砂土液化判别方法可靠性评价

在进行液化评价简化法与规范液化判别方法对比基础上，利用液化概率的对数回归方程，讨论了规范液化判别方法的可靠性。研究结果表明，我国规范液化判别方法其液化概率变动较大，对于烈度 Ⅶ 度，规范法的液化概率在0.17～0.42间，小于简化法概率0.36～0.43，偏保守。对于烈度 Ⅷ 度和 Ⅸ 度近地表场地，规范法的液化概率高达0.65～0.70，远远高于简化法的液化概率，安全裕度不够。对于含粘粒土质液化评价，规范方法的液化概率总体上都较简化法高，特别是烈度Ⅷ度高粘粒含量其液化概率为0.9。     

CPT-based probabilistic evaluation of seismic soil liquefaction potential using multi-gene genetic programming

In this paper, liquefaction potential of soil is evaluated within a probabilistic framework based on the post-liquefaction cone penetration test (CPT) data using an evolutionary artificial intelligence technique, multi-gene genetic programming (MGGP). Based on the developed limit state function using MGGP, a relationship is given between probability of liquefaction (P_L) and factor of safety against liquefaction using Bayesian theory. This Bayesian mapping function is further used to develop a P_L-based design chart for evaluation of liquefaction potential of soil. Using an independent database of 200 cases, the efficacy of the present MGGP-based probabilistic method is compared with that of the available probabilistic methods based on artificial neural network (ANN) and statistical methods. The proposed method is found to be more efficient in terms of rate of successful prediction of liquefaction and non-liquefaction cases, in three different ranges of P_L values compared to ANN and statistical methods.     

以标贯试验为依据的砂土液化确定性及概率判别法

核电厂址非基岩场地的地基液化问题是核电厂选址的关键问题,亟需建立核电厂址地基液化判别方法。回顾了以标贯试验和地表峰值加速度为依据的砂土液化判别方法的演化历史,依据Idriss-Boulanger确定液化临界曲线的基本方法,提出了确定液化临界曲线的基本原则,分别依据美国液化数据库、中国抗震规范液化判别式所用的液化数据及综合两者的液化数据资料,给出了相应的液化临界曲线,验证了液化临界曲线的位置对不同的细粒含量、有效上覆压力、现场试验方法的液化数据的合理性,分析了测量或估计土层循环应力比和修正标贯击数各种因素的不确定性对液化临界曲线的敏感性,结果表明：所提的液化临界曲线不易受各种因素的影响。利用Monte Carlo模拟、加权最大似然法和加权经验概率法,给出了液化临界曲线的名义抗液化安全系数与液化概率的经验关系式及概率等值线,并对核电厂Ⅰ类、Ⅱ类和Ⅲ类抗震物项地基,给出了相应的液化临界曲线。     

基于Logistic回归模型的砂土液化概率评价

以国内外23次地震中200组场地液化实测数据为基础,通过Logistic回归分析,建立关联修正标准贯入击数N160cs与循环应力比CSR的液化概率模型。以50 %液化概率水平为液化与非液化的临界点,建立了指数形式的抗液化应力比CRR计算式,新建概率模型预测饱和砂土液化与非液化的成功率分别为85.71 %和76.14 %,具有较高的可靠性。与已有模型比较,使用了新的数据和修正系数,消除了一些不合理的偏差,总体判别结果偏于安全。为了将确定性分析方法与概率分析方法联系起来,建立了抗液化安全系数FS与液化概率PL的关系式。算例结果表明,新建概率模型简单、实用、可靠。     

液化判别临界曲线的变化模式与一般规律

液化临界值与砂层深度的关系是液化判别方法的基本表征,但对比分析表明,现有液化判别方法的临界曲线有不同的表现模式,甚至定性相反。以Seed-Idriss模型为基础,推导出了砂层埋深对液化势影响的理论解答,提出了砂层埋深与液化临界值的普遍关系,得到了液化判别临界曲线的变化模式和一般规律。结果表明：一般而言,随砂层深度增加,水平地震剪应力和土体抗液化强度同时增大,但前者增大速率大于后者,液化势及液化临界值与砂层深度呈正相关关系;液化临界值与砂层深度呈非线性递增关系,浅埋处饱和砂层液化势递增较为剧烈,深埋处趋于平缓;我国规范CPT液化判别公式的液化临界值与砂层深度呈递减关系,存在定性错误,需要纠正;现有一些液化判别公式中,液化临界值与砂层深度呈线性递增关系,定性正确但模型需要改进。所得结果可为液化判别方法正确发展提供理论基础和借鉴。     

FOSM在水平场地液化概率评价中的应用

为了更好地进行场地液化评价,将可靠度理论引入水平场地液化概率评价中。以标准贯入试验(SPT)实测数据的统计分析结果为基础,用一次二阶矩法(FOSM)建立水平场地液化概率评价模型,分析了测试数据变异系数对抗液化安全系数与液化概率的影响,并建议了水平场地液化概率评价标准。实例分析表明,新建水平场地液化概率评价模型各参数的物理意义与统计指标明确,相比传统的确定性分析方法,不仅能判定液化的发生与否,还能给出液化发生的概率,这为进行基于风险分析的抗震设计提供了可能。     

细粒含量对尾矿材料液化特性的影响

为了模拟沉积分选后颗粒组成的变化对尾矿材料的动力特性的影响,尾矿筛分后按不同的细粒（颗粒直径小于 0.074 mm）含量制备尾矿试样,并进行了大量的土动力学试验。分析了细颗粒含量对尾矿材料的动力液化特性的影响规律。研究表明,对于铜矿类尾矿坝的尾矿材料,当细颗粒含量占到总量的35 %时其抗液化性能最佳。根据尾矿材料动力特性试验的研究结果,并结合现场的标准贯入试验成果,提出了适用于尾矿材料的细粒含量对标准贯入击数的修正式。该式可以分析不同细粒含量的尾矿材料的抗液化强度,提高尾矿坝液化判别方法的判别准确程度。     

基于人工神经网络的砂土液化势评价

本文利用静力触探（ＣＰＴ）场地液化数据,建立了液化势判定的反向传播神经网络模型,研究表明,同传统方法相比,人工神经网络方法在判别砂土液化势方面是可行的。     

Probabilistic assessment of soil liquefaction considering spatial variability of CPT measurements

The conventional liquefaction potential assessment methods (also known as simplified methods) profoundly rely on empirical correlations based on observations from case histories. A probabilistic framework is developed to incorporate uncertainties in the earthquake ground motion prediction, the cyclic resistance prediction, and the cyclic demand prediction. The results of a probabilistic seismic hazard assessment, site response analyses, and liquefaction potential analyses are convolved to derive a relationship for the annual probability and return period of liquefaction. The random field spatial model is employed to quantify the spatial uncertainty associated with the in-situ measurements of geotechnical material.     

以剪切波速与地表峰值加速度为依据的地震液化确定性及概率判别法

剪切波速作为土性的基本参数,为评价土体抵抗地震液化的能力提供了一种方法。回顾了以剪切波速和地表峰值加速度为依据的场地地震液化判别方法的演化历史,依据他人收集的现场液化资料,合计49次地震、618例液化/不液化场地数据,提出了确定液化临界曲线的基本原则,给出了基于修正剪切波速与地表峰值加速度的液化临界曲线,验证了液化临界曲线的位置对细粒含量、有效上覆压力、震级等因素取值变化的合理性,分析了估计土层循环应力比CSR的剪应力折减系数、震级标定系数、有效上覆压力修正系数等因素的不确定性对液化临界曲线的敏感性。结果表明：液化临界曲线对各种影响因素具有很好的适用性。利用Monte Carlo模拟、加权最大似然法和加权经验概率法,给出了建议的液化临界曲线的名义抗液化安全系数与液化概率的经验关系式及概率等值线,并对核电厂Ⅰ类、Ⅱ类和Ⅲ类抗震物项地基,分别建议了相应的液化临界曲线。该方法以丰富的现场液化数据为依据,具有广泛的应用前景。     

砂土地震液化的模糊概率评判方法

利用模糊数学中的模糊概率理论,建立了砂土地震液化的模糊概率综合评判模型。在此模型中,提出了模糊权重的概念,可充分考虑权重的模糊性,从而避免权重取值带来的不确定性。结合砂土地震液化特点,选取地震烈度、标准贯入击数、平均粒径和上覆有效压力作为主要评价影响因子,同时将液化程度划分为不液化、轻微液化、中等液化和严重液化4个等级,进而使其评判结果更为精细化。通过算例分析,表明文中方法对砂土液化评判的合理性与有效性。     

基于静力触探试验的液化判别新方法

近来地震液化灾害频发,再次成为研究重点,发展具有良好应用前景的基于静力触探试验（CPT）的液化判别方法对预防液化灾害具有重要意义。以Boulanger数据库171组数据为回归样本,分析既有方法存在的问题,提出了基于CPT液化判别的双曲线模型和计算公式,并通过提取2011年新西兰地震147组液化新数据,对该方法进行对比检验。研究表明,我国岩土工程勘察规范的CPT液化判别方法对浅埋砂层偏于保守,对深层土又明显偏于危险,而国际上具有代表性的Robertson方法,其液化临界线存在低烈度区不合理回弯、高烈度区又偏于保守的问题。提出的新公式在不同地震动强度和砂层埋深下均可给出合理判别结果,克服了国内外既有方法的缺点,并纳入到具有样板规范性质的《建筑工程抗震性态设计通则》修订稿中,可为我国相关规范修订和工程应用提供支持。     

基于动力触探的砾性土液化判别方法通用性研究

能量传递率是衡量贯入类试验锤击效率的一个重要指标。国外对这一指标需要进行现场实测,进而修正贯入试验的锤击数,建立评价场地承载力、液化势等特性的标准化锤击数。国内规范中,则较少考虑贯入试验的锤击能量传递率的问题,且缺少现场试验测试数据,导致基于贯入类试验锤击数的地基评价方法难以与国外标准进行横向对比。为解决这一问题,选取川滇地区西昌地震实验场的3个勘察试验点。采用能量测试仪实测标准贯入试验能量传递率,研究我国常规SPT试验装置锤击效率,并评价其稳定性。试验实测结果显示,现场标准贯入试验的锤击能量传递率均值基本超过75%。能量传递率随着贯入深度的增加稍有增加,地表下20 m范围内增长幅值为10%左右。试验结果可为评价我国常规SPT试验设备的锤击效率提供依据。     

双桥静力触探法判别上海薄夹层粘土地基液化研究

通过对11项典型工程场地进行原位取土及双桥静力触探原位测试分析,重点研究了上海地区薄层粘性土（或粘质粉土）夹层对液化判别的影响,统计分析了锥尖阻力qc、摩阻比Rf与土层粘粒含量的相关关系,提出了完全依据双桥静力触探试验的地基液化判别方法,在工程应用中取得了显著经济效益。     

Assessing probability of surface manifestation of liquefaction at a given site in a given exposure time using CPTU

This paper is a follow-up to a previous paper on the subject of liquefaction potential index (LPI), a parameter that is often used to characterize the potential for surface manifestation of liquefaction at a given site subjected to a given shaking level (represented by a pair of peak ground surface acceleration a_max and moment magnitude M_w). In the previous paper by Juang and his coworkers, the LPI was re-calibrated for a piezocone penetration test (CPTU) model, and a simplified model based on LPI was created for computing the conditional probability of surface manifestation of liquefaction (P_G). In this paper, the model for this conditional probability P_G is extended into a complete framework for assessing the probability of surface manifestation of liquefaction in a given exposure time at a given site subjected to all possible ground motions at all seismic hazard levels. This new framework is formulated and demonstrated with an example site in 10 different seismic regions in the United States.     

基于ANN和GIS耦合模型的场地地震液化势评价系统研究

采用组件式GIS (COMGIS)技术开发了结合BP神经网络分析模型的场地地震液化势评价系统,调用水平成层土地震反应分析程序SHAKE91实现设定地震下地震动影响场的模拟。在VB下调用Matlab神经网络工具箱来完成场地地震液化势评价模型在COMGIS系统中的模块化;利用GIS技术对评价结果,即液化势等级进行空间复合,给出场地潜在的地层液化势空间分布图。研究表明,SHAKE91应用程序在系统菜单下可直接调用,实现地震动影响场计算的模块化;BP神经网络技术应用于场地地震液化势评价中能达到较为理想的效果;系统的GIS空间分析功能可使评价结果与场地信息进行空间匹配,实现目标场地潜在地震液化势的快速评估。     

A FORM-based approach for probabilistic analysis in geotechnics: Application to a reinforced concrete drainage culvert

As numerical models are increasingly used as a design tool in geotechnical engineering, it is highly desirable if geotechnical reliability analysis can be conducted based on numeral models. Currently, the practical use of geotechnical reliability analysis-based numerical models is still quite limited. In this study, an easy to access method is derived to conduct geotechnical reliability analysis based on numerical models. To facilitate its application, a procedure is outlined to implement the suggested method such that geotechnical reliability analysis can be automated using existing geotechnical numerical packages. The procedure is illustrated in detail with an example, and the source codes provided can be easily adapted to analyze other similar problems. The method described in this paper is used to study the reliability of a deteriorating reinforced concrete drainage culvert in Shanghai, China. The suggested method provides a convenient means for reliability analysis of complex geotechnical problems.     

On the efficiency and predictability of strain energy for the evaluation of liquefaction potential: A numerical study

Strain energy concept has been employed by the researchers for the assessment of liquefaction phenomenon which is a disastrous type of earthquake-induced failure in saturated soils. The efficiency and predictability conditions of strain energy concept for liquefaction potential assessment are investigated herein using effective stress numerical analyses. Several earthquake ground motions were introduced to the base of a calibrated numerical model using an advanced fully coupled constitutive model. Results of the numerical analyses indicate that earthquake-induced excess pore pressure is more rigorously proportional to strain energy compared with the other examined intensity measures. Subsequently, a simple relationship was derived using the results of dynamic analyses to predict cumulative strain energy density in terms of magnitude, source to site distance, and effective overburden pressure. This relationship, which tries to guarantee the predictability condition of strain energy demand, has demonstrated a successful capability in discrimination between the liquefied and non-liquefied case histories recorded after several well-known earthquakes. This study has provided a practical linkage between numerical analysis and field observations. Finally, it is concluded that although strain energy approach possesses a great conceptual efficiency in liquefaction potential assessment, its precise prediction in actual field conditions involves some difficulties.     

Groundwater potential recharge estimation in bare soil using three soil moisture accounting models: field evaluation for a semi-arid foothill region

Performances of conventional and improved soil moisture balance as well as locally calibrated empirical models were evaluated in simulating potential recharge (R) and soil moisture content for a semi-arid foothill region. Models comparison with observed values using lysimeter data during [(2011–2012), (2012–2013)] reveal poor performance of conventional soil moisture balance model, underestimating annual R values. Improved soil moisture balance model provided acceptable estimation of annual R for 2011–2012 by considering the wetting of the near surface soil storage. However, it produced the worst simulation for daily soil moisture content once rainy season was over. Sensitivity analysis revealed that the precision degree of initial soil moisture deficit value would strongly influence estimation of R by improved soil moisture balance model, which can be viewed as a limiting factor. Additionally, locally calibrated model produced the best estimation of annual R and daily soil moisture content, which is suggested for the study region.     

Assessing spatial and attribute errors in large national datasets for population distribution models: a case study of Philadelphia county schools

Geospatial technologies and digital data have developed and disseminated rapidly in conjunction with increasing computing efficiency and Internet availability. The ability to store and transmit large datasets has encouraged the development of national infrastructure datasets in geospatial formats. National datasets are used by numerous agencies for analysis and modeling purposes because these datasets are standardized and considered to be of acceptable accuracy for national scale applications. At Oak Ridge National Laboratory a population model has been developed that incorporates national schools data as one of the model inputs. This paper evaluates spatial and attribute inaccuracies present within two national school datasets, Tele Atlas North America and National Center of Education Statistics (NCES). Schools are an important component of the population model, because they are spatially dense clusters of vulnerable populations. It is therefore essential to validate the quality of school input data. Schools were also chosen since a validated schools dataset was produced in geospatial format for Philadelphia County; thereby enabling a comparison between a local dataset and the national datasets. Analyses found the national datasets are not standardized and incomplete, containing 76 to 90 percent of existing schools. The temporal accuracy of updating annual enrollment values resulted in 89 percent inaccuracy for 2003. Spatial rectification was required for 87 percent of NCES points, of which 58 percent of the errors were attributed to the geocoding process. Lastly, it was found that by combining the two national datasets, the resultant dataset provided a more useful and accurate solution.