Evaluation of wear of turning carbide inserts using neural networks

Recent trends, being towards mostly unmanned automated machining systems and consistent system operations, need reliable on-line monitoring processes. A proper on-line cutting tool condition monitoring system is essential for deciding when to change the tool. Many methods have been attempted in this connection.Recently, artificial neural networks have been tried for this purpose because of its inherent simplicity and reasonably quick data-processing capability. The present work uses the back propagation algorithm for training the neural network of 5-3-1 structure. The technique shows close matching of estimation of average flank wear and directly measured wear value. Thus the system developed demonstrates the possibility of successful tool wear monitoring on-line.     

Study of polyaniline polyacrylamide composites by positron annihilation technique

Polyaniline doped with nonoxidizing Bronsted acids is recognized as a conducting material, as its electrical conductivity changes with percentage of doping. In the present work, different percentages of doped polyaniline were blended with polyacrylamide and their electrical conductivities as well as the positron annihilation lifetimes were measured. Analysis of data yielded three lifetime components. It was observed that the value of the short lifetime component remained constant for doping concentration, whereas that of the intermediate component τ₂ decreased. The relative intensity pertaining to τ₂, however, increased with the increase in doped PANI concentration. © 2003 Wiley Periodicals, Inc. J Appl Polym Sci 89: 930–933, 2003     

GPU accelerated novel particle filtering method

In this paper, a graphics processor unit (GPU) accelerated particle filtering algorithm is presented with an introduction to a novel resampling technique. The aim remains in the mitigation of particle impoverishment as well as computational burden, problems which are commonly associated with classical (systematic) resampled particle filtering. The proposed algorithm employs a priori-space dependent distribution in addition to the likelihood, and hence is christened as dual distribution dependent (D3) resampling method. Simulation results exhibit lesser values for root mean square error (RMSE) in comparison to that for systematic resampling. D3 resampling is shown to improve particle diversity after each iteration, thereby affecting the overall quality of estimation. However, computational burden is significantly increased owing to few excessive computations within the newly formulated resampling framework. With a view to obtaining parallel speedup we introduce a CUDA version of the proposed method for necessary acceleration by GPU. The GPU programming model is detailed in the context of this paper. Implementation issues are discussed along with illustration of empirical computational efficiency, as obtained by executing the CUDA code on Quadro 2000 GPU. The GPU enabled code has a speedup of 3 and 4 over the sequential executions of systematic and D3 resampling methods respectively. Performance both in terms of RMSE and running time have been elaborated with respect to different selections for threads per block towards effective implementations. It is in this context that, we further introduce a cost to performance metric (CPM) for assessing the algorithmic efficiency of the estimator, involving both quality of estimation and running time as comparative factors, transformed into a unified parameter for assessment. CPM values for estimators obtained from all such different choices for threads per block have been determined and a final value for the chosen parameter is resolved for generation of a holistic effective estimator.     

Al2O3─SiC Composites from Aluminosilicate Precursors

Al₂O₃ and SiC composite materials have been produced from mixtures of aluminosilicates (both natural minerals and synthetic) and carbon as precursor materials. These composites are produced by heating a mixture of kaolinite (or synthetic aluminosilicates) and carbon in stoichiometric proportion above 1550°C, so that only Al₂O₃ and SiC remain as the major phases. A similar process has also been used for synthesizing other composite powders having mixtures of Al₂O₃, SiC, TiC, and ZrO₂ in different proportions (all compounds together or selective mixtures of some of them), as desired. The microstructure of hot-pressed dense compacts, produced from these powders, revealed that the SiC phase is distributed very homogeneously, even occasionally within Al₂O₃ grains on a nanosize scale. The homogeneous distribution of SiC particles within the system produced high fracture toughness of the hot-pressed material (K_IC∼ 7.0 MPa · m^1/2) and having Vicker's hardness values greater than 2000 kgf/mm².     

The effect of feedstock and process conditions on the synthesis of high purity CNTs from aromatic hydrocarbons

High purity multi-walled carbon nanotubes were synthesized from aromatic hydrocarbons (benzene, toluene, xylene and trimethyl benzene) using ferrocene as the source of Fe catalyst. Screening studies of aromatic feeds at 675 °C, residence time of 14 s and Fe/C atom ratio of 1.07%, resulted in feedstock carbon conversion of 20-31%, CNT yield of 19.8-30.5%, and catalyst yield of 5.3-8.3 (g CNT/g catalyst). While the quality of the CNTs as determined by TGA, SEM, TEM and Raman spectroscopy, were high and comparable for different feedstocks; their carbon conversion, CNT yield and catalyst yield differed noticeably. A process optimization study for toluene feed showed that carbon conversion of more than 39%, CNT yield of 38.7% and catalyst yield of 18.3 can be achieved at temperature of 800 °C, Fe/C atom ratio of 0.47%, and residence time of 10-20 s.     

Aspects of poly(p-phenylene sulfide) degradation and stabilization. Part 1. Influence of polymer end groups on exposure induced coloration

In this paper we reviewed some of our work on the photo induced coloration of Poly(p-phenylene sulfide) (PPS) and compared it to recent results obtained from the thermal treatment of resins that varied in molecular weight and ionic content. The results from this study suggest that coloration of amorphous PPS films after UV irradiation is caused by products different from those that cause coloration in semicrystalline PPS after thermoxidation. In addition, we found that polymer end group chemistry and resin molecular weights play important roles in the thermoxidative coloration of PPS, but only nominally influence the photooxidative coloration of the resin. PPS coloration may arise from the accumulation of specific, colored products (e.g., phenyl-phenyl moieties) and the possible presence of intermolecular aggregates. The mechanism and extent by which these structures occur in UV irradiated or heated PPS are likely dependent upon the polymer morphology of the samples tested.     

Fischer–Tropsch synthesis: Deactivation of promoted and unpromoted cobalt–alumina catalysts

The loss in activity of Pt-promoted and unpromoted 25 wt% Co–Al₂O₃ catalysts has been compared under identical conditions except for adjustment of the space velocity to give the same initial CO-conversion. Both catalysts underwent a 200 h period of rapid, initial decline in CO conversion and then a slower, linear decline during the next 1000 h. Pt-promotion did not alter the cobalt dispersion (or average particle size) from that of the unpromoted catalyst but did increase the amount of cobalt that was reduced. When compared not by time-on-stream, but by the moles of Co converted per unit weight of catalyst, both the Pt-promoted and unpromoted catalysts decline in activity at the same rate.     

Victim retention for reducing cache misses in tiled chip multiprocessors

This paper presents CMP-VR (Chip-Multiprocessor with Victim Retention), an approach to improve cache performance by reducing the number of off-chip memory accesses. The objective of this approach is to retain the chosen victim cache blocks on the chip for the longest possible time. It may be possible that some sets of the CMPs last level cache (LLC) are heavily used, while certain others are not. In CMP-VR, some number of ways from every set are used as reserved storage. It allows a victim block from a heavily used set to be stored into the reserve space of another set. In this way the load of heavily used sets are distributed among the underused sets. This logically increases the associativity of the heavily used sets without increasing the actual associativity and size of the cache. Experimental evaluation using full-system simulation shows that CMP-VR has less off-chip miss-rate as compared to baseline Tiled CMP. Results are presented for different cache sizes and associativity for CMP-VR and baseline configuration. The best improvements obtained are 45.5% and 14% in terms of miss rate and cycles per instruction (CPI) respectively for a 4 MB, 4-way set associative LLC. Reduction in CPI and miss rate together guarantees performance improvement.