Study of particulate matter removal mechanism by using non-thermal plasma technology

Numbers of diesel engines in both stationary and mobile applications are increasing nowadays. Diesel engines emit lower Hydrocarbon (HC) and Carbon monoxide (CO) than gasoline engines. However, they can produce more nitrogen oxides (NOx) and have higher particulate matter (PM). On the other hand, emissions standards are getting stringent day by day due to considerable concerns about unregulated pollutants and particularly ultrafine particles deleterious effect on human health. Non-thermal plasma (NTP) treatment of exhaust gas is known as a promising technology for both NOx and PM reduction by introducing plasma inside the exhaust gas. Vehicle exhaust gases undergo chemical changes when exposed to plasma. In this study, the PM removal mechanism using NTP by applying high voltage pulses of up to 20 kVpp with a repetition rate of 10 kHz are investigated. It is found that, voltage increase not necessarily has a positive effect on PM removal in diesel engine emissions.

Effect of pulsed power on particle matter in diesel engine exhaust using a DBD plasma reactor

Nonthermal plasma (NTP) treatment of exhaust gas is a promising technology for both nitrogen oxides (NOX) and particulate matter (PM) reduction by introducing plasma into the exhaust gases. This paper considers the effect of NTP on PM mass reduction, PM size distribution, and PM removal efficiency. The experiments are performed on real exhaust gases from a diesel engine. The NTP is generated by applying high-voltage pulses using a pulsed power supply across a dielectric barrier discharge (DBD) reactor. The effects of the applied high-voltage pulses up to 19.44 kVpp with repetition rate of 10 kHz are investigated. In this paper, it is shown that the PM removal and PM size distribution need to be considered both together, as it is possible to achieve high PM removal efficiency with undesirable increase in the number of small particles. Regarding these two important factors, in this paper, 17 kVpp voltage level is determined to be an optimum point for the given configuration. Moreover, particles deposition on the surface of the DBD reactor is found to be a significant phenomenon, which should be considered in all plasma PM removal tests.

Intelligent reliability analysis with incomplete covariates

The reliability analysis is crucial to reducing unexpected down time, severe failures and ever tightened maintenance budget of engineering assets. Hazard based reliability methods are of particular interest as hazard reflects the current health status of engineering assets and their imminent failure risks. Most existing hazard models were constructed using the statistical methods. However, these methods were established largely based on two assumptions: one is the assumption of baseline failure distributions being accurate to the population concerned and the other is the assumption of effects of covariates on hazards. These two assumptions may be difficult to achieve and therefore compromise the effectiveness of hazard models in the application. To address this issue, a non-linear hazard modelling approach is developed in this research using neural networks (NNs), resulting in neural network hazard models (NNHMs), to deal with limitations due to the two assumptions for statistical models. With the success of failure prevention effort, less failure history becomes available for reliability analysis. Involving condition data or covariates is a natural solution to this challenge. A critical issue for involving covariates in reliability analysis is that complete and consistent covariate data are often unavailable in reality due to inconsistent measuring frequencies of multiple covariates, sensor failure, and sparse intrusive measurements. This problem has not been studied adequately in current reliability applications. This research thus investigates such incomplete covariates problem in reliability analysis. Typical approaches to handling incomplete covariates have been studied to investigate their performance and effects on the reliability analysis results. Since these existing approaches could underestimate the variance in regressions and introduce extra uncertainties to reliability analysis, the developed NNHMs are extended to include handling incomplete covariates as an integral part. The extended versions of NNHMs have been validated using simulated bearing data and real data from a liquefied natural gas pump. The results demonstrate the new approach outperforms the typical incomplete covariates handling approaches. Another problem in reliability analysis is that future covariates of engineering assets are generally unavailable. In existing practices for multi-step reliability analysis, historical covariates were used to estimate the future covariates. Covariates of engineering assets, however, are often subject to substantial fluctuation due to the influence of both engineering degradation and changes in environmental settings. The commonly used covariate extrapolation methods thus would not be suitable because of the error accumulation and uncertainty propagation. To overcome this difficulty, instead of directly extrapolating covariate values, projection of covariate states is conducted in this research. The estimated covariate states and unknown covariate values in future running steps of assets constitute an incomplete covariate set which is then analysed by the extended NNHMs. A new assessment function is also proposed to evaluate risks of underestimated and overestimated reliability analysis results. A case study using field data from a paper and pulp mill has been conducted and it demonstrates that this new multi-step reliability analysis procedure is able to generate more accurate analysis results.

Carbon dioxide reforming of methane to produce synthesis gas over metal-supported catalysts: State of the art

Carbon dioxide reforming of methane produces synthesis gas with a low hydrogen to carbon monoxide ratio, which is desirable for many industrial synthesis processes. This reaction also has very important environmental implications since both methane and carbon dioxide contribute to the greenhouse effect. Converting these gases into a valuable feedstock may significantly reduce the atmospheric emissions of CO2 and CH4. In this paper, we present a comprehensive review on the thermodynamics, catalyst selection and activity, reaction mechanism, and kinetics of this important reaction. Recently, research has centered on the development of catalysts and the feasible applications of this reaction in industry. Group VIII metals supported on oxides are found to be effective for this reason. However, carbon deposition causing catalyst deactivation is the major problem inhibiting the industrial application of the CO2/CH4 reaction. Ni-based catalysts impregnated on certain supports show carbon-free operation and thus attract much attention. To develop an effective catalyst for CO2 reforming of CH4 and accelerate the commercial application of the reaction, the following are identified to be the most important areas for future work: (1) selection of metal and support and studying the effect of their interaction on catalyst activity; (2) the effect of different promoter on catalyst activity; (3) the reaction mechanism and kinetics; and (4) pilot reactor performance and scale-up operation.

Pyrolysing poultry litter reduces N2O and CO2 fluxes

Application of poultry litter (PL) to soil can lead to substantial nitrous oxide (N2O) emissions due to the co-application of labile carbon (C) and nitrogen (N). Slow pyrolysis of PL to produce biochar may mitigate N2O emissions from this source, whilst still providing agronomic benefits. In a corn crop on ferrosol with similarly matched available N inputs of ca. 116 kg N/ha, PL-biochar plus urea emitted significantly less N2O (1.5 kg N2O-N/ha) compared to raw PL at 4.9 kg N2O-N/ha. Urea amendment without the PL-biochar emitted 1.2 kg N2O-N/ha, and the PL-biochar alone emitted only 0.35 kg N2O-N/ha. Both PL and PL-biochar resulted in similar corn yields and total N uptake which was significantly greater than for urea alone. Using stable isotope methodology, the majority (~ 80%) of N2O emissions were shown to be from non-urea sources. Amendment with raw PL significantly increased C mineralisation and the quantity of permanganate oxidisable organic C. The low molar H/C (0.49) and O/C (0.16) ratios of the PL-biochar suggest its higher stability in soil than raw PL. The PL-biochar also had higher P and K fertiliser value than raw PL. This study suggests that PL-biochar is a valuable soil amendment with the potential to significantly reduce emissions of soil greenhouse gases compared to the raw product. Contrary to other studies, PL-biochar incorporated to 100 mm did not reduce N2O emissions from surface applied urea, which suggests that further field evaluation of biochar impacts, and methods of application of both biochar and fertiliser, are needed.

Effect of palygorskite clay on pyrolysis of rape straw : an in situ catalysis study

Biomass tar restricts the wide application and development of biomass gasification technology. In the present paper, palygorskite, a natural magnesium-containing clay mineral, was investigated for catalytic pyrolysis of rape straw in situ and compared with the dolomite researched widely. The two types of natural minerals were characterized with XRD and BET. The results showed that combustible gas derived from the pyrolysis increased with an increase in gasification temperature. The Hconversion and Cconversion increased to 44.7% and 31% for the addition of palygorskite and increased to 41.3% and 31.3% for the addition of dolomite at the gasification temperature of 800 °C, compared with 15.1% and 5.6% without addition of the two types of material. It indicated that more biomass was converted into combustible gases implying the decrease in biomass tar under the function of palygorskite or dolomite and palygorskite had a slightly better efficiency than that of dolomite in the experimental conditions.

Carbon dioxide capture and gas separation on B80 fullerene

Exploring advanced materials for efficient capture and separation of CO2 is important for CO2 reduction and fuel purification. In this study, we have carried out first-principles density functional theory calculations to investigate CO2, N2, CH4, and H2 adsorption on the amphoteric regioselective B80 fullerene. Based on our calculations, we find that CO2 molecules form strong interactions with the basic sites of the B80 by Lewis acid–base interactions, while there are only weak bindings between the other three gases (N2, CH4, and H2) and the B80 adsorbent. The study also provides insight into the reaction mechanism of capture and separation of CO2 using the electron deficient B80 fullerene.

Spatial prediction of N2O emissions in pasture : a Bayesian model averaging analysis

Nitrous oxide (N2O) is one of the greenhouse gases that can contribute to global warming. Spatial variability of N2O can lead to large uncertainties in prediction. However, previous studies have often ignored the spatial dependency to quantify the N2O - environmental factors relationships. Few researches have examined the impacts of various spatial correlation structures (e.g. independence, distance-based and neighbourhood based) on spatial prediction of N2O emissions. This study aimed to assess the impact of three spatial correlation structures on spatial predictions and calibrate the spatial prediction using Bayesian model averaging (BMA) based on replicated, irregular point-referenced data. The data were measured in 17 chambers randomly placed across a 271 m(2) field between October 2007 and September 2008 in the southeast of Australia. We used a Bayesian geostatistical model and a Bayesian spatial conditional autoregressive (CAR) model to investigate and accommodate spatial dependency, and to estimate the effects of environmental variables on N2O emissions across the study site. We compared these with a Bayesian regression model with independent errors. The three approaches resulted in different derived maps of spatial prediction of N2O emissions. We found that incorporating spatial dependency in the model not only substantially improved predictions of N2O emission from soil, but also better quantified uncertainties of soil parameters in the study. The hybrid model structure obtained by BMA improved the accuracy of spatial prediction of N2O emissions across this study region.

Energy Transformed : Building Capacity in the Engineering Profession in Australia

Global pressures of burgeoning population growth and consumption are threatening efforts to reduce negative environmental pressures associated with development such as atmospheric, land and water pollution. For example, the world’s population is now growing at over 70 million per year or 1 billion per decade (Brown, 2007), increasing from 3.5 billion in 1970, to 5 billion in 1990, to 7 billion by 2010 (United Nations, 2002). In 1990 only 13 percent of the global population lived in cities, while in 2007 more than half did. More than 60 percent of the global population lives within 100 kilometers of the coastline (World Resources Institute, 2005) and nearly all of the population growth hereon is forecast to happen in developing countries (Postel, 1999). Future levels of stress on the global environment are therefore likely to increase if current trends are used for forecasting, which is particularly challenging as scientists are already observing significant signs of degradation and failure in environmental systems. For example, the Intergovernmental Panel on Climate Change Fourth Assessment Report (IPCC, 2007) provided an nequivocal link between climate change and current human activities, in particular: the burning of fossil fuels; deforestation and land clearing; the use of synthetic greenhouse gases; and decomposition of wastes from landfill. The UK Stern Review concluded that within our lifetime there is between a 77 to 99 percent chance (depending on the climate model used) of the global average temperature rising by more than 2 degrees Celsius (Stern, 2006), with a likely greenhouse gas concentration in the atmosphere of 550 parts per million (ppm) or more by around 2100.

Impulse facility simulation of hypervelocity radiating flows

We describe the X-series impulse facilities at The University of Queensland and show that they can produce useful high speed flows of relevance to the study of high temperature radiating flow flields characteristic of atmospheric entry. Two modes of operation are discussed: (a) the expansion tube mode which is useful for subscale aerodynamic testing of vehicles and (b) the non-reflected shock tube mode which can be used to emulate the nonequilibrium radiating region immediately following the bow shock of a flight vehicle.

Pore accessibility by methane and carbon dioxide in coal as determined by neutron scattering

Contrast-matching ultrasmall-angle neutron scattering (USANS) and small-angle neutron scattering (SANS) techniques were used for the first time to determine both the total pore volume and the fraction of the pore volume that is inaccessible to deuterated methane, CD4, in four bituminous coals in the range of pore sizes between ∼10 Å and ∼5 μm. Two samples originated from the Illinois Basin in the U.S.A., and the other two samples were commercial Australian bituminous coals from the Bowen Basin. The total and inaccessible porosity were determined in each coal using both Porod invariant and the polydisperse spherical particle (PDSP) model analysis of the scattering data acquired from coals both in vacuum and at the pressure of CD4, at which the scattering length density of the pore-saturating fluid is equal to that of the solid coal matrix (zero average contrast pressure). The total porosity of the coals studied ranged from 7 to 13%, and the volume of pores inaccessible to CD4 varied from ∼13 to ∼36% of the total pore volume. The volume fraction of inaccessible pores shows no correlation with the maceral composition; however, it increases with a decreasing total pore volume. In situ measurements of the structure of one coal saturated with CO2 and CD4 were conducted as a function of the pressure in the range of 1−400 bar. The neutron scattering intensity from small pores with radii less than 35 Å in this coal increased sharply immediately after the fluid injection for both gases, which demonstrates strong condensation and densification of the invading subcritical CO2 and supercritical methane in small pores.

Accessibility of pores in coal to methane and carbon dioxide

Fluid–solid interactions in natural and engineered porous solids underlie a variety of technological processes, including geological storage of anthropogenic greenhouse gases, enhanced coal bed methane recovery, membrane separation, and heterogeneous catalysis. The size, distribution and interconnectivity of pores, the chemical and physical properties of the solid and fluid phases collectively dictate how fluid molecules migrate into and through the micro- and meso-porous media, adsorb and ultimately react with the solid surfaces. Due to the high penetration power and relatively short wavelength of neutrons, smallangle neutron scattering (SANS) as well as ultra small-angle scattering (USANS) techniques are ideally suited for assessing the phase behavior of confined fluids under pressure as well as for evaluating the total porosity in engineered and natural porous systems including coal. Here we demonstrate that SANS and USANS can be also used for determining the fraction of the pore volume that is actually accessible to fluids as a function of pore sizes and study the fraction of inaccessible pores as a function of pore size in three coals from the Illinois Basin (USA) and Bowen Basin (Australia). Experiments were performed at CO2 and methane pressures up to 780 bar, including pressures corresponding to zero average contrast condition (ZAC), which is the pressure where no scattering from the accessible pores occurs. Scattering curves at the ZAC were compared with the scattering from same coals under vacuum and analysed using a newly developed approach that shows that the volume fraction of accessible pores in these coals varies between �90% in the macropore region to �30% in the mesopore region and the variation is distinctive for each of the examined coals. The developed methodology may be also applied for assessing the volume of accessible pores in other natural underground formations of interest for CO2 sequestration, such as saline aquifers as well as for estimating closed porosity in engineered porous solids of technological importance.

Stability of the bituminous coal microstructure upon exposure to high pressures of helium

Small-angle neutron scattering (SANS) and ultra-small-angle neutron scattering (USANS) measurements of the structure of two Australian bituminous coals (particle size of 1-0.5 mm) before, during, and after exposure to 155 bar of helium were made to identify any effects of pressure alone on the pore size distribution of coal and any irreversible effects upon exposure to high pressures of helium in the pore size range from 3 nm to 10 μm. No irreversible effects upon exposure were identified for any pore size. No effects of pressure on pore size distribution were observed, except for a small effect at a pore size of about 2 μm for one coal. This study provides a convenient baseline for SANS and USANS investigations on sorption of gases at elevated pressures on coals, by distinguishing between the effect of pressure alone on coal pore size distribution and against the effect of the gas to be investigated.

The past, present and future of carbon labelling for construction materials – a review

Global climate change is one of the most significant environmental issues that can harm human development. One central issue for the building and construction industry to address global climate change is the development of a credible and meaningful way to measure greenhouse gas (GHG) emissions. While Publicly Available Specification (PAS) 2050, the first international GHG standard, has been proven to be successful in standardizing the quantification process, its contribution to the management of carbon labels for construction materials is limited. With the recent publication of ISO 14067: Greenhouse gases – carbon footprint of products – requirements and guidelines for quantification and communication in May 2013, it is necessary for the building and construction industry to understand the past, present and future of the carbon labelling practices for construction materials. A systematic review shows that international GHG standards have been evolving in terms of providing additional guidance on communication and comparison, as well as less flexibility on the use of carbon labels. At the same time, carbon labelling schemes have been evolving on standardization and benchmarking. In addition, future actions are needed in the aspect of raising consumer awareness, providing benchmarking, ensuring standardization and developing simulation technologies in order for carbon labelling schemes for construction materials to provide credible, accurate and transparent information on GHG emissions.

Integrated approach for diagnostics and prognostics of HP LNG pump based on health state probability estimation

Effective machine fault prognostic technologies can lead to elimination of unscheduled downtime and increase machine useful life and consequently lead to reduction of maintenance costs as well as prevention of human casualties in real engineering asset management. This paper presents a technique for accurate assessment of the remnant life of machines based on health state probability estimation technique and historical failure knowledge embedded in the closed loop diagnostic and prognostic system. To estimate a discrete machine degradation state which can represent the complex nature of machine degradation effectively, the proposed prognostic model employed a classification algorithm which can use a number of damage sensitive features compared to conventional time series analysis techniques for accurate long-term prediction. To validate the feasibility of the proposed model, the five different level data of typical four faults from High Pressure Liquefied Natural Gas (HP-LNG) pumps were used for the comparison of intelligent diagnostic test using five different classification algorithms. In addition, two sets of impeller-rub data were analysed and employed to predict the remnant life of pump based on estimation of health state probability using the Support Vector Machine (SVM) classifier. The results obtained were very encouraging and showed that the proposed prognostics system has the potential to be used as an estimation tool for machine remnant life prediction in real life industrial applications.