Advancing understanding of indoor conditions using artificial intelligence methods

Physics of Fluids, Journal Year: 2025, Volume and Issue: 37(1)

Published: Jan. 1, 2025

This study presents a novel methodology for optimizing probe placement in indoor air-conditioned environments by integrating computational fluid dynamics simulations with artificial intelligence techniques an unsupervised learning framework. The “Reduce Uncertainty and Increase Confidence” algorithm identified spatially distinct thermal velocity clusters based on temperature magnitude distributions. Optimization of positions within these clusters, guided sequential least squares programing, resulted effective strategy to minimize redundancy while maximizing spatial coverage. highlights the interplay between temperature, relative humidity, velocity, turbulence intensity, revealing critical insights into airflow behavior its implications occupant comfort. findings presented underscore potential targeted provide robust framework advanced climate control.

Language: Английский

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On particle dispersion statistics using unsupervised learning and Gaussian mixture models

Physics of Fluids, Journal Year: 2024, Volume and Issue: 36(9)

Published: Sept. 1, 2024

Understanding the dispersion of particles in enclosed spaces is crucial for controlling spread infectious diseases. This study introduces an innovative approach that combines unsupervised learning algorithm with a Gaussian mixture model to analyze behavior saliva droplets emitted from coughing individual. The effectively clusters data, while captures distribution these clusters, revealing underlying sub-populations and variations particle dispersion. Using computational fluid dynamics simulation this integrated method offers robust, data-driven perspective on dynamics, unveiling intricate patterns probabilistic distributions previously unattainable. combined significantly enhances accuracy interpretability predictions, providing valuable insights public health strategies prevent virus transmission indoor environments. practical implications are profound, as it demonstrates potential advanced techniques addressing complex biomedical engineering challenges underscores importance coupling sophisticated algorithms statistical models comprehensive data analysis. impact findings significant, highlighting relevance research real-world applications.

Language: Английский

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A Computational Methodology for Assessing Wind Potential

Energies, Journal Year: 2024, Volume and Issue: 17(6), P. 1385 - 1385

Published: March 13, 2024

This paper introduces an innovative and eco-friendly computational methodology to assess the wind potential of a location with aid high-resolution simulations mesoscale numerical weather prediction model (WRF), coupled statistical “10% sampling condition”. The proposed is tested for complex terrain on Greek island Crete, where moderate strong winds prevail most year. results are promising, indicating that this method has great studying assessing areas interest. Adverse effects challenges associated energy production may be mitigated methods such as one. Mitigating should constitute main focus priority in research concerning production.

Language: Английский

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Risk Assessment of COVID-19 Transmission on Cruise Ships Using Fuzzy Rules

IFIP advances in information and communication technology, Journal Year: 2024, Volume and Issue: unknown, P. 336 - 348

Published: Jan. 1, 2024

Language: Английский

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