Evaluation of statistical uncertainty of cement-treated soil strength using Bayesian approach

The statistical parameters for the strength of cement-treated soil are evaluated by the strength of cored samples retrieved from cement-treated columns for a quality assurance procedure in the deep mixing method. The sample parameters include the statistical uncertainty associated with the statistical sample size and other factors. Therefore, a probabilistic characterization of the statistical parameters of strength is required to quantify the statistical uncertainty in the quality assurance process. This paper presents a quantitative analysis of the statistical uncertainty for the estimation of the strength of cement-treated columns. The Bayesian approach is adopted to evaluate the statistical uncertainty occurring in the determination of the statistical parameters of the strength from observed data. The inference is performed via a Markov chain Monte Carlo method, in which samples of the parameters are sequentially drawn from a joint posterior probability distribution. An example analysis is performed to illustrate the statistical uncertainty of the unconfined compressive strength of cored samples retrieved from cement-treated columns. The results show that the statistical parameters, inferred from the data with the sample size of approximately 40, include considerable uncertainty. The variability of the estimated statistical parameters is found to depend on both the sample size and the spatial correlation. The influence of the statistical uncertainty, caused in the estimation of the mean and standard deviations in strength, is examined within the framework of quality assurance in the deep mixing method.     

基于CPT的地基液化概率评价

通过LOGISTIC模型,以世界范围内19次大地震106个场地的液化案例为基础,构建基于CPT的液化概率评价模型,采用仅通过CPT试验即可获取的锥尖阻力和摩阻比作为评价参数,既体现严格的统计学意义又具有明确的物理意义,预测液化和非液化的可靠性分别达到91．2％和86．8％。并拟舍得到液化概率和抗液化安全系数的S型关系曲线以便于工程应用。理论分析与工程实例对比表明,相对于《岩土工程勘察规范》推荐的CPT模型,本文建议模型的评价结果和《建筑抗震设计规范》的SPT模型评价结果更为接近,且物理意义更为明确,为利用现场原位测试数据进行地基液化评价提供了更为简洁、准确的新途径,可以作为规范方法的有益补充。     

Evaluation of bio-diesel properties: a statistical approach

In this work, methyl esters of Pungamia (MEOP), ethyl esters of Pungamia (EEOP), and ethyl esters of Neem (EEON) were primarily produced by means of transesterification process using sodium methoxide (mixture of sodium hydroxide and methanol) and potassium methoxide (mixture of potassium hydroxide and methanol). Further, the fuel properties such as calorific value, flash point, density and viscosity of methyl and ethyl esters were determined using ASTM specified equipment. Also, the association between different blend ratios and fuel type with fuel properties was gauged with an assistance of two-way analysis of variance. The experimental outcomes revealed that the maximum ester content of bio-diesel was witnessed for potassium hydroxide catalyst and the quantity of catalyst used was less than that with sodium hydroxide for the same mass of the feedstock oil. Overall, the statistical analysis disclosed that there is a significant difference in the fuel properties of the different combination of fuel type and blend ratios.     

某场地地震液化危害评价及地基处理建议

分析了砂土液化原理,结合工程实际,对某高速公路特大桥的液化场地土液化等级、危害性进行了评价,并结合工程特点,给出了切实可行的处理建议,从而保证该特大桥地基处理的效果。     

Evaluation of multiple column curves using the experimental data-base approach

The paper describes an extensive survey of column tests and an evaluation of information on steel column strength. During the past twenty-five years numerous series of column tests have been conducted in European countries, North America and Japan. A total of 1665 individual test results which have been stored in an experimental data-base is retrieved and a statistical appraisal carried out to evaluate experimental column strength. Comparisons are made between the surveyed test data and the ECCS and SSRC multiple column curves. The authors also propose new multiple column formulae which explain more accurately the test data from a statistical viewpoint.     

基于可拓学理论的砂土液化势综合评价研究

将可拓学理论引入到砂土液化势评价工作中,利用网络编程技术开发了基于Web平台的可拓综合评价系统,选取最关键的7个参数作为评价指标,建立了砂土液化势的可拓评价模型,从而找到了砂土液化势评价行之有效的新途径。     

Liquefaction potential at Izmit Bay: comparison of predicted and observed soil liquefaction during the Kocaeli earthquake

The 1999 Kocaeli earthquake resulted in large-scale damage to structures and a death toll of more than 20,000. Numerous liquefaction and associated ground deformations caused by the earthquake were particularly observed along the southern coasts of Izmit Bay and Sapanca Lake, as well as the city of Adapazari. The paper discusses the soil liquefaction and lateral spreading along the southern coast of Izmit Bay. A microzonation map was created using the data from liquefaction susceptibility analyses and a liquefaction severity index. The predicted liquefiable zones showed good agreement with site observations. The assessment suggests that the amount of liquefaction-susceptible layers in the soil profile reduces away from the coastal zone.      

砂土液化分析及其防治措施

针对地基处理中的难题之一——砂土液化问题,首先分析了砂土的液化机理,然后给出了砂土的液化判别及影响因素,最后综述了目前国内外所采用的砂土液化治理措施,可供相关技术人员参考借鉴。     

砂土液化影响因素及其判别方法

砂土液化受动荷条件、埋藏条件和土性条件的制约，在进行砂土液化判别时不能从某一方面或某一统计公式简单评判。综合考虑各影响因索，采用多因子判别分析法加以判别。     

浅谈液化土的判别

以液化土为例,阐述了液化土的概念及形成机理,提出了工程上液化土判别的常用方法,以使工程技术人员对液化土有一个概括的了解,从而能根据工程的实际情况选择合理的液化土的判别方法。     

Experimental investigation on energy saving potential of smart HVAC unit

It is well known that ‘the energy can’t be created but could be saved’ and the energy resources are depleting at an alarming rate over the decades. The HVAC unit consumes 1/5th of the World’s electrical power consumption. Over the years several modifications have been made on the HVAC unit to save energy. This study implements the machine-to-machine interaction through Internet of things which reduces the human effort. The proposed system utilises the smart power controlling and modifying feedback systems from mobile phones integrated with human motion detectors. Due to the accurate feedback system, the room temperature can be maintained within the range of ±0.3°C. The experiment shows an interesting result that the power consumption of compressor can be reduced by 45% using the smart control HVAC unit. The client can also control the system through a web server which controls the actuators.     

地基液化评价的模糊不确定性分析

基于世界范围内19次中强震的CPT液化案例,通过构建客观性较强的液化隶属函数映射地基液化模糊性;基于LOGISTIC模型导出地基抗液化强度CRR曲线及其概率密度函数;借用中国华北地区地震动加速度衰减关系,构建CSR的概率密度函数,进而分析地基液化评价的模糊不确定性.结果表明,忽略地基液化评价的模糊不确定性,评价结果可能偏于危险;基于模糊不确定性的地基液化评价工程意义较为明显,可作为规范方法的有益参考.     

Improving prediction of soil liquefaction using hybrid optimization algorithms and a fuzzy support vector machine

The phenomenon of soil liquefaction is one of the most complex and interesting fields in geotechnical earthquakes that has drawn the attention of many researchers in recent years. The present study used hybrid particle swarm optimization and genetic algorithms with a fuzzy support vector machine (FSVM) as the classifier for the soil liquefaction prediction problem. Fuzzy logic is used to decrease the outlier sensitivity of the system by inferring the importance of each sample in the training phase to increase the ability of the classifier’s generalization. Using the appropriate combination of optimization algorithms, we can find the best parameters for the classifier during the training phase without the need for trial and error by the user due to the high accuracy of the classifier. The proposed approach was tested on 109 CPT-based field data from five major earthquakes between 1964 and 1983 recorded in Japan, China, the USA and Romania. Good results have been demonstrated for the proposed algorithm. Classification accuracy is 100% for the combination of the optimization algorithms with the FSVM classifier. The results show that the best kernel used in the training of the FSVM classifier is a radial basis function (RBF). According to the experimental results, the proposed algorithm can improve classification accuracy and that it is a feasible method for predicting soil liquefaction using the optimal parameters of the classifier with no user interface.

     

Effect of earthquake ground motions on soil liquefaction

During the 2011 off the Pacific Coast of Tohoku Earthquake, which was the largest earthquake in Japanese history, the soil liquefaction phenomenon was observed over a wide area along the Pacific Coast in Tohoku and in Kanto, including the Tokyo Bay area. Extensive damage was caused by the effect of soil liquefaction to residential lands and houses, as well as to infrastructures, such as roads, rivers, ports, and water supply/sewage systems. Since the 2011 off the Pacific Coast of Tohoku Earthquake occurred in a mega-size fault zone, with an area of 500 km×200 km, the duration of the strong shaking was extremely long compared to that in the data recorded for past earthquakes. Clarifying the effect of the characteristics of the ground motion on the soil liquefaction mechanism is one of the essential studies to be conducted, and effective countermeasures for the damaged structures need to be found.This paper presents the strong motion observation data obtained on the liquefied and the non-liquefied grounds and raises preliminary discussions on the mechanism of soil liquefaction based on this data. The effect of the duration and the number of cyclic loadings on the progress of the soil liquefaction phenomenon is also compared with that found in past strong motion data.     

高速公路路基砂土液化防治

介绍了砂土液化对道路造成严重破坏,从砂土液化研究的历史及砂土液化的机理入手,分析了影响砂土液化的原因,阐述了目前用于判别砂土液化所采用的一些先进的方法;结合公路特点提出高速公路路基砂土液化防治措施。     

砂土液化研究概述

在查阅大量资料的基础上,叙述了砂土的液化机理、影响因素以及液化的分析、判别方法及常用的地基处理方法,并指出液化土的加固处理是抗震工程的重要组成部分,应引起重视。     

Efficient inverse lighting: A statistical approach

Given a scene to illuminate satisfying a specific set of lighting intentions, the inverse lighting techniques allow us to obtain the unknown light source parameters, such as light position or flux emission. This paper introduces a new inverse lighting approach that uses the radiosity mean and variance to define lighting intentions of a scene. It is shown that these statistical parameters can be obtained without the previous calculation of the radiosity of the scene. Avoiding the explicit computation of the illumination of the scene results in a drastic reduction of the time required for the inverse process. This approach also provides a methodology that transforms a current set of lighting intentions into a single lighting intention with statistical parameters. The tests show that the processing time for solving the inverse problem can be reduced to a few seconds in most cases, improving previous work.     

Seismic gravelly soil liquefaction assessment based on dynamic penetration test using expanded case history dataset

The seismic liquefaction has been observed in gravelly soils, in addition to sandy soils. Despite sandy soils, there is still a shortage of an extended case history database for developing empirical, semi-empirical, and probabilistic models to predict this phenomenon in gravelly soils. This study examines the documentations of several case histories of gravelly soil liquefaction all around the world to create a database, and then to develop probabilistic models to consider uncertainties of the models as well as the parameters for evaluating gravelly soil liquefaction triggering caused by earthquakes. The logistic regression and Bayesian mapping function, both of which are based on the maximizing likelihood estimation, were applied to present classifier curves to predict the occurrence of liquefaction. Additionally, a sensitivity analysis on the bias sampling weighting factor was performed to assess its effect on the model’s prediction accuracy. The results point to the effect of extended database and sampling bias on the developed models. Meanwhile, this study highlights the importance of developing probabilistic models rather than deterministic ones to consider uncertainties.

     

Probabilistic models for the initiation of seismic soil liquefaction

A Bayesian framework for probabilistic assessment of the initiation of seismic soil liquefaction is described. A database, consisting of post-earthquake field observations of soil performance, in conjunction with in situ “index” test results is used for the development of probabilistically-based seismic soil liquefaction initiation correlations. The proposed stochastic model allows full and consistent representation of all relevant uncertainties. including (a) measurement/estimation errors, (b) model imperfection, (c) statistical uncertainty, and (d) inherent variabilities. Different sets of probabilistic liquefaction boundary curves are developed for the seismic soil liquefaction initiation hazard problem, representing various sources of uncertainty that are intrinsic to the problem. The resulting correlations represent a significant improvement over prior efforts, producing predictive relationships with enhanced accuracy and greatly reduced overall model uncertainty.     

饱和土液化判别公式的讨论

对2010版和2001版建筑抗震设计规范中饱和土液化判别公式进行了分析和讨论,指出了液化初判公式中几个尚未考虑到的问题;重点讨论了两本规范在液化判别公式形式、判别深度以及参数取值等方面的不同点,并得出了一些有益的结论,具有一定指导意义。