FlowLab is a computational fluid dynamics (CFD) software package designed to help teach fluid mechanics and ;transport phenomena. Based on ready-to-use exercises, FlowLab eliminates the long learning curve associated ;with general fluid flow modeling packages, making it easy to deploy as part of the undergraduate or masters-level ;curriculum. With FlowLab, you can:;Reinforce basic concepts of fluid mechanics and heat/mass transfer using computer simulation ;Use computing exercises to augment and complement existing laboratory-based curriculum ;Expand the learning experience with real-world applications of fluid flow and heat/mass transfer ;Expose students to CFD and CFD concepts - an increasingly important skill in the job market ;FlowLab’s exercises are easy to customize and fit into your existing curriculum, even if you are not an expert in CFD.

References in zbMATH (referenced in 22 articles )

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  1. Frolkovič, Peter; Mikula, Karol; Hahn, Jooyoung; Martin, Dirk; Basara, Branislav: Flux balanced approximation with least-squares gradient for diffusion equation on polyhedral mesh (2021)
  2. Galtsev, Oleg Vladimirovich: The evolution of the free boundary separating two immiscible viscous fluids in an elastic porous medium (2020)
  3. Kalita, Paragmoni; Sarmah, Sidharth: A new diffusion-regulated flux splitting method for compressible flows (2019)
  4. Zhou, Shuwen; Wang, Yu: Analysis and optimization of a cyclone integrated with a cartridge filter in a hazardous materials collection truck (2019)
  5. Ambrosi, Davide (ed.); Liu, Chun (ed.); Röger, Matthias (ed.); Stevens, Angela (ed.): The mathematics of mechanobiology and cell signaling. Abstracts from the workshop held February 25--March 3, 2018 (2018)
  6. Kanatchikov, Igor V.: Schrödinger wave functional in quantum Yang-Mills theory from precanonical quantization (2018)
  7. Tu, Jiyuan; Yeoh, Guan Heng; Liu, Chaoqun: Computational fluid dynamics. A practical approach (2018)
  8. Arnold, Anton (ed.); Carlen, Eric A. (ed.); Desvillettes, Laurent (ed.): Classical and quantum mechanical models of many-particle systems. Abstracts from the workshop held December 3--9, 2017 (2017)
  9. Adimurthi, A.; Aggarwal, Aekta; Veerappa Gowda, G. D.: Godunov-type numerical methods for a model of granular flow (2016)
  10. Kalita, Paragmoni; Dass, Anoop Kumar; Sarma, Abhishek: Effects of numerical diffusion on the computation of viscous supersonic flow over a flat plate (2016)
  11. Kalita, P.; Dass, A. K.: A diffusion-regulated scheme for the compressible Navier-Stokes equations using a boundary-layer sensor (2016)
  12. Prabhu, L.; Srinivas, J.: Performance evaluation of two meta-heuristic schemes in airfoil design (2016)
  13. Constantine, P. G.; Emory, M.; Larsson, J.; Iaccarino, G.: Exploiting active subspaces to quantify uncertainty in the numerical simulation of the hyshot II scramjet (2015)
  14. Wolosz, Krzysztof J.; Wernik, Jacek: Three-dimensional flow optimization of a nozzle with a continuous adjoint (2015)
  15. Wołosz, Krzysztof J.; Wernik, Jacek: ICEEM07: three-dimensional flow optimization of a pneumatic pulsator nozzle with a continuous adjoint (2015)
  16. Martins, Nuno M. C.; Carriço, Nelson J. G.; Ramos, Helena M.; Covas, Dídia I. C.: Velocity-distribution in pressurized pipe flow using CFD: accuracy and mesh analysis (2014)
  17. Tu, Yijuan; Yeoh, Guan Heng; Liu, Chaoqun: Computational fluid dynamics. A practical approach. (2013)
  18. Garzón-Alvarado, Diego Alexander; Galeano, C. H.; Mantilla, J. M.: Computational examples of reaction-convection-diffusion equations solution under the influence of fluid flow: first example (2012)
  19. Del Coz Díaz, J. J.; García Nieto, P. J.; Castro-Fresno, D.; Menéndez Rodríguez, P.: Steady state numerical simulation of the particle collection efficiency of a new urban sustainable gravity settler using design of experiments by FVM (2011)
  20. Zheng, Chao-Rong; Zhang, Yao-Chun; Zhang, Wen-Yuan: Large eddy simulation of separation control over a backward-facing step flow by suction (2011)

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