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AI-Driven Shear Capacity Model of Steel Studs in Composite Structural Systems
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In composite steel-concrete structures, shear connectors in the form of headed steel studs are commonly utilized to transfer longitudinal shear force developed at the interface between the two materials. To overcome the shortcomings of design codes, which frequently understate shear capacity and fail to take advantage of sophisticated computational methods, this paper presents an optimization attempt to estimate the shear strength of headed steel studs utilizing the Grey Wolf Optimizer (GWO) technique using MATLAB software. Data from 234 experimental tests are employed to identify and highlight key input parameters influencing the shear strength of headed steel studs. These key parameters include concrete compressive strength (f’c), diameter (D), and tensile strength of the steel stud shank (fu). After identifying and examining the limits of the experimental data, the proposed model has been developed using about 80% of the mixed raw dataset. The remaining 20% of the raw data is utilized to validate the proposed model. The predicted shear strength of headed steel studs closely matched the experimental results. This research offers an innovative strategy to measure the steel stud's shear capacity employing GWO, showing the current code's limitations. The GWO model showed excellent accuracy in predicting the shear strength with an R-value of 0.9922, indicating that the predicted value is in good agreement with experimental observations. Interestingly, the model's mean absolute error with 100 wolves in the GWO method was only 7.51%, showing the proposed model provides an improvement in shear capacity forecasting for practical structural engineering applications.

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Publication Date
Mon Aug 01 2016
Journal Name
Journal Of Engineering
Non-Linear Behavior of Strengthened Steel-Concrete Composite Beams with Partial Interaction of Shear Connectors
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In this research a theoretical study has been carried out on the behavior and strength of simply supported composite beams strengthened by steel cover plate taking into consideration partial interaction of shear connectors and nonlinear behavior of the materials and shear connectors. Following the procedure that already has been adopted by Johnson (1975), the basic differential equations of equilibrium and compatibility were reduced to single differential equation in terms of interface slip between concrete slab and steel beam. Furthermore, in order to consider the nonlinear behavior of steel, concrete and shear connectors, the basic equation was rearranged so that all terms related to materials are isol

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Publication Date
Sat Oct 01 2022
Journal Name
Structures
Behaviour and design of the ‘lockbolt’ demountable shear connector for sustainable steel-concrete composite structures
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In order to promote sustainable steel-concrete composite structures, special shear connectors that can facilitate deconstruction are needed. A lockbolt demountable shear connector (LB-DSC), including a grout-filled steel tube embedded in the concrete slab and fastened to a geometrically compatible partial-thread bolt, which is bolted on the steel section's top flange of a composite beam, was proposed. The main drawback of previous similar demountable bolts is the sudden slip of the bolt inside its hole. This bolt has a locked conical seat lug that is secured inside a predrilled compatible counter-sunk hole in the steel section's flange to provide a non-slip bolt-flange connection. Deconstruction is achieved by demounting the tube from the t

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Publication Date
Fri Nov 01 2019
Journal Name
Civil Engineering Journal
Experimental and Numerical Investigations of Composite Concrete–Steel Plate Shear Walls Subjected to Axial Load
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This research is presented experimental and numerical investigations of composite concrete-steel plate shear walls under axial loads to predicate the effect of both concrete compressive strength and aspect ratio of the wall on the axial capacity, lateral displacement and axial shortening of the walls. The experimental program includes casting and testing two groups of walls with various aspect ratios. The first group with aspect ratio H/L=1.667 and the second group with aspect ratio H/L=2. Each group consists of three composite concrete -steel plate wall with three targets of cube compressive strength of values 39, 54.75 and 63.3 MPa. The tests result obtained that the increase in concrete compressive strength results in increasing

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Publication Date
Fri Sep 01 2017
Journal Name
Journal Of Bridge Engineering
Novel Demountable Shear Connector for Accelerated Disassembly, Repair, or Replacement of Precast Steel-Concrete Composite Bridges
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A novel demountable shear connector for precast steel-concrete composite bridges is presented. The connector uses high-strength steel bolts, which are fastened to the top flange of the steel beam with the aid of a special locking nut configuration that prevents bolts from slipping within their holes. Moreover, the connector promotes accelerated construction and overcomes the typical construction tolerance issues of precast structures. Most importantly, the connector allows bridge disassembly. Therefore, it can address different bridge deterioration scenarios with minimum disturbance to traffic flow including the following: (1) precast deck panels can be rapidly uplifted and replaced; (2) connectors can be rapidly removed and replaced; and (

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Publication Date
Sat Jul 22 2023
Journal Name
Journal Of Engineering
Prediction of Smear Effect on the Bearing Capacity of Driven Piles
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This paper deals with prediction the effect of soil remoulding (smear) on the ultimate bearing capacity of driven piles. The proposed method based on detecting the decrease in ultimate bearing capacity of the pile shaft (excluding the share of pile tip) after sliding downward. This was done via conducting an experimental study on three installed R.C piles in a sandy clayey silt soil. The piles were installed so that a gap space is left between its tip and the base of borehole. The piles were tested for ultimate bearing capacity
according to ASTM D1143 in three stages. Between each two stages the pile was jacked inside the borehole until a sliding of about 200mm is achieved to simulate the soil remoulding due to actual pile driving. T

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Publication Date
Mon Oct 01 2012
Journal Name
Journal Of Engineering
Prediction of Smear Effect on the Bearing Capacity of Driven Piles
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This paper deals with prediction the effect of soil re-moulding (smear) on the ultimate bearing capacity of driven piles. The proposed method based on detecting the decrease in ultimate bearing capacity of the pile shaft (excluding the share of pile tip) after sliding downward. This was done via conducting an experimental study on three installed R.C piles in a sandy clayey silt soil. The piles were installed so that a gap space is left between its tip and the base of borehole. The piles were tested for ultimate bearing capacity according to ASTM D1143 in three stages. Between each two stages the pile was jacked inside the borehole until a sliding of about 200mm is achieved to simulate the soil re-moulding due to actual pile driving. The re

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Publication Date
Sat Oct 06 2012
Journal Name
Journal Of Engineering
Prediction of Smear Effect on the Bearing Capacity of Driven Piles
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Publication Date
Thu Apr 04 2024
Journal Name
Journal Of Electrical Systems
AI-Driven Prediction of Average Per Capita GDP: Exploring Linear and Nonlinear Statistical Techniques
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Average per capita GDP income is an important economic indicator. Economists use this term to determine the amount of progress or decline in the country's economy. It is also used to determine the order of countries and compare them with each other. Average per capita GDP income was first studied using the Time Series (Box Jenkins method), and the second is linear and non-linear regression; these methods are the most important and most commonly used statistical methods for forecasting because they are flexible and accurate in practice. The comparison is made to determine the best method between the two methods mentioned above using specific statistical criteria. The research found that the best approach is to build a model for predi

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Publication Date
Sat Sep 01 2018
Journal Name
2018 11th International Conference On Developments In Esystems Engineering (dese)
Sustainability Analysis and Shear Capacity of BubbleDeck Slabs with Openings
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Publication Date
Fri Feb 21 2025
Journal Name
2025 First International Conference On Advances In Computer Science, Electrical, Electronics, And Communication Technologies (ce2ct)
Enhancing Cloud Security Implementing AI-Based Intrusion Detection Systems
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The increasing complexity of assaults necessitates the use of innovative intrusion detection systems (IDS) to safeguard critical assets and data. There is a higher risk of cyberattacks like data breaches and unauthorised access since cloud services have been used more frequently. The project's goal is to find out how Artificial Intelligence (AI) could enhance the IDS's ability to identify and classify network traffic and identify anomalous activities. Online dangers could be identified with IDS. An intrusion detection system, or IDS, is required to keep networks secure. We must create efficient IDS for the cloud platform as well, since it is constantly growing and permeating more aspects of our daily life. However, using standard intrusion

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