The Effects of the Catalytic Converter on Two-Stroke Engine Performance, SAE Technical Paper 972741

The two-stroke engine, by its nature is very dependent on the unsteady gas dynamics within an exhaust system. This is demonstrated by the tuning effects on two-stroke engines, which have been well documented. In consideration of current emissions legislation, a two-stroke engine can be fitted with a catalytic converter for the outboard, utility or automotive markets. The catalytic substrate represents a major obstruction to the flow of exhaust gas, which hinders the progression of the main exhausted pulse, and in turn effects the scavenging of the cylinder and ultimately the performance of the engine.

Characterization of the AtsR Hybrid Sensor Kinase Phosphorelay Pathway and Identification of Its Response Regulator in Burkholderia cenocepacia

AtsR is a membrane-bound hybrid sensor kinase of Burkholderia cenocepacia that negatively regulates quorum sensing and virulence factors such as biofilm production, type 6-secretion and protease secretion. Here, we elucidate the mechanism of AtsR phosphorelay by site-directed mutagenesis of predicted histidine and aspartic acid phosphoacceptor residues. We demonstrate by in vitro phosphorylation that histidine-245 and aspartic acid-536 are conserved sites of phosphorylation in AtsR, and we also identify the cytosolic response regulator AtsT (BCAM0381) as a key component of the AtsR phosphorelay pathway. Monitoring the function of AtsR and its derivatives in vivo by measuring extracellular protease activity and swarming motility confirmed the in vitro phosphorylation results. Together, we find that the AtsR receiver domain plays a fine-tuning role in determining the levels of phosphotransfer from its sensor kinase domain to the AtsT response regulator.

Clicking Well-Defined Biodegradable Nanoparticles and Nanocapsules by UV-Induced Thiol-Ene Cross-Linking in Transparent Miniemulsions

A novel approach for the preparation of nanomaterials is developed by tuning miniemulsion reaction systems to be transparent in order to enable highly efficient photoreactions. Biodegradable nanoparticles and nanocapsules are obtained by UV-induced thiol-ene cross-linking of polylactide (PLA)-based precursor polymers preassembled in transparent miniemulsions. These well-defined nanomaterials may potentially serve as ideal scaffolds for drug delivery.

An abstract annotation model for skeletons

Multi-core and many-core platforms are becoming increasingly heterogeneous and asymmetric. This significantly increases the porting and tuning effort required for parallel codes, which in turn often leads to a growing gap between peak machine power and actual application performance. In this work a first step toward the automated optimization of high level skeleton-based parallel code is discussed. The paper presents an abstract annotation model for skeleton programs aimed at formally describing suitable mapping of parallel activities on a high-level platform representation. The derived mapping and scheduling strategies are used to generate optimized run-time code. © 2013 Springer-Verlag Berlin Heidelberg.

Controlling Subnanometer Gaps in Plasmonic Dimers Using Graphene

Graphene is used as the thinnest possible spacer between gold nanoparticles and a gold substrate. This creates a robust, repeatable, and stable subnanometer gap for massive plasmonic field enhancements. White light spectroscopy of single 80 nm gold nanoparticles reveals plasmonic coupling between the particle and its image within the gold substrate. While for a single graphene layer, spectral doublets from coupled dimer modes are observed shifted into the near-infrared, these disappear for increasing numbers of layers. These doublets arise from charger-transfer-sensitive gap plasmons, allowing optical measurement to access out-of-plane conductivity in such layered systems. Gating the graphene can thus directly produce plasmon tuning.

Log gf values for astrophysically important transitions Fe II

Aims. In a recent measurement, Meléndez & Barbuy (2009, A&A, 497, 611) report accurate log gf values for 142 important astrophysical lines with wavelengths in the range 4000 Å to 8000 Å. Their results include both solar and laboratory measurements. In this paper, we describe a theoretical study of these lines. Methods. The CIV3 structure codes, combined with our "fine-tuning" extrapolation process, are used to undertake a large-scale CI calculation involving the lowest 262 fine-structure levels belonging to the 3d4s, 3d, 3d4s, 3d4p, and 3d4s4p configurations. Results. We find that many of the 142 transitions are very weak intercombination lines. Other transitions are weak because the dominant configurations in the two levels differ by two orbitals. Conclusions. The comparison between our log gf values and the experimental values generally shows good agreement for most of these transitions, with our theoretical values agreeing slightly more closely with the solar than with the laboratory measurements. A detailed analysis of the small number of transitions for which the agreement between theory and experiment is not as good shows that such disagreements largely arise from severe cancellation due to CI mixing.

Pilot Tone Actuated Antenna Array Pattern Reconfiguration

A new strategy for remote reconfiguration of an antenna array far field radiation pattern is described. The scheme uses a pilot tone co-transmitted with a carrier signal from a location distant from that of a receive antenna array whose far field pattern is to be reconfigured. By mixing the co-transmitted signals locally at each antenna element in the array an IF signal is formed which defines an equivalent array spacing that can be made variable by tuning the frequency of the pilot tone with respect to the RF carrier. This makes the antenna array factor hence far field spatial characteristic reconfigurable on receive. For a 10 x 1 microstrip patch element array we show that the receive pattern can be made to vary from 35 to 10 degrees half power beam width as the difference frequency between the pilot and the carrier at 2.45 GHz varies between 10 MHz and 500 MHz carrier.

Tailoring Alphabetical Metamaterials in Optical Frequency: Plasmonic Coupling, Dispersion, and Sensing

Tailoring optical properties of artificial metamaterials, whose optical properties go beyond the limitations of conventional and naturally occurring materials, is of importance in fundamental research and has led to many important applications such as security imaging, invisible cloak, negative refraction, ultrasensitive sensing, transformable and switchable optics. Herein, by precisely controlling the size, symmetry and topology of alphabetical metamaterials with U, S, Y, H, U-bar and V shapes, we have obtained highly tunable optical response covering visible-to-infrared (Vis-NIR) optical frequency. In addition, we show a detailed study on the physical origin of resonance modes, plasmonic coupling, the dispersion of electronic and magnetic surface plasmon polaritons, and the possibility of negative refraction. We have found that all the electronic and magnetic modes follow the dispersion of surface plasmon polaritons thus essentially they are electronic- and magnetic-surface-plasmon-polaritons-like (ESPP-like and MSPP-like) modes resulted from diffraction coupling between localized surface plasmon and freely-propagating light. Based on the fill factor and formula of magnetism permeability, we predict that the alphabetical metamaterials should show the negative refraction capability in visible optical frequency. Furthermore, we have demonstrated the specific ultrasensitive surface enhanced Raman spectroscopy (SERS) sensing of monolayer molecules and femtomolar food contaminants by tuning their resonance to match the laser wavelength, or by tuning the laser wavelength to match the plasmon resonance of metamaterials. Our tunable alphabetical metamaterials provide a generic platform to study the electromagnetic properties of metamaterials and explore the novel applications in optical frequency.

The hydrodynamics of small seabed mounted bottom hinged wave energy converters in shallow water:PhD thesis

This thesis investigates the hydrodynamics of a small, seabed mounted, bottom hinged, wave energy converter in shallow water. The Oscillating Wave Surge Converter is a pitching flap-type device which is located in 10-15m of water to take advantage of the amplification of horizontal water particle motion in shallow water. A conceptual model of the hydrodynamics of the device has been formulated and shows that, as the motion of the flap is highly constrained, the magnitude of the force applied to the flap by the wave is strongly linked to the power absorption.

An extensive set of experiments has been carried out in the wave tank at Queen’s University at both 40th and 20th scales. The experiments have included testing in realistic sea states to estimate device performance as well as fundamental tests using small amplitude monochromatic waves to determine the force applied to the flap by the waves. The results from the physical modelling programme have been used in conjunction with numerical data from WAMIT to validate the conceptual model.

The work finds that tuning the OWSC to the incident wave periods is problematic and only results in a marginal increase in power capture. It is also found that the addition of larger diameter rounds to the edges of the flap reduces viscous losses and has a greater effect on the performance of the device than tuning. As wave force is the primary driver of device performance it is shown that the flap should fill the water column and should pierce the water surface to reduce losses due to wave overtopping.

With the water depth fixed at approximately 10m it is shown that the width of the flap has the greatest impact on the magnitude of wave force, and thus device performance. An 18m wide flap is shown to have twice the absorption efficiency of a 6m wide flap and captures 6 times the power. However, the increase in power capture with device width is not limitless and a 24m wide flap is found to be affected by two-dimensional hydrodynamics which reduces its performance per unit width, especially in sea states with short periods. It is also shown that as the width increases the performance gains associated with the addition of the end effectors reduces. Furthermore, it is shown that as the flap width increases the natural pitching period of the flap increases, thus detuning the flap further from the wave periods of interest for wave energy conversion.

The effect of waves approaching the flap from an oblique angle is also investigated and the power capture is found to decrease with the cosine squared of the encounter angle. The characteristic of the damping applied by the power take off system is found to have a significant effect on the power capture of the device, with constant damping producing between 20% and 30% less power than quadratic damping. Furthermore, it is found that applying a higher level of damping, or a damping bias, to the flap as it pitches towards the beach increases the power capture by 10%.

A further set of experiments has been undertaken in a case study used to predict the power capture of a prototype of the OWSC concept. The device, called the Oyster Demonstrator, has been developed by Aquamarine Power Ltd. and is to be installed at the European Marine Energy Centre, Scotland, in 2009.

The work concludes that OWSC is a viable wave energy converter and absorption efficiencies of up 75% have been measured. It is found that to maximise power absorption the flap should be approximately 20m wide with large diameter rounded edges, having its pivot close to the seabed and its top edge piercing the water surface.

Reconstructing the quantum state of oscillator networks with a single qubit

We introduce a scheme to reconstruct arbitrary states of networks composed of quantum oscillators-e. g., the motionalstate of trapped ions or the radiation state of coupled cavities. The scheme involves minimal resources and minimal access, in the sense that it (i) requires only the interaction between a one-qubit probe and a single node of the network; (ii) provides the Weyl characteristic function of the network directly from the data, avoiding any tomographic transformation; (iii) involves the tuning of only one coupling parameter. In addition, we show that a number of quantum properties can be extracted without full reconstruction of the state. The scheme can be used for probing quantum simulations of anharmonic many-body systems and quantum computations with continuous variables. Experimental implementation with trapped ions is also discussed and shown to be within reach of current technology.

A Framework for Prototyping and Reasoning about Distributed Systems

A framework supporting fast prototyping as well as tuning of distributed applications is presented. The approach is based on the adoption of a formal model that is used to describe the orchestration of distributed applications. The formal model (Orc by Misra and Cook) can be used to support semi-formal reasoning about the applications at hand. The paper describes how the framework can be used to derive and evaluate alternative orchestrations of a well know parallel/distributed computation pattern; and shows how the same formal model can be used to support generation of prototypes of distributed applications skeletons directly from the application description.

Optimisation of Kinetic Parameters for an After-treatment Catalyst

Mathematical modelling has become an essential tool in the design of modern catalytic systems. Emissions legislation is becoming increasingly stringent, and so mathematical models of aftertreatment systems must become more accurate in order to provide confidence that a catalyst will convert pollutants over the required range of conditions. 
Automotive catalytic converter models contain several sub-models that represent processes such as mass and heat transfer, and the rates at which the reactions proceed on the surface of the precious metal. Of these sub-models, the prediction of the surface reaction rates is by far the most challenging due to the complexity of the reaction system and the large number of gas species involved. The reaction rate sub-model uses global reaction kinetics to describe the surface reaction rate of the gas species and is based on the Langmuir Hinshelwood equation further developed by Voltz et al. [1] The reactions can be modelled using the pre-exponential and activation energies of the Arrhenius equations and the inhibition terms. 
The reaction kinetic parameters of aftertreatment models are found from experimental data, where a measured light-off curve is compared against a predicted curve produced by a mathematical model. The kinetic parameters are usually manually tuned to minimize the error between the measured and predicted data. This process is most commonly long, laborious and prone to misinterpretation due to the large number of parameters and the risk of multiple sets of parameters giving acceptable fits. Moreover, the number of coefficients increases greatly with the number of reactions. Therefore, with the growing number of reactions, the task of manually tuning the coefficients is becoming increasingly challenging. 
In the presented work, the authors have developed and implemented a multi-objective genetic algorithm to automatically optimize reaction parameters in AxiSuite®, [2] a commercial aftertreatment model. The genetic algorithm was developed and expanded from the code presented by Michalewicz et al. [3] and was linked to AxiSuite using the Simulink add-on for Matlab. 
The default kinetic values stored within the AxiSuite model were used to generate a series of light-off curves under rich conditions for a number of gas species, including CO, NO, C_{3H8 and C3H6. These light-off curves were used to generate an objective function.} 
This objective function was used to generate a measure of fit for the kinetic parameters. The multi-objective genetic algorithm was subsequently used to search between specified limits to attempt to match the objective function. In total the pre-exponential factors and activation energies of ten reactions were simultaneously optimized. 
The results reported here demonstrate that, given accurate experimental data, the optimization algorithm is successful and robust in defining the correct kinetic parameters of a global kinetic model describing aftertreatment processes.

Significance Driven Computation on Next-Generation Unreliable Platforms

In this paper, we propose a design paradigm for energy efficient and variation-aware operation of next-generation multicore heterogeneous platforms. The main idea behind the proposed approach lies on the observation that not all operations are equally important in shaping the output quality of various applications and of the overall system. Based on such an observation, we suggest that all levels of the software design stack, including the programming model, compiler, operating system (OS) and run-time system should identify the critical tasks and ensure correct operation of such tasks by assigning them to dynamically adjusted reliable cores/units. Specifically, based on error rates and operating conditions identified by a sense-and-adapt (SeA) unit, the OS selects and sets the right mode of operation of the overall system. The run-time system identifies the critical/less-critical tasks based on special directives and schedules them to the appropriate units that are dynamically adjusted for highly-accurate/approximate operation by tuning their voltage/frequency. Units that execute less significant operations can operate at voltages less than what is required for correct operation and consume less power, if required, since such tasks do not need to be always exact as opposed to the critical ones. Such scheme can lead to energy efficient and reliable operation, while reducing the design cost and overheads of conventional circuit/micro-architecture level techniques.

Shortening design time through multiplatform simulations with a portable OpenCL golden-model: the LDPC decoder case

Hardware designers and engineers typically need to explore a multi-parametric design space in order to find the best configuration for their designs using simulations that can take weeks to months to complete. For example, designers of special purpose chips need to explore parameters such as the optimal bitwidth and data representation. This is the case for the development of complex algorithms such as Low-Density Parity-Check (LDPC) decoders used in modern communication systems. Currently, high-performance computing offers a wide set of acceleration options, that range from multicore CPUs to graphics processing units (GPUs) and FPGAs. Depending on the simulation requirements, the ideal architecture to use can vary. In this paper we propose a new design flow based on OpenCL, a unified multiplatform programming model, which accelerates LDPC decoding simulations, thereby significantly reducing architectural exploration and design time. OpenCL-based parallel kernels are used without modifications or code tuning on multicore CPUs, GPUs and FPGAs. We use SOpenCL (Silicon to OpenCL), a tool that automatically converts OpenCL kernels to RTL for mapping the simulations into FPGAs. To the best of our knowledge, this is the first time that a single, unmodified OpenCL code is used to target those three different platforms. We show that, depending on the design parameters to be explored in the simulation, on the dimension and phase of the design, the GPU or the FPGA may suit different purposes more conveniently, providing different acceleration factors. For example, although simulations can typically execute more than 3x faster on FPGAs than on GPUs, the overhead of circuit synthesis often outweighs the benefits of FPGA-accelerated execution.

Cost-Directed Refactoring for Parallel Erlang Programs

This paper presents a new programming methodology for introducing and tuning parallelism in Erlang programs, using source-level code refactoring from sequential source programs to parallel programs written using our skeleton library, Skel. High-level cost models allow us to predict with reasonable accuracy the parallel performance of the refactored program, enabling programmers to make informed decisions about which refactorings to apply. Using our approach, we demonstrate easily obtainable, significant and scalable speedups of up to 21 on a 24-core machine over the sequential code.