Search NASA⌕ Search

Engineering topics

Brennan, Marissa

Publications and source records attributed to Brennan, Marissa.

Advanced Coating Compositions and Microstructures to Improve Uptime and Operational Flexibility in Cyclic, Low-Load Thermal Utility Plants

GE, the University of Tennessee, and Oak Ridge National Laboratory collaborated from 2020 to 2023 developing two key technologies for improving the viability of fuel switching and load following in thermal utility plants: a) cost-effective weld overlay compositions for boiler tubing b) cathodic arc coatings that deliver improvements in both erosion resistance and oxidation resistance in high temperature steam for HP turbine blades The team worked through a robust, logical project map to de-risk these two technologies and advance them from TRL 3 to TRL 6. For the cost-effective weld overlay, the team developed a ferritic filler material which was fabricated at a vendor for 18% the average market cost of Inconel 625 wire, had a corrosion rate 3x lower in conditions simulating a biomass-fired superheater and 10x lower in conditions simulating a coal-fired superheater, and was fabricated into prototype overlaid tubing that passed ASME requirements including transverse bending, dye penetrant inspection, and ASTM G-76 evaluation. For the cathodic arc coatings applied to steam turbine blades, the team developed a novel composition that was successfully transferred to a qualified vendor. The vendor was able to produce coated prototypes with 4x the as-deposited erosion resistance and 10.4x the post-steam-exposure erosion resistance of the TiN coating the vendor currently applies on GE steam turbine components, without significantly increasing process cost. These coated prototypes also passed a GE inspection and showed favorable performance in high temperature erosion, nanoindentation, sliding wear, scratch adhesion, and high cycle fatigue testing. If successfully deployed by GE, it is anticipated that the technologies will enable the following: • 25%-50% increase in time between outages for both boilers and HP turbines. • 50% decrease in cost for weld overlay on a per foot basis relative to todays NiCr alloys. • Adequate oxidation resistance and erosion for HP turbine inlet steam at >620°C and >220 bar. • No need for changes in component supply chain or any notable Capital Expenditures. 5 Decreasing component cost, increasing performance, and extending time between outages represent direct value propositions to GE and their customers. For the American consumer, these objectives translate into increased grid reliability (fewer unexpected outages), decreased Levelized Cost of Electricity, and improved environmental health (low-loading/load following to accelerate penetration of renewables). The results also have implications for wear resistant tooling, wire arc additive manufacturing, more durable components for syngas cleanup, and deployment of more efficient thermochemical pathways for carbon negative fuel production

09 BIOMASS FUELS↗

Robust Dissimilar Metal Friction Welded Spool for Enhanced Capability for Steam Power Components (Final Program Report)

This project successfully demonstrated the feasibility and advantages of producing durable, friction-welded dissimilar-metal spools, both with and without transition pieces, as well as the use of advanced oxidation-protective coatings for steam power applications. The work encompassed the optimization and full-scale production of NFA tubing, overcoming manufacturing and processing challenges to achieve enhanced strength, creep, and fatigue properties validated by extensive microstructural characterization. Optimized welding techniques were developed and refined for joining dissimilar materials, resulting in defect-free welds optimized for both low- and high-pressure boiler circuits. Systematic evaluation of welding parameters, coupled with heat treatments, ensured reliable performance and minimized weld defects such as banding and cracking. Comprehensive mechanical and non-destructive testing, including tensile, bend, fatigue, and CT scanning, confirmed the superior integrity and durability of the friction-welded joints under representative service conditions. To address oxidation-related degradation, a range of protective alloy coatings—such as IN625, APMT, Duplex 2507, and FeCrAlY—were selected and evaluated for their ability to counteract oxide notch formation at dissimilar metal interfaces. These coatings demonstrated improved oxidation resistance and long-term stability under thermal cycling, thereby extending weld service life. Thermal cyclic testing and long-term studies captured the phase stability and diffusion behavior of coated and uncoated configurations. Validated models for low-cycle fatigue (LCF), creep, and thermal mechanical fatigue (TMF) were developed to predict component life and failure modes. These models confirmed that friction-welded configurations exhibited significantly enhanced performance compared to conventional gas-tungsten arc welding (GTAW), with up to 7× improvement in creep resistance and at least 2× enhancement in fatigue properties. The introduction of a tailored transition piece further reduced thermally induced strains, enhancing fatigue life. The results demonstrate a robust pathway for retrofitting existing steam fleet components and upgrading future equipment to deliver substantially improved cold-start cycling behavior and reduction of unplanned outages due to premature weld failures.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Residual stress and microstructure in IN718-René41 graded superalloy fabricated by laser blown directed energy deposition

Additively printed Ni-based superalloy with a compositionally graded transition from IN718 to René41 was fabricated by laser blown-powder directed energy deposition (DED/LB-M), with the goals of meeting location-specific temperature capability and reducing component cost for hot gas path turbine components. Residual stress distribution in thin wall specimens with three sets of DED build parameters in the as-built and stress-relieved states was measured by neutron diffraction. For calculating residual stress, the calculated d0 method was found to be more appropriate as stress-free reference than using the lattice spacing measured from the stress-relief heat treated specimens. Longer dwell time (lower interpass temperature), higher energy input, smaller layer thickness resulted in a higher magnitude of tensile residual stresses at edges and compressive residual stresses at center of the specimens. The residual stress results did not show a strong dependence on graded compositions, indicating that the residual stress build-up was more geometry and process dependent. Non-destructive neutron imaging based on the attenuation coefficient qualitatively visualized the compositional variation in the bulk and showed good agreement with quantitative Electron Probe Micro-Analysis (EPMA) measurement. Grain structure, texture, and residual plastic strain along the build direction were characterized by Electron Backscatter Diffraction (EBSD). Long columnar grains with (001) preferred grain orientation were dominant along the build direction. Compositional change did not show an obvious effect on the epitaxial growth of dendrites and the continuation of the columnar grains. Residual plastic strain was relatively low in the as-built specimens.

36 MATERIALS SCIENCE↗

AI-Enabled Discovery and Physics-Based Optimization of Energy Efficient Processing Strategies for Advanced Turbine Alloys (Final Technical Report)

In this project, the multi-organizational team of academic and industrial researchers from the University of Kentucky an aerospace and energy generation OEM partner has leveraged novel Digital Process Twin (DPT) models of process/structure interactions (i.e., process-induced surface integrity) to advance a paradigm of fully integrated computational materials engineering (ICME). Using efficient process models as the core of a digital process simulator for a reinforcement learning algorithm, the team has integrated industrial data and metrics of structure/performance/energy relationships and manufacturing-related energy metrics to optimize dynamic processing parameters for significantly improved life-cycle energy efficiency of advanced γ-TiAl low-pressure turbine (LPT) alloys, as indicated by a set of design relevant parameters (e.g., residual stresses and scrap rate). The key objective and anticipated outcome of the project was at least a 10% reduction in life-cycle embodied energy for a recently developed, γ-TiAl low-pressure turbine (LPT) alloy and nickel-based superalloy Inconel 718, through the adoption of the proposed AI-enabled process optimization approach. The final project outcomes significantly exceeded this original target, realizing manufacturing-related energy efficiency improvements of more than 130% for TiAl and up to 80% for Inconel 718. Rather than following the prevailing and highly inefficient empirical paradigm, the proposed study demonstrated the feasibility of adopting a digital, physics-based process design and optimization paradigm. The recurring need for manual intervention, rework, reinspection causes significant production bottlenecks and unnecessary expense associated with delivering the requisite component quality. The OEM partner, and turbine industry in general, expect to reap significant cost and resource savings if an AI-optimized set of parameters can be applied to specific machining operations. The technical scope of the proposed project involved the paving of a realistic path towards model-based and AI-enabled Integrated Computational Materials Engineering (ICME), and away from inefficient empirical process optimization and legacy manufacturing practices, which are no longer able to efficiently process novel high-performance turbine alloy materials. The project team will address the fundamental knowledge gap that currently exists within the ICME paradigm with respect to the process/structure/performance/energy impacts of finishing processes. While significant resources have been devoted to the ‘early stages’ of manufacturing, such as alloy design, primary and secondary processing, finishing processes have not been adequately integrated within ICME. To provide an actionable path towards model-based finishing process design (e.g., machining, burnishing, grinding, polishing), we will employ a novel AI-enabled process optimization paradigm, based on a computationally efficient, physics-based process simulator. Through limited experimental work to calibrate and validate our process simulator model via an advanced in-situ characterization technique and process optimization via reinforcement learning, the project will seek to demonstrate a viable alternative to the inefficient ‘legacy’ processing strategies, empirical testing and broad scope machining learning approaches, all of which fail to adequately consider complex process physics. The project team has identified an intermetallic γ-TiAl LPT alloy, which is currently being used as part of the OEM partner’s advanced gas turbine designs. This particular alloy poses significant manufacturing challenges during finishing operations, which limit the degree to which the current turbine design can be manufactured in an energy- and cost-efficient manner. Empirical testing and numerical modeling efforts to optimize processing parameters for γ-TiAl have not been able to resolve these manufacturing challenges, so the proposed physics-based AI-enabled optimization technology would offer a truly novel and transformative capability. The multi-organizational team of academic and industry experts from the UKY and the OEM partner will work together closely to demonstrate the analytical and experimental critical function and characteristic proof of concept of this novel approach.

20 FOSSIL-FUELED POWER PLANTS↗