Alloy optimisation of bainitic steel for large plastic mould

Based on the phase transformation theories, especially the T₀ concept of bainite transformation, alloy optimisation of bainitic steel with carbides has been carried out aiming at the produce of plastic mould with large cross-section. The effect of manganese and silicon on proeutectoid ferrite and bainite transformation is explored by dilatometric analysis, XRD and different microscopy techniques. The results show that after the alloy optimisation, the transformation of proeutectoid ferrite is suppressed and when the cooling rate is lower than 0·1°C?s^??1, the new lower bainite transformation appears by decreasing carbon capacity of austenite and promoting carbide precipitation. Industrial production proves that the optimised alloy SDP1 can meet the demand for the plastic mould with the thickness of 1050?mm.     

Linear friction welding of Ti6Al4V: experiments and modelling

Linear friction welding of the Ti6Al4V alloy is studied. A new definition of the energy input rate is proposed, based on an integration over time of the in-plane force and velocity; a strong correlation with the upset rate is then found. The effective friction coefficient is estimated to be 0·5±0·1 for varying frequencies and amplitudes, with only a weak dependence on the processing conditions displayed. A model is proposed that accounts for both the conditioning and equilibrium stages of the process, which is shown to be in good agreement with the experimental data. The model is used to study the mechanism by which the flash is formed. A criterion is proposed by which the rippled nature of its morphology can be predicted.     

Prediction of rock mass P wave velocity using blasthole drilling information

In this paper, the development of the models for the prediction of rock mass P wave velocity is presented. For model development, the database of 53 cases including widely used and recorded drilling parameters and P wave velocity was constructed from the field studies conducted in 13 open pit lignite mines. Both conventional linear, non-linear multiple regression and Adaptive Neuro Fuzzy Inference System (ANFIS) were used for model development. Prediction performance indicators showed that ANFIS model presented the best performance and it can successfully be used for the preliminary prediction of P wave velocities of rock masses.     

Deep Neural Networks for Determining the Parameters of Buildings from Single-Shot Satellite Imagery

Journal of Computer and Systems Sciences International - The height of a building is a basic characteristic needed for analytical services. It can be used to evaluate the population and functional...     

PRATIT: a CNN-based emotion recognition system using histogram equalization and data augmentation

Multimedia Tools and Applications - Emotions are spontaneous feelings that are accompanied by fluctuations in facial muscles, which leads to facial expressions. Categorization of these facial...     

Inferring kinetic dissolution of NaCl in aqueous glycol solution using a low-cost apparatus and population balance model

An experimental methodology for inferring brine dissolution rate in monoethylene glycol (MEG) solutions at different temperatures using a webcam combined with a mathematical model is presented. The measurement system is designed to track the RGB (red, green, and blue) colour variations during the dissolution process. A dynamic model augmented with the population balance equation is applied to describe the dissolution process. Moreover, the dissolution rate is consistently related to the temperature and MEG concentration through the driving force based on the Gibbs energy and chemical affinity. The applied low-cost measurement apparatus proved to be a useful resource for tracking the dissolution dynamics in a wide range of undersaturation.     

Methodology for optimization of pouring variables using bottom pour for low masses of SS304 (<300 kg) in investment casting process (case study)

Bottom pour ladles with stopper rod systems are commonly used in the metal casting industry. However, stopper rod bottom-pouring systems have not yet been developed for the lower thermal masses of alloys typically used in the investment casting industry. Large thermal masses used with bottom pour systems are typically limited for ladles larger than 700 kg and to certain alloys with higher fluidity and longer solidification time like cast iron, aluminum alloys etc. In this study, bottom pour ladle designs and low thermal mass refractory systems have been developed and evaluated in production investment foundry trials with 300 kg pouring ladle. The ladles system and pouring practices used will be described along with the results from the pouring trials for SS304 that represents typical alloys used in Investment casting industries. Optimization of the variables used in an experimentation using Genetic algorithm is also explained.