mlsanityData to 7 Oct 2026

A Closed-Loop Multi-Agent Framework for Aerodynamics-Aware Automotive Styling Design

arXiv 2508.03370 ↗First posted 5 Aug 2025cs.CE cs.MAcited by 1

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Abstract (arXiv)

The core challenge in automotive exterior design is balancing subjective aesthetics with objective aerodynamic performance while dramatically accelerating the development cycle. To address this, we propose a novel, LLM-driven multi-agent framework that automates the end-to-end workflow from ambiguous requirements to 3D concept model performance validation. The workflow is structured in two stages: conceptual generation and performance validation. In the first stage, agents collaborate to interpret fuzzy design requirements, generate concept sketches, and produce photorealistic renderings using diffusion models. In the second stage, the renderings are converted to 3D point clouds, where a Drag Prediction Agent, built upon a lightweight surrogate model, provides near-instantaneous predictions of the drag coefficient and pressure fields, replacing time-consuming CFD simulations. The primary contribution of this work is the seamless integration of creative generation with a rapid engineering validation loop within a unified, automated system, which provides a new paradigm for efficiently balancing creative exploration with engineering constraints in the earliest stages of design.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). First posted on arXiv 5 Aug 2025.

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  3. 2026TurboAgent: An LLM-Driven Autonomous Multi-Agent Framework for Turbomachinery Aerodynamic Design
  4. 2026From Perception to Autonomous Computational Modeling: A Multi-Agent Approach
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  6. 2026VFEAgent: A Multimodal Agent Framework for End-to-End Automated Finite Element Analysis
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  8. 2025Toward Autonomous Engineering Design: A Knowledge-Guided Multi-Agent Framework