海底管道检测中对接站和常驻自主水下航行器的最优布局
Optimal Placement of Docking Stations and Resident AUVs for Subsea Pipeline Inspection
- Department of Marine Technology, Norwegian University of Science and Technology (NTNU)（挪威科技大学海洋技术系）
- Lakeside Labs GmbH（拉赫斯实验室）
机构由 AI 辅助整理，请以论文原文为准。
AI总结：
针对海底管道检测，提出两阶段混合整数线性规划框架，联合优化对接站布局和水下航行器分配，最小化响应时间，案例研究表明少数合理布局的对接站即可达最佳性能，成本与时间分析为设计检测网络提供指导。
AI中文摘要：
本文引入了一个两阶段混合整数线性规划框架，用于海底管道事故响应规划，联合优化海底对接板（SDP）布局和常驻自主水下航行器分配，以在空间不确定性下最小化最大响应时间和平均响应时间。第一阶段最小化所有潜在泄漏位置的最大响应时间，第二阶段在最大响应时间限制下降低平均响应时间。基于挪威 Johan Sverdrup 油气田的案例研究表明，只需少数布局良好的 SDP 就能实现最佳性能。成本与时间的帕累托分析揭示了部署支出与响应效率之间的权衡，为设计弹性且经济高效的海底检测网络提供了可操作的指导。
英文摘要：
A two-stage mixed-integer linear programming framework is introduced for subsea pipeline incident response planning, jointly optimizing Subsea Docking Plate (SDP) placement and resident autonomous underwater vehicle allocation to minimize both maximum and average response times under spatial uncertainty. Phase 1 minimizes the maximum response time across all potential leak locations. Phase 2 reduces the average response time subject to the maximum bound. A case study based on the Johan Sverdrup oil and gas field in Norway, with 9 SDP options and 33 pipelines, shows that just a few well-placed SDPs are enough to achieve top performance. A cost versus time Pareto analysis reveals the trade-off between deployment expenditure and response efficiency, providing actionable guidance for designing resilient and cost-effective subsea inspection networks.
