David L Henann

David L. Henann serves as the James R. Rice Associate Professor of Solid Mechanics in the Department of Engineering at Brown University's School of Engineering. His research focuses on continuum-level constitutive modeling of engineering materials, with particular expertise in granular materials, viscoelastic foams, and bubble dynamics in soft solids. Henann leads an active research group developing computational frameworks for material behavior prediction through numerical simulation.

• PhD, Massachusetts Institute of Technology (2011)
• SM, Massachusetts Institute of Technology (2008)
• BS, State University of New York at Binghamton (2006)

Henann's research spans constitutive theory development and computational implementation for complex material systems. His group pioneers nonlocal continuum models for granular flows, large-deformation viscoelastic theories for elastomeric foams, and high-strain-rate characterization of microcavitation phenomena. Current projects include modeling size segregation in granular media, bubble dynamics in viscoelastic hydrogels, and electromechanical instabilities in dielectric elastomers.

His publication record reveals consistent focus on material instability phenomena, constitutive model validation, and experimental-computational synergy. Henann frequently collaborates with experimental groups to validate theoretical frameworks, particularly in soft matter mechanics and cavitation dynamics.

• Eshelby Mechanics Award for Young Faculty (2020)
• NSF CAREER Award (2016)
• Pi Tau Sigma Gold Medal (ASME, 2016)
• Brown University Teaching Awards (2015-2016)

Henann maintains an active teaching portfolio covering continuum mechanics, solid mechanics, and plasticity at both undergraduate and graduate levels. His research group operates a computational mechanics laboratory with extensive Fortran-based simulation capabilities, evidenced by multiple open-source repositories on GitHub for granular rheology, foam modeling, and dielectric elastomer analysis. Current work focuses on extending nonlocal granular models to industrial applications and developing predictive frameworks for soft material failure under extreme loading conditions.