部件寿命服从威布尔分布时典型系统的寿命与剩余寿命估计

在实际工程中,对系统寿命以及剩余寿命的估计非常重要。在已知系统中部件寿命与可靠度的前提下,关于如何快速得到系统级寿命与剩余寿命的相关研究比较缺乏。针对这一问题,首先研究了可靠度、寿命以及剩余寿命的关系,进一步假设部件寿命服从同一威布尔分布,根据部件的寿命与可靠度函数,推导得到串联、并联和表决系统寿命与剩余寿命期望的封闭表达式,并给出了相应的计算方法。对于冷备系统,当部件寿命服从同一指数分布时,推得了系统寿命及剩余寿命期望的封闭表达式,而当部件寿命服从同一威布尔分布时,给出了系统寿命与剩余寿命的数值计算方法。仿真试验证明本文所提出的方法是准确高效的。最后,以卫星中的动量轮r/n(G)表决系统为例开展了实例研究,证明了该方法在工程实践中的有效性。     

激光冲击强化对Ti2AlNb合金微观组织及残余应力的影响

Ti2AlNb(O-Ti2AlNb)具有优异的力学性能,在航空发动机方面有远大应用前景.激光冲击强化(Laser Shock Peening,LSP)是一种先进的表面改性技术,能够在材料表面诱导产生高幅值、大深度的残余压应力,改善材料微观组织,提高材料抗疲劳、高温氧化等性能.本文采用激光冲击强化对Ti2AlNb合金进行表面改性,并研究其组织演变、残余应力以及高温环境对性能的影响.结果表明:激光冲击强化能够显著减小Ti2AlNb合金近表面的晶粒尺寸.显微硬度由冲击前的350 HV提升到395 HV;在冲击区域近表面产生了约-377 MPa的残余压应力;而在高温环境中,由激光冲击强化所诱导的材料近表面残余应力随时间逐渐释放,在600℃条件下,残余应力释放较为缓慢;而在720℃条件下,残余应力迅速释放.     

利用反预报方法从截面预言近滴线丰质子核的结合能

在Origin等数据处理软件中,当实验数据较少时,自由参数的不同初始化设置会导致较大的结果差异,这为物理结果的确定带来较大不确定性.通过最小二乘法分析了345MeV/u ~(78) Kr+~9Be反应中产生的丰质子同位素的截面和结合能,并得到线性回归方程.通过回归方程,利用结合能预报部分丰质子核素的截面,以及通过实验截面对近质子滴线核素的结合能进行反预报测量.这对于近质子滴线的丰质子核素实验测量具有较好的借鉴意义.     

线性回归分析与能源需求预测

结合实例介绍了回归模型方法在能源预测中的应用，具体地讨论了最简单、最基本的直线回归模型结构及参数估计方法，对于其他一些曲线回归模型则可通过变量代换转化为直线回归模型。     

Robustness of alternative non‐linearity tests for SETAR models

In recent years there has been a growing interest in exploiting potential forecast gains from the non‐linear structure of self‐exciting threshold autoregressive (SETAR) models. Statistical tests have been proposed in the literature to help analysts check for the presence of SETAR‐type non‐linearities in an observed time series. It is important to study the power and robustness properties of these tests since erroneous test results might lead to misspecified prediction problems. In this paper we investigate the robustness properties of several commonly used non‐linearity tests. Both the robustness with respect to outlying observations and the robustness with respect to model specification are considered. The power comparison of these testing procedures is carried out using Monte Carlo simulation. The results indicate that all of the existing tests are not robust to outliers and model misspecification. Finally, an empirical application applies the statistical tests to stock market returns of the four little dragons (Hong Kong, South Korea, Singapore and Taiwan) in East Asia. The non‐linearity tests fail to provide consistent conclusions most of the time. The results in this article stress the need for a more robust test for SETAR‐type non‐linearity in time series analysis and forecasting. Copyright © 2004 John Wiley & Sons, Ltd.     

动态校正的PI型广义预测控制器及其在反应釜系统中的仿真研究

提出了一种新型的广义预测控制器。由于在控制器的设计中,进行了预测误差的动态校正,并且控制器采用了比例积分型(PI)目标函数,因此该控制器对未建模动态具有很强的鲁棒性。应用低阶的模型对一个强放热的化学反应釜模型进行的仿真研究检验了该方法的有效性。     

层板复合材料疲劳性能测试实验

根据层板复合材料的性能与具体的铺层形式有关的特点 ,介绍了在层板复合材料疲劳性能测试中试件准备注意事项、疲劳性能测试的内容和实验控制程序的要求 ,以及为缩短实验时间、优化层板复合材料疲劳剩余强度和疲劳剩余刚度分析模型的参数估计 ,并减少测试所需试件数量的合理试件数的确定方法 .     

Finding finer functions for partially characterized proteins by protein-protein interaction networks

Based on high-throughput data, numerous algorithms have been designed to find functions of novel proteins. However, the effectiveness of such algorithms is currently limited by some fundamental factors, including (1) the low a-priori probability of novel proteins participating in a detailed function; (2) the huge false data present in high-throughput datasets; (3) the incomplete data coverage of functional classes; (4) the abundant but heterogeneous negative samples for training the algorithms; and (5) the lack of detailed functional knowledge for training algorithms. Here, for partially characterized proteins, we suggest an approach to finding their finer functions based on protein interaction sub-networks or gene expression patterns, defined in function-specific subspaces. The proposed approach can lessen the above-mentioned problems by properly defining the prediction range and functionally filtering the noisy data, and thus can efficiently find proteins’ novel functions. For thousands of yeast and human proteins partially characterized, it is able to reliably find their finer functions (e.g., the translational functions) with more than 90% precision. The predicted finer functions are highly valuable both for guiding the follow-up wet-lab validation and for providing the necessary data for training algorithms to learn other proteins.     

The controlling factors and distribution prediction of H2S formation in marine carbonate gas reservoir, China

Generally, there are some anhydrites in carbonate reservoir, as H2S is also familiar in carbonate oil and gas reservoirs. Nowadays, natural gas with high H2S concentration is usually considered as TSR origin, so there is close relationship between H2S and anhydrite. On the contrary, some carbonate rocks with anhydrite do not contain H2S. Recently, researches show that H2S is only a necessary condition of H2S formation. The reservoir porosity, sulfate ion content within formation water, reservoir temperature, oil/gas and water interface, hydrocarbon and some elements of reservoir rock have great controlling effects on the TSR occurrence. TSR deoxidizes hydrocarbon into the acidic gas such as H2S and CO2, and the H2S formation is controlled by TSR occurrence, so the relationship among reaction room, the contact chance of sulfate ion and hydrocarbon, the reservoir temperature has great influence on the TSR reaction. H2S has relatively active chemical quality, so it is still controlled by the content of heavy metal ion. Good conditions of TSR reaction and H2S preservation are the prerequisite of H2S distribu- tion prediction. This paper builds a predictive model based on the characteristic of natural gas reservoir with high H2S-bearing. In the porosity reservoir with anhydrite, the formation water is rich in sulfate and poor in heavy metal ion. Oil and gas fill and accumulate in the gas reservoir with good preservation conditions, and they suffered high temperature later, which indicates the profitable area of natural gas with high H2S-bearing.     

神经网络在可靠性分析中的应用

应用人工神经网络对舰炮发生故障的发射炮弹数进行了预测。借助前馈神经网络对非线性函数的逼近能力，对发生故障的发射炮弹数进行了单步预测，并与使用灰色数列预测的结果进行了对比，验证了人工神经网络进行可靠性预测的可行性。