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INSTRUCTORS:
Wonjun Cha
Cagla Meral Akgul
Akbar Whizin
Course Length: 1 hour
Purpose and Background
These presentations were recorded at Earth and Space 2026 Conference.
Granular Ratcheting Under ExtremeThermal Cycles: Shakedown, Ratcheting and Terminal Void Ratio (18 minutes)
Future lunar and Martian infrastructure will be subjected to extreme temperature fluctuations that can significantly influence the behavior of granular soils. This presentation examines the concepts of shakedown, ratcheting, and terminal void ratio as they relate to repeated thermal cycling in regolith materials. Laboratory experiments and discrete element simulations are used to investigate how particle expansion and contraction generate cumulative settlements and shear deformations without changes in external loading. The study demonstrates that the initial thermal cycles produce the largest deformations before approaching a stabilized condition. The effects of stress level, particle interactions, and cohesion on long-term performance are also explored. These findings provide valuable insight into the design of resilient extraterrestrial foundations and underground infrastructure.
Machine Learning-Based Evaluation of Regolith Simulants for In-Situ Construction Applications in Extraterrestrial Environments (19 minutes)
The success of future lunar construction depends heavily on selecting appropriate regolith simulants that accurately represent the diversity of actual lunar soils. This presentation introduces a machine learning framework that evaluates the geochemical coverage of existing simulants and predicts their engineering performance for in-situ construction applications. Principal Component Analysis (PCA) and clustering techniques are used to compare mission-derived lunar data with available terrestrial simulants, revealing important representativeness gaps. As a case study, supervised machine learning models are developed to predict geopolymer compressive strength using regolith chemistry and processing parameters. The study highlights the advantages and limitations of data-driven approaches and identifies opportunities to reduce experimental costs through predictive modeling. Attendees will gain insight into how artificial intelligence can accelerate the development of future lunar infrastructure technologies.
Discrete Element Modeling and Parametric Studies of Lunar Regolith Flow (19 minutes)
Efficient handling and transportation of lunar regolith will be essential for excavation, resource processing, and habitat construction on the Moon. This presentation explores the application of Discrete Element Modeling (DEM) to simulate granular flow behavior under lunar gravity conditions. Using the MFIX DEM framework, researchers perform parametric studies examining the influence of particle cohesion, friction, and restitution properties on hopper discharge and angle of repose behavior. Simulation results are compared with laboratory data and published measurements to validate the computational approach. The study also discusses ongoing efforts to incorporate more realistic particle shapes and electrostatic effects into future models. These advancements contribute to the development of reliable regolith handling systems for extraterrestrial operations.
Benefits and Learning Outcomes
Upon completion of this course, you will be able to:
- Explain the concepts of shakedown, ratcheting, and terminal void ratio in granular materials under cyclic thermal loading.
- Describe how extreme temperature cycles influence deformation and densification behavior in extraterrestrial regolith.
- Discuss the role of machine learning in evaluating the performance of regolith simulants for construction applications.
- Identify key geochemical and material parameters that influence the suitability of regolith simulants for in-situ resource utilization.
- Describe the principles of discrete element modeling (DEM) used to simulate lunar regolith flow behavior.
- Explain how material properties and model parameters affect regolith flow and handling in extraterrestrial environments.
Assessment of Learning Outcomes
Students' achievement of the learning outcomes will be assessed via a short post-test assessment (true-false, multiple choice, and/or fill in the blank questions).
Who Should Attend?
- Aerospace / Space Systems Engineers
- Civil Engineers (Geotechnical, Structural, Construction)
- Geotechnical / Materials Engineers
- Robotics & Autonomous Systems Engineers
- Researchers & Academics
- Government & Space Agency Professionals
How to Earn your CEUs/PDHs and Receive Your Certificate of Completion
To receive your certificate of completion, you will need to complete a short on-line post-test and receive a passing score of 70% or higher within 365 days of the course purchase.
How do I convert CEUs to PDHs?
1.0 CEU = 10 PDHs [Example: 0.1 CEU = 1 PDH]