Application of artificial intelligence for prediction, optimization, and control of thermal energy storage systems
Energy storage is one of the core concepts demonstrated incredibly remarkable
effectiveness in various energy systems. Energy storage systems are vital for maximizing the …
effectiveness in various energy systems. Energy storage systems are vital for maximizing the …
Leveraging machine learning in porous media
The emergence of artificial intelligence (AI) and, more particularly, machine learning (ML),
has had a significant impact on engineering and the fundamental sciences, resulting in …
has had a significant impact on engineering and the fundamental sciences, resulting in …
Composing partial differential equations with physics-aware neural networks
We introduce a compositional physics-aware FInite volume Neural Network (FINN) for
learning spatiotemporal advection-diffusion processes. FINN implements a new way of …
learning spatiotemporal advection-diffusion processes. FINN implements a new way of …
The deep arbitrary polynomial chaos neural network or how Deep Artificial Neural Networks could benefit from data-driven homogeneous chaos theory
Abstract Artificial Intelligence and Machine learning have been widely used in various fields
of mathematical computing, physical modeling, computational science, communication …
of mathematical computing, physical modeling, computational science, communication …
Machine learning modeling of reversible thermochemical reactions applicable in energy storage systems
Background Heat/cooling generation through reversible thermochemical reactions provides
high potential for application in thermochemical energy storage systems. However …
high potential for application in thermochemical energy storage systems. However …
Learning groundwater contaminant diffusion‐sorption processes with a finite volume neural network
Improved understanding of complex hydrosystem processes is key to advance water
resources research. Nevertheless, the conventional way of modeling these processes …
resources research. Nevertheless, the conventional way of modeling these processes …
Leveraging machine learning in porous media
B Ebrahimpour - Journal of Materials Chemistry A, 2024 - researchportal.port.ac.uk
The emergence of artificial intelligence (AI) and, more particularly, machine learning (ML),
has had a significant impact on engineering and the fundamental sciences, resulting in …
has had a significant impact on engineering and the fundamental sciences, resulting in …
ML-SPEAK: A Theory-Guided Machine Learning Method for Studying and Predicting Conversational Turn-taking Patterns
Predicting team dynamics from personality traits remains a fundamental challenge for the
psychological sciences and team-based organizations. Understanding how team …
psychological sciences and team-based organizations. Understanding how team …
Artificial Intelligence for thermal energy storage enhancement: A Comprehensive Review
Thermal energy storage (TES) plays a pivotal role in a wide array of energy systems, offering
a highly effective means to harness renewable energy sources, trim energy consumption …
a highly effective means to harness renewable energy sources, trim energy consumption …
Recovery Algorithm of Power Metering Data Based on Collaborative Fitting
Y Xu, X Kong, Z Zhu, C Jiang, S **ao - Energies, 2022 - mdpi.com
Electric energy metering plays a crucial role in ensuring fair and equitable transactions
between grid companies and power users. With the implementation of the State Grid …
between grid companies and power users. With the implementation of the State Grid …