3 citations · 5 across the 6 of their papers we have counts for
6 papers
Transformer-Based Interfaces for Mechanical Assembly Design: A Gear Train Case Study
Mohammadmehdi Ataei, Hyunmin Cheong, Jiwon Jun +3
Generative artificial intelligence (AI), particularly transformer-based models, presents new opportunities for automating and augmenting engineering design workflows. However, effe…
Optimal Design of Vehicle Dynamics Using Gradient-Based, Mixed-Fidelity Multidisciplinary Optimization
Hyunmin Cheong, Mehran Ebrahimi, Hesam Salehipour +2
In automotive engineering, designing for optimal vehicle dynamics is challenging due to the complexities involved in analysing the behaviour of a multibody system. Typically, a sim…
Elicitron: An LLM Agent-Based Simulation Framework for Design Requirements Elicitation
Mohammadmehdi Ataei, Hyunmin Cheong, Daniele Grandi +3
Requirements elicitation, a critical, yet time-consuming and challenging step in product development, often fails to capture the full spectrum of user needs. This may lead to produ…
Advancing Fluid-Based Thermal Management Systems Design: Leveraging Graph Neural Networks for Graph Regression and Efficient Enumeration Reduction
Saeid Bayat, Nastaran Shahmansouri, Satya RT Peddada +3
In this research, we developed a graph-based framework to represent various aspects of optimal thermal management system design, with the aim of rapidly and efficiently identifying…
Extracting Design Knowledge from Optimization Data: Enhancing Engineering Design in Fluid Based Thermal Management Systems
Saeid Bayat, Nastaran Shahmansouri, Satya RT Peddada +3
As mechanical systems become more complex and technological advances accelerate, the traditional reliance on heritage designs for engineering endeavors is being diminished in its e…
Multi-split configuration design for fluid-based thermal management systems
Saeid Bayat, Nastaran Shahmansouri, Satya RT Peddada +3
High power density systems require efficient cooling to maintain their thermal performance. Despite this, as systems get larger and more complex, human practice and insight may not…