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This research aims to present a standardized evaluation system to review and further enhance users’ levels of satisfaction with technologies, facilities, and services of a modern smart city at a time when the smart city paradigm has shifted from the focus of its infrastructural features to citizens. The study also seeks to verify the standardized system, so as to explore the possibility of its future application. For the goals, this research established the Structural Equation Model (SEM) based upon the basic structure of the Customer Satisfaction Index, which is a widely used ex-post assessment model, and upon implications of related studies. To verify the SEM, this study chose two cities, which are located far away from one another and employ different business methods, and conducted a survey of 212 and 197 residents, respectively, with the results being applied to the model for analysis to ascertain if the SEM is reliable and adequate. The analysis results showed that the model secures explanatory power in statistical terms, partially proving that it can be developed into a post-evaluation system for a citizens-centric smart city down the road. However, as meaningful differences were spotted in accordance with characteristics of each urban project, this study tried to come up with the background information of and reasons for such variations, to present implications for urban planning.

This paper proposed lithium-ion based high-voltage battery simulator. Matlab based battery parameters and modeling were implemented, and the characteristics of the modeled batteries were output by using three-phase grid-connected AC / DC PWM converters. The proposed methods were verified by PSIM.

In this paper, a pole-piece shape is proposed. We want to improve the low torque characteristics of the magnet gear and the large torque ripple problem. For the pole-piece design, the results were analyzed through the field finite element analysis. The relationship between the design variables and the objective function was analyzed using the Box-behnken method. Therefore the proposed pole-piece design increases the output density of the magnet gear and reduces the torque ripple which affects noise and vibration during gear operation. We also compared the transmission torque characteristics of general pole-piece, conventional magnetic flux concentrating type pole -piece, pole-piece of optimal design. It is confirmed that the pole-piece structure proposed in this paper has superior transmission torque characteristics.

Abstract SMART (System-integrated Modular Advanced ReacTor) is an integral reactor of 330 MW capacity with passive safety features under development in Korea. The design is developed by combining the firmly-established commercial reactor technologies with new and advanced technologies such as industry proven KOFA (Korea Optimized Fuel Assembly) based nuclear fuels, self-pressurizing pressurizer, helically coiled once-through steam generators, and new control concepts. The design of SMART focuses on enhancing the safety and reliability of the reactor by employing inherent safety features such as low core power density, elimination of large break loss of coolant accident, etc. In addition, in order to prevent the progression of emergency situations into accidents, the SMART is provided with a number of engineered safety features such as Passive Residual Heat Removal System, Passive Emergency Core Cooling System, Safeguard Vessel, and Passive Containment Over-Pressure Protection System. This paper presents an overview of the SMART design, characteristics of it’s safety systems, and results of over-pressure accident analyses. The results of the accident analyses show that the SMART provides the inherent over-pressure protection capability for design basis accidents without actuation of any protection devices such as safety valves, rupture disks, etc.

Abstract Recently, many studies have exploited the potential of deep learning to forecast energy demand, but they cannot explain the results. They only analyze the simple correlations between the input and output to discover the most important input features, or they depend on the manual investigation of the latent space embedded with power demand patterns. In this paper, to overcome these shortcomings, we propose a deep autoencoder that can explain the prediction results by manipulating the latent space. It consists of 1) a power encoder that embeds power information, 2) an auxiliary encoder that embeds auxiliary information for an interpretable latent space in two dimensions, 3) a predictor that predicts power demand by using concatenated values of the latent variables extracted from the two encoders, and 4) an explainer that provides the most important input features in predicting the future demand by utilizing the interpretable latent variables. Several experiments on a dataset of household electric energy demand show that the proposed model not only performs better than conventional models, with a mean squared error of 0.376 in predicting electricity demand for 60 min, but also provides the capacity to explain the results by analyzing the correlation of inputs, latent variables, and energy demand predicted.

Abstract The OECD/NEA Sandia Fuel Project provided unique thermal-hydraulic experimental data associated with Spent Fuel Pool (SFP) complete drain down. The study conducted at Sandia National Laboratories (SNL) was successfully completed (July 2009 to February 2013). The accident conditions of interest for the SFP were simulated in a full scale prototypic fashion (electrically heated, prototypic assemblies in a prototypic SFP rack) so that the experimental results closely represent actual fuel assembly responses. A major impetus for this work was to facilitate severe accident code validation and to reduce modeling uncertainties within the codes. Phase I focused on axial heating and burn propagation in a single PWR 17 × 17 assembly (i.e. “hot neighbors” configuration). Phase II addressed axial and radial heating and zirconium fire propagation including effects of fuel rod ballooning in a 1 × 4 assembly configuration (i.e. single, hot center assembly and four, “cooler neighbors”). This paper summarizes the comparative analysis regarding the final destructive ignition test of the phase I of the project. The objective of the benchmark is to evaluate and compare the predictive capabilities of computer codes concerning the ignition testing of PWR fuel assemblies. Nine institutions from eight different countries were involved in the benchmark calculations. The time to ignition and the maximum temperature are adequately captured by the calculations. It is believed that the benchmark constitutes an enlargement of the validation range for the codes to the conditions tested, thus enhancing the code applicability to other fuel assembly designs and configurations. The comparison of lumped parameter and CFD computer codes represents a further valuable achievement.

Domestic agro-byproduct potential in Korea is estimated to be approximately 4,018 × 103 tons of oil equivalent per year. Majority of agro-byproducts are unused and discarded. These unused agro-byproducts can potentially be converted into solid fuel for value addition. The energy potentials of solid fuels are generally characterized by proximate analysis and measuring calorific value; however, owing to the use of coal and coke, both the analyses could be expensive and time-consuming. Proximate analysis via thermogravimetric analysis is a relatively low cost and less time-consuming method than proximate analysis by ISO method (ISO 18134-1:2015, ISO 18123:2015, ISO 18122:2015). Thermogravimetric analysis-based proximate analysis of four agro-byproducts (pepper stem, perilla stem, corn stalk, and kenaf) was conducted. Additionally, the calorific values obtained from several equations based on the proximate analysis results were compared to that of the calorific value measured using calorimeter. The maximum difference between proximate analysis using thermogravimetric analysis and ISO method was 4.73%p, which was attributed to change in moisture content. It is recommended to measure the moisture content of biomass for 120–150 min (at 105 °C) and ash content for 80–120 min (at 815 °C). Three of the equations indicated a difference of less than 1.5 MJ kg−1 between the TGA-derived and the measured calorific value. For this study, It was determined that both proximate analysis and prediction calorific value can be conducted by thermogravimetric analysis.

New powertrain technologies, such as those used in Hybrid Electric Vehicles, have a price premium which is often offset by lower running costs. Total Cost of Ownership (TCO) combines these purchase and operating expenses to identify the most economical vehicles overall. This is a valuable assessment for both private and fleet purchasers. To date, no studies have compared Total Cost of Ownership across more than two vehicle markets or analysed historic costs. To address this gap, this research provides a more extensive assessment of TCO in three industrialized countries — the U.S.A. (California specifically), the UK, and Republic of Korea — for the time period from 2015 ∼ 2019. As an early analysis of the regional characteristics of TCO, this study aims to examine how TCO varies across different geographic regions and develop an analysis methodology for future analysis of environmental vehicles. To analyze the TCO under identical conditions for each region, the TCO result is calculated using data from conventional vehicles by utilizing sufficient statistical data. The TCO model includes registration and road taxes as well as insurance, fuel, financial interest, depreciation, and maintenance costs. To represent the local features, the research considers four vehicles from different manufacturers. Using the proposed TCO model, the regional characteristic is analyzed and a sensitivity analysis is performed with the parameters constituting the TCO model. This research has implications for both fleet purchasers and private owners considering new vehicles. The findings are also relevant for carmakers aiming to develop vehicle sales strategies optimized for specific regions.

Abstract This paper analyzes the operating characteristics of a superconducting magnetic energy storage (SMES) for the frequency control of an islanded microgrid operation. In the grid-connected mode of a microgrid, an imbalance between power supply and demand is solved by a power trade with the upstream power grid. The difference in the islanded mode is a critical problem because the microgrid is isolated from any power grid. For this reason, the frequency control during islanded microgrid operation is a challenging issue. A test microgrid in this paper consisted of a wind power generator, a PV generation system, a diesel generator and a load to test the feasibility of the SMES for controlling frequency during islanded operation as well as the transient state varying from the grid-connected mode to the islanded mode. The results show that the SMES contributes well for frequency control in the islanded operation. In addition, a dual and a single magnet type of SMES have been compared to demonstrate the control performance. The dual magnet has the same energy capacity as the single magnet, but there are two superconducting coils and each coil has half inductance of the single magnet. The effectiveness of the SMES application with the simulation results is discussed in detail.