Numerical and Experimental Study of Residual Stresses Estimation and Mechanical Properties Determination Using Spherical Indentation and the Surface Geometrical Parameters

Numerical and Experimental Study of Residual Stresses Estimation and Mechanical Properties Determination Using Spherical Indentation and the Surface Geometrical Parameters


Numerical and Experimental Study of Residual Stresses Estimation and Mechanical Properties Determination Using Spherical Indentation and the Surface Geometrical Parameters

نوع: Type: thesis

مقطع: Segment: PHD

عنوان: Title: Numerical and Experimental Study of Residual Stresses Estimation and Mechanical Properties Determination Using Spherical Indentation and the Surface Geometrical Parameters

ارائه دهنده: Provider: Arash Karbasian

اساتید راهنما: Supervisors: AmirHossein Mahmoudi (Ph.D)

اساتید مشاور: Advisory Professors:

اساتید ممتحن یا داور: Examining professors or referees: (Ph.D) Rahman Seifi (Ph.D) , Saeed Feli (Ph.D), Kazem Kashizadeh

زمان و تاریخ ارائه: Time and date of presentation: Saturday - 2 September 2023 - 11 AM

مکان ارائه: Place of presentation: Seminar No.3 of mechanic department

چکیده: Abstract: The behavior of materials and structures under different loading conditions depends on their mechanical properties and residual stresses. Traditionally, the material's plastic anisotropy is extracted using several uniaxial tensile and compressive tests, which are destructive and also not applicable to small parts or in situ applications. The mechanical properties and residual stresses of materials and components of structures that have been subjected to various environmental conditions and loading for a long period of time, may change compared to their initial values; Therefore, Given the importance of extracting the mechanical properties of these parts and taking into account the non-destructiveness of the adopted method, in the past years. Extracting and estimating the mechanical properties of materials using the continuous indentation method is one of the non-destructive and relatively low-cost solutions. In this method, the mechanical properties and residual stresses are estimated using load-indentation depth curves obtained from indentation tests along with analytical or numerical methods. In the current work, macro-spherical indentation and an inverse analysis were employed to simultaneously estimate isotropic and anisotropic plastic properties and the equi-biaxial residual stresses in steel and aluminium parts. The P-h curves and pile-up were obtained from a wide range of FE analyses with different material properties and equi-biaxial residual stresses states. Then, an inverse analysis method using an artificial neural network (ANN) was employed to determine both anisotropy properties and residual stresses. In other words, Neural network has been used as a powerful tool for constructing relationships between inputs and targets. The effectiveness of the proposed method was verified by several experimental cases with plastic anisotropy behavior of 316L stainless steel and 2024 aluminum alloy. In another section of this research, non-equibiaxial and biaxial residual stresses, as well as anisotropic and isotropic properties, were estimated with a novel-designed neural network. The proposed method was validated with several different engineering material properties. The effect of surface roughness on the Brinell hardness value and P-h curve of the macro-spherical indentation was also studied numerically and experimentally and it was shown that surface roughness can affect on indentation results. By using pile-up in two anisotropic directions around the indentation area, a correction theory has been presented to calculate the real Brinell hardness of materials, and the results showed that the corrected Brinell hardness value is lower than the traditional one.

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