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Abstract The South Korean government has been actively promoting an educational-facility improvement program as part of its energy-saving efforts. This research seeks to develop a decision support model for selecting the facility expected to be effective in generating energy savings and making the facility improvement program more effective. In this research, project characteristics and electric-energy consumption data for the year 2009 were collected from 6282 elementary schools located in seven metropolitan cities in South Korea. In this research, the following were carried out: (i) a group of educational facilities was established based on electric-energy consumption, using a decision tree; (ii) a number of similar projects were retrieved from the same group of facilities, using case-based reasoning; and (iii) the accuracy of prediction was improved, using the combination of genetic algorithms, the artificial neural network, and multiple regression analysis. The results of this research can be useful for the following purposes: (i) preliminary research on the systematic and continuous management of educational facilities’ electric-energy consumption; (ii) basic research on electric-energy consumption prediction based on the project characteristics; and (iii) practical research for selecting an optimum facility that can more effectively apply an educational-facility improvement program as a decision support model.

Nanosize copper embedded in the inert carbon shell (Cu@C) prepared by carbonization of Cu2+-β-CD at 573 K was dispersed in TiO2. The Cu@C (0.1% and 0.3%) dispersed TiO2 was used in assembling of photoanodes for dye-sensitized solar cells (DSSCs). By small angle X-ray scattering (SAXS) spectroscopy, it is found that the Cu@C dispersed TiO2 having an average Cu diameter of 18.3 nm and carbon shell thickness of 3–5 nm. Larger Cu nanoparticles having an average diameter of 24.5 nm in TiO2 was formed when their carbon shells were steam reformed at 673 K. The Cu nanoparticles having a spherical shape are well dispersed in TiO2, which significantly enhance the photo-excited electron transfer for the DSSC. Notably, the Cu dispersed TiO2 photoanode has a greater efficiency than the pure TiO2 one by at least 23%. This work exemplifies a simple and novel alternative to enhance DSSC efficiencies.

Abstract A high heat storage capacity form-stable composite phase change material (CPCM) with enhanced flame retardancy that integrated modified glass fibers with form-stable PCM was proposed. The modified glass fibers were wrapped by a composite flame retardant coating. The thermal and flame retardant properties of the CPCM were measured and compared to other CPCM samples. The results of vertical burning test indicated that the glass fibers improved the mechanical properties of the CPCM and prevented it from fracturing during the burning process. The modified glass fibers could further improve the flame retardancy of CPCM, and V-0 burning rating was achieved while the content of paraffin was maintained at 70 wt%, which means the proportion of flame retardants could be reduced. TGA results showed that the modified glass fibers could enhance the thermal stability and retard the degradation process of the CPCM, and the char residue was increased to 15.3%. Thermal cycling results indicated that the CPCM has good thermal reliability. The results of cone calorimeter test indicated that the peak heat release rate (PHRR) of flame retardant form-stable CPCM dropped by 58.8%, and the combustion rate could be greatly slowed down due to the protection of carbon layers formed by modified glass fibers. In addition, the thermal conductivity of CPCMs were greatly enhanced and the CPCM has good thermal reliability.

Abstract This paper discusses the minimization of the fuel consumption of a gasoline engine through dynamic optimization. The minimization uses a mean value model of the powertrain and vehicle. This model has two state variables: the pressure in the engine intake manifold and the engine speed. The control input is the throttle valve angle. The model is identified on a universal engine dynamometer. Optimal state and control trajectories are calculated using Bock’s direct multiple shooting method, implemented in the software MUSCOD-II. The developed approach is illustrated both in simulation and experimentally for a generic test case where a vehicle accelerates from 1100 rpm to 3700 rpm in 30 s . The optimized trajectories yield minimal fuel consumption. The experiments show that a linear engine speed trajectory yields an extra fuel consumption of 13 % when compared to the optimal trajectory. It is shown that, with a simple model, a significant amount of fuel can be saved without loss of the fun-to-drive.

Abstract Steady-state free and forced convective cooling of vertical, rectangular, 3 mm thick, 250 mm long fins, uniformly separated and protruding vertically upwards from a 250 mm × 190 mm isothermal horizontal base was investigated. For each combination of specified fin protrusion, horizontal forced air flow-rate in the direction along the fins and fin base temperature, the optimal fin spacing—corresponding to the maximum rate of heat loss—has been deduced. As the fin protrusion of the heat exchanger increases, this optimal value rises significantly in forced convection conditions, but declines slightly in the presence of free convection alone. The temperature distributions over the fins' surfaces were also studied, when the fin base was maintained at constant temperatures of either 40°C, 60°C or 80°C above that of the ambient environment. Large temperature depressions occurred near the leading edges and tips of the fins in forced convection, whereas much nearer isothermal temperature distributions were present under free convection conditions.

Abstract In recent years, solar steam generation has attracted many attentions due to its potential applications in desalination, etc. In the present work, a bi-layer solar steam generation system is prepared by daubing carbon particles on the sintered sawdust film, which possesses an advantage of adjustable porosities compared to widely used wood. Then, the influence of the porosity on the evaporation performance is explored. The experimental result indicates that: the porosity could significantly affect the water transportation in the film, and the water diffusivity increases almost linearly with the increase of the porosity. The evaporation efficiency increases with the increasing porosity, until the porosity reaches about 0.52 then decrease slowly. The positive effect of the increased water diffusivity and the negative effect of the increased thermal conductivity of the bottom film layer determine that the porosity of 0.52 is optimal for improving the evaporation efficiency. Under a solar light power of 1 kW·m−2, the optimal porosity gives an evaporation efficiency of 77.64%, which is comparable to the best performance of bi-layer systems reported in previous works. The conduction of heat through the bottom layer to the bulk water and the convection heat loss on the top surface contribute 83% to the total heat losses in the system, suggesting that the energy losses of these two modes should be further reduced in the future applications. Considering the accessible materials, easy preparation, low cost and high efficiency, we conclude that the 0.52-porosity system is suitable for being used as an efficient solar steam generation device.

Abstract To enhance prediction accuracy and reduce computation complexity, a decomposition–ensemble methodology with data-characteristic-driven reconstruction is proposed for crude oil price forecasting, based on two promising principles of “divide and conquer” and “data-characteristic-driven modeling”. Actually, this proposed model improves the existing decomposition–ensemble techniques in the “divide and conquer” framework, by formulating and incorporating a data-characteristic-driven reconstruction method based on the “data-characteristic-driven modeling”. Four main steps are involved in the proposed methodology, i.e., data decomposition for simplifying the complex data, component reconstruction based on the “data-characteristic-driven modeling” for capturing inner factors and reducing computational cost, individual prediction for each reconstructed component via a certain artificial intelligence (AI) tool, and ensemble prediction for final output. In the proposed data-characteristic-driven reconstruction, all decomposed modes are thoroughly analyzed to explore the hidden data characteristics, and are accordingly reconstructed into some meaningful components. For illustration and verification, the West Texas Intermediate (WTI) and Brent crude oil spot prices are used as the sample data, and the empirical results indicate that the proposed model statistically outperforms all considered benchmark models (including popular AI single models, typical decomposition–ensemble models without reconstruction, and similar decomposition–ensemble models with other existing reconstruction methods), since it has higher prediction accuracy and less computational time.

Abstract With the increasing demand for an environmentally-friendly fluid medium in the fluid-power industries, recent advances in water hydraulics technology have sparked renewed interest in the application of water, instead of oil, as the energy-transmission medium. This paper introduces the history of water hydraulics and its present research. The advantages and disadvantages of water as an energy-transmission medium are discussed. A water-hydraulic system in Nanyang Technological University is introduced.

Abstract The field of energy harvesting holds the promise of making our buildings “smart” if effective energy sources can be developed for use in ambient indoor conditions. Photovoltaics (PV), especially in its thin flexible form for easy integration, become a prime candidate for the aim, if tailored for low-density artificial light. We designed a test system which enabled us to measure the performance of PV devices under compact fluorescent lamp (CFL) and light-emitting diode (LED) illumination at different illuminance levels and compared polycrystalline and amorphous silicon cells with our own flexible dye solar cells (DSCs). Whereas poly-Si cells, with 15% outdoor efficiency, delivered at 200 lux under CFL only 2.8 μW/cm2 power density (and an efficiency of 4.4%), a-Si specifically designed for indoors, gave 5.9 μW/cm2 and 9.2% efficiency under the same CFL conditions (and 7.5% efficiency under LED). However, we show that the customization of flexible DSCs, by simply formulating ad-hoc less-concentrated, more transparent electrolytes, enabled these devices to outperform all others, providing average power densities of 8.0 μW/cm2 and 12.4% efficiencies under 200 lux CFL (more than quadruple compared to those measured at 1 sun), and 6.6 μW/cm2 and 10% efficiency under 200 lux LED illumination.