Stability and thermophysical properties of fly ash nanofluid for heat transfer applications

Improving the performance of heat transfer fluids is altogether significant. The best approach for improving the thermal conductivity is the addition of nanoparticles to the base fluid. In the present study, specific heat, dynamic viscosity, and thermal conductivity of water-based Indian coal fly ash stable nanofluid for 0.1% to 0.5% volume concentration in the temperature range of 30 to 60°C has been investigated. To evaluate an average particle diameter of 11.5 nm, the fly ash nanoparticles were characterized with scanning electron microscopy and dynamic light scattering. Using zeta potential, the stability of nanofluid in the presence of surfactant Triton X-100 was tested. Thermal conductivity and viscosity of fly ash nanofluid increased, while specific heat decreased as volume concentration increased. The effect of temperature on the fly ash nanofluid was directly proportional to its thermal conductivity and specific heat and inversely proportional to viscosity.     

Fatty acids from Macoma sp. of bivalve mollusc

Fatty acids of the total lipids of flesh and hepatopancreas of Macoma sp. have been determined. The level of 20:5w3 (ca 17%), a biologically important fatty acid, was found to be considerably high. Other major component fatty acids were 16:0, 16:1, 18:1 and 22:4w6. High levels of 22:5w6 (8%), 22:5w3 (8%) and 22:6w3 (ca 15%) were found in flesh lipid. Nonsaponifiables were also high (28–30%). Alkyl ether acyl glycerols were found in flesh (1.3%) and hepatopancreas (3.8%).     

Metallurgical Investigation of a Prematurely Failed Concentric Reducer Tube Used in a Hot-Rolling Mill

A concentric reducer tube, which was a part of the top exit roughing hydraulic descaler in a hot strip mill failed prematurely under working pressure. A detailed metallurgical investigation comprising physical examination, optical microscopy, scanning electron microscopy, and electron probe microanalysis was carried out to find out the genesis of the failure. Physical examination revealed cracks located symmetrically around the circumference of the tube that ran along its full length, up to the weld beads at both ends. Optical microscopy of etched samples revealed a banded ferrite-pearlite structure and the existence of forging folds near the change-in-section(160° fillets). Cracks were found to initiate from these forging folds. No structural abnormalities were found in the weld beads and heat-affected zones.     

Cement mortar impregnated with poly(methyl methacrylate-co-styrene)

Polymer-impregnated mortars were prepared by copolymerization of a monomer mixture of methyl methacrylate and styrene in the ratios of 13:87 and 40:60 using Co-60 gamma radiation. The copolymerization characteristics viz. the rate of polymerization, the extent of monomer loss, polymer loading, etc., were studied. The nature and molecular weight of the extractable polymer from the composite were determined. The flexural strength of the copolymer-impregnated composites was found to be better than that of the composites impregnated with component homopolymers.     

New block copolymers II. Synthesis and characterization of an ABA-type block copolymer

A new regular ABA-type triblock copolymer has been synthesized by polycondensation of the acid chloride of carboxy-terminated butadience-acrylonitrile rubber (CTBN) with hydroxyterminated polyethylene isophthalate (PEI) oligomer. This block copolymer was characterized by elemental (nitrogen) analysis, vapor pressure osmometry, viscometry, and IR and NMR spectroscopy. Quantitative estimation of block segments has been carried out by measuring the area under peaks assigned to various protons in the NMR spectrum of the polymer. NMR spectral analysis has been found to agree well with the nitrogen analysis of the polymer. The solubility and solution viscosity behavior of the polymer has also been studied.     

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.     

Topography of the flank wear surface

In many applications, topography represents the main external features of a surface. This paper describes the topography of the flank wear surface and also presents the relationship between the maximum flank wear and the topography parameters (roughness parameters) of the flank wear surface during the turning operation. A modern CNC lathe machine (Okuma LH35-N) was used for the machine turning operation. Three-dimensional surface roughness parameters of the flank wear surface were measured by a surface texture instrument (from Talysurf series) using surface topography software (Talymap). Based on the resulting experimental data, it is found that as the flank wear increases, the roughness parameters (sR_a, sR_q, and sR_t) on the flank surface increase significantly. The greater the roughness value of the flank wear surface, the higher the friction of the tool on the workpiece and the greater the heat generation that will occur, thus ultimately causing tool failure. On the other hand, positive skewness (sR_sk) indicates the presence of a small number of spikes on the flank surface of the cutting tool, which could quickly wear off during the machining process.     

Lattice Boltzmann method simulation of electroosmotic stirring in a microscale cavity

The suitable surface modification of microfluidic channels can enable a neutral electrolyte solution to develop an electric double layer (EDL). The ions contained within the EDL can be moved by applying an external electric field, inducing electroosmotic flows (EOFs) that results in associated stirring. This provides a solution for the rapid mixing required for many microfluidic applications. We have investigated EOFs generated by applying a steady electric field across a square cavity that has homogenous electric potentials along its walls. The flowfield is simulated using the lattice Boltzmann method. The extent of mixing is characterized for different electrode configurations and electric field strengths. We find that rapid mixing can be achieved by using this simple configuration which increases with increasing electric field strength. The mixing time for water-soluble organic molecules can be decreased by four orders of magnitude by suitable choice of wall zeta potential and electric field. We dedicate this paper to the memory of our colleagues Professors Kevin Granata and Liviu Librescu who fell tragically on April 16, 2007 while answering their call to serve higher education. They continue to inspire us. AM gratefully acknowledges support from Jadavpur University under the World Bank funded Technical Education Quality Improvement Programme of the Government of India and the hospitality of the Virginia Tech ESM Department where he conducted a portion of this work.     

Learning of grasp selection based on shape-templates

The ability to grasp unknown objects still remains an unsolved problem in the robotics community. One of the challenges is to choose an appropriate grasp configuration, i.e., the 6D pose of the hand relative to the object and its finger configuration. In this paper, we introduce an algorithm that is based on the assumption that similarly shaped objects can be grasped in a similar way. It is able to synthesize good grasp poses for unknown objects by finding the best matching object shape templates associated with previously demonstrated grasps. The grasp selection algorithm is able to improve over time by using the information of previous grasp attempts to adapt the ranking of the templates to new situations. We tested our approach on two different platforms, the Willow Garage PR2 and the Barrett WAM robot, which have very different hand kinematics. Furthermore, we compared our algorithm with other grasp planners and demonstrated its superior performance. The results presented in this paper show that the algorithm is able to find good grasp configurations for a large set of unknown objects from a relatively small set of demonstrations, and does improve its performance over time.     

TiO2 nanoparticle embedded nitrogen doped electrospun helical carbon nanofiber-carbon nanotube hybrid anode for lithium-ion batteries

TiO₂ nanoparticles decorated nitrogen (N) doped helical carbon nanofiber (CNF)-carbon nanotube (CNT) hybrid material is prepared by low-cost electrospinning technique followed by hydrothermal method. Morphological investigations establish helical structure of CNFs with hierarchical growth of CNTs around CNFs. The hybrid material shows a high specific surface area of 295.17 m² g^?1 with nanoporous structure. X-ray photoelectron spectroscopic studies establish Ti–O–C/Ti–C bond mediated charge transfer channel between TiO₂ nanoparticles and carbon structures with the success of N doping in CNFs. The electrospun hybrid material delivered high reversible charge capacities of 316 mAh g^?1 (100th cycle) and 244 mAh g^?1 (100th cycle) at a current density of 75 mA g^?1 and 186 mA g^?1 respectively. The charge capacities obtained for different applied current densities are higher than the conventional graphitic microporous microbeads anode. Results indicate that the hybrid material reported here shows high performance compare to graphite for LIBs.