24 citations · 67 across the 11 of their papers we have counts for
6 papers · 1 filter
Topology Optimization under Microscale Uncertainty using Stochastic Gradients
Subhayan De, Kurt Maute, Alireza Doostan
This paper considers the design of structures made of engineered materials, accounting for uncertainty in material properties. We present a topology optimization approach that opti…
Deterministic matrix sketches for low-rank compression of high-dimensional simulation data
Alec Michael Dunton, Alireza Doostan
Matrices arising in scientific applications frequently admit linear low-rank approximations due to smoothness in the physical and/or temporal domain of the problem. In large-scale…
Rapid Aerodynamic Shape Optimization Under Parametric and Turbulence Model Uncertainty: A Stochastic Gradient Approach
Lluís Jofre, Alireza Doostan
Aerodynamic optimization is ubiquitous in the design of most engineering systems interacting with fluids. A common approach is to optimize a performance function defined by a choic…
Bi-fidelity Reduced Polynomial Chaos Expansion for Uncertainty Quantification
Felix Newberry, Jerrad Hampton, Kenneth Jansen +1
A ubiquitous challenge in design space exploration or uncertainty quantification of complex engineering problems is the minimization of computational cost. A useful tool to ease th…
Task-parallel in-situ temporal compression of large-scale computational fluid dynamics data
Heather Pacella, Alec Dunton, Alireza Doostan +1
Present day computational fluid dynamics simulations generate extremely large amounts of data, sometimes on the order of TB/s. Often, a significant fraction of this data is discard…
Reliability-based Topology Optimization using Stochastic Gradients
Subhayan De, Kurt Maute, Alireza Doostan
This paper addresses the computational challenges in reliability-based topology optimization (RBTO) of structures associated with the estimation of statistics of the objective and…