Estimation of research reactor core parameters using cascade feed forward artificial neural networks

The pattern of the core reload program is very important for an optimize use of research reactors. Reactor safety issues and economic efficiency should be considered during pattern studies. In order to find the best core pattern for a research reactor, its reloading program should be solved as a multi-objective and constrained optimization problem. If considered objective functions of the optimization problem can be estimated in very short time, the optimal fuel reloading pattern can be used effectively. In this research a very fast estimation system for suggested core parameters has been developed using cascade feed-forward type of artificial neural networks (ANNs). Four main core parameters are suggested to optimize reactor core adequately. And also to get larger thermal fluxes in the desired irradiation box, a new flexible method was selected. A Software package has been developed to prepare and reform required data for ANNs training. The gradient descent method with momentum weight/bias learning rule has been used to train ANNs. To get the best conditions for considered ANNs training a vast study has been performed. It includes the effects of variation of hidden neurons, hidden layers, activation functions, learning and momentum coefficients, and also the number of training data sets on the training and simulation results. Some experimental convergence criteria are used to study them. A comparison selection rule has been used to adjust desirable conditions. Final training and simulation results show that developed ANNs can be trained and estimate suggested core parameters of research reactors very quickly. It improves effectively pattern optimization process of core reload program.     

QSAR Study of Antimicrobial 3-Hydroxypyridine-4-one and 3-Hydroxypyran-4-one Derivatives Using Different Chemometric Tools

A series of 3-hydroxypyridine-4-one and 3-hydroxypyran-4-one derivatives were subjected to quantitative structure-antimicrobial activity relationships (QSAR) analysis. A collection of chemometrics methods, including factor analysis-based multiple linear regression (FA-MLR), principal component regression (PCR) and partial least squares combined with genetic algorithm for variable selection (GA-PLS) were employed to make connections between structural parameters and antimicrobial activity. The results revealed the significant role of topological parameters in the antimicrobial activity of the studied compounds against S. aureus and C. albicans. The most significant QSAR model, obtained by GA-PLS, could explain and predict 96% and 91% of variances in the pIC₅₀ data (compounds tested against S. aureus) and predict 91% and 87% of variances in the pIC₅₀ data (compounds tested against C. albicans), respectively.     

An analysis of carbone monoxide distribution in large tunnel fires

Fire events and the related toxicants such as CO are responsible for many fatalities in the current century. These hazardous events are much more dangerous when they occur in enclosed spaces. In the present study, a theoretical relation is developed for horizontal distribution of CO in a large tunnel fire. Then, the developed criterion is used to study the effect of some rudimentary parameters such as the heat release rate (HRR) of fire and tunnel’s aspect ratio (AR) on CO and temperature stratification. Theoretical results of various heat release rates and aspect ratios for horizontal distribution of CO are compared with numerical results using fire dynamics simulator (FDS5.5). It is found that big fires have higher rates of CO concentration decay in comparison to the smaller ones due to higher air entrainment into the travelling plume. It is indicated that the smoke travelling at higher values of tunnel AR, dilutes faster. Moreover, using FDS5.5, the relevant variations in temperature and CO concentration are discussed for tunnel angles ranging from ?20° to 20°.     

Using the third-order shear deformation theory to examine magnetic-mechanical buckling of a two-dimensional functionally graded cylindrical panel with longitudinal and circumferential stiffeners

In this study, the magnetic-mechanical buckling of a cylindrical panel made of two-dimensional functionally graded materials (2D-FGMs) has been investigated. The panel contains longitudinal and circumferential stiffeners and has been subjected to a uniform magnetic field as well as axial load. Material properties of the cylindrical panel are assumed to vary continuously in radial and thickness directions as a function of the volume fraction of the components. The magnetic field has been exerted radially. Equilibrium and stability equations have been derived using both Hamilton's principle and principle of minimum potential energy based on the third-order shear deformation theory (TSDT). The generalized differential quadrature method (GDQ) has been employed to solve the coupled differential equations. Moreover, the effect of geometry, load, magnitude of the magnetic field, number of stiffeners, and volume fraction coefficient on the critical buckling load has been determined. The results are in good agreement with the previous related works.     

Correlating Isothermal Friction Factor Data for Micro-Fin Tubes Using Logistic Dose-Response Curve Fitting Method

Simultaneous heat transfer and friction factor experiments for plain and micro-fin tubes were conducted in our previous study. The results showed that the heat transfer characteristics of the micro-fin tubes were the same as for the plain tube. However, the friction factor characteristics of the micro-fin tubes in the transition region were different compared to the plain tube. This type of friction factor data cannot be easily correlated by the traditional regression method. Therefore, a logistic dose-response curve-fitting method is proposed in this study. This particular method has recently been used by other researchers in correlating the friction factor data in plain tubes. In this study, three sets of micro-fin tubes friction factor data with different inlets from our previous study were correlated by the logistic dose-response curve-fitting method. All the fully developed friction factor data for the entire flow regime were predicted by a composite logistic dose-response function within ±11% deviation. The majority of the data (over 85%) was predicted with less than ±5% deviation.     

Economic impacts and challenges of China’s petroleum industry: An input–output analysis

It is generally acknowledged that the petroleum industry plays an important role in China’s national economic and social development. The direct, indirect, and induced impacts of China’s petroleum industry are analyzed in this study by using the Input-Output approach. The study also considers the main challenges that China’s economy might face in the future. The research results suggest the following: (1) The total economic impacts coefficients on output, given each unit of final demands change in extraction of petroleum and processing of petroleum, are 1.9180 and 3.2747 respectively, and the corresponding economic impacts coefficients on GDP are 1.0872 and 0.9001 respectively; (2) Extraction of petroleum has a more direct impact on GDP, while processing of petroleum has a greater effect on the total output; (3) Extraction of petroleum’s total economic impacts coefficients on both output and GDP have remained stable in recent years after a period of long decline; processing of petroleum’s total economic impacts coefficient on output is steadily increasing; (4) Import uncertainty, the likelihood of rising oil prices, and net oil exports caused by items manufactured with petroleum products (i.e. “Made in China” goods) are the main challenges the petroleum industry will cause for China’s overall economy.     

<Emphasis Type="Italic">Borago officinalis</Emphasis> L. flower: a comprehensive study on bioactive compounds and its health-promoting properties

The herbal plant Borago officinalis L. flower were analysed for its bioactive compounds and antioxidant, antibacterial, anti-inflammatory and anticancer activities using different solvent polarities (methanol, ethanol and water). The RP-HPLC analyses of the methanolic extract confirmed the presence of phenolics (gallic acid, pyrogallol, salicylic acid, caffeic acid), flavonoids (myricetin, rutin) and isoflavonoid (daidzein). Besides, the major individual fatty acids of methanolic extract were α-linolenic, stearidonic, palmitic, linoleic and γ-linolenic acids. The methanolic extract possessed the highest antioxidant properties as compared to the ethanolic and water extracts. The flower methanolic, ethanolic and water extracts showed high, moderate and weak antibacterial activities against common human and foodborne pathogenic bacteria, respectively. Furthermore, the flower extracts showed weak anti-inflammatory in murine RAW 264.7 macrophage cells and low anticancer properties against human hepatic, prostate and colon cancer cells. This high-value flower could be considered as a source of putative antioxidant and antibacterial compounds to improve the human health and to be used as biopreservative in food and cosmetic industries.