3 resultados para Hierarchical zeolites


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Demand response (DR) algorithms manipulate the energy consumption schedules of controllable loads so as to satisfy grid objectives. Implementation of DR algorithms using a centralized agent can be problematic for scalability reasons, and there are issues related to the privacy of data and robustness to communication failures. Thus, it is desirable to use a scalable decentralized algorithm for the implementation of DR. In this paper, a hierarchical DR scheme is proposed for peak minimization based on Dantzig-Wolfe decomposition (DWD). In addition, a time weighted maximization option is included in the cost function, which improves the quality of service for devices seeking to receive their desired energy sooner rather than later. This paper also demonstrates how the DWD algorithm can be implemented more efficiently through the calculation of the upper and lower cost bounds after each DWD iteration.

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Safety on public transport is a major concern for the relevant authorities. We
address this issue by proposing an automated surveillance platform which combines data from video, infrared and pressure sensors. Data homogenisation and integration is achieved by a distributed architecture based on communication middleware that resolves interconnection issues, thereby enabling data modelling. A common-sense knowledge base models and encodes knowledge about public-transport platforms and the actions and activities of passengers. Trajectory data from passengers is modelled as a time-series of human activities. Common-sense knowledge and rules are then applied to detect inconsistencies or errors in the data interpretation. Lastly, the rationality that characterises human behaviour is also captured here through a bottom-up Hierarchical Task Network planner that, along with common-sense, corrects misinterpretations to explain passenger behaviour. The system is validated using a simulated bus saloon scenario as a case-study. Eighteen video sequences were recorded with up to six passengers. Four metrics were used to evaluate performance. The system, with an accuracy greater than 90% for each of the four metrics, was found to outperform a rule-base system and a system containing planning alone.

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Metal exchanged CHA-type (SAPO-34 and SSZ-13) zeolites are promising catalysts for selective catalytic reduction (SCR) of NOx by NH3. However, the understanding of the process at the molecular level is still limited, which hinders the identification of its mechanism and the design of more efficient zeolite catalysts. In this work, modelling the reaction over Cu-SAPO-34, a periodic density functional theory (DFT) study of NH3-SCR was performed using hybrid functional with the consideration of van der Waals (vdW) interactions. A mechanism with a low N–N coupling barrier is proposed to account for the activation of NO. The redox cycle of Cu2+ and Cu+, which is crucial for the SCR process, is identified with detailed analyses. Besides, the decomposition of NH2NO is shown to readily occur on the Brønsted acid site by a hydrogen push-pull mechanism, confirming the collective efforts of Brønsted acid and Lewis acid (Cu2+) sites. The special electronic and structural properties of Cu-SAPO-34 are demonstrated to play an essential role the reaction, which may have a general implication on the understanding of zeolite catalysis.