Enhanced Minimum Spanning Tree Optimization for Air-Lifted Artificial Upwelling Pipeline Network
Junjie Zhang | Wei Fan | Yonggang Zhao | Zhiyu Zou | Mengjie Qu | Ying Chen
Artificial upwelling (AU), a geoengineering technique aimed at transporting nutrient-enriched deep-sea water to the sunlit surface layers through artificial systems, is increasingly recognized as a promising approach to enhance oceanic fertility and stimulate primary marine productivity, thereby bolstering the ocean capacity for carbon sequestration. Several air-lifted AU systems have been implemented in countries such as Norway and China. However, research on the optimization of the air injection pipeline network (AIPN)—a critical component of the air-lifted AU system—remains limited. This paper introduces a refined minimum spanning tree algorithm to propose a novel approach for optimizing the AIPN. Furthermore, the bubble-entrained plume loss rate (<i>N<sub>BEP</sub></i>) is developed as a model to assess the efficiency of air-lifted AU systems, which is applied to three case studies involving air-lifted AU systems of varying scales. The findings indicate that the enhanced minimum spanning tree algorithm outperforms the conventional Prim’s algorithm, leading to an average 87% reduction in <i>N<sub>BEP</sub></i> of the optimized AIPN, compared to the AIPN of previous air-lifted AU systems while improving system stability. Consequently, the proposed optimization method for AIPN offers valuable scientific and practical insights for the engineering design of the air-lifted AU systems across diverse scales, offering transformative potential for large-scale carbon sequestration and marine productivity enhancement.
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