Industrial combustion systems are among the primary contributors to nitrogen oxide (NOx) emissions, posing challenges for air quality management and regulatory compliance. This study presents a computational and data-driven approach to the design and optimization of a natural gas burner employing a folded flame pattern with fuel staging. Using Computational Fluid Dynamics (CFD) simulations combined with Machine Learning (ML)-assisted predictive modeling, the burner geometry, fuel-air mixing behavior, and heat transfer dynamics were systematically optimized. A Support Vector Regression-based model was trained on CFD-generated data to guide design modifications and reduce reliance on trial-and-error experimentation. The resulting burner design achieved a 31% reduction in NOx emissions while maintaining combustion efficiency and improving flame stability. Lower peak flame temperatures contributed to reduced pollutant formation. Particle tracing analysis revealed recirculation zones that promoted optimal fuel-air mixing and heat transfer. This integrated CFD-ML framework demonstrates a scalable solution for cleaner combustion design. Future work will focus on experimental validation and the adaptability of the burner to alternative fuels such as hydrogen-rich blends and biogas, aiming to extend the applicability of this approach across diverse industrial settings.

• Klíčová slova
• CFD optimization, Combustion efficiency, Emission control, Fuel staging, Machine learning, NOx reduction,
• Publikační typ
• časopisecké články MeSH

BACKGROUND: Photosynthetic microalgae have been in the spotlight of biotechnological production (biofuels, lipids, etc), however, current barriers in mass cultivation of microalgae are limiting its successful industrialization. Therefore, a mathematical model integrating both the biological and hydrodynamical parts of the cultivation process may improve our understanding of relevant phenomena, leading to further optimization of the microalgae cultivation. RESULTS: We introduce a unified multidisciplinary simulation tool for microalgae culture systems, particularly the photobioreactors. Our approach describes changes of cell growth determined by dynamics of heterogeneous environmental conditions such as irradiation and mixing of the culture. Presented framework consists of (i) a simplified model of microalgae growth in a culture system (the advection-diffusion-reaction system within a phenomenological model of photosynthesis and photoinhibition), (ii) the fluid dynamics (Navier-Stokes equations), and (iii) the irradiance field description (Beer-Lambert law). To validate the method, a simple case study leading to hydrodynamically induced fluctuating light conditions was chosen. The integration of computational fluid dynamics (ANSYS Fluent) revealed the inner property of the system, the flashing light enhancement phenomenon, known from experiments. CONCLUSION: Our physically accurate model of microalgae culture naturally exhibits features of real system, can be applied to any geometry of microalgae mass cultivation and thus is suitable for biotechnological applications.

• Klíčová slova
• CFD, Flashing light enhancement, Mathematical modeling, Microalgae, Microalgae culture systems, Photosynthesis,
• MeSH
• biologické modely MeSH
• fotosyntéza * MeSH
• hydrodynamika * MeSH
• kultivační techniky * MeSH
• mikrořasy růst a vývoj   fyziologie   účinky záření   MeSH
• počítačová simulace MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH

Passage of nasal airflow during breathing is crucial in achieving accurate diagnosis and optimal therapy for patients with nasal disorders. Computational fluid dynamics (CFD) is the dominant method for simulating and studying airflow. The present study aimed to create a CFD nasal airflow model to determine the major routes of airflow through the nasal cavity and thus help with individualization of surgical treatment of nasal disorders. The three-dimensional nasal cavity model was based on computed tomography scans of the nasal cavity of an adult patient without nasal breathing problems. The model showed the main routes of airflow in the inferior meatus and inferior part of the common meatus, but also surprisingly in the middle meatus and in the middle part of the common nasal meatus. It indicates that the lower meatus and the lower part of the common meatus should not be the only consideration in case of surgery for nasal obstruction in our patient. CFD surgical planning could enable individualized precise surgical treatment of nasal disorders. It could be beneficial mainly in challenging cases such as patients with persistent nasal obstruction after surgery, patients with empty nose syndrome, and patients with a significant discrepancy between the clinical findings and subjective complaints.

• Klíčová slova
• 3D model, computational fluid dynamics, nasal airflow, nasal surgery, planning,
• Publikační typ
• časopisecké články MeSH