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With the formation of an international carbon-neutral framework, interest in reducing greenhouse gas emissions is increasing. Ammonia is a carbon-free fuel that can be directly combusted with the role of an effective hydrogen energy carrier, and its application range is expanding. In particular, as research results applied to power generation systems such as gas turbines and coal-fired power plants have been reported, the technology to use them is gradually being advanced. In the present study, starting with a fundamental combustion research case conducted to use ammonia as a fuel, the application research case for gas turbines and coal-fired power plants was analyzed. Finally, we report the results of the ammonia-air burning flame and pulverized coal-ammonia-air co-fired research conducted at the authors’ research institute.

As interest in point cloud processing has gradually increased in the industry, point cloud sampling techniques have been researched to improve deep learning networks. As many conventional models use point clouds directly, the consideration of computational complexity has become critical for practicality. One of the representative ways to decrease computations is downsampling, which also affects the performance in terms of precision. Existing classic sampling methods have adopted a standardized way regardless of the task-model property in learning. However, this limits the improvement of the point cloud sampling network’s performance. That is, the performance of such task-agnostic methods is too low when the sampling ratio is high. Therefore, this paper proposes a novel downsampling model based on the transformer-based point cloud sampling network (TransNet) to efficiently perform downsampling tasks. The proposed TransNet utilizes self-attention and fully connected layers to extract meaningful features from input sequences and perform downsampling. By introducing attention techniques into downsampling, the proposed network can learn about the relationships between point clouds and generate a task-oriented sampling methodology. The proposed TransNet outperforms several state-of-the-art models in terms of accuracy. It has a particular advantage in generating points from sparse data when the sampling ratio is high. We expect that our approach can provide a promising solution for downsampling tasks in various point cloud applications.

Diesel fuel exhibits excellent combustion characteristics and stability. However, diesel use is becoming restricted because of its associated environmental problems. Fuel emulsification, which increases efficiency and reduces pollution, became the solution of environmental problem. In this study, five water:diesel emulsions with mass ratios (0.3, 0.6, 1.0, 1.2, and 1.5) via ultrasonication were synthesized with and without surfactant. The optimal water:diesel ratio (=1:1) of an emulsion containing the surfactant was found by analyzing fuel concentration, mixing time, and viscosity. The combustion characteristics of single-droplet optimal emulsions were studied through ignition delay, burning rate, and total droplet lifetime at high temperature (400–700 °C) and pressure (1–15 bar), and micro-explosion phenomenon was observed. Although the ignition delay of emulsion increased, the total lifetime of the emulsion droplet was lower than that of diesel under 5 bar, 600 °C condition.

The purpose of this study is to recognize modeling methods for coal combustion and gasification in commercial process analysis codes. Many users have appreciated the reliability of commercial process analysis simulation codes; however, it is necessary to understand the physical meaning and limitations of the modeling results. Modeling of coal gasification phenomena has been embodied in commercial process analysis simulators such as Aspen. Commercial code deals with modeling of the gasification system with a number of reactor blocks supported by the specific code, not as a coal gasifier. However, the primary purpose of using process analysis simulation code is to interpret the whole plant cycle rather than an individual unit such as a gasifier. Equilibrium models of a coal gasifier are generally adopted in the commercial codes, where the method of Gibbs free energy minimization of chemical species is applied at the given temperature and pressure. The equilibrium model of the coal gasifier, RGibbs, in commercial codes provides users with helpful information, such as exit syngas temperature, composition, flow rate, performance of coal gasifier model, etc. with various input and operating conditions. This simulation code is being used to generate simple and fast response of results. Limitations and uncertainties are interpreted in the view of the gasification process, chemical reaction, char reactivity, and reactor geometry. In addition, case studies are introduced with examples. Finally, a way to improve the coal gasifier model is indicated, and a kinetically modified model considering reaction rate is proposed.

Rotary kiln reactors are frequently equipped with an axial burner with which solid burden material is directly heated. The burner flame provides the heat required for the vaporization of the water and the reaction of the solid phase. Lifters are commonly used along the length of the system to lift particulate solids and increase the heat transfer between the solid bed and the combustion gas. The material cascading from the lifters undergoes drying and reacting through direct contact with the gas stream. In this study, volume distribution of materials held within lifters was modeled according to the different lifter configuration and appropriate configuration was used for the design purpose. This was applied to the simplified one-dimensional heat balance model of a counter-current flow reactor, which contributes to the increase of the effective contact surface, and thereby enhances the heat transfer.