361 citations · 518 across the 7 of their papers we have counts for
7 papers
CFD-based Design Optimization of Ducted Hydrokinetic Turbines
Jeongbin Park, Bradford G. Knight, Yingqian Liao +6
Hydrokinetic turbines extract kinetic energy from moving water to generate renewable electricity, thus contributing to sustainable energy production and reducing reliance on fossil…
SMT 2.0: A Surrogate Modeling Toolbox with a focus on Hierarchical and Mixed Variables Gaussian Processes
Paul Saves, Remi Lafage, Nathalie Bartoli +6
The Surrogate Modeling Toolbox (SMT) is an open-source Python package that offers a collection of surrogate modeling methods, sampling techniques, and a set of sample problems. Thi…
Control Co-design of a Hydrokinetic Turbine: A Comparative Study of Open-loop Optimal Control and Feedback Control
Mohammad Reza Amini, Boxi Jiang, Yingqian Liao +3
Control co-design (CCD) explores physical and control design spaces simultaneously to optimize a system's performance. A commonly used CCD framework aims to achieve open-loop optim…
Control Co-design of a Hydrokinetic Turbine with Open-loop Optimal Control
Boxi Jiang, Mohammad Reza Amini, Yingqian Liao +2
This paper introduces a control co-design (CCD) framework to simultaneously explore the physical parameters and control spaces for a hydro-kinetic turbine (HKT) rotor optimization.…
Machine Learning in Aerodynamic Shape Optimization
Jichao Li, Xiaosong Du, Joaquim R. R. A. Martins
Machine learning (ML) has been increasingly used to aid aerodynamic shape optimization (ASO), thanks to the availability of aerodynamic data and continued developments in deep lear…
Learning High-Dimensional Parametric Maps via Reduced Basis Adaptive Residual Networks
Thomas O'Leary-Roseberry, Xiaosong Du, Anirban Chaudhuri +3
We propose a scalable framework for the learning of high-dimensional parametric maps via adaptively constructed residual network (ResNet) maps between reduced bases of the inputs a…
Gradient-enhanced kriging for high-dimensional problems
Mohamed Amine Bouhlel, Joaquim R. R. A. Martins
Surrogate models provide a low computational cost alternative to evaluating expensive functions. The construction of accurate surrogate models with large numbers of independent var…