Evaluation of the impact of the surrounding urban morphology on building energy consumption

Empirical models of minimum (T_min), average (T_avg) and maximum (T_max) air temperature for Singapore estate have been developed and validated based on a long-tem field measurement. There are three major urban elements, which influence the urban temperature at the local scale. Essentially, they are buildings, greenery and pavement. Other related parameters identified for the study, such as green plot ratio (GnPR), sky view factor (SVF), surrounding building density, the wall surface area, pavement area, albedo are also evaluated to give a better understanding on the likely impact of the modified urban morphology on energy consumption.The objective of this research is to assess and to compare how the air temperature variation of urban condition can affect the building energy consumption in tropical climate of Singapore. In order to achieve this goal, a series of numerical calculation and building simulation are utilized. A total of 32 cases, considering different urban morphologies, are identified and evaluated to give better a understanding on the implication of urban forms, with the reference to the effect of varying density, height and greenery density. The results show that GnPR, which related to the present of greenery, have the most significant impact on the energy consumption by reducing the temperature by up to 2 °C. The results also strongly indicate an energy saving of 4.5% if the urban elements are addressed effectively.     

Adaptive Power Control Scheme for Mobile Wireless Sensor Networks

Wireless Personal Communications - One of the major factors that affects the performance of wireless sensor networks (WSN) is its limited battery capacity. Mobile wireless sensor networks (MWSN)...     

Extruded/injection‐molded composites containing unripe plantain flour,ethylene–vinyl alcohol,and glycerol: Evaluation of mechanical property,storage conditions,biodegradability, and color

Extruded/injection‐molded composites of excellent mechanical property were produced from plantain flour (PF) blended with ethylene–vinyl alcohol (EVA) and glycerol. Scanning electron microscopy (SEM) revealed that composites had a smooth surface, indicative of an excellent compatibility between PF, EVA, and glycerol. Generally, tensile strength (TS), elongation at break (%E), and the displacement (DM), all decreased with increased PF content in the composite accompanied by an increase in Young's modulus (M). The composites with higher PF contents (60% or higher) had more stable mechanical properties. Selected composites (60% PF content) stored at ?20°C and 4°C for 40 h showed only minor changes in mechanical properties compared with controls (23°C). However, samples stored for a similar period at 80°C were drastically altered in their mechanical properties resulting in huge increases in TS and M and a 10‐fold decrease in the %E. Samples prestored at various relative humidities (RHs) for 40 h exhibited only slight decrease in TS and M and a concomitant increase in the %E with increased RH. Interestingly, sample prestored at both ?20°C and 80°C exhibited significantly higher rates and extents of degradation. SEM analysis of samples left in compost for 8 weeks showed a rapid surface erosion and material deterioration with time. Evaluation of the color produced during heat processing of starch in PF as a result of Maillard reaction showed an increase in the values of luminosity (L*), chroma (C*), and hue angle (h*) with decreased PF content in the composite. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2012     

Reinforcing Epoxy Polymer Composites Through Covalent Integration of Functionalized Nanotubes

Strong interfacial bonding and homogenous dispersion have been found to be necessary conditions to take full advantage of the extraordinary properties of nanotubes for reinforcement of composites. We have developed a fully integrated nanotube composite material through the use of functionalized single‐walled carbon nanotubes (SWNTs). The functionalization was performed via the reaction of terminal diamines with alkylcarboxyl groups attached to the SWNTs in the course of a dicarboxylic acid acyl peroxide treatment. Nanotube‐reinforced epoxy polymer composites were prepared by dissolving the functionalized SWNTs in organic solvent followed by mixing with epoxy resin and curing agent. In this hybrid material system, nanotubes are covalently integrated into the epoxy matrix and become part of the crosslinked structure rather than just a separate component. Results demonstrated dramatic enhancement in the mechanical properties of an epoxy polymer material, for example, 30–70 % increase in ultimate strength and modulus with the addition of only small quantities (1–4 wt.‐%) of functionalized SWNTs. The nanotube‐reinforced epoxy composites also exhibited an increased strain to failure, which suggests higher toughness.     

Learning decision trees from decision rules: A method and initial results from a comparative study

A standard approach to determining decision trees is to learn them from examples. A disadvantage of this approach is that once a decision tree is learned, it is difficult to modify it to suit different decision making situations. Such problems arise, for example, when an attribute assigned to some node cannot be measured, or there is a significant change in the costs of measuring attributes or in the frequency distribution of events from different decision classes. An attractive approach to resolving this problem is to learn and store knowledge in the form of decision rules, and to generate from them, whenever needed, a decision tree that is most suitable in a given situation. An additional advantage of such an approach is that it facilitates buildingcompact decision trees, which can be much simpler than the logically equivalent conventional decision trees (by compact trees are meant decision trees that may contain branches assigned aset of values, and nodes assignedderived attributes, i.e., attributes that are logical or mathematical functions of the original ones). The paper describes an efficient method, AQDT-1, that takes decision rules generated by an AQ-type learning system (AQ15 or AQ17), and builds from them a decision tree optimizing a given optimality criterion. The method can work in two modes: thestandard mode, which produces conventional decision trees, andcompact mode, which produces compact decision trees. The preliminary experiments with AQDT-1 have shown that the decision trees generated by it from decision rules (conventional and compact) have outperformed those generated from examples by the well-known C4.5 program both in terms of their simplicity and their predictive accuracy.     

Maximum power tracking control for a wind energy conversion system based on a quasi‐ARX neural network model

By itself, a wind turbine is already a fairly complex system with highly nonlinear dynamics. Changes in wind speed can affect the dynamic parameters of wind turbines, thus rendering the parameters uncertain. However, we can identify the dynamics of the wind energy conversion system (WECS) online by a quasi‐ARX neural network (QARXNN) model. A QARXNN presents a problem in searching for the coefficients of the regression vector (input vector). A multilayer perceptron neural network (MLPNN) is an embedded system that provides the unknown parameters used to parameterize the input vector. Fascinatingly, the coefficients of the input vector from prediction model can be set as controller parameters directly. The stability of the closed‐loop controller is guaranteed by the switching of the linear and nonlinear parts of the parameters. The dynamic of WECS is derived with given parameters, and then a wind speed signal created by a random model is fed to the system causing uncertainty parameters and reducing the power that can be absorbed from wind. By using a minimum variance controller, the maximum power is tracked from WECS. From the simulation results, it is observed that the proposed controller is effective in tracking the maximum power of WECS. © 2015 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Synthesis and application of p-tert-butylcalix[8]arene immobilized material for the removal of azo dyes

The present study describes synthesis of a new resin through immobilization of p-tert-butylcalix[8]arene onto silica and its application for the removal of azo dyes from aqueous media as well as from textile effluents. The newly synthesized material 4 is characterized by FT-IR spectroscopy, scanning electron microscope (SEM) and thermogravimetric analysis (TGA). Reactive Black-5 (RB-5) and Reactive Red-45 (RR-45) azo dyes were used as sorbate. Batch wise sorption experiments were conducted to optimize various experimental parameters such as the effect of sorbent dosage, electrolyte, pH, dye concentration, and contact time. The optimized pH for the effective removal of RB-5 and RR-45 dyes was 9 and 3, respectively. The increase in material 4 dosage increased the percent sorption. Both Langmuir and Freundlich isotherm models were applied to experimental data and Langmuir isotherm model found to be best fit. The results revealed that material 4 was potentially more effective sorbent for the sorption of selected azo dyes as compared to pure silica and p-tert-butylcalix[8]arene. The field studies also supported the effectiveness of material 4, which could be useful for the removal of both the dyes and also for the normalization of pH, TDS, conductivity and salinity near to the drinking water.