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Parametric Study on the Axial Behaviour of Concrete Filled Steel Tube (CFST) Columns
Raghabendra Yadav,
Baochun Chen
Issue:
Volume 3, Issue 4, July 2017
Pages:
21-25
Received:
27 October 2016
Accepted:
17 December 2016
Published:
15 November 2017
Abstract: Concrete filled steel tube (CFST) columns are widely used in civil engineering structures due to its abundant structural benefits like excellent seismic behaviour, ultimate load bearing capacity, fire resistivity, excellent ductility and energy absorption capacity, particularly in zones of high seismic risk. Due to their excellent engineering properties, CFST columns are used in buildings, bridges, electric transmission line and offshore structures. The ultimate load carrying capacity of CFST columns depends upon various parameters such as D/t ratio, steel grade, concrete grade, etc. Abaqus software is used for the finite element modelling of CFST Columns. In this study the ultimate axial load carrying capacity of CFST column is investigated by changing diameter-to-thickness (D/t) ratio, steel grade and concrete grade. Results shows that the ultimate load capacity decreases by increase in D/t ratio but increases by increase in steel grade and concrete grade.
Abstract: Concrete filled steel tube (CFST) columns are widely used in civil engineering structures due to its abundant structural benefits like excellent seismic behaviour, ultimate load bearing capacity, fire resistivity, excellent ductility and energy absorption capacity, particularly in zones of high seismic risk. Due to their excellent engineering prope...
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Inhibition Effects of Cobalt Nano Particles Against Fresh Water Algal Blooms Caused by Microcystis and Oscillatoria
Anusha L.,
Chingangbam Sushmita Devi,
Sibi G.
Issue:
Volume 3, Issue 4, July 2017
Pages:
26-32
Received:
17 June 2017
Accepted:
28 June 2017
Published:
28 November 2017
Abstract: Cyanobacterial blooms deplete nutrients, reduce water clarity, exhaust carbon di oxide and produces secondary metabolites which negatively affect aquatic organisms and water quality. Control of algal blooms using metal nano particles is one effective method for the safety of water environment. Cobalt nano particles (CoNPs) were synthesized and tested against microalgae isolated from fresh water cyanobacterial blooms by assessing the effects on growth rate, biomass concentration, photosynthetic pigments concentration and antioxidant enzyme activity. Microcystis and Oscillatoria were identified as the predominant isolates from algal blooms and treated with varying concentrations (1, 2, 3, 4 and 5 mg·L-1) of CoNPs. Steady decline in the growth rate of microalgae was observed at the end of 5 days indicating the toxicity of CoNPs on microalgal growth. At the end of cultivation period, 78% and 88% of reduction in biomass concentration of Microcystis and Oscillatoria were observed at 5 mg·L-1 of CoNPs. The chlorophyll content was reduced from 1.53 to 0.24 mg·L-1 in Microcystis and 1.63 to 0.29 mg·L-1 in Oscillatoria. There was a 69.3% and 73.2% decrease in carotenoid content of Microcystis and Oscillatoria respectively. Both protein and carbohydrate contents of the microalgae were reduced with increasing concentration of nano particles. The decrease in Super oxide dismutase (SOD) activity with increased nanoparticle concentration reveals the formation of stress in the microalgae. The increasing GSH activity proved the effect of CoNPs on the activation of antioxidative enzymes to protect the cells. This study demonstrates the efficiency of cobalt nano particles (CoNPs) on inhibition of fresh water algal blooms thereby reducing the eutrophication problem.
Abstract: Cyanobacterial blooms deplete nutrients, reduce water clarity, exhaust carbon di oxide and produces secondary metabolites which negatively affect aquatic organisms and water quality. Control of algal blooms using metal nano particles is one effective method for the safety of water environment. Cobalt nano particles (CoNPs) were synthesized and test...
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G2EDPS's First Module & Its First Extension Modules
Issue:
Volume 3, Issue 4, July 2017
Pages:
33-48
Received:
27 February 2017
Accepted:
29 March 2017
Published:
28 November 2017
Abstract: 100% renewable worldwide power grid (Global Grid) system needs a Global Grid Electricity Demand Prediction System (G2EDPS) with very short, short, medium and long term forecasting consoles. This paper presents the 1st core module and its 10 extension modules in the long term prediction console. A type 1 Mamdani like Fuzzy Inference System (FIS) with 7 triangle membership functions and 49 rules is designed for 2 input and 1 output variables for a 100 year forecasting period. The maximum absolute percentage errors (MAP), the mean absolute percentage errors (MAPE), and the Symmetric MAPE (SMAPE) of the best core module and its extension modules are respectively 0, 24; 0, 08; 0, 05 and 0, 22; 0, 07; 0, 05.
Abstract: 100% renewable worldwide power grid (Global Grid) system needs a Global Grid Electricity Demand Prediction System (G2EDPS) with very short, short, medium and long term forecasting consoles. This paper presents the 1st core module and its 10 extension modules in the long term prediction console. A type 1 Mamdani like Fuzzy Inference System (FIS) wit...
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