An investigation was conducted for the improvement of viscosity index of light lubricating oil fraction (40 stock)
obtained from vacuum distillation unit of lube oil plant of Daura Refinery, using solvent extraction process.
In this study furfural solvent was used to extract the undesirable materials which reduce the viscosity index of raw
lubricating oil fraction.
The studied effecting variables of extraction were extraction temperature range from 70 to 110°C, and solvent to oil
ratio range from 1:1 to 4:1 (wt/wt).
The n-d-M method was used for calculation of carbon distribution and structural group analysis of the raffinate
produced from furfural extraction.
Also the three component phase diagram for a mixed-base oil and furfural at different temperature was drawn.
The results of this investigation show that the viscosity index of lubricating oil fraction increases with increasing
extraction temperature and increasing the solvent to oil ratio and reaches 115.6 at extraction temperature 110°C and
solvent to oil ratio 4:1.
Further more, the results show that the viscosity, refractive index, density, sulfur content and percentage yield of
produced raffinate were decreased as the extraction temperature or solvent to oil ratio increases for extraction process.
The co-occurrence of metabolic syndrome with type 2 diabetes mellitus (T2DM) will potentiate the morbidity and mortality that may be associated with each case. Fasting triglycerides-glucose index (TyG index) has been recommended as a useful marker to predict metabolic syndrome. Our study aimed to introduce gender-specific cut-off values of triglycerides- glucose index for diagnosing metabolic syndrome associated with type 2 diabetes mellitus. The data were collected from Baghdad hospitals between May - December 2019. The number of eligible participants was 424. National cholesterol education program, Adult Treatment Panel III criteria were used to define metabolic syndrome. Measurement of fasting blood glucose, lipid pro
... Show MoreThe oil and gas industry relies heavily on IT innovations to manage business processes, but the exponential generation of data has led to concerns about processing big data, generating valuable insights, and making timely decisions. Many companies have adopted Big Data Analytics (BDA) solutions to address these challenges. However, determining the adoption of BDA solutions requires a thorough understanding of the contextual factors influencing these decisions. This research explores these factors using a new Technology-Organisation-Environment (TOE) framework, presenting technological, organisational, and environmental factors. The study used a Delphi research method and seven heterogeneous panelists from an Oman oil and gas company
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