neural networks. Regressions of approximately 0.95, 0.85 and 0.79 respectively were obtained. These models were validated using actual plant data from three different deinking plants manufacturing seven different grades of recycled pulp. It was found that the brightness and residual ink concentration could be predicted with correlations in excess of 0.9. Lower correlations of ca. 0.43 were obtained for the flotation yield. It is intended to use the data to develop predictive models to facilitate the management and optimization of commercial flotation deinking processes with respect to recycled paper inputs and process conditions.