ABSTRACT

In current investigation, we present a numerical investigation of multi nozzle entrainment-based hydraulic ejector system, which is intended for transporting polymetallic nodules (PMNs) from a nodule collector system to the mining machine. The system is primarily dependent on high velocity nozzle based entrainment system, where two kinds of nozzles are used viz. in-line nozzle and multi nozzle. The system delivers motive fluid through the nozzles at exceptionally high velocities to the converging zone. The rapid velocity of the nozzle jets induces negative pressure within the converging zone, facilitating the suction of fluids from the suction end. The combination of fluids from both the suction and motive ends is then discharged at the delivery end. The outcome of the current investigation shows that for motive flow rates ranging from 20 to 100 m3/hr, the total discharge flow lies between 46 to 245 m3/hr. For both the in-line nozzle based ejector system and multi nozzle based ejector system the delivery flow rate is varying between 2.3 to 2.45 times more than the motive flow inlet. However due to less pressure drop and more number of nozzles the multi nozzles ejector system proves more efficient system. The discharge flow rate attained by both of the system is sufficient for the transportation of nodules from the nodule collection end to the mining machine. These results offer valuable insights for designing an efficient nodules collector system capable of successful PMNs extraction under varying conditions.

INTRODUCTION

Deep sea mining holds particular relevance in the context of the green energy revolution and the growing electric vehicle (EV) industry (Hein et al., 2013a). As the world transitions away from fossil fuels toward renewable energy sources and electrified transportation, the demand for certain minerals such as cobalt, nickel, and rare earth elements has surged (Hein et al., 2020). These minerals are critical components in batteries and other technologies essential for renewable energy storage and electric vehicles (Manthiram, 2017; Nitta et al., 2015).

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