Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an ob

Codes of red, green, and blue data (RGB) extracted from a lab-fabricated colorimeter device were used to build a proposed classifier with the objective of classifying colors of objects based on defined categories of fundamental colors. Primary, secondary, and tertiary colors namely red, green, orange, yellow, pink, purple, blue, brown, grey, white, and black, were employed in machine learning (ML) by applying an artificial neural network (ANN) algorithm using Python. The classifier, which was based on the ANN algorithm, required a definition of the mentioned eleven colors in the form of RGB codes in order to acquire the capability of classification. The software's capacity to forecast the color of the code that belongs to an object under de

Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti

    In the drilling and production operations, the effectiveness of cementing jobs is crucial for efficient progress. The compressive strength of oil well cement is a key characteristic that reflects its ability to withstand forceful conditions over time. This study evaluates and improves the compressive strength and thickening time of Iraqi oil well cement class G from Babylon cement factory using two types of additives (Nano Alumina and Synthetic Fiber) to comply with the American Petroleum Institute (API) specifications. The additives were used in different proportions, and a set of samples was prepared under different conditions. Compressive strength and thickening time measurements were taken under different conditions. The amoun

Six proposed simply supported high strength-steel fiber reinforced concrete (HS-SFRC) beams reinforced with FRP (fiber reinforced polymer) rebars were numerically tested by finite element method using ABAQUS software to investigate their behavior under the flexural failure. The beams were divided into two groups depending on their cross sectional shape. Group A consisted of four trapezoidal beams with dimensions of (height 200 mm, top width 250 mm, and bottom width 125 mm), while group B consisted of two rectangular beams with dimensions of (125 ×200) mm. All specimens have same total length of 1500 mm, and they were also considered to be made of same high strength concrete designed material with 1% volume fraction of steel fiber.

This study aims to investigate the behavior and strength of self-compacted ferrocement slabs under punching shear load. Experimental results of thirteen square ferrocement slabs of 500×500 mm simply supported on all edges are presented.  The main parameters investigated include the volume fraction of reinforcement, slab thickness and size of load-bearing plate. The load deflection and cracking characteristics of the tested slabs are studied and compared.  The test results showed that the volume fraction of wire mesh has significant effect on both ultimate load and displacement. The increase of slab thickness leads to decrease in deflection values and increase in stiffness of slabs. Both ductility and stiffness increase as the

This paper presents the application of nonlinear finite element models in the analysis of dapped-ends pre-stressed reinforced concrete girders under static loading by using ANSYS software. The girder dimensions are (4.90 m span, 0.40 m depth, 0.20 m width, 0.20 m nib depth, and 0.10 m nib length) and the parameters considered in this research are the pre-stress effect, and strand profile (straight and draped).

    The numerical results are compared with the experimental results of the same girders. The comparisons are carried out in terms of initial prestress effect, load- deflection curve, and failure load. Good agreement was obtained between the analytical and experimental results. Even that, the

The present work is concerned with the investigation of the behavior and ultimate capacity of axially loaded reinforced concrete columns in presence of transverse openings under axial load plus uniaxial bending. The experimental program includes testing of twenty reinforced concrete columns (150 × 150 × 700 mm) under concentric and eccentric load. Parameters considered include opening size, load eccentricity and influence of the direction of load eccentricity with respect to the longitudinal axis of the opening. Experimental results are discussed based on load – lateral mid height deflection curves, load – longitudinal shortening behavior, ultimate load and failure modes. It is found that when the direction of load