Tensile and Permeation Properties of Austenitic Stainless Steel Tubing with Internal Tritium
Explore the source record for details and available documents.
SEARCH · Search NASA
Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Explore the source record for details and available documents.
The deformation mechanisms of neutron-irradiated 304 L stainless steel have been investigated using the in-situ electron backscattered diffraction (EBSD) technique. To decipher the role of irradiation, a detailed analysis was performed on irradiated miniature samples and compared with nonirradiated samples. Furthermore, at three levels of engineering strain, —0.0%, 4.8%, and 14.5%—microstructural features as well as EBSD were recorded at the identical location during in-situ deformation testing. Post-mortem analysis of the EBSD data revealed that the neutron-irradiated samples had higher fractions of the slip bands even at low amounts of deformation. Along with the slip bands, the neutron-irradiated sample showed the twins and martensitic phase formed almost parallel to the slip bands. In addition, the image results also indicated that the formation of twins and phases associated with the slip bands. A detailed mechanistic understanding has been investigated to identify the (111)γ planes orientation with respect to the loading direction associated with the formation of twins and martensite. The newly formed deformation twins and martensite were also found to maintain this relationship when they existed together.
Chromium self-diffusion through stainless steel (SS) matrix and along grain boundaries is an important mechanism controlling SS structural materials corrosion. For this work, Cr diffusion in austenitic SS was simulated using canonical ab initio molecular dynamics with realistic models of type-316 SS bulk, with and without Cr vacancies, and a low-energy Σ3 twin boundary typically observed at active corrosion sites. Cr self-diffusion coefficients at 750 and 850 °C calculated using Einstein’s diffusion equation are 4.2 × 10 –6 and 8.1 × 10 –6 Å 2 ps –1 in pristine bulk, 3.8 × 10 –3 and 5.5 × 10 –3 Å 2 ps –1 in bulk including Cr vacancies, and 9.5 × 10 –2 and 1.0 × 10 –1 Å 2 ps –1 at a Σ3[1 1 1]60° twin boundary.
The chromium (Cr) evaporation behavior of several different types of iron (Fe)-based AFA alloys and benchmark Cr 2 O 3 -forming Fe-based 310 and Ni-based 625 alloys was investigated for 500 h exposures at 800 °C to 900 °C in air with 10% H 2 O. The Cr evaporation rates from alumina-forming austenitic (AFA) alloys were ~5 to 35 times lower than that of the Cr 2 O 3 -forming alloys depending on alloy and temperature. The Cr evaporation behavior was correlated with extensive characterization of the chemistry and microstructure of the oxide scales, which also revealed a degree of quartz tube Si contamination during the test. As a result, long-term oxidation kinetics were also assessed at 800 to 1000 °C for up to 10,000 h in air with 10% H 2 O to provide further guidance for SOFC BOP component alloy selection.
For solidification rates at or near equilibrium solidification conditions the effects of chrome (Cr) and nickel (Ni) on stainless steel solidification modes and microstructures are well detailed. However, fusion-based additive manufacturing (FBAM) processes that rely on faster, more rapid solidification rates call for a more in-depth understanding of the effects of rapid solidification on the solidification behavior and how these change with variations in alloy composition. Eleven custom stainless steel (SS) alloys with unique compositions based on 316L were made using targeted alloying element additions to generate feedstock with Cr/Ni eq ratios ranging from 0.9 to 2.1. Two-piston splat quenching (SQ) was used to produce rapid solidification conditions similar to those achieved in powder bed fusion processes in a fraction of the time and cost of traditional methods. Employing heat transfer simulations, SEM, TEM, and STEM characterization techniques, the SQ process was found to consistently produce solidification rates estimated to be between ~ 0.4 and 1.6 m/s. Five unique solidification microstructures were identified within the rapidly solidified SQ samples (primary austenite, massively transformed ferrite to austenite, primary austenite and massively transformed ferrite to austenite, primary ferrite, and primary ferrite and massively transformed ferrite to austenite). Both the primary ferrite solidification mode and primary ferrite phase were found to form at lower Cr/Ni eq values than previously predicted. SQ samples with compositions that were within the compositional specifications for 316L SS, an alloy which is commonly used in FBAM processes, demonstrated a wider range of potential solidification modes and microstructures that could form at rapid solidification rates than expected. Finally, by using SQ as a means to simulate rapid solidification conditions similar to those observed in FBAM processes, potential new alloy compositions can be screened faster and more cost effectively than purchasing and running test batches of the metallic powder.
Parabolic rate constants, k p , were collected from published reports and calculated from corrosion product data (sample mass gain or corrosion product thickness) and tabulated for 75 alloys exposed to temperatures between ~800 and 2000 K (~500–1700 °C; 900–3000°F). Data were collected for environments including lab air, ambient and supercritical carbon dioxide, supercritical water, and steam. Materials studied include low- and high-Cr ferritic and austenitic steels, nickel superalloys, and aluminide materials. A combination of Arrhenius analysis, simple linear regression, supervised and unsupervised machine learning methods were used to investigate the relations between composition and oxidation kinetics. The supervised machine learning techniques produced the lowest mean standard errors. The most significant elements controlling oxidation kinetics were Ni, Cr, Al, and Fe, with Mo and Co composition also found to be significant features. The activation energies produced from the machine learning analysis were in the correct distributions for the diffusion constants for the oxide scales expected to dominate in each class.
Not provided.
Not provided.
Not provided.
In this experiment, the origin of dislocation structures in AM stainless steels was systematically investigated by controlling the effect of thermal stress through geometric constraints for the first time. Stainless steel 316L parts were produced in the form of “1D” rods, “2D” walls, and "3D" rectangular prisms to evaluate the effect of constraints to thermal expansion/shrinkage on the development of defect microstructures and to elucidate the origin of additively manufactured (AM) dislocation microstructures. Dislocation density, organization, chemical micro-segregation, precipitate structures, and misorientations were analyzed as a function of increasing constraints around solidifying material in 1D, 2D, and 3D components built using both directed energy deposition (DED) and powder-bed selective laser melting (SLM). In DED parts, the dislocation density was not dependent on local misorientations or micro-segregation patterns, but evolved from approximately ρ ⊥ = 10 12 m -2 in 1D parts to ρ ⊥ = 10 14 m -2 in 3D parts, indicating that it is primarily thermal distortions that produce AM dislocation structures. In DED 3D parts and SLM parts, dislocation densities were highest (ρ ⊥ ≈ 10 14 m -2 ) and corresponded to the formation of dislocation cells approximately 300-450 nm in diameter. Dislocation cells overlapped with dendrite micro-segregation in some but not all cases. The results illustrate that dendritic micro-segregation, precipitates, or local misorientations influence how the dislocations organize during processing, but are not responsible for producing the organized cell structures. Furthermore, this work shows that AM dislocation structures originate due to thermal distortions during printing, which are primarily dictated by constraints surrounding the melt pool and thermal cycling.
Explore the source record for details and available documents.
Not Available
Not Available
Not Available
Not Available