Investigations of ultrafine particles emitted by ships and other transport modes in the port of Brisbane

This research measured particle and gaseous emissions from ships and trains operating within the Port of Brisbane, and explored their influence on ambient air composition at a downwind suburban measurement site. The ship and train emission factor investigations resulted in the development of novel measurement techniques which permit the quantification of particle and gaseous emission factors using samples collected from post-emission exhaust plumes. The urban influence investigation phase of the project produced a new approach to identifying influences from ship emissions.

Periodic bubble emission and appearance of an ordered bubble sequence (train) during condensation in a single microchannel

Condensation of steam in a single microchannel, silicon test section was investigated visually at low flow rates. The microchannel was rectangular in cross-section with a depth of 30 pm, a width of 800 mu m and a length of 5.0 mm, covered with a Pyrex glass to allow for visualization of the bubble formation process. By varying the cooling rate during condensation of the saturated water vapor, it was possible to control the shape, size and frequency of the bubbles formed. At low cooling rates using only natural air convection from the ambient environment, the flow pattern in the microchannel consisted of a nearly stable elongated bubble attached upstream (near the inlet) that pinched off into a train of elliptical bubbles downstream of the elongated bubble. It was observed that these elliptical bubbles were emitted periodically from the tip of the elongated bubble at a high frequency, with smaller size than the channel width. The shape of the emitted bubbles underwent modifications shortly after their generation until finally becoming a stable vertical ellipse, maintaining its shape and size as it flowed downstream at a constant speed. These periodically emitted elliptical bubbles thus formed an ordered bubble sequence (train). At higher cooling rates using chilled water in a copper heat sink attached to the test section, the bubble formation frequency increased significantly while the bubble size decreased, all the while forming a perfect bubble train flowing downstream of the microchannel. The emitted bubbles in this case immediately formed into a circular shape without any further modification after their separation from the elongated bubble upstream. The present study suggests that a method for controlling the size and generation frequency of microbubbles could be so developed, which may be of interest for microfluidic applications. The breakup of the elongated bubble is caused by the large Weber number at the tip of the elongated bubble induced by the maximum vapor velocity at the centerline of the microchannel inside the elongated bubble and the smaller surface tension force of water at the tip of the elongated bubble.

Remote measurement of diesel locomotive emission factors and particle size distributions

A technique for analysing exhaust emission plumes from unmodified locomotives under real world conditions is described and applied to the task of characterizing plumes from railway trains servicing an Australian shipping port. The method utilizes the simultaneous measurement, downwind of the railway line, of the following pollutants; particle number, PM2.5 mass fraction, SO2, NOx and CO2, with the last of these being used as an indicator of fuel combustion. Emission factors are then derived, in terms of number of particles and mass of pollutant emitted per unit mass of fuel consumed. Particle number size distributions are also presented. The practical advantages of the method are discussed including the capacity to routinely collect emission factor data for passing trains and to thereby build up a comprehensive real world database for a wide range of pollutants. Samples from 56 train movements were collected, analyzed and presented. The quantitative results for emission factors are: EF(N)=(1.7±1)×1016 kg-1, EF(PM2.5)= (1.1±0.5) g·kg-1, EF(NOx)= (28±14) g·kg-1, and EF(SO2 )= (1.4±0.4) g·kg-1. The findings are compared with comparable previously published work. Statistically significant (p<α, α=0.05) correlations within the group of locomotives sampled were found between the emission factors for particle number and both SO2 and NOx.

Acoustic emission condition monitoring : an application for wind turbine fault detection

Low speed rotating machines which are the most critical components in drive train of wind turbines are often menaced by several technical and environmental defects. These factors contribute to mount the economic requirement for Health Monitoring and Condition Monitoring of the systems. When a defect is happened in such system result in reduced energy loss rates from related process and due to it Condition Monitoring techniques that detecting energy loss are very difficult if not possible to use. However, in the case of Acoustic Emission (AE) technique this issue is partly overcome and is well suited for detecting very small energy release rates. Acoustic Emission (AE) as a technique is more than 50 years old and in this new technology the sounds associated with the failure of materials were detected. Acoustic wave is a non-stationary signal which can discover elastic stress waves in a failure component, capable of online monitoring, and is very sensitive to the fault diagnosis. In this paper the history and background of discovering and developing AE is discussed, different ages of developing AE which include Age of Enlightenment (1950-1967), Golden Age of AE (1967-1980), Period of Transition (1980-Present). In the next section the application of AE condition monitoring in machinery process and various systems that applied AE technique in their health monitoring is discussed. In the end an experimental result is proposed by QUT test rig which an outer race bearing fault was simulated to depict the sensitivity of AE for detecting incipient faults in low speed high frequency machine.

Femtosecond superradiant emission in AlGaInAs quantum-well semiconductor laser structures.

Ultrashort superradiant pulse generation from a 1580 nm AlGaInAs multiple quantum-well (MQW) semiconductor structure has been experimentally demonstrated for the first time. Superradiance is confirmed by analyzing the evolution of the optical temporal waveforms and spectra. Superradiant trends and regimes are studied as a function of driving condition. An optical pulse train is obtained at 1580 nm wavelength, with pulse durations as short as 390 fs and pulse peak powers of 7.2 W.

Identifying the damage mechanisms in paper using the acoustic emission monitoring technique

This paper investigates the use of the acoustic emission (AE) monitoring technique for use in identifying the damage mechanisms present in paper associated with its production process. The microscopic structure of paper consists of a random mesh of paper fibres connected by hydrogen bonds. This implies the existence of two damage mechanisms, the failure of a fibre-fibre bond and the failure of a fibre. This paper describes a hybrid mathematical model which couples the mechanics of the mass-spring model to the acoustic wave propagation model for use in generating the acoustic signal emitted by complex structures of paper fibres under strain. The derivation of the mass-spring model can be found in [1,2], with details of the acoustic wave equation found in [3,4]. The numerical implementation of the vibro-acoustic model is discussed in detail with particular emphasis on the damping present in the numerical model. The hybrid model uses an implicit solver which intrinsically introduces artificial damping to the solution. The artificial damping is shown to affect the frequency response of the mass-spring model, therefore certain restrictions on the simulation time step must be enforced so that the model produces physically accurate results. The hybrid mathematical model is used to simulate small fibre networks to provide information on the acoustic response of each damage mechanism. The simulated AEs are then analysed using a continuous wavelet transform (CWT), described in [5], which provides a two dimensional time-frequency representation of the signal. The AEs from the two damage mechanisms show different characteristics in the CWT so that it is possible to define a fibre-fibre bond failure by the criteria listed below. The dominant frequency components of the AE must be at approximately 250 kHz or 750 kHz. The strongest frequency component may be at either approximately 250 kHz or 750 kHz. The duration of the frequency component at approximately 250 kHz is longer than that of the frequency component at approximately 750 kHz. Similarly, the criteria for identifying a fibre failure are given below. The dominant frequency component of the AE must be greater than 800 kHz. The duration of the dominant frequency component must be less than 5.00E-06 seconds. The dominant frequency component must be present at the front of the AE. Essentially, the failure of a fibre-fibre bond produces a low frequency wave and the failure of a fibre produces a high frequency pulse. Using this theoretical criteria, it is now possible to train an intelligent classifier such as the Self-Organising Map (SOM) [6] using the experimental data. First certain features must be extracted from the CWTs of the AEs for use in training the SOM. For this work, each CWT is divided into 200 windows of 5E-06s in duration covering a 100 kHz frequency range. The power ratio for each windows is then calculated and used as a feature. Having extracted the features from the AEs, the SOM can now be trained, but care is required so that the both damage mechanisms are adequately represented in the training set. This is an issue with paper as the failure of the fibre-fibre bonds is the prevalent damage mechanism. Once a suitable training set is found, the SOM can be trained and its performance analysed. For the SOM described in this work, there is a good chance that it will correctly classify the experimental AEs.

Polycyclic aromatic hydrocarbon emission loads and profiles from the burning of locally grown wood species in Victoria, Australia - Some pilot project results

A testing facility for combustion of biomass and sampling of emissions has been established at Deakin University. In this pilot project using this facility, four kinds of locally grown wood species were burned and the particle emissions sampled and analysed for Polycyclic Aromatic Hydrocarbons (PAHs). The selected wood species covering pine, red gum, yellow box and sugar gum, are the most popular domestic fuel wood in Australia. Particulate matter emissions from burning of each load of wood were sampled from the flue using a standard stack emission sampling train. The particle-laden filters were extracted and the .extract analysed to determine PAH concentrations by Gas Chromatographyl Mass Spectrometer (Gc/MS). The sampling was conducted under two different burning conditions with the air inlet of the combustion chamber fully open and with it half open. A suite of 15 PAHs, ranging from naphthalene (C IOHB) to dibenzolahlanthracene (C12H14), were selected for analysis. PAH profiles for the four wood species, under the different burning regimes, have been generated. Some preliminary emission factors for the different wood species have been derived as microgram of summed PAHs (rPAHs) emittedlkilogram of wood burned. Total Particulate Matter (TPM) emission factors were also obtained from gravimetric measurement of the sample filter before and after the combustion. Based on these emission factors, pine displayed the highest level of rPAHs emitted from the combustion of the four wood species, with sugar gum showing the lowest level of rPAHs emission. Emission factors associated with the slow burning condition clearly showed higher l:PAH levels compared to the faster burning condition. During the faster burning condition, red gum and pine show a higher percentage of rPAH to TPM than sugar gum or yellow box. Under the slower burning. the l:PAHlTPM ratio in every case was greater.

Thermal Treatments of Fe—Mn Alkoxide of Glycerol: Infrared absorption and emission

Synthetic Fe—Mn alkoxide of glycerol samples are submitted to controlled heating conditions and examined by IR absorption spectroscopy. On the other hand, the same sample is studied by infrared emission spectroscopy (IRES), upon heating in situ from 100 to 600°C. The spectral techniques employed in this contribution, especially IRES, show that as a result of the thermal treatments ferromagnetic oxides (manganese ferrite) are formed between 350 and 400°C. Some further spectral changes are seen at higher temperatures.

Thermal treatment of weddellite—a Raman and infrared emission spectroscopic study

Thermal transformations of natural calcium oxalate dihydrate known in mineralogy as weddellite have been undertaken using a combination of Raman microscopy and infrared emission spectroscopy. The vibrational spectroscopic data was complimented with high resolution thermogravimetric analysis combined with evolved gas mass spectrometry. TG–MS identified three mass loss steps at 114, 422 and 592 °C. In the first mass loss step water is evolved only, in the second and third steps carbon dioxide is evolved. The combination of Raman microscopy and a thermal stage clearly identifies the changes in the molecular structure with thermal treatment. Weddellite is the phase in the temperature range up to the pre-dehydration temperature of 97 °C. At this temperature, the phase formed is whewellite (calcium oxalate monohydrate) and above 114 °C the phase is the anhydrous calcium oxalate. Above 422 °C, calcium carbonate is formed. Infrared emission spectroscopy shows that this mineral decomposes at around 650 °C. Changes in the position and intensity of the C=O and C---C stretching vibrations in the Raman spectra indicate the temperature range at which these phase changes occur.

Quantification of motor vehicle emission factors from on road measurements

Assessment and prediction of the impact of vehicular traffic emissions on air quality and exposure levels requires knowledge of vehicle emission factors. The aim of this study was quantification of emission factors from an on road, over twelve months measurement program conducted at two sites in Brisbane: 1) freeway type (free flowing traffic at about 100 km/h, fleet dominated by small passenger cars - Tora St); and 2) urban busy road with stop/start traffic mode, fleet comprising a significant fraction of heavy duty vehicles - Ipswich Rd. A physical model linking concentrations measured at the road for specific meteorological conditions with motor vehicle emission factors was applied for data analyses. The focus of the study was on submicrometer particles; however the measurements also included supermicrometer particles, PM2.5, carbon monoxide, sulfur dioxide, oxides of nitrogen. The results of the study are summarised in this paper. In particular, the emission factors for submicrometer particles were 6.08 x 1013 and 5.15 x 1013 particles per vehicle-1 km-1 for Tora St and Ipswich Rd respectively and for supermicrometer particles for Tora St, 1.48 x 109 particles per vehicle-1 km-1. Emission factors of diesel vehicles at both sites were about an order of magnitude higher than emissions from gasoline powered vehicles. For submicrometer particles and gasoline vehicles the emission factors were 6.08 x 1013 and 4.34 x 1013 particles per vehicle-1 km-1 for Tora St and Ipswich Rd, respectively, and for diesel vehicles were 5.35 x 1014 and 2.03 x 1014 particles per vehicle-1 km-1 for Tora St and Ipswich Rd, respectively. For supermicrometer particles at Tora St the emission factors were 2.59 x 109 and 1.53 x 1012 particles per vehicle-1 km-1, for gasoline and diesel vehicles, respectively.