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Optimising heat exchanger network synthesis using convexity properties of the logarithmic mean temperature difference

机译:利用对数平均温差的凸性优化热交换器网络综合

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摘要

Industrial processes typically involve heating and cooling fluids via networks of heat exchangers which reuse excess process heat onsite. Optimally synthesising these networks of heat exchangers is a mixed-integer nonlinear optimisation problem with nonlinear terms including bilinear stream mixing, concave cost functions, and the logarithmic mean temperature difference (LMTD), which characterises the nonlinear nature of heat exchange. LMTD is typically associated with numerical difficulties, but, after adding the limits, this manuscript proves the strict convexity of LMTD~β, β<0, and also characterises the shape of the function for all β ≤ 1. These proofs motivate why previous, heuristic-based approaches work best when the problem is reformulated to move the LMTD terms into the objective. The convexity results also lead to an effective algorithm bounding the simultaneous synthesis model SYNHEAT from the online test set MlNLPLib2; this algorithm solves a series of mixed-integer linear optimisation problems converging to the global objective value of the original problem.
机译:工业过程通常涉及通过换热器网络加热和冷却流体,该换热器网络在现场重复使用多余的过程热。最佳地综合这些换热器网络是一个混合整数非线性优化问题,其非线性项包括双线性流混合,凹成本函数和对数平均温差(LMTD),这是热交换的非线性特性。 LMTD通常与数值上的困难有关,但是,在增加了限制之后,该手稿证明了LMTD〜β的严格凸性,β<0,并且表征了所有β≤1的函数的形状。当问题被重新表述以将LMTD术语移至目标时,基于启发式的方法最有效。凸性结果还导致了一种有效的算法,该算法限制了在线测试集MlNLPLib2的同时综合模型SYNHEAT;该算法解决了一系列混合整数线性优化问题,收敛到原始问题的全局目标值。

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