Hall-effect sensor design with physics-informed Gaussian process modeling
Magnetic field sensor devices have been widely used to track changes in magnetic flux
concentration, and the Hall sensors are promising in many engineering applications. Design …
concentration, and the Hall sensors are promising in many engineering applications. Design …
[HTML][HTML] Machine learning regression tools for erosion prediction of WC-10Co4Cr thermal spray coating
The prediction of erosion in WC-10Co4Cr thermal spray coating is predicted using
regression machine learning technique. A pot tester helped to examine the erosion rate of …
regression machine learning technique. A pot tester helped to examine the erosion rate of …
Multi-Task Learning for Design Under Uncertainty With Multi-Fidelity Partially Observed Information
The assessment of system performance and identification of failure mechanisms in complex
engineering systems often requires the use of computation-intensive finite element software …
engineering systems often requires the use of computation-intensive finite element software …
Data-Driven Control Co-Design for Indirect Liquid Cooling Plate With Microchannels for Battery Thermal Management
The demand for high-performance electric vehicles keeps increasing with the booming
electric vehicles market. Thus, battery cooling is significant in enabling the battery to work …
electric vehicles market. Thus, battery cooling is significant in enabling the battery to work …
Hall Effect Sensor Design Optimization With Multi-Physics Informed Gaussian Process Modeling
Magnetic field sensor devices have been widely used to track changes in magnetic flux
concentration, and the Hall sensors are promising in many engineering applications. Design …
concentration, and the Hall sensors are promising in many engineering applications. Design …
Multi-Task Multi-Fidelity Machine Learning for Reliability-Based Design With Partially Observed Information
In complex engineering systems, assessing system performance and underlying failure
mechanisms with respect to uncertain variables requires repeated testing, which is often …
mechanisms with respect to uncertain variables requires repeated testing, which is often …
Hierarchical surrogate modeling with multiple order partially observed information
Understanding the input and output relationship of a complex engineering system is an
essential task that attracts widespread interests in engineering design fields. To investigate …
essential task that attracts widespread interests in engineering design fields. To investigate …
Control Co-Design of Battery Packs With Immersion Cooling
To efficiently increase the energy density of the battery pack, cell-to-pack has become a
widely used packing technology for electric vehicles. Among different cooling methods …
widely used packing technology for electric vehicles. Among different cooling methods …
Physics-constrained machine learning for reliability-based design optimization
Summary & ConclusionsTo aid and improve the reliability of product designs, repeated
safety tests are required to find out the safety performance of the product with respect to …
safety tests are required to find out the safety performance of the product with respect to …
Reliability-Based Optimization of Offshore Salt Caverns for CO2 Abatement
In recent years, projects have been proposed to utilize salt caverns as a storage method for
supercritical CO2 (s-CO2) and have been carried out around the world, which can effectively …
supercritical CO2 (s-CO2) and have been carried out around the world, which can effectively …