Effects of various types of nanomaterials on PCM melting process in a thermal energy storage system for solar cooling application using CFD and MCMC methods

MA Alazwari, M Algarni, MR Safaei - International Journal of Heat and Mass …, 2022 - Elsevier
Latent heat thermal energy storage (LHTES) systems are attractive for bridging the energy
supply and demand gap. In such systems, reducing storage time is critical, especially for …

[HTML][HTML] Assessment of surrogate models for flood inundation: The physics-guided LSG model vs. state-of-the-art machine learning models

N Fraehr, QJ Wang, W Wu, R Nathan - Water Research, 2024 - Elsevier
Hydrodynamic models can accurately simulate flood inundation but are limited by their high
computational demand that scales non-linearly with model complexity, resolution, and …

Applying Bayesian Markov chain Monte Carlo (MCMC) modeling to predict the melting behavior of phase change materials

M Goodarzi, MA Elkotb, AK Alanazi, HM Abo-Dief… - Journal of Energy …, 2022 - Elsevier
A key practical application of PCM-based spherical containers is in packed bed thermal
energy storage (TES) devices utilized for air conditioning in large buildings. Proposing high …

Attribution and sensitivity analysis of runoff variation in the yellow river basin under climate change

L Chen, M Yang, X Liu, X Lu - Sustainability, 2022 - mdpi.com
The Yellow River Basin is a typical arid and semi-arid area, which is very sensitive to climate
change. In recent years, it has become the area with the greatest shortage of water …

Estimation of hydraulic conductivity in a watershed using sparse multi-source data via Gaussian process regression and Bayesian experimental design

CY Tseng, M Ghadiri, P Kumar, H Meidani - Advances in Water Resources, 2023 - Elsevier
Enhanced water management systems depend on accurate estimation of subsurface
hydraulic properties. However, geologic formations can vary significantly, so information …

[HTML][HTML] An adaptive multi-fidelity optimization framework based on co-Kriging surrogate models and stochastic sampling with application to coastal aquifer …

V Christelis, G Kopsiaftis, RG Regis… - Advances in Water …, 2023 - Elsevier
Surrogate modelling has been used successfully to alleviate the computational burden that
results from high-fidelity numerical models of seawater intrusion in simulation-optimization …

Parametric shape optimization of pin fin arrays using a multi-fidelity surrogate model based Bayesian method

S Ghosh, S Mondal, JS Kapat, A Ray - Applied Thermal Engineering, 2024 - Elsevier
The current work aims to develop a multi-fidelity Bayesian optimization methodology to
reduce computation time in CFD based design optimization of an internal cooling channel of …

Bayesian parameter inference for shallow subsurface modeling using field data and impacts on geothermal planning

MJ Kreitmair, N Makasis, K Menberg… - Data-Centric …, 2022 - cambridge.org
Understanding the subsurface is crucial in building a sustainable future, particularly for
urban centers. Importantly, the thermal effects that anthropogenic infrastructure, such as …

Multifidelity Surrogate Models for Efficient Uncertainty Propagation Analysis in Salars Systems

V Christelis, AG Hughes - Frontiers in Water, 2022 - frontiersin.org
Salars are complex hydrogeological systems where the high-density contrasts require
advanced numerical models to simulate groundwater flow and brine transport. Applying …

Effect of anthropogenic heat sources in the shallow subsurface at city-scale

MJ Kreitmair, N Makasis, A Bidarmaghz… - E3S Web of …, 2020 - e3s-conferences.org
Rapid rates of urbanisation are placing growing demands on cities for accommodation and
transportation, with increasing numbers of basements and tunnel networks being built to …