Morgan D. Sanger
  • Bio
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  • Publications
    • A database of cone penetration tests from North America (version 2)
    • A database of shear wave velocity tests from North America
    • AI-driven seismic velocity modelling in the North Sea: using onshore data to predict offshore conditions
    • Mechanics-informed machine learning for geospatial modeling of soil liquefaction: global and national surrogate models for simulation and near-real-time response
    • Pacific Northwest liquefaction hazard simulations
    • Informing predictions from above with data from below: a hierarchical geospatial liquefaction model for rapid response and simulation
    • Mechanics-informed machine learning for geospatial modeling of soil liquefaction: example model implementation in Jupyter Notebook and Matlab
    • Mechanics-informed machine learning for geospatial modeling of soil liquefaction: global model map products for LPI, LPIISH, and LSN
    • Mechanics-informed machine learning for geospatial modeling of soil liquefaction: New Zealand model map products for LPI, LPIISH, and LSN
    • Transportation infrastructure performance under seismic hazards with SimCenter Tools
    • A database of cone penetration tests from the Cascadia Subduction Zone
    • On the underutilization of artificial intelligence models in geotechnical practice
    • A database of cone penetration tests from North America
    • Why AI models for predicting soil liquefaction have been ignored, plus some that shouldn’t be
    • Meet Geo P. Tech, AI Chatbot Geotechnical Engineer: How AI Language Models Like 'ChatGPT' Could Change the Profession
    • Recycled concrete aggregate in base course applications: Review of field and laboratory investigations of leachate pH
    • Neutralization of high pH and alkalinity effluent from recycled concrete aggregate by common subgrade soil
    • Early introduction of STEM through sustainable engineering
    • Chemistry of recycled concrete aggregate leachate in pavement base course applications
    • Characterization of recycled concrete aggregate after eight years of field deployment
    • Fate and transport of recycled concrete aggregate leachate
    • Assessing the impact of contact time on leachate chemistry from recycled concrete aggregate
    • Environmental benefits of cold-in-place recycling
    • Environmental benefits of cold-in-place recycling
    • Revisiting geophysical interpretations of the Midcontinent Rift below Lake Superior
    • Seismic interpretation of the 1.1 Ga Midcontinent Rift volcanic interval beneath Lake Superior
    • Geospatial AI for liquefaction hazard and impact forecasting: a demonstrative study in the U.S. Pacific Northwest
    • Towards AI-driven seismic velocity modelling in the North Sea: Using onshore data to predict offshore conditions
  • Presentations
    • Liquefaction impacts on PacTrans mobility: Mechanics-informed AI modeling for simulation, disaster equity, and near-real-time response
    • Lessons in geotechnical earthquake engineering from large-magnitude earthquakes in Mexico
    • AI-driven seismic velocity modeling in the North Sea: using onshore data to predict offshore conditions
    • Integrating public and proprietary geotechnical data sources for improved parameter mapping
    • Mechanics-informed machine learning for geospatial modeling of liquefaction: global and national surrogate models for simulation and near-real-time response
    • Lessons from the graveyard: resurrecting AI for geohazard prediction in a riskier world
    • Why most AI models are ignored and why some probably shouldn’t be + geotechnical trends: Musings on education, research, and the future
    • Mechanics-informed machine learning for regional geohazard modeling
    • Application of AI/ML to large geospatial and geotechnical data sets for improved natural hazard modeling
    • A mechanics-informed machine learning model for regional liquefaction hazard planning and response
    • Rapid Map: A mechanics-informed machine learning model for regional liquefaction hazard planning and response
    • Mechanics-informed, geospatial machine learning for natural hazard planning and response
    • Why most “AI” models are ignored, plus some that probably shouldn’t be
    • Geosp-AI-tial liquefaction: mechanics-informed AI and geospatial data for liquefaction hazard planning and response
    • AI in geotechnical engineering practice
    • Navigating geohazards: AI-driven, near-real-time liquefaction predictions and insights for transportation networks
    • Introduction to generative AI and large language models
    • Drone usage
    • Geotechnical field investigation methods
    • Chemistry of recycled concrete aggregate leachate in pavement base course applications
    • Chemistry of recycled concrete aggregate leachate in pavement base course applications
    • Fate and transport of recycled concrete aggregate leachate
    • Assessing the impact of contact time on leachate chemistry from recycled concrete aggregate
    • Eva the Engineer: encouraging young women at the intersection of engineering and sustainability
    • Eva the Engineer: encouraging young women at the intersection of engineering and sustainability
    • Revisiting geophysical interpretations of the Midcontinent Rift below Lake Superior
    • Seismic interpretation of the 1.1 Ga Midcontinent Rift volcanic interval beneath Lake Superior
    • Environmental benefits of cold-in-place recycling
    • Environmental benefits of cold-in-place recycling
  • Library
    • Nexus: A Brief History of Information Networks from the Stone Age to AI by Yuval Noah Harari
    • The Big Dig by NPR
    • Video: The Future of Scientific Code in the Era of Generative AI
    • See what else I'm reading
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Early introduction of STEM through sustainable engineering

Jun 16, 2019·
T. Klink
,
Morgan D. Sanger
,
R. Olley
,
A. Pakes
,
T. B. Edil
,
S. Klinzing
· 0 min read
DOI PDF
Last updated on Jun 16, 2019
← Neutralization of high pH and alkalinity effluent from recycled concrete aggregate by common subgrade soil Dec 11, 2019
Chemistry of recycled concrete aggregate leachate in pavement base course applications May 1, 2019 →

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