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Przemyslaw S. Drezek, Slawomir Kubacki and Jerzy Zóltak
The forecasted growth in dynamic global air fleet size in the coming decades, together with the need to introduce disruptive technologies supporting net-zero emission air transport, demands more efficient design and optimization workflows. This research ...
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Aikaterini P. Kyprioti, Alexandros A. Taflanidis, Norberto C. Nadal-Caraballo, Madison C. Yawn and Luke A. Aucoin
Surrogate models, also referenced as metamodels, have emerged as attractive data-driven, predictive models for storm surge estimation. They are calibrated based on an existing database of synthetic storm simulations and can provide fast-to-compute approx...
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Tobias Martin, Arun Kamath, Gang Wang and Hans Bihs
The numerical framework of the open source CFD solver REEF3D is utilised to study the fluid?structure interaction of an open ocean aquaculture system and waves. The presence of the net is considered in the momentum equations of the fluid using a forcing ...
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Phuong Hoa Hoang, Hoang Nam Phan, Duy Thao Nguyen and Fabrizio Paolacci
Uncertainty quantification is an important issue in the seismic fragility analysis of bridge type structures. However, the influence of different sources of uncertainty on the seismic fragility of the system is commonly overlooked due to the costly re-ev...
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Joongjin Shin, Seokheum Baek and Youngwoo Rhee
In this study, a metamodel of an optimal arrangement of wind turbines was developed to maximize the energy produced by minimizing the energy loss due to wakes in a limited space when designing a wind farm. Metamodeling or surrogate modeling techniques ar...
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Chan Ho Jeong, Min Kyu Ko, Moonjin Lee and Seong Hyuk Lee
The present study aimed to numerically establish a new metamodel for predicting the propagation distribution of styrene, which is one of the hazardous and noxious substances (HNSs) spilled from ships. Three-dimensional computational fluid dynamics (CFD) ...
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Mohamed H. Aissa and Tom Verstraete
Kriging is increasingly used in metamodel-assisted design optimization. For expensive simulations; however, one can afford only a few samples to build the Kriging model, which consequently lacks prediction accuracy. We propose a bounded Kriging able to h...
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