High temperature mechanical strength and microstructural stability of advanced 9-12%Cr steels and ODS steels.
The present study proposes a comparison between several martensitic and ferritic steels in terms of creep strength and cyclic softening effect. The damage mechanisms are identified using fractographic observations and the microstructural evolutions are observed by TEM. The effects of a modified chemical composition on the high temperature mechanical behaviour are studied.
Creep-fatigue-oxidation interactions in a 9Cr-1Mo martensitic steel. Part III: Lifetime prediction
A model devoted to the prediction of the high temperature creep–fatigue lifetime of modified 9Cr–1Mo martensitic steels is proposed. This model is built on the basis of the physical mechanisms responsible for damage due to the interaction of creep, fatigue and oxidation. These mechanisms were identified thanks to detailed observations previously reported in part I and part II of this study. These observations led to the distinction of two main domains, corresponding to two distinct types of interaction between creep, fatigue and oxidation. As no intergranular creep damage can be observed in the tested loading range, the proposed modelling consists in the prediction of the number of cycles necessary for the initiation and the propagation of transgranular fatigue cracks. Propagation rate measurements under high stress low-cycle fatigue conditions were carried out to calibrate the Tomkins model used to predict the life spent in crack propagation, whereas the initiation stage is predicted using the model proposed by Tanaka and Mura. The predictions obtained compare very favorably with the experimental creep–fatigue lifetimes. Finally the extrapolations and limits of the model are discussed.
Linear Programming in the Allocation of Milk Resources for Cheese Making
Abstract To use linear programming, the cheese making process can be modeled as a resource conversion process. The relationship between input milk resources and output products can be analyzed using mass balance assumptions. The variables used in the linear programming model will represent the pounds of each milk resource chosen to formulate a vat of cheese milk. Additional variables will be used to represent the pounds of cream to be removed from a milk resource that has the potential to have cream removed. Three objectives that could be considered are 1) maximize net returns, 2) maximize cheese yield, or 3) minimize cost. A hypothetical example is used to illustrate how the cheese making process can be modeled. This linear programming model depends on formulas that relate ratio of casein to fat of milk to the fat on the dry basis of the cheese. Sensitivity analysis is performed to determine at what cost a milk resource not in the optimal formulation will replace a milk resource currently in the optimal formulation. The linear programming model can be an effective management tool in the allocation of milk resources for cheese making.