Bayesian Parameter Identification and Model Selection for Normalized Modulus Reduction Curves of Soils

This work develops a procedure that involves the use of Bayesian approach to quantify data scatterness, estimates the optimal values of model parameters, and selects the most appropriate model for the construction of normalized modulus reduction curves of soils. The proposed procedure is then demonstrated using real observation data based on a set of comprehensive resonant column tests on coarse-grained soils conducted in the study.     

光导纤维光谱技术无损鉴定彩绘文物颜料的研究

为了克服传统的有损文物分析技术对文物造成的破坏,研制出一种简易光导纤维反射光谱仪。建立了光导纤维反射光谱技术对颜料分析鉴定的基本方法,提供了一种简捷的文物颜料无损分析鉴定的新技术。通过对西安、重庆等地彩绘文物颜料成分的鉴定,表明光导纤维反射光谱法测量结果准确、可靠,在文物颜料鉴定等方面具有广阔的应用前景。     

Unconditional Reliability-Based Design of Tuned Liquid Column Dampers Under Stochastic Earthquake Load Considering System Parameters Uncertainties

The reliability-based design of tuned mass damper considering system parameters uncertainties is noteworthy. However, the same is not the case for liquid dampers. The present study deals with the reliability-based design of tuned liquid column dampers under random earthquake considering system parameters uncertainties. Using the conditional second-order information of response quantities, the total probability concept is applied to evaluate the unconditional failure probability which is subsequently used as the objective function to obtain the damping parameters. A numerical study elucidates the effect of system parameters uncertainties on the damper parameters optimization and safety of the structure.     

Real-time Seismic Damage Detection of Concrete Shear Walls Using Artificial Neural Networks

Concrete shear walls are widely employed in buildings as a main resistance system against lateral loads. Early identification of seismic damage to concrete shear walls is vital for deciding post-earthquake occupancy in these structures. In this article, a method based on artificial neural networks for real-time identification of seismic damage to concrete shear walls was proposed. Inter-story drifts and plastic hinge rotation of concrete walls were used as the inputs and outputs of a MLP neural network. Modal Pushover Analysis was employed to prepare well-distributed data sets for training the neural network. The proposed method was applied to a five-story concrete shear wall building. The results from the network were compared with those obtained from Nonlinear Time History Analysis. It was observed that the trained neural network successfully detected damage to concrete shear walls and accurately estimated the severity of seismic-induced damage.     

Impact Stiffness of the Contact-Element Models for the Pounding Analysis of Highway Bridges: Experimental Evaluation

For the requirement of pounding analysis of highway bridges, how to properly choose the impact stiffness has become a primary issue for an achieving accurate result. This article presents an evaluation test of the impact stiffness of four types of contact-element models based on the shaking table test results of a steel highway bridge model. The analytical results indicate that the theoretical impact parameters are significantly larger than the identified values because the assumptions for deriving those models cannot match the actual impact conditions. The possible reasons causing those differences are discussed at the end of this study.     

Dynamic Characteristic Analysis of Two Adjacent Multi-grid Composite Wall Structures with a Seismic Joint by a Bayesian Approach

Field ambient vibration tests and modal identification using a Bayesian approach are conducted for a building made of multi-grid composite wall structure and divided into two adjacent parts by a seismic joint, to investigate the dynamic characteristics of the special structural type and the effects of the infilled seismic joint. It is found that dynamic interactions between the two structural parts exist possibly induced by the infill of the building separation. Natural frequencies obtained from other two modal parameter identification methods and modal analysis results of finite element models considering dynamic interactions agree with those identified by the Bayesian approach.     

周-汉毛织品上红色染料主要成分的鉴定

对一批西周-汉毛织品上的红色染料进行了分析研究。从毛织品上提取、分离得红色染料一主要成分,经质谱(EIMS)、紫外可见吸收光谱(UV)、H核磁共振谱(HNMR)、C核磁共振谱(CNMR)分析鉴定,其主要成分为紫茜素。所有毛织品红色染料的高效液相色谱分析结果与标准品茜草素、紫茜素一致,只是两成分之间的含量不同,因而判断这些毛织物上的红色染料均来源于茜草属植物。     

On-line Model Updating in Hybrid Simulation Tests

Hybrid simulation has emerged as a relatively accurate and efficient tool for the evaluation of structural response under earthquake loading. In conventional hybrid simulation the response of a few critical components is obtained by testing while the numerical module is assumed to follow an analytical idealization. Where there is a much larger number of analytical components compared to the experimental parts, the overall response may be dominated by the idealized parts hence the value of hybrid simulation is diminished. It is proposed to modify the material constitutive relationship of the numerical model during the test, based on the data obtained from the physically tested component. An approach based on genetic algorithms is utilized as an optimization tool to identify the constitutive relationship parameters used in updating the numerical model. The proposed model updating approach is verified through two analytical examples of steel and reinforced concrete frames. The results show the effectiveness of the updating process in minimizing the errors, compared to the assumed exact solution.     

Evaluation of the Nonlinear Seismic Response of an Earth Dam: Nonparametric System Identification

A system identification framework is proposed to investigate the nonlinear dynamic response of massive earth dams using the seismic motion recorded by a sparse array of accelerometers. The framework includes a methodical step of nonparametric analyses to characterize the involved loading conditions and response mechanisms. This nonparametric step provides essential information to reduce the indeterminacy of the associated parametric identificatin problem and ensure a proper model selection, calibration, and validation. The proposed framework was applied to the Long Valley earth dam (California) and benchmarked using records of a series of 1980 earthquakes. This article presents the conducted correlation, spectral motion reconstruction, and nonparametric stress-strain analyses. These analyses revealed a complex three-dimensional dynamic response marked by non uniform boundary conditions and a shear stress-strain behavior slightly less nonlinear than what was observed in triaxial tests of soil samples taken from the dam core.     

基于时变参数模型的中国房地产投资研究

房地产投资能够直接带动国民经济增长,但发展过快也会给经济带来负效应,协调好房地产投资与国民经济发展的关系尤为重要。本文首先综述国内外相关研究成果,发现现有定量研究无法真实反映房地产业本身结构的变化;其次,建立时变参数模型,对房地产投资与国民经济发展之间的关系进行了实证研究;最后得出研究结论和政策建议。本文的研究结论:一是房地产投资对GDP拉动作用显著;二是房地产投资受GDP、国内银行贷款以及利率的影响各不相同。与现有研究文献相比较,本文在研究视角和方法上均有-定的突破。