A sequential sparse polynomial chaos expansion using Bayesian regression for geotechnical reliability estimations

Polynomial chaos expansions (PCEs) have been widely employed to estimate failure probabilities in geotechnical engineering. However, PCEs suffer from two deficiencies: (a) PCE coefficients are solved by the least-square minimization method which easily causes overfitting issues; (b) building a high order PCE is often computationally expensive. In order to overcome the aforementioned drawbacks, the Bayesian regression technique is employed to evaluate PCE coefficients, which not only provides a sparse solution but also avoids overfitting. With the aid of the predictive means and variances given by Bayesian analysis, a learning function is proposed to sequentially select the most informative samples that are critical to build a PCE. This sequential learning scheme can highly enhance the computational efficiency of PCEs. Besides, importance sampling (IS) is incorporated into the sequential learning (SL)-PCEs to deal with geotechnical problems with small failure probabilities. The proposed method of SL-PCE-IS is applied to three illustrative examples, which shows that the improved PCE method is more effective and efficient than the common PCEs method, leading to accurate estimations of small failure probabilities using fewer training samples.     

时空序列预测误差的敏感性试验分析

利用33模Lorenz系统得到的"理想"混沌时空序列,作为时空混沌序列"发生器".通过状态空间重构,建立"场时间序列"局域近似预测模型,对资料空间分辨率,资料的长度、噪音,以及模型的参数选取等因素进行敏感性试验分析,了解时空混沌序列预测中误差产生和增长的一些影响因素.得到以下初步结论:对于理想混沌时空序列(33模Lorenz系统)而言,与系统相适应的资料空间分辨率和较长的资料长度都将会提高预测精度;可预报时效与资料长度之间近似服从指数关系.另外,在建立预测模型时,适当的邻近点数目,以及采用二阶映射关系和迭代法都可以有效地改善预测精度.对于加入噪音的混沌时间序列,通过"场时间序列"的局域近似方法和4阶自回归方法的预测试验的对比表明,前者显示了更强的抗"干扰"能力.以上结论可以有分析地应用于短期气候预测中.     

岩性储集层的混沌识别技术研究

本文从动力学系统原理出发,论述了混沌理论中的李指数法,并从地震剖面上提取李指数,并应用李指数来区分和识别储集层的岩性变化特征和含油气性。计算和应用研究表明,李指数随着相空间维数的增加容易趋于稳定值,这就使它预测地震序列横向变化的可靠性增大,这正是李指数预测岩性和含油气性的一个优越性。成功地应用实例表明,混沌识别技术是岩性储集层的一种有效识别技术,并具有广阔的应用前景。     

变形岩体软弱破裂带的处理技术

在研究完成变形岩体软弱破裂带可灌性的基础上,采用旋喷注浆技术进行直接加固处理,提高破裂带的内聚力和内摩擦角,实践证明,抑制了岩体的变表,防止了滑坡的产生。     

Prediction of weather parameters on a very short time scale by an Auto Regressive process for aviation flight planning

Forecasting weather parameters such as temperature and pressure with a reasonable degree of accuracy three hours ahead of the scheduled departure of an aircraft helps economic and efficient planning of aircraft operations. However, these two parameters exhibit a high degree of persistency and have nonstationary mean and variance at sub-periods (i.e. at 0000, 0300, 0600,…, 2100UTC). Hence these series have been standardised (to have mean 0 and variance 1) and thereafter seasonal differenced (lag 8) to achieve almost near stationarity. An attempt has been made to fit the standardised and seasonal differenced series of Chennai (a coastal station) and Trichy (an inland station) airport into an Auto Regressive (AR) process. The model coefficients have been estimated based on adaptive filter algorithm which uses the method of convergence by the steepest descent. The models were tested with an independent data set and diagnostic checks were made on the residual error series. An independent estimation of fractal dimension has also been made in this study to conform the number parameters used in the AR processes. The models contemplated in this study are parsimonious and can be used to forecast surface temperature and pressure.     

裂隙岩体宏观力学参数的二维数值模拟

岩体通常含许多不同尺度的裂隙,因而力学性质非常复杂。由于现场测试及常规实验室试验常受各种条件的限制,因而其不能准确反映岩体的宏观物理力学性质。本文基于有限元分析软件对二维情况下的完整岩体和含不同倾角的软弱夹层的岩体在单轴和双轴压缩下进行了数值模拟,得到岩体变形的应力-应变曲线。该类曲线能反映裂隙对岩体力学参数的影响,对于指导工程实践有一定的意义,并且为获取岩体力学参数提供了新的途径。     

Polynomial chaos expansion and response surface method for nonlinear modelling of reference evapotranspiration

The feasibility of polynomial chaos expansion (PCE) and response surface method (RSM) models is investigated for modelling reference evapotranspiration (ET₀). The modelling results of the proposed models are validated against the M5 model tree and multi-layer perceptron neural network (MLPNN) methods. Two meteorological stations, Isparta and Antalya, in the Mediterranean region of Turkey, are inspected. Various input combinations of daily air temperature, solar radiation, wind speed and relative humidity are constructed as input attributes for the ET₀. Generally, the modelling accuracy is increased by increasing the number of inputs. Including wind speed in the model inputs considerably increases their accuracy in modelling ET₀. Mean absolute error (MAE), root mean square error (RMSE), agreement index (d) and Nash-Sutcliffe efficiency (NSE) are used as comparison criteria. The PCE is the most accurate model in estimating daily ET₀, giving the lowest MAE (0.036 and 0.037 mm) and RMSE (0.047 and 0.050 mm) and the highest d (0.9998 and 0.9999) and NSE (0.9992 and 0.9996) with the four-input PCE models for Isparta and Antalya, respectively.     

滇东北地区地震弱活动前兆异常特征研究

以鲁甸M_S6.5地震震中附近的鲁甸大坪子泉水氡、 水质观测资料为基础, 通过对其地震前后的异常特征进行差异性对比, 分析认为震前地震活动丛集, 水氡、 水质异常持续时间较长, 幅度较大, 表现为破年变异常现象; 震后为小震群弱活动, 水氡、 水质异常幅度相对较小, 持续时间较短, 多次出现同步转折, 表现为介质弱化区的前兆异常特征。 从水样测试结果, GNSS位移观测资料、 GPS时间序列曲线及地震活动性等方面分析了鲁甸水氡、 水质的异常机理, 认为鲁甸的水质离子组分群体异常, 与区域的变形活动有关, 局部应力的不断积累, 加剧了地下深部物质活动及构造活动; 近期的同步转折现象属于介质弱化区应力调整状态下的前兆异常。     

浙江夏季弱天气尺度强迫背景下午后局地热对流特征分析

利用常规高空观测资料、浙江多普勒雷达产品、ERA5逐小时再分析资料(0.25°×0.25°),统计分析了2015—2021年浙江夏季(6—8月)弱天气尺度强迫背景下午后局地热对流(根据移动速度分为移动型和少动型两类)的时空分布特征、生命周期特征、环境参数特征等。(1)两类热对流触发频次相当,年际变化均较大,但年、月、日变化趋势基本一致,午后出现少动型局地热对流的可能性更大,而傍晚出现移动型局地热对流的可能性更大。(2)局地热对流的触发与地形密切相关,对流高频区位于浙东沿海、浙西北、浙西南山区,浙中北平原和盆地均为低频区,热对流触发频次均随高度增加而减少,多触发于山脉及其附近的中低海拔处,中高海拔地区更容易触发少动型局地热对流。(3)两类对流均在弱垂直风切变环境下即可触发,移动型单体更容易得到发展。