A New Approach for Predicting the Pressure Drop in Various Types of Metal Foams Using a Combination of CFD and Machine Learning Regression Models

Jafarizadeh, Azadeh; Ahmadzadeh, MohammadAli; Mahmoudzadeh, Sajad; Panjepour, Masoud

doi:10.1007/s11242-022-01895-0

Cited by 4 publications

(1 citation statement)

References 56 publications

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“…Hybrid approaches combining CFD and ML techniques have gained significant attention recently, especially in fluid dynamics and engineering [94,95]. These approaches leverage the strengths of both CFD and ML to enhance the accuracy, efficiency, and robustness of simulations and extract valuable insights from complex fluid flow problems [96,97].…”

Section: Future Research Directions 111 Hybrid Cfd and Machine Learni...mentioning

confidence: 99%

Modeling Environmental Conditions in Poultry Production: Computational Fluid Dynamics Approach

Küçüktopçu,

Cemek,

Simsek

2024

Animals

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In recent years, computational fluid dynamics (CFD) has become increasingly important and has proven to be an effective method for assessing environmental conditions in poultry houses. CFD offers simplicity, efficiency, and rapidity in assessing and optimizing poultry house environments, thereby fueling greater interest in its application. This article aims to facilitate researchers in their search for relevant CFD studies in poultry housing environmental conditions by providing an in-depth review of the latest advancements in this field. It has been found that CFD has been widely employed to study and analyze various aspects of poultry house ventilation and air quality under the following five main headings: inlet and fan configuration, ventilation system design, air temperature–humidity distribution, airflow distribution, and particle matter and gas emission. The most commonly used turbulence models in poultry buildings are the standard k-ε, renormalization group (RNG) k-ε, and realizable k-ε models. Additionally, this article presents key solutions with a summary and visualization of fundamental approaches employed in addressing path planning problems within the CFD process. Furthermore, potential challenges, such as data acquisition, validation, computational resource requirements, meshing, and the selection of a proper turbulence model, are discussed, and avenues for future research (the integration of machine learning, building information modeling, and feedback control systems with CFD) are explored.

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Section: Future Research Directions 111 Hybrid Cfd and Machine Learni...mentioning

confidence: 99%

Modeling Environmental Conditions in Poultry Production: Computational Fluid Dynamics Approach

Küçüktopçu,

Cemek,

Simsek

2024

Animals

View full text Add to dashboard Cite

show abstract

Fluid dynamics and erosion analysis in industrial naphtha reforming: A CFD-DPM simulation approach

Mohebi,

Najafi,

Mozaffarian

et al. 2024

Powder Technology

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Evaluating the efficiency and effectiveness of non-Newtonian fluid flow in a double-pipe heat exchanger with porous medium via numerical simulation

Yaghoubzadeh Vishkaei,

Javaherdeh

2024

Numerical Heat Transfer, Part A: Applications

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A New Approach for Predicting the Pressure Drop in Various Types of Metal Foams Using a Combination of CFD and Machine Learning Regression Models

Cited by 4 publications

References 56 publications

Modeling Environmental Conditions in Poultry Production: Computational Fluid Dynamics Approach

Modeling Environmental Conditions in Poultry Production: Computational Fluid Dynamics Approach

Fluid dynamics and erosion analysis in industrial naphtha reforming: A CFD-DPM simulation approach

Evaluating the efficiency and effectiveness of non-Newtonian fluid flow in a double-pipe heat exchanger with porous medium via numerical simulation

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