Machine learning in aerodynamic shape optimization
Abstract Machine learning (ML) has been increasingly used to aid aerodynamic shape
optimization (ASO), thanks to the availability of aerodynamic data and continued …
optimization (ASO), thanks to the availability of aerodynamic data and continued …
Strategies towards a more sustainable aviation: A systematic review
F Afonso, M Sohst, CMA Diogo, SS Rodrigues… - Progress in Aerospace …, 2023 - Elsevier
As climate change is exacerbated and existing resources are depleted, the need for
sustainable industries becomes ever so important. Aviation is not an exception. Despite the …
sustainable industries becomes ever so important. Aviation is not an exception. Despite the …
SMT 2.0: A Surrogate Modeling Toolbox with a focus on hierarchical and mixed variables Gaussian processes
Abstract 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 …
offers a collection of surrogate modeling methods, sampling techniques, and a set of sample …
Efficient aerodynamic shape optimization with deep-learning-based geometric filtering
Surrogate-based optimization has been used in aerodynamic shape optimization, but it has
been limited due to the curse of dimensionality. Although a large number of variables are …
been limited due to the curse of dimensionality. Although a large number of variables are …
Towards a multi-fidelity & multi-objective Bayesian optimization efficient algorithm
Black-box optimization methods like Bayesian optimization are often employed in cases
where the underlying objective functions and their gradient are complex, expensive to …
where the underlying objective functions and their gradient are complex, expensive to …
[PDF][PDF] 变可信度近似模型及其在复杂装备优化设计中的应用研究进展
周奇， 杨扬， 宋学官， 韩忠华， 程远胜， 胡杰翔… - 机械工程 …, 2020 - scholar.archive.org
变可信度近似模型通过融合不同精度分析模型的数据, 可有效平衡近似模型预测性能和建模成本
之间的矛盾, 在复杂装备优化设计中受到广泛的关注. 综述变可信度近似模型及其在复杂装备 …
之间的矛盾, 在复杂装备优化设计中受到广泛的关注. 综述变可信度近似模型及其在复杂装备 …
COBALT: COnstrained Bayesian optimizAtion of computationaLly expensive grey-box models exploiting derivaTive information
JA Paulson, C Lu - Computers & Chemical Engineering, 2022 - Elsevier
Many engineering problems involve the optimization of computationally expensive models
for which derivative information is not readily available. The Bayesian optimization (BO) …
for which derivative information is not readily available. The Bayesian optimization (BO) …
Active learning and bayesian optimization: a unified perspective to learn with a goal
F Di Fiore, M Nardelli, L Mainini - Archives of Computational Methods in …, 2024 - Springer
Science and Engineering applications are typically associated with expensive optimization
problem to identify optimal design solutions and states of the system of interest. Bayesian …
problem to identify optimal design solutions and states of the system of interest. Bayesian …
Multi-objective optimization of cycloidal blade-controlled propeller: An experimental approach
G Fasse, M Sacher, F Hauville, JA Astolfi, G Germain - Ocean Engineering, 2024 - Elsevier
In recent years, innovative naval propulsion systems have been investigated thanks to the
growing development of unmanned underwater vehicles. Cycloidal propellers are promising …
growing development of unmanned underwater vehicles. Cycloidal propellers are promising …
Constrained robust Bayesian optimization of expensive noisy black‐box functions with guaranteed regret bounds
Many real‐world design problems involve optimization of expensive black‐box functions.
Bayesian optimization (BO) is a promising approach for solving such challenging problems …
Bayesian optimization (BO) is a promising approach for solving such challenging problems …