How to improve the combustion efficiency and reduce harmful emissions has been a hot research topic in the engine field and related disciplines. Researchers have found that nano-additives to diesel-biodiesel fuel blends have achieved significant results. Many research results and both current and previous studies on nanoparticles have shown that nano-additives play an essential role in improving the performance of internal combustion engines and reducing the emission of harmful substances. This paper summarizes the recent research progress of nanoparticles as additives for diesel-biodiesel fuel blends. Firstly, the excellent properties of nanoparticles are described in detail, and the preparation methods are summarized and discussed. Secondly, the effects of several commonly used nanoparticles as diesel-biodiesel fuel blends on combustion performance and harmful substances emissions in terms of combustion thermal efficiency, brake specific fuel consumption, CO, UHC and NOx, are reviewed. Finally, the effects of nano-additives on internal combustion engines, the environment and human health are discussed. The work carried out in this paper can effectively contribute to the application of nanomaterials in the fuel field. Based on our work, the researchers can efficiently select suitable nano-additives that enable internal combustion engines to achieve efficient combustion and low-emission characteristics.
Qinzhou Port is one of the most important ports in the "Beibu Gulf" of China. It is also the main hub port of the "21st century maritime silk road" strategy. Based on a basic collision risk assessment approach, an Event Sequence Diagram (ESD) model that explains the fourstage collision avoidance decision-making procedure is proposed from the perspectives of perception, cognition, decision, and execution. Using the historical data derived from collision accident reports from the Qinzhou Port waters from 2013 to 2017, as well as the data elicited from expert knowledge, a quantitative evaluation of probability distributions of different collision failure modes is performed. The results are also compared with relevant results from other types of navigation waters to analyse collision risk level of Qinzhou waters. At the same time, the main failures paths of collision avoidance decision making are identified. The proposed model can provide with an overall collision risk picture from a macro perspective.
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