MHD transient flows and heat transfer of dusty fluid in a channel with variable physical properties and Navier slip condition

AbstractIn this paper, we study the unsteady flow and heat transfer of a dusty fluid between two parallel plates with variable viscosity and electric conductivity. The fluid is driven by a constant pressure gradient and an external uniform magnetic field is applied perpendicular to the plates with a Navier slip boundary condition. The governing non-linear partial differential equations are solved numerically using a semi-implicit finite difference scheme. The effect of the wall slip parameter, viscosity and electric conductivity variation and the uniform magnetic field on the velocity and temperature fields for both the fluid and dust particles is discussed

PREDICTION OF CRUDE OIL VISCOSITY USING FEED-FORWARD BACK-PROPAGATION NEURAL NETWORK (FFBPNN)

Crude oil viscosity is an important governing parameter of fluid flow both in the porous media and in pipelines. So, estimating the oil viscosity at various operating conditions with accuracy is of utmost importance to petroleum engineers. Usually, oil viscosity is determined by laboratory measurements at reservoir temperature. However, laboratory experiments are rather expensive and in most cases, the data from such experiments are not reliable. So, petroleum engineers prefer to use published correlations but these correlations are either too simple or too complex and so many of them are region-based not generic. To tackle the above enumerated drawbacks, in this paper, a Feed-Forward Back-Propagation Neural Network (FFBPNN) model has been developed to estimate the crude oil viscosity (μo) of Undersaturated reservoirs in the Niger Delta region of Nigeria. The newly developed FFBPNN model shows good results compared to the existing empirical correlations. The μo FFBPNN model achieved an average absolute relative error of 0.01998 and the correlation coefficient (R2) of 0.999 compared to the existing empirical correlations. From the performance plots for the FFBPNN model and empirical correlations against their experimental values, the FFBPNN model's performance was excellent

Numerical Investigation of Entropy Generation in Unsteady MHD Generalized Couette Flow with Variable Electrical Conductivity

The thermodynamic second law analysis is utilized to investigate the inherent irreversibility in an unsteady hydromagnetic generalized Couette flow with variable electrical conductivity in the presence of induced electric field. Based on some simplified assumption, the model nonlinear governing equations are obtained and solved numerically using semidiscretization finite difference techniques. Effects of various thermophysical parameters on the fluid velocity, temperature, current density, skin friction, the Nusselt number, entropy generation number, and the Bejan number are presented graphically and discussed quantitatively

Computational Dynamics of Arterial Blood Flow in the Presence of Magnetic Field and Thermal Radiation Therapy

We conduct a numerical study to determine the influence of magnetic field and thermal radiation on both velocity and temperature distributions in a single blood vessel. The model here assumes that blood is a Newtonian incompressible conducting fluid with radially varying viscosity due to hematocrit variation. The transient equations of momentum and energy transport governing the flow in an axisymmetric configuration are solved numerically using a semi-implicit finite difference method. Results are presented graphically and discussed both qualitatively and quantitatively from the physiological point of view. The results of this work may enhance current understanding of the factors that determine the effects of hyperthermia treatment on tumor tissues

Impact of Processing on Physical, Chemical and Pasting Properties of Tamarind (T. indica) Seed Flour

Tamarind seed is a discarded waste material from the tamarind pulp industry. The seed contains plethora of nutrients, however its application as food ingredient in Nigeria is limited. This study investigated the impact of processing techniques on physical (colour), proximate, mineral, anti-nutrient and pasting properties of tamarind seed flour using standard methods. Unprocessed seeds (sample A) served as the control, soaked seeds (sample B), roasted seeds (sample C) and autoclaved seeds (sample D). The obtained flour samples were analysed for the physical (colour), proximate, mineral, anti-nutrient and pasting properties using standard methods. Colour values (L*) of seed flour decreased whereas a* and b* values increased in processed flours compared to the control. Raw and processed tamarind seed flours are composed mainly of carbohydrate (65.0-75.2%) and protein (2.3-12.7%) with minuscule quantities of dietary fibre (3.50-7.10%), fat (5.4-6.8%) and ash (1.25-2.08%). The results revealed the following ranges in mineral concentrations: calcium (11.72-18.76mg/100g), magnesium (125.48-152.55mg/100g), potassium (224.49-487.37mg/100g) and iron (22.34-31.04mg/100g). Boiling, autoclaving and roasting significantly (p≤0.05) altered the anti-nutritional contents of tamarind seeds. There exist variation in the pasting viscosities with the control and processed tamarind flours being significantly different (p≤0.05).  The study highlighted that roasting of the seeds could eliminate the anti-nutrients and improved the quality of seeds compared to soaking and autoclaving processes. Exploring the potential of tamarind seeds for human consumption will clearly reduce the over-dependence on common legumes as protein source in marginalised communities

AN ONTOLOGY-BASED KNOWLEDGE REPRESENTATION USING ANALYTIC HIERARCHY PROCESS FOR ENHANCING SELECTION OF PRODUCT PREFERENCES

Product alternatives, which emerges from large number of websites during searching, accounts for some hesitation experienced by customers in selecting satisfying product. As a result, making useful decision with many trade-off considerations becomes a major cause of such problem. Several approaches have been employed for product selection such as, fuzzy logic, Neuro-fuzzy, and weighted least square. However, these could not solve the problem of inconsistency and irrelevant judgement that occur in decision making. In this study, Ontology-based Analytic Hierarchy Process (AHP) was used for enhancing selection of product preferences. The model involved three fundamental components: product gathering, selection and decision making. Ontology Web Language (OWL) was utilized to define ontology in expressing product information gathering in a standard and structured manner for the purpose of interoperability while AHP was employed in making optimal choices. The procedure accepts customers’ perspectives as inputs which are classified into criteria and sub-criteria. Owl was created to foster customers’ interaction and priority estimation tool for AHP in order to generate the consistency ratio of individual judgements. The model was benchmarked with Geometric Mean (GM), Eigenvector (EV), Normalized Column Sum (NCS) Weighted Least Square (WLS) and Fuzzy Preference Programming (FPP). First and second order total deviations and violation rate were the performance parameters evaluation with AHP. The results showed that the minimum and maximum units of products are 2,452and 3,574, respectively. These implied that the proposed model was consistent, relevant and reflected a non-violation of judgment in selection of product preferences. &nbsp

Modelling the Effects of Temperature and Aging Time on the Rheological Properties of Drilling Fluids

The rheological properties of drilling fluid change owing to elevated temperature and aging time and these in effect, cause problems in drilling deep wells. A laboratory investigation of the effects of temperature and aging time on the properties of water-base drilling fluid is made with Fann Model 800 HighTemperature, High Pressure (HTHP) Viscometer. It is evident from the findings that effective viscosity, plastic viscosity and yield point decrease steadily with increase in temperature for all values of aging time. It is observed as well that viscosity at a given temperature decreases with increase in aging time and the aging effect are diminishing as the aging time increases especially for the effective viscosity and yield point. It is also observed from this study that viscosity, yield point, gel strength and shear stress at a given shear rate decrease with increase in temperature and aging time. Finally, this paper presents a predictive model equation good enough to analyse trends and predict future values for effective and plastic viscosities

WELL DELIVERABILITY PREDICTIONS OF GAS FLOW IN GAS-CONDENSATE RESERVOIRS, MODELLING NEAR-CRITICAL WELLBORE PROBLEM OF TWO PHASE FLOW IN 1 -DIMENSION

Production of gases from gas-condensate reservoirs are known to bear certain challenges largely due to the formation of retrograde condensates that hinder gas flow. The drop out of this liquid creates flow regions that are characterized by the liquid saturation as it affects the mobility of the two phase flow, thereby preventing the effective modeling of well productivity. In this study, a predictive model based on an analytical approach is developed to predict gas flow in gas condensate reservoirs. This study compares the estimated gas flow from the developed model for gas-condensate reservoirs to the flow of an existing model for gas reservoirs. This study observes the effects of liquid drop-out on productivity at low pressures and the condensate unloading pressure, which is comparable to that of commercial softwar

Phytotoxicity Level and Effects of Arsenic Phytoextraction using Helianthus Annuus L. (Sunflower)

Arsenic is one of the most deadly contaminants polluting the environment in many countries of the world today. It occurs naturally in many ores (Copper, Lead, Gold etc.), but human activities (like explosions, mining, pesticides applications etc.) and natural occurrences (like volcanoes, micro-organisms activities) have increased its amount in the environment to lethal levels. This research involved the growing of sunflower plants Helianthus annuus L. collected from the Institute of Agricultural Research and Training (IAR&T) on various concentrations of Arsenate contaminated soil for Arsenic phyto-extraction for seven weeks to know the phyto-toxicity level of Arsenic on sunflower (an Arsenic hyper-accumulator). After several observations and statistical evaluations using the Analysis of Variance, it was discovered that as from 2.0g – 3.0g of Arsenate per kg of soil, 0% germination occurred. Between 0.75g – 1.5g of Arsenate per kg of soil, the percentage germination was 10% - 50% (not significant) and percentage survival was 30% (not significant). Furthermore, between 0g – 1.5g of Arsenate per kg of soil, there was a percentage germination of 60% - 100% (significant) and a percentage survival of 60% - 100% (significant). Hence, for efficient and appreciable Arsenic phyto-extraction from an Arsenate contaminated soil using Sunflower a concentration of 0.5g and below of Arsenate per kg of soil should be ensured. As from 0.75g of Arsenate per kg of soil (Phytotoxicity level) the effects of Arsenic phyto-toxicity observed are delayed germination, wilting, drying-off, damping-off, foliage chlorosis and necrosis, reddening etc. Keywords:Phytoextraction, phytotoxicity, arsenic, sunflower, arsenate contaminated soi

Phytotoxicity Level and Effects of Arsenic Phytoextraction using Helianthus Annuus L. (Sunflower)

Arsenic is one of the most deadly contaminants polluting the environment in many countries of the world today. It occurs naturally in many ores (Copper, Lead, Gold etc.), but human activities (like explosions, mining, pesticides applications etc.) and natural occurrences (like volcanoes, micro-organisms activities) have increased its amount in the environment to lethal levels. This research involved the growing of sunflower plants Helianthus annuus L. collected from the Institute of Agricultural Research and Training (IAR&T) on various concentrations of Arsenate contaminated soil for Arsenic phyto-extraction for seven weeks to know the phyto-toxicity level of Arsenic on sunflower (an Arsenic hyper-accumulator). After several observations and statistical evaluations using the Analysis of Variance, it was discovered that as from 2.0g – 3.0g of Arsenate per kg of soil, 0% germination occurred. Between 0.75g – 1.5g of Arsenate per kg of soil, the percentage germination was 10% - 50% (not significant) and percentage survival was 30% (not significant). Furthermore, between 0g – 1.5g of Arsenate per kg of soil, there was a percentage germination of 60% - 100% (significant) and a percentage survival of 60% - 100% (significant). Hence, for efficient and appreciable Arsenic phyto-extraction from an Arsenate contaminated soil using Sunflower a concentration of 0.5g and below of Arsenate per kg of soil should be ensured. As from 0.75g of Arsenate per kg of soil (Phytotoxicity level) the effects of Arsenic phyto-toxicity observed are delayed germination, wilting, drying-off, damping-off, foliage chlorosis and necrosis, reddening etc. Keywords: Phytoextraction, phytotoxicity, arsenic, sunflower, arsenate contaminated soi