Hot Ductility and Deformation Behavior of C-Mn/Nb-Microalloyed Steel Related to Cracking During Continuous Casting

Hot ductility studies have been performed on C-Mn and C-Mn-Nb steels with an approach to simulate the effect of cooling conditions experienced by steel in secondary cooling zone during continuous casting. Thermal oscillations prior to tensile straining deteriorate hot ductility of steel by deepening and widening the hot ductility trough. C-Mn steels are found to exhibit ductility troughs in three distinct zones whereas C-Mn-Nb steel shows drop in ductility only at low temperature in the vicinity of ferrite transformation temperatures. Start of ferrite transformation in steels causes yield ratio to increase while work hardening rates and strength coefficient decrease with decrease in test temperature in presence of thermal oscillation prior to tensile testing. Inhibition of recrystallization due to build-up of AlN particles along with the presence of MnS particles in structure and low work hardening rates causes embrittlement of steel in austenitic range. Alloying elements enhancing work hardening rates in austenitic range can be promoted to improve hot ductility. The presence of low melting phase saturated with impurities along the austenitic grain boundaries causes intergranular fracture at high temperature in C-Mn steels.     

Analysis of Traffic Impact on Proposed Congestion Control Scheme in AODV

Wireless Personal Communications - Congestion is a noteworthy problem in Mobile Ad hoc Network, which occurs when number of users increases and a node carries data more than its capacity. In this...     

Effect of Coiling Temperature on the Microstructure and Mechanical Properties of Hot-Rolled Ti–Nb Microalloyed Ultra High Strength Steel

A novel low carbon Ti–Nb microalloyed hot rolled steel with minimum yield strength of 700 MPa and good balance of stretch-flangeability and impact toughness has been developed by controlled thermo-mechanical processing following thin slab direct rolling route. In the present work, the effects of two coiling temperatures on the resulting microstructure, micro-texture and mechanical properties on this Ti–Nb microalloyed steel have been studied. It is observed that increase in coiling temperature from 520 to 580 °C significantly affects the mechanical properties. Higher dislocation density and increased precipitation along with slightly smaller grain size is observed for 580 °C coiling temperature resulting in about 50 MPa increase in yield and tensile strengths as compared to 520 °C coiling temperature.     

Mathematical model for predicting the thermal and mechanical behaviour of rebar during quenching and self tempering

A mathematical model has been developed to predict the thermal and phase transformation behaviour of plain carbon steel rebars having mass contents of carbon in the range of 0.10 to 0.18 %, during quenching and self tempering process. The model takes into account the operating parameters such as rebar diameter, rolling speed, finishing temperature of rebar leaving the last stand of hot rolling mills. The design features of cooling tube and water flow rate have also been included in the model. The phase transformation kinetics from austenite to martensite at the surface, bainite beneath the surface and ferrite and pearlite in the core has been incorporated in the model. An attempt has been made to predict the yield strength of rebars as a function of chemical composition and volume fractions of different phases. In-plant trials were conducted at Visakhapatnam Steel Plant for 10 and 18 mm diameter rebars. Tempering temperature was measured and volume fractions of different phases and mechanical properties were determined. A very good agreement was found between measured and predicted volume fractions of martensite, bainite and ferrite + pearlite. Comparison between predicted and measured yield strength values show a reasonably good agreement under industrial conditions.     

Review of background subtraction methods using Gaussian mixture model for video surveillance systems

Foreground detection or moving object detection is a fundamental and critical task in video surveillance systems. Background subtraction using Gaussian Mixture Model (GMM) is a widely used approach for foreground detection. Many improvements have been proposed over the original GMM developed by Stauffer and Grimson (IEEE Computer Society conference on computer vision and pattern recognition, vol 2, Los Alamitos, pp 246–252, 1999. doi: 10.1109/CVPR.1999.784637) to accommodate various challenges experienced in video surveillance systems. This paper presents a review of various background subtraction algorithms based on GMM and compares them on the basis of quantitative evaluation metrics. Their performance analysis is also presented to determine the most appropriate background subtraction algorithm for the specific application or scenario of video surveillance systems.