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class="fas fa-envelope" style="color: #4a7dbe;"></i></a></div></div><div id="scroll-down"><i class="fas fa-angle-down scroll-down-effects"></i></div></header><main class="layout" id="content-inner"><div class="recent-posts" id="recent-posts"><div class="recent-post-item"><div class="post_cover left"><a href="/2025/02/12/Deep%20learning%20via%20CNN%20for%20identification%20of%20blue%20core%20phenomenon%20in%20helicon%20plasma%20discharge/" title="Deep learning via CNN for identification of blue core phenomenon in helicon plasma discharge"><img class="post-bg" src="https://source.unsplash.com/1920x1080/?plasma" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="Deep learning via CNN for identification of blue core phenomenon in helicon plasma discharge"></a></div><div class="recent-post-info"><a class="article-title" href="/2025/02/12/Deep%20learning%20via%20CNN%20for%20identification%20of%20blue%20core%20phenomenon%20in%20helicon%20plasma%20discharge/" title="Deep learning via CNN for identification of blue core phenomenon in helicon plasma discharge">Deep learning via CNN for identification of blue core phenomenon in helicon plasma discharge</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2025-02-12T06:31:17.000Z" title="Created 2025-02-12 14:31:17">2025-02-12</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E6%96%87%E7%8C%AE/">文献</a></span></div><div class="content">AbstractBased on deep learning image recognition techniques, a Convolutional Neural Network (CNN) model for discharge modes recognition of helicon plasma was trained. The accuracy of the model was evaluated using functions such as F1-score and confusion matrix. The final recognition accuracy was more than 98.18% after 30 iterations. Interpretable analysis was done using methods such as Gradient-weighted Class Activation Mapping (Grad-CAM) to verify the model’s robustness as well as repeatability ...</div></div></div><div class="recent-post-item"><div class="post_cover right"><a href="/2023/10/25/Relationship-of-mode-transitions-and-standing-waves-in-helicon-plasmas/" title="Relationship of mode transitions and standing waves in helicon plasmas"><img class="post-bg" src="https://source.unsplash.com/1920x1080/?plasma" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="Relationship of mode transitions and standing waves in helicon plasmas"></a></div><div class="recent-post-info"><a class="article-title" href="/2023/10/25/Relationship-of-mode-transitions-and-standing-waves-in-helicon-plasmas/" title="Relationship of mode transitions and standing waves in helicon plasmas">Relationship of mode transitions and standing waves in helicon plasmas</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2023-10-25T11:30:28.000Z" title="Created 2023-10-25 19:30:28">2023-10-25</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E6%96%87%E7%8C%AE/">文献</a></span></div><div class="content">螺旋子等离子体中的模式转换与驻波的关系
摘要螺旋波等离子体（HWP）源具有众所周知的高效率和高等离子体密度的优点，在许多领域有着广泛的应用。其关键机制在于模式转换，这也是多年来的一个突出问题。我们建立了一个流体模拟模型，并进一步开发了北京大学螺旋放电（PHD）代码。首次在模拟中再现了单回路天线放电的模式转换（也称为密度跃迁）。研究发现，大振幅 SHWs 是模式转换的原因，这与用于激光发生的谐振腔的模式转换类似。本文试图给出一个完整而定量的驻留谐振波（SHW）共振理论，以解释模式转换与 SHW 的关系。驻留螺旋波共振理论合理地解释了螺旋子等离子体中的几个关键问题，如模式转换和高效功率吸收，有助于改进未来的等离子体生成方法。
</div></div></div><div class="recent-post-item"><div class="post_cover left"><a href="/2023/10/14/Effects-of-magnetic-field-on-electron-power-absorption-in-helicon-fluid-simulation/" title="Effects of magnetic field on electron power absorption in helicon fluid simulation"><img class="post-bg" src="https://source.unsplash.com/1920x1080/?plasma" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="Effects of magnetic field on electron power absorption in helicon fluid simulation"></a></div><div class="recent-post-info"><a class="article-title" href="/2023/10/14/Effects-of-magnetic-field-on-electron-power-absorption-in-helicon-fluid-simulation/" title="Effects of magnetic field on electron power absorption in helicon fluid simulation">Effects of magnetic field on electron power absorption in helicon fluid simulation</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2023-10-14T08:09:12.000Z" title="Created 2023-10-14 16:09:12">2023-10-14</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E6%96%87%E7%8C%AE/">文献</a></span></div><div class="content">磁场对螺旋流体模拟中电子功率吸收的影响
摘要本研究开发了一种名为 “北京大学螺旋放电”（PHD）的代码，可以模拟背景磁场大于 500 G 和压力小于 1 Pa 的螺旋放电过程。代码中使用了两个流体方程。PHD 模拟得出了两个重要发现：（1）等离子体密度随背景磁场的时间演化呈现出第二次快速增长（称为第二次密度跃迁），类似于螺旋子等离子体中的模式转换；（2）在存在磁场的情况下，电子功率吸收的峰值位置出现在中心轴附近，这与没有磁场的情况不同。这些结果可能有助于加深对放电机制的理解。
介绍螺旋等离子体具有高等离子体密度、低压运行、稳态放电、高功率耦合效率以及等离子体区域无需电极等理想特性。除了用于等离子体研究以及可变比冲磁等离子体火箭、氦质子等离子体推进器和氦质子双层推进器等应用[1-7]，它们还因其多种优势而被用于材料加工[1, 8]。
关于螺旋子等离子体放电机制的统一理论尚未建立[9]。氦质子等离子体主要表现出电磁和静电两种耦合模式。电磁模式为弱阻尼，称为氦子波，而静电模式为强阻尼，称为 Trivelpiece-Gould (T-G) 波 [10-12]。陈指出，朗道阻尼机制在螺旋子放电中 ...</div></div></div><div class="recent-post-item"><div class="post_cover right"><a href="/2023/10/07/Damping-characteristics-of-helicon-and-Trivelpiece%E2%80%93Gould-waves-in-high-density-and-low-magnetic-field-helicon-plasma/" title="Damping characteristics of helicon and Trivelpiece–Gould waves in high density and low magnetic field helicon plasma"><img class="post-bg" src="https://source.unsplash.com/1920x1080/?plasma" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="Damping characteristics of helicon and Trivelpiece–Gould waves in high density and low magnetic field helicon plasma"></a></div><div class="recent-post-info"><a class="article-title" href="/2023/10/07/Damping-characteristics-of-helicon-and-Trivelpiece%E2%80%93Gould-waves-in-high-density-and-low-magnetic-field-helicon-plasma/" title="Damping characteristics of helicon and Trivelpiece–Gould waves in high density and low magnetic field helicon plasma">Damping characteristics of helicon and Trivelpiece–Gould waves in high density and low magnetic field helicon plasma</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2023-10-07T03:15:01.000Z" title="Created 2023-10-07 11:15:01">2023-10-07</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E6%96%87%E7%8C%AE/">文献</a></span></div><div class="content">高密度和低磁场螺旋子等离子体中螺旋子波和 Trivelpiece-Gould 波的阻尼特性
摘要通过采用暖等离子体模型并考虑介电张量元素中的回旋谐波效应，研究了在高密度（1x1013 cm 3）、低磁场（30-50 G）和中低中性气压（0.5-10mTorr）的螺旋子等离子体中，螺旋波和Trivelpiece-Gould（TG）波的方位对称模由于碰撞和动力学阻尼而产生的功率沉积特性。理论计算表明，磁场对螺旋子波和 TG 波之间的模耦合表面特性有显著影响；在典型的螺旋子等离子体电子温度范围 Te∈(3, 5) eV 中，存在临界中性气体压力，低于或高于该压力时，不同阻尼机制产生的不同波在功率沉积中起主导作用；同时，在低中性气体压力（~0.5 mTorr）情况下，朗道阻尼产生的 TG 波在功率沉积中起主导作用，随着磁场的增加，这种主导作用逐渐增强。
介绍</div></div></div><div class="recent-post-item"><div class="post_cover left"><a href="/2023/09/28/vue/" title="vue"><img class="post-bg" src="https://source.unsplash.com/1920x1080/?plasma" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="vue"></a></div><div class="recent-post-info"><a class="article-title" href="/2023/09/28/vue/" title="vue">vue</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2023-09-28T02:48:17.000Z" title="Created 2023-09-28 10:48:17">2023-09-28</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E5%89%8D%E7%AB%AF/">前端</a></span></div><div class="content">之前在idea上写过的vue代码找不到了，为了防止下次再找不到，写一个md记录一下。
vue 的安装需要15版本以上的npm
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1npm init vue@lastest
根据需求选择合适的开发环境
12345678√ Project name: ... vue01√ Add TypeScript? ... No / Yes√ Add JSX Support? ... No / Yes√ Add Vue Router for Single Page Application development? ... No / Yes√ Add Pinia for state management? ... No / Yes√ Add Vitest for Unit Testing? ... No / Yes√ Add an End-to-End Testing Solution? » No√ Add ESLint for code quality? ... No / Yes
执行
123cd vue01(创建项目的文件夹)npm installnpm run dev
项目基本文件如图（ ...</div></div></div><div class="recent-post-item"><div class="post_cover right"><a href="/2023/09/21/diffusion-model/" title="diffusion model"><img class="post-bg" src="https://source.unsplash.com/1920x1080/?plasma" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="diffusion model"></a></div><div class="recent-post-info"><a class="article-title" href="/2023/09/21/diffusion-model/" title="diffusion model">diffusion model</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2023-09-21T12:47:03.000Z" title="Created 2023-09-21 20:47:03">2023-09-21</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/">机器学习</a></span></div><div class="content">采样-ddpm神经网络尝试在每一步都完整预测噪点
对于预测到的噪点，我们使用原有的噪点图减去预测的噪点图，就会获得一个稍微清晰一点的图片。但是它并没有完全去除所有的噪点，所以需要很多步迭代才能获得较高质量的采样。
但是这种的神经网络需要类似这种正态分布的噪点样本作为输入，所以在每一次迭代需要加入额外的噪点。这样有利于稳定神经网络算法来区分接近数据集的平均值的样本。意思是，如果不加相应的噪点，nn只会生成相似的样本。
diffusion model的nn被称为UNet
UNet可以嵌入更多的信息，包括时间信息，上下文信息。
训练对样本加个噪点，然后让nn去算，然后相减，计算出loss，然后反向传播
为了让训练更加稳定，对每个样本选择随机的时间信息（迭代次数）。
控制样本通过嵌入上下文来控制训练模型。
比如你有一张牛油果的图片，然后有一句话”一颗成熟的牛油果“，然后你可以将加噪点的图片和这句话一同放入nn进行训练。
此时你有一个椅子的模型，就可以预测一个牛油果椅子。
上下文是一个可以控制生成的向量，可以是一句话，也可以是几个简短的关键字。
加速采样–ddim传统的采样需要很多时 ...</div></div></div><div class="recent-post-item"><div class="post_cover left"><a href="/2023/09/18/Physical-Properties-of-a-Low-Power-Helicon-Source-Operating-on-a-High-Frequency-Discharge-with-a-Capacitive-Component/" title="Physical Properties of a Low-Power Helicon Source Operating on a High-Frequency Discharge with a Capacitive Component"><img class="post-bg" src="https://source.unsplash.com/1920x1080/?plasma" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="Physical Properties of a Low-Power Helicon Source Operating on a High-Frequency Discharge with a Capacitive Component"></a></div><div class="recent-post-info"><a class="article-title" href="/2023/09/18/Physical-Properties-of-a-Low-Power-Helicon-Source-Operating-on-a-High-Frequency-Discharge-with-a-Capacitive-Component/" title="Physical Properties of a Low-Power Helicon Source Operating on a High-Frequency Discharge with a Capacitive Component">Physical Properties of a Low-Power Helicon Source Operating on a High-Frequency Discharge with a Capacitive Component</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2023-09-18T12:46:06.000Z" title="Created 2023-09-18 20:46:06">2023-09-18</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E6%96%87%E7%8C%AE/">文献</a></span></div><div class="content">利用带电容元件的高频放电运行的低功率螺旋源的物理特性
abstract本文介绍了对放置在纵向磁场中的低功率射频等离子体源（螺旋推进器）进行实验研究的结果，该等离子体源在电容射频放电和带有电容成分的感应射频放电中工作。结果表明，离子源的离子流和电子流特性与恒定磁场的感应有很大关系。在所研究的等离子体源中，电容性射频放电作为一种工作过程的基本适用性得到了证明。研究表明，随着放电中电容成分的出现，离子源出口处离子流的平均能量会略有增加。
introduction伴随着航天工业的发展，所用航天器的功率和质量范围也在不断扩大，这反过来又使得开发新型高效机载电动火箭推进器（ERT）变得尤为重要。同时，由电子补偿离子束（即不需要补偿阴极）的 ERT 方案对许多实际应用特别有吸引力。特别是，低轨道（200-400 公里）的成功开发需要这种 ERT，因为那里有残余大气，而传统的阴极方案由于氧化过程而不适用。
有希望获得补偿离子通量的 ERT 设计是螺旋推进器（HT）。其工作原理详见文献[1-5]。在此，我们仅简要说明该装置基于纵向外磁场中的感应射频（RF）放电。在气体放电室（GDC）中产生的等离子体从出 ...</div></div></div><div class="recent-post-item"><div class="post_cover right"><a href="/2023/09/04/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E5%B0%8Ftips/" title="深度学习小tips"><img class="post-bg" src="https://source.unsplash.com/1920x1080/?plasma" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="深度学习小tips"></a></div><div class="recent-post-info"><a class="article-title" href="/2023/09/04/%E6%B7%B1%E5%BA%A6%E5%AD%A6%E4%B9%A0%E5%B0%8Ftips/" title="深度学习小tips">深度学习小tips</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2023-09-04T01:12:54.000Z" title="Created 2023-09-04 09:12:54">2023-09-04</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0/">机器学习</a></span></div><div class="content">
用Tensorflow API:tf.keras搭建网络八
六步法
import
train, test
model = tf.keras.models
Sequentialmodel.compile
# 描述各层的网络结构
Sequentialmodel
拉直层：tf.keras.layers.Flatten()
全连接层：tf.keras.layers.Dense(神经元个数,activation="激活函数“, kernel_regularizer=哪种正则化)
(activation（字符串给出）可选: relu、softmax、sigmoid、tanh
kernel_regularizer可选: tf.keras.regularizers.l1()、tf.keras.regularizers.l2())
卷积层：tf.keras.layers.Conv2D(filters =卷积核个数,kernel_size=卷积核尺寸，strides=卷积步长，padding = "valid" o ...</div></div></div><div class="recent-post-item"><div class="post_cover left"><a href="/2023/08/30/Characteristics-of-temporal-evolution-of-particle-density-and-electron-temperature-in-helicon-discharge/" title="Characteristics of temporal evolution of particle density and electron temperature in helicon discharge"><img class="post-bg" src="https://source.unsplash.com/1920x1080/?plasma" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="Characteristics of temporal evolution of particle density and electron temperature in helicon discharge"></a></div><div class="recent-post-info"><a class="article-title" href="/2023/08/30/Characteristics-of-temporal-evolution-of-particle-density-and-electron-temperature-in-helicon-discharge/" title="Characteristics of temporal evolution of particle density and electron temperature in helicon discharge">Characteristics of temporal evolution of particle density and electron temperature in helicon discharge</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2023-08-30T06:04:27.000Z" title="Created 2023-08-30 14:04:27">2023-08-30</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E6%96%87%E7%8C%AE/">文献</a></span></div><div class="content">螺旋放电粒子密度和电子温度随时间演化特征
0 abstract在详细考虑电化学反应和碰撞关系的基础上，采用三维二流体方程的螺旋等离子体放电直接数值模拟模型，研究了粒子密度和电子温度随时间演化的特征。在弱电离的假设下，在整个计算域中直接求解与等离子体参数耦合的麦克斯韦方程组。所有偏微分方程均由 COMSOL MultiphysicsTM 中的有限元求解器采用全耦合方法求解。在这项工作中，数值案例是使用 Ar 工作介质和 Shoji 型天线进行计算的。数值结果表明，电子和基原子密度存在两种不同的时间演化模式，这可以通过离子泵浦效应来解释。电子温度的演变由两种方案控制：电磁波加热和粒子碰撞冷却。高射频功率导致高峰值电子温度，而高气压导致低稳定温度。此外，利用改进的CR模型进行了9条Ar I谱线的OES实验，通过模拟验证了结果的有效性，表明电子密度和温度的时间演化趋势与数值模拟结果吻合良好。
1 instruction由于螺旋放电可以以相对适中的输入功率产生均匀、高密度的等离子体，因此已广泛应用于等离子体蚀刻和薄膜沉积。在这十年中，太空电力推进领域受到越来越多的关注[1, 2]。脉冲螺旋等离子 ...</div></div></div><div class="recent-post-item"><div class="post_cover right"><a href="/2023/08/29/Design-of-a-novel-high-efficiency-antenna-for-helicon-plasma-sources/" title="Design of a novel high efficiency antenna for helicon plasma sources"><img class="post-bg" src="https://source.unsplash.com/1920x1080/?plasma" onerror="this.onerror=null;this.src='/img/404.jpg'" alt="Design of a novel high efficiency antenna for helicon plasma sources"></a></div><div class="recent-post-info"><a class="article-title" href="/2023/08/29/Design-of-a-novel-high-efficiency-antenna-for-helicon-plasma-sources/" title="Design of a novel high efficiency antenna for helicon plasma sources">Design of a novel high efficiency antenna for helicon plasma sources</a><div class="article-meta-wrap"><span class="post-meta-date"><i class="far fa-calendar-alt"></i><span class="article-meta-label">Created</span><time datetime="2023-08-29T13:05:56.000Z" title="Created 2023-08-29 21:05:56">2023-08-29</time></span><span class="article-meta"><span class="article-meta-separator">|</span><i class="fas fa-inbox"></i><a class="article-meta__categories" href="/categories/%E6%96%87%E7%8C%AE/">文献</a></span></div><div class="content">一种新型螺旋等离子体源高效天线的设计
abstract为螺旋等离子体源提出了一种新的天线配置，可以增加吸收功率和等离子体密度。使用标准 COMSOL Multiphysics 5.3 软件分析了电磁波图案对称性对具有普通天线的螺旋等离子体源（名古屋）中等离子体密度和吸收功率的影响。与理论模型预测相反，电磁波并不代表普通名古屋天线的对称图案。在这项工作中，提出了一种新的天线配置，它改善了螺旋等离子体源中波形的不对称性。通过模拟研究了相同条件下普通名古屋天线和我们提出的天线的等离子体参数，例如等离子体密度和吸收率。此外，将具有通用名古屋天线的七个运行螺旋等离子体源装置的等离子体密度与我们提出的天线和通用名古屋天线的仿真结果进行了比较。模拟结果表明，使用我们提出的天线产生的等离子体密度大约是使用普通名古屋天线产生的等离子体密度的两倍。事实上，模拟结果表明，螺旋波的电场和磁场对称性对于增强波粒耦合起着至关重要的作用。结果，波粒能量交换和螺旋等离子体源的等离子体密度将增加。
instructionHelicon 等离子体源产生低温、高密度和低压等离子体（Chen 2006）。如今，方便且经济的螺 ...</div></div></div><nav id="pagination"><div class="pagination"><span class="page-number current">1</span><a class="page-number" href="/page/2/#content-inner">2</a><span class="space">…</span><a class="page-number" href="/page/11/#content-inner">11</a><a class="extend next" rel="next" href="/page/2/#content-inner"><i class="fas fa-chevron-right fa-fw"></i></a></div></nav></div><div class="aside-content" id="aside-content"><div class="card-widget card-info"><div class="is-center"><div class="avatar-img"><img src="/pic/avatar.png" onerror="this.onerror=null;this.src='/img/friend_404.gif'" alt="avatar"/></div><div class="author-info__name">SHYEE</div><div class="author-info__description"></div></div><div class="card-info-data site-data is-center"><a href="/archives/"><div class="headline">Articles</div><div class="length-num">106</div></a><a href="/tags/"><div class="headline">Tags</div><div class="length-num">107</div></a><a 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