Response of Materials During Sliding on Various Surface Textures

In the present investigation, soft materials, such as Al-4Mg alloy, high-purity Al and pure Mg pins were slid against hard steel plates of various surface textures to study the response of materials during sliding. The experiments were conducted using an inclined pin-on-plate sliding apparatus under both dry and lubricated conditions in an ambient environment. Two kinds of frictional response, namely steady-state and stick-slip, were observed during sliding. In general, the response was dependent on material pair, normal load, lubrication, and surface texture of the harder material. More specifically, for the case of Al-4Mg alloy, the stick-slip response was absent under both dry and lubricated conditions. For Al, stick-slip was observed only under lubricated conditions. For the case of Mg, the stick-slip response was seen under both dry and lubricated conditions. Further, it was observed that the amplitude of stick-slip motion primarily depends on the plowing component of friction. The plowing component of friction was the highest for the surfaces that promoted plane strain conditions and was the lowest for the surfaces that promoted plane stress conditions near the surface.     

X-ray diffraction and H-storage in ultra-small palladium particles

In situ X-ray diffraction (XRD) and gravimetric hydrogen uptake measurements of d ∼ 2–3 nm spherical PdH_x particles have been studied in the temperature and pressure range of 323 < T < 428 K and 0 < P < 10 bar. The Pd particles were protected from sintering with a hydrogen-permeable carbon coating. While only containing ∼300–1000 atoms, the Pd particles were found to exhibit the same fcc structure and lattice constant as the bulk. Our isothermal studies show that, with increasing x, these highly crystalline PdH_x nanoparticles also exhibit a complete transformation from the dilute α solid solution phase to the more concentrated β hydride phase. However, we observed that the character of the α–β phase transition in these nanoparticles is very different from that in the bulk. Indeed, the hydrogen uptake isotherm exhibits a noticeable positive slope in the α + β co-existence region. Furthermore, we also observed a noticeable narrowing of the α + β co-existence region (δx) in the nanoparticles. Also, a significant suppression of the critical temperature T_c for the phase boundary was observed: T_c(nano) ≈ 430 K while T_c(bulk) ≈ 570 K. These results signal a significant change in the thermodynamic behavior of very small hydride nanoparticles that may be common to many other nano-scale metal hydride systems as well.     

A powerful algorithm for power system planning amenable to small computers

This paper presents the development of a highly effective and reliable piecewise fast decoupled load flow algorithm. The algorithm requires minimal storage, independent of the system size, and can be used effectively for system planning on small computers.     

Determining Hydraulic Characteristics of Production Wells using Genetic Algorithm

Proper well management requires the determination of characteristic hydraulic parameters of production wells such as well loss coefficient (C) and aquifer loss coefficient (B), which are conventionally determined by the graphical analysis ofstep-drawdowntest data. However, in the present study, the efficacy of a non-conventional optimization technique called Genetic Algorithm (GA), which ensures near-optimal or optimal solutions, is assessedin determining well parameters from step-drawdown test data. Computer programs were developed to optimize the well parametersby GA technique for two cases: (i) optimization of B and C only, and (ii) optimization of B, C and p (exponent) as well as to evaluate the well condition. The reliability and robustness of the developed computer programs were tested usingnine sets of published and unpublished step-drawdown data from varying hydrogeologic conditions. The well parameters obtained by the GA technique were compared with those obtained by the conventional graphical method in terms of root mean square error(RMSE) and visual inspection. It was revealed that the GA technique yielded more reliable well parameters with significantlylow values of RMSE for almost all the datasets, especially in caseof three-variable optimization. The optimal values of the parametersB, C and p for the nine datasets were found to range from 0.382 to 2.292 min m^-2, 0.091 to 3.262, and 1.8 to 3.6, respectively. Because of a wide variation of p, the GA techniqueresulted in considerably different but dependable and robust well parameters as well as well specific capacity and well efficiency compared to the graphical method. The condition of three wells was found to be good, one well bad and that of the remaining five wells satisfactory. The performance evaluation of the developed GA code indicated that a proper selection of generation number and population size is essential to ensure efficient optimization. Furthermore,a sensitivity analysis of the obtained optimal parameters demonstrated that the GA technique resulted in a unique set ofthe parameters for all the nine datasets. It is concluded thatthe GA technique is an effective and reliable numerical tool for determining the characteristic hydraulic parameters of production wells.     

A new method to test system diagnosability

A new necessary and sufficient condition for t-diagnosability of a system is proposed. It is shown that the new scheme is computationally more efficient than the existing one for checking the diagnosability of a system.     

The Effects of Learning on Optimal Lot Size Determination—Multiple Product Case

This article extends the analysis of an earlier paper by the authors for a single product to lot size determination for manufacturing cycles of multiple products. The effects of production breaks, learning interactions due to commonality of tasks and different learning rates for products are considered in the formulation of an equation for the average production time per unit. The equation is applied to an equal lot size per product model. An analysis of a model restricted to equal production intervals per product per cycle is also presented. A sample problem is solved to demonstrate the application of the effects of learning to multiple product lot size determination.     

On the thermodynamics of oxygen in molten copper,Cu-Sn,and Cu-Ag alloys

Measurements of oxygen activity in molten copper, Cu-Sn, and Cu-Ag alloys at 1135°C have been made utilizing the solid-state electrolyte technique. The activity coefficient of oxygen in molten copper at low oxygen levels (<0.1 pet) was found to be 0.12. The interaction parameters of silver and tin on oxygen were found to be ε _O ^Ag = 4.52 and ε _O ^Sn =-10.5. Comparison of experimental data with solution models revealed that the behavior of oxygen in Cu-O-Ag alloys is in accordance with predictions of Alcock and Richardson’s quasichemical model when a coordination number between 1 and 4 is assumed, depending on the silver and oxygen content. Furthermore, agreement with Belton’s quasichemical model based on the assumption of Ag-O dipoles serves to strengthen the evidence for the existence of Ag-O species in solution. The behavior of oxygen in the Cu-O-Sn system also shows better agreement with the quasichemical model than with the random model, with low coordination numbers favored in dilute tin solutions, increasing to larger values in Cu-60 Sn solutions.     

Electroactive Shape Memory Effect of Polyurethane Composites Filled with Carbon Nanotubes and Conducting Polymer

We report the electroactive shape memory composites obtained by shape memory polyurethane block copolymer (PU) and multi-walled carbon nanotubes (MWNTs), and polypyrrole (PPy). An addition of combined MWNTs and PPy contributed to an enhancement in conductivity of PU-MWNTs composites. PU containing 2.5% MWNTs showed better mechanical and thermal properties than other composites, but conductivity was not sufficient for showing the shape memory effect by applying electrical voltages. However, when the composite was lightly coated by PPy (2.5%), its conductivity was the highest than other composites. Such the conductivity of this composite was enough to show electroactive shape recovery by heating above transition temperature of 40-48°C due to melting of polycaprolactone soft segment domain. The good shape recovery of 90-96% could be obtained in the shape recovery test when an electric field of 25 V was applied.     

Automatic clustering algorithm based on multi-objective Immunized PSO to classify actions of 3D human models

Multi-objective clustering algorithms are preferred over its conventional single objective counterparts as they incorporate additional knowledge on properties of data in the from of objectives to extract the underlying clusters present in many datasets. Researchers have recently proposed some standardized multi-objective evolutionary clustering algorithms based on genetic operations, particle swarm optimization, clonal selection principles, differential evolution and simulated annealing, etc. In many cases it is observed that hybrid evolutionary algorithms provide improved performance compared to that of individual algorithm. In this paper an automatic clustering algorithm MOIMPSO (Multi-objective Immunized Particle Swarm Optimization) is proposed, which is based on a recently developed hybrid evolutionary algorithm Immunized PSO. The proposed algorithm provides suitable Pareto optimal archive for unsupervised problems by automatically evolving the cluster centers and simultaneously optimizing two objective functions. In addition the algorithm provides a single best solution from the Pareto optimal archive which mostly satisfy the users' requirement. Rigorous simulation studies on 11 benchmark datasets demonstrate the superior performance of the proposed algorithm compared to that of the standardized automatic clustering algorithms such as MOCK, MOPSO and MOCLONAL. An interesting application of the proposed algorithm has also been demonstrated to classify the normal and aggressive actions of 3D human models.     

Variability of mesopause temperature derived from two independent methods using meteor radar and its comparison with SABER and EOS MLS and a collocated multi-wavelength dayglow photometer over an equatorial station,Thumba (8.5° N, 76.5° E)

Two independent methods for deriving mesopause temperature using meteor radar installed at an equatorial station, Thumba (8.5° N, 76.5° E), are discussed in this article. This meteor radar-derived mesopause temperature is then compared with two different types of spaceborne measurement, namely (i) Sounding the Atmosphere using Broadband Emission Radiometry (SABER) and (ii) the Earth Observing System Microwave Limb Sounder (EOS MLS), and a collocated multi-wavelength dayglow photometer (DGPM). The meteor radar-derived temperature is in fairly good agreement with all the three measurement techniques, with an uncertainty of ±10°. This study focuses on a detailed evaluation and inter-comparison of mesopause temperature derived from different measurement techniques. An attempt is also made to compare the suitability of these observations to study planetary waves and other oscillation activities in the mesospheric region.