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Torrefaction is a thermal treatment process to pre-treat biomass at temperature of under an inert atmosphere. It was known that torrefaction process strongly depended on the decomposition temperature of the lignocellulosic constituents in biomass. In this work, the torrefaction characteristics of baggase has been studied. This study focuses on the relation between the energy yields, heating values, gas emission, volatile and ash constituents with torrefaction temperatures and times. The activation energies of baggase torrefaction has been studied by using TGA (Thermogravimetric Analyzer). From this work, it was seen that ash constituents and heating values were increased with torrefaction temperature, while volatile constituents and energy yields decreased. It was also found that carbon monoxide containing oxygen were decomposed at a lower temperature than those of hydrocarbon compounds, .

This paper presents a CFD analysis of three types of axial-flow magnesium-based automotive cooling fans. The numerical modeling was conducted for geometrically modified fan designs: one with no-beads, the second one with beads at the suction-side of the fan namely reverse-beads fan, and the third one with beads installed at the pressure-side of the fan namely forward-beads fan. The effect of geometric modifications of the fan blades on the volumetric flow rate, fan efficiency, and energy efficiency was investigated using Reynolds-averaged Navier-Stokes (RANS) equations following the multiple reference frame methodology. The fan with no-beads was fabricated using 3D printing technology and tested to measure the flow velocity. Subsequently, the fans with beads along with the no-beads fan designs were numerically analyzed. The volumetric flow rate, fan efficiency, and energy efficiency were quantified as a function of fan rotating speed. The results show that the reverse-beads fan produced a relatively more volumetric flow rate and energy-efficient compared to the forward-beads fan. Moreover, to further improve the performance of the reverse-beads fan, the location and size of the bead structure were varied along the radial direction of the fan blade. The optimized reverse-beads fan significantly improves the fan performance.

Abstract Wood biomass char was used in a direct carbon fuel cell (DCFC) as an alternative fuel. This has many advantages because the DCFC is a high-efficiency system and wood biomass is a carbon-free and regenerative material. Several analytical techniques were employed to analyze the characteristics of three fuels, their effects on the cell’s performance, and the electrochemical reactions between the fuels and the electrolyte in the system. The morphological and textural characteristics of biomass char were similar to those of two types of coal used as fuels for a DCFC system in spite of the char’s significantly lower carbon content. A practical evaluation of the fuels used in the DCFC system was conducted, and when using the biomass char, the maximum power density was 60–70% that of the corresponding value for coal under the same conditions. The performance of the biomass char fuel was improved by stirring. The possibility of its practical application was also discussed.

Abstract This study newly introduces a complementary cooperative algorithm considering generative adversarial network (GAN)-Conditional Latent Space (CLS) combined with bidirectional long short-term memory (BLSTM) for improved and efficient lithium-ion rechargeable battery state prediction. The GAN-CLS algorithm, which is an advanced method of GAN, can generate corresponding images from an input label description. Long short-term memory (LSTM) is a specific recurrent neural network (RNN) architecture that can predict sequences more accurately than conventional RNNs. In terms of battery state prediction, the combination of two methods (GAN-CLS and LSTM) surely provides more improved and efficient rechargeable battery state prediction in contrast to conventional state predictors. The procedure of this study is as follows. First, we propose methods to enhance the data from battery charge/discharge by converting prepared data to images; then, the GAN-CLS method is used to generate corresponding battery data from previous images. Subsequently, the generated data is used to train the BLSTM model. Finally, the trained model is used to predict the battery state. By various experiments and verification, it is concluded that the proposed study can be a good solution for rechargeable battery state prediction (reduction of the time cost 50 times in modeling and 20 times in train/test, provision of a more accurate prediction mean square error (MSE) smaller than 0.0025 and the average MSE less than 0.0013).

For the first time, we here propose a green methodology to modify a low bandgap polymer for highly efficient solar cells using atmospheric pressure plasma jet or soft plasma operating on different feeding gases (air, Ar and N2). The physical properties of the modified polymer were investigated using conductivity measurements, UV-visible spectroscopy, photoluminescence spectroscopy, X-ray photoelectron spectroscopy, cyclic voltammograms, atomic force microscopy, cathodoluminescence and confocal Raman spectroscopy. Further, we examined the variation of the work function of the polymer before and after plasma treatment using a γ-focused ion beam. Additionally, photovoltaic cells based on the plasma-modified polymer having ITO/PEDOT:PSS/PHVTT (with or without plasma modification):PC71BM/LiF/Al configuration were fabricated and then characterized. We found that the power conversion efficiency (PCE) of the plasma-modified polymer increased dramatically as compared to the control polymer (without plasma treatment). PCE of the control polymer was found to be 4.11%, while after air, Ar and N2 gas plasma treatment the polymer showed PCEs of 4.85%, 4.87% and 5.14% respectively. Thus, plasma treatment not only alters the surface properties, but also modifies the bulk properties (changes in HOMO and LUMO bandgap level). Hence, this work provides new dimensions to explore more about plasma and polymer chemistry.

In this study, we developed a 3D-model-based technology that can evaluate solar access by analyzing solar radiation and shade to find the optimal location for a solar system. We developed an algorithm that can quickly calculate viewshed by applying ray-casting technology, which is useful in the field of computer graphics. To apply the developed technology, an unmanned aerial vehicle (DJI MAVIC 3) was used to create a 3D model by taking 320 photos of the Kangwon National University Samcheok campus. To verify the developed technology, a comparison with image-based analysis using a 360-degree camera was performed for 30 points. As a result of applying the developed technology to the study area, it was possible to calculate the solar access for each point. In general, image-based analysis exaggerates the effects of objects such as trees, whereas the developed technique can produce realistic results if the 3D objects were well built. If the technology is further developed in the future, it can be used to increase the efficiency of solar power generation.

Nowadays, wave energy plays an important role in renewable energy resource. In over thirty years, researches in wave energy converter system (WEC) have been deployed and carried out. This paper presents a design of wave energy converter using 5 cylinders combining with hydraulic power take-off system in order to convert the mechanical energy from ocean wave to electricity, or another useful and usable source. The WEC uses ordered 5 cylinders to represent the motion of the floating buoy under the wave elevation. The design and specification of the WEC system are presented. Buoy and wave interaction mathematical model is built and the hydraulic mathematical model is also presented. The system performance test is implemented and the result is shown.

The Energy Information Administration (EIA) of the U.S. Department of Energy has projected net electricity generation through 2040 for ten selected countries and the world. These ten countries including China and the U.S. are projected to produce 70% of the world electricity generation. Some of the past projections by EIA have been rated too conservative. Using a simple experience curve, we produce alternative projections for comparison. Our projections are significantly higher for eight out of the ten countries. Utilities operating in these eight countries may need to reexamine their plan for future net electricity generation.

Abstract A polymer-based flexible pulsating heat pipe (FPHP) as a flexible heat spreader was developed, and a series of experiments were conducted to evaluate the thermal performance and the long-term reliability of the FPHP. The FPHP consisted of a multilayer laminated film and a low-density polyethylene (LDPE) sheet. HFE-7000 was used as the working fluid, and the width, length, and thickness of the FPHP were 53.4 mm, 85.5 mm, and 1 mm, respectively. To minimize the permeation of non-condensable gases (NCGs) in a lateral direction, the heat-sealed flanges were covered with the indium coating. Owing to the indium-coated flanges, the long-term reliability of the FPHP drastically increased. The lifetime of the FPHP was defined to evaluate the long-term reliability. The FPHP had a lifetime of 18.2 days in the acceleration test environment, which was equivalent to 306 days in a standard atmosphere and 17 times longer than the previous polymer-based PHP. The FPHP had the thermal resistance of 2.41 K/W, which is 37% lower than that of the copper reference sample in a vertical orientation. Under bending conditions as well as in a horizontal orientation, the FPHP still operated well as a PHP, but the thermal resistance increased slightly. The fabrication method of the FPHP is effective in minimizing the permeation of NCGs in a lateral direction and can pave the way for fabricating a thin flexible heat spreader that has high flexibility, high thermal performance, and long-term reliability.