无失效数据机载多余度EWIS可靠性研究

针对高可靠度机载多余度EWIS各组成部分寿命服从指数分布但参数未知的情况，提出采用无失效数据可靠度分析方法评估EWIS的可靠度水平。通过Monte-Carlo仿真方法对连接形式为“先并联、后串联”EWIS各组成部分寿命进行抽样，利用“最小最大值”方法获得系统寿命的抽样值，用概率纸检验法初步判断EWIS寿命是否服从威布尔分布，再用Pearson拟合优度检验法判断EWIS寿命是否服从威布尔分布。结合无故障飞行时间的样本值与EWIS寿命服从威布尔分布的假设，采用无失效数据分析方法评估EWIS的可靠度水平。研究方法对机载多余度EWIS无失效数据可靠度分析有一定的贡献。     

Simulation Study on Hydrogen-Heating-Power Poly-Generation System based on Solar Driven Supercritical Water Biomass Gasification with Compressed Gas Products as an Energy Storage System

Supercritical water gasification driven by solar energy is a promising way for clean utilization of biomass with high moisture content, but direct discharge of liquid residual causes energy waste and decreases energy efficiency. To reduce energy waste, a poly-generation system for hydrogen-rich gas production coupling heat supply and power generation based on supercritical water gasification of biomass driven by concentrated solar energy was established in this paper, which also provided a novel energy storage method to overcome the shortcomings of solar discontinuity. Thermodynamic model of the system was proposed and life cycle assessment(LCA) of the system was conducted. Influence of different parameters(temperature of 600℃ to 800℃, outlet temperature of heat exchanger of 42℃ to 56℃, biomass slurry concentration of 5% to 6.5%) on the gasification performance, energy and exergy efficiency, energy distribution and global warming potential(GWP) was discussed. The results indicated that hydrogen yield increased as gasification temperature increased since free radical reaction was enhanced which gas production reaction was classified into. Molar fraction of hydrogen increased as gasification temperature increased and reached 65.6% at 750℃. Energy and exergy efficiency of the system reached 74.84% and 34.87% at 700℃ and 600℃ respectively and that of gas production was 18.15% at 650℃, which was the highest. Increasing reaction temperature and decreasing biomass slurry concentration were effective ways to decrease GWP. Optimal operating parameter was reaction temperature of 650℃, outlet temperature of heat exchanger of 50℃ and biomass concentration of 5%.     

316L不锈钢non-Masing特性分析和疲劳寿命预测

对316L不锈钢在不同应变范围下分别进行了293 K和873 K试验温度下的低周疲劳试验，讨论了材料循环特性的幅值相关性和温度相关性，比较了不同条件下non-Masing特性，并利用能量方法进行了低周疲劳寿命预测。实验结果表明, 在不同条件下，循环初期会出现不同程度的循环硬化现象，随后会出现循环软化、饱和直至材料失效；与873 K 试验条件相比，材料在293 K温度下的non-Masing特性更为显著；在大应变范围下，两温度下材料的non-Masing特性更加明显。采用能量方法进行疲劳寿命预测时，预测结果均位于两倍分散带内，且基于non-Masing特性得到了比基于Masing特性更为精确的预测结果。在873 K温度和大应变范围下，显著的动态应变时效效应导致考虑non-Masing与Masing特性的预测结果相差不大。     

A Step toward Molecular Evolution of RNA: Ribose Binds to Prebiotic Fatty Acid Membranes,and Nucleosides Bind Better than Individual Bases Do

A major challenge in understanding how biological cells arose on the early Earth is explaining how RNA and membranes originally colocalized. We propose that the building blocks of RNA (nucleobases and ribose) bound to self-assembled prebiotic membranes. We have previously demonstrated that the bases bind to membranes composed of a prebiotic fatty acid, but evidence for the binding of sugars has remained a technical challenge. Here, we used pulsed-field gradient NMR spectroscopy to demonstrate that ribose and other sugars bind to membranes of decanoic acid. Moreover, the binding of some bases is strongly enhanced when they are linked to ribose to form a nucleoside or – with the addition of phosphate – a nucleotide. This enhanced binding could have played a role in the molecular evolution leading to the production of RNA.     

高速列车转向架构架损伤、等效应力及寿命分布特性研究

为分析高速列车转向架构架损伤、等效应力及寿命分布特性，对构架疲劳关键测点进行动应力线路实测并对测点实测时域数据波形进行解析；基于实测应力时间历程及雨流计数法编制二维应力谱，利用Goodman等寿命方程将二维应力谱等效转换为一维应力谱；阐述线性累积损伤及非线性累积损伤模型的建立方法并对实测数据的线性累积损伤及非线性累积损伤进行了计算及对比分析；分别基于线性累积损伤理论及非线性累积损伤理论推导出各理论下的等效应力，基于实测数据对两种等效应力进行了计算及对比分析；通过结合非线性累积损伤及线性累积损伤理论计算的等效应力及不同可靠度下的材料S-N曲线计算并对比分析构架结构的疲劳寿命。研究结果表明，与非线性疲劳分析理论相比，线性疲劳分析理论对高速列车转向架构架的疲劳特性评估偏于保守。     

A novel PEM fuel cell remaining useful life prediction method based on singular spectrum analysis and deep Gaussian processes

Accurate remaining useful life (RUL) prediction of proton exchange membrane fuel cells (PEMFCs) can assess the reliability of fuel cells to determine the occurrence of failures and mitigate their operational risk. However, is it quite challenging to design a high-precision prediction method because the implicit degradation details of PEMFCs are difficult to learn well from the measurement data with high-frequency noise. Recognizing this, a novel RUL prediction method based on singular spectrum analysis (SSA) and deep Gaussian process (DGP) is proposed in this paper. The SSA-based method is firstly employed to preprocess the measurement data, which can strengthen the effective information of PEMFC degradation data at the same time remove the noise and spikes that interfere with degradation prediction. As a deep structural model, DGP has strong feature learning ability which can represent the nonlinear details of degradation data and give more accurate prediction results. At the same time, it serves as a probabilistic model that can provide the confidence interval to enhance reliability of RUL prediction. The effectiveness of the proposed method is evaluated by experimental data of the PEMFCs under steady-state conditions, and the results show that the SSA-DGP method has higher accuracy and reliability than conventional methods.     

Performance degradation prediction of proton exchange membrane fuel cell using a hybrid prognostic approach

The proton exchange membrane fuel cell has been widely used for industrial systems; however, its performance gradually degrades during use. Therefore, the study on the performance degradation prediction of fuel cells is helpful to extend its lifespan. In this paper, a novel hybrid approach using a combination of model-based adaptive Kalman filter and data-driven NARX neural network is proposed to predict the degradation of fuel cells. The overall degradation trend (i.e., irreversible degradation process) is captured by an empirical aging model and adaptive Kalman filter. Meanwhile, the detail degradation information (i.e., reversible degradation process) is depicted by the NARX neural network. Moreover, the correlation analysis of the reversible voltage time series is carried out to obtain the number of delays of the NARX neural network based on the autocorrelation function and the partial autocorrelation function. Then, the total degradation prediction is the sum of the overall degradation prediction and the detail degradation prediction. Finally, the prognostic capability of the proposed method is verified by two aging datasets, and the results show the effectiveness and superiority of the proposed method which can provide accurate degradation forecasting and remaining useful life.     

Improved properties of scandia and yttria co-doped zirconia as a potential thermal barrier material for high temperature applications

Due to the limited temperature capability of current YSZ thermal barrier coating (TBC) material, considerable effort has been expended world-wide to research new candidates for TBC applications above 1200?°C. Our study suggested that Sc₂O₃ and Y₂O₃ co-doped ZrO₂ (ScYSZ) had excellent t’ phase stability even after annealed at 1500?°C for 336?h. The thermal expansion coefficient of ScYSZ was comparable to the value of YSZ. The thermal conductivity of fully dense ScYSZ was in the range of 2.13–1.91?W?m^?1?K^?1 (25–1300?°C), approximately 25% lower than that of YSZ. Although the fracture toughness of dense ScYSZ was slightly lower than YSZ, an evident decline in elastic modulus was found. Additionally, thermal cycling lifetime of plasma sprayed ScYSZ coating (914 cycles) at 1300?°C was about 2.6 times longer than its YSZ counterpart. The superior comprehensive properties confirm that ScYSZ is a prospective candidate material for high-temperature TBC application.     

基于Bootstrap方法的密封寿命可靠性评估

针对高可靠、长寿命密封件在小样本试验下的可靠性寿命评估需求,提出一种基于虚拟增广样本和Bootstrap方法的密封寿命小样本数据可靠性评估方法。并以轴用阶梯圈为例,进行寿命可靠性评估。首先通过虚拟增广法将轴用阶梯圈台架寿命试验数据样本数增广至10个,使得样本数满足Bootstrap方法的适用条件;然后再利用Bootstrap方法得到轴用阶梯圈的寿命可靠性评估结果。     

脉冲电磁处理参数对YT15硬质合金服役寿命的影响

采用COMSOL Multiphysics有限元分析软件对脉冲电磁处理设备进行仿真建模,利用正交试验的方法研究了磁通密度、磁脉冲个数、脉冲电压、电脉冲组数对YT15硬质合金刀具服役寿命的影响规律。通过极差分析得到了各因素的影响主次关系以及最佳脉冲电磁处理参数,并分析了切削过程的主切削力及磨损量变化,结果表明:脉冲电磁处理可使YT15硬质合金刀具服役寿命增长57.2%;最佳的处理参数组合为磁通密度2T,磁脉冲个数10,脉冲电压0.8V,电脉冲组数20;磁通密度和磁脉冲个数对其寿命影响较大,脉冲电压和电脉冲组数影响较弱;脉冲电磁处理后的刀具切削力较未处理有所降低,后刀面磨损速度明显减缓。