Experimental Thermal Performance Characterization of Flat Grooved Heat Pipes

ABSTRACT

The thermal characterization of aluminum flat grooved heat pipes is performed experimentally for different groove dimensions. Three heat pipes with groove widths of 0.2?mm, 0.4?mm, and 1.5?mm are used in the experiments. The effect of the amount of the working fluid is extensively studied for each groove width. The results reveal that, although all three succeed in dissipating the heat input through the phase change of the working fluid by continuous evaporation and condensation, the effectiveness of the heat transfer increases with reduced groove width. Furthermore, it is observed that there exists an optimum operating point, where the temperature difference between the heating and cooling sections is at a minimum, and the magnitude of this temperature difference is a strong function of the groove width. To the best of the authors’ knowledge, the combined effects of groove dimensions and the amount of the working fluid, from fully flooded to dry, is reported for the first time for aluminum flat grooved heat pipes.     

Evaluation of deflection amplification factor in steel moment‐resisting frames

Steel moment‐resisting frames (SMRFs) are the most common type of structural systems used in steel structures. The first step of structural design for SMRFs starts with the selection of the structural sections on the basis of story drift limitation. ASCE 7 (2010) requires that the inelastic story drifts be obtained by multiplying the deflections determined by elastic analysis under design earthquake forces with a deflection amplification factor (C_d). For special moment‐resisting frames, C_d is given as 5.5 in ASCE 7 (2010). Lower C_d values will increase the overall inelastic response of the structure. On the other hand, the inelastic response of the structure is expected to be less severe when designed for higher C_d values. The performance objective is that the structure should sustain the inelastic deformation demand imposed due to design earthquake ground motions. This study aims at investigating the inelastic seismic response that low‐rise, medium‐rise and high‐rise SMRFs can experience under design earthquake ground motions and maximum considered earthquake (MCE) level ground motions and evaluating the deflection amplification factors (C_d) for SMRFs in a rational way. For this purpose, nonlinear dynamic time history and pushover analyses will be carried out on SMRFs with 4, 9 and 20 stories. The results indicate that the current practice for computing the inelastic story drifts for SMRFs is rational and the frames designed complying with the current code requirements can sustain the inelastic deformations imposed during design earthquake ground motions when seismically designed and detailed. Copyright © 2013 John Wiley & Sons, Ltd.     

Identification of Components of the Aggregation Pheromone of the Guam Strain of Coconut Rhinoceros Beetle,Oryctes rhinoceros,and Determination of Stereochemistry

The coconut rhinoceros beetle, Oryctes rhinoceros (Linnaeus 1758) (Coleoptera: Scarabaeidae: Dynastinae) (CRB), is endemic to tropical Asia where it damages both coconut and oil palm. A new invasion by CRB occurred on Guam in 2007 and eradication attempts failed using commonly applied Oryctes rhinoceros nudivirus (OrNV) isolates. This and subsequent invasive outbreaks were found to have been caused by a previously unrecognized haplotype, CRB-G, which appeared to be tolerant to OrNV. The male-produced aggregation pheromone of the endemic, susceptible strain of O. rhinoceros (CRB-S) was previously identified as ethyl 4-methyloctanoate. Following reports from growers that commercial lures containing this compound were not attractive to CRB-G, the aim of this work was to identify the pheromone of CRB-G. Initial collections of volatiles from virgin male and female CRB-G adults from the Solomon Islands failed to show any male- or female-specific compounds as candidate pheromone components. Only after five months were significant quantities of ethyl 4-methyloctanoate and 4-methyloctanoic acid produced by males but not by females. No other male-specific compounds could be detected, in particular methyl 4-methyloctanoate, 4-methyl-1-octanol, or 4-methyl-1-octyl acetate, compounds identified in volatiles from some other species of Oryctes. Ethyl 4-methyloctanoate elicited a strong electroantennogram response from both male and female CRB-G, but these other compounds, including 4-methyloctanoic acid, did not. The enantiomers of ethyl 4-methyloctanoate and 4-methyloctanoic acid were conveniently prepared by enzymatic resolution of the commercially-available acid, and the enantiomers of the acid, but not the ester, could be separated by gas chromatography on an enantioselective cyclodextrin phase. Using this approach, both ethyl 4-methyloctanoate and 4-methyloctanoic acid produced by male CRB-G were shown to be exclusively the (R)-enantiomers whereas previous reports had suggested male O. rhinoceros produced the (S)-enantiomers. However, re-examination of the ester and acid produced by male CRB-S from Papua New Guinea showed that these were also the (R)-enantiomers. In field trapping experiments carried out in the Solomon Islands, both racemic and ethyl (R)-4-methyloctanoate were highly attractive to both male and female CRB-G beetles. The (S)-enantiomer and the corresponding acids were only weakly attractive. The addition of racemic 4-methyloctanoic acid to ethyl 4-methyloctanoate did significantly increase attractiveness, but the addition of (R)- or (S)-4-methyloctanoic acid to the corresponding ethyl esters did not. Possible reasons for the difference in assignment of configuration of the components of the CRB pheromone are discussed along with the practical implications of these results.

     

Ternary encoding based feature extraction for binary text classification

A novel framework for termset based feature extraction is proposed for binary text classification. The proposed approach is based on the encoding of the terms within a termset. The ternary codes ‘+1’ and ‘?1’ are used to represent the class that the term supports, whereas ‘0’ denotes no support to any of the classes. Four different encoding schemes are proposed where the term weights and the term occurrence probabilities in the positive and negative documents are used to define the ternary code of a given term. The ternary patterns are utilized to define novel features by splitting them into positive and negative codes where each code is treated as a different feature extractor. Use of the derived features individually and together with bag of words representation are both investigated. The histograms of the resultant features are also employed to study the improvements that can be achieved using a small number of additional features to augment bag of words representation. Experiments conducted on four benchmark datasets with different characteristics have shown that the proposed feature extraction framework provides significant improvements compared to the bag of words representation.     

Nonlinear transformation of term frequencies for term weighting in text categorization

In automatic text categorization, the influence of features on the decision is set by the term weights which are conventionally computed as the product of term frequency and collection frequency factors. The raw form of term frequencies or their logarithmic forms are generally used as the term frequency factor whereas the leading collection frequency factors take into account the document frequency of each term. In this study, it is firstly shown that the best-fitting form of the term frequency factor depends on the distribution of term frequency values in the dataset under concern. Taking this observation into account, a novel collection frequency factor is proposed which considers term frequencies. Five datasets are firstly tested to show that the distribution of term frequency values is task dependent. The proposed method is then proven to provide better F₁ scores compared to two recent approaches on majority of the datasets considered. It is confirmed that the use of term frequencies in the collection frequency factor is beneficial on tasks which does not involve highly repeated terms. It is also shown that the best F₁ scores are achieved on majority of the datasets when smaller number of features are considered.