Prediction of modulus of elasticity of UHPC using maximum likelihood estimation method

Alsalman, Ali; Kareem, Rahman S.; Dang, Canh N.; Martí‐Vargas, José R.; Hale, William

doi:10.1016/j.istruc.2021.11.002

Cited by 9 publications

(6 citation statements)

References 44 publications

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“…Growth in MOE was observed with rise in age of curing for all the mixes, it was due to improvement of particles bonding and development of C-S-H(gel). Ali Alsalman et al [48] reported that modulus of elastic plays a key role in design of structures elements and it also concluded that MOE is directly depending on ingredients of concrete and compressive strength. Medine Ispir et al [49] investigated and illustrated about the curve pattern of stress-strain of lean concrete.…”

Section: Modulus Of Elasticitymentioning

confidence: 99%

Prediction of mechanical properties of concrete blended with marble stone powder by artificial neural network

Ramesh Babu,

Thangamani,

Kishore

et al. 2024

MATEC Web Conf.

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The current research work is mainly concentrated on the mechanical properties concrete blended with marble stone power resulted from waste sludge marble processing it has a high specific area. M25 grade concrete mix design was considered for this research work. The mechanical properties of concrete i.e. compressive strength, unit weight, splitting tensile strength, modulus of elasticity and flexural strength were considered for the study. The compressive strength of these mixes was measured on 150mm ×150mm × 150mm cubes and tension test split tensile test 150 mm dia × 300 mm height cylinders. The concrete unit weight was considered for calculating the elastic modulus of concrete. The investigational values were matched with ACI, CEB-FIP, BIS and AASHTO LRFD empirical equation and regression analysis was done. The empirical equation result was compared with regression analysis of Artificial Neural Network, and conclusion was brough down that regression analysis of artificial neural network had better prediction than that of above-mentioned empirical equations. The study concluded that 15% replacement of marble power attained highest strength and optimum replacement, 25% replacement was concluded as economical replacement to attain designed strength.

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Section: Modulus Of Elasticitymentioning

confidence: 99%

Prediction of mechanical properties of concrete blended with marble stone powder by artificial neural network

Ramesh Babu,

Thangamani,

Kishore

et al. 2024

MATEC Web Conf.

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“…where D c and D t are the compression and tension damage parameter of concrete, respectively; σ c and σ t are the compressive stress and tensile stress of concrete; E c is the elastic modulus of concrete [25], 30,041 MPa; ϵ in NSC−c and ϵ in NSC−t are the inelastic strains corresponding to the compressive stress σ NSC−c and the tensile stress σ NSC−t of concrete, respectively; and b c is a constant with the range of 0 and 1.…”

Section: Concrete and Uhpcmentioning

confidence: 99%

“…Where D UC−c and D UC−t are the compression and tension damage parameters of UHPC, as shown in Figure 9; σ UC−c and σ UC−t are the compressive stress and tensile stress of UHPC, respectively; E UC is the elastic modulus of UHPC [25], 41617MPa; ϵ in UC−c and ϵ in UC−t are the inelastic strains corresponding to the compressive stress σ UC−c and tensile stress σ UC−t , respectively.…”

Section: Concrete and Uhpcmentioning

confidence: 99%

“…F slab = ε slab E S A slab (25) where F UHPC is the resulting force of the UHPC layer, E UHPC is the elastic modulus of UHPC, ε UHPC is the strain of UHPC, A UHPC is the area of the UHPC layer, F top−steel is the resulting force of the top steel reinforcements, ε top−steel is the strain of the top steel reinforcements, E S is the elastic modulus of the steel reinforcements, A top−steel is the area of the steel reinforcements in the UHPC, F mid−steel is the resulting force of the steel reinforcements in the concrete, ε mid−steel is the strain of the steel reinforcements in the concrete, A mid−steel is the area of the steel reinforcements in the concrete, F f lange is the resulting force of the flange of the steel ribs, ε f lange is the strain of the flange of the steel ribs, A f lange is the area of the flange of the steel ribs, F web−1 is the resulting force of the web of steel ribs above the neutral axis, ε web−1 is the maximum strain of the web of steel ribs above the neutral axis, A web−1 is the area of the web of steel ribs above the neutral axis, F web−2 is the resulting force of the web of steel ribs below the neutral axis, ε web−2 is the strain of the web of steel ribs below the neutral axis, A web−2 is the area of the web of steel ribs below the neutral axis, F concrete is the resulting force of the compressive concrete, ε concrete is the maximum strain of the compressive concrete, and A concrete is the area of the compressive concrete. The height of the neutral axis can be determined according to the force equilibrium (Equation ( 26)).…”

Section: Cracking Resistance and Bearing Capacitymentioning

confidence: 99%

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Flexural Performance of Steel–Normal Concrete–Ultra-High-Performance Concrete Composite Slabs with Steel Ribs

Guo,

Liu,

2024

Buildings

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For steel–concrete composite bridges, the cracking of concrete in the tensile zone influences the serviceability of bridges and decreases their durability. UHPC, as a high-tensile and -durability material, is used to replace a part of the concrete to enhance the tensile performance. Thus, the steel–normal concrete–UHPC composite slab, as a new composite structure, is formed. This paper investigates the flexural behaviours of steel–normal concrete–UHPC composite slabs through a full-scale experiment, numerical simulation, and theoretical analysis. The research results indicate that (1) UHPC enhances the flexural performance of the tensile zone and delays the development of cracks. The initial cracking force of concrete increases from 44 kN to 91 kN. (2) UHPC effectively enhances the carrying capacity of composite slabs. A 50 mm UHPC layer makes the flexural bearing capacity of steel–concrete composite slabs increase by 13.51%. (3) The construction methods influence the initial cracking force of composite slabs. For full-span scaffolding construction, the initial cracking force decreases from 91 kN to 69 kN compared with construction without brackets. (4) The theoretical model considering the tensile contribution of cracking UHPC can accurately predict the bearing capacity of the composite slabs. And the theoretical values of the bearing capacity are lower than the experimental values, which makes the composite slabs safer in service.

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“…The graph in Figure 11 shows the relationship between the compressive strength and modulus of elasticity of UHPC. The results of the calculation of the UHPC modulus of elasticity using the formulas from the works [59][60][61] are also presented (Table 6). The best convergence with the actual values is shown by Equation ( 9), which can be recommended for use for approximate determination of the UHPC modulus of elasticity.…”

Section: Modulus Of Elasticity and Poisson's Coefficientmentioning

confidence: 99%

The Effects of Corrugated Steel Fiber on the Properties of Ultra-High Performance Concrete of Different Strength Levels

Soloviev,

Matiushin

2023

Buildings

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This article describes the influence of corrugated steel fiber on the mechanical properties and fracture energy of Ultra-High Performance Concretes (UHPC) of various strength levels. Three UHPC formulations with compressive strengths of 143, 152, and 177 MPa were tested. The following parameters for the formulations without fiber and those containing 2% steel fiber by volume were determined: compressive strength, splitting tensile strength, flexural strength, modulus of elasticity, Poisson’s ratio and critical stress intensity factor. From the axial tensile test results, the following parameters were obtained: the cracking stress, tensile strength, and fracture energy of Ultra-High Performance Fiber Reinforced Concrete (UHPFRC) of different strength levels. With the introduction of steel fiber, an increase in all the investigated parameters is observed regardless of the strength of the concrete matrix. The most remarkable influence the fiber has on the splitting tensile strength, flexural strength and critical stress intensity coefficient, the increase is up to 1.6–3.2 times. There was a slight increase in compressive strength and elastic modulus—up to 5.0–7.4% depending on the composition. Poisson’s ratio was equal to 0.2 regardless of the strength of the concrete matrix and the presence of steel fiber. Based on the test results, equations were proposed to predict the properties of UHPC and UHPFRC depending on the water–cement ratio, silica fume content, cement compressive strength and the volumetric content of corrugated steel fiber. The calculated and experimental values showed good convergence with a correlation coefficient in the range of 0.885–0.997.

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Prediction of modulus of elasticity of UHPC using maximum likelihood estimation method

Cited by 9 publications

References 44 publications

Prediction of mechanical properties of concrete blended with marble stone powder by artificial neural network

Prediction of mechanical properties of concrete blended with marble stone powder by artificial neural network

Flexural Performance of Steel–Normal Concrete–Ultra-High-Performance Concrete Composite Slabs with Steel Ribs

The Effects of Corrugated Steel Fiber on the Properties of Ultra-High Performance Concrete of Different Strength Levels

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