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ABSTRACT Enzyme-Induced Carbonate Precipitation (EICP) using a plant-derived form of the urease enzyme to induce the precipitation of calcium carbonate (CaCO3) shows promise as a method of stabilizing soil for the mitigation of fugitive dust. Fugitive dust is a significant problem in Arizona, particularly in Maricopa County. Maricopa County is

ABSTRACT Enzyme-Induced Carbonate Precipitation (EICP) using a plant-derived form of the urease enzyme to induce the precipitation of calcium carbonate (CaCO3) shows promise as a method of stabilizing soil for the mitigation of fugitive dust. Fugitive dust is a significant problem in Arizona, particularly in Maricopa County. Maricopa County is an EPA air quality non-attainment zone, due primarily to fugitive dust, which presents a significant health risk to local residents. Conventional methods for fugitive dust control, including the application of water, are either ineffective in arid climates, very expensive, or limited to short term stabilization. Due to these limitations, engineers are searching for new and more effective ways to stabilize the soil and reduce wind erosion. EICP employs urea hydrolysis, a process in which carbonate precipitation is catalyzed by the urease enzyme, a widely occurring protein found in many plants and microorganisms. Wind tunnel experiments were conducted in the ASU/NASA Planetary Wind Tunnel to evaluate the use of EICP as a means to stabilize soil against fugitive dust emission. Three different soils were tested, including a native Arizona silty-sand, a uniform fine to medium grained silica sand, and mine tailings from a mine in southern Arizona. The test soil was loosely placed in specimen container and the surface was sprayed with an aqueous solution containing urea, calcium chloride, and urease enzyme. After a short period of time to allow for CaCO3 precipitation, the specimens were tested in the wind tunnel. The completed tests show that EICP can increase the detachment velocity compared to bare or wetted soil and thus holds promise as a means of mitigating fugitive dust emissions.
ContributorsKnorr, Brian (Author) / Kavazanjian, Edward (Thesis advisor) / Houston, Sandra (Committee member) / Zapata, Claudia (Committee member) / Arizona State University (Publisher)
Created2014
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This dissertation describes development of a procedure for obtaining high quality, optical grade sand coupons from frozen sand specimens of Ottawa 20/30 sand for image processing and analysis to quantify soil structure along with a methodology for quantifying the microstructure from the images. A technique for thawing and stabilizing

This dissertation describes development of a procedure for obtaining high quality, optical grade sand coupons from frozen sand specimens of Ottawa 20/30 sand for image processing and analysis to quantify soil structure along with a methodology for quantifying the microstructure from the images. A technique for thawing and stabilizing frozen core samples was developed using optical grade Buehler® Epo-Tek® epoxy resin, a modified triaxial cell, a vacuum/reservoir chamber, a desiccator, and a moisture gauge. The uniform epoxy resin impregnation required proper drying of the soil specimen, application of appropriate confining pressure and vacuum levels, and epoxy mixing, de-airing and curing. The resulting stabilized sand specimen was sectioned into 10 mm thick coupons that were planed, ground, and polished with progressively finer diamond abrasive grit levels using the modified Allied HTP Inc. polishing method so that the soil structure could be accurately quantified using images obtained with the use of an optical microscopy technique. Illumination via Bright Field Microscopy was used to capture the images for subsequent image processing and sand microstructure analysis. The quality of resulting images and the validity of the subsequent image morphology analysis hinged largely on employment of a polishing and grinding technique that resulted in a flat, scratch free, reflective coupon surface characterized by minimal microstructure relief and good contrast between the sand particles and the surrounding epoxy resin. Subsequent image processing involved conversion of the color images first to gray scale images and then to binary images with the use of contrast and image adjustments, removal of noise and image artifacts, image filtering, and image segmentation. Mathematical morphology algorithms were used on the resulting binary images to further enhance image quality. The binary images were then used to calculate soil structure parameters that included particle roundness and sphericity, particle orientation variability represented by rose diagrams, statistics on the local void ratio variability as a function of the sample size, and the local void ratio distribution histograms using Oda's method and Voronoi tessellation method, including the skewness, kurtosis, and entropy of a gamma cumulative probability distribution fit to the local void ratio distribution.
ContributorsCzupak, Zbigniew David (Author) / Kavazanjian, Edward (Thesis advisor) / Zapata, Claudia (Committee member) / Houston, Sandra (Committee member) / Arizona State University (Publisher)
Created2011
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Description
The climate-driven volumetric response of unsaturated soils (shrink-swell and frost heave) frequently causes costly distresses in lightly loaded structures (pavements and shallow foundations) due to the sporadic climatic fluctuations and soil heterogeneity which is not captured during the geotechnical design. The complexity associated with the unsaturated soil mechanics combined with

The climate-driven volumetric response of unsaturated soils (shrink-swell and frost heave) frequently causes costly distresses in lightly loaded structures (pavements and shallow foundations) due to the sporadic climatic fluctuations and soil heterogeneity which is not captured during the geotechnical design. The complexity associated with the unsaturated soil mechanics combined with the high degree of variability in both the natural characteristics of soil and the empirical models which are commonly implemented tends to lead to engineering judgment outweighing the results of deterministic computations for the basis of design. Recent advances in the application of statistical techniques and Bayesian Inference in geotechnical modeling allows for the inclusion of both parameter and model uncertainty, providing a quantifiable representation of this invaluable engineering judgement. The overall goal achieved in this study was to develop, validate, and implement a new method to evaluate climate-driven volume change of shrink-swell soils using a framework that encompasses predominantly stochastic time-series techniques and mechanistic shrink-swell volume change computations. Four valuable objectives were accomplished during this research study while on the path to complete the overall goal: 1) development of an procedure for automating the selection of the Fourier Series form of the soil suction diffusion equations used to represent the natural seasonal variations in suction at the ground surface, 2) development of an improved framework for deterministic estimation of shrink-swell soil volume change using historical climate data and the Fourier series suction model, 3) development of a Bayesian approach to randomly generate combinations of correlated soil properties for use in stochastic simulations, and 4) development of a procedure to stochastically forecast the climatic parameters required for shrink-swell soil volume change estimations. The models presented can be easily implemented into existing foundation and pavement design procedures or used for forensic evaluations using historical data. For pavement design, the new framework for stochastically forecasting the variability of shrink-swell soil volume change provides significant improvement over the existing empirical models that have been used for more than four decades.
ContributorsOlaiz, Austin Hunter (Author) / Zapata, Claudia (Thesis advisor) / Houston, Sandra (Committee member) / Kavazanjian, Edward (Committee member) / Soltanpour, Yasser (Committee member) / Arizona State University (Publisher)
Created2022