Enhancement of fatigue life of Ni-Ti-Fe shape memory alloys by thermal cycling

The effect of thermal cycling on the load-controlled tension-tension fatigue behavior of a Ni-Ti-Fe shape memory alloy (SMA) at room temperature was studied. Considerable strain accumulation was observed to occur in this alloy under both quasi-static and cyclic loading conditions. Though, in all cases, steady-state is reached within the first 50-100 cycles, the accumulated steady-state strain, epsilon(p.ss), is much smaller in thermally cycled alloy. As a result, the fatigue performance of them was found to be significantly enhanced vis-a-vis the as-solutionized alloy. Furthermore, under load-controlled conditions, the fatigue life of Ni-Ti-Fe alloys was found to be exclusively dependent on epsilon(p.ss). Observations made by profilometry and differential scanning calorimetry (DSC) indicate that the 200-500% enhancement in fatigue life of thermally cycled alloy is due to the homogeneous distribution of the accumulated fatigue strain. (C) 2010 Elsevier B.V. All rights reserved.

A near-optimal initial seed value selection in K-means means algorithm using a genetic algorithm

The K-means algorithm for clustering is very much dependent on the initial seed values. We use a genetic algorithm to find a near-optimal partitioning of the given data set by selecting proper initial seed values in the K-means algorithm. Results obtained are very encouraging and in most of the cases, on data sets having well separated clusters, the proposed scheme reached a global minimum.

Aperiodic Variability in the Cane-Zebiak Model: A Diagnostic Study

The finite predictability of the coupled ocean-atmosphere system is determined by its aperiodic variability. To gain insight regarding the predictability of such a system, a series of diagnostic studies has been carried out to investigate the role of convergence feedback in producing the aperiodic behavior of the standard version of the Cane-Zebiak model. In this model, an increase in sea surface temperature (SST) increases atmospheric heating by enhancing local evaporation (SST anomaly feedback) and low-level convergence (convergence feedback). The convergence feedback is a nonlinear function of the background mean convergence field. For the set of standard parameters used in the model, it is shown that the convergence feedback contributes importantly to the aperiodic behaviour of the model. As the strength of the convergence feedback is increased from zero to its standard value, the model variability goes from a periodic regime to an aperiodic regime through a broadening of the frequency spectrum around the basic periodicity of about 4 years. Examination of the forcing associated with the convergence feedback reveals that it is intermittent, with relatively large amplitude only during 2 or 3 months in the early part of the calendar year. This seasonality in the efficiency of the convergence feedback is related to the strong seasonality of the mean convergence over the eastern Pacific. It is shown that if the mean convergence field is fixed at its March value, aperiodic behavior is produced even in the absence of annual cycles in the other mean fields. On the, other hand, if the mean convergence field is fixed at its September value, the coupled model evolution remains close to periodic, even in the presence of the annual cycle in the other fields. The role of convergence feedback on the aperiodic variability of the model for other parameter regimes is also examined. It is shown that a range exists in the strength of the SST anomaly feedback for which the model variability is aperiodic even without the convergence feedback. It appears that in the absence of convergence feedback, enhancement of the strength of the air-sea coupling in the model through other physical processes also results in aperiodicity in the model.

Enhancement of Surface Flashover Performance of High Voltage Ceramic Disc Insulators

In this paper, an effort is made to study accurately the field distribution for various types of ceramic insulators used for high-voltage transmission. The surface charge simulation method (SCSM) is employed for the field computation. With the help of SCSM program, a Novel field reduction electrode is designed and developed to reduce the maximum field around the pin region. In order to experimentally analyze the performance of discs with field reduction electrode, special artificial pollution test facility was built and utilized. The experimental results show better surface flashover performance of ceramic insulators used in high-voltage transmission and distribution systems.

A Shapley Value-Based Approach to Discover Influential Nodes in Social Networks

Our study concerns an important current problem, that of diffusion of information in social networks. This problem has received significant attention from the Internet research community in the recent times, driven by many potential applications such as viral marketing and sales promotions. In this paper, we focus on the target set selection problem, which involves discovering a small subset of influential players in a given social network, to perform a certain task of information diffusion. The target set selection problem manifests in two forms: 1) top-k nodes problem and 2) lambda-coverage problem. In the top-k nodes problem, we are required to find a set of k key nodes that would maximize the number of nodes being influenced in the network. The lambda-coverage problem is concerned with finding a set of k key nodes having minimal size that can influence a given percentage lambda of the nodes in the entire network. We propose a new way of solving these problems using the concept of Shapley value which is a well known solution concept in cooperative game theory. Our approach leads to algorithms which we call the ShaPley value-based Influential Nodes (SPINs) algorithms for solving the top-k nodes problem and the lambda-coverage problem. We compare the performance of the proposed SPIN algorithms with well known algorithms in the literature. Through extensive experimentation on four synthetically generated random graphs and six real-world data sets (Celegans, Jazz, NIPS coauthorship data set, Netscience data set, High-Energy Physics data set, and Political Books data set), we show that the proposed SPIN approach is more powerful and computationally efficient. Note to Practitioners-In recent times, social networks have received a high level of attention due to their proven ability in improving the performance of web search, recommendations in collaborative filtering systems, spreading a technology in the market using viral marketing techniques, etc. It is well known that the interpersonal relationships (or ties or links) between individuals cause change or improvement in the social system because the decisions made by individuals are influenced heavily by the behavior of their neighbors. An interesting and key problem in social networks is to discover the most influential nodes in the social network which can influence other nodes in the social network in a strong and deep way. This problem is called the target set selection problem and has two variants: 1) the top-k nodes problem, where we are required to identify a set of k influential nodes that maximize the number of nodes being influenced in the network and 2) the lambda-coverage problem which involves finding a set of influential nodes having minimum size that can influence a given percentage lambda of the nodes in the entire network. There are many existing algorithms in the literature for solving these problems. In this paper, we propose a new algorithm which is based on a novel interpretation of information diffusion in a social network as a cooperative game. Using this analogy, we develop an algorithm based on the Shapley value of the underlying cooperative game. The proposed algorithm outperforms the existing algorithms in terms of generality or computational complexity or both. Our results are validated through extensive experimentation on both synthetically generated and real-world data sets.

Size dependence of the bulk modulus of semiconductor nanocrystals from first-principles calculations

The variation in the bulk modulus of semiconductor nanoparticles has been studied within first-principles electronic-structure calculations using the local density approximation (LDA) for the exchange correlation. Quantum Monte Carlo calculations carried out for a silicon nanocrystal Si87H76 provided reasonable agreement with the LDA results. An enhancement was observed in the bulk modulus as the size of the nanoparticle was decreased, with modest enhancements being predicted for the largest nanoparticles studied here, a size just accessible in experiments. To access larger sizes, we fit our calculated bulk moduli to the same empirical law for all materials, the asymptote of which is the bulk value of the modulus. This was found to be within 2-10% of the independently calculated value. The origin of the enhancement has been discussed in terms of Cohen's empirical law M.L. Cohen, Phys. Rev. B 32, 7988 (1985)] as well as other possible scenarios.

Energy-Efficient Fault Tolerance in Chip Multiprocessors Using Critical Value Forwarding

Relentless CMOS scaling coupled with lower design tolerances is making ICs increasingly susceptible to wear-out related permanent faults and transient faults, necessitating on-chip fault tolerance in future chip microprocessors (CMPs). In this paper we introduce a new energy-efficient fault-tolerant CMP architecture known as Redundant Execution using Critical Value Forwarding (RECVF). RECVF is based on two observations: (i) forwarding critical instruction results from the leading to the trailing core enables the latter to execute faster, and (ii) this speedup can be exploited to reduce energy consumption by operating the trailing core at a lower voltage-frequency level. Our evaluation shows that RECVF consumes 37% less energy than conventional dual modular redundant (DMR) execution of a program. It consumes only 1.26 times the energy of a non-fault-tolerant baseline and has a performance overhead of just 1.2%.

Photoluminescence enhancement and quenching in metal-semiconductor quantum dot hybrid arrays

Hybrid monolayer arrays of metal and semiconductor quantum dots have been prepared to study the exciton-plasmon interaction. We observed crossover from strong quenching to enhancement in photoluminescence of the quantum dots as a function of the emission wavelength for fixed interparticle spacings. Remarkably, the enhancement is observed even for extremely short separation at which strong quenching has been observed and predicted earlier. A significant redshift in emission maxima is also observed for quantum dots with quenched emission. The possible role of collective phenomena as well as strong interactions in such ordered hybrid arrays in controlling the emission is discussed. (C) 2011 American Institute of Physics. doi:10.1063/1.3553766]

Effect of Li+-ion on enhancement of photoluminescence in Gd2O3:Eu3+ nanophosphors prepared by combustion technique

Gd2O3:Eu3+ (4 mol%) nanophosphor co-doped with Li+ ions have been synthesized by low-temperature solution combustion technique in a short time. Powder X-ray diffractometer (PXRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), UV-VIS and photoluminescence (PL) techniques have been employed to characterize the synthesized nanoparticles. It is found that the lattice of Gd2O3:Eu3+ phosphor transforms from monoclinic to cubic as the Li+-ions are doped. Upon 254 nm excitation, the phosphor showed characteristic luminescence D-5(0) -> F-7(J) (J= 0-4) of the Eu3+ ions. The electronic transition located at 626 nm (D-5(0) -> F-7(2)) of Eu3+ ions was stronger than the magnetic dipole transition located at 595 nm (D-5(0) -> F-7(1)). Furthermore, the effects of the Li+ co-doping as well as calcinations temperature on the PL properties have been studied. The results show that incorporation of Li+ ions in Gd2O3:Eu3+ lattice could induce a remarkable improvement of their PL intensity. The emission intensity was observed to be enhanced four times than that of with out Li+-doped Gd2O3:Eu3+. (C) 2010 Elsevier B.V. All rights reserved,

Enhancement in Bath Mixing and Plume area in a New Degassing Process - A Computational Fluid Dynamic Study

Reaction between the various species in slag and metal phase is usually mass transfer controlled. There have been continuous efforts to increase the reaction efficiency in slag-metal system, especially during decarburization of steel to produce the ultra low carbon steel (ULCS) in secondary steelmaking. It has been found that the surface reaction is a dominant factor in the final stage of decarburization. In the initial stage, the inner site reaction is major factor in the refining process. The mixing of bath affects the later reaction. However, the former reaction (surface reaction) is affected by the plume size area at the top of the metal surface. Therefore, a computational study has been made to understand the fluid dynamics of a new secondary steelmaking process called Revolutionary Degasser Activator (REDA) to study the bath mixing and plume area. REDA process has been considered as it is claimed that this process can reduce the carbon content in steel below 10ppm in a less time than the other existing processes such as RH and Tank degasser. This study shows that both bath mixing and plume area are increased in REDA process facilitating it to give the desired carbon content in less time. Qualitative comments are made on slag-metal reaction system based on this finding.

Defects induced enhancement of Eu3+Emission in yttria (Y2O3:Eu3+)

Bixbyite type Y2O3:Eu3+ apart from being the efficient red phosphor extensively used in trichromatic fluorescent lamps, it is a typical system one can apply Jorgensen's refined electron spin pairing theory. This can be used to explain the enhancement in Eu3+ emission intensity observed with the aliovalent substitution in the yttria host matrix. Results based on these are explained qualitatively by considering a simple configurational coordinate model. Futhermore, an insight into the different types of defects induced with the aliovalent substitution in the yttria lattice has become possible with EPR probe.

Sensitivity Enhancement in Solid-State Separated Local Field NMR Experiments by the Use of Adiabatic Cross-Polarization

Measurement of dipolar couplings using separated local field (SLF) NMR experiment is a powerful tool for structural and dynamics studies of oriented molecules such as liquid crystals and membrane proteins in aligned lipid bilayers. Enhancing the sensitivity of such SLF techniques is of significant importance in present-day solid-state NMR methodology. The present study considers the use of adiabatic cross-polarization for this purpose, which is applied for the first time to one of the well-known SLF techniques, namely, polarization inversion spin exchange at the magic angle (PISEMA). The experiments have been carried out on a single crystal of a model peptide, and a dramatic enhancement in signal-to-noise up to 90% has been demonstrated.

Macro-economic analysis of forestry options on carbon sequestration in India

The forestry sector provides a number of climate change mitigation options. Apart from this ecological benefit, it has significant social and economic relevance. Implementation of forestry options requires large investments and sustained long-term planning. Thus there is a need for a detailed analysis of forestry options to understand their implications on stock and flow of carbon, required investments, value of forest wealth, contribution to GNP and livelihood, demand management, employment and foreign trade. There is a need to evaluate the additional spending on forestry by analysing the environmental (particularly carbon abatement), social and economic benefits. The biomass needs for India are expected to increase by two to three times by 2020. Depending upon the forest types, ownership patterns and land use patterns, feasible forestry options are identified. It is found among many supply options to be feasible to meet the 'demand based needs' with a mix of management options, species choices and organisational set up. A comparative static framework is used to analyze the macro-economic impacts. Forestry accounts for 1.84% of GNP in India. It is characterized by significant forward industrial linkages and least backward linkage. Forestry generates about 36 million person years of employment annually. India imports Rs. 15 billion worth of forest based materials annually. Implementation of the demand based forestry options can lead to a number of ecological, economic and institutional changes. The notable ones are: enhancement of C stock from 9578 to 17 094 Mt and a net annual C-sequestration from 73 to 149 Mt after accounting for all emissions; a trebling of the output of forestry sector from Rs. 49 billion to Rs. 146 billion annually; an increase in GDP contribution of forestry from Rs. 32 billion to Rs. 105 billion over a period of 35 years; an increase in annual employment level by 23 million person years, emergence of forestry as a net contributor of foreign exchange through trading of forestry products; and an increase in economic value of forest capital stock by Rs. 7260 billion with a cost benefit analysis showing forestry as a profitable option. Implementation of forestry options calls for an understanding of current forest policies and barriers which are analyzed and a number of policy options are suggested. (C) 1997 Elsevier Science B.V.

Resonance de-enhancement in the 2(1)A(g) state of trans-azobenzene

We analyze the origin of de-enhancement for a number of vibrational modes in the 2(1)A(g) excited state of trans-azobenzene. We have used the time-dependent wave packet analysis of the RR intensities by including the multimode damping effects in the calculation. This avoids the use of unrealistically large values for the damping parameter. It is concluded that the de-enhancement is caused by the interference between the two uncoupled electronic states, and that the intensities observed under the so-called symmetry forbidden 2(1)A(g) <-- 1(1)A(g) transition are purely due to resonance excitation. It is also observed that the use of the time-dependent approach to study the de-enhancement effects caused by multiple electronic states on the RR intensities is not necessarily useful if one is interested in the structural dynamics.

Enhancement of uniaxial magnetic anisotropy in Fe thin films grown on GaAs(001) with an MgO underlayer

The understanding and control of anisotropy in Fe films grown on cubic systems such as GaAs and MgO has been of interest from the point of view of applications in devices. We report magnetic anisotropy studies on Fe/GaAs(001) and Fe/MgO/GaAs(001) prepared by pulsed laser deposition. In Fe/GaAs(001), magneto optical Kerr effect (MOKE) measurements revealed a dominant uniaxial anisotropy for Fe thickness less than 20 monolayers (ML) and this was confirmed by ferromagnetic resonance (FMR) studies. Multiple steps in the hysteresis loops were observed for Fe films of thickness 20 and 25 ML. Whereas, in Fe/MgO/GaAs(001), even at 25 ML of Fe, the uniaxial anisotropy remained dominant. The anisotropy constants obtained from FMR spectra have shown that the relative strength of uniaxial anisotropy is higher as compared to the cubic anisotropy constant in the case of Fe/MgO/GaAs(001). (C) 2011 American Institute of Physics. doi:10.1063/1.3556941]