Corrosion- induced damage in reinforced concrete structure such as bridges, parking garages, and buildings, and the related cost for maintaining them in a serviceable condition, is a source of major concern for the owners of these structures.
Fly ash produced from south Baghdad power plant with different concentrations (20, 25 and 30) % by weight from the cement ratio were used as a corrosion inhibitor as a weight ratio from the cement content.
The concrete batch ratio under study was (1:1.5:3) cement, sand and gravel respectively which is used in Iraq. All the raw materials used were locally manufactured.
Concrete slabs (250x250x70) mm dimensions were casted, using Poly-wood molds. Two steel bars were embedded in the central position of each slab at the mid- height (about 35 mm), with a space of 100 mm between each other.
A 16 concrete slabs were prepared (0, 20, 25 and 30) wt. % of fly ash. The specimens were partially immersed in 3.5 wt. % NaCl solution in order to predict the corrosion.
Half-cell potential test technique was used to estimate the corrosion rate which is occurred in the steel bar due to the migration of chloride ions through the concrete, depending on the ASTM C876-08.
The result shows that the potential values of steel in concrete were shifts to the positive direction with increasing the percentage of fly ash, because the reduction of porosity by the addition of fly ash which fill the pores and inhibit the chloride ions to reach to steel.
The results also show that the further increase of fly ash (30%) the possibility of carbonation is increased which result in reduction its alkalinity, thereby permitting corrosion of embedded steel.
The 3-parameter Weibull distribution is used as a model for failure since this distribution is proper when the failure rate somewhat high in starting operation and these rates will be decreased with increasing time .
In practical side a comparison was made between (Shrinkage and Maximum likelihood) Estimators for parameter and reliability function using simulation , we conclude that the Shrinkage estimators for parameters are better than maximum likelihood estimators but the maximum likelihood estimator for reliability function is the better using statistical measures (MAPE)and (MSE) and for different sample sizes.
Note:- ns : small sample ; nm=median sample
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In this paper , concrete micro-piles were used to improve the bearing capacity of the soil which is supporting the shallow foundation by using groups of (4; 6 and 9)bored short micro-piles which have, (D=0.125m and D=0.1m), and length to diameter ratio (L/D) equal to (6; 10 and 12) respectively. To calculate the bearing capacity of the micro-piles,(Tomlinson) and (Lamda) methods were used; also the soil properties were taken from Al-Muthana airport,(Al-Qyssi,2001) [1]. The results show that; increasing the number of piles and/ or the diameters and lengths; and the interaction between the bearing capacity of the shallow foundation with the bearing capacity of the pile group which leads to increasing the strength against the external loads
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One of the most important challenges facing project management at present time is to ensure project accomplishment in spite of the specific restrictions like the specific time the financial resources specialized to do the project ; which require an accurate consideration for time and cost . the modern village project (residential building aspect) is one of the great project that ministry of agriculture is trying to do Wasit governorate it is chosen as the work in this project is dilatory for that is being studied in term of some modern mathematical and scientific methods like critical path method (CPM)which is one of the project management and scheduling methods to know the time needed to accomplish residential building pro
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This investigation aims to explore the potential of waterworks sludge (WS), low-cost byproduct of water treatment processes, as a sorbent for removing Congo Red (CR) dyes. This will be achieved by precipitating nano-sized (MgAl-LDH)-layered double hydroxide onto the surface of the sludge. The efficiency of utilizing MgAl-LDH to modify waterworks sludge (MWS) for use in permeable reactive barrier technology was confirmed through analysis with Fourier transform infrared and X-ray diffraction. The isotherm model was employed to elucidate the adsorption mechanisms involved in the process. Furthermore, the COMSOL model was utilized to establish a continuous testing model for the analysis of contaminant transport under diverse conditions. A st
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This investigation aims to explore the potential of waterworks sludge (WS), low-cost byproduct of water treatment processes, as a sorbent for removing Congo Red (CR) dyes. This will be achieved by precipitating nano-sized (MgAl-LDH)-layered double hydroxide onto the surface of the sludge. The efficiency of utilizing MgAl-LDH to modify waterworks sludge (MWS) for use in permeable reactive barrier technology was confirmed through analysis with Fourier transform infrared and X-ray diffraction. The isotherm model was employed to elucidate the adsorption mechanisms involved in the process. Furthermore, the COMSOL model was utilized to establish a continuous testing model for the analysis of contaminant transport under diverse conditions.
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The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. To automate and optimize these procedures, AI algorithms such as character recognition, facial recognition, predictive algorithms and automatic data processing can be implemented. The proposed method is to use the R-CNN object detection model to detect passport objects in real-time images collected by passport control cameras. This paper describes the step-by-step process of the proposed approach, which includes pre-processing, training and testing the R-CNN model, integrating it into the passport control system, and evaluating its accuracy and speed for efficient passenger flow
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The map of permeability distribution in the reservoirs is considered one of the most essential steps of the geologic model building due to its governing the fluid flow through the reservoir which makes it the most influential parameter on the history matching than other parameters. For that, it is the most petrophysical properties that are tuned during the history matching. Unfortunately, the prediction of the relationship between static petrophysics (porosity) and dynamic petrophysics (permeability) from conventional wells logs has a sophisticated problem to solve by conventional statistical methods for heterogeneous formations. For that, this paper examines the ability and performance of the artificial intelligence method in perme
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