参数空间变异性下地下水污染监测网多目标优化机制研究

基于野外实际含水层参数存在空间变异性的客观事实,研发概率Pareto遗传算法(Probabilistic Pareto genetic algorithm,PPGA),用于求解考虑含水层参数空间变异性下地下水污染监测网多目标优化设计问题。PPGA在ε-改进非劣支配遗传算法(epsilon-dominance non-dominated sorted genetic algorithm II,ε-NSGAII)的基础上通过添加概率择优排序和概率拥挤度技术,寻求考虑参数空间变异条件下地下水污染监测网模拟—优化耦合模型的Pareto最优解。将优化结果与蒙特卡洛(Monte Carlo,MC)模拟分析结果进行对比,验证优化结果的可靠性。算例求解结果表明:在求解考虑参数空间变异性条件下地下水污染监测网多目标优化设计问题时,PPGA优化所得Pareto最优解变异性小,可靠性高,可为决策者提供一系列稳定可靠的监测方案。     

φ71 mm绳索取心铝合金钻杆的研制

介绍了国内外铝合金钻杆的研制现状,分析了绳索取心铝合金钻杆在地质钻探中的优势。对φ71 mm×5.5 mm绳索取心铝合金钻杆体与钢接头连接结构进行了详细设计。通过对试验钻杆进行静拉力、扭矩试验,得出了铝合金钻杆体与钢接头主要技术参数。     

卵漂石地层深基坑高压旋喷桩止水帷幕施工工艺

结合青海省微电机厂棚户区改造项目深基坑止水帷幕施工的成功经验,总结出卵漂石地层深基坑双排单重管高压旋喷桩止水帷幕施工的施工工艺及技术要点。     

网络并行电法与传统电法超前探测效果对比

网络并行电法是以分布式并行智能电极电位差信号采集方法为技术核心支撑的直流电法,其数据采集模拟地震勘探方式进行,与常规电法每次供电只能采得一个测点数据不同,并行电法每次供电可同时获得多个测点数据,是一种全电场观测技术。运用两种方法对龙岩市新罗区大弯煤矿和武平荧石矿进行超前探测试验对比研究,并经实际巷道掘进揭露验证,表明网络并行电法技术较传统电法技术效果更好,效率更高。     

岩石本构模型智能辨识方法研究

岩石本构模型是研究岩石力学特征和变形机制的基础,而本构模型或模型中相关参数的识别是本构模型研究中的热点和难点问题。本文基于红板岩室内力学实验数据,分别利用遗传算法、BP神经网络以及遗传规划对红板岩本构模型进行了模式识别,结果表明,遗传算法进行参数识别需要事先假定流变模型的形式,误差较大,而BP神经网络和遗传规划可以一次性同时确定流变模型的结构形式及参数,有效避免模型假定所带来的误差。而遗传规划与BP神经网络相比,具有精度高、收敛快,可视化程度高等特点,为岩石本构参数及模型的智能识别方法的选取提供参考。     

A three-level framework for multi-risk assessment

The effective management of the risks posed by natural and man-made hazards requires all relevant threats and their interactions to be considered. This paper proposes a three-level framework for multi-risk assessment that accounts for possible hazard and risk interactions. The first level is a flow chart that guides the user in deciding whether a multi-hazard and risk approach is required. The second level is a semi-quantitative approach to explore if a more detailed, quantitative assessment is needed. The third level is a detailed quantitative multi-risk analysis based on Bayesian networks. Examples that demonstrate the application of the method are presented.     

A Bayesian network approach for predicting seismic liquefaction based on interpretive structural modeling

The Bayesian network (BN) is a type of graphical network based on probabilistic inference that has been gradually applied to assessment of seismic liquefaction potential. However, how to construct a robust BN remains underexplored in this field. This paper aims to present an efficient hybrid approach combining domain knowledge and data to construct a BN that facilitates the integration of multiple factors and the quantification of uncertainties within a network model to assess seismic liquefaction. Initially, only using given domain knowledge, a naive network model can be constructed using interpretive structural modeling. Thereafter, some effective information about the naive model is provided to construct a robust model using structural learning of BN from historic data. Finally, the returning predictive results and the predictive results are compared to other methods including non-probabilistic and probabilistic models for seismic liquefaction using the metrics of the overall accuracy, the area under the curve of receiver operating characteristic, prediction, recall and F₁ score. The methodology proposed in this paper achieved better performance, and we discussed the power and value of the proposed approach at the end of this paper, which suggest that BN is a good alternative tool for seismic liquefaction prediction.     

大型高精度GNSS基线向量网并行抗差估计

针对大型GNSS基线向量网的特点,在改进的相关观测抗差估计RECO方案的基础上采用并行计算技术进行相关抗差估计的并行计算(简称"并行抗差估计"),并给出了可行的解算步骤。通过算例分析,验证了大型GNSS基线向量网的并行相关抗差估计,不仅有效抑制了观测异常对参数估值的影响,而且显著提高了计算效率。     

基于CORS站的GPS平面控制网起算点兼容性研究

不同等级或者不同时期布设控制点都可能存在较大误差,如果以误差较大点做起算,都会扭曲GPS测量的精度,严重影响GPS成果可靠性。文中以某城市四等GPS控制网为例,探讨以城市CORS站分析GPS控制网起算点兼容性,并得到成功应用。     

采用弱基准和抗差估计的重力网平差

以沿海某测区绝对重力和相对重力网数据处理为例,详细描述了弱基准重力网平差的方法,绝对重力和相对重力先验权的确定,用抗差等价权来调整相对重力的权、重力仪参数的取舍。结果表明,弱基准能有效地提高整网的精度;抗差估计能有效地探测并降低异常数据的权。重力点平均中误差为13.6×10-8 ms-2,偶然误差检验符合正态分布。