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Modeling and Optimization of Docking Stations and AUVs for Ice Floe Measurement

机译:用于浮冰测量的扩展坞和AUV的建模和优化

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We consider an Arctic drilling platform, which must withstand seasonal ice floes and be protected against extreme ice features. Adequate ice floe thickness estimates are not discernible from satellite images, so autonomous underwater vehicles (AUVs) equipped with sonar scan the thickness of the floes. We approximate this system by an M/G/k+G queue and develop a high fidelity simulation model. We develop and solve a stochastic facility location model, which addresses the design and operational decisions related to the system. Finally, we create a visualization tool to graphically represent the docking station configurations, ice floe arrivals, and the AUV scanning process. These simulations were part of a desktop study and have not been validated through field trials, which we hope to accomplish in the next phase of this study.
机译:我们考虑了一个北极钻井平台,该平台必须能够承受季节性的浮冰,并具有极高的防冰功能。从卫星图像中无法识别出足够的浮冰厚度估算值,因此配备声纳的自动水下航行器(AUV)会扫描浮冰的厚度。我们通过M / G / k + G队列对该系统进行近似,并开发出高保真度仿真模型。我们开发并解决了随机设施选址模型,该模型解决了与系统相关的设计和运营决策。最后,我们创建了一个可视化工具,以图形方式表示坞站配置,浮冰到达和AUV扫描过程。这些模拟是桌面研究的一部分,尚未通过现场试验进行验证,我们希望在本研究的下一阶段中完成该模拟。

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