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Optimized stress-strain modeling of eco-friendly fiber-reinforced concrete members using meta-heuristic algorithms
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Eco-friendly concrete is produced using the waste of many industries. It reduces the fears concerning energy utilization, raw materials, and mass-produced cost of common concrete. Several stress-strain models documented in the literature can be utilized to estimate the ultimate strength of concrete components reinforced with fibers. Unfortunately, there is a lack of data on how non-metallic fibers, such as polypropylene (PP), affect the properties of concrete, especially eco-friendly concrete. This study presents a novel approach to modeling the stress-strain behavior of eco-friendly polypropylene fiber-reinforced concrete (PFRC) using meta-heuristic particle swarm optimization (PSO) employing 26 PFRC various mixtures. The cement was partially replaced by ground granulated blast furnace slag (GGBFS) with various amounts to make the concrete eco-friendly. The concrete was reinforced with several quantities of PP fiber. Specific cases of beams and cylinders made from PFRC were examined to learn more about their performance. The research contributes valuable insights to eco-friendly concrete design by integrating industrial byproducts (GGBFS) and non-metallic fibers, aligning with sustainable construction trends. The study demonstrates that adding sustainable fibers to concrete improves its structural integrity while lessening its environmental impact. Experimental testing validates the proposed model, showing a significant connection between the expected and actual stress-strain behavior. In terms of absolute relative error (ARE), the dataset proves that the suggested model has both the greatest (ARE 5 %) and worst (ARE > 15 %) frequencies. The proposed model demonstrates promising accuracy (R-value = 0.9975) and highlights the effectiveness of PSO in parameter optimization. Additionally, the usage of GGBFS instead of OPC resulted in CO2 reduction up to 42 %. Comparative analysis of the proposed model against existing models registered an excellent forecasted accuracy.

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Publication Date
Mon Apr 21 2025
Journal Name
Structural Concrete
On the effectiveness of shear reinforcement type in <scp>GFRP</scp>‐reinforced concrete beams: Experimental study
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Abstract<p>This study investigated the shear performance of concrete beams with GFRP stirrups vs. traditional steel stirrups. Longitudinal glass fiber‐reinforced polymer (GFRP) bars were used to doubly reinforce the tested beams at both the top and bottom of their cross sections. To accomplish this, several stirrup spacings were provided. Eight beam specimens, measuring 300 × 250 × 2400 mm, were used in an experimental program to test under a two‐point concentrated load with an equal span‐to‐depth ratio until failure. Four beams in Group I have standard mild steel stirrups of 8 mm diameter, while four beams in Group II have GFRP stirrups with the same adopted diameter. The difference betwe</p> ... Show More
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Publication Date
Thu Nov 29 2018
Journal Name
Civil Engineering Journal
Strength and Serviceability of Reinforced Concrete Deep Beams with Large Web Openings Created in Shear Spans
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Deep beams are used in wide construction fields such as water tanks, foundations, and girders in multi-story buildings to provide certain areas free of columns. In practice it is quite often occurring to create web opening in deep beams to supply convenient passage of ventilation ducts, cable channels, gas and water pipes. Experimental studies of ten 10 deep beams were carried out, where two of them are control specimens without openings and eight with large web openings in the shear spans. The variables that have been adopted are the ratio of the shear span to the overall depth of the member cross-section, location and dimensions of the opening. Test results showed that there was a decrease in the load carrying capacity of deep bea

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Publication Date
Tue Oct 01 2024
Journal Name
Dental Hypotheses
Evaluation of Impact, Tensile, and Flexural Strength of Natural Wool Fiber Reinforced Polymethyl Methacrylate Denture Base Material: An In Vitro Study
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Introduction: This study was carried out to assess the effect of natural wool fiber addition on the impact, tensile, and flexural strengths of the heat-cured acrylic denture base material. Methods: Short wool fibers with and without chemical surface treatment were added to polymethyl methacrylate (PMMA) at a percentage of 0.25% by weight. A total of 90 acrylic specimens were prepared and divided into three groups according to the tests performed. Impact strength, tensile strength, and flexural strength tests were evaluated. The statistical analysis of the results data was performed using the one-way analysis of variance (ANOVA) test and Tukey’s post hoc test

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Publication Date
Sat Dec 01 2012
Journal Name
Journal Of Engineering
Optimized Zero and First Order Design of Micro Geodetic Networks
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Precision is one of the main elements that control the quality of a geodetic network, which defines as the measure of the network efficiency in propagation of random errors. This research aims to solve ZOD and FOD problems for a geodetic network using Rosenbrock Method to optimize the geodetic networks by using MATLAB programming language, to find the optimal design of geodetic network with high precision. ZOD problem was applied to a case study network consists of 19 points and 58 designed distances with a priori deviation equal to 5mm, to determine the best points in the network to consider as control points. The results showed that P55 and P73 having the minimum ellipse of error and considered as control points. FOD problem was applie

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Publication Date
Sat Apr 19 2025
Journal Name
Plos One
Early Detection of Autism Spectrum Disorder in Children Using Different Machine Learning Algorithms
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Abstract<p>Autism spectrum disorder(ASD) is a neurological condition marked by impaired communication abilities, social detachment, and repetitive behaviors in individuals. Global health organization facing difficulties in establishing an effective ASD diagnostic system that facilitates precise analysis and early autism prediction. It is a scientific issue that necessitates resolution. This research presents an approach for the early prediction of children with ASD utilizing significant variables through machine learning (ML) methods. Three stages comprise the suggested technique. First, a 1250-case ASD dataset was identified and preprocessed. Five extremely effective traits with high Pearson c</p> ... Show More
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Publication Date
Wed Dec 01 2021
Journal Name
Civil And Environmental Engineering
Prediction of the Delay in the Portfolio Construction Using Naïve Bayesian Classification Algorithms
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Abstract<p>Projects suspensions are between the most insistent tasks confronted by the construction field accredited to the sector’s difficulty and its essential delay risk foundations’ interdependence. Machine learning provides a perfect group of techniques, which can attack those complex systems. The study aimed to recognize and progress a wellorganized predictive data tool to examine and learn from delay sources depend on preceding data of construction projects by using decision trees and naïve Bayesian classification algorithms. An intensive review of available data has been conducted to explore the real reasons and causes of construction project delays. The results show that the postpo</p> ... Show More
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Publication Date
Fri Oct 13 2023
Journal Name
Engineering, Technology &amp; Applied Science Research
The Experimental and Theoretical Effect of Fire on the Structural Behavior of Laced Reinforced Concrete Deep Beams
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A Laced Reinforced Concrete (LRC) structural element comprises continuously inclined shear reinforcement in the form of lacing that connects the longitudinal reinforcements on both faces of the structural element. This study conducted a theoretical investigation of LRC deep beams to predict their behavior after exposure to fire and high temperatures. Four simply supported reinforced concrete beams of 1500 mm, 200 mm, and 240 mm length, width, and depth, respectively, were considered. The specimens were identical in terms of compressive strength (  40 MPa) and steel reinforcement details. The same laced steel reinforcement ratio of 0.0035 was used. Three specimens were burned at variable durations and steady-state temperatures (one

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of The Mechanical Behavior Of Materials
Influence of water-absorbent polymer balls on the structural performance of reinforced concrete beam: An experimental investigation
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Abstract<p>This research investigated the influence of water-absorbent polymer balls (WAPB) on reinforced concrete beams’ structural behavior experimentally. Four self-compacted reinforced concrete beams of identical geometric layouts 150 mm × 200 mm × 1,500 mm, reinforcement details, and compressive strength <inline-formula> <alternatives> <inline-graphic xmlns:xlink="http://www.w3.org/1999/xlink" xlink:href="graphic/j_jmbm-2022-0024_eq_001.png"></inline-graphic> <math xmlns:m="http://www.w3.org/1998/Math/MathML"> <msubsup> <mrow> </mrow></msubsup></math></alternatives></inline-formula></p> ... Show More
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Publication Date
Thu Oct 08 2026
Journal Name
Journal Of Baghdad College Of Dentistry
Comparison of regional bond strength of post space of fiber-reinforced post luted with two types of cements at different testing times
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Back ground: This in vitro study was carried out to investigate the effect of post space regions (coronal, middle and apical), Time and the mode of polymerization (dual, self-cured) of the cements used on the bond strength between translucent fiber post and root dentin by using push-out test. Materials and Methods: Forty eight extracted mandibular first premolars (single root) were instrumented with ProTaper Universal system files (for hand use) and obturated with gutta percha for ProTaper and AH26® root canal sealer following the manufacturer instructions, after 24 hours post space was prepared using FRC postec® plus drills no.3 creating 8 mm depth post space. The prepared samples were randomly divided into two main groups (24 samples ea

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Publication Date
Thu Feb 01 2018
Journal Name
Journal Of Engineering
Mathematical Modeling of Compaction Curve Using Normal Distribution Functions
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Compaction curves are widely used in civil engineering especially for road constructions, embankments, etc. Obtaining the precise amount of Optimum Moisture Content (OMC) that gives the Maximum Dry Unit weight gdmax. is very important, where the desired soil strength can be achieved in addition to economic aspects.

In this paper, three peak functions were used to obtain the OMC and gdmax. through curve fitting for the values obtained from Standard Proctor Test. Another surface fitting was also used to model the Ohio’s compaction curves that represent the very large variation of compacted soil types.

The results showed very good correlation between the values obtained from some publ

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