Statistical investigation on influence of grain size on effective strengths of particulate reinforced metal matrix composites

Chen, Geng; Zhang, Lele; Bezold, Alexander; Broeckmann, Christoph; Weichert, Dieter

doi:10.1016/j.cma.2019.04.044

Cited by 10 publications

(3 citation statements)

References 43 publications

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“…In our previous works [32,33], an integrated numerical approach for predicting the ultimate strength and endurance limit of PRMMC materials is proposed which incorporates homogenization, direct methods, and statistical analysis. In the present study, this method is extended to the case of high dimensional load space such that the strengths of PRMMCs subjected to superimposed tensile and shear stress can be evaluated.…”

Section: Introductionmentioning

confidence: 99%

Statistical Analyses of the Strengths of Particulate Reinforced Metal Matrix Composites (PRMMCs) Subjected to Multiple Tensile and Shear Stresses

Chen

Xin

Zhang

et al. 2021

Chin. J. Mech. Eng.

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For design and application of particulate reinforced metal matrix composites (PRMMCs), it is essential to predict the material strengths and understand how do they relate to constituents and microstructural features. To this end, a computational approach consists of the direct methods, homogenization, and statistical analyses is introduced in our previous studies. Since failure of PRMMC materials are often caused by time-varied combinations of tensile and shear stresses, the established approach is extended in the present work to take into account of these situations. In this paper, ultimate strengths and endurance limits of an exemplary PRMMC material, WC-Co, are predicted under three independently varied tensile and shear stresses. In order to cover the entire load space with least amount of weight factors, a new method for generating optimally distributed weight factors in an n dimensional space is formulated. Employing weight factors determined by this algorithm, direct method calculations were performed on many statistically equivalent representative volume elements (SERVE) samples. Through analyzing statistical characteristics associated with results the study suggests a simplified approach to estimate the material strength under superposed stresses without solving the difficult high dimensional shakedown problem.

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Section: Introductionmentioning

confidence: 99%

Statistical Analyses of the Strengths of Particulate Reinforced Metal Matrix Composites (PRMMCs) Subjected to Multiple Tensile and Shear Stresses

Chen

Xin

Zhang

et al. 2021

Chin. J. Mech. Eng.

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“…Composites of multiple phases were studied by homogenization theory [22,23], and non-periodic random composites, auto modeling techniques, and statistical measures [24][25][26] were involved. Different hardening models of material were analyzed [25][26][27][28][29][30][31][32], as were temperature loads [28,29] and multidimensional load domains [6,30]. In the macro scale, besides pressure vessels and piping, components of high-speed train were also studied [31,32].…”

Section: Introductionmentioning

confidence: 99%

Lower bound limit and shakedown analysis of orthotropic material

Fang

Zhang

Chen

et al. 2020

Mathematics and Mechanics of Solids

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We present in this study a new approach for predicting the plastic and shakedown limits of structures composed of orthotropic materials. In this approach, the Hill yield criterion is introduced to Melan’s theorem. By formulating the problem by means of the finite element method and solving the resulting large-scale nonlinear optimization problem we successfully predict the plastic and shakedown limits of structures having complex geometries made from multi-orthotropic materials. Several numerical examples are elaborated in this study for evaluating the accuracy, general applicability, as well as the efficiency of the established numerical scheme. Overall, the study confirms that the direct method can be extended and adopted as a viable means for design and analysis of structures made of orthotropic materials.

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“…In our previous works [1,2], in order to predict the ultimate strength and endurance limit of PRMMC materials, we proposed an integrated numerical approach which incorporates homogenization, direct methods, and statistical analysis. The main emphasis of this approach is to apply direct methods to many SERVE samples owning both real and synthetic microstructures, deriving statistics of interests, and then interpreting them by carefully selected statistical models so as to identify important structure-performance relationships.…”

Section: Introductionmentioning

confidence: 99%

Statistical Analyses of the Strengths of Particulate Reinforced Metal Matrix Composites (PRMMCs) Subjected to Multiple Tensile and Shear Stresses

Chen¹,

Shu²,

Zhang³

et al. 2020

Preprint

Self Cite

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Predicting the material strengths of particulate reinforced metal matrix composites (PRMMCs) and understanding how these properties are related to the constituents and microstructural features are essential for material designers and application engineers. To this end, a computational approach consists of the direct methods, homogenization, and statistical analyses is introduced in our previous studies [1,2]. Since in various engineering applications failure of PRMMC materials are caused by time-varied combinations of tensile and shear stresses, to take into account of such situations the established approach is extended in the present work. In this paper, ultimate strengths and endurance limits of an exemplary PRMMC material, WC-Co, are predicted under three independently varied tensile and shear stresses. In order to cover the entire load space with least amount of weight factors, a new method for generating optimally distributed weight factors in an n dimensional space is formulated. Employing weight factors determined by this algorithm, direct method calculations were performed on many statistically equivalent representative volume elements (SERVE) samples, and through analyzing statistical characteristics associated with results the study suggests a simplified approach to estimate the material strength under superposed stresses without solving the difficult high dimensional shakedown problem.

show abstract

Statistical investigation on influence of grain size on effective strengths of particulate reinforced metal matrix composites

Cited by 10 publications

References 43 publications

Statistical Analyses of the Strengths of Particulate Reinforced Metal Matrix Composites (PRMMCs) Subjected to Multiple Tensile and Shear Stresses

Statistical Analyses of the Strengths of Particulate Reinforced Metal Matrix Composites (PRMMCs) Subjected to Multiple Tensile and Shear Stresses

Lower bound limit and shakedown analysis of orthotropic material

Statistical Analyses of the Strengths of Particulate Reinforced Metal Matrix Composites (PRMMCs) Subjected to Multiple Tensile and Shear Stresses

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