This research is devoted to investigate relationship between both Ultrasonic Pulse Velocity and Rebound Number (Hammer Test) with cube compressive strength and also to study the effect of steel reinforcement on these relationships.
A study was carried out on 32 scale model reinforced concrete elements. Non destructive testing campaign (mainly ultrasonic and rebound hammer tests) made on the same elements. About 72 concrete cubes (15 X 15 X15) were taken from the concrete mixes to check the compressive strength.. Data analyzed.Include the possible correlations between non destructive testing (NDT) and compressive strength (DT) Statistical approach is used for this purpose. A new relationships obtained from correlations results is give

Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's p

Wellbore instability and sand production onset modeling are very affected by Sonic Shear Wave Time (SSW). In any field, SSW is not available for all wells due to the high cost of measuring. Many authors developed empirical correlations using information from selected worldwide fields for SSW prediction. Recently, researchers have used different Artificial Intelligence methods for estimating SSW. Three existing empirical correlations of Carroll, Freund, and Brocher are used to estimate SSW in this paper, while a fourth new empirical correlation is established. For comparing with the empirical correlation results, another study's Artificial Neural Network (ANN) was used. The same data t

Machine learning has a significant advantage for many difficulties in the oil and gas industry, especially when it comes to resolving complex challenges in reservoir characterization. Permeability is one of the most difficult petrophysical parameters to predict using conventional logging techniques. Clarifications of the work flow methodology are presented alongside comprehensive models in this study. The purpose of this study is to provide a more robust technique for predicting permeability; previous studies on the Bazirgan field have attempted to do so, but their estimates have been vague, and the methods they give are obsolete and do not make any concessions to the real or rigid in order to solve the permeability computation. To

An experiment was conducted in a greenhouse - research station B - College of Agricultural Engineering Sciences, University of Baghdad, during the fall season of 2018 with the aim of propagating and initially studying the field performance of 18 and 20 potential potato lines derived from Rivera and Arizona cv. after in vitro exposure of nodal segments to different dosages of gamma rays (0, 10, 20, and 30 Gray) and EMS (0, 10, 20, and 30 mM). Each control cultivar and their derived lines were independently cultured in plastic bags according to the RCBD, with three replications. The results showed that the highest plant height and number of leaves were obtained from Arizona derived lines which gave 60.11 cm and 25.30 leaves.plant-1 in

Experiments have been conducted to study the local and average heat transfer by mixed
convection for hydrodynamically fully developed, thermally developing and fully developed
laminar upward air flow in an inclined annulus with adiabatic inner cast iron tube and uniform
heated outer aluminum tube with an aspect ratio ( Ω = 0.72) and (L/Dh≈40) for both calming and
test sections). A wide range of Reynolds number from 859 to 2024 has been covered, and heat
flux has been varied from 159 W/m2 to 812 W/m2 (these values of heat flux and Reynolds
number gave Richardson number range from 0.03 to 0.٣٨), with angles of annulus inclination
φ =0o (horizontal position), φ =60o (inclined position), and φ =90o (vertical posi

The aim of this study is to investigate the existence of some heavy metals (lead, cadmium, chromium) in colored plastic table dishes and study the migration of these metals to the food meals and the affecting factors in migration , such as storage period and food temperature. Six kinds of colored plastic table dishes were collected from Baghdad markets. The heavy metals in table dishes and in the prepared food meals put in them were estimated using atomic absorption spectrophotometer (Shimadzu A5000). The results indicated the existence of lead in all samples (1.61_1.00 mg/ kg) and chromium in three samples (0.85_0.97 mg/ kg) while other samples are free of chromium, and cadmium. Investigating the migration of these metals to food at dif

A hand gesture recognition system provides a robust and innovative solution to nonverbal communication through human–computer interaction. Deep learning models have excellent potential for usage in recognition applications. To overcome related issues, most previous studies have proposed new model architectures or have fine-tuned pre-trained models. Furthermore, these studies relied on one standard dataset for both training and testing. Thus, the accuracy of these studies is reasonable. Unlike these works, the current study investigates two deep learning models with intermediate layers to recognize static hand gesture images. Both models were tested on different datasets, adjusted to suit the dataset, and then trained under different m

Groundwater can be assessed by studying water wells. This study was conducted in Al-Wafa District, Anbar Governorate, Iraq. The water samples were collected from 24 different wells in the study area, in January 2021. A laboratory examination of the samples was conducted. Geographical information systems technique was relied on to determine the values of polluting elements in the wells. The chemical elements that were measured were [cadmium, lead, cobalt and chromium]. The output of this research were planned to be spatial maps that show the distribution of the elements with respect to their concentrations. The results show a variation in the heavy elements concentrations at the studied area groundwater. The samples show different values