Roschen Sasikumar

Competition between nucleation and early growth of ferrite from austenite—studies using cellular automaton simulations

Abstract A model for the nucleation of ferrite on austenite grain boundaries and the growth of these nuclei along the grain boundary and into the grain, is developed. A cellular automaton algorithm, with transformation rules based on this model, is used to simulate the decomposition of austenite into ferrite. When performed under continuous cooling conditions, the simulations give an insight into the competition between nucleation and early growth, which determines the variation of ferrite grain size with the cooling rate and with austenite grain size. The number of ferrite grains per austenite grain, ferrite grain size and the kinetics of ferrite formation are obtained as a function of the cooling rate and austenite grain size. Contour plots of the volume fraction of ferrite in the cells at different times, enables visualization of the ferrite growth process.

Chaos game representation for comparison of whole genomes.

BackgroundChaos game representation of genome sequences has been used for visual representation of genome sequence patterns as well as alignment-free comparisons of sequences based on oligonucleotide frequencies. However the potential of this representation for making alignment-based comparisons of whole genome sequences has not been exploited.ResultsWe present here a fast algorithm for identifying all local alignments between two long DNA sequences using the sequence information contained in CGR points. The local alignments can be depicted graphically in a dot-matrix plot or in text form, and the significant similarities and differences between the two sequences can be identified. We demonstrate the method through comparison of whole genomes of several microbial species. Given two closely related genomes we generate information on mismatches, insertions, deletions and shuffles that differentiate the two genomes.ConclusionAddition of the possibility of large scale sequence alignment to the repertoire of alignment-free sequence analysis applications of chaos game representation, positions CGR as a powerful sequence analysis tool.

Intelligent design of feeders for castings by augmenting CAD with genetic algorithms

The design of feeders for castings has been mostly based on empirical rules, heuristics and past experience. This paper presents a novel approach to the problem by augmenting genetic algorithms with CAD to optimize the feeder dimensions. The synergy of CAD and genetic algorithms generates a class of optimal feeders that also satisfy the standard criteria laid down in literature. A CAD platform is used as the front-end to create the solid model of the casting, divide it into feeding sections and calculate the volume and surface area of each feeding section. The feeding sections are made such that each section satisfies the feedpath requirement and ensures a critical modulus gradient. The genetic algorithm works on this data to design feeders keeping the yield as the optimization parameter and simultaneously satisfying the constraints of minimum volume and modulus.

Size and Morphology of Gas Porosity in Castings—Insights into Computational Experiments Using a Cellular Automaton Model

Aluminium castings are known to be prone to micro-porosity formation which appears as fine porosity in the inter-dendritic and inter-granular regions of castings. The size, distribution and morphology of such pores significantly affect mechanical and fatigue properties of castings. We use a cellular automaton simulation model as a virtual experimental set-up to study growth of gas bubbles in solidifying aluminium castings. The model assumes that gas porosity originates from pre-existing micro-bubbles that grow by diffusion of hydrogen from the solid–liquid interfaces into the bubbles. The major factors that limit the growth of the bubbles are the finite time available for the diffusion of hydrogen and the space constraint imposed by the growing solid. While the diffusion limitation to pore growth has been studied well, the effect of the space constraint has not received much attention. Our cellular automaton model with growth rules specially adapted for bubble growth tracks the solid–liquid and bubble–liquid interfaces explicitly on a fine grid. Numerical experiments are performed with a eutectic Al–Si alloy solidified with different grain sizes and solidification rates. The micro-structural environment in which a pre-existing bubble finds itself is seen to be the most critical factor that determines the final size and morphology of porosity.

Indigenous Development and Industrial Application of Metal Casting Simulation Software

Metal casting is a multi-physics process involving many physical phenomena like fluid flow, phase transformation, heat transfer, microstructure evolution, defect formation and thermal stresses. Virtual casting based on process modeling and computer simulation of the above phenomena enables foundry engineers to reduce physical trials, and optimize various process parameters to achieve the desired quality and yield. A multi-disciplinary team of researchers from IIT Bombay and CSIR-NIIST combined their work in casting design and simulation, respectively, and teamed up with 3D Foundry Tech to create an integrated software package called AutoCAST FLOW+. Foundry engineers are able to visualize mold filling, temperature profiles during casting solidification and cooling curves; predict related defects like air blow hole, cold shut, shrinkage porosity and hard zones; and optimize the feeding and gating design. Two industrial case studies demonstrating its successful application for quality improvement are presented. The software has been implemented in several engineering institutes, raising the awareness and interest among students as well as teachers in metal casting field. These efforts are expected to lead to indigenous capability in casting simulation technology suitable for the local requirements.

VOLUME SEGMENTATION BY POST-PROCESSING DATA FROM SIMULATION OF SOLIDIFICATION IN THE METAL CASTING PROCESS

In the process of interpreting simulation results, new post-processing techniques are developed. This work presents a post-processing method that analyzes the solidification pattern formed by simulation of the solidification process of molten metal in a mold to produce shaped castings. Simulations generally involve numerical solutions of differential equations which are discretized by dividing the three-dimensional computational domain into small finite volume elements using a 3D grid. The locations of the grid points and values of the solidification time at these locations are used to divide the spatial data into 3D sections such that starting from a hotspot location within the section that has high solidification time, there is a gradient outwards with lower values of solidification time. Each section is assumed to be fed by one or more feeders that must freeze only after the section has solidified completely. The volume of a feeder can be determined from the volume of the section it is supposed to feed. The volume and surface area of sections are determined approximately to calculate feeder size and dimensions. The post-processing algorithm is a simulation-based quantitative approach to feeder design which in conventional foundry practice has been more of an art than science. It is also general enough for use in other 3D segmentation applications.

An Alternate Hypothesis for the Origin of Mitochondria

The currently accepted view on the origin of mitochondria and chloroplasts is that mitochondria came into being by endosymbiosis of an α-proteobacterium by a proto-eukaryote and chloroplasts arose later by endosymbiosis of a cyanobacterium by an already “mitochondriate” eukaryote. However, the unique capability of cyanobacteria to perform both oxygenic photosynthesis and aerobic respiration prompts a more parsimonious hypothesis that a single endosymbiotic uptake of a cyanobacterium could have led to the birth of both the organelles. Such a hypothesis seems to have escaped any serious consideration probably because of the molecular phylogenetic evidence based on aminoacid sequences in favor of an α-proteobacterial ancestry of mitochondria. Molecular phylogenetics is a powerful tool for probing ancestral relationships, but it is known not to be infallible. We bring together arguments such as parsimony, timing of evolutionary and geological events, structural and functional similarity of cyanobacterial membranes to both the organellar membranes and molecular evidence based on nucleotide sequence comparisons, so as to create the plausibility of this alternate hypothesis.