The present study investigates the arc behavior and temperature distribution in a water plasma with mist generation under different mist feeding rates. The arc fluctuation was observed using a high-speed camera with arc voltage measurement. Further, the arc temperature was visualized by a high-speed video camera and band–pass filters based on the Boltzmann plot method. The experimental results showed that the arc fluctuation was in the restrike mode, and the frequency as well as the arc length apparently increased with an increase of mist feeding rate due to stronger drag force. Higher arc existence probability was also observed. At the same time, the mist feeding rate played an important role in controlling the arc area with high temperature. This study will open up new opportunities for waste treatment by understanding the fundamental arc characteristics in a water plasma system.

Design process of the engineering plastic parts is performed by several companies, and the companies systematize experiences to prepare standards for proceeding the design process. According to the prepared standards, they revise product design to fulfill requirements. These standards are collectively referred to as “engineering standards” which comprise design standards including standard designs and guidelines to modify the same. Further, since development of the engineering plastic parts is managed on a project basis where they have competitions to select their counterparts, each company necessarily develops its engineering standards separately. Under the above situation, the companies introduce computer aided engineering (CAE) environment to achieve efficient design revision. The CAE environment was expected to eliminate redundant design revision and evaluation. However, due to inconsistency of the design standards among the companies, inefficient trial-and-error approach is not avoidable in the design process. The companies have to adjust simulation results obtained from the counterparts according to their own design standards to be used in their design revision. Such an adjustment is an ad-hoc approach to be repeated in each project. In view of the project-based management, however, the design standards cannot be adjusted to be consistent. Therefore, to overcome the inefficient trial-and-error approach, the present paper proposes a framework for coordinating the design standards that conforms to the structure of engineering plastic industry. The framework was developed by incorporating activities for coordinating the design standards to the previously reported reference business process model for the design process. Whether the developed framework can coordinate the design standards between different companies was confirmed by simulating two illustrative examples. In the simulation, the framework described the process of updating the design standards. Accordingly, the developed framework was confirmed to be effective to resolve the inefficient trial-and-error approach.

A novel methodology based on independent component analysis-statistical characteristics (ICA-SC) is proposed in this study to monitor multivariable systems whose variables present significant levels of autocorrelation. Initially, ICA is utilized to find the independent components of the process. Then, a window data set in the IC subspace is obtained using default parameters, such as window width and sliding size. Subsequently, the statistical characteristics of each window data set, including the mean and the variance of monitored independent components, are calculated. Finally, a new statistic index based on these calculated statistical characteristics is developed to monitor the status of the current process, and a fault diagnosis strategy based on the contribution charts of these independent components is used for analyzing the cause of abnormal change. The simulation results of a numerical case and Tennessee Eastman benchmark process illustrate that ICA-SC can reduce the computational complexity and improve the fault detection rate of a dynamic process with significant autocorrelation when compared with traditional multivariable monitoring methodologies such as dynamic component analysis (DPCA) and ICA.

Self-heat recuperation drastically reduces the energy consumption of thermal processes by adding work to circulate the whole process heat without heat addition. However, its theoretical foundations have not been fully established yet. This paper aims to elucidate the thermodynamic mechanism of self-heat recuperation with non-isentropic compression and expansion for a thermal gas cycle in terms of exergy analysis. The exergy analysis was performed with a modularization method using the module expression flow, the temperature–entropy, and the energy conversion diagram. The exergy analysis led to the significant conclusions that self-heat recuperation minimizes the energy consumption of gas thermal processes and that key information can be easily obtained by simply focusing on the exergy destruction without using complex process simulations. Heat circulation is driven by adding the work input to provide the minimum work required for heat transfer using the compressor, and theoretically all the excess work can be recovered to offset part of the work input using the expander. In practice, the irreversibility of adiabatic compression and expansion destroys part of the excess work, leading to a decrease in the excess work and an equivalent increase in the waste heat. The net work input is equal to the minimum work required for heat circulation and is converted into waste heat, whose anergy is transformed from the exergy destruction due to heat transfer, non-isentropic compression, and non-isentropic expansion. The minimum work required for heat circulation can be quantified by calculating the waste heat via the total exergy destruction. Thus, self-heat recuperation is the most energy-efficient solution to the design and retrofit of energy-saving gas thermal processes and is promising for process intensification. A case demonstration with numerical results on the heat circulation of air is presented to facilitate an intuitive understanding of the thermodynamic mechanism.

This study employed simulation software to model the coal-based polygeneration systems (PGSs). The carbon-utilization ratios (η^C), hydrogen-utilization ratios (η^H), and energy-saving ratios (ESRs) were used to quantitatively analyze the performance of various coal-based PGSs. This analysis was based on two parameters: the unreacted gas circulation ratio (r) and the ratio of synfuel energy output to power output (λ). The results indicate that both r and λ affect the η^C, η^H, and ESR values. Increasing r was found to increase element utilization and ESRs, and a better performance was achieved when a water-gas shift (WGS) reactor was utilized. The highest η^C, η^H, and ESR values obtained were 29.08, 37.89, and 17.68%, respectively. Increasing λ was also found to increase element utilization and ESRs. When λ=4 and both unreacted-gas circulation and the WGS reactor were employed, the highest element-utilization ratios (η^C=19.59%, η^H=37.78%) and ESR (19.78%) were achieved. In the corresponding case where a WGS reactor was not used, the η^H value significantly improved over the range λ=0.0–2.0.

The present study further develops an approach in predicting reactions undergone by coal volatiles in a reducing section (reductor) of an air-blown two-stage entrained flow gasifier toward designing a better gasification process. A detailed chemical kinetic model was first applied to simulate chemical reactions of a complex molecular mixture of the coal volatiles evolved due to rapid pyrolysis of coal fed into the reductor. The composition of volatiles was determined based on pyrolysis-gas chromatography experiments, where 22 compounds including inorganic gases (H₂, H₂O, CO and CO₂), light hydrocarbon gases (C₁–C₄) and aromatic hydrocarbons (benzene to pyrene) were identified. Gas composition at the reductor inlet was estimated by integrating the information on the experimentally obtained molecular composition of the volatiles, and the thermodynamically calculated composition of inorganic gases generated from the combustor and the coal feeding rates into reductor and combustor. Concentration profiles of the individual chemical species, as well as soot particles along with the flow direction of the reductor, were revealed by using an extended detailed chemical kinetic model involving 202 species, 1,351 gas-phase reactions and 101 surface reactions for soot formation and growth. The simulation highlighted that near-complete decomposition of tar (<1.5 mg/Nm³) regarded as a set of all aromatic hydrocarbons is likely to require operation temperature of the reductor at temperatures as high as 1,200°C, when the combustor is operated at 1,800°C.

In this study, hydrothermal leaching of spent lithium-ion battery (LIB) cathode materials, Li(Ni, Mn, Co)O₂ (NMC), was performed with citric acid using a batch-type device and a flow system in turn. Before the hydrothermal experiments, NMC cathode materials were pretreated and characterized. The effect of citric acid concentration on leaching efficiencies of metal components was studied using the batch-type device. Then, the preliminary experimental conditions for the continuous hydrothermal leaching using the flow system were determined and pre-set, including the temperature of 200°C, the citric acid concentration of 0.4 mol/L, the pulp density of 10 g/L, and the flow rate of 30 mL/min. Finally, NMC cathode materials were leached continuously in hydrothermal water using the flow system. The leachate with a high leaching efficiency can be collected continuously since 65 min of feeding the slurry, and the maximum leaching efficiency of Li, Co, Ni, and Mn was 96%, 91%, 98%, and 94%, respectively. This is the first time to achieve the continuous leaching of spent LIB cathode materials, which is significant for the future application in practice.