Ferritic ductile iron (DI) GJS 400 and high-silicon strengthened ductile irons (HSSDIs) with 3.5 and 4.5 wt% of silicon contents were produced with different cooling rates, and the microstructures were analyzed to find the main microstructure parameters. The Y-blocks GJS 400 presented good nodularity, while the heavy section GJS 400 presented some graphite degeneracy with a lower nodularity. The 3.5 wt% HSSDI shown a good nodularity, while with increasing silicon content to 4.5 wt%, significant graphite degeneracy occurred with the appearance of chunky graphite. Samples were tensile tested and the tensile data were analyzed through the physical-based constitutive Voce equation, and the Voce parameters were plotted to produce a matrix assessment diagram (MAD). Y-blocks and heavy section GJS 400 data lied on two distinct lines in MAD, and they had, however, positive and negative intercepts which meant indeed two contradictory plastic behaviors. The intercept of the best fitting line of the GJS 400 Y-blocks data was positive and so consistent with the physical meaning of Voce equation, while the intercept of the best fitting line of the GJS 400 heavy section data was negative, which meant an unexpected opposite plastic behavior. Same behavior was reported for the investigated HSSDIs, resulting in positive intercept of the best fitting line in MAD for the 3.5 wt% HSSDI data and negative intercept for the 4.5 wt% HSSDI data. The uniform strain energy density (SED U ) that is the area below the tensile flow curve up to the uniform strain, i.e., the strain where necking begins, was also investigated. SED U resulted to be almost constant for all the GJS 400 Y-blocks tensile flow curves and 3.5 wt% HSSDI, which was typical of a sound material, while in GJS 400 heavy section and 4.5 wt% HSSDI, SED U changed significantly in a systematic way, indicating that metallurgical defects had affected the plastic behavior. So it was concluded that in the MAD the best fitting line of the tensile data with positive intercept was a possible indication of the material soundness, while the negative intercept was indication of defected material. The results suggested that the MAD analysis produced from tensile Voce parameters can be a useful and easy tool for industry not only to classify the production routes of DIs (Si content mainly and heat treatments), but also to identify possible microstructure poorness within a single DI grade.
A novel approach to the modelling and simulation of the industrial compaction process of ceramic powders is proposed, based on a combination of: (i) continuum mechanics modelling of the constitutive response of the material; (ii) finite element discretization and computer implementation of the mechanical model; (iii) parametric identification by a multi-objective optimization of simulated experimental tests. The capabilities of the proposed approach are highlighted through computer simulations of realistic industrial compaction processes, namely, the forming of an axisymmetric tablet and of a three-dimensional ceramic tile.The presented methods and the pointed out results pave the way for the introduction of so-called virtual prototyping into the industrial practice of ceramic forming processes.
The formulation of a probability‐stress‐life (P‐S‐N) curve is a necessary step beyond the basic S‐N relation when dealing with reliability. This paper presents a model, relevant to materials that exhibits a fatigue limit, which considers the number of cycles to failure and the occurrence of the failure itself as statistically independent events, described with different distributions and/or different degree of scatter. Combining these two as a parallel system leads to the proposed model. In the case where the S‐N relation is a Basquin's law, the formulations of the probability density function, cumulative distribution function, quantiles, parameter and quantile confidence interval are presented in a procedure that allows practically any testing strategy.
The result is a flexible model combined with the tools that deliver a wide range of information needed in the design phase. Finally, an extension to include static strength and applicability to fatigue crack growth and defects‐based fatigue approach are presented.
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