PCB desorption kinetics under realistic shear and turbulence [progress report]

We hypothesize that the impact of PCB desorption from resuspended sediments depends upon the intensity of the resuspension (which scales to bottom stress in the absence of organisms), the rate at which each congener desorbs (which depends on the size and hydrophobicity of the chemical, the relative amount of 'labile' and 'resistant' forms, and the size distribution of the suspended particles), and the residence time of the particles in the water column (which depends on the time-variable water column turbulence regime and the particle settling velocities). In order to accurately quantify the impact of PCB desorption from Hudson River sediments, we are conducting experiments that realistically mimic bottom shear stress and water column turbulence and rapidly measure PCB congener release. The objectives of this study are to measure the kinetics of PCB congener desorption from Hudson River sediments under realistic bottom shear and water column turbulence conditions and to quantify the impact of shear stress and contaminant aging on PCB desorption kinetics.

Investigation on the ecological impact of constructing and activities of petrochemical industries of petrochemical special economic zone of Mahshahr on the abundance and diversity of macrobenthic fauna in Jafari Creek, north-west of the Persian Gulf

The impact of Petrochemical Special Economic Zone (PETZONE) activities on the health status of Jafari Creek was studied by assessing the changes in macroinvertebrate assemblages in nine sites during September 2006- January 2008. Furthermore to evaluate the ecological status of the Jafari Creek the WFD indices (i.e. AMBI, M-AMBI) were used. The relationship between spatial pattern of macro invertebrate assemblages and ambient factors (i.e. water temperature, salinity, pH, dissolved oxygen, turbidity, electrical conductivity, total dissolved solid, total hardness, total nitrogen, ammonia, total phosphorous, chemical oxygen demand, biological oxygen demand, sediment grain size distribution, sediment organic content, heavy metals contents) was measured. Background Enrichment indices, Contamination factor and Contamination degree, were used to assess the health status in the study area based on Nickel, Lead, Cadmium and Mercury contents of the sediments. The macrobenthic communities had a low diversity and were dominated by opportunistic taxa, and the AMBI and M-AMBI indices need to be calibrated before using in Persian Gulf and its coastal waters. The BIO-ENV analysis identified pH, dissolved oxygen, TDS, and the total organic content of sediments as the major environmental variables influencing the infaunal pattern. This suggests that management should attempt to ensure minimal disturbance to environmental variables underlying the spatial variation in macroinvertebrate assemblages. Background Enrichment indices showed that the health of Jafari Creek has declined over time due to the constant discharge of heavy metals to the Creek system. Furthermore WQS index shows that the quality condition of the water column in Jafari Creek, regard to the calculated number (3) is week. These indices also identified a significant degree of pollution in the study area. The decrease in the ecological potential of Jafari Creek was best highlighted by the alteration in macrobenthic assemblages.

An investigation of the kinetics of CO2 uptake by a synthetic calcium based sorbent

This study examines the kinetics of carbonation by CO2 at temperatures of ca. 750 °C of a synthetic sorbent composed of 15 wt% mayenite (Ca12Al14O33) and CaO, designated HA-85-850, and draws comparisons with the carbonation of a calcined limestone. In-situ XRD has verified the inertness of mayenite, which neither interacts with the active CaO nor does it significantly alter the CaO carbonation–calcination equilibrium. An overlapping grain model was developed to predict the rate and extent of carbonation of HA-85-850 and limestone. In the model, the initial microstructure of the sorbent was defined by a discretised grain size distribution, assuming spherical grains. The initial input to the model – the size distribution of grains – was a fitted parameter, which was in good agreement with measurements made with mercury porosimetry and by the analysis of SEM images of sectioned particles. It was found that the randomly overlapping spherical grain assumption offered great simplicity to the model, despite its approximation to the actual porous structure within a particle. The model was able to predict the performance of the materials well and, particularly, was able to account for changes in rate and extent of reaction as the structure evolved after various numbers of cycles of calcination and carbonation.

An investigation of the kinetics of CO 2 uptake by a synthetic calcium based sorbent

This study examines the kinetics of carbonation by CO 2 at temperatures of ca. 750°C of a synthetic sorbent composed of 15wt% mayenite (Ca 12Al 14O 33) and CaO, designated HA-85-850, and draws comparisons with the carbonation of a calcined limestone. In-situ XRD has verified the inertness of mayenite, which neither interacts with the active CaO nor does it significantly alter the CaO carbonation-calcination equilibrium. An overlapping grain model was developed to predict the rate and extent of carbonation of HA-85-850 and limestone. In the model, the initial microstructure of the sorbent was defined by a discretised grain size distribution, assuming spherical grains. The initial input to the model - the size distribution of grains - was a fitted parameter, which was in good agreement with measurements made with mercury porosimetry and by the analysis of SEM images of sectioned particles. It was found that the randomly overlapping spherical grain assumption offered great simplicity to the model, despite its approximation to the actual porous structure within a particle. The model was able to predict the performance of the materials well and, particularly, was able to account for changes in rate and extent of reaction as the structure evolved after various numbers of cycles of calcination and carbonation. © 2011 Elsevier Ltd.

Identification of Materials from Construction Site Images Using Content Based Image Retrieval Techniques

The capability to automatically identify shapes, objects and materials from the image content through direct and indirect methodologies has enabled the development of several civil engineering related applications that assist in the design, construction and maintenance of construction projects. Examples include surface cracks detection, assessment of fire-damaged mortar, fatigue evaluation of asphalt mixes, aggregate shape measurements, velocimentry, vehicles detection, pore size distribution in geotextiles, damage detection and others. This capability is a product of the technological breakthroughs in the area of Image and Video Processing that has allowed for the development of a large number of digital imaging applications in all industries ranging from the well established medical diagnostic tools (magnetic resonance imaging, spectroscopy and nuclear medical imaging) to image searching mechanisms (image matching, content based image retrieval). Content based image retrieval techniques can also assist in the automated recognition of materials in construction site images and thus enable the development of reliable methods for image classification and retrieval. The amount of original imaging information produced yearly in the construction industry during the last decade has experienced a tremendous growth. Digital cameras and image databases are gradually replacing traditional photography while owners demand complete site photograph logs and engineers store thousands of images for each project to use in a number of construction management tasks. However, construction companies tend to store images without following any standardized indexing protocols, thus making the manual searching and retrieval a tedious and time-consuming effort. Alternatively, material and object identification techniques can be used for the development of automated, content based, construction site image retrieval methodology. These methods can utilize automatic material or object based indexing to remove the user from the time-consuming and tedious manual classification process. In this paper, a novel material identification methodology is presented. This method utilizes content based image retrieval concepts to match known material samples with material clusters within the image content. The results demonstrate the suitability of this methodology for construction site image retrieval purposes and reveal the capability of existing image processing technologies to accurately identify a wealth of materials from construction site images.

UV durable colour pigment doped SmA liquid crystal composites for outdoor trans-reflective bi-stable displays

High brightness trans-reflective bi-stable displays based on smectic A (SmA) liquid crystals (LCs) can have nearly perfect transparency in the clear state and very high reflection in the scattered state. Because the LC material in use is stable under UV radiation, this kind of displays can stand for strong day-light and therefore be ideal for outdoor applications from e-books to public signage and advertisement. However, the colour application has been limited because the traditional colourants in use are conventional dyes which are lack of UV stability and that their colours are easily photo bleached. Here we present a colour SmA display demonstrator using pigments as colourant. Mixing pigments with SmA LCs and maintain the desirable optical switching performance is not straightforward. We show here how it can be done, including how to obtain fine sized pigment nano-particles, the effects of particle size and size distribution on the display performance. Our optimized pigments/SmA compositions can be driven by a low frequency waveform (∼101Hz) to a scattered state to exhibit colour while by a high frequency waveform (∼103Hz) to a cleared state showing no colour. Finally, we will present its excellent UV life-time (at least >7.2 years) in comparison with that of dye composition (∼2.4 years). The complex interaction of pigment nano-particles with LC molecules and the resulting effects on the LC electro-optical performances are still to be fully understood. We hope this work will not only demonstrate a new and practical approach for outdoor reflective colour displays but also provide a new material system for fundamental liquid crystal colloid research work. © 2012 SPIE.

Investigation of DyBa2Cu3O7-d superconducting domains grown by the infiltration technique starting with small size Dy-211 particles

An infiltration and growth process is here used as an alternative to the classical top-seeded melt-textured growth process for the production of Dy-123 single-domains with finely dispersed small size Dy-211 particles. The starting materials are the 211-particles and a barium and copper rich liquid phase precursor. The infiltration and growth process allows for controlling both the spatial and size distribution of the 211-particles in the final superconducting 123-single-domain. The main parameters (set-ups, maximum processing temperature with respect to the peritectic temperature, nature of reactant, porosity of the 211-preform) of the infiltration and growth process are discussed. Moreover, different processes of chimie douce are shown in order to produce Dy-211 particles with controlled shape and size, particles that can be used as precursors for the infiltration and growth process. © 2005 IOP Publishing Ltd.

Complex chemistry DNS of n-heptane spray autoignition at high pressure and intermediate temperature conditions

Direct Numerical Simulations (DNS) of turbulent n-heptane sprays autoigniting at high pressure (P=24bar) and intermediate air temperature (Tair=1000K) have been performed to investigate the physical mechanisms present under conditions where low-temperature chemistry is expected to be important. The initial turbulence in the carrier gas, the global equivalence ratio in the spray region, and the initial droplet size distribution of the spray were varied. Results show that spray ignition exhibits a spotty nature, with several kernels developing independently in those regions where the mixture fraction is close to its most reactive value ξMR (as determined from homogeneous reactor calculations) and the scalar dissipation rate is low. Turbulence reduces the ignition delay time as it promotes mixing between air and the fuel vapor, eventually resulting in lower values of scalar dissipation. High values of the global equivalence ratio are responsible for a larger number of ignition kernels, due to the higher probability of finding regions where ξ=ξMR. Spray polydispersity results in the occurrence of ignition over a wider range of mixture fraction values. This is a consequence of the inhomogeneities in the mixing field that characterize these sprays, where poorly mixed rich spots are seen to alternate with leaner ones which are well-mixed. The DNS simulations presented in this work have also been used to assess the applicability of the Conditional Moment Closure (CMC) method to the simulation of spray combustion. CMC is found to be a valid method for capturing spray autoignition, although care should be taken in the modelling of the unclosed terms appearing in the CMC equations. © 2013 The Combustion Institute.

Flow field measurements of pulverized coal combustion using optical diagnostic techniques

This paper demonstrates the application of laser Doppler velocimetry (LDV) and particle image velocimetry (PIV) techniques to a particle-laden reacting flow of pulverized coal. A laboratory-scale open-type annular burner is utilized to generate velocity profiles of coal particles and micrometric alumina particles. Pair-wise two-component LDV measurements and high-speed stereo PIV measurements provide three-dimensional velocity components of the flow field. A detailed comparison of velocities for alumina and coal particle seeding revealed differences attributed to the wide size distribution of coal particles. In addition, the non-spherical shape and high flame luminosity associated with coal particle combustion introduces noise to the Mie scatter images. The comparison of mean and RMS velocities measured by LDV and PIV techniques showed that PIV measurements are affected by the wide size distribution of coal particles, whereas LDV measurements become biased toward the velocity of small particles, as signals from large particles are rejected. This small-particle bias is also reflected in the spectral characteristics for both techniques, which are in good agreement within the range of frequencies accessible. PIV measurements showed an expected lack of response of large coal particles to the turbulence fluctuations. The overall good agreement between LDV and PIV measurements demonstrates the applicability of the high-speed PIV technique to a particle-laden, high luminosity coal flame while highlighting some of its limitations. © 2013 Springer-Verlag Berlin Heidelberg.

Preliminary model development for predicting strength and stiffness of cement-stabilized soils using artificial neural networks

This paper presents ongoing work on data collection and collation from a large number of laboratory cement-stabilization projects worldwide. The aim is to employ Artificial Neural Networks (ANN) to establish relationships between variables, which define the properties of cement-stabilized soils, and the two parameters determined by the Unconfined Compression Test, the Unconfined Compressive Strength (UCS), and stiffness, using E50 calculated from UCS results. Bayesian predictive neural network models are developed to predict the UCS values of cement-stabilized inorganic clays/silts, as well as sands as a function of selected soil mix variables, such as grain size distribution, water content, cement content and curing time. A model which can predict the stiffness values of cement-stabilized clays/silts is also developed and compared to the UCS model. The UCS model results emulate known trends better and provide more accurate estimates than the results from the E50 stiffness model. © 2013 American Society of Civil Engineers.

Development of predictive models for cement stabilized soils

Factors that affect the engineering properties of cement stabilized soils such as strength are discussed in this paper using data on these factors. The selected factors studied in this paper are initial soil water content, grain size distribution, organic matter content, binder dosage, age and curing temperature, which has been collated from a number of international deep mixing projects. Some resulting correlations from this data are discussed and presented. The concept of Artificial Neural Networks and its applicability in developing predictive models for deep mixed soils is presented and discussed using a subset of the collated data. The results from the neural network model were found to emulate the known trends and reasonable estimates of strength as a function of the selected variables were obtained. © 2012 American Society of Civil Engineers.

HYDROGRAPHIC VARIATIONS IN SIZE STRUCTURE OF PLANKTON BIOMASS IN A CHANGJIANG FLOODPLAIN LAKE

The size structure of the planktonic community in a Changjiang floodplain lake (Lake Chenhu, Hubei, P. R. China) was described for the inundation period of May through September 1983. The modality of the Sheldon-type size distributions changed hydrographically with the spectral profiles being bimodal during low, rising, mid-high and falling water phases, and trimodal soon after filling and shortly before falling. The modal peaks corresponded respectively to the dominant organisms of chlorophytes and nauplii, while the troughs centered on the bacteria and macrocrustacean size classes in the lake. The slope of the normalized biomass spectrum (an index of plankton size distribution) was less than -1.0 for the filling and falling phases or close to -1.0 for the high water period, indicating that the planktonic biomass tended to decrease or evenly distributes across logarithmically ordered size classes, respectively. This observed variation in the size distribution of the plankton community mainly resulted from changes in water levels and contents of particulate inorganic matter (PIM) in the lake.

Size distributions of quantum islands on stepped substrates

The size distributions of self-assembled quantum islands on stepped substrates are studied using kinetic Monte Carlo simulations. It is found that the energy barrier E-SW between the step and the terrace region is the key factor in affecting the size distribution of islands. With small E-SW (<= 0.1 eV), lines of uniform islands can be obtained at relative low surface coverage. As the surface coverage is increased, wirelike islands can be obtained. Scaling behavior is obeyed for the size distributions of the wirelike islands. When the size distributions are separated into their width and length components, however, scaling is only observed in the length distribution of the wirelike islands. With larger E-SW, the size distribution of islands shows a clear bimodal size distribution and anomalous growth temperature dependent island size evolutions are observed. The simulation results reproduce qualitatively the phenomena observed in the cases of InAs islands grown on stepped GaAs substrates. (c) 2009 American Institute of Physics. [doi:10.1063/1.3248367]

Ordered InAs quantum dots with controllable periods grown on stripe-patterned GaAs substrates

GaAs (001) substrates are patterned by electron beam lithography and wet chemical etching to control the nucleation of InAs quantum dots (QDs). InAs dots are grown on the stripe-patterned substrates by solid source molecular beam epitaxy, A thick buffer layer is deposited on the strip pattern before the deposition of InAs. To enhance the surface diffusion length of the In atoms, InAs is deposited with low growth rate and low As pressure. The AFM images show that distinct one-dimensionally ordered InAs QDs with homogeneous size distribution are created, and the QDs preferentially nucleate along the trench. With the increasing amount of deposited InAs and the spacing of the trenches, a number of QDs are formed beside the trenches. The distribution of additional QDs is long-range ordered, always along the trenchs rather than across the spacing regions.

Temperature-dependent bimodal size evolution of InAs quantum dots on vicinal GaAs(100) substrates

The effects of growth temperature on the bimodal size distribution of InAs quantum dots on vicinal GaAs(100) substrates grown by metal organic chemical vapor deposition are studied. An abnormal trend of the bimodal size evolution on temperature is observed. With the increase of the growth temperature, while the density of the large dots decreases continually, that of the small dots first grows larger when temperature was below 520 degrees C, and then exhibits a sudden decrease at 535 degrees C. The trend is explained by taking into account the presence of multiatomic steps on the substrates. Photoluminescence (PL) studies show that quantum dots on vicinal substrates have a narrower PL linewidth, a longer emission wavelength, and a larger PL intensity than those of the dots with exact substrates. (c) 2006 American Institute of Physics.