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AI Demos by industry

Waste management AI Demos

Review contamination, groundwater transport, and source-termination choices. Explore geological context and uncertainty relevant to waste disposal and management. Browse interactive demonstrations relevant to this area, with methods, screenshots, and resource links.

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Choose an industry to explore relevant demonstrations. Research & scientific AI brings together methods used across industries.

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Geo Modeling

The geological modeling example brings surface terrain and subsurface structures together in a synthetic three-dimensional field. Wells, horizons, faults, and temperature intervals can be examined in the same scene to understand their spatial relationships. This integrated perspective helps geoscience teams explain subsurface geometry and discuss how well information relates to a broader geological interpretation.

  • Combines wells, geological horizons, faults, terrain, and temperature intervals in an interactive 3D scene.
  • Relates well trajectories and depth-dependent temperatures to their surrounding geological context.
  • Provides layer controls, terrain opacity, vertical relief, and well inspection.
  • Provides access to our open-source and proprietary ML for geospatial analyses.
  • Uses deterministic synthetic geology for illustration; the scene is not a field-validated subsurface interpretation.

Bayesian Information Gap Decision

Environmental decisions often depend on both monitoring evidence and uncertainty that extends beyond a single assumed scenario. This demo combines Bayesian evidence with information-gap stress testing to compare contaminant source-termination choices. By showing how far each option can tolerate departures from its assumptions, it helps users discuss robustness alongside a selected limit on modeled failure probability.

  • Combines Bayesian monitoring evidence with information-gap stress testing for contaminant source termination.
  • Compares four choices against a selected maximum acceptable modeled failure probability.
  • Measures how much uncertainty each choice tolerates before exceeding that limit.
  • Supports comparison under deep uncertainty; the model informs the decision rather than making it for the operator.

Groundwater Source Unmixing

Groundwater sampled at a well can contain a mixture of chemical influences from several sources. This demo applies NMFk to separate those mixtures into candidate source fingerprints and estimate their contributions at individual wells. Examining alternative source counts, stability, and reconstruction behavior helps users develop and compare explanations for observed groundwater chemistry.

  • Separates mixed groundwater chemistry into hidden source fingerprints using NMFk.
  • Compares candidate source counts and repeat-run stability.
  • Relates each recovered source to contributions at individual wells.
  • Can hide one measurement to examine its reconstruction, while preserving the distinction between measured and estimated chemistry.

Contaminant Source Identification

Monitoring wells record the downstream consequences of a release, while its original timing and movement through groundwater may remain uncertain. This synthetic inverse problem uses concentration histories to investigate a release window and an associated transport speed. Bringing the monitoring layout and estimated source behavior together helps users understand how observations constrain a possible contamination history.

  • Uses monitoring-well concentration histories to infer a contaminant release window.
  • Estimates the groundwater transport speed connecting a release to downstream monitoring wells.
  • Provides quick and stability-check depths for the synthetic inverse problem.
  • Presents the monitoring layout, concentration histories, source timing, and transport estimate together for interpretation.