The objective of this research is to study experimentally and theoretically the girder vertical load share of the curved I-Girder bridges subjected to the point load in addition to the self-weigh and supper imposed dead loads. The experimental program consist of manufacturing and testing the five simply supported bridge models was scaled down by (1/10) from a prototype of 30m central span. The models carriageway central radii are 30 m, 15m or 10m. The girder spacing of the first two models is 175 mm with an overall carriageway width of 650mm. The girder spacing of the other three bridge models is 200mm with the overall carriageway width of 700 mm. The overall depth of the composite section was 164 mm. To investigate the effect of live load position on the girder vertical load share a point load was applied at different load levels and was varied across bridge width. Experimental results show that the main factor effect on the girder load share were the point load position, load level and the bridge curvature value, while the girder spacing had a less effect than that. The ANSYS Worckbench 14.5 commercial software was adopted to build up the Finite Element model. Results have shown that the numerical model was slightly stiffer than the experimental test bridge model. A good agreement was obtained between the experimental and analytical results for all models, the maximum deviation in results reach to13% in such a single case, while the convergence results are the prevailing situation.
(14)
(10)
(27)
(25)
Prediction of daily rainfall is important for flood forecasting, reservoir operation, and many other hydrological applications. The artificial intelligence (AI) algorithm is generally used for stochastic forecasting rainfall which is not capable to simulate unseen extreme rainfall events which become common due to climate change. A new model is developed in this study for prediction of daily rainfall for different lead times based on sea level pressure (SLP) which is physically related to rainfall on land and thus able to predict unseen rainfall events. Daily rainfall of east coast of Peninsular Malaysia (PM) was predicted using SLP data over the climate domain. Five advanced AI algorithms such as extreme learning machine (ELM), Bay
... Show More
(22)
(16)
(7)
(9)
(34)
(28)
(38)
(37)
(2)
Land Use / Land Cover (LULC) classification is considered one of the basic tasks that decision makers and map makers rely on to evaluate the infrastructure, using different types of satellite data, despite the large spectral difference or overlap in the spectra in the same land cover in addition to the problem of aberration and the degree of inclination of the images that may be negatively affect rating performance. The main objective of this study is to develop a working method for classifying the land cover using high-resolution satellite images using object based method. Maximum likelihood pixel based supervised as well as object approaches were examined on QuickBird satellite image in Karbala, Iraq. This study illustrated that
... Show More
(12)
(7)
(78)
(61)
The present paper(Spacio-Temporal Relations in the Translated Text in Both Russian and Arabic) focuses on the spacio-temporal effect in the translated text; it is possible to compose the translation text simultaneously with the process of the composing the original text. This is carried out during the simultaneous consecutive translation. And, the time and place of composing the translation might greatly differ from the time and place of composing the original textt. The translator may tackle a text of an ancient time and written in a language which might have changed, and may thus appear as another language where the author might have talked on behalf of a people who had lived or are living in apparently different geographic
... Show More