Analysis of CFRP strap-strengthened reinforced concrete beams using the modified compression field theory (MCFT)

External, prestressed carbon fiber reinforced polymer (CFRP) straps can be used to enhance the shear strength of existing reinforced concrete beams. In order to effectively design a strengthening system, a rational predictive theory is required. The current work investigates the ability of the modified compression field theory (MCFT) to predict the behavior of rectangular strap strengthened beams where the discrete CFRP strap forces are approximated as a uniform vertical stress. An unstrengthened control beam and two strengthened beams were tested to verify the predictions. The experimental results suggest that the MCFT could predict the general response of a strengthened beam with a uniform strap spacing < 0.9d. However, whereas the strengthened beams failed in shear, the MCFT predicted flexural failures. It is proposed that a different compression softening model or the inclusion of a crack width limit is required to reflect the onset of shear failures in the strengthened beams.

Compression techniques applied to multiple speech recognition systems

Speech recognition systems typically contain many Gaussian distributions, and hence a large number of parameters. This makes them both slow to decode speech, and large to store. Techniques have been proposed to decrease the number of parameters. One approach is to share parameters between multiple Gaussians, thus reducing the total number of parameters and allowing for shared likelihood calculation. Gaussian tying and subspace clustering are two related techniques which take this approach to system compression. These techniques can decrease the number of parameters with no noticeable drop in performance for single systems. However, multiple acoustic models are often used in real speech recognition systems. This paper considers the application of Gaussian tying and subspace compression to multiple systems. Results show that two speech recognition systems can be modelled using the same number of Gaussians as just one system, with little effect on individual system performance. Copyright © 2009 ISCA.

Numerical investigation of the active role of the actin cytoskeleton in the compression resistance of cells.

Numerous in-vitro studies have established that cells react to their physical environment and to applied mechanical loading. However, the mechanisms underlying such phenomena are poorly understood. Previous modelling of cell compression considered the cell as a passive homogenous material, requiring an artificial increase in the stiffness of spread cells to replicate experimentally measured forces. In this study, we implement a fully 3D active constitutive formulation that predicts the distribution, remodelling, and contractile behaviour of the cytoskeleton. Simulations reveal that polarised and axisymmetric spread cells contain stress fibres which form dominant bundles that are stretched during compression. These dominant fibres exert tension; causing an increase in computed compression forces compared to round cells. In contrast, fewer stress fibres are computed for round cells and a lower resistance to compression is predicted. The effect of different levels of cellular contractility associated with different cell phenotypes is also investigated. Highly contractile cells form more dominant circumferential stress fibres and hence provide greater resistance to compression. Computed predictions correlate strongly with published experimentally observed trends of compression resistance as a function of cellular contractility and offer an insight into the link between cell geometry, stress fibre distribution and contractility, and cell deformability. Importantly, it is possible to capture the behaviour of both round and spread cells using a given, unchanged set of material parameters for each cell type. Finally, it is demonstrated that stress distributions in the cell cytoplasm and nucleus computed using the active formulation differ significantly from those computed using passive material models.

Policy optimisation of POMDP-based dialogue systems without state space compression

The partially observable Markov decision process (POMDP) has been proposed as a dialogue model that enables automatic improvement of the dialogue policy and robustness to speech understanding errors. It requires, however, a large number of dialogues to train the dialogue policy. Gaussian processes (GP) have recently been applied to POMDP dialogue management optimisation showing an ability to substantially increase the speed of learning. Here, we investigate this further using the Bayesian Update of Dialogue State dialogue manager. We show that it is possible to apply Gaussian processes directly to the belief state, removing the need for a parametric policy representation. In addition, the resulting policy learns significantly faster while maintaining operational performance. © 2012 IEEE.

Fabrication, densification, and replica molding of 3D carbon nanotube microstructures

The introduction of new materials and processes to microfabrication has, in large part, enabled many important advances in microsystems, labon- a-chip devices, and their applications. In particular, capabilities for cost-effective fabrication of polymer microstructures were transformed by the advent of soft lithography and other micromolding techniques 1,2, and this led a revolution in applications of microfabrication to biomedical engineering and biology. Nevertheless, it remains challenging to fabricate microstructures with well-defined nanoscale surface textures, and to fabricate arbitrary 3D shapes at the micro-scale. Robustness of master molds and maintenance of shape integrity is especially important to achieve high fidelity replication of complex structures and preserving their nanoscale surface texture. The combination of hierarchical textures, and heterogeneous shapes, is a profound challenge to existing microfabrication methods that largely rely upon top-down etching using fixed mask templates. On the other hand, the bottom-up synthesis of nanostructures such as nanotubes and nanowires can offer new capabilities to microfabrication, in particular by taking advantage of the collective self-organization of nanostructures, and local control of their growth behavior with respect to microfabricated patterns. Our goal is to introduce vertically aligned carbon nanotubes (CNTs), which we refer to as CNT "forests", as a new microfabrication material. We present details of a suite of related methods recently developed by our group: fabrication of CNT forest microstructures by thermal CVD from lithographically patterned catalyst thin films; self-directed elastocapillary densification of CNT microstructures; and replica molding of polymer microstructures using CNT composite master molds. In particular, our work shows that self-directed capillary densification ("capillary forming"), which is performed by condensation of a solvent onto the substrate with CNT microstructures, significantly increases the packing density of CNTs. This process enables directed transformation of vertical CNT microstructures into straight, inclined, and twisted shapes, which have robust mechanical properties exceeding those of typical microfabrication polymers. This in turn enables formation of nanocomposite CNT master molds by capillary-driven infiltration of polymers. The replica structures exhibit the anisotropic nanoscale texture of the aligned CNTs, and can have walls with sub-micron thickness and aspect ratios exceeding 50:1. Integration of CNT microstructures in fabrication offers further opportunity to exploit the electrical and thermal properties of CNTs, and diverse capabilities for chemical and biochemical functionalization 3. © 2012 Journal of Visualized Experiments.

Modelling failure of composite specimens with defects under compression loading

Composite structures exhibit many different failure mechanisms, but attempts to model composite failure frequently make a priori assumptions about the mechanism by which failure will occur. Wang et al. [1] conducted compressive tests on four configurations of composite specimen manufactured with out-of-plane waviness created by ply-drop defects. There were significantly different failures for each case. Detailed finite element models of these experiments were developed which include competing failure mechanisms. The model predictions correlate well with experimental results-both qualitatively (location of failure and shape of failed specimen) and quantitatively (failure load). The models are used to identify the progression of failure during the compressive tests, determine the critical failure mechanism for each configuration, and investigate the effect of cohesive parameters upon specimen strength. This modelling approach which includes multiple competing failure mechanisms can be applied to predict failure in situations where the failure mechanism is not known in advance. © 2013 Elsevier Ltd. All rights reserved.

Gasoline fuelled partially premixed compression ignition in a light duty multi cylinder engine: A study of low load and low speed operation

The objective of this study was to examine the operating characteristics of a light duty multi cylinder compression ignition engine with regular gasoline fuel at low engine speed and load. The effects of fuel stratification by means of multiple injections as well as the sensitivity of auto-ignition and burn rate to intake pressure and temperature are presented. The measurements used in this study included gaseous emissions, filter smoke opacity and in-cylinder indicated information. It was found that stable, low emission operation was possible with raised intake manifold pressure and temperature, and that fuel stratification can lead to an increase in stability and a reduced reliance on increased temperature and pressure. It was also found that the auto-ignition delay sensitivity of gasoline to intake temperature and pressure was low within the operating window considered in this study. Nevertheless, the requirement for an increase of pressure, temperature and stratification in order to achieve auto-ignition time scales small enough for combustion in the engine was clear, using pump gasoline. Copyright © 2009 SAE International.

Autoignition of alcohols and ethers in a rapid compression machine

The autoignition characteristics of methanol, ethanol and MTBE (methyl tert-butyl ether) have been investigated in a rapid compression machine at pressures in the range 20-40 atm and temperatures within 750-1000 K. All three oxygenated fuels tested show higher autoignition temperatures than paraffins, a trend consistent with the high octane number of these fuels. The autoignition delay time for methanol was slightly lower than predicted values using reported reaction mechanisms. However, the experimental and measured values for the activation energy are in very good agreement around 44 kcal/mol. The measured activation energy for ethanol autoignition is in good agreement with previous shock tube results (31 kcal/mol), although ignition times predicted by the shock tube correlation are a factor of three lower than the measured values. The measured activation energy for MTBE, 41.4 kcal/mol, was significantly higher than the value previously observed in shock tubes (28.1 kcal/mol). The onset of preignition, characterized by a slow energy release prior to early ignition was observed in some instances. Possible reasons for these ocurrences are discussed. © Copyright 1993 Society of Automotive engineers, Inc.

Bayesian updating of a unified soil compression model

Some amount of differential settlement occurs even in the most uniform soil deposit, but it is extremely difficult to estimate because of the natural heterogeneity of the soil. The compression response of the soil and its variability must be characterised in order to estimate the probability of the differential settlement exceeding a certain threshold value. The work presented in this paper introduces a probabilistic framework to address this issue in a rigorous manner, while preserving the format of a typical geotechnical settlement analysis. In order to avoid dealing with different approaches for each category of soil, a simplified unified compression model is used to characterise the nonlinear compression behavior of soils of varying gradation through a single constitutive law. The Bayesian updating rule is used to incorporate information from three different laboratory datasets in the computation of the statistics (estimates of the means and covariance matrix) of the compression model parameters, as well as of the uncertainty inherent in the model.