Recently, the use of clean energy is required by the society due to environmental problems caused by air pollution. In addition, with the frequent occurrence of natural disasters, it is all the more necessary to develop diverse distributed power generation and storage methods. The need to secure hydrogen as a new renewable energy source has increased year by year, and renewable energy options have attracted wider attention not only from a cost perspective, but also thanks to their environmental friendliness. In this paper, we highlight a completely self-sustainable renewable energy system consisting of unique equipment that technical college students in the Chugoku-Shikoku region developed with their technical prowess. Separately, we developed an experimental renewable energy management system and conducted experiments to check whether this system will function properly when a natural disaster occurs. We confirmed that the system is highly effective in that situation.

The process of collecting and disposing of coastal marine debris isn’t usually economically feasible without government subsidies. However, Ishida et al. reported this process can be made profitable by linking Styrofoam waste oil liquefaction equipment with decentralized energy systems. Examples of these energy systems include cogeneration systems (CGS) and photovoltaic power generation. In this study, a model was developed to examine which part of a coastal debris disposal operation system should be assisted with profits generated from a coastal marine debris disposal network linked to CGS. This is expected to dispose of as much coastal marine debris as possible in a short period of time. Specifically, it was modeled using deep Q-learning (DQN), which is one of deep reinforcement learning methods. On the premise that a certain amount of marine debris reached the coast, the model incorporated the combination of three elements, namely greater profits gained by increasing the capacity of CGS, stocking profits for a certain period of time and marine debris collection. The model developed herein made it possible to handle the amount of coastal marine debris that wouldn’t have been treated if profits were spent on the coastal marine debris disposal network on a yearly basis. This DQN-based model resulted in the development of a strategy, which reflects the view that “the larger the initial amount of litter becomes, the longer the stock period of profits from CGS should become.”

In this study, we have evaluated NO_x reduction performance of the exhaust gas component recirculation (EGCR) system by conducting an experiment and a numerical simulation. In this system, NO_x is separated from diesel engine exhaust gas and concentrated using adsorbents, and then concentrated NO_x is mixed into diesel engine intake air. In the experiment, NO_x concentrated during the adsorption and desorption processes in the EGCR system was simulated by using a NO cylinder and it was supplied into the intake air of a diesel engine to elucidate the effect of the NO_x supply on NO_x reduction. The results showed that the more NO_x was provided into the intake, the less NO_x was produced, and that NO_x reduction effects were more prominent during low load operation. In the numerical simulation, we evaluated the impact of the EGCR system using a model we developed based on data from the diesel engine in the experiment when NO_x was supplied into the intake air. Then we compared the results of the experiment and those of the numerical simulation.

  The calculation formula for the CCAI (Calculated Carbon Aromaticity Index) was derived from engine experiments using distillate and residual oils. The author prepared two-component test fuels that are a mixture of an alkane and an aromatic hydrocarbon, both of which have different boiling points. The test fuels were produced with various components and mixing ratios. This study evaluated the effect of evaporation characteristics on the CCAI and the cetane number. In addition, a method for modifying the CCAI was examined based on the liquid properties and the mixing ratios of the two components. It was confirmed that a correlation exists between the CCAI and the cetane number when test fuels with different mixing ratios of the two components are used. In contrast, test fuels containing a mixture of two different components did not have the same cetane number even if they had the same CCAI. These characteristics of the simplified two-component fuels were similar to those of marine fuels confirmed by previous studies. The evaporation rate behavior of the test fuels could be either unimodal or bimodal depending on the types of two fuels. The cetane number of a test fuel with a bimodal evaporation rate was not always small. The enhanced CCAI, which was the volume average of the CCAI formula adjusted for each alkane and aromatic component, had a higher correlation with the cetane number than the current CCAI does.