• Energy Research
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Abstract A change in the thermal environment of an urban area affects health, living conditions, and energy consumption. In urban planning, urban parks are one of the methods for improving the thermal environment and saving cooling energy. Urban park construction can mitigate temperature, but it also causes urban development by increasing local attractiveness. To achieve efficient energy saving through parks in urban planning, the purpose of this study is to investigate the relationship between building energy consumption and urban characteristics both before and after the construction of an urban park. This study targeted Seoul's Gyeongui line forest, which was recently converted into a linear park on the former railway as an urban regeneration project. We analyzed the relationship between energy consumption and urban characteristics using a regression model, focusing on the changes before and after the construction. In this study, urban characteristics include environment, building physical characteristics, and economic variables. The results show that the construction of the urban park reduced not only temperature but also building energy consumption. The energy reduction effect of the park was limited to a marginal distance. Meanwhile, the urban park construction caused land prices to rise and prompted new development, and this changed the urban characteristics of the area and affected energy consumption. Despite changes in urban characteristics, urban park planning is an effective methods of reducing the energy consumption involved in cooling urban areas. We recommend comprehensive consideration of the urban factors when making park policy to reduce urban temperature and energy consumption.

Project: Coupled Model Intercomparison Project Phase 6 (CMIP6) datasets - These data have been generated as part of the internationally-coordinated Coupled Model Intercomparison Project Phase 6 (CMIP6; see also GMD Special Issue: http://www.geosci-model-dev.net/special_issue590.html). The simulation data provides a basis for climate research designed to answer fundamental science questions and serves as resource for authors of the Sixth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC-AR6). CMIP6 is a project coordinated by the Working Group on Coupled Modelling (WGCM) as part of the World Climate Research Programme (WCRP). Phase 6 builds on previous phases executed under the leadership of the Program for Climate Model Diagnosis and Intercomparison (PCMDI) and relies on the Earth System Grid Federation (ESGF) and the Centre for Environmental Data Analysis (CEDA) along with numerous related activities for implementation. The original data is hosted and partially replicated on a federated collection of data nodes, and most of the data relied on by the IPCC is being archived for long-term preservation at the IPCC Data Distribution Centre (IPCC DDC) hosted by the German Climate Computing Center (DKRZ). The project includes simulations from about 120 global climate models and around 45 institutions and organizations worldwide. Summary: These data include the subset used by IPCC AR6 WGI authors of the datasets originally published in ESGF for 'CMIP6.CMIP.SNU.SAM0-UNICON.piControl' with the full Data Reference Syntax following the template 'mip_era.activity_id.institution_id.source_id.experiment_id.member_id.table_id.variable_id.grid_label.version'. The SAM0-UNICON (SNU Atmosphere Model version 0 with Unified Convection Scheme) climate model, released in 2017, includes the following components: aerosol: MAM3, atmos: CAM5.3 with UNICON (1deg; 288 x 192 longitude/latitude; 30 levels; top level ~2 hPa), land: CLM4.0, ocean: POP2 (Displaced Pole; 320 x 384 longitude/latitude; 60 levels; top grid cell 0-10 m), seaIce: CICE4.0. The model was run by the Seoul National University, Seoul 08826, Republic of Korea (SNU) in native nominal resolutions: aerosol: 100 km, atmos: 100 km, land: 100 km, ocean: 100 km, seaIce: 100 km.

We devise a novel electrochemical method that enables the analysis of the average molecular weight (MW) of polyethylene glycol (PEG) in an acidic Cu plating bath. During the cyclic voltammetry analysis of the Cu plating bath, a hysteretic voltammogram is generated, and it is related to the MW of PEG. This relationship is used for the analysis of the average MW of PEG in the acidic Cu plating solution, with the error of analysis being less than 9%.

Recently, there have been frequent fluctuations in the wholesale prices of electricity following the increased penetration of renewable energy sources. Therefore, retailers face price risks caused by differences between wholesale prices and retail rates. As a hedging against price risk, retailers can utilize critical peak pricing (CPP) in a price-based program. This study proposes a novel multi-stage stochastic programming (MSSP) model for a retailer with self-generation photovoltaic facility to optimize both its bidding strategy and the CPP operation, in the face of several uncertainties. Using MSSP, decisions can be determined sequentially with realization of the uncertainties over time. Furthermore, to ensure a global optimum, a mixed integer non-linear programming is transformed into mixed integer linear programming through three linearization steps. In a numerical simulation, the effectiveness of the proposed MSSP model is compared with that of a mean-value deterministic model based on a rolling horizon method. We also investigate the optimal strategy of a retailer by changing various input parameters and perform a sensitivity analysis to assess the impacts of different uncertain parameters on the retailer’s profit. Finally, the effect of the energy storage system on the proposed optimization problem is investigated.

Although applying a specific perspective (e.g. energy citizenship) provides valuable information about citizens’ actions in relation to energy issues, confining their actions into just one category risks limiting our knowledge. This paper explores this hypothesis through a case study of residents’ energy-related activities at the Seokkwan Doosan apartment complex in Seoul. This research compares four citizenship types with Andrew Dobson’s categories and applies them all to the case study. This research yields the following findings. The Seokkwan case appears to have a mixture of all the citizenship characteristics discussed in this paper. The case study shows that only the concept of sustainability citizenship is suitable for explaining both rights and responsibilities. Although the case study only focuses on the private sphere, residents’ activities clearly had public implications, which are characteristics of all the types of citizenship. Regarding territoriality and nonterritoriality, aspects of ecological, sustainability, and energy citizenships appear only weakly. The case study reveals virtues of all citizenships. This case study reveals that the hypothesis is correct: we should be cautious about applying only a particular type of citizenship to a diverse case study.

Abstract Supercritical carbon dioxide (S-CO2) power cycle has been under the spotlight for years as one of the promising solutions to resolve the energy and environmental problem. The most of previous studies focused on cycle performances and applicable configuration. In this study, detailed and extensive analysis on the recompression S-CO2 power cycle was carried out to reflect more practical and desirable conditions. This study focused on the optimization of the S-CO2 cycle by evaluation of the irreversibility of the recuperators using the effectiveness analysis and pinch point temperature difference (PPTD) analysis. Split ratio from the main stream to the recompressor and compression ratio were considered as independent parameters. From the simulation, the characteristics and performance of the recompression cycle were discussed. The optimum operating conditions were determined in combinations of PPTDs of the two recuperators. With the performance curves, control strategy of the two independent parameters is ranged for desirable operation of S-CO2 power cycle.

This paper deals with in-flight calibration method of gyros and attitude sensors of the spacecraft on orbit. On-orbit calibration is an in-flight calibration process for more precise spacecraft attitude determination. For the spacecraft which is required more precise pointing accuracy, on-orbit calibration should be performed after the launch to accommodate attitude estimation error caused by vibration and thermal shocks. In this paper, a Quaternion based Extended Kalman Filter (EKF) is used to perform the on-orbit calibration. The observability of on-orbit calibration along trajectories is discussed by Lie-derivative-based observability analysis, and the degree of observability is computed by singular value decomposition (SVD). It is shown that the system is globally observable with calibration maneuver and the analysis results about the observable degree of each state are presented.

This study was conducted to develop a phase-space dataset in the International Atomic Energy Agency (IAEA) format for Monte Carlo (MC) simulations of the Leksell Gamma Knife® (LGK, Elekta Instrument AB, Stockholm, Sweden) Perfexion™ (PFX). An open-source MC code, namely, the Geant4 toolkit with a recently updated multi-threaded mode, was used to maximize the efficiency of the developed IAEA phase-space dataset. The absorbed dose profiles for single shots of the LGK PFX were calculated using the developed dataset and compared with those from radiochromic film measurements and Leksell GammaPlan® version 11.0.3 (LGP, Elekta Instruments) for verification. The mean relative absorbed dose differences in all single shots were less than 3.6% compared with the films and less than 4.0% compared with LGP. The collimator output factors were also calculated for all single shots and compared with the LGP results. The simulated collimator output factor was 0.816 ± 0.003 for a 4-mm shot and 0.903 ± 0.001 for an 8-mm shot in a spherical water phantom. The efficiency of the developed dataset was evaluated by comparing the times required for various simulations. Simulations with the phase-space dataset ran 25, 8.2 and 3.2 times faster than simulations without the phase-space dataset for 4-, 8-, and 16-mm shots, respectively. Using the dataset developed in this study, MC simulations of the LGK PFX can be performed more efficiently for various purposes, such as treatment plan verification and beam quality factor calculations.