About determining the coefficient η for J-integral for SEN(B) specimens

Graba, M.

doi:10.1063/5.0007813

Cited by 2 publications

(1 citation statement)

References 11 publications

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“…Many researchers apply multiple mathematical programs to identify specific connections between the parameters analyzed, thanks to scientific advancements in hardware and software technology. This is why, regardless of the domain to which it refers, e.g., industry, agriculture, medicine, the environment, and so on, mathematical modeling has progressed [1][2][3][4][5][6][7][8]. As a result, in addition to traditional equations, such as those used in physics to explain specific events, many scientific articles have recently appeared in the literature that present mathematical correlations connecting the parameters under study.…”

Section: Introductionmentioning

confidence: 99%

Extraction of Mathematical Correlations Applied in the Aerodynamic Separation of Solid Particles

et al. 2022

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This article describes the methodology used to identify the mathematical equation that describes the correlations between the input and output parameters of an experiment. As a technological process, aerodynamic separation was chosen to represent the behavior of a solid particle within an ascending vertical airflow. The experimental data were used to identify two parameters, namely the average linear velocity and the angular velocity. The Table Curve 3D program was used to develop a mathematical equation describing the dependence between the input parameters (the shape and size of the solid particle, as well as the velocity of the airflow) and the monitored parameters. A pyramid-type analysis (following a filtering system, a general equation was determined from a large number of equations that characterize an experimental set mathematically) was designed in order to determine a single mathematical equation that describes the correlation between the input variables and those obtained as accurately as possible. The determination of the mathematical equation started with the number of equations generated by the Table Curve 3D program; then, the equations with a correlation coefficient greater than 0.85 were chosen; and finally, the common equations were identified. Respecting the working methodology, one equation was identified, which has for the average linear velocity, a correlation coefficient r2 of between 0.88-0.99 and 0.86–0.99 for the angular velocity.

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Section: Introductionmentioning

confidence: 99%

Extraction of Mathematical Correlations Applied in the Aerodynamic Separation of Solid Particles

et al. 2022

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Characteristics of selected measures of stress triaxiality near the crack tip for 145Cr6 steel - 3D issues for stationary cracks

Graba

2020

Open Engineering

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AbstractIn the paper the numerical analysis of the stress fields for 145Cr6 steel, near crack tip is presented, based on three-dimensional finite element method (FEM) analysis. The FEM analysis is focused on SEN(B) specimens with relative crack length a/W ≈ 0.30. In addition to the presentation of the normal components of the stress tensor, the paper presents selected measures of stress triaxiality parameters, measured for the value of the J-integral, corresponding to the experimentally determined fracture toughness, denoted as JIC, which is considered to be a material constant or material characteristic [1, 2]. Presented topic is a continuation of papers [3, 4],whichwere based on experimental analysis, presented in [5].

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About determining the coefficient η for J-integral for SEN(B) specimens

Cited by 2 publications

References 11 publications

Extraction of Mathematical Correlations Applied in the Aerodynamic Separation of Solid Particles

Extraction of Mathematical Correlations Applied in the Aerodynamic Separation of Solid Particles

Characteristics of selected measures of stress triaxiality near the crack tip for 145Cr6 steel - 3D issues for stationary cracks

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