93 research outputs found
Recrystallization Texture Development in CP-Titanium
Most of the structural components are subjected to annealing as a final forming operation for different applications. It is therefore very important to understand/know the texture development during annealing of a material. This will decide the mechanical property of the component. Annealing texture of cubic crystal system has been widely researched, but little work has been done for the hexagonal close-packing materials. In the present study recrystallization texture development in CP-titanium was investigated. CP-titanium plates were subjected to cold rolling of 90% reduction in thickness. The rolled samples were then subjected to isochronal annealing at 5000C, 6000C and 7000C for 30minutes to obtain the recrystallization temperature, determined by EBSD analysis. Final annealing was carried out at 600oC for different soaking time: 10sec, 20sec, 1min, 2min, 5min, 10min, 20min and 30min to establish the texture development during annealing. These annealed samples were subsequently characterized under XRD (X-ray Diffraction) for bulk texture measurement. The initial deformation texture i.e. (1 1 -2 4) got attenuated with time and development of new basal orientation i.e. (0 0 0 1) and non-basal orientations i.e. (2 1 -3 7), (3 1 -4 9) and (5 1 -6 15) were observed
ADVENTURES ON NETWORKS: DEGREES AND GAMES
A network consists of a set of nodes and edges with the edges representing pairwise connections between nodes. Examples of real-world networks include the Internet, the World Wide Web, social networks and transportation networks often modeled as random graphs. In the first half of this thesis, we explore the degree distributions of such random graphs. In homogeneous networks or graphs, the behavior of the (generic) degree of a single node is often thought to reflect the degree distribution of the graph defined as the usual fractions of nodes with given degree. To study this preconceived notion, we introduce a general framework to discuss the conditions under which these two degree distributions coincide asymptotically in large random networks. Although Erdos-Renyi graphs along with other well known random graph models satisfy the aforementioned conditions, we show that there might be homogeneous random graphs for which such a conclusion may fail to hold. A counterexample to this common notion is found in the class of random threshold graphs. An implication of this finding is that random threshold graphs cannot be used as a substitute to the Barabasi-Albert model for scale-free network modeling, as proposed in some works.
Since the Barabasi-Albert model was proposed, other network growth models were introduced that were shown to generate scale-free networks. We study one such basic network growth model, called the fitness model, which captures the inherent attributes of individual nodes through fitness values (drawn from a fitness distribution) that influence network growth. We characterize the tail of the network-wide degree distribution through the fitness distribution and demonstrate that the fitness model is indeed richer than the Barabasi-Albert model, in that it is capable of producing power-law degree distributions with varying parameters along with other non-Poisson degree distributions.
In the second half of the thesis, we look at the interactions between nodes in a game-theoretic setting. As an example, these nodes could represent interacting agents making decisions over time while the edges represent the dependence of their payoffs on the decisions taken by other nodes. We study learning rules that could be adopted by the agents so that the entire system of agents reaches a desired operating point in various scenarios motivated by practical concerns facing engineering systems. For our analysis, we abstract out the network and represent the problem in the strategic-form repeated game setting.
We consider two classes of learning rules -- a class of better-reply rules and a new class of rules, which we call, the class of monitoring rules. Motivated by practical concerns, we first consider a scenario in which agents revise their actions asynchronously based on delayed payoff information. We prove that, under the better-reply rules (when certain mild assumptions hold), the action profiles played by the agents converge almost surely to a pure-strategy Nash equilibrium (PSNE) with finite expected convergence time in a large class of games called generalized weakly acyclic games (GWAGs). A similar result is shown to hold
for the monitoring rules in GWAGs and also in games satisfying a payoff interdependency structure. Secondly, we investigate a scenario in which the payoff information is unreliable, causing agents to make erroneous decisions occasionally. When the agents follow the better-reply rules and the payoff information becomes more accurate over time, we demonstrate the agents will play a PSNE with probability tending to one in GWAGs. Under a similar setting, when the agents follow the monitoring rule, we show that the action profile weakly converges to certain characterizable PSNE(s). Finally, we study a scenario where an agent might erroneously execute an intended action from time to time. Under such a setting, we show that the monitoring rules ensure that the system reaches PSNE(s) which are resilient to deviations by potentially multiple agents
Fick-Jacobs description and first passage dynamics for diffusion in a channel under stochastic resetting
Transport of particles through channels is of paramount importance in
physics, chemistry and surface science due to its broad real world
applications. Much insights can be gained by observing the transition paths of
a particle through a channel and collecting statistics on the lifetimes in the
channel or the escape probabilities from the channel. In this paper, we
consider the diffusive transport through a narrow conical channel of a Brownian
particle subject to intermittent dynamics, namely, stochastic resetting. As
such, resetting brings the particle back to a desired location from where it
resumes its diffusive phase. To this end, we extend the Fick-Jacobs theory of
channel-facilitated diffusive transport to resetting-induced transport. Exact
expressions for the conditional mean first passage times, escape probabilities
and the total average lifetime in the channel are obtained, and their behaviour
as a function of the resetting rate are highlighted. It is shown that resetting
can expedite the transport through the channel -- rigorous constraints for such
conditions are then illustrated. Furthermore, we observe that a carefully
chosen resetting rate can render the average lifetime of the particle inside
the channel minimal. Interestingly, the optimal rate undergoes continuous and
discontinuous transitions as some relevant system parameters are varied. The
validity of our one-dimensional analysis and the corresponding theoretical
predictions are supported by three-dimensional Brownian dynamics simulations.
We thus believe that resetting can be useful to facilitate particle transport
across biological membranes -- a phenomena that can spearhead further
theoretical and experimental studies
Controlled coalescence-induced droplet jumping on flexible superhydrophobic substrates
Sessile droplets coalescing on superhydrophobic substrates spontaneously jump
from the surface. In this process, the excess surface energy available at the
initiation of coalescence overcomes the minimal surface adhesion and manifests
as sufficient kinetic energy to propel the droplets away from the substrate.
Here, we show that the coalescence induced droplet jumping velocity is
significantly curtailed if the superhydrophobic substrate is flexible in
nature. Through detailed experimental measurements and numerical simulations,
we demonstrate that the droplet jumping velocity and jumping height can be
reduced by as much as 40 % and 64%, respectively, by synergistically tuning the
substrate stiffness and substrate frequency. We show that this hitherto
unexplored aspect of droplet coalescence jumping can be gainfully exploited in
water harvesting from dew and fog harvesting. Additionally, through an exemplar
butterfly wing substrate, we demonstrate that this effect is likely to manifest
on many natural superhydrophobic substrates due to their inherent flexibility
Bandwidth Optimal Pipeline Schedule for Collective Communication
We present a strongly polynomial-time algorithm to generate bandwidth optimal
allgather/reduce-scatter on any network topology, with or without switches. Our
algorithm constructs pipeline schedules achieving provably the best possible
bandwidth performance on a given topology. To provide a universal solution, we
model the network topology as a directed graph with heterogeneous link
capacities and switches directly as vertices in the graph representation. The
algorithm is strongly polynomial-time with respect to the topology size. This
work heavily relies on previous graph theory work on edge-disjoint spanning
trees and edge splitting. While we focus on allgather, the methods in this
paper can be easily extended to generate schedules for reduce, broadcast,
reduce-scatter, and allreduce
Primary transitional cell carcinoma of bulbar urethra
Primary urethral carcinoma (UC) is a rare entity, and bulbar UCs of transitional cell origin are even rarer. Primary presentation as a scrotal abscess and urethrocutaneous fistula is rarely documented in UC patients. We present a case of a 66-year-old male presenting to emergency department with a scrotal abscess. Following blind incision and drainage, the urethral injury was suspected, and biopsy of suspicious lesion was taken from scrotum which came out to be invasive transitional cell carcinoma. A wide local excision of the tumor was done after workup. Hence, all patients with scrotal abscess and urethrocutaneous fistula should be investigated before performing any blind procedure
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