[HTML][HTML] Machine learning enhanced control co-design optimization of an immersion cooled battery thermal management system
The development of lithium-ion battery technology has ensured that battery thermal
management systems are an essential component of the battery pack for next-generation …
management systems are an essential component of the battery pack for next-generation …
Multi-fidelity physics-informed convolutional neural network for heat map prediction of battery packs
The layout of battery cells in liquid-based battery thermal management systems determines
the temperature distribution within a battery pack, which, in turn, affects the safety, reliability …
the temperature distribution within a battery pack, which, in turn, affects the safety, reliability …
[HTML][HTML] Uncertainty quantification of mechanical behavior of corroded Al-Fe self-pierce riveting joints with statistical shape modeling
Due to its versatility, efficiency, and rapid cycle time, the automotive industry widely employs
Self-Piercing Riveting (SPR) as a preferred technique to join dissimilar materials. Despite its …
Self-Piercing Riveting (SPR) as a preferred technique to join dissimilar materials. Despite its …
Uncertainty quantification of additively manufactured architected cellular materials for energy absorption applications
With advances in additive manufacturing (AM), the technology has significantly increased
the applications in a wide range of industrial sectors. For example, stereolithography (SLA) …
the applications in a wide range of industrial sectors. For example, stereolithography (SLA) …
Deep Learning-Based Multifidelity Surrogate Modeling for High-Dimensional Reliability Prediction
L Shi, B Pan, W Chen, Z Wang - ASCE-ASME J …, 2024 - asmedigitalcollection.asme.org
Multifidelity surrogate modeling offers a cost-effective approach to reducing extensive
evaluations of expensive physics-based simulations for reliability prediction. However …
evaluations of expensive physics-based simulations for reliability prediction. However …
Reliability-Based Design Optimization of Additive Manufacturing for Lithium Battery Silicon Anode
With the blooming of the electric vehicle market and the advancement in the lithium-ion
battery industry, silicon anode has shown great potential for the next-generation battery …
battery industry, silicon anode has shown great potential for the next-generation battery …
[PDF][PDF] " AI-Powered Integrated Multi-Task Learning for Reliability and Performance Optimization in Design with Multi-Fidelity Data and Partial Observations
K Sheriffdeen, M Ade - 2024 - researchgate.net
In the era of complex engineering design, optimizing reliability and performance while
managing the constraints of multi-fidelity data and partial observations is a critical challenge …
managing the constraints of multi-fidelity data and partial observations is a critical challenge …
[PDF][PDF] " AI-Driven Cross-Domain Multi-Task Learning for Enhanced Reliability-Based Design with Multi-Fidelity and Partially Observed Data
K Sheriffdeen - 2024 - easychair.org
The integration of Artificial Intelligence (AI) into reliability-based design processes has
opened new avenues for optimizing complex engineering systems. This research explores …
opened new avenues for optimizing complex engineering systems. This research explores …
[引用][C] AI-Enhanced Hybrid Multi-Fidelity and Multi-Task Learning Framework for Optimized Design Under Uncertainty and Incomplete Data
K Sheriffdeen, T Adebayo - 2024
[引用][C] Adaptive AI-Driven Multi-Task Multi-Fidelity Learning for Dynamic Design Optimization with Uncertainty and Incomplete Information
K Sheriffdeen - 2024