Determination of Partial Safety Coefficients of Structural Reliability Based on Contaminated Distribution

Partial safety factors must be evaluated precisely for the given target reliability index to ensure the certain level of structural reliability due to uncertain factors.The current studies of partial safety factors do not consider human error in construction for structural reliability.A mathematically model should be improved to simulate the partial safety coefficient concerned uncertainty factors which concern the effect of human error in construction.We employ the contaminated distribution to obtain the realistic mean value and standard variance of variable of structural parameters which coexist with random error human error.The reasonable partial safety coefficient can be calculated based on the realistic value of structural parameters concerned the effects of random error and gross error.

Nonparametric estimation for contamination distribution

In the paper, for the contamination distribution model F（x） = （1-α）F1（x）＋αF2（x）, the estimates of α and F1 （x） are studied using two different ways when F2 （x） is known and the strong consistency of the two estimates is proved. At the same time the consistency rate of estimate α is also given.

Particle size distribution and characteristics of heavy metals in road-deposited sediments from Beijing Olympic Park

Due to rapid urbanization and industrialization, heavy metals in road-deposited sediments（RDSs） of parks are emitted into the terrestrial, atmospheric, and water environment, and have a severe impact on residents＇ and tourists＇ health. To identify the distribution and characteristic of heavy metals in RDS and to assess the road environmental quality in Chinese parks, samples were collected from Beijing Olympic Park in the present study. The results indicated that particles with small grain size（〈150 μm） were the dominant fraction. The length of dry period was one of the main factors affecting the particle size distribution, as indicated by the variation of size fraction with the increase of dry days. The amount of heavy metal（i.e., Cu, Zn, Pb and Cd） content was the largest in particles with small size（〈150 μm） among all samples. Specifically, the percentage of Cu, Zn, Pb and Cd in these particles was 74.7%, 55.5%, 56.6% and 71.3%, respectively.Heavy metals adsorbed in sediments may mainly be contributed by road traffic emissions. The contamination levels of Pb and Cd were higher than Cu and Zn on the basis of the mean heavy metal contents. Specifically, the geoaccumulation index（I geo） decreased in the order：Cd〉Pb〉Cu〉Zn. This study analyzed the mobility of heavy metals in sediments using partial sequential extraction with the Tessier procedure. The results revealed that the apparent mobility and potential metal bioavailability of heavy metals in the sediments, based on the exchangeable and carbonate fractions, decreased in the order： Cd〉Zn≈Pb〉Cu.

Variational quality control of non-Gaussian innovations and its parametric optimizations for the GRAPES m3DVAR system

The magnitude and distribution of observation innovations,which have an important impact on the analyzed accuracy,are critical variables in data assimilation.Variational quality control(VarQC)based on the contaminated Gaussian distribution(CGD)of observation innovations is now widely used in data assimilation,owing to the more reasonable representation of the probability density function of innovations that can sufficiently absorb observations by assigning different weights iteratively.However,the inaccurate parameters prevent VarQC from showing the advantages it should have in the GRAPES(Global/Regional Assimilation and PrEdiction System)m3DVAR system.Consequently,the parameter optimization methods are considerable critical studies to improve VarQC.In this paper,we describe two probable CGDs to include the non-Gaussian distribution of actual observation errors,Gaussian plus flat distribution and Huber norm distribution.The potential optimization methods of the parameters are introduced in detail for different VarQCs.With different parameter configurations,the optimization analysis shows that the Gaussian plus flat distribution and the Huber norm distribution are more consistent with the long-tail distribution of actual innovations compared to the Gaussian distribution.The VarQC’s cost and gradient functions with Huber norm distribution are more reasonable,while the VarQC’s cost function with Gaussian plus flat distribution may converge on different minimums due to its nonconcave properties.The weight functions of two VarQCs gradually decrease with the increase of innovation but show different shapes,and the VarQC with Huber norm distribution shows more elasticity to assimilate the observations with a high contamination rate.Moreover,we reveal a general derivation relationship between the CGDs and VarQCs.A novel schematic interpretation that classifies the assimilated data into three categories in VarQC is presented.They are conducive to the development of a new VarQC method in the future.