Fused silica is extensively utilized as a crucial optical material owing to its exceptional optical properties and thermal stability in diverse sectors such as semiconductor technology, astronomy, and military applications. However, the inherent hardness and brittleness of fused silica led to the occurrence of sub-surface defects during machining and manufacturing processes. These defects, comprising micro-cracks, scratches, and pits, remain concealed beneath the material's surface or within the post-polishing re-deposition layer, eluding conventional detection methods. Nonetheless, they exert a substantial influence on the performance of optical components, particularly in high-power laser systems. Sub-surface defects markedly diminish the laser-induced damage threshold of optical components by reducing optical transmittance, escalating scattering loss, and potentially compromising mechanical strength. This paper investigates the current theoretical frameworks and research trajectories in this domain. It delineates the application context and imperatives for fused silica optical components, elucidates the principles and ramifications of sub-surface defects, and provides a succinct overview of the contemporary research status and applicability spectrum of various damage and non-damage defect detection technologies. Furthermore, it synthesizes extant detection methodologies, delineates the merits and demerits of distinct defect detection approaches, and delineates avenues for future development and research.
A new task scheduling scheme based on dispersed computing is proposed to address the problem of poor utilization of idle computing resources in the network by the traditional computing paradigm. The scheme designs a dispersed computing task scheduling model to reduce the load pressure on NCPs in a recursive manner by combining the idea of multiple hops. For the characteristics of geographic dispersion and network dynamics in the dispersed computing environment, the time delay is selected as the optimization objective, and the task scheduling decision is made in a distributed manner by combining it with the artificial fish swarm algorithm. At the same time, the scheduling algorithm is designed mainly by setting variable step size and field of view so that the algorithm can guarantee the convergence speed while the solution accuracy is improved. The experiments show that the algorithm meets the high requirements of dispersed computing on time delay and achieves the expected goal of the system.
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