The main objective of this study is to characterize the main factors which may affect the behavior of segmental prestressed concrete beams comprised of multi segments. The 3-D finite element program ABAQUS was utilized. The experimental work was conducted on twelve simply supported segmental prestressed concrete beams divided into three groups depending on the precast segments number. They all had an identical total length of 3150mm, but each had different segment numbers (9, 7, and 5 segments), in other words, different segment lengths. To simulate the genuine fire disasters, nine beams were exposed to high-temperature flame for one hour, the selected temperatures were 300°C (572°F), 500°C (932°F) and 700°C (1292°F) as recommended by ASTM–E119. Four numerical models have been utilized to represent the unburned and the burned specimens at the three elevated temperatures. Calibration and simulation of the experimental work were conducted, while comparisons were made with the experimental results. These included the prestress effect, load-deflection relation under applied load, and load at failure of the reference beam and the beams after the exposure to fire.
The present work presents a new experimental study of the enhancement of turbulent
convection heat transfer inside tubes for combined thermal and hydrodynamic entry length of one
popular “turbulator” (twisted tape with width slightly less than internal tube diameter) inserted for
fire tube boilers. Cylindrical combustion chamber was used to burn (1.6 to 7kg/h) fuel oil #2 to
deliver hot gases with ranges of Reynolds number (10500 to 21700), and (11400 to 24150) for both
empty and inserted tube respectively.A uniform wall temperature technique was used by keeping
approximately constant water temperature difference (25ºC) between inlet and exit cooling water in
parallel flow shell and tube heat exchanger. The test
This paper tackles with principal component analysis method (PCA ) to dimensionality reduction in the case of linear combinations to digital image processing and analysis. The PCA is statistical technique that shrinkages a multivariate data set consisting of inter-correlated variables into a data set consisting of variables that are uncorrelated linear combination, while ensuring the least possible loss of useful information. This method was applied to a group of satellite images of a certain area in the province of Basra, which represents the mouth of the Tigris and Euphrates rivers in the Shatt al-Arab in the province of Basra.
... Show MoreIs in this research review of the way minimum absolute deviations values based on linear programming method to estimate the parameters of simple linear regression model and give an overview of this model. We were modeling method deviations of the absolute values proposed using a scale of dispersion and composition of a simple linear regression model based on the proposed measure. Object of the work is to find the capabilities of not affected by abnormal values by using numerical method and at the lowest possible recurrence.
The expansion of building blocks at the expense of agricultural land is one of the main problems causing climate change within the urban area of a city. The research came to determine these indicators, as a study was conducted on the expansion of the building blocks in three municipalities in the city of Baghdad for a period of four decades extended in the form of time cycles for the period (1981-2021) and using ArcMap GIS 10.7 technology. Then, the impact of this expansion on temperature rates was evaluated, as they are the most important climatic elements due to their significant effect on the rest of the elements. The results showed a clear, direct relationship between the increase in urban expansion rates and the corresponding r
... Show MoreAdult of dipterous flies were collected monthly from exposed animals carcasses during the period from February 2006 to January 2007 in Baghdad city. The results obtained showed that flies could be collected all over the year with variation of their population density in different seasons. The majority of the collected species were abundant during Spring and late Autumn (at lowest numbers) . In this investigation, nineteen species confined to four families were collected; these families are: Calliphoridae, Muscidae, Sarcophagidae and Fanniidae. The species Musca domestica Linn .was the most abundant followed by Chrysomya megacephala ( Fabricius ) , while Pollenia sp . and Fannia sp . were the least abundant species.
The experiment was carried out at the Field Crops Research Station, College of Agricultural Engineering Sciences - University of Baghdad in Jadiriyah, with the aim of evaluating the performance of partial diallel hybrids and inbred lines of maize and estimating general combining ability(GCA), specific combining ability (SCA) and some genetic parameters. The experiment was carried out in two seasons, spring and fall 2020. Eight inbred lines of maize were used in the study (BI9/834, BSW18, LW/5 L8/844, ZA17W194, Z117W, ZI17W9, ZI7W4), numbered (1,2,3,4,5,6,7,8), It was sowed in the spring season and entered into a cross-program according to a partial diallel crossing system to obtain tw
Near surface mounted (NSM) carbon fibers reinforced polymer (CFRP) reinforcement is one of the techniques for reinforcing masonry structures and is considered to provide significant advantages. This paper is composed of two parts. The first part presents the experimental study of brick masonry walls reinforced with NSM CFRP strips under combined shear-compression loads. Masonry walls have been tested under vertical compression, with different bed joint orientations 90° and 45° relative to the loading direction. Different reinforcement orientations were used including vertical, horizontal, and a combination of both sides of the wall. The second part of this paper comprises a numerical analysis of unreinforced brick masonry (URM) wa
... Show MoreThis paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe
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