Search published articles


Showing 5 results for Random Field

Afshin Firouzi, Ali Reza Rahai,
Volume 9, Issue 3 (9-2011)
Abstract

Corrosion of reinforcement due to frequently applied deicing salts is the major source of deterioration of concrete bridge decks, e.g. severe cracking and spalling of the concrete cover. Since crack width is easily recordable in routine visual inspections there is a motivation to use it as an appropriate indicator of condition of RC bridge elements in decision making process of bridge management. While few existing research in literature dealing with spatial variation of corrosion-induced cracking of RC structures is based on empirical models, in this paper the extent and likelihood of severe cracking of a hypothetical bridge deck during its lifetime is calculated based on a recently proposed analytical model for corrosion-induced crack width. Random field theory has been utilized to account for spatial variations of surface chloride concentration, as environmental parameter, and concrete compressive strength and cover depth as design parameters. This analysis enables to track evolution of cracking process, spatially and temporally, and predict the time for the first repair of bridge deck based on acceptable extent of cracked area. Furthermore based on a sensitivity analysis it is concluded that increasing cover depth has a very promising effect in delaying corrosion phenomenon and extension of the service life of bridge decks.


A. Tarighat,
Volume 10, Issue 4 (12-2012)
Abstract

Chloride ion ingress in concrete is the main reason of concrete corrosion. In real world both uncertainty and stochasticity are

main attributes of almost all measurements including testing and modeling of chloride content profile in concrete. Regarding

these facts new models should be able to represent at least some of the uncertainties in the predictions. In this paper after

inspiration from classical physics related to diffusion and random walk concepts a stochastic partial differential equation (SPDE)

of diffusion is introduced to show a more realistic modeling/calibration scheme for construction of stochastic chloride content

profile in concrete. Diffusion SPDE provides a consistent quantitative way of relating uncertainty in inputs to uncertainty in

outputs. Although it is possible to run sensitivity analysis to get some statistical results from deterministic models but the nature

of diffusion is inherently stochastic. Brownian motion process (Wiener process) is used in SPDE to simulate the random nature

of the diffusion in heterogeneous media or random fields like concrete. The proposed method can be used to calibrate/model the

chloride ion profile in concrete by only some limited data for a given depth. Then the stochastic chloride ion diffusion can be

simulated by langevin equation. Results of the method are compared with data from some references and all show good

agreements.


M. B. Esfandiari Sowmehsaraei, R. Jamshidi Chenari,
Volume 12, Issue 1 (1-2014)
Abstract

Soil reinforced with fiber shows characteristics of a composite material, in which fiber inclusion has a significant effect on soil permeability. Concerning to the higher void ratio of carpet fibers, at first stages it may be expected that an increase in fiber content of the reinforced soil would result in an increase in permeability of the mixture. However, the present article demonstrates that fiber inclusion will decrease the permeability of sand-fiber composite.A series of constant head permeability tests have been carried out to show the effects and consequently, a new system of phase relationships was introduced to calculate the dry mass for the sand portion of the composite. Monte Carlo simulation technique adopted with finite element theory was employed to back calculate the hydraulic conductivity of individual porous fibers from the laboratory test results. It was observed that the permeability coefficient of the porous fibers are orders of magnitude less than the skeletal sand portion due to the fine sand particle entrapment and also the fiber volume change characteristics.
R. Jamshidi Chenari, P. Pishgah ,
Volume 12, Issue 2 (4-2014)
Abstract

In this technical note, a methodology is introduced for reliability calculation of consolidation settlement based on cone penetration test (CPT) data. The present study considers inherent soil variability which influences consolidation settlements results. To proceed reliability analysis, the measured data of a sample corrected cone tip resistance (􀝍􀯧) is detrended using a quadratic trend and the residuals are assumed to be lognormally distributed random field. Realizations of 􀝍􀯧 is generated by using spatial variability of residuals including standard deviation and the scale of fluctuation. The quadratic trend and the generated residuals are then combined to correlate shear and bulk modulus as input consolidation properties for coupled analysis and subsequently consolidation settlement was calculated by using finite difference method adopted in Monte Carlo simulations. The results of reliability analysis are presented describing the range of possible settlements by considering characteristics of uncertainties involved at the particular site. Number of realizations rendering settlements smaller than the allowable settlement must be such that guarantee proper performance or acceptable reliability index.
Khaled Farah, Mounir Ltifi, Tarek Abichou, Hedi Hassis,
Volume 12, Issue 3 (7-2014)
Abstract

The purpose of this study is to compare the results of different probabilistic methods such as the perturbation method, Stochastic Finite Element Method (SFEM) and Monte Carlo Method. These methods were used to study the convergence of direct approach for slope stability analysis and are developed for a linear soil behavior. In this study, two dimensional random fields are used and both the First Order Reliability Method (FORM) and Limited Step Length Iteration Method (LSLIM) have been adopted to evaluate the reliability index. The study found that the perturbation method of the second order is easy to apply using the field’s theory because accuracy is reached even with different coefficients of variation of input variables, while the spectral finite element method yields accurate results only for high levels of solution development.

Page 1 from 1     

© 2019 All Rights Reserved | International Journal of Civil Engineering

Designed & Developed by : Yektaweb