Machine learning driven interpretation of computational fluid dynamics simulations to develop student intuition

2020 ◽  
Vol 28 (3) ◽  
pp. 490-496
Author(s):  
Nathan J. Patterson
Keyword(s):  
Machine Learning ◽  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Computational Fluid Dynamics Simulations ◽  
Dynamics Simulations

scholarly journals Aerodynamic analysis of uphill drafting in cycling

2021 ◽  
Vol 24 (1) ◽  
Author(s):  
T. van Druenen ◽  
B. Blocken
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
High Speed ◽  
Scientific Literature ◽  
Sensitivity Analyses ◽  
Air Resistance ◽  
Wind Tunnel Measurements ◽  
Aerodynamic Effect ◽  
Computational Fluid Dynamics Simulations ◽  
Dynamics Simulations

AbstractSome teams aiming for victory in a mountain stage in cycling take control in the uphill sections of the stage. While drafting, the team imposes a high speed at the front of the peloton defending their team leader from opponent’s attacks. Drafting is a well-known strategy on flat or descending sections and has been studied before in this context. However, there are no systematic and extensive studies in the scientific literature on the aerodynamic effect of uphill drafting. Some studies even suggested that for gradients above 7.2% the speeds drop to 17 km/h and the air resistance can be neglected. In this paper, uphill drafting is analyzed and quantified by means of drag reductions and power reductions obtained by computational fluid dynamics simulations validated with wind tunnel measurements. It is shown that even for gradients above 7.2%, drafting can yield substantial benefits. Drafting allows cyclists to save over 7% of power on a slope of 7.5% at a speed of 6 m/s. At a speed of 8 m/s, this reduction can exceed 16%. Sensitivity analyses indicate that significant power savings can be achieved, also with varying bicycle, cyclist, road and environmental characteristics.

scholarly journals Evaluation of Active Heat Sinks Design under Forced Convection—Effect of Geometric and Boundary Parameters

Materials ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2041
Author(s):  
Eva C. Silva ◽  
Álvaro M. Sampaio ◽  
António J. Pontes
Keyword(s):  
Fluid Dynamics ◽  
Computational Fluid Dynamics ◽  
Additive Manufacturing ◽  
Pressure Drop ◽  
Forced Convection ◽  
Thermal Performance ◽  
Heat Sinks ◽  
Trapezoidal Shape ◽  
Computational Fluid Dynamics Simulations ◽  
Dynamics Simulations

This study shows the performance of heat sinks (HS) with different designs under forced convection, varying geometric and boundary parameters, via computational fluid dynamics simulations. Initially, a complete and detailed analysis of the thermal performance of various conventional HS designs was taken. Afterwards, HS designs were modified following some additive manufacturing approaches. The HS performance was compared by measuring their temperatures and pressure drop after 15 s. Smaller diameters/thicknesses and larger fins/pins spacing provided better results. For fins HS, the use of radial fins, with an inverted trapezoidal shape and with larger holes was advantageous. Regarding pins HS, the best option contemplated circular pins in combination with frontal holes in their structure. Additionally, lattice HS, only possible to be produced by additive manufacturing, was also studied. Lower temperatures were obtained with a hexagon unit cell. Lastly, a comparison between the best HS in each category showed a lower thermal resistance for lattice HS. Despite the increase of at least 38% in pressure drop, a consequence of its frontal area, the temperature was 26% and 56% lower when compared to conventional pins and fins HS, respectively, and 9% and 28% lower when compared to the best pins and best fins of this study.

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