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Automated targeting technique for concentration- and property-based total resource conservation network

机译:基于集中和基于属性的总资源保护网络的自动定位技术

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Resource conservation networks (RCNs) are among the most effective systems for reducing the consumption of fresh materials and the discharge of waste streams. A typical RCN involves multiple elements of resource pre-treatment, material reuse/recycle, regeneration/interception, and waste treatment for final discharge. Due to the close interactions among these individual elements, simultaneous synthesis of a total RCN is necessary. This paper presents an optimisation-based procedure known as automated targeting technique to locate the minimum resource usage or total cost of a concentration- or property-based total RCNs. This optimisation-based approach provides the same benefits as conventional pinch analysis techniques in yielding various network targets prior to detailed design. Additionally, this approach offers more advantages than the conventional pinch-based techniques through its flexibility in setting an objective function and the ability to handle different impurities/properties for reuse/recycle and waste treatment networks. Furthermore, the concentration-based RCN is treated as the special case of property integration, and solved by the same model. Literature examples are solved to illustrate the proposed approach.
机译:资源节约网络(RCN)是减少新鲜材料消耗和废物流排放的最有效系统之一。典型的RCN涉及资源预处理,物料再利用/循环,再生/拦截和最终排放废物处理的多个要素。由于这些单个元素之间的紧密相互作用,因此必须同时合成整个RCN。本文介绍了一种基于优化的程序,称为自动目标定位技术,用于定位基于集中或基于属性的总RCN的最小资源使用或总成本。这种基于优化的方法在详细设计之前产生各种网络目标时,提供了与常规捏分析技术相同的优势。此外,该方法通过设置目标函数的灵活性以及为重用/回收和废物处理网络处理不同杂质/特性的能力,比常规的基于捏的技术更具优势。此外,基于浓度的RCN被视为属性集成的特例,并通过相同的模型进行求解。解决了文献实例以说明所提出的方法。

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