Effect of high temperature, biaxial stretching on the thermal and mechanical properties of HDPE/MWCNT sheet

High density polyethylene (HDPE)/multi-walled carbon nanotube (MWCNT) composites containing 4 wt% MWCNTs were prepared by melt mixing followed by compression moulding into sheet. Compression moulded sheets were heated to just below the melting temperature and biaxially stretched at ratios (SRs) of 2, 2.5 and 3.0. The effect of stretching on the thermal and mechanical properties of the sheet was studied by differential scanning calorimetry (DSC) and tensile testing. DSC results show that the crystallinity of all the stretched samples increases by approximately 13% due to strain induced crystallization. The melting temperature of the biaxially stretched samples increases only slightly while crystallization temperature is not affected. Tensile test results indicate that at a SR of 2.5 the elastic modulus of the stretched composites increases by 17.6% relative to the virgin HDPE, but the breaking strength decreases by 33%. While the elastic modulus and breaking strength of the HDPE/MWCNT samples continue to increase as SR increases they drop off after a SR of 2.5 for the virgin HDPE. This is probably due to the constraining influence of the nanotubes preventing the relaxation of polymer chains caused by adiabatic heating at high SRs. The addition of MWCNTs results in significant strain hardening during deformation. While this will lead to increased energy requirement in forming it will also result in a more stable process and the ability to produce deep draw containers with more uniform wall thickness

On the maximum energy of shock-accelerated cosmic rays at ultra-relativistic shocks

The maximum energy to which cosmic rays can be accelerated at weakly magnetised ultra-relativistic shocks is investigated. We demonstrate that for such shocks, in which the scattering of energetic particles is mediated exclusively by ion skin-depth scale structures, as might be expected for a Weibel-mediated shock, there is an intrinsic limit on the maximum energy to which particles can be accelerated. This maximum energy is determined from the requirement that particles must be isotropized in the downstream plasma frame before the mean field transports them far downstream, and falls considerably short of what is required to produce ultra-high-energy cosmic rays. To circumvent this limit, a highly disorganized field is required on larger scales. The growth of cosmic ray-induced instabilities on wavelengths much longer than the ion-plasma skin depth, both upstream and downstream of the shock, is considered. While these instabilities may play an important role in magnetic field amplification at relativistic shocks, on scales comparable to the gyroradius of the most energetic particles, the calculated growth rates have insufficient time to modify the scattering. Since strong modification is a necessary condition for particles in the downstream region to re-cross the shock, in the absence of an alternative scattering mechanism, these results imply that acceleration to higher energies is ruled out. If weakly magnetized ultra-relativistic shocks are disfavoured as high-energy particle accelerators in general, the search for potential sources of ultra-high-energy cosmic rays can be narrowed.

Improvement of the efficiency of energy transfer in the hydro-entanglement process

Hydro-entanglement is a versatile process for bonding non-woven fabrics by the use of fine, closely-spaced, high-velocity jets of water to rearrange and entangle arrays of fibres. The cost of the process mainly depends on the amount of energy consumed. Therefore, the economy of the process is highly affected by optimisation of the energy required. In this paper a parameter called critical pressure is introduced which is indicative of the energy level requirement. The results of extensive experimental work are reported and analysed to give a clear understanding of the effect of the web and fibre properties on the critical pressure in the hydro-entanglement process. Furthermore, different energy-transfer distribution schemes are tested on various fabrics. The optimum scheme which involves the lowest energy consumption and the best fabric properties is identified. © 2001 Published by Elsevier Science Ltd. All rights reserved.

ALEA: Fine-Grain Energy Profiling with Basic Block Sampling

Energy efficiency is an essential requirement for all contemporary computing systems. We thus need tools to measure the energy consumption of computing systems and to understand how workloads affect it. Significant recent research effort has targeted direct power measurements on production computing systems using on-board sensors or external instruments. These direct methods have in turn guided studies of software techniques to reduce energy consumption via workload allocation and scaling. Unfortunately, direct energy measurements are hampered by the low power sampling frequency of power sensors. The coarse granularity of power sensing limits our understanding of how power is allocated in systems and our ability to optimize energy efficiency via workload allocation.
We present ALEA, a tool to measure power and energy consumption at the granularity of basic blocks, using a probabilistic approach. ALEA provides fine-grained energy profiling via sta- tistical sampling, which overcomes the limitations of power sens- ing instruments. Compared to state-of-the-art energy measurement tools, ALEA provides finer granularity without sacrificing accuracy. ALEA achieves low overhead energy measurements with mean error rates between 1.4% and 3.5% in 14 sequential and paral- lel benchmarks tested on both Intel and ARM platforms. The sampling method caps execution time overhead at approximately 1%. ALEA is thus suitable for online energy monitoring and optimization. Finally, ALEA is a user-space tool with a portable, machine-independent sampling method. We demonstrate two use cases of ALEA, where we reduce the energy consumption of a k-means computational kernel by 37% and an ocean modelling code by 33%, compared to high-performance execution baselines, by varying the power optimization strategy between basic blocks.