Chloé Arson

Biography

Dr. Chloé Arson is a Professor in the School of Civil and Environmental Engineering (CEE) at Cornell University and an adjunct faculty in the Schools of CEE and Earth and Atmospheric Sciences at the Georgia Institute of Technology (Georgia Tech). She earned her Ph.D. at Ecole Nationale des Ponts et Chaussées (France) in 2009. She was an Assistant Professor at Texas A&M University from 2009 to 2012. Then, she worked as an Assistant Professor (2012-2016), Associate Professor (2016-2022) and Professor (2022-2023) in the Georgia Tech School of CEE. Dr. Arson joined the faculty at Cornell University in Summer 2023. 

Research Interests

Dr. Arson’s expertise is damage and healing rock mechanics, micro-macro modeling of porous media, and computational geomechanics. Her group develops numerical tools to assess the performance and environmental impacts of underground storage and rock fracturing, explain the formation of soil by rock weathering, and design sustainable bio-inspired geotechnical systems. Lately, Arson started investigating the use of artificial intelligence (AI) to optimize subsurface exploration and enhance multi-scale geomechanical models.

Mechanics of particulate fragmentation

Understanding the mechanisms that trigger fragmentation in granular media and cemented aggregates is of primary importance for optimizing the stability of earth structures, designing ballast and processing food. Arson’s group uses the Discrete Element Method to simulate particulate flow and aggregate particle crushing.

Adaptive homogenization informed by AI

Damage and healing rock mechanics is important to design safe underground storage facilities, assess the impact of hydraulic fracturing, understand fault dynamics, and simulate geomorphological processes. Arson’s group developed original thermodynamic and micromechanical models of crack initiation, opening, closure and rebonding for carbonate rock, granite, and halite, which are common geological host materials. The lab now uses AI to detect the microstructure features that are the most important to capture rock behavior at the macro-scale.

Poromechanical modeling to mitigate climate change

Landscapes encode the history of the climate. For example, saprolite, the intermediate material between rock and soil, plays a critical role in the evolution of topography, nutrient supply, landslide hazards, and the global carbon cycle. The subsurface also bears resources used for the production of energy and construction materials. It is thus important to assess the response of soils, rocks and other geomaterials to a varying climate and to increasing societal demands. Arson’s group implemented a micro-macro model of anisotropic damage upon time-dependent biotite expansion in the Finite Element Method (FEM) to understand the impact of bedrock weathering on mechanical damage in typical landscapes. The lab is also working on the forecast of greenhouse gas emissions from sediments subjected to hydraulic forcings.

Computational fracture mechanics to advance energy geotechnology

Predicting the occurrence of large-scale fractures (0.1m-10m) as the result of the interaction and/or coalescence of microscopic cracks is important to predict many instabilities in geomechanics. To this end, Arson’s group developed computational tools to simulate the propagation of a discrete fracture within a continuum damage process zone, both with Cohesive Zone models and the eXtended Finite Element Method. Simulation results highlighted the influence of intrinsic anisotropy on fluid-driven fracture propagation, which is of significance for deep geothermal energy extraction and cavern stability. The lab also simulated time-dependent damage propagation and healing of salt rock at the vicinity of geological storage facilities.

Smart autonomous subsurface exploration

Dr. Arson is currently leading a research effort that aims to develop a self-propelled Burrowing Robot with an Integrated Sensor System (BRISS). Arson’s group assessed the performance of compound anchors with a novel method that combines the FEM with Smoothed Particle Hydrodynamics. Her lab also analyzed the deformation and failure mechanisms induced by the pressurization of a cylindrical body at shallow depth, which bridged an important knowledge gap, since no analytical solution accounts for the geostatic gradient. Because of the lack of closed-form solutions, it is challenging to predict in situ stresses to back-calculate soil properties from data collected by embarked sensors. That is why Arson’s group has trained and tested neural networks that can estimate mechanical properties of a granular soil from the stress field at the soil/robot interface. Arson’s group is also developing bio-inspiration strategies to minimize the energy and power needed to explore underground and construct durable tunnel systems in which to deploy monitoring systems.

Network construction dynamics

Arson’s lab has modeled biological dynamic networks to increase the adaptability of infrastructure. It was found that the cost and performance of a leaf venation network are comparable to those of a spanning tree but an order of magnitude faster, which suggests that rapid leaf inspired solutions could be used to initialize more optimal spanning tree algorithms. Arson’s group studied the mechanisms of plant root growth in natural soil and the response of root architectures to obstacles to seek biomimetic solutions to demands for infrastructure network adaptation. The research team also designed image analysis tools to assess network resilience in slime mold, a protist, amoeba-like organism that grows by foraging. The observation of slime mold network fusion in different environments highlighted morphing strategies that could inspire civil engineers to adapt infrastructure in response to terrorist threats, natural disasters, and pandemics.

Areas of Interest

• Artificial Intelligence
• Computational Mechanics
• Computational Solid Mechanics
• Earth and Atmospheric Science
• Geotechnical Engineering
• Heat and Mass transfer
• Scientific Computing
• Signal and Image Processing
• Structural Engineering
• Surface Science
• Sustainable Energy Systems