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Odeh Dababneh, Timoleon Kipouros and James F. Whidborne
In this paper, a practical optimization framework and enhanced strategy within an industrial setting are proposed for solving large-scale structural optimization problems in aerospace. The goal is to eliminate the difficulties associated with optimizatio...
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Odeh Dababneh, Timoleon Kipouros and James F. Whidborne
In this paper, a practical optimization framework and enhanced strategy within an industrial setting are proposed for solving large-scale structural optimization problems in aerospace. The goal is to eliminate the difficulties associated with optimizatio...
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Xiaoyu Han, Chenyu Li, Zifan Wang and Guohua Liu
Neural architecture search (NAS) has shown great potential in discovering powerful and flexible network models, becoming an important branch of automatic machine learning (AutoML). Although search methods based on reinforcement learning and evolutionary ...
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Angel Alejandro Juan, Canan Gunes Corlu, Rafael David Tordecilla, Rocio de la Torre and Albert Ferrer
Soft constraints are quite common in real-life applications. For example, in freight transportation, the fleet size can be enlarged by outsourcing part of the distribution service and some deliveries to customers can be postponed as well; in inventory ma...
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Lev Utkin, Andrey Ageev, Andrei Konstantinov and Vladimir Muliukha
A new modification of the isolation forest called the attention-based isolation forest (ABIForest) is proposed for solving the anomaly detection problem. It incorporates an attention mechanism in the form of Nadaraya?Watson regression into the isolation ...
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Sadik Ozgur Degertekin, Mohammad Minooei, Lorenzo Santoro, Bartolomeo Trentadue and Luciano Lamberti
Metaheuristic algorithms currently represent the standard approach to engineering optimization. A very challenging field is large-scale structural optimization, entailing hundreds of design variables and thousands of nonlinear constraints on element stre...
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Alberto Racca, Tom Verstraete and Lorenzo Casalino
This paper addresses the problem of the design optimization of turbomachinery components under thermo-mechanical constraints, with focus on a radial turbine impeller for turbocharger applications. Typically, turbine components operate at high temperature...
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Jared A. Cook, Ralph C. Smith, Jason M. Hite, Razvan Stefanescu and John Mattingly
Surrogate models are increasingly required for applications in which first-principles simulation models are prohibitively expensive to employ for uncertainty analysis, design, or control. They can also be used to approximate models whose discontinuous de...
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Himangshu Kalita, Alvaro Diaz-Flores and Jekan Thangavelautham
Missions targeting the extreme and rugged environments on the moon and Mars have rich potential for a high science return, although several risks exist in performing these exploration missions. The current generation of robots is unable to access these h...
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Junho Chun
This paper proposes a reliability-based design optimization (RBDO) approach that adopts the second-order reliability method (SORM) and complex-step (CS) derivative approximation. The failure probabilities are estimated using the SORM, with Breitung?s for...
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Roberto Agromayor and Lars O. Nord
Axial turbines are the most common turbine configuration for electric power generation and propulsion systems due to their versatility in terms of power capacity and range of operating conditions. Mean-line models are essential for the preliminary design...
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Girolamo Musso, Iara Figueiras, Héléna Goubel, Afonso Gonçalves, Ana Laura Costa, Bruna Ferreira, Lara Azeitona, Simão Barata, Alain Souza, Frederico Afonso, Inês Ribeiro and Fernando Lau
The commercial space launch sector is currently undergoing a significant shift, with increasing competition and demand for launch services, as well as growing concerns about the environmental impact of rocket launches. To address these challenges, within...
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