Showing papers in "International Journal of Physical Sciences in 2011"

Heavy metals contamination of soil and groundwater at automobile mechanic villagesin Ibadan, Nigeria

Abstract: The aim was to determine the concentrations of heavy metals, in soil and groundwater at automobile mechanic villages located in Ibadan, Nigeria, compare the results with guidelines from various countries, draw conclusions and make recommendations. Soil and groundwater samples from 7 automobile mechanic villages and a control site in Ibadan, Nigeria were analysed for selected heavy metals namely: Cd, Cu, Pb, Cr and Ni. Soil samples were obtained in triplicates and at depths of 0 to 15, 15 to 30, 30 to 45 and 45 to 60 cm. Water samples were obtained from dug wells at the sites. Overall, values of Cd, Cu, Pb, Ni and Cr in the workshop soil samples ranged from 0.41 to 17.23; 1.48 to 476.0; 18.25 to 15100; 2.0 to 25.0 and 2.0 to 29.75 mg.kg-1 respectively. Evidence of contamination of these soils was obvious when these values were compared to those of the control. Ni was below detection limit in all control samples while Pb and Cd were less than 0.05 and 0.002 mg.kg-1 respectively. Cu ranged from 4.30 to 10.05 mg.kg-1 while Cr ranged from 6.25 to 19.75 mg.kg-1. Compared to established limits set for soils in some countries, the values measured in this study were higher than these limits in several cases. Compared to the limits set by WHO for drinking water, values measured in the groundwater samples were lower than those limits for the heavy metals with the exception of Cu where all the values were higher than the limits. The recommendations of the study include execution of some form of phyto-remediation measures at the villages; strict compliance to regulatory limits in sludge to be released from these villages into the environment and the enforcement of other environmental protection regulations to arrest the ongoing buildup of these metals on those locations. Findings from this study will be of immense help to researchers and environmental regulators working in this area of interest in developing countries. Key words: Soil, groundwater, lead, cadmium, copper, chromium, nickel.

Thermal stabilizers for poly(vinyl chloride): A review

Abstract: Poly(vinyl chloride) (PVC) is one of the most important commercial plastic materials, but it is thermally unstable at processing temperature. Processing of PVC at elevated temperatures requires the use of thermal stabilizers. Widely used thermal stabilizers for PVC incorporate toxic heavy metal and organo-tin compounds that have been severely criticized based on environmental concern. In order to address this issue, several organic and inorganic compounds that are compatible with the polymer had been investigated. When introduced at relatively low amount, they function as excellent thermal stabilizers for PVC. The compounds function as primary and secondary stabilizers and also as co-stabilizers. These classes of chemical compounds would lead to ideal PVC thermal stabilizers that could be termed “green thermal stabilizers”. Key words: Poly(vinyl chloride), organic stabilizers, inorganic stabilizer, stabilization, thermal stabilizers.

A state of art review of peat: Geotechnical engineering perspective

Abstract: Peat is a type of soft soil composed of high contents of fibrous organic matters and is produced by the partial decomposition and disintegration of mosses, sedges, trees, and other plants that grow in marshes and other wet place in the condition of lack of oxygen. These soils are geotechnically problematic as they show high compressibility and low shear strength. In this paper, the origin of peat and its different engineering properties (moisture content, bulk density, specific gravity, void ratio, permeability, compressibility, shear strength) are discussed in the perspective of a geotechnical engineer. The engineering behavior of peat can be improved by chemical stabilization using sodium silicate grout system, cement stabilization, cement stabilized columns, and fiber reinforcement to name a few. Key words: Peat, compressibility, shear strength, chemical stabilization, fiber reinforcement.

Adaptive neuro-fuzzy inference system based model for rainfall forecasting in Klang River, Malaysia

Abstract: Runoff prediction still represents an extremely important issue in applied hydrology. On the other hand, rainfall is one of the most complicated effective hydrologic processes in runoff prediction. For a developing country such as Malaysia which is prone to flood disaster having such an expert model for runoff forecasting is a very vital matter. In this article, an adaptive neuro-fuzzy inference system (ANFIS) model is proposed to forecast the rainfall for Klang River in Malaysia on monthly basis. To be able to train and test the ANFIS and ANN models, the statistical data from 1997 to 2008, was obtained from Klang gates dam data. The optimum structure and optimum input pattern of model was determined through trial and error. Different combinations of rainfall were produced as inputs and five different criteria were used in order to evaluate the effectiveness of each network and its ability to make precise prediction. The performance of the ANFIS model is compared to artificial neural network (ANN) model. The five criteria are root mean square error (RMSE), Correlation Coefficient (), and Nash Sutcliffe coefficient (NE), gamma coefficient (GC) Spearman correlation coefficient (SCC). The result indicate that the ANFIS model showed higher rainfall forecasting accuracy and low error compared to the ANN model. Furthermore, the rainfall estimated by this technique was closer to actual data than the other one. Key word: Klang gate, ANFIS, forecasting model.

State of an art review of peat: General perspective

Abstract: Peat can be defined as the accumulation of 100% pure organic material which contains at least 65% organic matter or less than 35% mineral content. The distribution of peat deposits is extensive. It constituents 5 to 8% of the earth land surface and nearly 60% of the wetlands of the world are peat. The composition of peat differs from location to location. This is due to the reasons such as the origin fibre, climate and humidity. Physical properties of peat are greatly dependent to a large degree on porosity and pore-size distribution. These in turn are related to particle-size distribution. Both the particle size and structure and the resulting porosity of peat are controlled primarily by the degree of decomposition. With increasing decomposition, the size of organic particles decreases, resulting in smaller pores and more dry material per unit volume. Generally, the texture of peat is considered coarse when compared with clay. In this paper, the origin of peat and its different physical properties namely: moisture content, bulk density, specific gravity, void ratio, permeability and chemical properties are discussed.

Effects of friction stir welding process parameters on appearance and strength of polypropylene composite welds

Abstract: Friction stir welding is a solid-state joining process that has gained acceptable progress in recent years. This method which was first used for welding of aluminum and its alloys is now employed for welding of other materials such as polymers and composites. In this article, friction stir welding has been used for butt joining polypropylene composite plates having 30% glass fiber by weight. The effects of important process parameters such as tool pin geometry, tool rotational speed, work linear speed and tool tilt angle on weld appearance and tensile strength were investigated experimentally. Different tool pin geometries were used to find their effects on weld quality. Using the tool pin which produced the best weld quality, the effects of other process parameters on weld quality were also investigated. The results indicated that tool pin geometry had a significant influence on weld quality and the effects of rotational speed and tilt angle on weld appearance and strength were more than that of work linear speed. Key words: Friction stir welding, polypropylene composite, glass fiber, weld appearance, tensile strength.

Thermodynamic performance analysis of gas-turbine power-plant

Abstract: This paper was presented the parametric study of thermodynamic performance on gas turbine power plant. The variation of operating conditions (compression ratio, turbine inlet and exhaust temperature, air to fuel ratio, isentropic compressor and turbine efficiency, and ambient temperature) on the performance of gas turbine (thermal efficiency, compressor work, power, specific fuel consumption, heat rate) were investigated. The analytical formula for the specific work and efficiency were derived and analyzed. The programming of performance model for gas turbine was developed utilizing the MATLAB software. The results show that the compression ratio, ambient temperature, air to fuel ratio as well as the isentropic efficiencies are strongly influence on the thermal efficiency. In addition, the thermal efficiency and power output decreases linearly with increase of the ambient temperature and air to fuel ratio. However, the specific fuel consumption and heat rate increases linearly with increase of both ambient temperature and air to fuel ratio. Thus the thermodynamic parameters on cycle performance are economically feasible and beneficial for the gas turbine operations.

A review of control architectures for autonomous navigation of mobile robots

Abstract: A mobile robot as an intelligent system needs to sense the surroundings, perceive the working environment, plan a trajectory and execute proper reaction using the information. Robotic control architectures define how these abilities should be integrated to construct and develop an autonomous navigation. The control architectures could be classified into three categories: Deliberative (Centralized) navigation, Reactive (Behaviour-based) navigation and hybrid (Deliberative - Reactive) navigation. This paper reviews various control architectures for autonomous navigation of mobile robots. The significance, advantages and drawbacks of the architectures are discussed and compared with each other. Key words: Intelligent system, mobile robot, autonomous navigation, control architecture.

Using spectral mapping techniques on short wave infrared bands of ASTER remote sensing data for alteration mineral mapping in SE Iran

Abstract: Spectral mapping techniques were applied on shortwave infrared of advanced spaceborne thermal emission and reflection radiometer (ASTER) data for discriminating between hydrothermal alteration zones, and the identification of high potential mineralized lithologic unit associated with hydrothermal porphyry copper mineralization in the Central Iranian Volcanic Belt. In this study, shortwave infrared radiations of ASTER data were processed with spectral angle mapping, linear spectral unmixing, matched filtering, and mixture tuned matched filtering techniques. Two copper mining districts were used as reference to demonstrate the applicability of the spectral mapping techniques for spectral distinction of specific hydrothermal alteration zones such as argillic, phyllic and propylitic. The results of this study showed that spectral information can be used for generating spatial alteration mineral maps for purely virgin regions, and it can provide a cost-effective method to discriminate the new prospects for porphyry copper exploration prior to detailed and costly ground investigations. Key words: ASTER, spectral mapping techniques, hydrothermal alteration minerals, copper exploration.

Improvement of gas turbine performance based on inlet air cooling systems: A technical review

Abstract: Performance of a gas turbine is mainly depends on the inlet air temperature. The power output of a gas turbine depends on the flow of mass through it. This is precisely the reason why on hot days, when air is less dense, power output falls off. A rise of 1°C temperature of inlet air decreases the power output by 1%. The aim of this paper is to review up to date techniques that were developed to cool inlet air to gas turbine. The techniques including the mechanical chillers, media type evaporative coolers and absorption chillers have been reviewed. It is found that the power consumption of the cool inlet air is of considerable concern since it decreases the net power output of gas turbine. In addition, the mechanical chiller auxiliary power consumption is very high compared to media type evaporative coolers. Furthermore, the reviewed works revealed that the efficiency of evaporative cooler largely depends on moisture present in the air. The gas turbine power augmentation through inlet air chilling is effectively used to boost power during high ambient temperature usually synchronous with on-peak power generation, allowing levelling of gas turbine power output. Key words: Gas turbine, absorption cooler, evaporative cooler, chiller.

Artificial neural network technique for rainfall forecasting applied to Alexandria, Egypt

Abstract: Two rainfall prediction models were developed and implemented in Alexandria, Egypt. These models are Artificial Neural Network ANN model and Multi Regression MLR model. A Feed Forward Neural Network FFNN model was developed and implemented to predict the rainfall on yearly and monthly basis. In order to evaluate the incomes of both models, statistical parameters were used to make the comparison between the two models. These parameters include the Root Mean Square Error RMSE, Mean Absolute Error MAE, Coefficient Of Correlation CC and BIAS. The data set that has been used in this study includes daily measurements for the rainfall and temperature and cover the period from 1957 to 2009. The FFNN model has shown better performance than the MLR model. The MLR model revealed a humble prediction performance. The linear nature of MLR model estimators makes it inadequate to provide good prognostics for a variable characterized by a highly nonlinear physics. On the other hand, the ANN model is a nonlinear mapping tool, which potentially is more suitable for rain (nonlinear physics) forecasts. More detailed studies are necessary due to uncertainties inherent in weather forecasting and efforts should be addressed to the problem of quantifying them in the ANN models. Key words: Neual network, multi regression, rainfall forecasting, Alexandria city.

The exp-function method for new exact solutions of the nonlinear partial differential equations

Abstract: This article was published in the International Journal of Physical Sciences [© 2011 Academic Journals] and the definite version is available at : 10.5897/IJPS11.1026

Nano sized copper particles by electrolytic synthesis and characterizations

Abstract: This work reports a simple, novel, cost effective and eco-friendly electrolytic synthesis of copper nanoparticles using copper sulphate as metal precursor. The synthesis rate is much faster than other methods and this approach is suitable for large scale production. They are characterized by X-ray diffraction (XRD); scanning electron microscope and Fourier transform-infra red (FT-IR) techniques to analyze size, morphology and functional groups. XRD studies reveal a high degree of crystallinity and monophasic nature of copper nanoparticles. Their particle size is found to be 24 nm and specific surface area (SSA) is 28 m2/g. SSA analysis of copper nanoparticles reports that increasing their SSA improves their antibacterial actions. Microbiology essay finds that copper nanoparticles are effective against Escherichia coli and Bacillus megaterium bacteria. SSA of bacteria analysis reveals that it plays a major role while on reactions with antimicrobial agents. Key words: X-ray diffraction (XRD), copper nanoparticles, Williamson Hall plot, electrolysis, Debye-Scherrer.

Performance of artificial neural network and regression techniques for rainfall-runoff prediction

Abstract: Different types of methods have been used in runoff prediction involving conceptualand empirical models. Nevertheless, none of these methods can be considered as a single superior model. Owing to the complexity of the hydrological process, the accurate runoff is difficult to be predicted using the linear recurrence relations or physically based watershed. The linear recurrence relation model does not attempt to take into account the nonlinear dynamic of the hydrological process. The Artificial Neural Network (ANN) is a new technique with a flexible mathematical structure that is capable of identifying complex non-linear relationships between input and output data when compared to other classical modelling techniques. Therefore, the present study aims to utilize an Artificial Neural Network (ANN) to predict the rainfall-runoff relationship in a catchment area located in a Tanakami region of Japan. The study illustrates the applications of the feed forward back propagation with hyperbolic tangent neurons in the hidden layer and linear neuron in the output layer is used for rainfall prediction. To evaluate the performance of the proposed model, three statistical indexes were used, namely; Correlation coefficient (R), mean square error (MSE) and correlation of determination (R2). The results showed that the feed forward back propagation Neural Network (ANN) can describe the behaviour of rainfall-runoff relation more accurately than the classical regression model. Key words: Rainfall-runoff, artificial neural network, linear regression.

Assessment of the effects of dry anaerobic co- digestion of cow dung with waste water sludge on biogas yield and biodegradability

Abstract: Dry anaerobic digestion has been treated as feasible process for potential renewable energy recovery with nutrient-rich fertilizer and sustainable solid waste management. Dry methane fermentation of undiluted cow manure (CM), waste water sludge (WWS) and their mixtures into different ratios were conducted at 35°C in the laboratory-scale single-stage batch reactors for 63 days. The specific biogas production obtained for the CM/WWS ratios of 1:0, 4:1, 3:2, 2:3, 1:4 and 0:1 were 56.94, 58.51, 61.64, 63.12, 59.30 and 55.39 L/kg, with methane yield were 32.01, 33.14, 35.31, 36.91, 34.76 and 32.63 L/kg respectively. The experimental results showed that the co-digestion with CM/WWS ratio of 2:3 obtained highest total biogas production of 63.12 L/kg, methane yield of 0.328 m3/kgVS and total solid (TS), volatile solids (VS), chemical oxygen demand (COD), total organic carbon (TOC) reductions of 34.24, 54.80, 55.22 and 70.71% compared to the other co-digestion ratios and single digestions. It was also revealed that co-digestion resulted in 3.11-13.99% higher methane gas yields, due to synergistic effect. The synergistic effect is mainly attributed to more balanced nutrients and increased buffering capacity. Key words: Dry anaerobic digestion process, co-digestion, specific energy production, methane.

Wavelet fault diagnosis and tolerant of induction motor: A review

Abstract: This paper presents a review of the researches done on fault tolerant control types, methods, main objectives of the fault tolerant control and fault diagnosis of induction motor faults that used the wavelet transform. Wavelet transform from the fault diagnosis point of view, is a summary of the wavelet types (continuous and discrete), machine faults, diagnosis methods and their validation, respectively. Types of software, generality of codes, one dimensional and two dimensional DWT and frequency characteristics components of healthy and faulty induction motor are given. Finally, stator short winding and open winding are taken as a case study to show the effectiveness of the wavelet techniques for fault diagnosis. Key words: Wavelet, induction motor, fault diagnosis, fast Fourier transform, fault indicator, fault tolerant control.

Statistical analysis of S-box in image encryption applications based on majority logic criterion

Abstract: The S-box is used in various block ciphers and the complexity of encryption essentially depends on the strength of S-box. The strength of an S-box can be measured by analyzing its statistical and algebraic properties. The S-box is the only non-linear component in various block ciphers capable of creating confusion. Many S-boxes have been proposed with similar algebraic and statistical properties. Therefore, it is sometimes difficult to choose an S-box for a particular application. The performances of these S-boxes vary and depend on the nature of data and their application. In this paper, we propose a criterion to analyze the prevailing S-boxes and study their strengths and weaknesses in order to determine their suitability in image encryption applications. The proposed criterion uses the results from correlation analysis, entropy analysis, contrast analysis, homogeneity analysis, energy analysis, and mean of absolute deviation analysis. These analyses are applied to advanced encryption standard (AES), affine-power-affine (APA), gray, Lui J, residue prime, S 8 AES, SKIPJACK, and Xyi Sboxes. The results of these analyses are further examined and a majority logic criterion is used to determine the appropriateness of an S-box to image encryption applications.

Effects of the fine recycled concrete aggregates on the concrete properties

Abstract: In this experimental study, the effects of the recycled fine recycled concrete aggregate (FRA) that was manufactured from concrete wastes on the concrete properties were investigated. In concrete mixtures, 0, 10, 20, 30, 40, 50 and 100% by weight FRA were used instead of river sand. Afterwards, unit weight and water absorption ratios and 28-day compressive strength were determined. According to the test results obtained, it was seen that FRA can be used up to 10 % ratio for producing C30 concrete, between 20-50% ratios for producing C25 concrete. Thus, environmental impacts and consumption of the natural resources can be significantly reduced by using recycled fine concrete aggregates in concrete applications. Key words: Compressive strength, concrete, normal crushed aggregate, recycled fine concrete aggregate, waste concrete.

Polymer-noble metal nanocomposites: Review

Abstract: Polymer-noble metal nanocomposites have been extensively investigated due to their potential ability to provide materials with novel mechanical, electronic or chemical behaviour for technological applications. Many preparative procedures have been proposed and detailed characterizations have been carried out on conducting polymer-noble metal nanocomposites; thanks to the rapid improvement in analytical techniques on surface and nanoscale materials. This review focuses on the preparation, characterization of polymer-noble metal nanocomposites and some potential areas for applications such as sensors, batteries (fuel cells) and capacitors. Key words: Polymer, noble metal, nanocomposites, preparation, characterization.

Thermal insulation and physical properties of particleboards from pineapple leaves

Abstract: The aims of this research were to study the production processes and properties of thermal insulation produced from pineapple leaves using natural rubber latex as a binder. Thermal insulation boards were made by spraying the pretreated natural rubber latex onto pineapple fiber to form a squared thermal insulation with the size of 20 and 1.5 cm thickness. Test results on thermal and physical properties showed that the thermal insulation produced from pineapple leaves fiber exhibited a considerably good thermal insulation. The thermal conductivity of the thermal insulation was 0.035 W/m.K with density of 210 kg/m3, which was closed to the commercial insulator. The result showed that pineapple fibrous insulator was extremely potential to replace the synthesis fibrous insulator. Key words: Agricultural residue, spray process, insulating boards, low thermal conductivity.

An application of different artificial intelligences techniques for water quality prediction

Abstract: Artificial Intelligence (AI) is a new technique with a flexible mathematical structure that is capable of identifying complex non-linear relationships between input and output data when compared with other classical modelling techniques. In this study, different techniques of AI have been investigated in prediction of water quality parameters including: multi-layer perceptron neural networks (MLP-ANN), ensemble neural networks (E-ANN) and support vector machine (SVM). The parameters were investigated in terms of the following: the dissolved oxygen (DO), biochemical oxygen demand (BOD) and chemical oxygen demand (COD). To assess the effect of input parameters on the model, the sensitivity analysis was adopted. To evaluate the performance of the proposed model, three statistical indexes were used, namely; correlation coefficient (CC), mean square error (MSE) and correlation of efficiency (CE). The principle aim of this study is to develop a computationally efficient and robust approach for predicting water quality parameters which could reduce the cost and labour for measuring these parameters. This research concentrates on the Johor river in Johor State, Malaysia where the dynamics of river water quality are significantly altered. Key words: Artificial intelligence, water quality prediction model.

Application of artificial neural networks to predict compressive strength of high strength concrete

Abstract: A method to predict 28-day compressive strength of high strength concrete (HSC) by using MFNNs is proposed in this paper. The artificial neural networks (ANN) model is constructed trained and tested using the available data. A total of 368 different data of HSC mix-designs were collected from technical literature. The data used to predict the compressive strength with ANN consisted of eight input parameters which include cement, water, coarse aggregate, fine aggregate, silica fume, superplasticizer, fly ash and granulated grated blast furnace slag. For the training phase, different combinations of layers, number of neurons, learning rate, momentum and activation functions were considered. The training was terminated when the root mean square error (RMSE) reached or was less than 0.001 and the results were tested with test data set. A total of 30 architectures were studied and the 8-10-6-1 architecture was the best possible architecture. The results show that the relative percentage error (RPE) for the training set was 7.02% and the testing set was 12.64%.The ANNs models give high prediction accuracy, and the research results demonstrate that using ANNs to predict concrete strength is practical and beneficial. Key words: Multilayer feedforward neural networks (MFNNs), artificial neural networks (ANNs), relative percentage error (RPE), high strength concrete (HSC), root mean square error (RMSE).

Numerical study of laminar mixed convection heat transfer of power-law non-Newtonian fluids in square enclosures by finite volume method

Abstract: In this study, we have numerically considered mixed convection heat transfer in a square enclosure with cold left and right walls, insulated moving upper wall and hot fixed lower wall. The governing flows of two reliable articles were initially modeled and after validating calculations, the given flow of the study was solved by finite volume method. To examine the effects of different factors, such as Prandtl, Reynolds and Rayleigh numbers on heat transfer in a square enclosure, the laminar flow of Newtonian fluids was approximated and then laminar flow of non-Newtonian fluids, such as carboxy methyl cellulose (CMC) andcarboxy poly methylene (Carbopol) water solutions were studied for different Richardson numbers. It was found from the results obtained in the present study that when Ri is less than 1, governing heat transfer inside the enclosure is forced convection for non-Newtonian fluids similar to Newtonian ones. When Ri increases, the effect of forced convection is reduced and natural convection heat transfer increases. It was also found that in constant Grashof numbers, if n decreases, the dimensionless temperature increases. Also, if n is constant, any increase in Grashof number causes a higher dimensionless temperature. It may be related to the fact that in similar conditions, any increase in forced convection, makes shear stresses more. Key words: Richardson number, power-law non-Newtonian fluids, mixed convection heat transfer, square enclosure, finite volume method.

Spectral transformation of ASTER data and the discrimination of hydrothermal alteration minerals in a semi-arid region, SE Iran.

Abstract: We investigated the spectral transformation of Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) remote-sensing data of a semi-desert realm. Hydroxyl-bearing mineral zones were identified and discriminated based on distinctive shortwave infrared radiation (SWIR) properties of the ASTER data. Principal component analysis (PCA), minimum noise fraction (MNF), and band ratioing methods were applied, compared and combined in order to accurately locate hydrothermal alteration zones in two major mining districts of SE Iran. The strategy in this study consisted of using PC images and associated statistics factors yielded by PCA transformation for the identification of vegetation and iron oxide minerals in the visible and near infrared radiation (VNIR), clay minerals in the shortwave infrared radiation (SWIR), and silicate rocks in the thermal infrared radiation (TIR) of the ASTER data, respectively. The PCA results were verified by comparison with obtained results by minimum noise fraction and band ratio methods and also prior knowledge about the study area. In conclusion, the discrimination of alteration zones with high potential for copper and gold mineralization by spectral transformation of the ASTER data is a reliable, fast and relatively low cost with great ability to assist exploration geologists in the reconnaissance stages of mineral exploration.

Effect of cement content and water/cement ratio on fresh concrete properties without admixtures

Abstract: This paper investigates the effects of cement content and water/cement ratio on workable fresh concrete properties with slump changing between 90 to 110 mm, and determines the relations among fresh concrete properties such as slump, compacting factor, VeBe, unit weight and setting times of mortar with temperature history. The experiments were conducted under laboratory conditions on eight different concrete mixtures prepared from ordinary Portland cement (cement contents of 300, 350, 400, 450, 500, 550, 600 and 650 kg/m3) and crushed limestone coarse and fine aggregates. Relations such as (a) VeBe time/unit weight/slump/K-slump/compacting factor/w/c ratio for cement content, (b) K-slump/compacting factor/unit weight/VeBe time for slump, (c) aggregate/cement ratio/unit weight/VeBe time for compacting factor, and (d) penetration resistance for elapsed time were determined. It was observed that increasing the cement content causes increase in the slump, K-slump, compacting factor and fresh concrete unit weight, and reduces VeBe time. Proposed fresh concrete relationships are quite appropriate for concretes without using any mineral or chemical admixtures. Key words: Fresh concrete, slump, compacting factor, VeBe time, unit weight, setting time.

Agricultural waste as a low cost adsorbent for heavy metal removal from wastewater

Abstract: Biosorption was carried out in a batch process to test the suitability of Amaranthus hybridus (African spinach) stalk and Carica papaya (pawpaw) seed for removal of Mn (II) and Pb (II) ions from aqueous solution. The amount of metal ions removed from solution depended on the metal ion-substrate contact time, ion concentration and ion type. The contact time was 90 min for both substrates. The results indicated that the amount of absorbed metal ions varied with substrates materials, and the order of removal of heavy metals by the biosorbents was Mn (II)>Pb (II). Furthermore, Mn (II) had higher removal percentages than Pb (II) ions in both substrates. In all cases, C. papaya seeds showed greater adsorptive capacity than A. hybridus stalk. The result from both biomasses significantly fitted the Freundlich adsorption isotherm. The results obtained through the study showed both substrates are favourable for sorption and removal of heavy metal from aqueous solution. Key words: Amaranthus hybridus stalk, Carica papaya seeds, adsorption, manganese, lead, contact time.

Application of advanced spaceborne thermal emission and reflection radiometer (ASTER) data in geological mapping

Abstract: The spectral and spatial properties of the advanced spaceborne thermal emission and reflection radiometer (ASTER) data can be used in detailed lithological and hydrothermal alteration mapping related to copper and gold mineralization, particularly the shortwave infrared radiation subsystem where hydrothermal alteration minerals have diagnostic spectral absorption features. This paper reviews the technical characteristics of ASTER data and related image processing techniques applicable to ASTER data for lithological and hydrothermal alteration mineral mapping. The hydrothermal alteration zones associated with porphyry copper deposit, such as phyllic, argillic and propylitic, can be discriminated from one another by virtue of their spectral absorption features, which are recognizable by ASTER special bands. The differentiation and identification of phyllic zone are important for exploring porphyry copper mineralization as an indicator of the high potential area with economical mineralization of copper. In this way, we attempt to demonstrate how ASTER remote sensing data can identify and discriminate the hydrothermal alteration zones and lithological units in a regional scale. It is therefore concluded that remote sensing techniques are viable options for geological applications, offering reliable and relatively low cost methods, and could be utilized further to other virgin regions for lithological mapping and for initial steps of mineral exploration.

Path planning for a mobile robot in dynamic environments

Abstract: Path planning for mobile robots has been gaining extensive research attention recently. Optimal path planning increases the effectiveness of a mobile robot. There are many algorithms to solve the path planning problems overcoming obstacles. However most of the algorithms are applicable to specific shapes or suitable for static environments. This paper introduces a new method of global path planning for a robot moving in an environment cluttered with obstacles which have arbitrary shape, size and location. The proposed algorithm is applicable to static, partially dynamic as well as dynamic environments containing obstacles. Simulation of variety of cases are presented and discussed.

Degradation studies of amines and alkanolamines during sour gas treatment process

Abstract: Aqueous solutions of alkanolamines are widely used for the removal of acidic gases such as H 2S, CO 2, COS and CS 2 in the sour gas treatment process. In spite of the resistance of alkanolamines to chemical breakdown, plant and laboratory reports indicate that, on prolonged use, alkanolamines may be transformed into undesirable products from which the amines are not easily recovered. This phenomenon, commonly referred to as 'amine degradation', not only leads to amine losses, but may also contribute to operational problems such as foaming, corrosion, high solution viscosity and fouling as a result of decreasing the plant life. Amine based gas purification plants having absorption and stripping system, solvents are degraded at these two units mainly by oxidative degradation at absorber condition and thermal degradation at stripper condition. Identification of amine degradation routes, remediation of degradation, types of degradation products and studies on degradation reaction mechanism becomes essential for successful plant operation. Gas chromatography-mass spectrometry (GC-MS), ion chromatograph (IC), high performance liquid chromatography (HPLC), nuclear magnetic resonance spectroscopy (NMR) and Fourier transform infrared absorption spectrometry (FT-IR) are extensively used to identify the various degradation products. A comprehensive review of the latest research activities on alkanolamines degradation, best method for identification, various properties of degradation products and their classification is presented in this paper. This study would help to develop better understanding of amine degradation. © 2011 Academic Journals.

Assessment of high strength and light weight aggregate concrete properties using ultrasonic pulse velocity technique

Abstract: In this study, the ultrasonic pulse velocity technique as a non-destructive testing of concrete was used to assess the effect of some criteria on high strength and light weight aggregate concrete. The study included several concrete mix design with ages of 7, 28 and 90 days. The effect of age, cement content, water ratio and slump on two concrete types was studied and discussed. The use of ultrasonic pulse velocity technique to assessconcrete strength and quality was a good choice for effects determination. Key words: Non destructive testing (NDT), ultrasonic pulse velocity (UPV), compressive strength, regression analysis.