2015 IEEE International Conference on Plasma Sciences (ICOPS) 2015
DOI: 10.1109/plasma.2015.7179768
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Planar wire array Z-pinches on QiangGuang-I facility

Abstract: Planar wire array Z pinches were carried out on the QiangGuang-I facility (1.3 MA, 100 ns). The effect of prepulse current and insulating coatings on the Z pinch behavior is investigated. Commonly there is a multichannel gas switch filled with 0.5 Mpa dry air between the transmission line and the MITL to cut off the prepulse current. By varying gas pressure filled in the switch, the parameters of the prepulse current can be controlled. With a 0.2 Mpa pressure the prepulse amplitude and duration are 70 kA and 2… Show more

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Cited by 3 publications
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“…As a result, the training process of the FNOs may become challenging and potentially prone to over‐fitting in small data regimes. [ 60,67 ] To overcome these limitations, the implicit neural operator architectures were proposed, [ 60,80,81 ] where the skip connections were added between the integral layers and all layers share the same set of trainable parameter, W , c , and ϕ. In particular, the architecture Equation was modified as: vl+1false(xfalse)=scriptIIFNOfalse[vl(x)false]:=vlfalse(xfalse)+1Lσfalse(Wvlfalse(xfalse)+scriptF1false[ϕ·scriptF[vlfalse(·false)]false](x)badbreak+cfalse)$$\begin{eqnarray} v_{l+1}(x)=\mathcal {I}^{IFNO}[v_l(x)]:&=& v_l(x)+\dfrac{1}{L}\sigma (Wv_l(x) \nonumber\\ && +\mathcal {F}^{-1}[\phi \cdot \mathcal {F}[v_l(\cdot)$$]](x)+ c) \end{eqnarray}As a result, the NO architecture has substantially smaller number of trainable parameters, while still serves as a universal approximator for fixed point PDE solvers.…”
Section: Methodsmentioning
confidence: 99%
“…As a result, the training process of the FNOs may become challenging and potentially prone to over‐fitting in small data regimes. [ 60,67 ] To overcome these limitations, the implicit neural operator architectures were proposed, [ 60,80,81 ] where the skip connections were added between the integral layers and all layers share the same set of trainable parameter, W , c , and ϕ. In particular, the architecture Equation was modified as: vl+1false(xfalse)=scriptIIFNOfalse[vl(x)false]:=vlfalse(xfalse)+1Lσfalse(Wvlfalse(xfalse)+scriptF1false[ϕ·scriptF[vlfalse(·false)]false](x)badbreak+cfalse)$$\begin{eqnarray} v_{l+1}(x)=\mathcal {I}^{IFNO}[v_l(x)]:&=& v_l(x)+\dfrac{1}{L}\sigma (Wv_l(x) \nonumber\\ && +\mathcal {F}^{-1}[\phi \cdot \mathcal {F}[v_l(\cdot)$$]](x)+ c) \end{eqnarray}As a result, the NO architecture has substantially smaller number of trainable parameters, while still serves as a universal approximator for fixed point PDE solvers.…”
Section: Methodsmentioning
confidence: 99%
“…Euonymus alatus [Euonymus alatus (Thunb.) Sieb], the twig outgrowths of celastraceae plants, contains compounds such as stigmast-4-en-3-one, quercetin, β-sitosterol, dehydrodicatechin, aromadendrin, d-catechin, 4 β-sitosterone, alatamine, and wilfordine (Lei et al, 2015;Rui-xi et al, 2015;Yanxiu et al, 2021). Ligustici (Ligusticum chuanxiong Hort), i.e., dried Ligusticum plant content, contains compounds such as tetramethylpyrazine, perlolyrine, ligustilide, wallichilide, senkyunolide, vanillic acid, caffeic acid, protocatechuic acid, and ferulic acid (Jiangang et al, 2019;Li Qian, 2020;Zhonghui et al, 2020).…”
Section: Chemical Components Of Shen Ma Yi Zhi Granulementioning
confidence: 99%
“…Safronova et al [13] studied x-ray radiant efficiency with different metals, experiment indicated the x-ray yields from mid-atomic-number (Ag) exceed twice those from low-atomic-number (Al) produced by PWA Z-pinch plasmas. Sheng et al [14] used PWA with a mixture of dielectric-coated wires and bare wires to observe the pinch process. They found that the surface insulation can increase the deposited energy and influence the evolution of ablation, implosion, and stagnation, while made little effect on magnetohydrodynamic instabilities or radiation yields.…”
Section: Introductionmentioning
confidence: 99%