Mechanical response of carbon fiber composite sandwich panels with pyramidal truss cores

The combination of light carbon fiber reinforced polymer (CFRP) composite materials with structurally efficient sandwich panel designs offers novel opportunities for ultralight structures. Here, pyramidal truss sandwich cores with relative densities ρ̄ in the range 1-10% have been manufactured from carbon fiber reinforced polymer laminates by employing a snap-fitting method. The measured quasi-static shear strength varied between 0.8 and 7.5 MPa. Two failure modes were observed: (i) Euler buckling of the struts and (ii) delamination failure of the laminates. Micro-buckling failure of the struts was not observed in the experiments reported here while Euler buckling and delamination failures occurred for the low (ρ̄≤1%) and high (ρ̄>1%) relative density cores, respectively. Analytical models for the collapse of the composite cores by these failure modes are presented. Good agreement between the measurements and predictions based on the Euler buckling and delamination failure of the struts is observed while the micro-buckling analysis over-predicts the measurements. The CFRP pyramidal cores investigated here have a similar mechanical performance to CFRP honeycombs. Thus, for a range of multi-functional applications that require an "open-celled" architecture (e.g. so that cooling fluid can pass through a sandwich core), the CFRP pyramidal cores offer an attractive alternative to honeycombs. © 2012 Elsevier Ltd. All rights reserved.

Digital radio distribution system over multiple cabling types

This paper demonstrates a novel digital radio distribution system able to transmit not only over optical fibres and coaxial cables but also over twisted pair cables. The digitised RF signal is compressed for maximum transmission efficiency in a way that allows for integral self-learning algorithms to be introduced for multi-service applications. © 2013 IEEE.

Non-catalytic multi-fuel reformer for syngas production for fuel cell applications

Rich combustion of n-heptane, diesel oil, jet A-1 kerosene, and bio-diesel (rapeseed-oil methyl ester) were studied to produce hydrogen enriched gas, ready for the cleanup stages for fuel cell applications. n-heptane was successfully reformed up to an equivalence ratio of 3:1, reaching a conversion efficiency up to 83% for a packed bed of alumina bead burner. Diesel, kerosene and bio-diesel were reformed to synthesis gas with conversion efficiency up to 65%. At equivalence ratio of 2:1 and P=7 kw, stability, low HC formation, high conversion efficiency, and low soot emission were achieved. A common synthesis gas composition around this condition was 15 and 13% H2, 15 and 17% CO, and 4 and 4.5% CO2 for n-heptane and diesel, jet A-1 and bio-diesel, respectively, for burner A. This is an abstract of a paper presented at the 2010 Spring National Meeting (San Antonio, TX 3/21-25/2010).

Selecting a multi-agent system development tool for industrial applications: A case study of self-serving aircraft assets

Industrialists have few example processes they can benchmark against in order to choose a multi-agent development kit. In this paper we present a review of commercial and academic agent tools with the aim of selecting one for developing an intelligent, self-serving asset architecture. In doing so, we map and enhance relevant assessment criteria found in literature. After a preliminary review of 20 multiagent platforms, we examine in further detail those of JADE, JACK and Cougaar. Our findings indicate that Cougaar is well suited for our requirements, showing excellent support for criteria such as scalability, persistence, mobility and lightweightness. © 2010 IEEE.

Toxicity and imaging of multi-walled carbon nanotubes in human macrophage cells.

Multi-walled carbon nanotubes (MWNTs) have been proposed for use in many applications and concerns about their potential effect on human health have led to the interest in understanding the interactions between MWNTs and human cells. One important technique is the visualisation of the intracellular distribution of MWNTs. We exposed human macrophage cells to unpurified MWNTs and found that a decrease in cell viability was correlated with uptake of MWNTs due to mainly necrosis. Cells treated with purified MWNTs and the main contaminant Fe(2)O(3) itself yielded toxicity only from the nanotubes and not from the Fe(2)O(3). We used 3-D dark-field scanning transmission electron microscopy (DF-STEM) tomography of freeze-dried whole cells as well as confocal and scanning electron microscopy (SEM) to image the cellular uptake and distribution of unpurified MWNTs. We observed that unpurified MWNTs entered the cell both actively and passively frequently inserting through the plasma membrane into the cytoplasm and the nucleus. These suggest that MWNTs may cause incomplete phagocytosis or mechanically pierce through the plasma membrane and result in oxidative stress and cell death.

Multi-channel signal separation

The separation of independent sources from mixed observed data is a fundamental and challenging problem. In many practical situations, observations may be modelled as linear mixtures of a number of source signals, i.e. a linear multi-input multi-output system. A typical example is speech recordings made in an acoustic environment in the presence of background noise and/or competing speakers. Other examples include EEG signals, passive sonar applications and cross-talk in data communications. In this paper, we propose iterative algorithms to solve the n × n linear time invariant system under two different constraints. Some existing solutions for 2 × 2 systems are reviewed and compared.

An approximate likelihood method for estimating static parameters in multi-target tracking models

This paper considers a class of dynamic Spatial Point Processes (PP) that evolves over time in a Markovian fashion. This Markov in time PP is hidden and observed indirectly through another PP via thinning, displacement and noise. This statistical model is important for Multi object Tracking applications and we present an approximate likelihood based method for estimating the model parameters. The work is supported by an extensive numerical study.