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Multiple Objectives for Genetically Optimized Coupled Inversion Method for Jet Models in Flowing Ambient Fluid

机译:流动环境中射流模型的遗传优化耦合反演方法的多个目标

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AbstractOptimal dilution and the lowest possible energy consumption are essential environmental and economic objectives for deep sea sewage discharge. In this paper, a new method with multiple parameters and objectives, nonlinear, genetically optimized and coupled inversion for determining jet ratios and angles was established by coupling Genetic Algorithms (GAs) with Anisotropic Turbulent Buoyant Jet Models with variable densities to achieve these objectives. The multiple objectives were taken into account for the jet model and the Operation Energy Consumption Equation was input into the GAs. Real coding methodology was utilized to avoid the precision losses of binary coding. A multiple parameters matching designed cases methodology was used to improve the convergence velocity. The fluctuated convergence curves that were utilized for searching for the optimal multiple parameters showed that the present method is suitable for the multiple objectives optimizing inversion problem. The numerical results of t...
机译:摘要最佳稀释和尽可能低的能耗是深海污水排放的重要环境和经济目标。本文通过将遗传算法(GA)与具有可变密度的各向异性湍流浮力射流模型相结合,建立了一种具有多个参数和目标,非线性,遗传优化和耦合反演的新方法来确定射流比和角度,以实现这些目标。射流模型考虑了多个目标,并且将运行能耗公式输入了GA。利用真实编码方法来避免二进制编码的精度损失。使用多参数匹配设计案例方法来提高收敛速度。用于寻找最优多参数的波动收敛曲线表明,该方法适用于多目标优化反演问题。 t ...的数值结果

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