923 resultados para suspended solids


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The ability to forecast machinery failure is vital to reducing maintenance costs, operation downtime and safety hazards. Recent advances in condition monitoring technologies have given rise to a number of prognostic models for forecasting machinery health based on condition data. Although these models have aided the advancement of the discipline, they have made only a limited contribution to developing an effective machinery health prognostic system. The literature review indicates that there is not yet a prognostic model that directly models and fully utilises suspended condition histories (which are very common in practice since organisations rarely allow their assets to run to failure); that effectively integrates population characteristics into prognostics for longer-range prediction in a probabilistic sense; which deduces the non-linear relationship between measured condition data and actual asset health; and which involves minimal assumptions and requirements. This work presents a novel approach to addressing the above-mentioned challenges. The proposed model consists of a feed-forward neural network, the training targets of which are asset survival probabilities estimated using a variation of the Kaplan-Meier estimator and a degradation-based failure probability density estimator. The adapted Kaplan-Meier estimator is able to model the actual survival status of individual failed units and estimate the survival probability of individual suspended units. The degradation-based failure probability density estimator, on the other hand, extracts population characteristics and computes conditional reliability from available condition histories instead of from reliability data. The estimated survival probability and the relevant condition histories are respectively presented as “training target” and “training input” to the neural network. The trained network is capable of estimating the future survival curve of a unit when a series of condition indices are inputted. Although the concept proposed may be applied to the prognosis of various machine components, rolling element bearings were chosen as the research object because rolling element bearing failure is one of the foremost causes of machinery breakdowns. Computer simulated and industry case study data were used to compare the prognostic performance of the proposed model and four control models, namely: two feed-forward neural networks with the same training function and structure as the proposed model, but neglected suspended histories; a time series prediction recurrent neural network; and a traditional Weibull distribution model. The results support the assertion that the proposed model performs better than the other four models and that it produces adaptive prediction outputs with useful representation of survival probabilities. This work presents a compelling concept for non-parametric data-driven prognosis, and for utilising available asset condition information more fully and accurately. It demonstrates that machinery health can indeed be forecasted. The proposed prognostic technique, together with ongoing advances in sensors and data-fusion techniques, and increasingly comprehensive databases of asset condition data, holds the promise for increased asset availability, maintenance cost effectiveness, operational safety and – ultimately – organisation competitiveness.

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Reliability analysis has several important engineering applications. Designers and operators of equipment are often interested in the probability of the equipment operating successfully to a given age - this probability is known as the equipment's reliability at that age. Reliability information is also important to those charged with maintaining an item of equipment, as it enables them to model and evaluate alternative maintenance policies for the equipment. In each case, information on failures and survivals of a typical sample of items is used to estimate the required probabilities as a function of the item's age, this process being one of many applications of the statistical techniques known as distribution fitting. In most engineering applications, the estimation procedure must deal with samples containing survivors (suspensions or censorings); this thesis focuses on several graphical estimation methods that are widely used for analysing such samples. Although these methods have been current for many years, they share a common shortcoming: none of them is continuously sensitive to changes in the ages of the suspensions, and we show that the resulting reliability estimates are therefore more pessimistic than necessary. We use a simple example to show that the existing graphical methods take no account of any service recorded by suspensions beyond their respective previous failures, and that this behaviour is inconsistent with one's intuitive expectations. In the course of this thesis, we demonstrate that the existing methods are only justified under restricted conditions. We present several improved methods and demonstrate that each of them overcomes the problem described above, while reducing to one of the existing methods where this is justified. Each of the improved methods thus provides a realistic set of reliability estimates for general (unrestricted) censored samples. Several related variations on these improved methods are also presented and justified. - i

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This paper is concerned with some plane strain and axially symmetric free surface problems which arise in the study of static granular solids that satisfy the Coulomb-Mohr yield condition. Such problems are inherently nonlinear, and hence difficult to attack analytically. Given a Coulomb friction condition holds on a solid boundary, it is shown that the angle a free surface is allowed to attach to the boundary is dependent only on the angle of wall friction, assuming the stresses are all continuous at the attachment point, and assuming also that the coefficient of cohesion is nonzero. As a model problem, the formation of stable cohesive arches in hoppers is considered. This undesirable phenomena is an obstacle to flow, and occurs when the hopper outlet is too small. Typically, engineers are concerned with predicting the critical outlet size for a given hopper and granular solid, so that for hoppers with outlets larger than this critical value, arching cannot occur. This is a topic of considerable practical interest, with most accepted engineering methods being conservative in nature. Here, the governing equations in two limiting cases (small cohesion and high angle of internal friction) are considered directly. No information on the critical outlet size is found; however solutions for the shape of the free boundary (the arch) are presented, for both plane and axially symmetric geometries.

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The flood flow in urbanised areas constitutes a major hazard to the population and infrastructure as seen during the summer 2010-2011 floods in Queensland (Australia). Flood flows in urban environments have been studied relatively recently, although no study considered the impact of turbulence in the flow. During the 12-13 January 2011 flood of the Brisbane River, some turbulence measurements were conducted in an inundated urban environment in Gardens Point Road next to Brisbane's central business district (CBD) at relatively high frequency (50 Hz). The properties of the sediment flood deposits were characterised and the acoustic Doppler velocimeter unit was calibrated to obtain both instantaneous velocity components and suspended sediment concentration in the same sampling volume with the same temporal resolution. While the flow motion in Gardens Point Road was subcritical, the water elevations and velocities fluctuated with a distinctive period between 50 and 80 s. The low frequency fluctuations were linked with some local topographic effects: i.e, some local choke induced by an upstream constriction between stairwells caused some slow oscillations with a period close to the natural sloshing period of the car park. The instantaneous velocity data were analysed using a triple decomposition, and the same triple decomposition was applied to the water depth, velocity flux, suspended sediment concentration and suspended sediment flux data. The velocity fluctuation data showed a large energy component in the slow fluctuation range. For the first two tests at z = 0.35 m, the turbulence data suggested some isotropy. At z = 0.083 m, on the other hand, the findings indicated some flow anisotropy. The suspended sediment concentration (SSC) data presented a general trend with increasing SSC for decreasing water depth. During a test (T4), some long -period oscillations were observed with a period about 18 minutes. The cause of these oscillations remains unknown to the authors. The last test (T5) took place in very shallow waters and high suspended sediment concentrations. It is suggested that the flow in the car park was disconnected from the main channel. Overall the flow conditions at the sampling sites corresponded to a specific momentum between 0.2 to 0.4 m2 which would be near the upper end of the scale for safe evacuation of individuals in flooded areas. But the authors do not believe the evacuation of individuals in Gardens Point Road would have been safe because of the intense water surges and flow turbulence. More generally any criterion for safe evacuation solely based upon the flow velocity, water depth or specific momentum cannot account for the hazards caused by the flow turbulence, water depth fluctuations and water surges.

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Atmospheric concentration of total suspended particulate matter (TSP) and associated heavy metals are a great concern due to their adverse health impacts and contribution to stormwater pollution. This paper discusses the outcomes of a study which investigated the variation of atmospheric TSP and heavy metal concentrations with traffic and land use characteristics during weekdays and weekends. Data for this study was gathered from fifteen sites at the Gold Coast, Australia using a high volume air sampler. The study detected consistently high TSP concentrations during weekdays compared to weekends. This confirms the significant influence of traffic related sources on TSP loads during weekdays. Both traffic and land use related sources equally contribute to TSP during weekends. Almost all the measured heavy metals showed high concentration on weekdays compared to weekends indicating significant contributions from traffic related emissions. Among the heavy metals, Zn concentration was the highest followed by Pb. It is postulated that re-suspension of previously deposited reserves was the main Pb source. Soil related sources were the main contributors of Mn.

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Partition of heavy metals between particulate and dissolve fraction of stormwater primarily depends on the adsorption characteristics of solids particles. Moreover, the bioavailability of heavy metals is also influenced by the adsorption behaviour of solids. However, due to the lack of fundamental knowledge in relation to the heavy metals adsorption processes of road deposited solids, the effectiveness of stormwater management strategies can be limited. The research study focused on the investigation of the physical and chemical parameters of solids on urban road surfaces and, more specifically, on heavy metal adsorption to solids. Due to the complex nature of heavy metal interaction with solids, a substantial database was generated through a series of field investigations and laboratory experiments. The study sites for the build-up pollutant sample collection were selected from four urbanised suburbs located in a major river catchment. Sixteen road sites were selected from these suburbs and represented typical industrial, commercial and residential land uses. Build-up pollutants were collected using a wet and dry vacuum collection technique which was specially designed to improve fine particle collection. Roadside soil samples were also collected from each suburb for comparison with the road surface solids. The collected build-up solids samples were separated into four particle size ranges and tested for a range of physical and chemical parameters. The solids build-up on road surfaces contained a high fraction (70%) of particles smaller than 150ìm, which are favourable for heavy metal adsorption. These solids particles predominantly consist of soil derived minerals which included quartz, albite, microcline, muscovite and chlorite. Additionally, a high percentage of amorphous content was also identified in road deposited solids. In comparing the mineralogical data of surrounding soil and road deposited solids, it was found that about 30% of the solids consisted of particles generated from traffic related activities on road surfaces. Significant difference in mineralogical composition was noted in different particle sizes of build-up solids. Fine solids particles (<150ìm) consisted of a clayey matrix and high amorphous content (in the region of 40%) while coarse particles (>150ìm) consisted of a sandy matrix at all study sites, with about 60% quartz content. Due to these differences in mineralogical components, particles larger than and smaller than 150ìm had significant differences in their specific surface area (SSA) and effective cation exchange capacity (ECEC). These parameters, in turn, exert a significant influence on heavy metal adsorption. Consequently, heavy metal content in >150ìm particles was lower than in the case of fine particles. The particle size range <75ìm had the highest heavy metal content, corresponding with its high clay forming minerals, high organic matter and low quartz content which increased the SSA, ECEC and the presence of Fe, Al and Mn oxides. The clay forming minerals, high organic matter and Fe, Al and Mn oxides create distinct groups of charge sites on solids surfaces and exhibit different adsorption mechanisms and bond strength, between heavy metal elements and charge sites. Therefore, the predominance of these factors in different particle sizes leads to different heavy metal adsorption characteristics. Heavy metals show preference for association with clay forming minerals in fine solids particles, whilst in coarse particles heavy metals preferentially associate with organic matter. Although heavy metal adsorption to amorphous material is very low, the heavy metals embedded in traffic related materials have a potential impact on stormwater quality.Adsorption of heavy metals is not confined to an individual type of charge site in solids, whereas specific heavy metal elements show preference for adsorption to several different types of charge sites in solids. This is attributed to the dearth of preferred binding sites and the inability to reach the preferred binding sites due to competition between different heavy metal species. This confirms that heavy metal adsorption is significantly influenced by the physical and chemical parameters of solids that lead to a heterogeneity of surface charge sites. The research study highlighted the importance of removal of solids particles from stormwater runoff before they enter into receiving waters to reduce the potential risk posed by the bioavailability of heavy metals. The bioavailability of heavy metals not only results from the easily mobile fraction bound to the solids particles, but can also occur as a result of the dissolution of other forms of bonds by chemical changes in stormwater or microbial activity. Due to the diversity in the composition of the different particle sizes of solids and the characteristics and amount of charge sites on the particle surfaces, investigations using bulk solids are not adequate to gain an understanding of the heavy metal adsorption processes of solids particles. Therefore, the investigation of different particle size ranges is recommended for enhancing stormwater quality management practices.

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For the analysis of material nonlinearity, an effective shear modulus approach based on the strain control method is proposed in this paper by using point collocation method. Hencky’s total deformation theory is used to evaluate the effective shear modulus, Young’s modulus and Poisson’s ratio, which are treated as spatial field variables. These effective properties are obtained by the strain controlled projection method in an iterative manner. To evaluate the second order derivatives of shape function at the field point, the radial basis function (RBF) in the local support domain is used. Several numerical examples are presented to demonstrate the efficiency and accuracy of the proposed method and comparisons have been made with analytical solutions and the finite element method (ABAQUS).

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The photocatalytic disinfection of Enterobacter cloacae and Enterobacter coli using microwave (MW), convection hydrothermal (HT) and Degussa P25 titania was investigated in suspension and immobilized reactors. In suspension reactors, MW-treated TiO(2) was the most efficient catalyst (per unit weight of catalyst) for the disinfection of E. cloacae. However, HT-treated TiO(2) was approximately 10 times more efficient than MW or P25 titania for the disinfection of E. coli suspensions in surface water using the immobilized reactor. In immobilized experiments, using surface water a significant amount of photolysis was observed using the MW- and HT-treated films; however, disinfection on P25 films was primarily attributed to photocatalysis. Competitive action of inorganic ions and humic substances for hydroxyl radicals during photocatalytic experiments, as well as humic substances physically screening the cells from UV and hydroxyl radical attack resulted in low rates of disinfection. A decrease in colony size (from 1.5 to 0.3 mm) was noted during photocatalytic experiments. The smaller than average colonies were thought to occur during sublethal (•) OH and O(2) (•-) attack. Catalyst fouling was observed following experiments in surface water and the ability to regenerate the surface was demonstrated using photocatalytic degradation of oxalic acid as a model test system

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Solids are widely identified as a carrier of harmful pollutants in stormwater runoff exerting a significant risk to receiving waters. This paper outlines the findings of an in-depth investigation on heavy metal adsorption to solids surfaces. Pollutant build-up samples collected from sixteen road sites in residential, industrial and commercial land uses were separated into four particle size ranges and analysed for a range of physico-chemical parameters and nine heavy metals including Iron (Fe), Aluminum (Al), Lead (Pb), Zinc (Zn), Cadmium (Cd), Chromium (Cr), Manganese (Mn), Nickel (Ni) and Copper (Cu). High specific surface area (SSA) and total organic carbon (TOC) content in finer particle size ranges was noted, thus confirming strong correlations with heavy metals. Based on their physico-chemical characteristics, two different types of solids originating from traffic and soil sources were identified. Solids generated by traffic were associated with high loads of heavy metals such as Cd and Cr with strong correlation with SSA. This suggested the existence of surface dependent bonds such as cation exchange between heavy metals and solids. In contrast, Fe, Al and Mn which can be attributed to soil inputs showed strong correlation with TOC suggesting strong bonds such as chemsorption. Zn was found to be primarily attached to solids by bonding with the oxides of Fe, Al and Mn. The data analysis also confirmed the predominance of the finer fraction, with 70% of the solids being finer than 150 µm and containing 60% of the heavy metal pollutant load.

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In urbanised areas, the flood flows constitute a hazard to populations and infrastructure as illustrated during major floods in 2011. During the 2011 Brisbane River flood, some turbulent velocity data were collected using acoustic Doppler velocimetry in an inundated street. The field deployment showed some unusual features of flood flow in the urban environment. That is, the water elevations and velocities fluctuated with distinctive periods between 50 and 100 s linked with some local topographic effects. The instantaneous velocity data were analysed using a triple decomposition. The velocity fluctuations included a large energy component in the slow fluctuation range, while the turbulent motion components were much smaller. The suspended sediment data showed some significant longitudinal flux. Altogether the results highlighted that the triple decomposition approach originally developed for period flows is well suited to complicated flows in an inundated urban environment.

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Rapid urbanisation and resulting continuous increase in traffic has been recognised as key factors in the contribution of increased pollutant loads to urban stormwater and in turn to receiving waters. Urbanisation primarily increases anthropogenic activities and the percentage of impervious surfaces in urban areas. These processes are collectively responsible for urban stormwater pollution. In this regard, urban traffic and land use related activities have been recognised as the primary pollutant sources. This is primarily due to the generation of a range of key pollutants such as solids, heavy metals and PAHs. Appropriate treatment system design is the most viable approach to mitigate stormwater pollution. However, limited understanding of the pollutant process and transport pathways constrains effective treatment design. This highlights necessity for the detailed understanding of traffic and other land use related pollutants processes and pathways in relation to urban stormwater pollution. This study has created new knowledge in relation to pollutant processes and transport pathways encompassing atmospheric pollutants, atmospheric deposition and build-up on ground surfaces of traffic generated key pollutants. The research study was primarily based on in-depth experimental investigations. This thesis describes the extensive knowledge created relating to the processes of atmospheric pollutant build-up, atmospheric deposition and road surface build-up and establishing their relationships as a chain of processes. The analysis of atmospheric deposition revealed that both traffic and land use related sources contribute total suspended particulate matter (TSP) to the atmosphere. Traffic sources become dominant during weekdays whereas land use related sources become dominant during weekends due to the reduction in traffic sources. The analysis further concluded that atmospheric TSP, polycyclic aromatic hydrocarbons (PAHs) and heavy metals (HMs) concentrations are highly influenced by total average daily heavy duty traffic, traffic congestion and the fraction of commercial and industrial land uses. A set of mathematical equation were developed to predict TSP, PAHs and HMs concentrations in the atmosphere based on the influential traffic and land use related parameters. Dry deposition samples were collected for different antecedent dry days and wet deposition samples were collected immediately after rainfall events. The dry deposition was found to increase with the antecedent dry days and consisted of relatively coarser particles (greater than 1.4 ìm) when compared to wet deposition. The wet deposition showed a strong affinity to rainfall depth, but was not related to the antecedent dry period. It was also found that smaller size particles (less than 1.4 ìm) travel much longer distances from the source and deposit mainly with the wet deposition. Pollutants in wet deposition are less sensitive to the source characteristics compared to dry deposition. Atmospheric deposition of HMs is not directly influenced by land use but rather by proximity to high emission sources such as highways. Therefore, it is important to consider atmospheric deposition as a key pollutant source to urban stormwater in the vicinity of these types of sources. Build-up was analysed for five different particle size fractions, namely, <1 ìm, 1-75 ìm, 75-150 ìm, 150-300 ìm and >300 ìm for solids, PAHs and HMs. The outcomes of the study indicated that PAHs and HMs in the <75 ìm size fraction are generated mainly by traffic related activities whereas the > 150 ìm size fraction is generated by both traffic and land use related sources. Atmospheric deposition is an important source for HMs build-up on roads, whereas the contribution of PAHs from atmospheric sources is limited. A comprehensive approach was developed to predict traffic and other land use related pollutants in urban stormwater based on traffic and other land use characteristics. This approach primarily included the development of a set of mathematical equations to predict traffic generated pollutants by linking traffic and land use characteristics to stormwater quality through mathematical modelling. The outcomes of this research will contribute to the design of appropriate treatment systems to safeguard urban receiving water quality for future traffic growth scenarios. The „real world. application of knowledge generated was demonstrated through mathematical modelling of solids in urban stormwater, accounting for the variability in traffic and land use characteristics.