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Balancing surface quality and machining efficiency in recycling process achieved by micro ball-end milling of flawed potassium dihydrogen phosphate optics

  • Jian Cheng
  • , Hongqin Lei
  • , Linjie Zhao
  • , Qi Liu
  • , Youwang Hu
  • , Mingjun Chen
  • Central South University
  • Harbin Institute of Technology

Research output: Contribution to journalArticlepeer-review

3   Link opens in a new tab Citations (SciVal)

Abstract

In the inertial confinement fusion experiments, under high-power laser irradiation, the dimension of micro-flaws on the potassium dihydrogen phosphate (KDP) surface can expand dramatically, leading to the failure of optical components. Conical mitigation pits (CMP) processed by a ball-end cutter are the preferred microstructures to eliminate surface flaws and recycle flawed KDP optics. However, due to the presence of numerous surface flaws, and deliquescent nature of soft-brittle KDP optics, obtaining high-quality and high-efficiency CMP surfaces in dry milling poses an urgent challenge. In this work, based on the finite element model, the optimal cutting edge radius (Re) of a ball-end cutter is determined to be 1.8 μm in accordance with the maximum tensile stress, stress distribution morphology, and cutting force. Moreover, using a ball-end cutter with the optimal Re, CMP preparation experiments are conducted to establish the initial population of non-dominated sorting genetic algorithm (NSGA-II). The prediction models of processing time (t) and surface roughness (Sa) based on the NSGA-II are developed, with average relative errors reach 2.5 % and 10.4 %, respectively. Besides, considering the demand of the recycling process under various working conditions, the quality- and efficiency priority solutions are obtained by fast non-dominated sorting algorithm and elite strategy. Under the premise of ensuring the optimal CMP surface quality, the recommended layer milling allowance, feed speed, spindle speed, and tool mark interval are 0.5 μm, 0.4 mm/s ∼ 0.9 mm/s, 4.3 × 104 r/min ∼4.6 × 104 r/min and 5 μm for acceptable repair efficiency. Compared with previous reparative processes, the optimal combination of micro-milling parameters obtained by machine learning reduces the average t for a single conical mitigation pit (with a Sa less than 30 nm) from 360 s to 278 s, achieving a reduction of 23 %. This work can provide technical supports and engineering application values for achieving a high-quality recycling process and increasing the laser damage resistance of flawed KDP optics.

Original languageEnglish
Article numbere01388
JournalSustainable Materials and Technologies
Volume44
Early online date2 Apr 2025
DOIs
Publication statusPublished - 31 Jul 2025

Data Availability Statement

Data will be made available on request.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • Ball-end milling
  • Cutting edge radius
  • Multi-objective optimization
  • Potassium dihydrogen phosphate
  • Surface flaw

ASJC Scopus subject areas

  • Renewable Energy, Sustainability and the Environment
  • General Materials Science
  • Waste Management and Disposal
  • Industrial and Manufacturing Engineering

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