No abstract

This paper investigated the seismic retrofitting of an existing cable-stayed bridge through the use of a seismic isolation system. The bridge is situated in a high seismic zone. During the Saguenay earthquake 1988, one of the anchorage plates of the bridge supports failed. Herein, several configurations of seismic isolation system were considered to identify an appropriate solution for the seismic retrofitting of the bridge in both the longitudinal and transverse directions. A three-dimensional model of the bridge was created, and its seismic behavior studied through nonlinear dynamic time-history analysis. The comparative performance study among the five retrofitting configurations showed that the partial seismic isolation of the bridge led to an enhancement of the seismic response of the bridge in one direction only. However, the overall seismic response of the cable-stayed bridge substantially improved in the longitudinal and transverse directions in cases where the isolation systems were utilized between the supports and the deck-tower connection of the bridge.

Predicting hydrological variables is a very useful tool in water resource management. The importance of the forecast in environmental issues causes us to use more accurate statistical methods for studying the weather and climate change. The main objective of this study is to investigate the use of additive and multiplicative forms of the Holt-Winters time series model to predict environmental variables such as temperature, precipitation, and sunshine hours for one year in advance. As the Holt-Winters model uses a weighted average of current and past values to provide predictions, in this study higher emphasis is placed on the recent observations by using larger weights for these data compared to the older ones. As a case study, monthly environmental data (i.e., precipitation, maximum temperature, minimum temperature and sunshine hours) collected for a span of 30 years (from 1981 to 2010) from Robat Gharah-BilStation located in Golestan, Iran was used. After modeling the data through additive and multiplicative procedures, the main three smoothing parameters of the model are optimized using a nonlinear optimization method. Based on this study, using the multiplicative form of Holt-Winters time series results in an overall of 4% less mean absolute percentage error (MAPE) compared to the additive one. The result showed that this model is more efficient in predicting and modeling climate parameters, which show stable patterns of cycle and seasonality.

The Bio-Ecological Drainage System (BIOECODS) is a sustainable drainage system, which adopt a "control at source" approach for urban stormwater management in Malaysia. This study attempted to model a small-scale BIOECODS using InfoWorks SD. New modelling techniques are used to fully integrate/couple the surface and on-line subsurface conveyance system, in which overland flow routing is described by a stormwater management model that uses nonlinear reservoir method and kinematic wave approximation of the St Venant equation, and subsurface flow is described by Horton method in conjunction with Soil Conservation Service (SCS) curve number (CN) method. The observed water levels at primary outlets are compared with those obtained from model simulation. The modelling approach/technique has been proven successful as the hydrographs (predicted and observed) match each other closely, with a mean error in the range of 4.58-7.32%. Results from the model showed that the BIOECODS is able to attenuate peak flow by 60-75%, and increase the lag time by 20 mins within an area of <28300 m 2 when compared with a traditional drainage system.

There are different ways to estimate suspended sediment load of a river. The conventional sediment rating curve model has been used widely due to its simplicity and required parameters. The most important limitation of the conventional SRC model is its relatively low precision and underestimation of the suspended sediment load in most studies. However, in this study, the concept of SRC model segmentation is introduced based on the curve slope under the title of developed SRC-S model. The most important feature is the simplicity of the presented application. To compare the conventional SRC and the developed SRC-S models, data from two hydrometry stations in northern Iran were selected. Graphical study of the models shows that the developed SRC-S model enjoys more fitting precision in comparison with the conventional SRC model, and also has improved underestimation error of suspended sediment load in higher rates of river flow discharge. Six numerical criteria for model accuracy (Nash-Sutcliffe, root-mean-square error, and mean absolute error, difference ratio, efficiency ratio improved and index of agreement) are used for quantitative comparison of the results of conventional and developed models. Accordingly, we found that the mentioned criteria have improved significantly compared to the conventional model.