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Optimization of fuels from waste composition with application of genetic algorithm

机译:应用遗传算法优化废物成分燃料

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The objective of this article is to elaborate a method to optimize the composition of the fuels from sewage sludge (PBS fuel - fuel based on sewage sludge and coal slime, PBM fuel - fuel based on sewage sludge and meat and bone meal, PBT fuel - fuel based on sewage sludge and sawdust). As a tool for an optimization procedure, the use of a genetic algorithm is proposed. The optimization task involves the maximization of mass fraction of sewage sludge in a fuel developed on the basis of quality-based criteria for the use as an alternative fuel used by the cement industry. The selection criteria of fuels composition concerned such parameters as: calorific value, content of chlorine, sulphur and heavy metals. Mathematical descriptions of fuel compositions and general forms of the genetic algorithm, as well as the obtained optimization results are presented. The results of this study indicate that the proposed genetic algorithm offers an optimization tool, which could be useful in the determination of the composition of fuels that are produced from waste.
机译:本文的目的是详细说明一种方法,以优化污水污泥中燃料的成分(PBS燃料-基于污水污泥和煤泥的燃料,PBM燃料-基于污水污泥以及肉和骨粉的燃料,PBT燃料-以污水污泥和锯末为基础的燃料)。作为优化过程的工具,提出了一种遗传算法。优化任务包括使燃料中污水污泥的质量分数最大化,该燃料是基于质量标准开发的,用作水泥行业使用的替代燃料。燃料成分的选择标准涉及以下参数:热值,氯,硫和重金属的含量。给出了燃料成分的数学描述和遗传算法的一般形式,以及获得的优化结果。这项研究的结果表明,所提出的遗传算法提供了一种优化工具,可用于确定由废物产生的燃料的成分。

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