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In this study, cargo boil-off gas (BOG) re-liquefaction systems for ammonia-fueled liquefied carbon dioxide (LCO2) carriers were analyzed. These systems use cold energy from ammonia to reliquefy the CO2 BOG. In this study, a system that can completely reliquefy the CO2 BOG at all engine loads using only one heat exchanger is proposed, instead of the existing cascade system that requires multiple components. R744, which has a low global warming potential, was used as the working fluid for the refrigeration cycle in the CO2 BOG re-liquefaction system. The organic Rankine cycle (ORC) was used to reduce the net power consumption of the system. The existing and proposed systems were classified into Case 1 (existing system), Case 2 (our proposed system), and Case 3 (Case 2 combined with an ORC). Thermodynamic and economic analyses were conducted. Case 2 is a system with a simpler configuration than Case 1, but it has a similar thermodynamic performance. Case 3 has a higher exergy destruction rate than Cases 1 and 2, owing to the ORC, but it can significantly reduce the net power consumption. The economic analysis shows that Cases 2 and 3 reduce the total annual costs by 17.4% and 20.1%, respectively, compared to Case 1. The proposed systems are significantly more advantageous for long-term operation than existing systems. [ABSTRACT FROM AUTHOR]

Recently, the CO2 power cycle has attracted attention because of tightening environmental regulations. The turbine is a factor that greatly affects the efficiency of the cycle. The radial outflow turbine is a turbomachine with the various advantages of an axial flow turbine and a radial inflow turbine, but the design theory for the turbine is uncertain. In this study, a preliminary design algorithm for a radial outflow turbine with a multi-stage configuration is presented. To verify the preliminary design algorithm, a preliminary design for a two-stage radial outflow turbine for a CO2 power cycle was carried out, and a computational fluid dynamic analysis was performed. Consequently, values close to the target performance were obtained, but blade optimization was performed to obtain more satisfactory results. The final geometry of the radial outflow turbine was obtained through optimization considering the blade exit angle related to the deviation angle, blade maximum thickness-true chord ratio, and incidence angle. In the final geometry, the error rates of power ( W ˙ ), efficiency ( η t s ), and pressure ratio ( P R t s ) between target performance and computational fluid dynamic results were improved to 5.0%, 4.8%, and 1.8%, respectively. The performance and flow characteristics of the initial and final geometries were analyzed. [ABSTRACT FROM AUTHOR]

In this paper, we propose a graph-based multiscale saliency-detection algorithm by modeling eye movements as a random walk on a graph. The proposed algorithm first extracts intensity, color, and compactness features from an input image. It then constructs a fully connected graph by employing image blocks as the nodes. It assigns a high edge weight if the two connected nodes have dissimilar intensity and color features and if the ending node is more compact than the starting node. Then, the proposed algorithm computes the stationary distribution of the Markov chain on the graph as the saliency map. However, the performance of the saliency detection depends on the relative block size in an image. To provide a more reliable saliency map, we develop a coarse-to-fine refinement technique for multiscale saliency maps based on the random walk with restart (RWR). Specifically, we use the saliency map at a coarse scale as the restarting distribution of RWR at a fine scale. Experimental results demonstrate that the proposed algorithm detects visual saliency precisely and reliably. Moreover, the proposed algorithm can be efficiently used in the applications of proto-object extraction and image retargeting. [ABSTRACT FROM PUBLISHER]