activity
20142018
most citedQuantifying and Reducing Model-Form Uncertainties in Reynolds-Averaged Navier-Stokes Simulations: A Data-Driven, Physics-Based Bayesian Approach

316 citations · 895 across the 13 of their papers we have counts for

collaborators
Showing 2016Show all

5 papers · 1 filter

physics.geo-ph2016★ 3 cited

Particle dynamics in self-generated dunes over a range of hydraulic and sediment transport conditions using LES--DEM

Rui Sun, Heng Xiao, Kyle Strom

Direct measurement of vertical and longitudinal sediment fluxes on migrating sandy bedforms are extremely difficult to perform in both the field and laboratory. In this study we us…

physics.comp-ph2016★ 42 cited

Realistic Representation of Grain Shapes in CFD--DEM Simulations of Sediment Transport: A Bonded-Sphere Approach

Rui Sun, Heng Xiao

Development of algorithms and growth of computational resources in the past decades have enabled simulations of sediment transport processes with unprecedented fidelities. The Comp…

physics.comp-ph2016★ 24 cited

Quantification of Uncertainties in Turbulence Modeling: A Comparison of Physics-Based and Random Matrix Theoretic Approaches

Jian-Xun Wang, Rui Sun, Heng Xiao

Numerical models based on Reynolds-Averaged Navier-Stokes (RANS) equations are widely used in engineering turbulence modeling. However, the RANS predictions have large model-form u…

physics.comp-ph2016★ 12 cited

Sediment Micromechanics in Sheet Flows Induced by Asymmetric Waves: A CFD-DEM Study

Rui Sun, Heng Xiao

Understanding the sediment transport in oscillatory flows is essential to the investigation of the overall sediment budget for coastal regions. This overall budget is crucial for t…

physics.flu-dyn2016★ 183 cited

SediFoam: A general-purpose, open-source CFD-DEM solver for particle-laden flow with emphasis on sediment transport

Rui Sun, Heng Xiao

With the growth of available computational resource, CFD-DEM (computational fluid dynamics-discrete element method) becomes an increasingly promising and feasible approach for the…