The shaped pulses control and operation on the SG-III prototype facility

Li, Ping; Wang, Wei; Shen, Jin; Huang, Wanqing; Wang, Wenyi; Su, Jingqin; Zhao, Runchang

doi:10.1088/1555-6611/aaa9dc

Laser Phys.

2018

DOI: 10.1088/1555-6611/aaa9dc

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The shaped pulses control and operation on the SG-III prototype facility

Ping Li

Wei Wang

Jin Shen

et al.

Abstract: The laser driven inertial confined fusion experiments require careful temporal shape control of the laser pulse. Two approaches are introduced to improve the accuracy and efficiency of the close loop feedback system for long term operation in TIL; the first one is a statistical model to analyze the variation of the parameters obtained from previous shots, the other is a matrix algorithm proposed to relate the electrical signal and the impulse amplitudes. With the model and algorithm applied in the pulse shapin… Show more

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Cited by 2 publications

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Continuous gradient fusion class activation mapping: segmentation of laser-induced damage on large-aperture optics in dark-field images

Han,

Huang,

Dong

et al. 2023

High Pow Laser Sci Eng

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Segmenting dark-field images of laser-induced damage on large-aperture optics in high-power laser facilities is challenged by complicated damage morphology, uneven illumination and stray light interference. Fully supervised semantic segmentation algorithms have achieved state-of-the-art performance but rely on a large number of pixellevel labels, which are time-consuming and labor-consuming to produce. LayerCAM, an advanced weakly supervised semantic segmentation algorithm, can generate pixel-accurate results using only image-level labels, but its scattered and partially underactivated class activation regions degrade segmentation performance. In this paper, we propose a weakly supervised semantic segmentation method, continuous gradient class activation mapping (CAM) and its nonlinear multiscale fusion (continuous gradient fusion CAM). The method redesigns backpropagating gradients and nonlinearly activates multiscale fused heatmaps to generate more fine-grained class activation maps with an appropriate activation degree for different damage site sizes. Experiments on our dataset show that the proposed method can achieve segmentation performance comparable to that of fully supervised algorithms.

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Continuous gradient fusion class activation mapping: segmentation of laser-induced damage on large-aperture optics in dark-field images

Han,

Huang,

Dong

et al. 2023

High Pow Laser Sci Eng

View full text Add to dashboard Cite

show abstract

CNN-based neural network model for amplified laser pulse temporal shape prediction with dynamic requirement in high-power laser facility

et al. 2022

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The temporal shape of laser pulses is one of the essential performances in the inertial confinement fusion (ICF) facility. Due to the complexity and instability of the laser propagation system, it is hard to predict the pulse shapes precisely by pure analytic methods based on the physical model [Frantz-Nodvik (F-N) equation]. Here, we present a data-driven model based on a convolutional neural network (CNN) for precise prediction. The neural network model introduces sixteen parameters neglected in the F-N equation based models to expand the representation dimension. The sensitivity analysis of the experimental results confirms that these parameters have different degrees of influence on the temporal output shapes and cannot be ignored. The network characterizes the whole physical process with commonality and specificity features to improve the description ability. The prediction accuracy evaluated by a root mean square of the proposed model is 7.93%, which is better compared to three optimized physical models. This study explores a nonanalytic methodology of combining prior physical knowledge with data-driven models to map the complex physical process by numerical models, which has strong representation capability and great potential to model other measurable processes in physical science.

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The shaped pulses control and operation on the SG-III prototype facility

Cited by 2 publications

References 20 publications

Continuous gradient fusion class activation mapping: segmentation of laser-induced damage on large-aperture optics in dark-field images

Continuous gradient fusion class activation mapping: segmentation of laser-induced damage on large-aperture optics in dark-field images

CNN-based neural network model for amplified laser pulse temporal shape prediction with dynamic requirement in high-power laser facility

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