Driven by data or derived through physics? a review of hybrid physics guided machine learning techniques with cyber-physical system (cps) focus

R Rai, CK Sahu - IEEe Access, 2020 - ieeexplore.ieee.org
A multitude of cyber-physical system (CPS) applications, including design, control,
diagnosis, prognostics, and a host of other problems, are predicated on the assumption of …

A review on model-based diagnosis methodologies for PEMFCs

R Petrone, Z Zheng, D Hissel, MC Péra… - International Journal of …, 2013 - Elsevier
The proton exchange membrane fuel cell systems (PEMFC) s are interesting devices for
energy conversion. Recent researches are aimed at developing new monitoring and …

Integration of machine learning and first principles models

L Rajulapati, S Chinta, B Shyamala… - AIChE …, 2022 - Wiley Online Library
Abstract Model building and parameter estimation are traditional concepts widely used in
chemical, biological, metallurgical, and manufacturing industries. Early modeling …

Supervised deep belief network for quality prediction in industrial processes

X Yuan, Y Gu, Y Wang - IEEE Transactions on Instrumentation …, 2020 - ieeexplore.ieee.org
Deep belief network (DBN) has recently been applied for soft sensor modeling with its
excellent feature representation capacity. However, DBN cannot guarantee that the …

Formulation graphs for mapping structure-composition of battery electrolytes to device performance

V Sharma, M Giammona, D Zubarev… - Journal of Chemical …, 2023 - ACS Publications
Advanced computational methods are being actively sought to address the challenges
associated with the discovery and development of new combinatorial materials, such as …

A knowledge-and-data-driven modeling approach for simulating plant growth: A case study on tomato growth

XR Fan, MZ Kang, E Heuvelink, P De Reffye, BG Hu - Ecological Modelling, 2015 - Elsevier
This paper proposes a novel knowledge-and-data-driven modeling (KDDM) approach for
simulating plant growth that consists of two submodels. One submodel is derived from all …

Crack detection in Mindlin-Reissner plates under dynamic loads based on fusion of data and models

K Agathos, K Tatsis, S Nicoli, SPA Bordas… - Computers & Structures, 2021 - Elsevier
In this paper, system identification is coupled with optimization-based damage detection to
provide accurate localization of cracks in thin plates, under dynamic loading. Detection …

A static moving boundary modelling approach for simulation of indirect evaporative free cooling systems

M Rampazzo, M Lionello, A Beghi, E Sisti… - Applied Energy, 2019 - Elsevier
Abstract Evaporative Cooling and Free-Cooling technologies have gained a growing
interest in air-conditioning systems and they are suitable in different air conditioning …

Modelling and control of a free cooling system for data centers

A Beghi, L Cecchinato, G Dalla Mana, M Lionello… - Energy Procedia, 2017 - Elsevier
Data centers are facilities hosting a large number of servers dedicated to data storage and
management. In recent years, their power consumption has increased significantly due to …

[HTML][HTML] Automated Data–Driven Model Extraction and Validation of Inverter Dynamics with Grid Support Function

S Subedi, B Poudel, P Aslami, R Fourney… - e-Prime-Advances in …, 2023 - Elsevier
This research focuses on the evolving dynamics of the power grid, where traditional
synchronous generators are being replaced by non-synchronous power electronic converter …