Experimental study of the effects of temperature variation on droplet size and wetness fraction in a low-pressure model steam turbine

The three-stage low-pressure model steam turbine at the Institute of Thermal Turbomachinery and Machinery Laboratory (ITSM) was used to study the impact of three different steam inlet temperatures on the homogeneous condensation process and the resulting wetness topology. The droplet spectrum as well as the particle number concentration were measured in front of the last stage using an optical-pneumatic probe. At design load, condensation starts inside the stator of the second stage. A change in the steam inlet temperature is able to shift the location of condensation onset within the blade row up- or downstream and even into adjoining blade passages, which leads to significantly different local droplet sizes and wetness fractions due to different local expansion rates. The measured results are compared to steady three-dimensional computational fluid dynamics calculations. The predicted nucleation zones could be largely confirmed by the measurements. Although the trend of measured and calculated droplet size across the span is satisfactory, there are considerable differences between the measured and computed droplet spectrum and wetness fractions. © IMechE 2013 Reprints and permissions: sagepub.co.uk/ journalsPermissions.nav.

Investigation of the dilution process for measurement of particulate matter from spark-ignition engines

Measurements of particulate matter (PM) from spark ignition (SI) engine exhaust using dilution tunnels will become more prevalent as emission standards are tightened. Hence, a study of the dilution process was undertaken in order to understand how various dilution related parameters affect the accuracy with which PM sizes and concentrations can be determined. A SI and a compression ignition (CI) engine were separately used to examine parameters of the dilution process; the present work discusses the results in the context of SI exhaust dilution. A Scanning Mobility Particle Sizer (SMPS) was used to measure the size distribution, number density, and volume fraction of PM. Temperature measurements in the exhaust pipe and dilution tunnel reveal the degree of mixing between exhaust and dilution air, the effect of flowrate on heat transfer from undiluted and diluted exhaust to the environment, and the minimum permissible dilution ratio for a maximum sample temperature of 52°C. Measurements of PM concentrations as a function of dilution ratio show the competing effects of temperature and particle/vapor concentrations on particle growth dynamics, which result in a range of dilution ratios-from 13 to 18-where the effect of dilution ratio, independent of flowrate, is kept to a minimum. This range of dilution ratios is therefore optimal in order to achieve repeatable PM concentration measurements. Particle dynamics during transit through the tunnel operating at the optimal dilution ratio was found statistically insignificant compared to data scatter. Such small differences in number concentration may be qualitatively representative of particle losses for SI exhaust, but small increases in PM volume fraction during transit through the tunnel may significantly underestimate accretion of mass due to unburned hydrocarbons (HCs) emitted by SI engines. The fraction of SI-derived PM mass due to adsorbed/absorbed vapor, estimated from these data, is consistent with previous chemical analyses of PM. © 1998 Society of Automotive Engineers, Inc.

Updated correlation between aircraft smoke number and black carbon concentration

Aircraft emissions of black carbon (BC) contribute to anthropogenic climate forcing and degrade air quality. The smoke number (SN) is the current regulatory measure of aircraft particulate matter emissions and quantifies exhaust plume visibility. Several correlations between SN and the exhaust mass concentration of BC (CBC) have been developed, based on measurements relevant to older aircraft engines. These form the basis of the current standard method used to estimate aircraft BC emissions (First Order Approximation version 3 [FOA3]) for the purposes of environmental impact analyses. In this study, BC with a geometric mean diameter (GMD) of 20, 30, and 60 nm and filter diameters of 19 and 35 mm are used to investigate the effect of particle size and sampling variability on SN measurements. For BC with 20 and 30 nm GMD, corresponding to BC emitted by modern aircraft engines, a smaller SN results from a given CBC than is the case for BC with 60 nm GMD, which is more typical of older engines. An updated correlation between CBC and SNthat accounts for typical size of BC emitted by modern aircraft is proposed. An uncertainty of ±25% accounts for variation in GMD in the range 20-30 nm and for the range of filter diameters. The SN-CBC correlation currently used in FOA3 underestimates by a factor of 2.5-3 for SN <15, implying that current estimates of aircraft BC emissions derived from SN are underestimated by the same factor. Copyright © American Association for Aerosol Research.

Effect of bend orientation on life and puncture point location due to solid particle erosion of a high concentration flow in pneumatic conveyors

An investigation into predicting failure of pneumatic conveyor pipe bends due to hard solid particle impact erosion has been carried out on an industrial scale test rig. The bend puncture point locations may vary with many factors. However, bend orientation was suspected of being a main factor due to the biased particle distribution pattern of a high concentration flow. In this paper, puncture point locations have been studied with different pipe bend orientations and geometry (a solids loading ratio of 10 being used for the high concentration flow). Test results confirmed that the puncture point location is indeed most significantly influenced by the bend orientation (especially for a high concentration flow) due to the biased particle distribution and biased particle flux distribution. © 2004 Elsevier B.V. All rights reserved.

Effect of particle concentration on erosion rate of mild steel bends in a pneumatic conveyor

Particle concentration is known as a main factor that affects erosion rate of pipe bends in pneumatic conveyors. With consideration of different bend radii, the effect of particle concentration on weight loss of mild steel bends has been investigated in an industrial scale test rig. Experimental results show that there was a significant reduction of the specific erosion rate for high particle concentrations. This reduction was considered to be as a result of the shielding effect during the particle impacts. An empirical model is given. Also a theoretical study of scaling on the shielding effect, and comparisons with some existing models, are presented. It is found that the reduction in specific erosion rate (relative to particle concentration) has a stronger relationship in conveying pipelines than has been found in the erosion tester. © 2004 Elsevier B.V. All rights reserved.

The role of the catalytic particle in the growth of carbon nanotubes by plasma enhanced chemical vapor deposition

Vertically aligned carbon nanotubes were synthesized by plasma enhanced chemical vapor deposition using nickel as a metal catalyst. High resolution transmission electron microscopy analysis of the particle found at the tip of the tubes reveals the presence of a metastable carbide Ni3C. Since the carbide is found to decompose upon annealing at 600 degreesC, we suggest that Ni3C is formed after the growth is stopped due to the rapid cooling of the Ni-C interstitial solid solution. A detailed description of the tip growth mechanism is given, that accounts for the composite structure of the tube walls. The shape and size of the catalytic particle determine the concentration gradient that drives the diffusion of C atoms across and though the metal. (C) 2004 American Institute of Physics.

A backward particle interpretation of Feynman-Kac formulae

We design a particle interpretation of Feynman-Kac measures on path spaces based on a backward Markovian representation combined with a traditional mean field particle interpretation of the flow of their final time marginals. In contrast to traditional genealogical tree based models, these new particle algorithms can be used to compute normalized additive functionals "on-the-fly" as well as their limiting occupation measures with a given precision degree that does not depend on the final time horizon. We provide uniform convergence results with respect to the time horizon parameter as well as functional central limit theorems and exponential concentration estimates. Our results have important consequences for online parameter estimation for non-linear non-Gaussian state-space models. We show how the forward filtering backward smoothing estimates of additive functionals can be computed using a forward only recursion.

Wear of hardfacing white cast irons by solid particle erosion

The response of three commercial weld-hardfacing alloys to erosive wear has been studied. These were high chromium white cast irons, deposited by an open-arc welding process, widely used in the mineral processing and steelmaking industries for wear protection. Erosion tests were carried out with quartz sand, silicon carbide grit and blast furnace sinter of two different sizes, at a velocity of 40 m s-1 and at impact angles in the range 20° to 90°. A monolithic white cast iron and mild steel were also tested for comparison. Little differences were found in the wear rates when silica sand or silicon carbide grit was used as the erodent. Significant differences were found, however, in the rankings of the materials. Susceptibility to fracture of the carbide particles in the white cast irons played an important role in the behaviour of the white cast irons. Sinter particles were unable to cause gross fracture of the carbides and so those materials with a high volume fraction of carbides showed the greatest resistance to erosive wear. Silica and silicon carbide were capable of causing fracture of the primary carbides. Concentration of plastic strain in the matrix then led to a high wear rate for the matrix. At normal impact with silica or silicon carbide erodents mild steel showed a greater resistance to erosive wear than these alloys. © 1995.

Multiple object tracking using evolutionary MCMC-based particle algorithms

Algorithms are presented for detection and tracking of multiple clusters of co-ordinated targets. Based on a Markov chain Monte Carlo sampling mechanization, the new algorithms maintain a discrete approximation of the filtering density of the clusters' state. The filters' tracking efficiency is enhanced by incorporating various sampling improvement strategies into the basic Metropolis-Hastings scheme. Thus, an evolutionary stage consisting of two primary steps is introduced: 1) producing a population of different chain realizations, and 2) exchanging genetic material between samples in this population. The performance of the resulting evolutionary filtering algorithms is demonstrated in two different settings. In the first, both group and target properties are estimated whereas in the second, which consists of a very large number of targets, only the clustering structure is maintained. © 2009 IFAC.

Optimal design of Functionally Graded Materials using a procedural model and Particle Swarm Optimization

A new method for the optimal design of Functionally Graded Materials (FGM) is proposed in this paper. Instead of using the widely used explicit functional models, a feature tree based procedural model is proposed to represent generic material heterogeneities. A procedural model of this sort allows more than one explicit function to be incorporated to describe versatile material gradations and the material composition at a given location is no longer computed by simple evaluation of an analytic function, but obtained by execution of customizable procedures. This enables generic and diverse types of material variations to be represented, and most importantly, by a reasonably small number of design variables. The descriptive flexibility in the material heterogeneity formulation as well as the low dimensionality of the design vectors help facilitate the optimal design of functionally graded materials. Using the nature-inspired Particle Swarm Optimization (PSO) method, functionally graded materials with generic distributions can be efficiently optimized. We demonstrate, for the first time, that a PSO based optimizer outperforms classical mathematical programming based methods, such as active set and trust region algorithms, in the optimal design of functionally graded materials. The underlying reason for this performance boost is also elucidated with the help of benchmarked examples. © 2011 Elsevier Ltd. All rights reserved.