Long-term product consistency test of simulated 90-19/Nd HLW glass

Chemical durability of 90-19/Nd glass, a simulated high-level waste (HLW) glass in contact with the groundwater was investigated with a long-term product consistency test (PCT). Generally, it is difficult to observe the long term property of HLW glass due to the slow corrosion rate in a mild condition. In order to overcome this problem, increased contacting surface (S/V = 6000 m⁻¹) and elevated temperature (150 °C) were employed to accelerate the glass corrosion evolution. The micro-morphological characteristics of the glass surface and the secondary minerals formed after the glass alteration were analyzed by SEM-EDS and XRD, and concentrations of elements in the leaching solution were determined by ICP-AES. In our experiments, two types of minerals, which have great impact on glass dissolution, were found to form on 90-19/Nd HLW glass surface when it was subjected to a long-term leaching in the groundwater. One is Mg-Fe-rich phyllosilicates with honeycomb structure; the other is aluminosilicates (zeolites). Mg and Fe in the leaching solution participated in the formation of phyllosilicates. The main components of phyllosilicates in alteration products of 90-19/Nd HLW glass are nontronite (Na_0.3Fe₂Si₄O₁₀(OH)₂·4H₂O) and montmorillonite (Ca_0.2(Al,Mg)₂Si₄O₁₀(OH)₂·4H₂O), and those of aluminosilicates are mordenite ((Na₂,K₂,Ca)Al₂Si₁₀O₂₄·7H₂O)) and clinoptilolite ((Na,K,Ca)₅Al₆Si₃₀O₇₂·18H₂O). Minerals like Ca(Mg)SO₄ and CaCO₃ with low solubility limits are prone to form precipitant on the glass surface. Appearance of the phyllosilicates and aluminosilicates result in the dissolution rate of 90-19/Nd HLW glass resumed, which is increased by several times over the stable rate. As further dissolution of the glass, both B and Na in the glass were found to leach out in borax form.     

结合迁移学习的轻量级指纹分类模型

目的 目前的指纹分类模型存在操作繁琐、参数较多、所需数据规模大、无法充分利用指纹特征信息等问题,而进行快速准确的指纹分类在大型指纹识别系统中至关重要。方法 传统的机器学习方法大多假设已标注数据与未标注数据的分布是相同的,而迁移学习允许源空间、任务空间在测试集和训练集中的分布是不同的,并且迁移学习仅专注目标任务的训练,使得网络模型根据需求更具个性化。因此,本文提出一种基于迁移学习的轻量级指纹分类模型。该模型结合迁移学习,首先采用梯度估计的方法求取指纹图像的方向场图并且做增强处理;然后将扩展的指纹方向场图数据集用于本文提出的轻量级Finger-SqueezeNet的预训练,使其达到一定的分类效果,从而初步实现网络模型参数的调整;最后保留预训练模型部分的网络参数不变,使用指纹图像数据集NIST-DB4对Finger-SqueezeNet网络进行参数微调（fine tuning）。结果 在使用相同的指纹数据集在本文提出的纯网络模型进行分类训练后发现,未采用迁移学习方法对网络模型进行预训练得到的平均分类结果为93%,而通过预训练后的网络模型可以达到98.45%,最终采用单枚指纹测试的方法得到的测试结果达到95.73%。对比同种类型的方法以及验证标准后可知,本文的指纹分类模型在大幅度减少网络参数的同时仍能达到较高的准确率。结论 采用指纹类内迁移学习方法和轻量级神经网络相结合进行分类,适当利用了指纹特征信息,而且有望使指纹分类模型拓展到移动端。     

机床功率监控系统的数学模型及其应用

从机床能量传输数学模型出发,首次建立了机床功率信息传感型监控系统（简称机床功率监控系统）的数学模型,提出了些模型在研究机床功率信息动态响应特性,提示功率住处随切削负载率和在外界干扰信息作用下的变化规律,识别刀具磨损、破损状态,诊断机械加工故障,测试机械加工过程中的某些机械量或电量等方面有着多种功能和用途,并列举了应用此模型提示机床功率监控系统中功率信息的迟滞响应特性的实例。     

环保型硫化促进剂CBBS在橡胶中的应用研究

研究环保型硫化促进剂CBBS在天然橡胶(NR)和丁苯橡胶(SBR)硫黄硫化体系胶料中的应用。结果表明:在NR炭黑补强胶料中促进剂CBBS胶料具有硫化活性高、硫化平坦性好、交联程度大的特点,促进剂CBBS的炭黑/白炭黑并用补强胶料的硫化特性和硫化物物理性能较优;在SBR炭黑补强胶料中促进剂CBBS胶料具有焦烧时间长和加工安全性好的特点,促进剂CBBS的炭黑/白炭黑并用补强胶料的硫化速度较慢,但硫化胶物理性能优异。     

基于物元模型的电力变压器故障的可拓诊断方法

为了提高传统的油中溶解气体分析的诊断能力,提出了一种定性与定量相结合的电力变压器故障的可拓诊断方法。首先基于可拓学中的物元理论,建立了定性地描述电力变压器故障诊断问题的物元模型;其次引入可拓集合中的关联函数,根据故障特征定量地计算故障发生的程度;最后以195台次电力变压器为例验证了该方法的有效性。结果表明该方法能够克服IEC三比值法中无法诊断多重故障和无匹配的故障编码的不足,且具有更高的诊断准确率。     

基于EJ299-33A探测器的核材料时间关联测量系统的时间分辨

n-γ的时间关联测量可提取核材料的质量、增殖因数,其中时间分辨是表征关联精度的1个重要指标。本文基于数字化数据获取与处理方法,对具有n-γ甄别能力的塑料闪烁体EJ299-33A探测器组成的核材料时间关联测量系统的时间分辨进行研究,采用⁶⁰Co与²²Na γ源进行了对比测量,分析了源对本征时间分辨的影响,进一步通过离线的条件加载反演,给出时间分辨的等效电子能量阈值依赖关系。通过对²⁵²Cf自发裂变时间关联谱的测量和解耦,讨论了时间分辨对不同符合事件的影响。结果表明：系统时间分辨随阈值增加而减少,在阈值为230 keVee时采用⁶⁰Co测量的结果约为560 ps,可满足核材料快时间符合测量的精度要求,而在相同条件下,由于正电子湮没位置的不确定性和延迟符合的影响,²²Na源测量的时间分辨展宽至816 ps;裂变事件时间关联测量中n-n符合受时间分辨的相对影响小于γ-γ符合。     

克拉玛依油田储集层中的沸石矿物及其与油气关系

沸石类矿物在克拉玛依油田石炭系、二叠系及三叠系的储集层都有分布.在石炭系火山岩(玄武岩)储集层中的沸石类矿物,与在二叠系(及三叠系)粗碎屑沉积岩储集层中的沸石矿物,从沸石矿物的种类及成因上都是不同的.这些矿物对于研究火山岩的蚀变作用以及粗碎屑沉积岩的成岩演化有着重要的意义,并对储集层的储集空间和渗流条件形成一定的影响.无论对火山岩储集层还是对碎屑沉积岩储集层,沸石矿物的存在都与油气的运移和富集有较密切的关系,在储量计算、油藏注水开发中,沸石矿物也有重要影响.     

输电阻塞管理的灵敏度分析模型及算法

在电力市场环境下，系统的运行方式将更加多变，发生输电阻塞的概率大为增加。文中提出了一种利用灵敏度分析进行实时阻塞管理的数学模型及算法，即在出现阻塞时，根据注入功率与支路潮流的灵敏度来削减对阻塞影响最大的发电出力或负荷，从而有效地消除阻塞。针对阻塞管理的实时性要求及阻塞只与局部电网有关的特点，采用部分求逆及稀疏矢量法等措施，使算法快速、实用。最后通过算例系统的计算，验证了所提算法的正确性和有效性。     

Swelling and thermal properties of porous PNIPAM/PEG hydrogels prepared by radiation polymerization

In this study,a series of porous intelligent hydrogels were synthesized by radiation exhibiting the lower critical solution temperature（LCST） and fast response involving a combination of A’-isopropyl acrylamideas monomer, polyethylene glycol（PEG） as pore-forming agent and N,N-methylene-bis-acrylamide as crosslinking agent.The hydrogels were analyzed by Fourier transform infrared spectroscopy,and the influence of radiation doses on their swelling and thermal behaviors were studied.Their surface morphologies were examined by scanning electron microscopy.The results showed that PEG molecules only acted as pore-forming agent in the cross-linked polymerization.Their swelling ratios reduced with increasing radiation doses.The LCST was around 37℃,and varied little with the radiation doses.The frozen water content of PNIPAM/PEG₆₀₀₀ hydrogel reduced with increasing the radiation dose,and was greater than that of PN1PAM hydrogel at 15 kGy.Hydrogel macropores were prepared by PEG agent,and the hydrogels without PEG had a dense surface.The porous hydrogels are expected to be applied in the field of artificial intelligence material.     

Failure initiation and propagation of Li4SiO4 pebbles in fusion blankets

Lithium orthosilicate (Li₄SiO₄) pebbles are considered to be a candidate as solid tritium breeder in the helium cooled pebble bed (HCPB) blanket. These ceramic pebbles might be crushed during thermomechanical loading in the blanket. In this work, the failure initiation and propagation of pebbles in pebble beds is investigated using the discrete element method (DEM). Pebbles are simplified as mono-sized elastic spheres. Every pebble has a contact strength in terms of critical strain energy, which is derived from a validated strength model and crush test data for pebbles from a specific batch of Li₄SiO₄ pebbles. Pebble beds are compressed uniaxially and triaxially in DEM simulations. When the strain energy absorbed by a pebble exceeds its critical energy it fails. The failure initiation is defined as a given small fraction of pebbles crushed. It is found that the load level for failure initiation can be very low. For example, if failure initiation is defined as soon as 0.02% of the pebbles have been crushed, the pressure required for uniaxial loading is about 2.5 MPa. Therefore, it is essential to study the influence of failure propagation on the macroscopic response of pebble beds. Thus a reduction ratio defined as the size ratio of a pebble before and after its failure is introduced. The macroscopic stress–strain relation is investigated with different reduction ratios. A typical stress plateau is found for a small reduction ratio.