Influence of oxide scales on the corrosion behaviors of B510L hot-rolled steel strips

The influence of oxide scales on the corrosion behaviors of B510 L hot-rolled steel strips was investigated in this study. Focused ion beams and scanning electron microscopy were used to observe the morphologies of oxide scales on the surface and cross sections of the hot-rolled steel. Raman spectroscopy and X-ray diffraction were used for the phase analysis of the oxide scales and corrosion products. The corrosion potential and impedance were measured by anodic polarization and electrochemical impedance spectroscopy. According to the results, oxide scales on the hot-rolled strips mainly comprise iron and iron oxides. The correlation between mass gain and test time follows a power exponential rule in the damp-heat test. The corrosion products are found to be mainly composed of γ-Fe OOH, Fe3O4, ？-Fe OOH, and γ-Fe2O3. The contents of the corrosion products are different on the surfaces of the steels with and without oxide scales. The steel with oxide scales is found to show a higher corrosion resistance and lower corrosion rate.

GU'S FUNCTION SCALE OF ION HYDRATION FORCE AND CHARGE SIZE

Water Vapor Chemistry" as a new science was discovered and established from trace analysis in Gu’s laboratory(Gu, 1991; Gu et al., 1991). Gu’s Function shows that the trace metal ion concentration in water vapor has positive correlation to"specific electron affinity constant"last ionization potential Iz/ion valence Z and negative correlation to ion volume V and coordination number N(Gu, 1994). Gu’s Func-tion C=f[(Iz/Z)/VN]of the bond parameter in water vapor chemistry corresponds to the potential energy function Z’ e2/r in the Schrodinger Equation of quantum chemistry. In different ions with the same 2+ charge, the ion concentration of water-water vapor transfer may be much different. This shows that the 2+ charge of different ions has different attractive force (hydration force). This different attractive force of the charge can be scaled with the relative energy or charge size from Gu’s Function.

DEFLECTION METHOD FROM TWO SIDES OXIDATION TO STUDY EFFECT OF Y ON INTERNAL STRESS OF OXIDE SCALES

Au investigation was carried ont of the effect of Y addition upon the internal stress of Al_2O_3 scale formed during oxidation of sputtering coating on Co-30Cr-6Al alloy and the growth stress of oxidized film on Fe-23Cr-5Al alloy heating up to 900℃ in air,using a specially designed deflection method from thin strip specimen with coat- ings,ion-implanted Y on one side and oxidized onto both sides.Results indicate that Y may decrease the internal stress of oxide scale on 2×10^(17) Y^+/cm^2 implanted Co- 30Cr-6Al coating,and increase one on 2×10^(16) Y^+/cm^2 implanted Fe-23Cr-5Al alloy. This seems due to whether or not Y promotes the plastic deformation of oxide scale.In addition,at initial oxidation stage,the change of growth stress of oxide scale formed on Y-implanted Co-30Cr-6Al coating may be related to the influence of Y on oxidation process of the coating.

Large scale silver nanowires network fabricated by MeV hydrogen (H＋) ion beam irradiation

A random two-dimensional large scale nano-network of silver nanowires （Ag-NWs） is fabricated by MeV hydrogen （H＋） ion beam irradiation. Ag-NWs are irradiated under H＋ ion beam at different ion fluences at room temperature. The Ag-NW network is fabricated by H＋ ion beam-induced welding of Ag-NWs at intersecting positions. H＋ ion beam induced welding is confirmed by transmission electron microscopy （TEM） and scanning electron microscopy （SEM）. Moreover, the structure of Ag NWs remains stable under H＋ ion beam, and networks are optically transparent. Morphology also remains stable under H＋ ion beam irradiation. No slicings or cuttings of Ag-NWs are observed under MeV H＋ ion beam irradiation. The results exhibit that the formation of Ag-NW network proceeds through three steps： ion beam induced thermal spikes lead to the local heating of Ag-NWs, the formation of simple junctions on small scale, and the formation of a large scale network. This observation is useful for using Ag-NWs based devices in upper space where protons are abandoned in an energy range from MeV to GeV. This high-quality Ag-NW network can also be used as a transparent electrode for optoelectronics devices.

Effects of information transmission delay and channel blocking on synchronization in scale-free Hodgkin-Huxley neuronal networks

In this paper,we investigate the evolution of spatiotemporal patterns and synchronization transitions in dependence on the information transmission delay and ion channel blocking in scale-free neuronal networks.As the underlying model of neuronal dynamics,we use the Hodgkin-Huxley equations incorporating channel blocking and intrinsic noise.It is shown that delays play a significant yet subtle role in shaping the dynamics of neuronal networks.In particular,regions of irregular and regular propagating excitatory fronts related to the synchronization transitions appear intermittently as the delay increases.Moreover,the fraction of working sodium and potassium ion channels can also have a significant impact on the spatiotemporal dynamics of neuronal networks.As the fraction of blocked sodium channels increases,the frequency of excitatory events decreases,which in turn manifests as an increase in the neuronal synchrony that,however,is dysfunctional due to the virtual absence of large-amplitude excitations.Expectedly,we also show that larger coupling strengths improve synchronization irrespective of the information transmission delay and channel blocking.The presented results are also robust against the variation of the network size,thus providing insights that could facilitate understanding of the joint impact of ion channel blocking and information transmission delay on the spatiotemporal dynamics of neuronal networks.

Schrodinger-Langevin Equation and Ion Transport atNano Scale

Schrodinger-Langevin equation has been constructed for the ion-transport for K-ion channel. The stability of the solutions of this equation has been discussed under various physical situations. This will shed new light on the ion transport at nano-scale as well as the possibility of ion trapping and quantum information processing.

基于锂离子电池电化学机理特性的电气等值模型研究

为更准确地表征低倍率充放电工况下电池内外部的动态状况,该文根据锂离子电池电化学原理推导出一种机理电气等值模型,明确机理电气等值模型相关电气元件参数的计算方法,揭示其与锂离子电池电化学参数之间的关联。所提机理电气等值模型兼具锂离子电化学模型的精度以及常规经验等效电路模型在储能控制参数整定、大规模储能电站等效建模方面便捷性的优势,更适用于新型电力系统场景下的储能电站建模、仿真、参数整定及安全监测。

重离子相对生物效应的双尺度模拟方法比较研究

重离子放射治疗是一种重要的癌症治疗手段,准确评估重离子的辐射生物效应对于提高粒子放疗的精细化水平具有重要意义。本研究基于双尺度剂量学方法和蒙特卡罗模拟,从宏观和微观两个尺度对^(12)C离子的相对生物效应(RBE)进行对比分析。本研究采用宏观的细胞存活线性平方模型(LQ)和微观的微剂量动力学模型(MKM)计算两个尺度的^(12)C离子RBE在体内的分布。蒙特卡罗模拟290 MeV/u的展宽^(12)C离子束在水模型内的宏观剂量及传能线密度(LET)分布,进而计算宏观^(12)C离子RBE。同时统计不同位置处体素内的粒子谱信息,并作为二次源项进行微剂量线能谱的模拟,进而计算微观尺度的^(12)C离子RBE。结果显示,10%细胞存活分数对应的物理剂量水平下,坪区两个尺度^(12)C离子RBE计算结果差异为16%,在布拉格峰处差异为25%。本研究提出了一种计算相同照射情况下宏观和微观两种尺度重离子RBE的模拟方法,并为重离子RBE模型的改进和临床应用提供参考。

离子微聚式物理除垢在油田供热系统中的应用

油田供热站锅炉,反冲洗水富含置换出来的钙镁离子,在高温下,造成反冲洗水管道结垢严重。通过介绍离子微聚式物理除垢技术原理,根据该技术在油田的应用分析,证实该技术在防垢除垢上的有效性,通过现场应用分析,可以看出离子微聚式防垢除垢效果明显,适用于污水排放管道系统。

锂离子电池汽车全尺寸火灾试验研究进展综述

分析近年来国内外发生的锂离子电池电动汽车火灾事故,对电动汽车的火灾风险进行简要概括。重点针对美国、加拿大、奥地利、瑞典、中国等国家在锂离子电池电动汽车全尺寸火灾试验及火灾防控方面的科研成果进行综述。根据国内外研究成果,对不同电池容量的锂离子电池电动汽车的热释放速率进行汇总,重点总结燃烧总热释放量、热释放速率峰值和释放有毒氟化氢气体与电池容量的关系。旨在为我国锂离子电池电动汽车火灾防控和火灾风险评估技术研究提供必要的数据参考。

基于混合尺度健康因子的LSTM-Transformer锂电池寿命预测

为提高锂电池剩余使用寿命(RUL)预测的精度,提出基于混合尺度健康因子的集成模型进行RUL预测。针对电池退化数据噪声大,数据量少和非线性特点捕捉不全的问题,首先提出奇异值分解(SVD)对电容信号处理,通过奇异值的能量分布优化变分模态分解(VMD)的最佳模态数,降噪重构出直接健康因子SR。提出一种幅度、相位双扰动(APP)的数据增强方法,依据SR数据分布变化,生成人工标记数据ESR,此ESR与电容相关系数均高于0.97。将SR、ESR结合GRA算法择取的3个间接健康因子,建立了更全面的混合尺度寿命特征信息;此外,为了避免单一模型预测的局限性,采用LSTM模型改进了Transformer结构中的解码器,引入新兴Optuna框架分析了影响模型预测精度的关键超参数并对它们进行了优化。最后通过NASA数据进行实验,并与RNN、LSTM、Transformer以及现有模型方法进行比较,结果证明RMSE控制在2.39%以内,MAE在1.59%以内,且预测性能受预测起点的影响小,稳定性更高,95%置信区间更窄。

基于多时间尺度Cholesky分解AEKF的锂电池SOC估计

建立可靠的锂电池荷电状态估算模型,获取精确估算值已成为锂离子电池组能源和安全管理的核心。选择锂离子电池的二阶等效电路模型为研究对象,提出了一种基于Cholesky分解优化多时间尺度自适应扩展卡尔曼滤波算法。状态方程中,对应不同状态变量子方程,选择不同采样周期,解决不同状态变量的不同时间尺度问题。考虑噪声变化,在扩展卡尔曼滤波的基础上,引入噪声的迭代估计,实现噪声的自适应矫正,结合Cholesky分解方法以克服计算的舍入误差问题。在不同工况下,选用不同型号的锂电池进行实验验证,验证该算法的普适性和有效性。

基于跳跃连接多尺度CNN的锂离子电池剩余寿命预测

为更好地利用卷积神经网络(CNN)中所有卷积层获取的特征信息,提出一种基于跳跃连接多尺度CNN的锂离子电池剩余寿命预测模型。该模型以电池的健康因子作为输入,利用基于跳跃连接的多尺度CNN模型,同时提取锂离子电池健康因子不同尺度的局部特征信息和全局特征信息,并通过信息融合模块融合所有的局部特征信息和全局特征信息,最后输出剩余寿命的预测值。实验结果表明,所提方法可更准确地预测锂离子电池剩余寿命,与经典的CNN方法、Bi-LSTM方法、EMD-LSTM方法和VMD-GRU方法相比,其均方根误差(ERMSE)分别降低75.7%、78.3%、83.8%、77.8%,平均绝对误差(EMAE)分别降低80.7%、80.9%、86.8%、82.3%,平均绝对百分误差(EMAPE)分别降低81.0%、82.2%、87.0%、83.1%,模型判定系数(R2)分别增加17.4%、23.2%、44.5%、25.8%。

The effect of inorganic salt precipitation on oil recovery during CO2 flooding:A case study of Chang 8 block in Changqing oilfield,NW China

Static experiments and dynamic displacement experiments were conducted to quantitatively determine the amount of precipitate generated by the CO_(2)-formation water reaction at different temperatures,pressures,and scaling ion concentrations during CO_(2) flooding in the Chang 8 block of Changqing Oilfield,the influence of precipitate on the physical properties of reservoirs was investigated,and the corresponding mathematical characterization model was established.The mathematical characterization equation was used to correct the numerical simulation model of E300 module in Eclipse software.The distribution pattern of inorganic salt precipitates during continuous CO_(2) flooding in Chang 8 block was simulated,and the influence of inorganic salt precipitates on oil recovery was predicted.The inorganic salt precipitate generated during CO_(2)-formation water reaction was mainly CaCO_(3),and the pressure difference and scaling ion concentration were proportional to the amount of precipitate generated,while the temperature was inversely proportional to the amount of precipitate.The rate of core porosity change before and after CO_(2) flooding was positively correlated with temperature and flooding pressure difference.The core porosity increase in the CO_(2)-formation water-core reaction experiment was always lower than that of CO_(2)-distilled water-core reaction experiment because of precipitation.The area around the production wells had the most precipitates generated with the injection of CO_(2).The oil field became poor in development because of the widely distributed precipitate and the recovery decreased to 33.45% from 37.64% after 20-year-CO_(2) flooding when considering of precipitation.

钙离子光时标守时技术研究

近年来光学频率标准(光钟)技术快速发展,国际时间频率咨询委员会计划于2030年用光钟重新定义“秒”,并提出了技术路线,光时标的研究也成为时间频率领域的研究热点。利用钙离子光钟驾驭微波氢钟,开展高精度光时标信号TS(Ca^(+))产生技术研究。结果表明,钙离子光钟准连续稳定运行率可达87%,稳定度达8×10^(-17)/day。对光钟和氢钟的频率比对测量分别采用微波频率锁定方案(上转换)和光生超稳微波方案(下转换),上转换方案引入了并放大了噪声,测量数据比氢钟稳定度差,而下转换方案产生超稳微波,测量数据频率稳定度与氢钟几乎重合,实现了光钟对氢钟的准确测量。将测量得到的频差数据直接置入相位微跃计,产生光时标TS(Ca^(+)),独立运行的光时标TS(Ca^(+))在一个月内与UTC偏差保持在0.6 ns以内。研究成果为报送秒定义数据和驾驭自由原子时TAI提供技术基础,为提升我国光时标守时能力提供了宝贵的技术支持和工程经验。

基于多维度多尺度特征的锂离子电池RUL估计方法

准确预测锂离子电池的剩余使用寿命(RUL)对储能系统的高效安全运行具有重要意义。针对已有数据驱动方法估计RUL中提取老化特征不够全面以及需要先预测健康状态变化再估计RUL的不足,本文提出一种利用多维度多尺度特征的RUL估计方法,采用恒流充电电压片段数据直接估计电池的RUL。该模型对数据进行维度变换后利用不同尺度卷积操作提取电压片段的老化特征来映射RUL。基于牛津大学、NASA、马里兰大学公开数据集进行模型验证,验证结果表明该模型能够利用电压片段数据直接估算电池的RUL,无需电池自身SOH变化作为训练数据,对比于基于单一维度的固定尺度的特征具有更高的准确性和通用性。

基于递归图多尺度特征的储能锂离子电池剩余寿命预测方法

锂离子电池在长期循环使用过程中不可避免地会出现性能退化,这直接影响储能锂离子电池系统的稳定运行。为此,本工作提出基于递归图多尺度特征的锂离子电池剩余寿命预测方法,用于解决从一维状态信号中提取关键退化特征的局限性。鉴于递归图像内蕴含丰富的时空退化特征,首先,构建深度学习多尺度特征提取架构,通过可变大小的感受野,识别同一电压区域在多个周期内的时间维度变化以及相邻电压区域之间空间维度的递归图像时空演变,进而提取深层多尺度特征,用于实现从多尺度特征到RUL的映射建模。再次,通过开展综合评估实验,对所提出方法的预测效果进行系统验证。研究结果表明,该方法使用有限数量的充电过程递归图作为输入,能实现模型快速收敛和准确预测。此外,在跨倍率预测场景中,相较于浅层指标,可实现在2C倍率下将绝对误差和均方根误差的指标性能提升约7倍和5.7倍。最后,通过开展与一维序列输入的对比实验,进一步验证基于递归图多尺度特征进行锂离子电池剩余寿命预测的有效性,实现了各评价指标约50%和43%的性能提升,同时成像所需时序电压采样点数据量相对较小。

基于KPCA-MTCN的锂离子电池故障诊断方法

为了维护储能系统的安全稳定运行,本文针对锂离子电池故障诊断这一重要问题,提出了一种结合核主成分分析(KPCA)和多尺度时序卷积网络(MTCN)的故障诊断方法.该方法首先归一化故障数据,然后利用KPCA降低数据维度并校验数据的可靠性;其次,根据故障类型对数据进行标注,并按比例划分训练集和测试集;接着在训练阶段使用霜冰算法(RIME)优化MTCN模型的超参数以提高模型的精度;最后基于故障数据验证MTCN的分类精度,并与长短期记忆神经网络(LSTM)、卷积神经网络(CNN)、Xception和ResNet50进行比较.在KPCA验证充电故障和未知故障数据的可靠性后,基于两组数据测试的结果表明,相比于CNN和LSTM,MTCN对于两组故障的分类准确率均为最高,分别达到了99.265%和99.688%,与Xception和ResNet50较为接近.同时针对训练数据量的测试结果表明,在训练数据量较少时MTCN仍能保持较好的诊断效果,说明MTCN的并行结构可以从不同的尺度提取更多的时序信息.

Conductivity Studies in Proton Irradiated AgI-Ag2O-V2O5-TeO2 Super-Ionic Glass System

The electrical properties of proton ion beam irradiated glass samples are carried out by impedance spectroscopy in the frequency range from 10 Hz to 32 MHz. The ion beam of energy 3 MeV and fluence of of 1014 particles cm-2 was chosen for irradiation. The conductivity of the super ionic glass samples increases after irradiation and other electrical parameters like dielectric constant, dielectric loss and modulus of the proton irradiated glass samples as a function of glass composition and temperature are observed to change. The dielectric constant and the dielectric losses are increased after irradiation and the modulus parameters confirm the non-Debye nature for irradiated samples also.

油田采出水结垢离子矿化浮选技术研究

随着油田开发进入中后期,采出液成分日益复杂,部分油田采出液中钙、镁等成垢离子含量高、矿化度高,导致地面管网流程、设施设备等结垢严重,成为影响油田降本增效及开发水平的主要因素之一。在对采出水一般物化特性深度认知的基础上,通过对不同水处理工艺的沉积物成分进行分析及产出机理研究,探索开展油田采出水成垢离子矿化浮选分离技术研究,建立了采出水结垢趋势模型,形成了采出水结垢离子的捕集方法、结垢离子复合体高效捕收方案,开发了泡沫浮选除垢技术及装备,设计并开展现场试验工艺方案优化。通过现场应用,现场连续运行试验达到了成垢离子去除率70%、沉积物产出量与现有技术相比降低30%以上的效果。研究表明,该矿化浮选工艺能有效降低采出水中成垢离子含量,同时实现处理成本低、沉积物产出量少的目标,可广泛应用于采出水处理、锅炉用水处理等方面。