300 resultados para sugar transport

em Queensland University of Technology - ePrints Archive


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A major strategic goal in making ethanol from lignocellulosic biomass a cost-competitive liquid transport fuel is to reduce the cost of production of cellulolytic enzymes that hydrolyse lignocellulosic substrates to fermentable sugars. Current production systems for these enzymes, namely microbes, are not economic. One way to substantially reduce production costs is to express cellulolytic enzymes in plants at levels that are high enough to hydrolyse lignocellulosic biomass. Sugar cane fibre (bagasse) is the most promising lignocellulosic feedstock for conversion to ethanol in the tropics and subtropics. Cellulolytic enzyme production in sugar cane will have a substantial impact on the economics of lignocellulosic ethanol production from bagasse. We therefore generated transgenic sugar cane accumulating three cellulolytic enzymes, fungal cellobiohydrolase I (CBH I), CBH II and bacterial endoglucanase (EG), in leaves using the maize PepC promoter as an alternative to maize Ubi1 for controlling transgene expression. Different subcellular targeting signals were shown to have a substantial impact on the accumulation of these enzymes; the CBHs and EG accumulated to higher levels when fused to a vacuolar-sorting determinant than to an endoplasmic reticulum-retention signal, while EG was produced in the largest amounts when fused to a chloroplast-targeting signal. These results are the first demonstration of the expression and accumulation of recombinant CBH I, CBH II and EG in sugar cane and represent a significant first step towards the optimization of cellulolytic enzyme expression in sugar cane for the economic production of lignocellulosic ethanol.

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This paper addresses the problem of scheduling a cane transport system involving both rail transport and road transport, where the road transport operates from several sidings in the rail network. An iterative approach for scheduling the rail transport system has been developed using existing rail transport scheduling tools. The assumption that harvesters serviced by road transport are effectively operating from the rail siding from which their bins are supplied seems a reasonable starting point for the analysis. There is a need to manually modify the schedule to take into account the road transport schedule to ensure that full bins are not collected before the road transport system delivers them back to the rail siding.

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Derailments are a significant cost to the Australian sugar industry with damage to rail infrastructure and rolling stock in excess of $2 M per annum. Many factors can contribute to cane rail derailments. The more prevalent factors are discussed. Derailment statistics on likely causes for cane rail derailments are presented with the case of empty wagons on the main line being the highest contributor to business cost. Historically, the lateral to vertical wheel load ratio, termed the derailment ratio, has been used to indicate the derailment probability of rolling stock. When the derailment ratio reaches the Nadal limit of 0.81 for cane rail operations, there is a high probability that a derailment will occur. Contributing factors for derailments include the operating forces, the geometric variables of the rolling stock and the geometric deviations of the railway track. These combined, have the capacity to affect the risk of derailment for a cane rail transport operating system. The derailment type that is responsible for creating the most damage to assets and creating mill stops is the flange climb derailment, as these derailments usually occur at speed with a full rake of empty wagons. The typical forces that contribute to the flange climb derailment case for cane rail operations are analysed and a practical derailment model is developed to enable operators to better appreciate the most significant contributing factors to this type of derailment. The paper aims to: (a) improve awareness of the significance of physical operating parameters so that these principles can be included in locomotive driver training and (b) improve awareness of track and wagon variables related to the risk of derailment so that maintainers of the rail system can allocate funds for maintenance more effectively.

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The sugarcane transport system plays a critical role in the overall performance of Australia’s sugarcane industry. An inefficient sugarcane transport system interrupts the raw sugarcane harvesting process, delays the delivery of sugarcane to the mill, deteriorates the sugar quality, increases the usage of empty bins, and leads to the additional sugarcane production costs. Due to these negative effects, there is an urgent need for an efficient sugarcane transport schedule that should be developed by the rail schedulers. In this study, a multi-objective model using mixed integer programming (MIP) is developed to produce an industry-oriented scheduling optimiser for sugarcane rail transport system. The exact MIP solver (IBM ILOG-CPLEX) is applied to minimise the makespan and the total operating time as multi-objective functions. Moreover, the so-called Siding neighbourhood search (SNS) algorithm is developed and integrated with Sidings Satisfaction Priorities (SSP) and Rail Conflict Elimination (RCE) algorithms to solve the problem in a more efficient way. In implementation, the sugarcane transport system of Kalamia Sugar Mill that is a coastal locality about 1050 km northwest of Brisbane city is investigated as a real case study. Computational experiments indicate that high-quality solutions are obtainable in industry-scale applications.

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Cane railway systems provide empty bins for harvesters to fill and full bins of cane for the factory to process. These operations need to be conducted in a timely fashion to minimise delays to harvesters and the factory and to minimise the cut-to-crush delay, while also minimising the cost of providing this service. A range of tools has been provided over the years to assist in this process. This paper reviews the objectives of the cane transport system and the tools available to achieve those objectives. The facilities within these tools to assist in the control of costs are highlighted.