A Study on the Optimization of Water Jet Decontamination Performance Parameters Based on the Response Surface Method
Source abstract
Abstract
The substrate that adheres between the teeth of the traveling track plate during the operation of a deep-sea polymetallic nodule mining vehicle affects the driving performance, so this study aimed to investigate the effect of the water jet on the cleaning and decontamination performance of the track under different conditions. An optimization design method based on response surface methodology (RSM) is proposed. Based on the Box–Behnken design, the optimization variables of jet pressure, jet target distance, and impact angle, and the target response of jet strike pressure on tracks, were selected, and the numerical simulation method was combined with the response surface method to establish the regression model of the response of each optimization variable to the jet strike pressure on tracks and to determine the optimal parameter combinations. The study findings indicate that the primary factor influencing the pressure of the jet striking the crawler is the jet pressure. The hierarchical order of influence on the pressure of the jet striking the crawler, under the interaction of the three factors, is as follows: jet pressure and impact angle, jet pressure and target distance of the jet, and target distance of the jet and impact angle. The maximum pressure of the jet striking the crawler occurs when the jet pressure is 0.983 MPa, the target distance is 0.14 m, and the impact angle is 89.5°. Overall, the proposed design serves as a systematic framework for parameter optimization in the cleaning and decontamination process, and the research method and results provide theoretical references for the optimal design of mining truck desorption efficiency, which is critical for increasing mining efficiency and lowering energy consumption.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Marine and Coastal Research · Fire Detection and Safety Systems · Fire dynamics and safety research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
College of Mechanical Engineering, Hunan University of Technology, Zhuzhou 412007, China
Changsha Institute of Mining Research Co., Ltd., Changsha 410012, China
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Show source-provided references
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