Evaluation and monitoring of impact resistance of fiber reinforced concrete by adaptive neuro fuzzy algorithm

Cao, Yan; Zandi, Yousef; Rahimi, Abouzar; Petković, Dalibor; Denić, Nebojša; Stojanović, Jelena; Spasić, Boban; Vujović, Vuk; Khadimallah, Mohamed Amine; Assilzadeh, Hamid

doi:10.1016/j.istruc.2021.09.072

Cited by 22 publications

(10 citation statements)

References 73 publications

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“…The positive effect of fibers on the impact resistance is due to their action as tiny reinforcing elements that help delay the widening of tensile cracks. Fibers bridge the two sides of the initiated cracks arresting its propagation and opening by withstanding the tensile stresses induced across the cracks under the repeated impact loads [ 40 , 41 ]. Therefore, the failure is postponed compared to plain specimens.…”

Section: Resultsmentioning

confidence: 99%

Experimental and Analytical Modeling of Flexural Impact Strength of Preplaced Aggregate Fibrous Concrete Beams

2022

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Preplaced aggregate fibrous concrete (PAFC) is a revolutionary kind of concrete composite that is gaining popularity and attracting the interest of academics from across the world. PAFC is a uniquely designed concrete prepared by stacking and packing premixed fibers and coarse aggregate in a steel mold. The gaps between the fibers and aggregates are subsequently filled by injecting a cement grout with high flowability. This study investigates the impact performance of three different sizes of PAFC beams. Steel and polypropylene fibers were used in a 3% dosage to make three different beam sizes, measuring 550 × 150 × 150 mm, 400 × 100 × 100 mm, and 250 × 50 × 50 mm. According to ACI Committee 544, all beams were subjected to a drop weight flexural impact test. Compressive strength, impact energies at initial crack and failure, ductility index, and failure mode were evaluated. Additionally, analytical modeling was used to compute the failure impact energy for the fibrous beams. The results showed that the addition of fibers increased the capacity of the tested beams to absorb greater flexural impact energy. Compared to polypropylene fibers, steel fibers had better crack propagation and opening resistance because of their higher tensile strength and crimped and hooked end configuration. For all large-size beams, the analysis of the percentage increase in impact energy at the failure stages was found to be 5.3 to 14.6 times higher than the impact energy at cracking.

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Section: Resultsmentioning

confidence: 99%

Experimental and Analytical Modeling of Flexural Impact Strength of Preplaced Aggregate Fibrous Concrete Beams

2022

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“…Training RMSE shows the influence of the inputs on stocks' selling or buying decisions. Smaller training error more influence on the decision (Nikolić, Mitić, Kocić, & Petković, 2017;Petković, Petković, Kuzman, Milovančević, Wakil, Ho, & Jermsittiparsert, 2020;Cao, Zandi, Rahimi, Petković, Denić, Stojanović, & Assilzadeh, 2021;Stojanović, Petkovic, Alarifi, Cao, Denic, Ilic, & Milickovic, 2021;Kuzman, Petković, Denić, Petković, Ćirković, Stojanović, & Milić, 2021;Petković, Barjaktarovic, Milošević Spasić, Stojanović, & Milovancevic, 2021). Checking RMSE is used for overfitting tracking between training and checking data.…”

Section: Resultsmentioning

confidence: 99%

Evaluation of optimal economic and technical indicators for agriculture stock trading decision

Kuzman¹,

Petković²,

Petković³

2021

Int J Econ Practice & Policy

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The main goal of the research was to determine which indicators are the most impactful on the buy and sell triggers of stocks to maximize profits of the trade. The aim was to determine the agriculture stock price movements based on economic and technical indicators. The investors in the stock market want to maximize trade profits by buying or selling the stocks. Technical and economic analyses are conducted to determine whether to sell or buy agriculture stocks. Since many factors could impact stocks profit decisions, it is essential to determine which parameter has more or less influence on the decision. For such a purpose adaptive neuro-fuzzy inference system (ANFIS) was used since the method is suitable for redundant and nonlinear data. Generally, technical indicators are more valuable and impactful for agricultural stock trading decision-making. Technical indicator moving average convergence and divergence (MACD) strongly influences the stock trading decision. Economic indicator relative change after smoothing 15 days federal rate has the most decisive influence on the stock trading decision.

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“…based on element, material, and structure [7][8][9][10][11][12][13][14][15]. The second heading includes the studies in which assessments such as fire, seismic, condition, damage, performance, and capacity were made [16][17][18][19][20]. Finally, the third heading includes the studies on monitoring [21], crack diagnosis [22], classification of damages [23], parameter ranking [24], crack identification [25], response control [26], structural control [27], selection of construction systems [28], optimization [29] and etc.…”

Section: Introductionmentioning

confidence: 99%

1D Fuzzy inverse logic method and its use in the design of thick reinforced concrete columns

ÖZTEKİN

2024

Sigma J Eng Nat Sci - Sigma Müh Fen Bil Derg

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In this study, without using any uniaxial force and bending moment (N-M) interaction diagrams, designs were carried out on thick columns subjected to uniaxial bending and compression by a novel 1 dimensional (1D) Fuzzy Inverse Logic (FIL) method. For this purpose, firstly, a Fuzzy Logic (FL) model was developed and the FIL method was applied to it thereafter. While, the cross-section width (b), the cross-section height (h), the rebar diameter(), the numbers of reinforcement rows (Rx and Ry) placed into the cross-section in X and Y directions, the characteristic concrete compressive strength(fck) and the axial force ratio Nr=N/(b.h.(fck/1.5)) were taken as variable parameters, concrete cover thickness (c), rebar strength (fyd) and k1 parameter defined for the concrete pressure block were kept constant in the developed FL model. After designs were performed on 15 columns having different variable variations by the 1D FIL method, moment bearing capacities of the obtained 9737 alternative designs determined conventionally were compared with the desired moment values. The evaluations made on the comparisons show that the FIL method is not only a very effective artificial intelligence method for the design of reinforced concrete thick columns but also a promising method for many other problems such as control, optimization, design, etc.

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Evaluation and monitoring of impact resistance of fiber reinforced concrete by adaptive neuro fuzzy algorithm

Cited by 22 publications

References 73 publications

Experimental and Analytical Modeling of Flexural Impact Strength of Preplaced Aggregate Fibrous Concrete Beams

Experimental and Analytical Modeling of Flexural Impact Strength of Preplaced Aggregate Fibrous Concrete Beams

Evaluation of optimal economic and technical indicators for agriculture stock trading decision

1D Fuzzy inverse logic method and its use in the design of thick reinforced concrete columns

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