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| 1 |
ID:
142267
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| Summary/Abstract |
This article presents a model to estimate North Korea's uranium enrichment capacity and to identify probable bottlenecks for scaling up that capacity. Expert assessment is used to identify and estimate the size of key centrifuge materials and component stockpiles. Bayesian probability networks are used to characterize uncertainties in these stockpiles and a deterministic optimization model to estimate the capacity of North Korea's uranium enrichment program given the assumed components and materials constraints. A Monte Carlo simulation model is used to propagate uncertainties through the optimization model. An illustration of this approach, based on the opinions of three experts, suggests that North Korea was likely (about 80 percent chance) to have a larger uranium enrichment capacity than what was displayed to visitors to the Yongbyon nuclear complex in 2010. The three most important bottlenecks to increases in enrichment capacity are the availability of pivot bearings, maraging steel, and high-strength aluminum. The nature of the model allows it to be easily updated as new information becomes available about centrifuge materials and component stockpiles.
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| 2 |
ID:
094403
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| Publication |
2010.
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| Summary/Abstract |
This paper analyzes the potential contribution of carbon capture and storage (CCS) technologies to greenhouse gas emissions reductions in the U.S. electricity sector. Focusing on capture systems for coal-fired power plants until 2030, a sensitivity analysis of key CCS parameters is performed to gain insight into the role that CCS can play in future mitigation scenarios and to explore implications of large-scale CCS deployment. By integrating important parameters for CCS technologies into a carbon-abatement model similar to the EPRI Prism analysis (EPRI, 2007 ), this study concludes that the start time and rate of technology diffusion are important in determining emissions reductions and fuel consumption for CCS technologies. Comparisons with legislative emissions targets illustrate that CCS alone is very unlikely to meet reduction targets for the electric-power sector, even under aggressive deployment scenarios. A portfolio of supply and demand-side strategies is needed to reach emissions objectives, especially in the near term. Furthermore, model results show that the breakdown of capture technologies does not have a significant influence on potential emissions reductions. However, the level of CCS retrofits at existing plants and the eligibility of CCS for new subcritical plants have large effects on the extent of greenhouse gas emissions reductions.
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