All Stories

  1. DNS-Calibrated Physics-Informed Neural Networks with Learnable Constants for Reynolds Number Extrapolation in Turbulent Channel Flows
  2. Prediction of neutral gas pressure in Wendelstein 7-X: Statistical analysis and machine learning
  3. Reconstructing turbulence: A deep learning–enhanced interpolation approach
  4. Advancing Fluid Mechanics with Artificial Intelligence and Machine Learning
  5. Turbulent channel flow: A physics-informed neural network approach with embedded parameter optimization
  6. Physically Consistent Self-Diffusion Coefficient Calculation with Molecular Dynamics and Symbolic Regression
  7. Data driven prediction of the neutral gas pressure in the stellarator Wendelstein 7-X
  8. A review of deep learning for super-resolution in fluid flows
  9. Advancing super-resolution of turbulent velocity fields: An artificial intelligence approach
  10. Spatiotemporal super-resolution forecasting of high-speed turbulent flows
  11. Enhancing indoor temperature mapping: High-resolution insights through deep learning and computational fluid dynamics
  12. Comparison of super-resolution deep learning models for flow imaging
  13. Refining Flow Structures with Deep Learning and Super Resolution Methods
  14. Turbulent Micropolar Open-Channel Flow
  15. Ultra-scaled deep learning temperature reconstruction in turbulent airflow ventilation
  16. From Sparse to Dense Representations in Open Channel Flow Images with Convolutional Neural Networks
  17. Deep learning architecture for sparse and noisy turbulent flow data
  18. A deep learning super-resolution model for turbulent image upscaling and its application to shock wave–boundary layer interaction
  19. The application of data science and machine learning techniques in predicting the compressive strength of confined concrete
  20. Reassessing the transport properties of fluids: A symbolic regression approach
  21. A hybrid molecular dynamics/machine learning framework to calculate the viscosity and thermal conductivity of Ar, Kr, Xe, O and Ν
  22. Twofold Machine-Learning and Molecular Dynamics: A Computational Framework
  23. The Educational Role of Cinema in Physical Sciences
  24. Convolutional neural networks for compressible turbulent flow reconstruction
  25. Can Artificial Intelligence Accelerate Fluid Mechanics Research?
  26. Fluid Properties Extraction in Confined Nanochannels with Molecular Dynamics and Symbolic Regression Methods
  27. Impact of an inclined magnetic field on couple stress fluid flow over a stretching surface with effect of Stefan blowing, radiation and chemical reaction
  28. Adaptive thermal comfort model and active occupant behaviour in a mixed-mode apartment. A synergy to sustainability.
  29. Smoothed Particle Hydrodynamics-Based Study of 3D Confined Microflows
  30. Artificial Intelligence in Physical Sciences: Symbolic Regression Trends and Perspectives
  31. Influence of carbon nanotube suspensions on Casson fluid flow over a permeable shrinking membrane: an analytical approach
  32. Fiber-Reinforced Polymer Confined Concrete: Data-Driven Predictions of Compressive Strength Utilizing Machine Learning Techniques
  33. Thermosolutal Marangoni Convection for Hybrid Nanofluid Models: An Analytical Approach
  34. Analytical investigation of an incompressible viscous laminar Casson fluid flow past a stretching/shrinking sheet
  35. The Electrical Conductivity of Ionic Liquids: Numerical and Analytical Machine Learning Approaches
  36. Applying new methodologies in order to extrapolate new insights
  37. A combined clustering/symbolic regression framework for fluid property prediction
  38. Current Trends in Fluid Research in the Era of Artificial Intelligence: A Review
  39. Machine learning symbolic equations for diffusion with physics-based descriptions
  40. Effects of channel size, wall wettability, and electric field strength on ion removal from water in nanochannels
  41. Investigation of water desalination/purification with molecular dynamics and machine learning techniques
  42. A Water/Ion Separation Device: Theoretical and Numerical Investigation
  43. Nanoscale slip length prediction with machine learning tools
  44. An assessment of SPH simulations of sudden expansion/contraction 3-D channel flows
  45. Machine Learning Techniques for Fluid Flows at the Nanoscale
  46. Molecular Dynamics Simulations of Ion Drift in Nanochannel Water Flow
  47. Teaching cinema with machinima
  48. Molecular dynamics simulations of ion separation in nano-channel water flows using an electric field
  49. Particle-based modeling and meshless simulation of flows with Smoothed Particle Hydrodynamics
  50. Multi-parameter analysis of water flows in nanochannels
  51. Darcy-Weisbach friction factor at the nanoscale: From atomistic calculations to continuum models
  52. Friction factor in nanochannel flows
  53. Molecular dynamics simulation on flows in nano-ribbed and nano-grooved channels
  54. Fluid structure and system dynamics in nanodevices for water desalination
  55. A quasi-continuum multi-scale theory for self-diffusion and fluid ordering in nanochannel flows
  56. Fluid Flow at the Nanoscale: How Fluid Properties Deviate from the Bulk
  57. How wall properties control diffusion in grooved nanochannels: a molecular dynamics study
  58. Parameters Affecting Slip Length at the Nanoscale
  59. A novel image processing method to determine the nutritional condition of lobsters
  60. Unified description of size effects of transport properties of liquids flowing in nanochannels
  61. Surface wettability effects on flow in rough wall nanochannels
  62. Effect of wall roughness on shear viscosity and diffusion in nanochannels
  63. Effects of wall roughness on flow in nanochannels
  64. Transport properties of liquid argon in krypton nanochannels: Anisotropy and non-homogeneity introduced by the solid walls
  65. Variation of Transport Properties Along Nanochannels: A Study by Non-equilibrium Molecular Dynamics