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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.
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Effect of Power Plant Capacity on the CAPEX, OPEX, and LCOC of the CO2 Capture Process in Pre-Combustion Applications
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Zero- and negative-emissions fossil-fired power plants using CO2 capture by conventional aqueous amines
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Modeling the operational flexibility of natural gas combined cycle power plants coupled with flexible carbon capture and storage via solvent storage and flexible regeneration
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Ab initio study of tungsten-based alloys under fusion power-plant conditions
Tungsten (W) is considered a leading candidate for structural and functional materials in future fusion energy devices. The most attractive properties of tungsten for magnetic and inertial fusion energy reactors are its high melting point, high thermal conductivity, low sputtering yield, and low long-term disposal radioactive footprint. However, tungsten also presents a very low fracture toughness, primarily associated with intergranular failure and bulk plasticity, limiting its applications. In recent years, several families of tungsten-based alloys have been explored to overcome the aforementioned limitations of pure tungsten. These include tungsten-based high-entropy alloys (W-HEAs) and tungsten-based Self-passivating Metal Alloys with Reduced Thermo-oxidation or “SMART alloys” (W-SAs). Given their proximity to the plasma, it is crucial to understand how the exposure of these candidate plasma-facing materials (PFMs) to the neutron fluxes expected in fusion reactors impacts their material behavior over time. In this work, we present a computational approach that combines inventory codes and first-principles DFT electronic structure calculations to understand the behavior of transmuting tungsten-based PFMs. In particular, we calculate the changes in the chemical composition, production uncertainties, the elastic and ductility properties, and the density of states for five tungsten-based PFMs when exposed to EU-DEMO fusion first wall conditions for ten years.
Explainable machine-learning tools for predictive maintenance of circulating water systems in nuclear power plants
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Dynamic bayesian networks based abnormal event classifier for nuclear power plants in case of cyber security threats
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Modeling interconnections of safety and financial performance of nuclear power plants part 1: Categorical review and theoretical bases
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Preliminary Life Cycle Assessment of a Net-zero Power Plant Co-fired with Waste Coal and Biomass
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Evaluating the reliability of machine-learning-based predictions used in nuclear power plant instrumentation and control systems
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Techno-economic assessment and environmental impact of concentrating solar power plants in Iran
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Pilot-scale study on flue gas moisture recovery in a coal-fired power plant
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Spatial impacts of technological innovations on the levelized cost of energy for offshore wind power plants in the United States
Recent studies predict significant decreases in the future levelized cost of energy (LCOE) of offshore wind energy, much of which is attributed to anticipated cost reductions from technological innovation. This study evaluates the spatial variability of LCOE caused by technology-induced decreases in a range of capital, operational, and financial cost categories. A spatial cost model of fixed-bottom and floating offshore wind plants is used to model the impact across thousands of potential United States sites. A specified change in an individual turbine subsystem cost produces a range of LCOE outcomes due to the varying geospatial characteristics of the considered sites and the nonlinear, interactive dependency on these input parameters; for example, a 10.8% improvement in net capacity factor can reduce LCOE by between 6% and 20% at different sites. This work expands upon the existing offshore wind literature, which typically evaluates cost sensitivities at a single site and does not consider the spatial variance in LCOE. The results suggest that the impact of technological innovations can be considerable and should be considered on a spatial as well as temporal basis when prioritizing technology innovation research or funding decisions to advance offshore wind technologies in the United States.