J. Allen Haynes

The Effect of Environment on TBC Lifetime

While the water vapor content of the combustion gas in natural gas-fired land based turbines is ∼10%, it can be 20–85% with coal-derived (syngas or H2) fuels or innovative turbine concepts for more efficient carbon capture. Additional concepts envisage working fluids with high CO2 contents to facilitate carbon capture and sequestration. To investigate the effects of changes in the gas composition on thermal barrier coating (TBC) lifetime, furnace cycling tests (1 and 100h cycles) were performed in air with 10, 50 and 90 vol.% water vapor and CO2-10%H2O and compared to prior results in dry air or O2. Two types of TBC’s were investigated: (1) diffusion bond coatings (Pt diffusion or Pt-modified aluminide) with commercial electron-beam physical vapor-deposited yttria-stabilized zirconia (YSZ) top coatings on second-generation superalloy N5 and N515 substrates and (2) high velocity oxygen fuel (HVOF) sprayed MCrAlYHfSi bond coatings with air-plasma sprayed YSZ top coatings on superalloys X4, 1483 or 247 substrates. For both types of coatings exposed in 1h cycles, the addition of water vapor resulted in a decrease in coating lifetime, except for Pt diffusion coatings which were unaffected by the environment. In 100h cycles, environment was less critical, perhaps because coating failure was chemical (i.e. due to interdiffusion) rather than mechanical. In both 1h and 100h cycles, CO2 did not appear to have any negative effect on coating lifetime.Copyright

Hot-Tearing of Multicomponent Al-Cu Alloys Based on Casting Load Measurements in a Constrained Permanent Mold

Hot-tearing is a major casting defect that is often difficult to characterize, especially for multicomponent Al alloys used for cylinder head castings. The susceptibility of multicomponent Al-Cu alloys to hot-tearing during permanent mold casting were investigated using a constrained permanent mold in which the load and displacement were measured. The experimental results for hot tearing susceptibility are compared with those obtained from a hot-tearing criterion based on temperature range evaluated at fraction solids of 0.87 and 0.94. The Cu composition was varied from approximately 5–8 pct. (weight). Casting experiments were conducted without grain refining. The measured load during casting can be used to indicate the severity of hot tearing. However, when small hot-tears are present, the load variation cannot be used to detect and assess hot-tearing susceptibility.

Petascale supercomputing to accelerate the design of high-temperature alloys

Abstract Recent progress in high-performance computing and data informatics has opened up numerous opportunities to aid the design of advanced materials. Herein, we demonstrate a computational workflow that includes rapid population of high-fidelity materials datasets via petascale computing and subsequent analyses with modern data science techniques. We use a first-principles approach based on density functional theory to derive the segregation energies of 34 microalloying elements at the coherent and semi-coherent interfaces between the aluminium matrix and the θ′-Al2Cu precipitate, which requires several hundred supercell calculations. We also perform extensive correlation analyses to identify materials descriptors that affect the segregation behaviour of solutes at the interfaces. Finally, we show an example of leveraging machine learning techniques to predict segregation energies without performing computationally expensive physics-based simulations. The approach demonstrated in the present work can be applied to any high-temperature alloy system for which key materials data can be obtained using high-performance computing.