三面受火的方钢管混凝土柱耐火极限

编制了预测方钢管混凝土柱三面火灾作用下高温反应的数值分析程序,并将之用于不同荷载比、截面边长、长细比、荷载偏心率、钢材和混凝土强度及含钢率共480种工况下方钢管混凝土柱耐火极限参数分析,得到了三面火灾作用下方钢管混凝土柱耐火极限的主要影响参数及其影响规律。基于参数分析结果,定量给出了该受火条件下方钢管混凝土柱耐火极限的简化计算方法。研究结果表明:荷载比、截面边长、长细比是三面火灾作用下方钢管混凝土柱耐火极限的主要影响参数,表现为截面边长越大,荷载比和长细比越小,构件的耐火极限越大。由于存在极强偏心,当荷载作用点偏于背火面时荷载偏心率亦有较大影响。     

中国火灾最佳灰色回归组合预测模型

火灾现象具有随机性、模糊性,是个复杂的灰色系统行为。研究火灾发生的规律及发展趋势,具有实用价值。笔者给出最小二乘估计意义下的最佳组合预测模型的定义,并求得其权的公式和证明权的惟一性;用回归分析方法建立多个回归模型,并按3条标准即①回归指数大、②系统误差小、③模型精度高,选定最佳非线性回归模型;用灰色理论建立多个灰色模型,并按3条标准即①后验差比值小、②小误差概率大、③预测关联度大,选定最佳灰色模型;再将最佳回归模型与最佳灰色模型有机地结合起来建立中国火灾最佳灰色回归组合预测模型。组合预测模型综合利用前两者提供的不同的有用信息,改善了单一模型的局限性,提高了预测精度,减少了预测误差。组合模型预测中国年火灾起数处于动态增长过程。     

Research on an Online Identification Algorithm for a Thevenin Battery Model by an Experimental Approach

To improve the estimation accuracy of battery’s inner state for battery management system, an online parameters identification algorithm for Thevenin battery model is researched. The Thevenin model and parameters identification algorithm based on recursive least square adaptive filter algorithm was built with the Simulink/xPC Target. The results of hardware-in-loop experiment, which uses Federal Urban Driving Schedule test to verify the parameters identification approach, show the proposed approach can accurately identify the model parameters within 1% maximum terminal voltage estimation error, and the State of Charge error which calculated by the open circuit voltage estimates can be efficiently reduced to 4%.     

基于四阶B-样条最小二乘法的油气管道凹痕缺陷应变计算方法

针对油气管道上的凹痕缺陷,ASME B31.8提出采用基于应变的评价方法,但在内检测数据到应变求解的过程中,缺少噪声消除和轮廓拟合的相关方法。提出了采用四阶B-样条最小二乘拟合算法将检测数据进行噪声消除和轮廓拟合,实现从含有噪声的检测数据到应变求解的应变评价方法。采用文中所提方法和有限元方法,详细计算了几种典型凹痕的轴向弯曲应变、环向弯曲应变及其总应变。对比结果表明,该方法不仅能够较为精确的计算出弯曲应变值,还能得到较准确的弯曲应变分布情况。环向弯曲应变受在线检测工具精度的限制存在一定误差。计算发现,现有标准中忽略了环向薄膜应变分量,这使得总应变的计算结果不够准确。     

Kullback-Leibler distance-based enhanced detection of incipient anomalies

Accurate and effective anomaly detection and diagnosis of modern engineering systems by monitoring processes ensure reliability and safety of a product while maintaining desired quality. In this paper, an innovative method based on Kullback-Leibler divergence for detecting incipient anomalies in highly correlated multivariate data is presented. We use a partial least square (PLS) method as a modeling framework and a symmetrized Kullback-Leibler distance (KLD) as an anomaly indicator, where it is used to quantify the dissimilarity between current PLS-based residual and reference probability distributions obtained using fault-free data. Furthermore, this paper reports the development of two monitoring charts based on the KLD. The first approach is a KLD-Shewhart chart, where the Shewhart monitoring chart with a three sigma rule is used to monitor the KLD of the response variables residuals from the PLS model. The second approach integrates the KLD statistic into the exponentially weighted moving average monitoring chart. The performance of the PLS-based KLD anomaly-detection methods is illustrated and compared to that of conventional PLS-based anomaly detection methods. Using synthetic data and simulated distillation column data, we demonstrate the greater sensitivity and effectiveness of the developed method over the conventional PLS-based methods, especially when data are highly correlated and small anomalies are of interest. Results indicate that the proposed chart is a very promising KLD-based method because KLD-based charts are, in practice, designed to detect small shifts in process parameters.     

巢湖流域SRTM高程误差的空间分异研究

数字高程模型是进行地学研究的重要基础数据,SRTM、DEM是公众可以免费获取的精度达90m的DEM数据.以我国1:5万DEM为参考数据,以巢湖流域为研究区,利用高程中误差模型和单位面积土地填挖方对SRTM、DEM进行高程精度研究,并分析了高程误差的空间分异规律.结果表明,SRTM、DEM的高程中误差和单位面积土地填挖方随着地貌类型的变化呈现明显的空间分异性,这主要由于SRTM像元精度不高所致.在研究区内的33块样区中,绝大部分都是在二级精度评价标准之内,可见SRTM、DEM整体精度较高.     

Evaluating weather effects on interannual variation in net ecosystem productivity of a coastal temperate forest landscape: A model intercomparison

Forest productivity is strongly affected by seasonal weather patterns and by natural or anthropogenic disturbances. However weather effects on forest productivity are not currently represented in inventory-based models such as CBM-CFS3 used in national forest C accounting programs. To evaluate different approaches to modelling these effects, a model intercomparison was conducted among CBM-CFS3 and four process models (ecosys, CN-CLASS, Can-IBIS and 3PG) over a 2500 ha landscape in the Oyster River (OR) area of British Columbia, Canada. The process models used local weather data to simulate net primary productivity (NPP), net ecosystem productivity (NEP) and net biome productivity (NBP) from 1920 to 2005. Other inputs used by the process and inventory models were generated from soil, land cover and disturbance records. During a period of intense disturbance from 1928 to 1943, simulated NBP diverged considerably among the models. This divergence was attributed to differences among models in the sizes of detrital and humus C stocks in different soil layers to which a uniform set of soil C transformation coefficients was applied during disturbances. After the disturbance period, divergence in modelled NBP among models was much smaller, and attributed mainly to differences in simulated NPP caused by different approaches to modelling weather effects on productivity. In spite of these differences, age-detrended variation in annual NPP and NEP of closed canopy forest stands was negatively correlated with mean daily maximum air temperature during July-September (T_amax) in all process models (R² = 0.4-0.6), indicating that these correlations were robust. The negative correlation between T_amax and NEP was attributed to different processes in different models, which were tested by comparing CO₂ fluxes from these models with those measured by eddy covariance (EC) under contrasting air temperatures (T_a). The general agreement in sensitivity of annual NPP to T_amax among the process models led to the development of a generalized algorithm for weather effects on NPP of coastal temperate coniferous forests for use in inventory-based models such as CBM-CFS3: NPP′ = NPP − 57.1 (T_amax − 18.6), where NPP and NPP′ are the current and temperature-adjusted annual NPP estimates from the inventory-based model, 18.6 is the long-term mean daily maximum air temperature during July-September, and T_amax is the mean value for the current year. Our analysis indicated that the sensitivity of NPP to T_amax was nonlinear, so that this algorithm should not be extrapolated beyond the conditions of this study. However the process-based methodology to estimate weather effects on NPP and NEP developed in this study is widely applicable to other forest types and may be adopted for other inventory based forest carbon cycle models.     

反距离加权法天气衍生品空间基差风险对冲效果

天气衍生品作为一项金融创新产品,为天气风险的管理和转移提供了新的途径.与传统衍生品不同的是,天气衍生品合约标的物是常见的天气变量,本身不具有资产价格,因此面临的并不是传统意义上的基差风险.天气衍生品的基差风险包括产品基差风险和空间基差风险,这些基差风险严重影响着天气衍生品的风险对冲效果,阻碍了市场发展,也是研究的重点与难点.相比产品基差风险因特定部门而异,空间基差风险具有不可避免的特点.依据反距离加权法,增加空间多样性构建天气衍生品组合,可用于对冲空间基差风险,但需要经验数据验证.研究表明,天气衍生品收益与假设收益的均方根误差(RMSE)能够很好的量化天气敏感企业遇到的天气风险,天气风险对冲效果可以通过RMSE的变化值进行度量;构建中国华东地区降雨量看跌期权交易,相较单一地区收益偏差,期权买方采用空间组合策略取得了更好的空间基差风险对冲效果.此外,研究结果发现,在构建天气衍生品空间组合时,组合中气象观测点的数目并不是越多越好,即较少的观测点个数即能显著降低天气风险对冲效果,这也为实践操作提供了便利.     

硬度测量法测定20号钢球化等级的实验

为快速、便捷地获得20号钢球化等级,避免传统金相组织观察比对法存在主观判断偏差和制作金相试样的过程烦琐,实验采用简易的硬度测量法对20号钢的硬度进行测量,并对测量数据进行相关性分析,得到20号钢平均硬度值与球化等级线性负相关的特性。采用最小二乘法拟合得到20号钢平均硬度值与球化等级的线性回归关系式,并据此关系式实现对未知球化等级的20号钢进行测定。通过硬度测量法测定的未知球化等级20号钢,与金相组织观察比对法的评定结果基本吻合。     

OMEGA算法在导弹振动工程中的应用

目的研究位移、速度和加速度谱之间的转换关系,给出三者功率谱密度之间的转换公式,进而用于导弹运输振动环境的设计。同时,研究加速度信号转换为振动位移的方法,并应用于导弹舱内单机设备安全间隙的设计。方法利用OMEGA算法,首先将加速度传感器测得的加速度时域信号转换成加速度频域信号,随后将加速度谱转换成位移谱,并计算位移谱中每个谱线对应的幅值、相位和圆频率,最后将各位移分量简单叠加得到振动位移的时间历程。结果采用该方法计算了高速公路上导弹的运输振动位移功率谱,并得到垂向、横向和纵向的峰-峰位移分别为3.32,0.46,2.14 mm。同时,计算了飞行环境下导弹舱内单机设备的振动位移,与所测得位移在幅值上相当,时域曲线形态一致。结论该方法能够很好地应用于导弹振动工程设计。