• Energy Research
• KR close

The performance of the CO2 absorber column using mono-ethanolamine (MEA) solution as chemical solvent are predicted by a One-Dimensional (1-D) rate based model in the present study. 1-D Mass and heat balance equations of vapor and liquid phase are coupled with interfacial mass transfer model and vapor-liquid equilibrium model. The two-film theory is used to estimate the mass transfer between the vapor and liquid film. Chemical reactions in MEA-CO2-H2O system are considered to predict the equilibrium pressure of CO2 in the MEA solution. The mathematical and reaction kinetics models used in this work are calculated by using in-house code. The numerical results are validated in the comparison of simulation results with experimental and simulation data given in the literature. The performance of CO2 absorber column is evaluated by the 1-D rate based model using various reaction rate coefficients suggested by various researchers. When the rate of liquid to gas mass flow rate is about 8.3, 6.6, 4.5 and 3.1, the error of CO2 loading and the CO2 removal efficiency using the reaction rate coefficients of Aboudheir et al. is within about 4.9 % and 5.2 %, respectively. Therefore, the reaction rate coefficient suggested by Aboudheir et al. among the various reaction rate coefficients used in this study is appropriate to predict the performance of CO2 absorber column using MEA solution. [Acknowledgement. This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF), funded by the Ministry of Education, Science and Technology (2011-0017220)].

In the potential induced degradation (PID) phenomenon, the output power of a photovoltaic (PV) module decreases due to the high potential difference between the PV system and the ground. This voltage forcefully moves the positive charge in the module to the surface of the solar cell. The accumulated charge leads to the performance deterioration of the module, namely, PID of the module. We conducted a study to accurately predict the output reduction of the module operating in various installation conditions coming from the PID phenomenon. We investigated the leakage current flowing through front glass laminated with encapsulation material simultaneously exposed to various performance conditions of the PV system, namely, relative humidity, temperature, and applied voltage, which have an important effect on the PID of the module. The degradation of the module coming from PID was calculated on the basis of the obtained leakage current. To confirm the calculated data, modules with one solar cell were manufactured and the power loss results of the modules' exposure to various PID generation experiments were compared with the expected results. The results showed that we could predict the degradation of the modules by PID within a 2% tolerance under the PV system installation conditions.

Abstract A tele-operated mobile robot has been developed for the preventive maintenance and remote inspection of nuclear power plants such as remote maintenance work in reactor coolant system at PWR and inspection of pressure tubes in calandria at PHWR. The extendable inspection mast attached on the mobile platform enables human eyes to look into reactor face during full power plant operation. These robotic systems have been developed for keeping human workers from high radiation exposure in hostile nuclear environments

Controlling the morphological structure of titanium dioxide (TiO2) is crucial for obtaining superior power conversion efficiency for dye‐sensitized solar cells. Although the sol–gel‐based process has been developed for this purpose, there has been limited success in resisting the aggregation of nanostructured TiO2, which could act as an obstacle for mass production. Herein, we report a simple approach to improve the efficiency of dye‐sensitized solar cells (DSSC) by controlling the degree of aggregation and particle surface charge through zeta potential analysis. We found that different aqueous colloidal conditions, i.e., potential of hydrogen (pH), water/titanium alkoxide (titanium isopropoxide) ratio, and surface charge, obviously led to different particle sizes in the range of 10–500 nm. We have also shown that particles prepared under acidic conditions are more effective for DSSC application regarding the modification of surface charges to improve dye loading and electron injection rate properties. Power conversion efficiency of 6.54%, open‐circuit voltage of 0.73 V, short‐circuit current density of 15.32 mA/cm2, and fill factor of 0.73 were obtained using anatase TiO2 optimized to 10–20 nm in size, as well as by the use of a compact TiO2 blocking layer.

Abstract Clothing insulation is a key variable in the prediction of occupant thermal comfort. Consequently, the aim of the current study was to develop predictive models that forecast clothing insulation levels of building occupants. Using field measurements, we investigated the influence of outdoor environment factors and mode of transport on clothing insulation levels of university students. Our results showed that both the mode of transport and weather variables influenced the clothing insulation levels of the students. We then developed a deep neural network model that forecasts mean daily clothing insulation levels using outdoor air temperature at 6 am, dew point temperature at 6 am, gender, season and mode of transport in the based on the collected data from 1316 questionnaire surveys. In addition, we revealed that outdoor environment factors had stronger associations with clothing insulation levels than indoor environment elements. The developed deep neural network model indicated a high R² value of 0.90. In comparison to the deep neural network model, a developed linear model using the same data indicated a lower R² value of 0.698, which implies that the proposed deep neural network model provides an efficient method to forecast clothing insulation levels.

The work proposed a reliability demonstration test (RDT) process, which can be employed to determine whether a finite population is accepted or rejected. Bayesian and non-Bayesian approaches were compared in the proposed RDT process, as were lot and sequential sampling. One-shot devices, such as bullets, fire extinguishers, and grenades, were used as test targets, with their functioning state expressible as a binary model. A hypergeometric distribution was adopted as the likelihood function for a finite population consisting of binary items. It was demonstrated that a beta-binomial distribution was the conjugate prior of the hypergeometric likelihood function. According to the Bayesian approach, the posterior beta-binomial distribution is used to decide on the acceptance or rejection of the population in the RDT. The proposed method in this work could be used to select item providers in a supply chain, who guarantee a predetermined reliability target and confidence level. Numerical examples show that a Bayesian approach with sequential sampling has the advantage of only requiring a small sample size to determine the acceptance of a finite population.

Abstract Because of the increased need for virtual analysis during the vehicle manufacturing processes, more stringent optimization methods are required for the simulation field. Owing to the use of big data from engine testing, 1D analysis can provide more powerful approaches in the conceptual design phase for car makers. In this study, system-level optimization of dual-loop EGR was performed at both the engine and vehicle level, whereas our previous research had been performed at the engine level. Depending on the virtually developed engine and vehicle models and control scheme from our previous works, improved driving capabilities could be observed under light-duty diesel vehicle systems under the world-harmonized light-vehicles test procedure (WLTP). The numerical model was extended through two steps. The first step includes model conversion from the base engine model with an HP EGR system to a virtual engine model with a dual-loop EGR system. The second step represents mode extension from the virtual engine model with a dual-loop EGR system to a vehicle model with a dual-loop EGR system. Optimizing the dominant parameters and using design of experiment (DoE)-based multi-objective Pareto optimization methods in each step, fuel economy could be improved by approximately, 1.5% and the deNOX rate was approximately 5% that of the conventional NEDC. It is implied that the dual-loop EGR system and gear strategy could improve vehicle performance under difficult driving conditions.

Tangential-firing boilers develop large swirling fireballs by using pulverized coal and air from the corners of the burner zone. During operation, however, the boiler may experience an uneven air supply between corners; this deforms the fireball, raising various issues concerning performance and structural safety. This study investigated the characteristic boiler performance and the role of burner tilting in a 500 MWe boiler with secondary air (SA) in two corners that are up to 1.9 times larger than those in the other corners. Computational fluid dynamics simulations with advanced coal combustion sub-models were employed with the following two sets of cases: (i) six cases of actual operation to validate the modeling and (ii) sixteen cases for the parametric study of SA flow ratio and burner tilt between −15° and +26°. The results showed that the uneven SA supply deteriorated the boiler performance in various aspects and the burner tilt can be used to alleviate its impact. With a larger SA supply from the left wind box, the mass flow, heat absorption, and O2 concentration were larger in the right half of the heat exchanger sections owing to the rotating flow. The corresponding imbalance in the reaction stoichiometry increased the peak temperature entering the tube bundles by up to 60 °C and NO emissions by 6.7% as compared with normal operations. The wall heat absorption was up to 19% larger on the right and front walls. The high burner tilt of +26° helped alleviate the impact of uneven SA supply on the heat distribution and uniformity of the flow pattern and temperature, whereas a +15° burner tilt was the least favorable.