TUNING OF COMPONENT CHARACTERISTICS MAPS IN OFF DESIGN SIMULATION OF GAS TURBINES

A reliable simulation model is an essential component of health monitoring system for gas turbine engines. Hence a thermodynamic simulation model of a twin spool gas turbine engine is being developed for use in an engine health monitoring (EHM) system. This model is based on mass and energy conservation principles across each component of the gas turbine engine. The model is being developed with limited design point information and measured gas path parameters available from the test bed. Both on-design and off-design models are being developed in Matlab® programming environment. Component characteristics maps available in the open literature are being scaled and used in the off design simulation. The scaling parameters used in the maps are tuned to improve the agreement between simulation model and data collected from engine test bed. Both tuned and un-tuned results of the simulation along with their respective errors are presented. The scheme to incorporate the model in the physics based health monitoring module is also briefly presented. Conf Name: ISSS International Conference on Smart Materials, Structures and System

A conceptual framework for the adoption of big data analytics by e-commerce startups: a case-based approach

E-commerce start-ups have ventured into emerging economies and are growing at a significantly faster pace. Big data has acted like a catalyst in their growth story. Big data analytics (BDA) has attracted e-commerce firms to invest in the tools and gain cutting edge over their competitors. The process of adoption of these BDA tools by e-commerce start-ups has been an area of interest as successful adoption would lead to better results. The present study aims to develop an interpretive structural model (ISM) which would act as a framework for efficient implementation of BDA. The study uses hybrid multi criteria decision making processes to develop the framework and test the same using a real-life case study. Systematic review of literature and discussion with experts resulted in exploring 11 enablers of adoption of BDA tools. Primary data collection was done from industry experts to develop an ISM framework and fuzzy MICMAC analysis is used to categorize the enablers of the adoption process. The framework is then tested by using a case study. Thematic clustering is performed to develop a simple ISM framework followed by fuzzy analytical network process (ANP) to discuss the association and ranking of enablers. The results indicate that access to relevant data forms the base of the framework and would act as the strongest enabler in the adoption process while the company rates technical skillset of employees as the most important enabler. It was also found that there is a positive correlation between the ranking of enablers emerging out of ISM and ANP. The framework helps in simplifying the strategies any e-commerce company would follow to adopt BDA in future. © 2019, Springer-Verlag GmbH Germany, part of Springer Nature

Phytoremediation of heavy metal-contaminated sites: Eco-environmental concerns, field studies, sustainability issues and future prospects

Environmental contamination due to heavy metals (HMs) is of serious ecotoxicological concern worldwide because of their increasing use at industries. Due to non-biodegradable and persistent nature, HMs cause serious soil/water pollution and severe health hazards in living beings upon exposure. HMs can be genotoxic, carcinogenic, mutagenic, and teratogenic in nature even at low concentration. They may also act as endocrine disruptors and induce developmental as well as neurological disorders and thus, their removal from our natural environment is crucial for the rehabilitation of contaminated sites. To cope with HM pollution, phytoremediation has emerged as a low-cost and eco-sustainable solution to conventional physico-chemical cleanup methods that require high capital investment and labor alter soil properties and disturb soil microflora. Phytoremediation is a green technology wherein plants and associated microbes are used to remediate HM-contaminated sites to safeguard the environment and protect public health. Hence, in view of the above, the present paper aims to examine the feasibility of phytoremediation as a sustainable remediation technology for the management of metals-contaminated sites. Therefore, this paper provides an in-depth review on both the conventional and novel phytoremediation approaches, evaluate their efficacy to remove toxic metals from our natural environment, explore current scientific progresses, field experiences and sustainability issues and revise world over trends in phytoremediation research for its wider recognition and public acceptance as a sustainable remediation technology for the management of contaminated sites in 21st century

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Work done under ICMR extramural fund in collaboration with ICMR-National Institute of Cholera and Enteric Diseases (NICED), KolkataWhile searching for Escherichia coli O157 in the aquatic environment of Calcutta using an immunodetection procedure, we fortuitously detected five strains of Citrobacter braakii, which cross-reacted with the commercially available O157 polyvalent antiserum. The five C. braakii isolates gave positive results when a sensitive dot-ELISA was performed with E. coli O157 monoclonal antibody. Further, the O157 monoclonal antibody recognized the bands of proteinase K treated whole cells of lipopolysaccharide of all the C. braakii isolates. Apart from weak reactions with two or three of the DNA probes, all the C. braakii strains did not hybridize with the other probes spanning the minimum region required for O157 O-antigen biosynthesis. These strains did not possess any of the virulence genes that are commonly found in the Shiga toxin-producing E. coli (STEC) specially the serotype O157: H7. Therefore, it appears that the serological cross-reaction between C. braakii and E. coli O157 antiserum is based on structural mimicry between the O-polysaccharide of C. braakii and E. coli O157.ICMR New Delh