Subsurface Biomining Simulation
Subsurface Biomining Simulation - Related Videos
00:13
Using Flexible Gold-Titanium Reaction Cells to Simulate Pressure-Dependent Microbial Activity in the Context of Subsurface Biomining
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Cited by 3 •
2019
This protocol describes microbial experiments under elevated pressures to study in situ biomining processes. The experimental approach employs a rocking high-pressure reactor equipped with a gold-titanium reaction cell containing a microbial culture in an acidic, iron-rich medium.
10:21
A High Throughput Screen for Biomining Cellulase Activity from Metagenomic Libraries
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Cited by 24 •
2011
This protocol describes a high throughput screen for cellulolytic activity from a metagenomic library expressed in Escherichia coli. The screen is solution based and highly automated, and uses one-pot chemistry in 384 well microplates with the final readout as an absorbance measurement.
07:58
Data Processing Methods for 3D Seismic Imaging of Subsurface Volcanoes: Applications to the Tarim Flood Basalt
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Cited by 3 •
2017
Three-dimensional (3D) reflection seismology is a powerful method for imaging subsurface volcanoes. By using industrial 3D seismological data from the Tarim Basin, we illustrate how to extract the sills and the conduits of subsurface volcanoes from seismic data cubes.
11:34
Subsurface Defect Localization by Structured Heating Using Laser Projected Photothermal Thermography
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Cited by 7 •
2017
This method aims at locating vertical subsurface defects. Here, we couple a laser with a spatial light modulator and trigger its video input to heat a sample surface deterministically with two anti-phased modulated lines while acquiring highly resolved thermal images. The defect position is retrieved from evaluating thermal wave interference minima.
09:49
Visualizing Hyporheic Flow Through Bedforms Using Dye Experiments and Simulation
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Cited by 4 •
2015
This manuscript describes how to create regular bedforms in a flume, visualize flow through the bedforms, and use computer simulations to simulate the hyporheic flow. The computer simulations compare well with the experimental observations. This coupled simulation and experiment is well-suited for both research and educational purposes.
FAQs
These simulations work by coupling fluid flow, solute transport, mineral dissolution, and microbial activity within one computational representation. Fluid movement determines where injected materials travel, transport governs concentration changes, dissolution represents mineral release, and microbial activity links biological processes to recovery behavior. This coupling lets engineers examine interacting effects rather than treating each process in isolation.
Permeability, temperature, reaction rates, and nutrient delivery are central variables because they affect how fluids and microbes interact with ore-bearing geological materials. Changing permeability can alter fluid movement, while temperature and reaction rates influence process behavior. Nutrient delivery affects the conditions available for microbial activity, allowing engineers to test operational limits and compare recovery estimates.
Reaction rates and microbial activity connect biological behavior with mineral dissolution and metal recovery. Their representation helps the model estimate how quickly relevant processes may proceed under subsurface conditions. Examining these factors alongside fluid flow and solute transport reveals whether the simulated system can support the expected recovery, or whether interacting conditions may limit performance.
Engineers first represent the underground rock formation and the relevant interactions among injected fluids, microbes, minerals, and transported solutes. They then vary conditions such as permeability, temperature, reaction rates, and nutrient delivery across computational scenarios. The resulting predictions can be examined for estimated metal recovery, operational limits, and environmental risks before field deployment.
The approach is useful during process design and site evaluation, particularly before committing to costly and disruptive field experimentation. Engineers can test multiple subsurface conditions computationally, compare expected recovery, and identify constraints in advance. This reduces reliance on trial and error while supporting decisions about whether an in situ biomining strategy merits further development.
Simulation results can provide estimates of metal recovery and indicate how operating conditions may influence performance. They can also identify limits associated with permeability, temperature, reaction rates, nutrient delivery, and environmental risk. Engineers can use these outputs to refine process design, evaluate candidate sites, and optimize in situ biomining before field deployment.