Changes to airborne pollen counts across Europe

A progressive global increase in the burden of allergic diseases has affected the industrialized world over the last half century and has been reported in the literature. The clinical evidence reveals a general increase in both incidence and prevalence of respiratory diseases, such as allergic rhinitis (common hay fever) and asthma. Such phenomena may be related not only to air pollution and changes in lifestyle, but also to an actual increase in airborne quantities of allergenic pollen. Experimental enhancements of carbon dioxide (CO) have demonstrated changes in pollen amount and allergenicity, but this has rarely been shown in the wider environment. The present analysis of a continental-scale pollen data set reveals an increasing trend in the yearly amount of airborne pollen for many taxa in Europe, which is more pronounced in urban than semi-rural/rural areas. Climate change may contribute to these changes, however increased temperatures do not appear to be a major influencing factor. Instead, we suggest the anthropogenic rise of atmospheric CO levels may be influential.

Particle Swarm algorithm with Fuzzy decision making for a multi-objective economic and environmental optimization of design of a thermal system

Multi-Objective optimization for designing of a benchmark cogeneration system known as CGAM cogeneration system has been performed. In optimization approach, the thermoeconomic and Environmental aspects have been considered, simultaneously. The environmental objective function has been defined and expressed in cost terms. One of the most suitable optimization techniques developed using a particular class of search algorithms known as; Multi-Objective Particle Swarm Optimization (MOPSO) algorithm has been used here. This approach has been applied to find the set of Pareto optimal solutions with respect to the aforementioned objective functions. An example of fuzzy decision-making with the aid of Bellman-Zadeh approach has been presented and a final optimal solution has been introduced.

Simulation of Au particle interaction on graphene sheets

The interaction of Au particles with few layer graphene is of interest for the formation of the next generation of sensing devices(1). In this paper we investigate the coupling of single gold nanoparticles to a graphene sheet, and multiple gold nanoparticles with a graphene sheet using COMSOL Multiphysics. By using these simulations we are able to determine the electric field strength and associated hot-spots for various gold nanoparticle-graphene systems. The Au nanoparticles were modelled as 8 nm diameter spheres on 1.5 nm thick (5 layers) graphene, with properties of graphene obtained from the refractive index data of Weber(2) and the Au refractive index data from Palik(3). The field was incident along the plane of the sheet with polarisation tested for both s and p. The study showed strong localised interaction between the Au and graphene with limited spread; however the double particle case where the graphene sheet separated two Au nanoparticles showed distinct interaction between the particles and graphene. An offset was introduced (up to 4 nm) resulting in much reduced coupling between the opposed particles as the distance apart increased. Findings currently suggest that the graphene layer has limited interaction with incident fields with a single particle present whilst reducing the coupling region to a very fine area when opposing particles are involved. It is hoped that the results of this research will provide insight into graphene-plasmon interactions and spur the development of the next generation of sensing devices.

Numerical simulations of particle deposition in metal foam heat exchangers

Australia is a high-potential country for geothermal power with reserves currently estimated in the tens of millions of petajoules, enough to power the nation for at least 1000 years at current usage. However, these resources are mainly located in isolated arid regions where water is scarce. Therefore, wet cooling systems for geothermal plants in Australia are the least attractive solution and thus air-cooled heat exchangers are preferred. In order to increase the efficiency of such heat exchangers, metal foams have been used. One issue raised by this solution is the fouling caused by dust deposition. In this case, the heat transfer characteristics of the metal foam heat exchanger can dramatically deteriorate. Exploring the particle deposition property in the metal foam exchanger becomes crucial. This paper is a numerical investigation aimed to address this issue. Two dimensional (2D) numerical simulations of a standard one-row tube bundle wrapped with metal foam in cross-flow are performed and highlight preferential particle deposition areas.

Numerical simulations of particle deposition in metal foam heat exchangers

Australia is a high potential country for geothermal power with reserves currently estimated in the tens of millions of petajoules, enough to power the nation for at least 1000 years at current usage.However, these resources are mainly located in isolated arid regions where water is scarce. Therefore, wet cooling systems for geothermal plants in Australia are the least attractive solution and thus air-cooled heat exchangers are preferred. In order to increase the efficiency of such heat exchangers, metal foams have been used. One issue raised by this solution is the fouling caused by dust deposition. In this case, the heat transfer characteristics of the metal foam heat exchanger can dramatically deteriorate. Exploring the particle deposition property in the metal foam exchanger becomes crucial. This paper is a numerical investigation aimed to address this issue. Two-dimensional(2D numerical simulations of a standard one-row tube bundle wrapped with metal foam in cross-flow are performed and highlight preferential particle deposition areas.

On Chinese Modal Particle A (啊) : A Pragmatic and Semantic Study

Chinese modal particles feature prominently in Chinese people’s daily use of the language, but their pragmatic and semantic functions are elusive as commonly recognised by Chinese linguists and teachers of Chinese as a foreign language. This book originates from an extensive and intensive empirical study of the Chinese modal particle a (啊), one of the most frequently used modal particles in Mandarin Chinese. In order to capture all the uses and the underlying meanings of the particle, the author transcribed the first 20 episodes, about 20 hours in length, of the popular Chinese TV drama series Kewang ‘Expectations’, which yielded a corpus data of more than 142’000 Chinese characters with a total of 1829 instances of the particle all used in meaningful communicative situations. Within its context of use, every single occurrence of the particle was analysed in terms of its pragmatic and semantic contributions to the hosting utterance. Upon this basis the core meanings were identified which were seen as constituting the modal nature of the particle.

A modified particle swarm optimization for correlated phenomena

The wide applicability of correlation analysis inspired the development of this paper. In this paper, a new correlated modified particle swarm optimization (COM-PSO) is developed. The Correlation Adjustment algorithm is proposed to recover the correlation between the considered variables of all particles at each of iterations. It is shown that the best solution, the mean and standard deviation of the solutions over the multiple runs as well as the convergence speed were improved when the correlation between the variables was increased. However, for some rotated benchmark function, the contrary results are obtained. Moreover, the best solution, the mean and standard deviation of the solutions are improved when the number of correlated variables of the benchmark functions is increased. The results of simulations and convergence performance are compared with the original PSO. The improvement of results, the convergence speed, and the ability to simulate the correlated phenomena by the proposed COM-PSO are discussed by the experimental results.

Distribution state estimation based on particle swarm and doubly loop mutant optimization (DLM-PSO)

This paper presents a novel algorithm based on particle swarm optimization (PSO) to estimate the states of electric distribution networks. In order to improve the performance, accuracy, convergence speed, and eliminate the stagnation effect of original PSO, a secondary PSO loop and mutation algorithm as well as stretching function is proposed. For accounting uncertainties of loads in distribution networks, pseudo-measurements is modeled as loads with the realistic errors. Simulation results on 6-bus radial and 34-bus IEEE test distribution networks show that the distribution state estimation based on proposed DLM-PSO presents lower estimation error and standard deviation in comparison with algorithms such as WLS, GA, HBMO, and original PSO.

Parameter estimation of thrust models of uninhabited airborne systems

This paper presents a method for the estimation of thrust model parameters of uninhabited airborne systems using specific flight tests. Particular tests are proposed to simplify the estimation. The proposed estimation method is based on three steps. The first step uses a regression model in which the thrust is assumed constant. This allows us to obtain biased initial estimates of the aerodynamic coeficients of the surge model. In the second step, a robust nonlinear state estimator is implemented using the initial parameter estimates, and the model is augmented by considering the thrust as random walk. In the third step, the estimate of the thrust obtained by the observer is used to fit a polynomial model in terms of the propeller advanced ratio. We consider a numerical example based on Monte-Carlo simulations to quantify the sampling properties of the proposed estimator given realistic flight conditions.

Thermal stability and decomposition kinetics of styrene-butadiene rubber nanocomposites filled with different particle sized kaolinites

A series of styrene-butadiene rubber (SBR) nanocomposites filledwith different particle sized kaolinites are prepared via a latex blending method. The thermal stabilities of these clay polymer nanocomposites (CPN) are characterized by a range of techniques including thermogravimetry (TG), digital photos, scanning electron microscopy (SEM) and Raman spectroscopy. These CPN show some remarkable improvement in thermal stability compared to that of the pure SBR. With the increase of kaolinite particle size, the residual char content and the average activation energy of kaolinite SBR nanocomposites all decrease; the pyrolysis residues become porous; the crystal carbon in the pyrolysis residues decrease significantly from 58.23% to 44.41%. The above results prove that the increase of kaolinite particle size is not beneficial in improving the thermal stability of kaolinite SBR nanocomposites.

Insight into morphology and structure of different particle sized kaolinites with same origin

The particle size, morphology, crystallinity order and structural defects of four kaolinite samples are characterized by the techniques including particle size analysis, scanning electron microscopy (SEM), X-ray diffraction (XRD), Raman spectroscopy, Fourier transform infrared spectroscopy (FTIR) and magic angle spinning nuclear magnetic resonance spectroscopy (MAS NMR). The particle size of four kaolinite samples gradually increases. Four samples all belong to the ordered kaolinite and show a decrease in structural order with the increase of kaolinite particle size. The changes of structural defect are proved by the increase of the band splitting in Raman spectroscopy, the decrease of the intensity of absorption bands in infrared spectroscopy, and the decrease of equivalent silicon atom and the increase of nonequivalent aluminum atom in MAS NMR spectroscopy. The differences in morphology and structural defect are attributed to the broken bonds of Al–O–Si, Al–O–Al and Si–O–Si and the Al substitution for Si in tetrahedral sheets.

High-frequency global navigation satellite system’s receivers for airborne gravimetry

The development of global navigation satellite systems (GNSS) provides a solution of many applied problems with increasingly higher quality and accuracy nowadays. Researches that are carried out by the Bavarian Academy of Sciences and Humanities in Munich (BAW) in the field of airborne gravimetry are based on sophisticated data processing from high frequency GNSS receiver for kinematic aircraft positioning. Applied algorithms for inertial acceleration determination are based on the high sampling rate (50Hz) and on reducing of such factors as ionosphere scintillation and multipath at aircraft /antenna near field effects. The quality of the GNSS derived kinematic height are studied also by intercomparison with lift height variations collected by a precise high sampling rate vertical scale [1]. This work is aimed at the ways of more accurate determination of mini-aircraft altitude by means of high frequency GNSS receivers, in particular by considering their dynamic behaviour.

Characteristics of ultrafine particle sources and deposition rates in primary school classrooms

The aim of this work was to investigate changes in particle number concentration (PNC) within naturally ventilated primary school classrooms arising from local sources either within or adjacent to the classrooms. We quantify the rate at which ultrafine particles were emitted either from printing, grilling, heating or cleaning activities and the rate at which the particles were removed by both deposition and air exchange processes. At each of 25 schools in Brisbane, Australia, two weeks of measurements of PNC and CO2 were taken both outdoors and in the two classrooms. Bayesian regression modelling was employed in order to estimate the relevant rates and analyse the relationship between air exchange rate (AER), particle infiltration and the deposition rates of particle generated from indoor activities in the classrooms. During schooling hours, grilling events at the school tuckshop as well as heating and printing in the classrooms led to indoor PNCs being elevated by a factor of more than four, with emission rates of (2.51 ± 0.25) x 1011 p min-1, (8.99 ± 6.70) x 1011 p min-1 and (5.17 ± 2.00) x 1011 p min-1, respectively. During non-school hours, cleaning events elevated indoor PNC by a factor of above five, with an average emission rate of (2.09 ± 6.30) x 1011 p min-1. Particles were removed by both air exchange and deposition; chiefly by ventilation when AER > 0.7 h-1 and by deposition when AER < 0.7 h-1.

A particle based model to simulate microscale morphological changes of plant tissues during drying

Fundamental understanding on microscopic physical changes of plant materials is vital to optimize product quality and processing techniques, particularly in food engineering. Although grid-based numerical modelling can assist in this regard, it becomes quite challenging to overcome the inherited complexities of these biological materials especially when such materials undergo critical processing conditions such as drying, where the cellular structure undergoes extreme deformations. In this context, a meshfree particle based model was developed which is fundamentally capable of handling extreme deformations of plant tissues during drying. The model is built by coupling a particle based meshfree technique: Smoothed Particle Hydrodynamics (SPH) and a Discrete Element Method (DEM). Plant cells were initiated as hexagons and aggregated to form a tissue which also accounts for the characteristics of the middle lamella. In each cell, SPH was used to model cell protoplasm and DEM was used to model the cell wall. Drying was incorporated by varying the moisture content, the turgor pressure, and cell wall contraction effects. Compared to the state of the art grid-based microscale plant tissue drying models, the proposed model can be used to simulate tissues under excessive moisture content reductions incorporating cell wall wrinkling. Also, compared to the state of the art SPH-DEM tissue models, the proposed model better replicates real tissues and the cell-cell interactions used ensure efficient computations. Model predictions showed good agreement both qualitatively and quantitatively with experimental findings on dried plant tissues. The proposed modelling approach is fundamentally flexible to study different cellular structures for their microscale morphological changes at dehydration.

Performance and gaseous and particle emissions from a liquefied petroleum gas (LPG) fumigated compression ignition engine

In this study, an LPG fumigation system was fitted to a Euro III compression ignition (CI) engine to explore its impact on performance, and gaseous and particulate emissions. LPG was introduced to the intake air stream (as a secondary fuel) by using a low pressure fuel injector situated upstream of the turbocharger. LPG substitutions were test mode dependent, but varied in the range of 14-29% by energy. The engine was tested over a 5 point test cycle using ultra low sulphur diesel (ULSD), and a low and high LPG substitution at each test mode. The results show that LPG fumigation coerces the combustion into pre-mixed mode, as increases in the peak combustion pressure (and the rate of pressure rise) were observed in most tests. The emissions results show decreases in nitric oxide (NO) and particulate matter (PM2.5) emissions; however, very significant increases in carbon monoxide (CO) and hydrocarbon (HC) emissions were observed. A more detailed investigation of the particulate emissions showed that the number of particles emitted was reduced with LPG fumigation at all test settings – apart from mode 6 of the ECE R49 test cycle. Furthermore, the particles emitted generally had a slightly larger median diameter with LPG fumigation, and had a smaller semi-volatile fraction relative to ULSD. Overall, the results show that with some modifications, LPG fumigation systems could be used to extend ULSD supplies without adversely impacting on engine performance and emissions.