Hanyang University
Hanyang University
We develop a robust, reliability-based design method to maximize the reliability and robustness of an engineering system while achieving its optimal mechanical performance under uncertain inputs. See details here.
We develop a multifidelity method to effectively assessing failure levels. This allows for effectively maintenance planning and risk-avoidance design for a complex system. See details here.
We develop a multi-body dynamic model for an axial flux motor to predict fault modes in vibration and structural behavior.
We predict occupant injury kinematics via vehicle crash simulations with a human body model (e.g. Global Human Body Models Consortium model). Our study aims to develop an optimally reliable and safe restraint design that account for uncertainties in occupant posture, body physique, and various crash scenarios.
We develop a GPU-accelerating combustion model using MFiX-EXA for an exa-scale biomass boiler application in a power plant. With this model, we optimize the operational design to maximize the efficiency and robustness of the combustion process.
We develop an AI-based prognostics algorithm to reliably predict anomalies in engineering systems, including electric propulsion systems used in advanced air mobility.
We are always seeking PhD candidates with a strong passion for uncertainty quantification and innovative design.
RED LAB
Chung Mong-Koo Automotive Research Center, 222 Wangsimni-ro, Seongdong-gu Seoul Seoul 04763
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