The content of fatty acid methyl esters (FAME) is a crucial property of biodiesel and serves as an indicator of the transesterification reaction that converts vegetable oil into biodiesel. To facilitate the rapid estimation of FAME quickly in the biodiesel industries, simple methods such as measuring refractive index, density, and dynamic viscosity measurements were employed to monitor the progress of transesterification of castor oil to biodiesel. Blends of castor oil and biodiesel were mixed at different weights to find correlations between FAME content and refractive index, density, and dynamic viscosity measurements. The transesterification of castor oil with methanol was carried out to examine how the refractive index, density, and dynamic viscosity properties change in relation to the conversion ratio. The results show that the optimal conditions for the transesterification of castor oil with methanol involve using amethanolic solution of KOH at 45 °C and 150 min with 18:1 mole ratio. This study demonstrated that these measurements were simple, fast, and suitable for monitoring the conversion of castor oil to its methyl and determining the % FAME content in castor biodiesel prepared.
<p>The current work investigated the combustion efficiency of biodiesel engines under diverse ratios of compression (15.5, 16.5, 17.5, and 18.5) and different biodiesel fuels produced from apricot oil, papaya oil, sunflower oil, and tomato seed oil. The combustion process of the biodiesel fuel inside the engine was simulated utilizing ANSYS Fluent v16 (CFD). On AV1 diesel engines (Kirloskar), numerical simulations were conducted at 1500 rpm. The outcomes of the simulation demonstrated that increasing the compression ratio (CR) led to increased peak temperature and pressures in the combustion chamber, as well as elevated levels of CO<sub>2</sub> and NO mass fractions and decreased CO emission values un
... Show MoreAn experiment was carried out in the fields of Agriculture College-Baghdad University during spring and autumn of 2015 by using a randomized complete blocks design with three replications. The first season hybridization was established among three pure cultivars of cowpea (Vigna uniguiculata L.) which: Ramshorn, California black eye and Rahawya in full diallel crosses according to Griffing with first method and fixed model (3 parents+ 3 diallel hybrids +3 reciprocal hybrids) and a comparison experiment was in autumn season. The result of statistical analysis showed that there was a significant difference among the parents and their hybrids for all the studied characters. The parent 1 was the higher for root nodules number , leaf number, pod
... Show MoreThe statistical distributions study aimed to obtain on best descriptions of variable sets phenomena, which each of them got one behavior of that distributions . The estimation operations study for that distributions considered of important things which could n't canceled in variable behavior study, as result this research came as trial for reaching to best method for information distribution estimation which is generalized linear failure rate distribution, throughout studying the theoretical sides by depending on statistical posteriori methods like greatest ability, minimum squares method and Mixing method (suggested method).
The research
... Show MoreThe goal (purpose) from using development technology that require mathematical procedure related with high Quality & sufficiency of solving complex problem called Dynamic Programming with in recursive method (forward & backward) through finding series of associated decisions for reliability function of Pareto distribution estimator by using two approach Maximum likelihood & moment .to conclude optimal policy
Rate of penetration plays a vital role in field development process because the drilling operation is expensive and include the cost of equipment and materials used during the penetration of rock and efforts of the crew in order to complete the well without major problems. It’s important to finish the well as soon as possible to reduce the expenditures. So, knowing the rate of penetration in the area that is going to be drilled will help in speculation of the cost and that will lead to optimize drilling outgoings. In this research, an intelligent model was built using artificial intelligence to achieve this goal. The model was built using adaptive neuro fuzzy inference system to predict the rate of penetration in
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