Geophysical monitoring and reactive transport modeling of ureolytically-driven calcium carbonate precipitation

Ureolytically-driven calcium carbonate precipitation is the basis for a promising in-situ remediation method for sequestration of divalent radionuclide and trace metal ions. It has also been proposed for use in geotechnical engineering for soil strengthening applications. Monitoring the occurrence, spatial distribution, and temporal evolution of calcium carbonate precipitation in the subsurface is critical for evaluating the performance of this technology and for developing the predictive models needed for engineering application. In this study, we conducted laboratory column experiments using natural sediment and groundwater to evaluate the utility of geophysical (complex resistivity and seismic) sensing methods, dynamic synchrotron x-ray computed tomography (micro-CT), and reactive transport modeling for tracking ureolytically-driven calcium carbonate precipitation processes under site relevant conditions. Reactive transport modeling with TOUGHREACT successfully simulated the changes of the major chemical components during urea hydrolysis. Even at the relatively low level of urea hydrolysis observed in the experiments, the simulations predicted an enhanced calcium carbonate precipitation rate that was 3-4 times greater than the baseline level. Reactive transport modeling results, geophysical monitoring data and micro-CT imaging correlated well with reaction processes validated by geochemical data. In particular, increases in ionic strength of the pore fluid during urea hydrolysis predicted by geochemical modeling were successfully captured by electrical conductivity measurements and confirmed by geochemical data. The low level of urea hydrolysis and calcium carbonate precipitation suggested by the model and geochemical data was corroborated by minor changes in seismic P-wave velocity measurements and micro-CT imaging; the latter provided direct evidence of sparsely distributed calcium carbonate precipitation. Ion exchange processes promoted through NH4+ production during urea hydrolysis were incorporated in the model and captured critical changes in the major metal species. The electrical phase increases were potentially due to ion exchange processes that modified charge structure at mineral/water interfaces. Our study revealed the potential of geophysical monitoring for geochemical changes during urea hydrolysis and the advantages of combining multiple approaches to understand complex biogeochemical processes in the subsurface

2D Transparency Space—Bring Domain Users and Machine Learning Experts Together

Machine Learning (ML) is currently facing prolonged challenges with the user acceptance of delivered solutions as well as seeing system misuse, disuse, or even failure. These fundamental challenges can be attributed to the nature of the “black-box” of ML methods for domain users when offering ML-based solutions. That is, transparency of ML is essential for domain users to trust and use ML confidently in their practices. This chapter argues for a change in how we view the relationship between human and machine learning to translate ML results into impact. We present a two-dimensional transparency space which integrates domain users and ML experts together to make ML transparent. We identify typical Transparent ML (TML) challenges and discuss key obstacles to TML, which aim to inspire active discussions of making ML transparent with a systematic view in this timely field

Soil Stabilization Against Water Erosion via Calcite Precipitation by Plant-Derived Urease

Stabilization is often necessary to improve the stiffness, strength and durability of both natural and compacted soils. Soils are typically stabilized via the addition of hydraulic binders, such as cement and lime, which present however relatively high carbon and energy footprints. Alternative stabilization techniques are therefore explored to minimize environmental impact while preserving good material properties. Among these techniques, enzyme induced calcite precipitation (EICP) has gained prominence in recent years. EICP exploits the action of the urease enzyme to catalyze the hydrolysis of urea and to produce carbonate ions, which then react with calcium ions inside the pore water to cause precipitation of calcium carbonate (i.e. calcite). The precipitated mineral bonds particles together, thus improving the hydro-mechanical characteristics of the soil. This paper presents a preliminary investigation on the use of plant-derived urease, instead of pure reagent-grade urease, to minimize environmental and financial costs. The urease enzyme is obtained from a liquid soybeans extract, inside which urea and calcium chloride are dissolved. This stabilizing solution is then mixed with a silty clay to produce stabilized samples, which are subjected to water erosion tests