Carbon dioxide from earthworks: a bottom-up approach.

Concerns over climate change mean engineers need to understand the greenhouse gas emissions associated with infrastructure projects. Standard coefficients are increasingly used to calculate the embodied emissions of construction materials, but these are not generally appropriate to inherently variable earthworks. This paper describes a new tool that takes a bottom-up approach to calculating carbon dioxide emissions from earthworks operations. In the case of bulk earthworks this is predominantly from the fuel used by machinery moving materials already on site. Typical earthworks solutions are explored along with the impact of using manufactured materials such as lime.

Response probability distribution of built-up vibro-acoustic systems

The vibro-acoustic response of built-up structures, consisting of stiff components with low modal density and flexible components with high modal density, is sensitive to small imperfections in the flexible components. In this paper, the uncertainty of the response is considered by modeling the low modal density master system as deterministic and the high modal density subsystems in a nonparametric stochastic way, i.e., carrying a diffuse wave field, and by subsequently computing the response probability density function. The master system's mean squared response amplitude follows a singular noncentral complex Wishart distribution conditional on the subsystem energies. For a single degree of freedom, this is equivalent to a chi-square or an exponential distribution, depending on the loading conditions. The subsystem energies follow approximately a chi-square distribution when their relative variance is smaller than unity. The results are validated by application to plate structures, and good agreement with Monte Carlo simulations is found. © 2012 Acoustical Society of America.

Overview and status of bottom-up silicon nanowire electronics

This review summarises the recent advances in the field of silicon nanowire electronics from bottom-up assembled materials. The aim is to draw a comparison between bottom-up and top-down approaches, examining respective achievements and evaluating advantages and disadvantages of each methodology. Existing techniques for synthesis and doping are discussed to provide the framework in which practical electronic applications can be developed. Next, key device categories are reviewed, emphasising current challenges and proposed solutions. Finally, field perspectives are outlined. © 2012 Elsevier Ltd.

Er3+ excitation and up-conversion processes in y 2-xErxSi2O7 films for planar optical amplifiers

Structural and optical properties of Y2-xErxSi 2O7 thin films have been studied. For higher Er content mechanisms related to Er-Er interactions increase optical efficiency. Moreover the influence of up-conversion has been estimated. ©2009 IEEE.

The vibro-acoustic analysis of built-up systems using a hybrid method with parametric and non-parametric uncertainties

An existing hybrid finite element (FE)/statistical energy analysis (SEA) approach to the analysis of the mid- and high frequency vibrations of a complex built-up system is extended here to a wider class of uncertainty modeling. In the original approach, the constituent parts of the system are considered to be either deterministic, and modeled using FE, or highly random, and modeled using SEA. A non-parametric model of randomness is employed in the SEA components, based on diffuse wave theory and the Gaussian Orthogonal Ensemble (GOE), and this enables the mean and variance of second order quantities such as vibrational energy and response cross-spectra to be predicted. In the present work the assumption that the FE components are deterministic is relaxed by the introduction of a parametric model of uncertainty in these components. The parametric uncertainty may be modeled either probabilistically, or by using a non-probabilistic approach such as interval analysis, and it is shown how these descriptions can be combined with the non-parametric uncertainty in the SEA subsystems to yield an overall assessment of the performance of the system. The method is illustrated by application to an example built-up plate system which has random properties, and benchmark comparisons are made with full Monte Carlo simulations. © 2012 Elsevier Ltd. All rights reserved.

A simple criterion for filament break-up in drop-on-demand inkjet printing

Jets from drop-on-demand inkjet print-heads consist of a main drop with a trailing filament, which either condenses into the main drop, or breaks up into satellite drops. Filament behaviour is quantitatively similar to that of larger, free symmetrical filamentscan be predicted from the aspect ratio and Ohnesorge number. Symmetrical filaments generated from inkjet print-heads show the same behaviour. A simple model, based on competition between the processes of axial shortening and radial necking, predicts the critical aspect ratio below which the jet condenses into a single drop. The success of this simple criterion supports the underlying physical model. © 2013 American Institute of Physics.

200 v superjunction N-type lateral insulated-gate bipolar transistor with improved latch-up characteristics

This paper evaluates the technique used to improve the latching characteristics of the 200 V n-type superjunction (SJ) lateral insulated-gate bipolar transistor (LIGBT) on a partial silicon-on-insulator. SJ IGBT devices are more prone to latch-up than standard IGBTs due to the presence of a strong pnp transistor with the p layer serving as an effective collector of holes. The initial SJ LIGBT design latches at about 23 V with a gate voltage of 5 V with a forward voltage drop (VON) of 2 V at 300 Acm2. The latch-up current density is 1100 Acm2. The latest SJ LIGBT design shows an increase in latch-up voltage close to 100 V without a significant penalty in VON. The latest design shows a latch-up current density of 1195 A cm2. The enhanced robustness against static latch-up leads to a better forward bias safe operating area. © 1963-2012 IEEE.

Scaling the Indian Buffet Process via Submodular Maximization

Inference for latent feature models is inherently difficult as the inference space grows exponentially with the size of the input data and number of latent features. In this work, we use Kurihara & Welling (2008)'s maximization-expectation framework to perform approximate MAP inference for linear-Gaussian latent feature models with an Indian Buffet Process (IBP) prior. This formulation yields a submodular function of the features that corresponds to a lower bound on the model evidence. By adding a constant to this function, we obtain a nonnegative submodular function that can be maximized via a greedy algorithm that obtains at least a one-third approximation to the optimal solution. Our inference method scales linearly with the size of the input data, and we show the efficacy of our method on the largest datasets currently analyzed using an IBP model.