Nov. 9 Technical Session Recording Now Available

Speaker #1

Eleanor Fadely

University of California - Davis, Davis, California

In Situ Manganese Biomineralization in Granular Media for Contaminant Removal

Co-authors: Gaitan Gehin, Lena Ray, Veronica Morales, and Jasquelin Pena, University of California - Davis

Abstract

In situ bioremediation is beneficial for contaminant mitigation at sites where pump-and-treat methods have failed due to long residence times or inaccessible zones of pollution. However, bioremediation in porous media, such as soil or sediment, is limited by structural, chemical, and hydrologic heterogeneities that restrict microbial distribution and nutrient delivery. Microbially- mediated oxidation, or biomineralization, of manganese (Mn) is a promising method for in situ remediation of metal contamination. As strong chemical oxidants and sorbents, biogenic Mn oxides are particularly suited to transform and/or immobilize metal ions. However, knowledge of inter- and intra-pore transport mechanisms and fluid mixing is necessary to implement Mn biomineralization for the remediation of impaired environments.

This research uses microfluidics and epifluorescence microscopy to examine the pore-scale biogeochemistry of Mn biomineralization in a simulated porous medium based on the Ottawa silica test sand. Microfluidic reactors enable experimentation under tightly controlled environmental conditions while allowing for complete visualization of microbial processes over time and space at the scale of individual bacteria and bacteria-mineral aggregates. Using this platform, we aim to determine the optimal hydrodynamic conditions and nutrient delivery necessary for Mn-oxidizing bacteria (Pseudomonas putida GB-1) to uniformly colonize a granular medium and oxidize Mn. Preliminary results demonstrate that P. putida GB-1 distributed throughout the porous medium to form large aggregates in pore bodies between sand grains and along grain boundaries. Microbial aggregates produced dark brown precipitates, indicating the presence of Mn oxides (MnOx) associated with the stationary phase of bacterial growth and shift from planktonic to biofilm life stage. Future flow-field analysis will characterize the relative effects of advective and diffusive nutrient transport to sites of microbial growth and Mn oxidation using dimensionless Péclet and Damköhler numbers, in order to optimize biofilms formation and MnOx precipitation. Optimization of pore-scale Mn biomineralization will help upscale this process to column reactors and field test sites.
 

Speaker #2

Nancy Merino

Lawrence Livermore National Laboratory, Livermore, California

Subsurface Planktonic Microbial Communities as a Tool to Track Groundwater Hydraulic Connectivity and Water Quality

Co-authors: Tracie R. Jackson, Nevada Water Science Center; James H. Campbell, Northwest Missouri State; Annie B. Kersting, Lawrence Livermore National Laboratory; Josua Sackett, Desert Research Institute, University of Nevada; Jenny C. Fisher, Desert Research Institute, Indiana University Northwest; James C. Bruckner, Desert Research Institute; Mavrik Zavarin, Lawrence Livermore National Laboratory; Scott D. Hamilton-Brehm, Desert Research Institute, Southern Illinois University; Duane P. Moser, Desert Research Institute

Abstract

Remediation of subsurface sites requires understanding of the underlying hydrogeochemical processes to assess the risks associated with contaminants, and subsequently, to develop and implement the appropriate remediation method. Several approaches and models are used to characterize subsurface sites, with particular focus on potential transport of contaminants via groundwater contaminant plumes. As such, the toolkit for monitoring the hydrogeochemical processes of groundwater systems includes water-level and water-quality monitoring. However, groundwater systems also are impacted by endemic microbial communities that may help inform groundwater-flow paths, connectivity, and water quality.

In this study, we examined the planktonic microbial communities of the Death Valley Regional Flow System (DVRFS), a 100,000 km2 region with water quantity and quality issues that includes the Nevada National Security Site (NNSS, formerly Nevada Test Site). We demonstrated that the regional-scale groundwater microbiome can reflect groundwater biogeochemical conditions and flow paths identified by regional groundwater models. Samples were collected from 36 locations in three DVRFS groundwater basins: Pahute Mesa–Oasis Valley (PMOV), Ash Meadows (AM), and Alkali Flat–Furnace Creek Ranch (AFFCR). Diversity within and between communities varied by location and separated into two overall groups by the AM and the PMOV/AFFCR basins. Network analysis demonstrated that clusters of common microbes represented groundwaters with similar geochemical conditions. Null model analyses also identified that communities within locations were more similar than expected by random chance. Overall, the DVRFS planktonic microbiome reflected the following flow paths: (1) Spring Mountains to Ash Meadows; (2) Frenchman Flat and Yucca Flat to Amargosa Desert; and (3) Amargosa Desert to Death Valley. The PMOV flow paths were not supported by microbial community analyses, suggesting that microbial differences could result from slow travel times, groundwater mixing, biogeologic barriers, or underground nuclear tests. This study demonstrates the utility of combining microbial data with hydrogeochemical information to comprehensively characterize groundwater systems.

Prepared by LLNL under Contract DE-AC52-07NA27344 (IM#: LLNL-ABS-8271).

 

Speaker #3

Bozo Vazic (INVITED)

The University of Utah, Salt Lake City, Utah

Exploring the Effect of Pore Morphology on Mechanical Properties: A Higher-Order Homogenization Approach

Co-authors: Emek B. Abali, Uppsala University; Pania Newell, The University of Utah

Abstract

Most natural and man-made porous materials have heterogeneous structures across scales. In many cases, such structural heterogeneity is rooted in the underlying morphology (e.g., pore sizes, pore distribution, pore shapes, and pore strut/wall size). Although, porous structures are appealing in a variety of engineering and scientific fields, such as aerospace, energy-storage technology, and bio engineering, their heterogeneous structure must be fully understood to optimize their performance. Unfortunately, such variation of the underlying pore structure is usually ignored in many continuum scale modeling. This is mainly due to the difficulty of capturing the complex relationship between effective material properties and the underlying morphology of the porous material.

In this presentation, we will numerically investigate the effect of complex micropore morphology on the effective mechanical properties of a porous system. To account for the pore shapes and variability in the pore distribution besides the porosity, we adopt a higher-order asymptotic homogenization method. The second-order scheme used in this study is an extension of the first- order computational homogenization framework where the use of a generalized continuum enables us to introduce length scale into the material constitutive law and capture the absolute size of the pores and pore distribution. By employing this model on a set of numerical problems with different combinations of porosity, pore shapes, and distributions, we studied the relationship between the underlying morphology and effective material properties.

The results show a strong influence of pore shape on the effective material properties, with some shapes having more noticeable impact than other (e.g., circle and square pores have an almost identical effect). However, analysis of pore distribution demonstrates little to no effect on effective material properties. Moreover, we have observed that even for isotropic matrix material, different pore shapes will produce different material behavior, such as elliptic pores produce orthotropic material behavior while circular and square ones lead to cubic material behavior. Furthermore, the results for the higher-order parameters indicate a strong influence of the pore shape/distribution and the size of the representative volume element.

 

Speaker #4

Fred Day-Lewis

PNNL

Geophysical Approaches to Understand Immobile Porosity: Review and Recent Advances

Co-authors: Martin A. Briggs, U.S. Geological Survey; Kamini Singha, Colorado School of Mines; Lee D. Slater, Rutgers University Newark

Abstract

Immobile (or less mobile) porosity arising from multi-scale aquifer heterogeneity has been implicated in the prolonged timeframes observed for groundwater remediation. The storage and release of solute from immobile porosity manifests as contaminant rebound following pump-and-treat remediation, development of anoxic microzones in streambeds, and other transport phenomena that are inconsistent with classical advective-dispersive transport. The role of immobile porosity has been represented in simulation models as first-order mobile/immobile exchange, multi-rate mass transfer, multiple interacting continua, and other processes. Estimation of the parameters of these models is challenging and commonly involves history matching rather than in-situ measurement; further, characterization rarely considers spatial or multi-scale variability. In this presentation, we review recent and ongoing advances in the direct geophysical assessment of immobile porosity and the exchange between immobile and mobile pore spaces. We discuss the potential for time-lapse electrical, nuclear magnetic resonance, and spectral induced polarization for multi-scale characterization of immobile porosity and other parameters. We review results from laboratory experiments and also field experiments in lakebeds, streambeds and boreholes. Pore-scale simulation is used to investigate the relations between observations, geophysical measurements, and the parameters associated with immobile porosity and its role in transport. 

 

Speaker #5

Glenn E. Hammond

PNNL

Reducing Geochemical Complexity to Decrease Simulation Runtimes for Reactive Transport

Abstract

For many real-world modeling scenarios, there are bounds on the speedup provided by high performance computing (HPC) due to limitations in solver scalability. Any further reduction in simulation runtime must come through simplification of the numerical model (e.g., simplified geochemistry). This presentation describes the application of a prototypical dynamic KD model to replicate equilibrium surface complexation for a test problem based on uranium geochemistry and transport at the Hanford 300 Area. The dynamic KD model calculates a distribution coefficient (KD) as a nonlinear function of the fraction of river water within a grid cell, which is much cheaper than calculating full geochemistry (e.g., aqueous speciation, mineral precipitation-dissolution, surface complexation). The study demonstrates that the dynamic KD model delivers speedups on the order of 10-20x while providing similar accuracy to equilibrium surface complexation.

 

 

Speaker #6

Mark Rockhold

PNNL

Alternative Conceptual Models for Subsurface Flow and Transport at the Hanford Site

Co-authors: Bryan He and Vicky Freedman, PNNL

Abstract

Subsurface heterogeneity and sparse characterization and monitoring data typically result in significant uncertainty about groundwater flow and contaminant transport behavior. Alternative conceptual models (ACMs) of the subsurface are therefore needed to assess the potential variability and uncertainty in groundwater flow and transport of contaminants of concern. The objectives of this study are to evaluate the influence of specific features (i.e., high-permeability paleochannels) and processes (i.e., flow through basalt) on predictions of subsurface flow and contaminant transport at the Hanford Site. The results are important for evaluating uncertainties in contaminant fate and transport, and for informing remedy decisions and characterization and monitoring activities. A multipoint geostatistics (MPS) framework is used to assimilate multi-scale and disparate data types, including grain-size distribution data from core samples, electrical resistivity tomography (ERT) results from surface resistivity measurements, and LiDAR-based digital elevation data. Training images (TIs) used for MPS simulations are developed from the outlines of relic paleochannel features visible in the LiDAR data. Binned grain-size distribution metrics, and sampled and binned ERT results, are used as hard (known) and soft (uncertain) data, respectively, in conditional MPS simulations. Details of the TI generation, hard and soft data encoding, and MPS simulation results are presented. 

 

Speaker #7

Tim scheibe

PNNL

Community Data-Model Integration Infrastructure: An Orchestration-Based Scientific Computing Workflow Platform for Multiscale Model Coupling and Data Integration at a Scientific User Facility

Co-authors: Susana Roque-Malo, Sarah Leichty, Vanessa Garayburu-Caruso, Xiaoliang He, Steven Yabusaki, and Kurt H. Maier, PNNL

Abstract

Hybrid multiscale models use a variety of computational strategies to couple various single-scale simulation tools to increase process fidelity and resolution while maintaining computational efficiency. There have recently been several examples of such model coupling for subsurface flow and reactive transport, for example coupling pore-scale (e.g., Stokes flow) simulations with continuum scale (e.g., Darcy flow) simulations. To broaden the applicability and usability of this approach, we are developing a new infrastructure for data-model integration on high-performance parallel computers, including multi-physics and multi-scale model coupling, at a scientific user facility focused on environmental molecular science. This infrastructure takes advantages of modern cloud software known as orchestration tools, which allow users to create arbitrarily complex scientific workflows with contingencies on availability of prior data and model outputs. We have implemented this numerical framework and tested it on a proxy simulator and are currently working on a scientific use case focused on flow and transport in the rhizosphere and associated soil-microbe-mineral interactions. This presentation will illustrate the development of underlying conceptual models for multi-model coupling and data integration, and implementation of the orchestration-based numerical framework for selected use cases. The data-model integration infrastructure and a suite of associated open-source codes, together with the required high-performance computational hardware, are freely available to the scientific community through a peer-reviewed proposal process.