A simple diesel engine air-path model to predict the cylinder charge during transients: Strategies for reducing transient emissions spikes

Simple air-path models for modern (VGT/EGR equipped) diesel engines are in common use, and have been reported in the literature. This paper addresses some of the shortcomings of control-oriented models to allow better prediction of the cylinder charge properties. A fast response CO2 analyzer is used to validate the model by comparing the recorded and predicted CO2 concentrations in both the intake port and exhaust manifold of one of the cylinders. Data showing the recorded NOx emissions and exhaust gas opacity during a step change in engine load illustrate the spikes in both NOx and smoke seen during transient conditions. The predicted cylinder charge properties from the model are examined and compared with the measured NOx and opacity. Together, the emissions data and charge properties paint a consistent picture of the phenomena occurring during the transient. Alternative strategies for the fueling and cylinder charge during these load transients are investigated and discussed. Experimental results are presented showing that spikes in both NOx and smoke can be avoided at the expense of some loss in torque response. Even if the torque response must be maintained, it is demonstrated that it is still possible to eliminate spikes in NOx emissions for the transient situation being examined. Copyright © 2006 SAE International.

Linear regression under fixed-rank constraints: A Riemannian approach

In this paper, we tackle the problem of learning a linear regression model whose parameter is a fixed-rank matrix. We study the Riemannian manifold geometry of the set of fixed-rank matrices and develop efficient line-search algorithms. The proposed algorithms have many applications, scale to high-dimensional problems, enjoy local convergence properties and confer a geometric basis to recent contributions on learning fixed-rank matrices. Numerical experiments on benchmarks suggest that the proposed algorithms compete with the state-of-the-art, and that manifold optimization offers a versatile framework for the design of rank-constrained machine learning algorithms. Copyright 2011 by the author(s)/owner(s).

Regression on fixed-rank positive semidefinite matrices: A Riemannian approach

The paper addresses the problem of learning a regression model parameterized by a fixed-rank positive semidefinite matrix. The focus is on the nonlinear nature of the search space and on scalability to high-dimensional problems. The mathematical developments rely on the theory of gradient descent algorithms adapted to the Riemannian geometry that underlies the set of fixedrank positive semidefinite matrices. In contrast with previous contributions in the literature, no restrictions are imposed on the range space of the learned matrix. The resulting algorithms maintain a linear complexity in the problem size and enjoy important invariance properties. We apply the proposed algorithms to the problem of learning a distance function parameterized by a positive semidefinite matrix. Good performance is observed on classical benchmarks. © 2011 Gilles Meyer, Silvere Bonnabel and Rodolphe Sepulchre.

Riemannian metric and geometric mean for positive semidefinite matrices of fixed rank

This paper introduces a new metric and mean on the set of positive semidefinite matrices of fixed-rank. The proposed metric is derived from a well-chosen Riemannian quotient geometry that generalizes the reductive geometry of the positive cone and the associated natural metric. The resulting Riemannian space has strong geometrical properties: it is geodesically complete, and the metric is invariant with respect to all transformations that preserve angles (orthogonal transformations, scalings, and pseudoinversion). A meaningful approximation of the associated Riemannian distance is proposed, that can be efficiently numerically computed via a simple algorithm based on SVD. The induced mean preserves the rank, possesses the most desirable characteristics of a geometric mean, and is easy to compute. © 2009 Society for Industrial and Applied Mathematics.

Noncontact measurement of charge carrier lifetime and mobility in GaN nanowires

The first noncontact photoconductivity measurements of gallium nitride nanowires (NWs) are presented, revealing a high crystallographic and optoelectronic quality achieved by use of catalyst-free molecular beam epitaxy. In comparison with bulk material, the NWs exhibit a long conductivity lifetime (>2 ns) and a high mobility (820 ± 120 cm 2/(V s)). This is due to the weak influence of surface traps with respect to other III-V semiconducting NWs and to the favorable crystalline structure of the NWs achieved via strain-relieved growth. © 2012 American Chemical Society.

Direct observation of charge-carrier heating at WZ-ZB InP nanowire heterojunctions.

We have investigated the dynamics of hot charge carriers in InP nanowire ensembles containing a range of densities of zinc-blende inclusions along the otherwise wurtzite nanowires. From time-dependent photoluminescence spectra, we extract the temperature of the charge carriers as a function of time after nonresonant excitation. We find that charge-carrier temperature initially decreases rapidly with time in accordance with efficient heat transfer to lattice vibrations. However, cooling rates are subsequently slowed and are significantly lower for nanowires containing a higher density of stacking faults. We conclude that the transfer of charges across the type II interface is followed by release of additional energy to the lattice, which raises the phonon bath temperature above equilibrium and impedes the carrier cooling occurring through interaction with such phonons. These results demonstrate that type II heterointerfaces in semiconductor nanowires can sustain a hot charge-carrier distribution over an extended time period. In photovoltaic applications, such heterointerfaces may hence both reduce recombination rates and limit energy losses by allowing hot-carrier harvesting.

A laboratory-scale buried charge simulator

An experimental technique has been developed in order to mimic the effect of landmine loading on materials and structures to be studied in a laboratory setting, without the need for explosives. Compressed gas is discharged beneath a sand layer, simulating the dynamic flow generated by a buried explosive. High speed photography reveals that the stages of soil motion observed during a landmine blast are replicated. The effect of soil saturation and the depth of the sand layer on sand motion are evaluated. Two series of experiments have been performed with the buried charge simulator to characterise subsequent impact of the sand. First, the time variation in pressure and impulse during sand impact on a stationary target is evaluated using a Kolsky bar apparatus. It is found that the pressure pulse imparted to the Kolsky bar consists of two phases: an initial transient phase of high pressure (attributed to wave propagation effects in the impacting sand), followed by a lower pressure phase of longer duration (due to lateral flow of the sand against the Kolsky bar). Both phases make a significant contribution to the total imparted impulse. It is found that wet sand exerts higher peak pressures and imparts a larger total impulse than dry sand. The level of imparted impulse is determined as a function of sand depth, and of stand-off distance between the sand and the impacted end of the Kolsky bar. The second study uses a vertical impulse pendulum to measure the momentum imparted by sand impact to a target which is free to move vertically. The effect of target mass upon imparted momentum is investigated. It is concluded that the laboratory-scale sand impact apparatus is a flexible tool for investigating the interactions between structures and dynamic sand flows. © 2013 Elsevier Ltd. All rights reserved.

The influence of 1D, meso- and crystal structures on charge transport and recombination in solid-state dye-sensitized solar cells

We have prepared single crystalline SnO2 and ZnO nanowires and polycrystalline TiO2 nanotubes (1D networks) as well as nanoparticle-based films (3D networks) from the same materials to be used as photoanodes for solid-state dye-sensitized solar cells. In general, superior photovoltaic performance can be achieved from devices based on 3-dimensional networks, mostly due to their higher short circuit currents. To further characterize the fabricated devices, the electronic properties of the different networks were measured via the transient photocurrent and photovoltage decay techniques. Nanowire-based devices exhibit extremely high, light independent electron transport rates while recombination dynamics remain unchanged. This indicates, contrary to expectations, a decoupling of transport and recombination dynamics. For typical nanoparticle-based photoanodes, the devices are usually considered electron-limited due to the poor electron transport through nanocrystalline titania networks. In the case of the nanowire-based devices, the system becomes limited by the organic hole transporter used. In the case of polycrystalline TiO2 nanotube-based devices, we observe lower transport rates and higher recombination dynamics than their nanoparticle-based counterparts, suggesting that in order to improve the electron transport properties of solid-state dye-sensitized solar cells, single crystalline structures should be used. These findings should aid future design of photoanodes based on nanowires or porous semiconductors with extended crystallinity to be used in dye-sensitized solar cells. © 2013 The Royal Society of Chemistry.