Consequence modelling,vulnerability assessment and fuzzy fault tree analysis of hazardous storages in an industrial area

The hazards associated with major accident hazard (MAH) industries are fire, explosion and toxic gas releases. Of these, toxic gas release is the worst as it has the potential to cause extensive fatalities. Qualitative and quantitative hazard analyses are essential for the identitication and quantification of the hazards associated with chemical industries. This research work presents the results of a consequence analysis carried out to assess the damage potential of the hazardous material storages in an industrial area of central Kerala, India. A survey carried out in the major accident hazard (MAH) units in the industrial belt revealed that the major hazardous chemicals stored by the various industrial units are ammonia, chlorine, benzene, naphtha, cyclohexane, cyclohexanone and LPG. The damage potential of the above chemicals is assessed using consequence modelling. Modelling of pool fires for naphtha, cyclohexane, cyclohexanone, benzene and ammonia are carried out using TNO model. Vapor cloud explosion (VCE) modelling of LPG, cyclohexane and benzene are carried out using TNT equivalent model. Boiling liquid expanding vapor explosion (BLEVE) modelling of LPG is also carried out. Dispersion modelling of toxic chemicals like chlorine, ammonia and benzene is carried out using the ALOHA air quality model. Threat zones for different hazardous storages are estimated based on the consequence modelling. The distance covered by the threat zone was found to be maximum for chlorine release from a chlor-alkali industry located in the area. The results of consequence modelling are useful for the estimation of individual risk and societal risk in the above industrial area.Vulnerability assessment is carried out using probit functions for toxic, thermal and pressure loads. Individual and societal risks are also estimated at different locations. Mapping of threat zones due to different incident outcome cases from different MAH industries is done with the help of Are GIS.Fault Tree Analysis (FTA) is an established technique for hazard evaluation. This technique has the advantage of being both qualitative and quantitative, if the probabilities and frequencies of the basic events are known. However it is often difficult to estimate precisely the failure probability of the components due to insufficient data or vague characteristics of the basic event. It has been reported that availability of the failure probability data pertaining to local conditions is surprisingly limited in India. This thesis outlines the generation of failure probability values of the basic events that lead to the release of chlorine from the storage and filling facility of a major chlor-alkali industry located in the area using expert elicitation and proven fuzzy logic. Sensitivity analysis has been done to evaluate the percentage contribution of each basic event that could lead to chlorine release. Two dimensional fuzzy fault tree analysis (TDFFTA) has been proposed for balancing the hesitation factor invo1ved in expert elicitation .

Evaluation of cyanobacteria for biomass production and effluent treatment

The microalgae gained importance as food and feed as well as source of fine chemicals since the l960’s. Spirulina became the trend setter due to its easily culturable properties as well as nutritional composition. A rapid expansion of microalgal industry occurred in the Asia-Pacific region as microalgae came to stay as a health food supplement. Microalgae have been an integral component of oxidation ponds usually incorporated with wastewater treatment. Over the last few decades, efforts have been made to apply intensive microalgal cultures to perform biological tertiary treatment of secondary effluents. Given the limited number of species still available for commercial exploitation, it is imperative to isolate and cultivate those photosynthetic organisms with high growth rate and biomass accumulation, which could play the dual role of cleaning the wastewater and also providing useful biomass. This has been the objective of this study ie. 0 To develop pure cultures of local isolates of Cyanobacteria for extraction of biochemicals of commercial value 0 To couple biomass production with effluent treatment

Studies on seed pathology and seedling diseases of some important indigenous tree species of kerala

In forestry, availability of healthy seeds is an important factor in raising planting stock. Initial seed health and storage conditions are the major factors governing the germinability of seeds. Like seeds of agricultural and horticultural crops, forest tree seeds are also liable to be affected by micro-organisms during storage, which affects the germination, and reduces the viability. Further introduction of seed-borne diseases into newly sown crops/areas on account of using unhealthy seeds is also not ruled out. Availability of healthy stock of seedlings is intrinsic for raising plantations and to meet this requirement elimination of nursery diseases by appropriate chemicals is of prime imortance. As exotic tree species may become susceptible to various native pathogens, it is generally considered better to select indigenous tree species for large scale plantations as they are well adapted to local environment. However, before taking up large scale afforestation progranme involving any indigenous tree species, it is essential to have knowledge about seed disorders and seedling diseases and their management. with a View to select appropriate tree species with fewer seed disorders and seedling disease problems for use in further plantation programme, four indigenous tree species such as Albizia odoratissima (L.f) Benth., Lagerstroemia microcazpa Wt., Pterocazpus marsupiwn Roxb. and Xylia xylocarpa (Roxb.) Taub. were evaluated to meet the above parameters

“Studies on glucose tolerant β-glucosidases from a novel Byssochlamys fulva and their applications in biomass to ethanol conversion”

Beta-glucosidases are critical enzymes in biomass hydrolysis process and is important in creating highly efficient enzyme cocktails for the bio-ethanol industry. Among the two strategies proposed for overcoming the glucose inhibition of commercial cellulases, one is to use heavy dose of BGL in the enzyme blends and the second is to do simultaneous saccharification and fermentation where glucose is converted to alcohol as soon as it is being generated. While the former needs extremely high quantities of enzyme, the latter is inefficient since the conditions for hydrolysis and fermentation are different. This makes the process technically challenging and also in this case, the alcohol generation is lesser, making its recovery difficult. A third option is to use glucose tolerant β-glucosidases which can work at elevated glucose concentrations. However, there are very few reports on such enzymes from microbial sources especially filamentous fungi which can be cultivated on cheap biomass as raw material. There has been very less number of studies directed at this, though there is every possibility that filamentous fungi that are efficient degraders of biomass may harbor such enzymes. The study therefore aimed at isolating a fungus capable of secreting glucose tolerant β- glucosidase enzyme. Production, characterization of β-glucosidases and application of BGL for bioethanol production were attempted.

Studies on the induction of variation through in vitro culture in Jatropha curcas L

Given the economic importance of Jatropha curcas, and its limited availability in the wild, it would be desirable to establish plantations ofthe tree so as to obtain assured supply of raw material for extraction of phytochemicals, and seeds for production of biodiesel. However both seed propagation as well as propagation by cuttings is unsatisfactory in this tree species. Seeds have poor viability and are genetically heterozygous leading to genetic variability in terms of growth, biomass, seed yield, and oil content. Stern cuttings have poor roots and the trees are easily uprooted. Tissue culture techniques could possibly be gainfully employed in the propagation of elite plants ofJaIropha. When plant tissue is passaged through in vitro culture, there is possibility of induction of variations. An estimation of somaclonal variability is useful in a determination of culture protocols. Molecular markers could be employed to estimate the amount of variations induced in callus and regenerants by different honnonal combinations used in culture. In this context the present study aims to develop an in vitro propagation protocol for the production of plantlets and to evaluate the variation induced in callus and regenerants in comparison with mother plant by the use of molecular markers and by studying phytochemicals and bio active compounds present in callus and regenerated plants

A Novel Decision Tree Algorithm for Numeric Datasets - C 4.5*Stat

Decision trees are very powerful tools for classification in data mining tasks that involves different types of attributes. When coming to handling numeric data sets, usually they are converted first to categorical types and then classified using information gain concepts. Information gain is a very popular and useful concept which tells you, whether any benefit occurs after splitting with a given attribute as far as information content is concerned. But this process is computationally intensive for large data sets. Also popular decision tree algorithms like ID3 cannot handle numeric data sets. This paper proposes statistical variance as an alternative to information gain as well as statistical mean to split attributes in completely numerical data sets. The new algorithm has been proved to be competent with respect to its information gain counterpart C4.5 and competent with many existing decision tree algorithms against the standard UCI benchmarking datasets using the ANOVA test in statistics. The specific advantages of this proposed new algorithm are that it avoids the computational overhead of information gain computation for large data sets with many attributes, as well as it avoids the conversion to categorical data from huge numeric data sets which also is a time consuming task. So as a summary, huge numeric datasets can be directly submitted to this algorithm without any attribute mappings or information gain computations. It also blends the two closely related fields statistics and data mining

Prediction of Learning Disabilities in School Age Children using SVM and Decision Tree

This paper highlights the prediction of Learning Disabilities (LD) in school-age children using two classification methods, Support Vector Machine (SVM) and Decision Tree (DT), with an emphasis on applications of data mining. About 10% of children enrolled in school have a learning disability. Learning disability prediction in school age children is a very complicated task because it tends to be identified in elementary school where there is no one sign to be identified. By using any of the two classification methods, SVM and DT, we can easily and accurately predict LD in any child. Also, we can determine the merits and demerits of these two classifiers and the best one can be selected for the use in the relevant field. In this study, Sequential Minimal Optimization (SMO) algorithm is used in performing SVM and J48 algorithm is used in constructing decision trees.

Biobutanol from lignocellulosic biomass by a novel Clostridium sporogenes BE01

In the current study, a novel non-acetone forming butanol and ethanol producer Was isolated and identified. Based on the 16s rDNA sequence BLAST and phylogenetic analyses, it was found to have high similarity with the reported hydrogen producing strains of Clostridium sporogenes. Biochemical studies revealed that it is lipase and protease positive. The lipolytic and proteolytic properties are the very important characteristics of Clostridium sporogenes. Sugar utilization profile studies were positive for glucose, saccharose, cellobiose and weakly positive result to xylose. This study demonstrated C. sporogenes BE01, an isolate from NIIST is having potential to compete with existing, well known butanol producers with the advantage of no acetone in the final solvent mixture. Rice straw hydrolysate is a potent source of substrate for butanol production by C. sporogenes BE01. Additional supplementation of vitamins and minerals were avoided by using rice straw hydrolysate as substrate. Its less growth, due to the inhibitors present in the hydrolysate and also inhibition by products resulted in less efficient conversion of sugars to butanol. Calcium carbonate played an important role in improving the butanol production, by providing the buffering action during fermentation and stimulating the electron transport mediators and redox reactions favoring butanol production. Its capability to produce acetic acid, butyric acid and hydrogen in significant quantities during butanol production adds value to the conversion process of lignocellulosic biomass to butanol. High cell density fermentation by immobilizing the cells on to ceramic particles improved the solvents and VFA production. Reduced sugar utilization from the concentrated hydrolysate could be due to accumulation of inhibitors in the hydrolysate during concentration. Two-stage fermentation was very efficient with immobilized cells and high conversions of sugars to solvents and VFAs were achieved. The information obtained from the study would be useful to develop a feasible technology for conversion of lignocellulosic biomass to biobutanol.