A unique physics-aided deep learning model for predicting viscosity of nanofluids-Reference-Cited by-同舟云学术

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A unique physics-aided deep learning model for predicting viscosity of nanofluids

Published:2022-09-13 Issue:3 Volume:24 Page:167-181
ISSN:1550-2287
Container-title:International Journal for Computational Methods in Engineering Science and Mechanics
language:en
Short-container-title:International Journal for Computational Methods in Engineering Science and Mechanics

Author:

Bhaumik Bivas¹,Chaturvedi Shivam²,Changdar Satyasaran³^ORCID,De Soumen¹^ORCID

Affiliation:

1. Department of Applied Mathematics, University of Calcutta, Kolkata, India

2. Chemical Engineering Department, Malaviya National Institute of Technology, Jaipur, India

3. Department of Computer Science, University of Copenhagen, Copenhagen, Denmark

Publisher

Informa UK Limited

Subject

Computational Mathematics,Computational Mechanics

Link

https://www.tandfonline.com/doi/pdf/10.1080/15502287.2022.2120441

Reference50 articles.

1. Theory-Guided Data Science: A New Paradigm for Scientific Discovery from Data

2. Quantitative model validation techniques: New insights

3. Integration of model verification, validation, and calibration for uncertainty quantification in engineering systems

4. Uncertainty Quantification for Additive Manufacturing Process Improvement: Recent Advances

5. Computationally efficient multiscale modeling for probabilistic analysis of CFRP composites with micro-scale spatial randomness

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3. Peristaltic transport of Sutterby nanofluid flow in an inclined tapered channel with an artificial neural network model and biomedical engineering application;Scientific Reports;2024-01-04

4. Modelling the thermal conductivity of nanofluids using a novel model of models approach;Journal of Thermal Analysis and Calorimetry;2023-11-06

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