309 resultados para Stochastic Behaviour
Resumo:
Phase transformation behaviour of amorphous electroless Ni-B coating with a targeted composition of Ni-6wt% B is characterized in conjunction with microstructural development and hardness. Microscopic observations of the as-deposited coating display a novel microstructure which is already phase separated at multiple length scales. Spherical colonies of similar to 5 mu m consist of 2-3 mu m nodular regions which are surrounded by similar to 2-3 mu m region that contains fine bands ranging from 10 to 70 nm in width. The appearance of three crystalline phases in this binary system at different stages of heat treatment and the concomitant variation in hardness are shown to arise from nanoscale fluctuations in the as-deposited boron content from 4 to 8 wt%. High temperature annealing reveals continuous crystallization up to 430 degrees C, overlapping with the domain of B loss due to diffusion into the substrate. The implications of such a microstructure for optimal heat treatment procedures are discussed. (C) 2011 Elsevier B.V. All rights reserved.
Resumo:
We present two efficient discrete parameter simulation optimization (DPSO) algorithms for the long-run average cost objective. One of these algorithms uses the smoothed functional approximation (SFA) procedure, while the other is based on simultaneous perturbation stochastic approximation (SPSA). The use of SFA for DPSO had not been proposed previously in the literature. Further, both algorithms adopt an interesting technique of random projections that we present here for the first time. We give a proof of convergence of our algorithms. Next, we present detailed numerical experiments on a problem of admission control with dependent service times. We consider two different settings involving parameter sets that have moderate and large sizes, respectively. On the first setting, we also show performance comparisons with the well-studied optimal computing budget allocation (OCBA) algorithm and also the equal allocation algorithm. Note to Practitioners-Even though SPSA and SFA have been devised in the literature for continuous optimization problems, our results indicate that they can be powerful techniques even when they are adapted to discrete optimization settings. OCBA is widely recognized as one of the most powerful methods for discrete optimization when the parameter sets are of small or moderate size. On a setting involving a parameter set of size 100, we observe that when the computing budget is small, both SPSA and OCBA show similar performance and are better in comparison to SFA, however, as the computing budget is increased, SPSA and SFA show better performance than OCBA. Both our algorithms also show good performance when the parameter set has a size of 10(8). SFA is seen to show the best overall performance. Unlike most other DPSO algorithms in the literature, an advantage with our algorithms is that they are easily implementable regardless of the size of the parameter sets and show good performance in both scenarios.
Resumo:
We analyze the AlApana of a Carnatic music piece without the prior knowledge of the singer or the rAga. AlApana is ameans to communicate to the audience, the flavor or the bhAva of the rAga through the permitted notes and its phrases. The input to our analysis is a recording of the vocal AlApana along with the accompanying instrument. The AdhAra shadja(base note) of the singer for that AlApana is estimated through a stochastic model of note frequencies. Based on the shadja, we identify the notes (swaras) used in the AlApana using a semi-continuous GMM. Using the probabilities of each note interval, we recognize swaras of the AlApana. For sampurNa rAgas, we can identify the possible rAga, based on the swaras. We have been able to achieve correct shadja identification, which is crucial to all further steps, in 88.8% of 55 AlApanas. Among them (48 AlApanas of 7 rAgas), we get 91.5% correct swara identification and 62.13% correct R (rAga) accuracy.
Resumo:
This research is focused on understanding the role of microstructural variables and processing parameters in obtaining optimised dual phase structures in medium carbon low alloy steels. Tempered Martensite structures produced at 300, 500, and 650 degrees C, were cold rolled to varied degrees ranging from 20 to 80% deformation. Intercritical annealing was then performed at 740, 760, and 780 degrees C for various time duration ranging from 60 seconds to 60 minutes before quenching in water. The transformation behaviour was studied with the aid of optical microscopy and hardness curves. From the results, it is observed that microstructural condition, deformation, and intercritical temperatures influenced the chronological order of the competing stress relaxation and decomposition phase reactions which interfered with the rate of the expected alpha -> gamma transformation. The three unique transformation trends observed are systematically analyzed. It was also observed that the 300 and 500 degrees C tempered initial microstructures were unsuitable for the production of dual structures with optimized strength characteristics.