Unveiling latent chemical mechanisms: Hybrid modeling for estimating spatiotemporally varying parameters in moving boundary problems

S Pahari, P Shah, J Sang-Il Kwon - Industrial & Engineering …, 2024 - ACS Publications
Hybrid modeling has gained substantial recognition due to its capacity to seamlessly
integrate machine learning methodologies while preserving the fundamental physical …

A multiphysics model for predicting spatiotemporal temperature profiles in microwave-heated carbon capture processes

RP Bhavsar, B Bhadriraju, GA Lee, S Nagpal… - Chemical Engineering …, 2024 - Elsevier
Due to alarming rise in atmospheric CO 2 ppm levels, the direct air capture process has
been engineered to capture low concentrations of CO 2 directly from the atmosphere using …

Lignin structure dynamics: Advanced real-time molecular sensing strategies

CH Lee, J Kim, J Ryu, W Won, CG Yoo… - Chemical Engineering …, 2024 - Elsevier
Lignin, with its abundant and high energy density, offers potential for sustainable biofuels
and chemicals. However, current research faces two primary challenges: limited …

Commodity intelligent pricing and replenishment decision based on dynamic programming model based on sliding window and XGBoost regression algorithm

Y Huang, L Wu, H Wang, Z Li - Proceedings of the 2023 5th International …, 2023 - dl.acm.org
Smart pricing and replenishment decisions for goods are very important decisions for
retailers and manufacturers in their operations. These decisions have a direct impact on the …

Comparison and analysis of various machine learning algorithms in predicting the excitation current of constant speed AC motor

M Mo, F Tan, H Ding, N Ge - Applied and Computational Engineering, 2024 - ewadirect.com
With the wide application of motor in industry, transportation, home appliances and other
fields, the performance requirements of motor are getting higher and higher, in which the …