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Highlighted Research
Implicit Sampling
The Mathematics Group at Berkeley Lab has developed a methodology called implicit sampling to find unbiased high-probability samples efficiently. Using a variationally enhanced process, implicit sampling enables researchers to zero in on the high-probability regions of a sample space. Read More »
High-Order Methods for Fluid-Structure Interaction with Applications to Vertical Axis Wind Turbine Simulations
The Mathematics Group has developed new numerical schemes for high-order accurate simulations of fluids and solids. This has led to efficient solvers that scale well on the new generation of multi-core computer architectures. Read More »
Mathematical and Algorithmic Methodologies for Computing Multiphase Multiphysics
CRD Math researchers built the Voronoi Implicit Interface Method to track multiple coupled interfaces moving under complex physics constraints, such as industrial foams, bone, and bubbles. Read More »
Long-time Dynamics and Optimization of Nonlinear PDE
The Math Group at Berkeley Lab is developing new computational tools to study dynamic problems with time-periodic forcing or symmetry. Read More »
