ANALYSIS, MODIFICATION, AND EVALUATION OF THE COLD FLOW PROPERTIES OF VEGETABLE OILS AS BASE OIL FOR INDUSTRIAL LUBRICANTS

Poor cold flow properties of vegetable oils are a major problem preventing the usage of many abundantly available vegetable oils as base stocks for industrial lubricants. The major objective of this research is to improve the cold flow properties of vegetable oils by various techniques like additive addition and different chemical modification processes. Conventional procedure for determining pour point is ASTM D97 method. ASTM D97 method is time consuming and reproducibility of pour point temperatures is poor between laboratories. Differential Scanning Calorimetry (DSC) is a fast, accurate and reproducible method to analyze the thermal activities during cooling/heating of oil. In this work coconut oil has been chosen as representative vegetable oil for the analysis and improvement cold flow properties since it is abundantly available in the tropics and has a very high pour point of 24 °C. DSC is used for the analysis of unmodified and modified vegetable oil. The modified oils (with acceptable pour points) were then subjected to different tests for the valuation of important lubricant properties such as viscometric, tribological (friction and wear properties), oxidative and corrosion properties.A commercial polymethacrylate based PPD was added in different percentages and the pour points were determined in each case. Styrenated phenol(SP) was added in different concentration to coconut oil and each solution was subjected to ASTM D97 test and analysis by DSC. Refined coconut oil and other oils like castor oil, sunflower oil and keranja oil were mixed in different proportions and interesterification procedure was carried out. Interesterification of coconut oil with other vegetable oils was not found to be effective in lowering the pour point of coconut oil as the reduction attained was only to the extent of 2 to 3 °C.Chemical modification by acid catalysed condensation reaction with coconut oil castor oil mixture resulted in significant reduction of pour point (from 24 ºC to -3 ºC). Instead of using triacylglycerols, when their fatty acid derivatives (lauric acid- the major fatty acid content of coconut oil and oleic acid- the major fatty acid constituents of monoand poly- unsaturated vegetable oils like olive oil, sunflower oil etc.) were used for the synthesis , the pour point could be brought down to -42 ºC. FTIR and NMR spectroscopy confirmed the ester structure of the product which is fundamental to the biodegradability of vegetable oils. The tribological performance of the synthesised product with a suitable AW/EP additive was comparable to the commercial SAE20W30 oil. The viscometric properties (viscosity and viscosity index) were also (with out additives) comparable to commercial lubricants. The TGA experiment confirmed the better oxidative performance of the product compared to vegetable oils. The sample passed corrosion test as per ASTM D130 method.

Behaviour of laterised normal and self compacting concrete subjected to elevated temperatures

Concrete is a universal material in the construction industry. With natural resources like sand and aggregate, fast depleting, it is time to look for alternate materials to substitute these in the process of making concrete. There are instances like exposure to solar radiation, fire, furnaces, and nuclear reactor vessels, special applications like missile launching pads etc., where concrete is exposed to temperature variations In this research work, an attempt has been made to understand the behaviour of concrete when weathered laterite aggregate is used in both conventional and self compacting normal strength concrete. The study has been extended to understand the thermal behaviour of both types of laterised concretes and to check suitability as a fire protection material. A systematic study of laterised concrete considering parameters like source of laterite aggregate, grades of Ordinary Portland Cement (OPC) and types of supplementary cementitious materials (fly ash and GGBFS) has been carried out to arrive at a feasible combination of various ingredients in laterised concrete. A mix design methodology has been proposed for making normal strength laterised self compacting concrete based on trial mixes and the same has also been validated. The physical and mechanical properties of laterised concretes have been studied with respect to different variables like exposure temperature (200°C, 400°C and 600°C) and cooling environment (air cooled and water cooled). The behaviour of ferrocement elements with laterised self compacting concrete has also been studied by varying the cover to mesh reinforcement (10mm to 50mm at an interval of 10mm), exposure temperature and cooling environment.

Meteorological aspects of an abnormal cooling event over Iran in April 2009

During the period from 12 to 15 April, 2009 nearly the entire Iran, apart from the southern border, experienced an advective cooling event. While winter freezing concerns are typical, the nature of this freezing event was unusual with respect to its date of occurrence and accompanying synoptic meteorological situation. To analyze the freezing event, the relevant meteorological data at multiple levels of the atmosphere were examined from the NCEP/ NCAR reanalysis dataset. The results showed that a polar vortex was responsible for the freezing event over the country extending southward extraordinarily in such a way that its ridge influenced most parts of Iran. This was recognized as an abnormal extension of a polar vortex in the recent years. The sea-level pressure fields indicated that a ridge of large-scale anticyclone centered over Black Sea extended southward and prevailed over most parts of Iran. This resulted in the formation of a severe cold air advection from high latitudes (Polar region) over Iran. During the study period, moisture pumping was observed from the Arabian Sea and Persian Gulf. The winds at 1000 hPa level blew with a magnitude of 10 m s-1 toward south in the region of convergence (between -2 9 10-6 s-1 and -12 9 10-6 s-1). The vertical profilesof temperature and humidity also indicated that the ICE structural icing occurred at multiple levels of the atmosphere, i.e, from 800 hPa through 400 hPa levels. In addition to the carburetor (or induction), icing occurred between 900 and 700 hPa levels in the selected radiosonde stations during the study period. In addition, the HYSPLIT backward trajectory model outputs were in quite good agreement with the observed synoptic features

Development of Techniques for the Automatic Extraction and Grade Detection of Glioma Tumors from Conventional Brain Magnetic Resonant Images

Cerebral glioma is the most prevalent primary brain tumor, which are classified broadly into low and high grades according to the degree of malignancy. High grade gliomas are highly malignant which possess a poor prognosis, and the patients survive less than eighteen months after diagnosis. Low grade gliomas are slow growing, least malignant and has better response to therapy. To date, histological grading is used as the standard technique for diagnosis, treatment planning and survival prediction. The main objective of this thesis is to propose novel methods for automatic extraction of low and high grade glioma and other brain tissues, grade detection techniques for glioma using conventional magnetic resonance imaging (MRI) modalities and 3D modelling of glioma from segmented tumor slices in order to assess the growth rate of tumors. Two new methods are developed for extracting tumor regions, of which the second method, named as Adaptive Gray level Algebraic set Segmentation Algorithm (AGASA) can also extract white matter and grey matter from T1 FLAIR an T2 weighted images. The methods were validated with manual Ground truth images, which showed promising results. The developed methods were compared with widely used Fuzzy c-means clustering technique and the robustness of the algorithm with respect to noise is also checked for different noise levels. Image texture can provide significant information on the (ab)normality of tissue, and this thesis expands this idea to tumour texture grading and detection. Based on the thresholds of discriminant first order and gray level cooccurrence matrix based second order statistical features three feature sets were formulated and a decision system was developed for grade detection of glioma from conventional T2 weighted MRI modality.The quantitative performance analysis using ROC curve showed 99.03% accuracy for distinguishing between advanced (aggressive) and early stage (non-aggressive) malignant glioma. The developed brain texture analysis techniques can improve the physician’s ability to detect and analyse pathologies leading to a more reliable diagnosis and treatment of disease. The segmented tumors were also used for volumetric modelling of tumors which can provide an idea of the growth rate of tumor; this can be used for assessing response to therapy and patient prognosis.