This paper presents a numerical study of Supercritical Carbon Dioxide (sCO 2) flow in see-through labyrinth seals. The Computational Fluid Dynamic (CFD) simulation of this scenario is performed under the framework of OpenFOAM. Properties of sCO 2 are implemented into OpenFOAM with a user-defined interface. A test facility was constructed to measure the leakage rate and pressure drop of sCO 2 in see-through labyrinth seals. Various designs and conditions have been tested to study the flow characteristic and provide validation data for numerical model. The primary goal is to verify the model's capability to predict leakage rate, with a secondary goal focused on using the code to optimize the seal design for sCO 2. This research concludes with some guidelines for the see-through labyrinth seal optimization.

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Supercritical CO2 (sCO2) power cycles find potential application with a variety of heat sources including nuclear, concentrated solar (CSP), coal, natural gas, and waste heat sources, and consequently cover a wide range of scales. Most studies to date have focused on the performance of sCO2 power cycles, while economic analyses have been less prevalent, due in large part to the relative scarcity of reliable cost estimates for sCO2 power cycle components. Further, the accuracy of existing sCO2 techno-economic analyses suffer from a small sample set of vendor-based component costs for any given study. Improved accuracy of sCO2 component cost estimation is desired to enable a shift in focus from plant efficiency to economics as a driver for commercialization of sCO2 technology. This study reports on sCO2 component cost scaling relationships that have been developed collaboratively from an aggregate set of vendor quotes, cost estimates, and published literature. As one of the world’s largest supporters of sCO2 research and development, the Department of Energy (DOE) National Laboratories have access to a considerable pool of vendor component costs that span multiple applications specific to each National Laboratory’s mission, including fossil-fueled sCO2 applications at the National Energy Technology Laboratory (NETL), CSP at the National Renewable Energy Laboratory (NREL), and CSP, nuclear, and distributed energy sources at Sandia National Laboratories (SNL). The resulting cost correlations are relevant to sCO2 components in all these applications, and for scales ranging from 5–750 MWe. This work builds upon prior work at SNL, in which sCO2 component cost models were developed for CSP applications ranging from 1–100 MWe in size. Similar to the earlier SNL efforts, vendor confidentiality has been maintained throughout this collaboration and in the published results. Cost models for each component were correlated from 4–24 individual quotes from multiple vendors, although the individual cost data points are proprietary and not shown. Cost models are reported for radial and axial turbines, integrally-geared and barrel-style centrifugal compressors, high temperature and low temperature recuperators, dry sCO2 coolers, and primary heat exchangers for coal and natural gas fuel sources. These models are applicable to sCO2-specific components used in a variety of sCO2 cycle configurations, and include incremental cost factors for advanced, high temperature materials for relevant components. Non-sCO2-specific costs for motors, gearboxes, and generators have been included to allow cycle designers to explore the cost implications of various turbomachinery configurations. Finally, the uncertainty associated with these component cost models is quantified by using AACE International-style class ratings for vendor estimates, combined with component cost correlation statistics.

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A simplified qualitative analysis was performed to investigate the possibility of using counter flow induced draft cooling tower option to reject heat from the supercritical carbon dioxide Brayton cycle for Advanced Fast reactor (AFR)-100 and Advanced Burner reactor (ABR)-1000 plants. A Code was developed to estimate the tower dimensions, power and water consumption, and to perform economic analysis. The code developed was verified against a vendor provided quotation and is used to understand the effect of ambient air and water conditions on the design of cooling tower. The calculations indicated that there exists optimum water conditions for given ambient air conditions which will result in minimum power consumption, thereby increasing the cycle efficiency. A cost-based optimization technique is used to estimate the optimum water conditions which will improve the overall plant economics. A comparison of different cooling options for the S-CO 2 cycle indicated that the cooling tower option is a much more practical and economical option compared to the dry air cooling or direct water cooling options.