Effects of carbon nanofibers on cell morphology, thermal conductivity and crush strength of carbon foam

The effects of low volume fractions of carbon nanofibers on the structure, thermal conductivity and crush strength of carbon foam were examined. Bulk density of the foam increased linearly with the fiber fraction reflecting the morphological changes in the cells. Thermal conductivity increased at low fiber fractions, but dropped at higher fiber fractions. Crush strength increased linearly with fiber fraction for short length fibers, but decreased for the longer length fibers. Scanning electron microscopy, petrography, and X-ray diffraction illustrated the complex effects of the carbon nanofibers on the foam. Available models for thermal conductivity and crush strength have been extended to accommodate these effects incorporating cell structure and morphology (macroeffect), presence of fibers (microeffect), and graphite crystal d-spacing (nanoeffect). This research has shown that the nanofibers have a complex role in the macro, micro, and nanoproperties of the composite foam.     

Developments in low-cost housing

The co-ordinator of working group W63 shows, in this abridged version of his paper, how several countries have brought a degree of pragmatism to their innovations, which take account of the realities of their situation in terms of material and manpower resources and the level of technology appropriate to their needs.     

STRANDS: Interactive Simulation of Thin Solids using Cosserat Models

Strands are thin elastic solids that are visually well approximated as smooth curves, and yet possess essential physical behaviors characteristic of solid objects such as twisting. Common examples in computer graphics include: sutures, catheters, and tendons in surgical simulation; hairs, ropes, and vegetation in animation. Physical models based on spring meshes or 3D finite elements for such thin solids are either inaccurate or inefficient for interactive simulation. In this paper we show that models based on the Cosserat theory of elastic rods are very well suited for interactive simulation of these objects. The physical model reduces to a system of spatial ordinary differential equations that can be solved efficiently for typical boundary conditions. The model handles the important geometric non‐linearity due to large changes in shape. We introduce Cosserat‐type physical models, describe efficient numerical methods for interactive simulation of these models, and implementation results.     

Characterization of sputtered SmCo thin films for light element contamination using RBS and HIERDA techniques

Samarium cobalt films were prepared on silicon substrates with and without a chromium buffer layer at room temperature and 600°C using direct current unbalanced magnetron sputtering. For obtaining ideal magnetic properties, the films should be free from impurities, such as O, Al and others. Rutherford backscattering spectrometry and heavy ion elastic recoil detection analysis were used to determine the composition and film thickness and to monitor the light element contamination across film thickness. X-ray diffractometer and superconducting quantum interference device were employed to characterize the structure and magnetic properties of the films, respectively. The results obtained led to an improved design of the ground shield and the use of a sorption pump to effectively minimize aluminium and oxygen concentration in the films, respectively.     

Incremental penetration depth estimation between convex polytopes using dual-space expansion

We present a fast algorithm to estimate the penetration depth between convex polytopes in 3D. The algorithm incrementally seeks a "locally optimal solution" by walking on the surface of the Minkowski sums. The surface of the Minkowski sums is computed implicitly by constructing a local dual mapping on the Gauss map. We also present three heuristic techniques that are used to estimate the initial features used by the walking algorithm. We have implemented the algorithm and compared its performance with earlier approaches. In our experiments, the algorithm is able to estimate the penetration depth in about a milli-second on an 1 GHz Pentium PC. Moreover, its performance is almost independent of model complexity in environments with high coherence between successive instances.     

Numerical Analysis of Heat Transport Behavior in the Ferromagnetic Metallic State of La0.80Ca0.20MnO3 Manganites

The lattice contribution to the thermal conductivity (κ_ph) in La_0.80Ca_0.20 MnO₃ manganites is discussed within the Debye-type relaxation rate approximation in terms of the acoustic phonon frequency and relaxation time. The theory is formulated when heat transfer is limited by the scattering of phonons from defects, grain boundaries, charge carriers, and phonons. The lattice thermal conductivity dominates in La–Ca–MnO manganites and is an artifact of strong phonon-impurity and -phonon scattering mechanisms in the ferromagnetic metallic state. The electronic contribution to the thermal conductivity (κ_e) is estimated following the Wiedemann–Franz law. This estimate sets an upper bound on κ_e, and in the vicinity of the Curie temperature (240 K) κ_e is about 1% of total heat transfer of manganites. Another important contribution in the metallic phase should come from spin waves (κ_m). It is noticed that κ_m increases with a T² dependence on the temperature. These channels for heat transfer are algebraically added and κ_tot develops a broad peak at about 55 K, before falling off at lower temperatures. The behavior of the thermal conductivity in manganites is determined by competition among the several operating scattering mechanisms for the heat carriers and a balance between electron, magnon, and phonon contributions. The numerical analysis of heat transfer in the ferromagnetic metallic phase of manganites shows similar results as those revealed from experiments.      

Effective parameter study for the facile and controlled growth of silver molybdate nano/micro rods

Controlled growth of nano/micro structures by controlling the effective parameters is the basic requirement for the application point of view in various areas. Here we report the facile growth of silver molybdate nano/micro rods by mixing the solution of silver nitrate and ammonium molybdate at ambient condition followed by hydrothermal treatment at various temperatures for 12 h. To achieve the goal for the synthesis of long, high yield and homogeneous nanorods various effective parameters have been studied to set the most effective conditions for the growth. Among possible effective parameters first the temperature of the furnace was set by warring the temperature and then at the set temperature the concentration of reactants (NH₄)₆Mo₇O₂₄ and silver nitrate are varied respect to each other. The pH and temperature values were monitored during the mixing of the reactants. Structural/microstructural characterization revealed the optimum condition of 150°C of the furnace and the concentration of (NH₄)₆Mo₇O₂₄ and silver nitrate as described in various tables.     

Fuzzy modeling of system behavior for risk and reliability analysis

The main objective of the article is to permit the reliability analyst's/engineers/managers/practitioners to analyze the failure behavior of a system in a more consistent and logical manner. To this effect, the authors propose a methodological and structured framework, which makes use of both qualitative and quantitative techniques for risk and reliability analysis of the system. The framework has been applied to model and analyze a complex industrial system from a paper mill. In the quantitative framework, after developing the Petrinet model of the system, the fuzzy synthesis of failure and repair data (using fuzzy arithmetic operations) has been done. Various system parameters of managerial importance such as repair time, failure rate, mean time between failures, availability, and expected number of failures are computed to quantify the behavior in terms of fuzzy, crisp and defuzzified values. Further, to improve upon the reliability and maintainability characteristics of the system, in depth qualitative analysis of systems is carried out using failure mode and effect analysis (FMEA) by listing out all possible failure modes, their causes and effect on system performance. To address the limitations of traditional FMEA method based on risky priority number score, a risk ranking approach based on fuzzy and Grey relational analysis is proposed to prioritize failure causes.     

Cooperative energy management in distributed wireless real-time systems

This work is based on the observation that existing energy management techniques for mobile devices, such as Dynamic Voltage Scaling (DVS), are non-cooperative in the sense that they reduce the energy consumption of a single device, disregarding potential consequences for other constraints (e.g., end-to-end deadlines) and/or other devices (e.g., energy consumption on neighboring devices). This paper argues that energy management in distributed wireless real-time systems has to be end-to-end in nature, requiring a coordinated approach among communicating devices. A cooperative distributed energy management technique (Co-DVS) is proposed that (1) adapts and maintains end-to-end latencies within specified timeliness requirements (deadlines) and (2) enhances energy savings at the devices with the highest pay-off factors that represent the relative benefits or significance of conserving energy at a device. The proposed technique employs a feedback-based approach to dynamically distribute end-to-end slack among the devices based on their pay-off factors.