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Aerodynamic inverse design can improve vehicle and aircraft efficiency, but practical design rarely seeks performance alone: vehicle refinement must reduce drag while preserving visual features linked to design language, brand recognition…

Machine Learning · Computer Science 2026-05-29 Huaguan Chen , Ning Lin , Luxi Chen , Jiacheng Cen , Rui Zhang , Wenbing Huang , Chongxuan Li , Hao Sun

Road vehicles contribute to significant levels of greenhouse gas (GHG) emissions. A potential strategy for improving their aerodynamic efficiency and reducing emissions is through active adaptation of their exterior shapes to the…

Robotics · Computer Science 2026-01-06 Peng Zhang , Branson Blaylock

The aerodynamic optimization process of cars requires multiple iterations between aerodynamicists and stylists. Response Surface Modeling and Reduced-Order Modeling are commonly used to eliminate the overhead due to Computational Fluid…

Computational Engineering, Finance, and Science · Computer Science 2022-05-26 Sam Jacob Jacob , Markus Mrosek , Carsten Othmer , Harald Köstler

An evolutionary multi-objective aerodynamic design optimization method using the computational fluid dynamics (CFD) simulations incorporating deep neural network (DNN) to reduce the required computational time is proposed. In this approach,…

Fluid Dynamics · Physics 2023-05-01 Yukito Tsunoda , Akira Oyama

Aerodynamic shape optimization has established itself as a valuable tool in the engineering design process to achieve highly efficient results. A central aspect for such approaches is the mapping from the design parameters which encode the…

Computational Engineering, Finance, and Science · Computer Science 2019-10-17 Jakub Kmec , Sebastian Schmitt

In recent years, the use of machine learning-based surrogate models for computational fluid dynamics (CFD) simulations has emerged as a promising technique for reducing the computational cost associated with engine design optimization.…

Generative AI models have made significant progress in automating the creation of 3D shapes, which has the potential to transform car design. In engineering design and optimization, evaluating engineering metrics is crucial. To make…

Machine Learning · Computer Science 2023-06-13 Binyang Song , Chenyang Yuan , Frank Permenter , Nikos Arechiga , Faez Ahmed

We introduce a reinforcement learning (RL) based adaptive optimization algorithm for aerodynamic shape optimization focused on dimensionality reduction. The form in which RL is applied here is that of a surrogate-based, actor-critic policy…

This paper proposes the response surface method for finite element model updating. The response surface method is implemented by approximating the finite element model surface response equation by a multi-layer perceptron. The updated…

Computational Engineering, Finance, and Science · Computer Science 2007-05-23 Tshilidzi Marwala

Aerodynamic drag on flat-backed vehicles like vans and trucks is dominated by a low-pressure wake, whose control is critical for reducing fuel consumption. This paper presents an experimental study at $Re_W\approx 78,300$ on active flow…

Multidisciplinary design optimization methods aim at adapting numerical optimization techniques to the design of engineering systems involving multiple disciplines. In this context, a large number of mixed continuous, integer and…

Engineering design optimization requires an efficient combination of a 3D shape representation, an optimization algorithm, and a design performance evaluation method, which is often computationally expensive. We present a prompt evolution…

Artificial Intelligence · Computer Science 2024-08-13 Melvin Wong , Thiago Rios , Stefan Menzel , Yew Soon Ong

This paper develops a surrogate model refinement approach for the simulation of dynamical systems and the solution of optimization problems governed by dynamical systems in which surrogates replace expensive-to-compute state- and…

Optimization and Control · Mathematics 2025-09-08 Jonathan R. Cangelosi , Matthias Heinkenschloss

Surface registration is a technique that is used in various areas such as object recognition and 3D model reconstruction. Problem of surface registration can be analyzed as an optimization problem of seeking a rigid motion between two…

Computer Vision and Pattern Recognition · Computer Science 2013-10-02 Vedran Hrgetić , Tomislav Pribanić

The computational cost of traditional Computational Fluid Dynamics-based Aerodynamic Shape Optimization severely restricts design space exploration. This paper introduces TripOptimizer, a fully differentiable deep learning framework for…

Machine Learning · Computer Science 2025-12-04 Parsa Vatani , Mohamed Elrefaie , Farhad Nazarpour , Faez Ahmed

Superomniphobic textures are at the frontier of surface design for vast arrays of applications. Despite recent significant advances in fabrication methods for reentrant and doubly reentrant microstructures, design optimisation remains a…

Soft Condensed Matter · Physics 2019-10-16 Jack Panter , Yonas Gizaw , Halim Kusumaatmaja

A main challenge in mechanical design is to efficiently explore the design space while satisfying engineering constraints. This work explores the use of 3D generative models to explore the design space in the context of vehicle development,…

Computer Vision and Pattern Recognition · Computer Science 2024-10-28 Hayata Morita , Kohei Shintani , Chenyang Yuan , Frank Permenter

Aerodynamic shape optimization has many industrial applications. Existing methods, however, are so computationally demanding that typical engineering practices are to either simply try a limited number of hand-designed shapes or restrict…

Computational Engineering, Finance, and Science · Computer Science 2018-02-13 Pierre Baqué , Edoardo Remelli , François Fleuret , Pascal Fua

An Interactive Genetic Algorithm is proposed to progressively sketch the desired side-view of a car profile. It adopts a Fourier decomposition of a 2D profile as the genotype, and proposes a cross-over mechanism. In addition, a formula…

Neural and Evolutionary Computing · Computer Science 2013-03-22 François Cluzel , Bernard Yannou , Markus Dihlmann

We propose a data-driven 3D shape design method that can learn a generative model from a corpus of existing designs, and use this model to produce a wide range of new designs. The approach learns an encoding of the samples in the training…

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