Propulsion Performance of Spanwise Flexible Wing Using Unsteady Panel Method

In this paper, the propulsion performance of a spanwise flexible oscillating wing, which is broadly similar to the undulation of a fin fluke, is investigat     

Germination and seedling growth of corn (Zea mays l.) under varying levels of copper and zinc

The heavy metal tolerance in corn (Zea mays L.) var. ‘Neelum’ was assessed at germination and seedling growth after having subjected it to different concentrations of CuSO₄ and ZnSO₄. Germination was not affected by any of the metal tested, whereas initial growth was strongly inhibited by increasing concentrations of ZnSO₄. Seedlings developed toxicity symptoms in the presence of both metals but more chlorotic and necrotic regions were observed at varying levels of ZnSO₄ than CuSO₄. The metal accumulation was concentration dependent. Z. mays seedlings accumulated more copper in roots but greater contents of zinc in their shoots. On the basis of results presented here, it can be concluded that the cultivar of the species tested has shown a marked sensitivity to the presence of small amounts of metals present in the growth medium. The data support the assumption that metal sensitivity is probably due to strong tendency of the species to accumulate them. This justifies that the corn variety ‘Neelum’ is not suitable for the cultivation under situations where water and soil suffer from occasional and/ or transitory metal pollution.     

Isotopically Enriched Geogenic δ81Br and δ37Cl: Primary Evidence for the Ascending Brine Model

Mass balance calculations and hydrodynamics of groundwater flow suggest that the solutes in brines of the coastal sabkha aquifer from the Emirate of Abu Dhabi are derived largely from ascending geologic brines into the sabkha from the underlying formations. Solute interpretation for the ascending brine model (ABM) was based on two independent but secondary lines of evidence (solute ratios and solute fluxes). In the current study, direct primary evidence for this ABM was provided through analyses of δ⁸¹Br, δ³⁷Cl, and ⁸⁷Sr/⁸⁶Sr. Different solute histories of geologic brine and sea water provide an “isotopic fingerprint” that can uniquely distinguish between the two possible sources. Samples from the coastal sabkha aquifer of Abu Dhabi were determined to have a mean δ⁸¹Br of 1.17‰ that is statistically equal, at the 95% confidence level, to the mean of 1.11‰ observed in the underlying geologic brine and statistically different than sea water. Similarly, the δ³⁷Cl in sabkha brine has a mean of 0.25‰ and is statistically equal to a mean of 0.21‰ in the underlying geologic brines at the 95% confidence level and statistically different from sea water. Also, dissolved strontium isotope data are consistent with the ABM and even with the complex set of processes in the sabkha, the variance in strontium isotope results is similar to the geologic brine. These observations provide primary direct evidence consistent that the major source of these solutes (and presumably others in the aquifer) is from discharging geologic brines, not from adjacent sea water.     

Estimation of coda and shear wave attenuation in the volcanic area in SE Sabalan Mountain,NW Iran

The quality factors of coda and shear waves have been estimated for the SE Sabalan Mountain, geothermal region in northwestern Iran. We have analyzed 65 local earthquakes with magnitude of 2.8 to 6.1 and 2.8 to 5 for shear and coda wave quality factor estimation, respectively. These events were recorded on five stations installed by Building and Housing Research Center Network. Coda normalization and Spectral decay methods have been used to estimate the frequency dependence attenuation relation for shear wave, and single back-scattering method for coda waves. We have observed that the coda normalization method has supplied significantly higher Q _S values as compared to the spectral method. The results show that, in general, Q values are significantly smaller for the entire frequency range as compared to tectonically active areas and are close to the values for volcanic areas.     

Metamorphosis of marine organic matter in the jurassic deposits from Sharab area,Taiz Governorate of southwestern Yemen: Thermal effect of tertiary volcanic rocks

The Tertiary volcanic rocks are widely exposed in the Sharab area of Taiz Governorate, southwestern Yemen. The Jurassic calcareous shale and black limestone deposits collected closely to theTertiary volcanic rocks were investigated to provide information regarding the thermal effects of Tertiary volcanic rocks on organic materials. The bulk geochemical results indicate that the analysed Jurassic deposits are organically lean with present-day TOC values less than 0.95% and very low HI values (< 50 mg HC/g TOC), with a predominantly Type IV kerogen (inert carbon). This is attributed to thermal effect on the original organic matter as indicated by high thermal maturity data, consistent with post-mature to metagenesis stage. The present study also suggests that the high thermal maturity of the Jurassic marine deposits is due to the presence of the alkali basalts which have invaded the Jurassic rocks during late Oligocene to early Miocene (~10 Ma). Thus, the heat flow caused by Tertiary basaltic rocks further increased the temperature level and led to metamorphosis of organic matter and converted it to graphitic materials (inert carbon).     

Application of fuzzy multi-attribute decision-making to select and to rank the post-mining land-use

The selection of an optimal reclamation method is one of the most important portions of the surface mining design. There are many factors in this problem which seriously influence decision-making. The fuzzy set theory was applied due to the effect of uncertain parameters involved in the decision-making process. Therefore, the fuzzy multi-attribute decision-making method was proposed. The aim of this study is to use the fuzzy technique for order preference by similarity to ideal solution method for ranking the optimal post-mining land-use and the fuzzy analytic hierarchy process method in order to determine the weights of each criterion. This approach is applied to the surface coal mine by employing 28 criteria which influence the decision-making procedure. The TOPSIS and AHP methods have been the most used methods of mining decision-making and demonstrated their ability to make critical decisions. By evaluating the alternatives and considering effective criteria with proposed methods, agriculture is the optimal post-mining land-use.     

Prediction of river flow using hybrid neuro-fuzzy models

The complex nature of hydrological phenomena, like rainfall and river flow, causes some limitations for some admired soft computing models in order to predict the phenomenon. Evolutionary algorithms (EA) are novel methods that used to cover the weaknesses of the classic training algorithms, such as trapping in local optima, poor performance in networks with large parameters, over-fitting, and etc. In this study, some evolutionary algorithms, including genetic algorithm (GA), ant colony optimization for continuous domain (ACO_R), and particle swarm optimization (PSO), have been used to train adaptive neuro-fuzzy inference system (ANFIS) in order to predict river flow. For this purpose, classic and hybrid ANFIS models were trained using river flow data obtained from upstream stations to predict 1-, 3-, 5-, and 7-day ahead river flow of downstream station. The best inputs were selected using correlation coefficient and a sensitivity analysis test (cosine amplitude). The results showed that PSO improved the performance of classic ANFIS in all the periods such that the averages of coefficient of determination, R², root mean square error, RMSE (m³/s), mean absolute relative error, MARE, and Nash-Sutcliffe efficiency coefficient (NSE) were improved up to 0.19, 0.30, 43.8, and 0.13%, respectively. Classic ANFIS was only capable to predict river flow in 1-day ahead while EA improved this ability to 5-day ahead. Cosine amplitude method was recognized as an appropriate sensitivity analysis method in order to select the best inputs.     

FuzzyKrig: a comprehensive matlab toolbox for geostatistical estimation of imprecise information

Using kriging has been accepted today as the most common method of estimating spatial data in such different fields as the geosciences. To be able to apply kriging methods, it is necessary that the data and variogram model parameters be precise. To utilize the imprecise (fuzzy) data and parameters, use is made of fuzzy kriging methods. Although it has been 30 years since different fuzzy kriging algorithms were proposed, its use has not become as common as other kriging methods (ordinary, simple, log, universal, etc.); lack of a comprehensive software that can perform, based on different fuzzy kriging algorithms, the related calculations in a 3D space can be the main reason. This paper describes an open-source software toolbox (developed in Matlab) for running different algorithms proposed for fuzzy kriging. It also presents, besides a short presentation of the fuzzy kriging method and introduction of the functions provided by the FuzzyKrig toolbox, 3 cases of the software application under the conditions where: 1) data are hard and variogram model parameters are fuzzy, 2) data are fuzzy and variogram model parameters are hard, and 3) both data and variogram model parameters are fuzzy.