Investigation of thermal residual stresses during laser ablation of tantalum carbide coated graphite substrates using micro-Raman spectroscopy and COMSOL multiphysics

Laser ablation of high-temperature ceramic coatings results in thermal residual stresses due to which the coatings fail by cracking and debonding. Hence, the measurement of such residual stresses during laser ablation process holds utmost importance from the view of performance of coatings in extreme conditions. The present research aims at investigating the effect of laser parameters such as laser pulse energy, scanning speed and line spacing on thermal residual stresses induced in tantalum carbide-coated graphite substrates. Residual stresses were measured using micro-Raman spectroscopy and correlated with Raman peak shifts. Transient thermal analysis was performed using COMSOL Multiphysics to model the single ablated track and residual stresses were reported at low, moderate and high pulse energy regimes. The results showed that the initial laser conditions caused higher tensile residual stresses. Moderate pulse energy regime comprised higher compressive residual stresses due to off centre overlapping of the laser pulses. Higher pulse energy (250 μJ), higher scanning speed (1000 mm/s) and moderate line spacing (20 μm) caused accumulation of tensile residual stresses during the final stage of laser ablation. The deviation of experimental residual stresses from COMSOL numerical model was attributed to unaccounted additional stresses induced during thermal spraying process and deformation potentials in the numerical model.     

Towards finding the best-fit distribution for OSN data

The Journal of Supercomputing - Currently, all online social networks (OSNs) are considered to follow a power-law distribution. In this paper, the degree distribution for multiple OSNs has been...     

A simulation study of reduction kinetics for sponge iron production in a rotary hearth furnace

ABSTRACT

A mathematical model has been developed by coupling genetic algorithm (GA) with heat and material balance equations to estimate rate parameters and solid-phase evolution related to the reduction of iron ore-coal composite pellets in a multi-layer bed Rotary hearth Furnace (RHF). The present process involves treating iron ore-coal composite pellets in a crucible over the hearth in RHF. The various solid phases evolved at the end of the process are estimated experimentally, and are used in conjunction with the model to estimate rate parameters. The predicted apparent activation energy for the wustite reduction step is found to be lower than those of the reduction of higher oxides. The thermal efficiency is found to decrease significantly with an increase in the carbon content of the pellet. Thermal efficiency was also found to increase mildly up to three layers. Multilayer bed remains as a potential design parameter to increase thermal efficiency.     

Impact of Climate Change on Future Flood Susceptibility: an Evaluation Based on Deep Learning Algorithms and GCM Model

Floods are common and recurring natural hazards which damages is the destruction for society. Several regions of the world with different climatic conditions face the challenge of floods in different magnitudes. Here we estimate flood susceptibility based on Analytical neural network (ANN), Deep learning neural network (DLNN) and Deep boost (DB) algorithm approach. We also attempt to estimate the future rainfall scenario, using the General circulation model (GCM) with its ensemble. The Representative concentration pathway (RCP) scenario is employed for estimating the future rainfall in more an authentic way. The validation of all models was done with considering different indices and the results show that the DB model is most optimal as compared to the other models. According to the DB model, the spatial coverage of very low, low, moderate, high and very high flood prone region is 68.20%, 9.48%, 5.64%, 7.34% and 9.33% respectively. The approach and results in this research would be beneficial to take the decision in managing this natural hazard in a more efficient way.

     

Identifying crop water stress using deep learning models

Neural Computing and Applications - The identification of water stress is a major challenge for timely and effective irrigation to ensure global food security and sustainable agriculture. Several...     

An application of chemometric techniques to analyze the effects of the wave function modifications on the intermolecular stretching frequencies of the hydrogen-bonded complexes

Factorial design and principal component models are used to determine how ab initio H-bond stretching frequencies depend on characteristics of the molecular orbital wave functions of acetylene–HX, ethylene–HX and cyclopropane–HX π-type hydrogen complexes with X=F, Cl, CN, NC and CCH. The results obtained for the three sets of complexes show that factorial design and principal component analyses complement each other. Factorial design calculations clearly show that these frequencies are affected mostly by inclusion of electron correlation on the calculation level. On average, their values are increased by about 25 cm⁻¹ due to a change from the Hartree–Fock (HF) to Möller–Plesset 2 (MP2) level. Valence, diffuse and polarization main effects as well as valence–diffuse, diffuse–correlation and polarization–correlation interaction effects are also important to better describe a factorial model to the H-bond stretching frequencies of these hydrogen complexes. This simplified model has been successful in reproducing the complete ab initio results, which correspond to two hundred and forty calculations. Principal component analyses applied only to hydrogen-bonded complexes whose experimental frequencies are known, has revealed that the six-dimensional original space can be accurately represented by a bidimensional space defined by two principal components. Its graphical representation reveals that the experimental intermolecular stretching frequencies are in closest agreement with the MP2/6–31+G and MP2/6–311+G ab initio results.