Mixing between fuel and shell materials in ICF implosions can affect implosion dynamics and even prevent ignition. We use data from a series of separated reactant experiments on the National Ignition Facility to calibrate and test the predictive power of gas–shell mix models. Two models are used to estimate fuel–shell mix: a Reynolds-averaged turbulence model and molecular diffusion. Minor uncertainties in capsule manufacture, experimental conditions, and values for mix model parameters produce significant variation in simulation results. Using input/output pairs from 1D simulations, we train Gaussian process surrogate models to predict experimental quantities of interest. The surrogates are used to construct posteriors for mix model parameters by marginalizing over uncertainties in capsule manufacture and experimental conditions. Mix models are calibrated with a subset of experimental data (neutron yields, ion temperature, and bang time) and tested using the remaining data. In general, both the diffusion and turbulence model correctly predict experimental DT and TT neutron yields. Despite having more free parameters, the turbulence model underpredicts ion temperature at high convergence ratio. The simpler diffusion model correctly predicts these temperatures, suggesting nonhydrodynamic gas–shell mix. The computational model consistently overpredicts DD neutron yield, indicating possible shortcomings outside of the mix model.

中文翻译：

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用分离的反应物模拟 ICF 中的气壳混合

在 ICF 内爆中燃料和壳材料之间的混合会影响内爆动力学，甚至阻止点火。我们使用来自国家点火设施的一系列分离反应物实验的数据来校准和测试气体-壳层混合模型的预测能力。两种模型用于估计燃料-壳层混合：雷诺平均湍流模型和分子扩散。胶囊制造、实验条件和混合模型参数值的微小不确定性会导致模拟结果出现显着变化。使用来自一维模拟的输入/输出对，我们训练高斯过程代理模型来预测感兴趣的实验量。代理用于通过边缘化胶囊制造和实验条件中的不确定性来构建混合模型参数的后验。混合模型使用一组实验数据（中子产率、离子温度和爆炸时间）进行校准，并使用剩余数据进行测试。一般来说，扩散和湍流模型都正确预测了实验 DT 和 TT 中子产额。尽管有更多的自由参数，湍流模型在高收敛比时低估了离子温度。更简单的扩散模型正确预测了这些温度，表明非流体动力气壳混合。计算模型始终高估了 DD 中子产额，表明混合模型之外可能存在缺陷。尽管有更多的自由参数，湍流模型在高收敛比时低估了离子温度。更简单的扩散模型正确预测了这些温度，表明非流体动力气壳混合。计算模型始终高估了 DD 中子产额，表明混合模型之外可能存在缺陷。尽管有更多的自由参数，湍流模型在高收敛比时低估了离子温度。更简单的扩散模型正确预测了这些温度，表明非流体动力气壳混合。计算模型始终高估了 DD 中子产额，表明混合模型之外可能存在缺陷。