Production of fatty acid esters (biodiesel) from oleic acid and 2-ethylhexanol using sulfated zirconia as solid catalyst for the production of biodiesel was investigated in this work.

       The parameters studied were temperature of reaction (100 to 130°C), molar ratio of alcohol to free fatty acid (1:1 to 3:1), concentration of catalyst (0.5 to 3%wt), mixing speed (500 to 900 rpm) and types of sulfated zirconia (i.e modified, commercial, prepared  catalyst according to literature and reused catalyst). The results show the best conversion to biodiesel was 97.74% at conditions of 130°C, 3:1, 2wt% and 650 rpm using modified catalyst respectively. Also, modified c

A potential alternative energy resource to meet energy demands is the vast amount of gas stored in hydrate reserves. However, major challenges in terms of exploration and production surround profitable and effective exploitation of these reserves. The measurement of acoustic velocity is a useful method for exploration of gas hydrate reserves and can be an efficient method to characterize the hydrate-bearing sediments. In this study, the compressional wave velocity (P-wave velocity) of consolidated sediments (Bentheimer) with and without tetrahydrofuran hydrate-bearing pore fillings were measured using the pulse transmission method. The study has found that the P-wave velocity of consolidated sediments increase with increasing hydrate format

Prediction of penetration rate (ROP) is important process in optimization of drilling due to its crucial role in lowering drilling operation costs. This process has complex nature due to too many interrelated factors that affected the rate of penetration, which make difficult predicting process. This paper shows a new technique of rate of penetration prediction by using artificial neural network technique. A three layers model composed of two hidden layers and output layer has built by using drilling parameters data extracted from mud logging and wire line log for Alhalfaya oil field. These drilling parameters includes mechanical (WOB, RPM), hydraulic (HIS), and travel transit time (DT). Five data set represented five formations gathered

This deals with estimation of Reliability function and one shape parameter (?) of two- parameters Burr – XII , when ?(shape parameter is known) (?=0.5,1,1.5) and also the initial values of (?=1), while different sample shze n= 10, 20, 30, 50) bare used. The results depend on empirical study through simulation experiments are applied to compare the four methods of estimation, as well as computing the reliability function . The results of Mean square error indicates that Jacknif estimator is better than other three estimators , for all sample size and parameter values

Forecasting is one of the important topics in the analysis of time series, as the importance of forecasting in the economic field has emerged in order to achieve economic growth. Therefore, accurate forecasting of time series is one of the most important challenges that we seek to make the best decision, the aim of the research is to suggest employing hybrid models to predict daily crude oil prices. The hybrid model consists of integrating the linear component, which represents Box Jenkins models, and the non-linear component, which represents one of the methods of artificial intelligence, which is the artificial neural network (ANN), support vector regression (SVR) algorithm and it was shown that the proposed hybrid models in the predicti

Commercial, industrial, and military activity, largely in the 19th and 20th centuries, have led to  environmental pollution that can threaten human health and ecosystem function, liquid gas petroleum (LPG) products are the major sources of energy for industry and daily life that cause environmental contamination during various stages of production, transportation, refining and use. Screening of bacterial isolate by using clear zone techniques and biomass and optical density. Results revealed that isolate Burkholdaria cepatia showed a high ability for hydrocarbons biodegradation and this isolate identified depending on morphological cultural, gram stain, microscopic features, biochemical tests, and VITEK2 compact.   In this study,

This study was conducted to determine the activity of plant Sesbania rostrata and two isolate from arbuscular mycorrhizae fungi (A,B) as a bioremediation of soil polluted by cadmium and lead elements in north and south of Baghdad city. The results showed that the average of soil pollution by cadmium and lead elements in north of Baghdad was less than the average of soil pollution in the south of Baghdad which recorded 10.0, 9.0 mg/kg and 27.0, 25.0 mg/kg respectively. The plant Sesbania recorded ability to accumulate the lead element in shoot system 19.65 mg/kg and in root system 27.2 mg/kg and for cadmium element 19.6, 24.6 mg/kg in shoot and root respectively. The results showed that the isolate A from soil pollution is more effected

The purpose of this study is to evaluate the hydraulic performance and efficiency of using direction diverting blocks, DDBs, fixed on the surface on an Ogee spillway in reducing the acceleration and dissipating the energy of the incoming supercritical flow. Fifteen types of DDB models were made from wood with a triangulate shape and different sizes were used. Investigation tests on pressure distribution at the DDBs boundaries were curried out to insure there is no negative pressures is developed that cause cavitation. In these tests, thirty six test runs were accomplished by using six types of blocks with the same size but differ in apex angle. Results of these test showed no negative pressures developed at the boundarie

Recurrent strokes can be devastating, often resulting in severe disability or death. However, nearly 90% of the causes of recurrent stroke are modifiable, which means recurrent strokes can be averted by controlling risk factors, which are mainly behavioral and metabolic in nature. Thus, it shows that from the previous works that recurrent stroke prediction model could help in minimizing the possibility of getting recurrent stroke. Previous works have shown promising results in predicting first-time stroke cases with machine learning approaches. However, there are limited works on recurrent stroke prediction using machine learning methods. Hence, this work is proposed to perform an empirical analysis and to investigate machine learning al