Precision Polishing of Ablator Capsules via in situ Process Monitoring and Machine Learning–Based Optimization-Reference-Cited by-同舟云学术

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Precision Polishing of Ablator Capsules via in situ Process Monitoring and Machine Learning–Based Optimization

Published:2024-09-10 Issue: Volume: Page:1-13
ISSN:1536-1055
Container-title:Fusion Science and Technology
language:en
Short-container-title:Fusion Science and Technology

Author:

Tiwari Akash¹,Jin Shilan¹,Galla Shashank¹,Botcha Bhaskar²,Hayes Sean³,Biener Monika³,Bhardwaj Kshitij³,Bukkapatnam Satish¹,Ding Yu⁴,Antonios Alexos⁵,Baldi Pierre⁵,Bhandarkar Suhas³^ORCID

Affiliation:

1. Texas A&M University, Industrial and Systems Engineering, College Station, Texas 77843

2. Apple Corp, Cupertino, California 95014

3. Lawrence Livermore National Laboratory, Materials Science Division, Livermore, California 94550

4. Georgia Institute of Technology, Industrial and Systems Engineering, Atlanta, Georgia 30332

5. University of California at Irvine, Department of Computer Science, Irvine, California 92697

Funder

U.S. Department of Energy by LLNL

LLNL laboratory-directed research and development

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/15361055.2024.2385224

Reference29 articles.

1. Achievement of Target Gain Larger than Unity in an Inertial Fusion Experiment

2. Ignition and inertial confinement fusion at the National Ignition Facility

3. Targets for Inertial Confinement Fusion

4. Progress toward Ignition and Burn Propagation in Inertial Confinement Fusion

5. Development of the indirect‐drive approach to inertial confinement fusion and the target physics basis for ignition and gain

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