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Development and validation of compressible mixture viscous fluid algorithm applied to predict the evolution of inertial fusion energy chamber gas and the impact of gas on direct-drive target survival.

机译:可压缩混合物粘性流体算法的开发和验证,用于预测惯性聚变能室气体的演化以及气体对直接驱动目标生存的影响。

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摘要

Inertial confinement fusion is one of two primary approaches to the production of fusion energy for power generation. Due to the high cost of experimentation for large scale systems such as Laser Inertial Fusion Energy (Laser IFE), the ability to accurately simulate the expected performance using properly validated models is of critical importance. The evolution of the chamber environment from target injection through the generation of fusion energy is a key issue for the success of Laser IFE. Because burn emissions have the potential to damage IFE chamber walls, chamber gas is investigated to protect the wall. In the research presented, a new fluid algorithm for gas mixtures is created through the extension and correction of a prior single gas algorithm for IFE chamber gases. Once validated, this algorithm is applied to an array of chamber gases, densities, and geometric configurations. Resulting chamber states are used to estimate direct-drive target survival within the gas. This defines a new safe design window for chamber gas. This work also highlights key areas of future research to minimize uncertainty in the system design window.
机译:惯性约束聚变是生产用于发电的聚变能量的两种主要方法之一。由于对大型系统(例如激光惯性聚变能量(Laser IFE))进行试验的成本很高,因此,使用经过正确验证的模型准确模拟预期性能的能力至关重要。腔室环境从目标注入到聚变能量生成的演变是激光IFE成功的关键问题。由于燃烧排放物有可能损坏IFE腔室壁,因此对腔室气体进行了研究以保护壁。在提出的研究中,通过扩展和校正现有的用于IFE腔室气体的单一气体算法,创建了一种新的气体混合物流体算法。验证后,此算法将应用于一系列腔室气体,密度和几何结构。所得的腔室状态用于估计气体中直接驱动目标的存活率。这为腔室气体定义了一个新的安全设计窗口。这项工作还强调了未来研究的关键领域,以最大程度地减少系统设计窗口中的不确定性。

著录项

  • 作者

    Martin, Robert Scott.;

  • 作者单位

    University of California, San Diego.;

  • 授予单位 University of California, San Diego.;
  • 学科 Engineering Aerospace.;Engineering Nuclear.;Engineering Mechanical.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 228 p.
  • 总页数 228
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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