This research presents fatigue life test results for several versions of 208-size (40-mm bore) Pyrowear 675 angular contact bearings. Results with different heat treatments of the Pyrowear 675 materials in a hybrid configuration (silicon nitride rolling elements) are compared to all-metal AISI M50, hybrid AISI M50, and hybrid AISI M50NiL configurations. Bearings were tested for rolling contact fatigue life at an applied thrust load of 22,250 N resulting in maximum Hertzian contact stress values of 3.10 (all metal) and 3.55 (hybrid) GPa. Rolling contact fatigue life testing was conducted at 128°C using a gas turbine engine lubricant conforming to MIL-PRF-23699G. All versions of hybrid Pyrowear 675 bearings showed significant improvement in fatigue life compared to baseline M50 and M50NiL bearing materials. After testing, selected bearings were analyzed for tribofilms using Auger electron spectroscopy. Auger electron spectroscopy showed phosphorus-rich tribofilm formation on the Pyrowear 675 bearing contact zones. The results suggest that the tricresyl phosphate antiwear additive used in current gas turbine lubricant formulations positively reacts with Pyrowear 675 surfaces and shows no detrimental effect on fatigue life at the test conditions studied here.
A centralized
optimization strategy is proposed to determine optimal raw material
purchasing and plant operation practices as applied to primary steelmaking
in the steel processing industry. Raw materials are purchased on the
open market and include coal, iron ore pellets, and scrap steel. There
are many raw material vendors, providing products varying in quality
and price. It is desired to determine the least costly method of both
purchasing and processing the raw materials to make steel of acceptable
quality. A model for primary steelmaking is developed using a combination
of mass balances and empirical relationships. The model, in addition
to process constraints, is combined with an economic objective function
and the resulting optimization problem solved using a mixed-integer
nonlinear programming (MINLP) solver. Case studies illustrate the
strong connection between plant sections, and the significant impact
that the carbon, volatile matter, and phosphorus content of the coals
and pellets have on raw material selection. Raw material uncertainty
is incorporated using two-stage stochastic programming. The results
indicate that by making a slightly more expensive raw material purchase,
the frequency of constraint violation during processing can be significantly
reduced.
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