Advanced GPU Computing

Experience the speed and precision of GPU computing in our simulations, revolutionizing the way industries handle granular materials.

Digital Twin Technology

Transform equipment monitoring and optimization with our customized software solutions, creating digital twins for enhanced operational insights.

Industry Impact

Elevate your equipment understanding with a DEM or SPH simulation, optimizing productivity and efficiency.

Revolutionizing manufacturing industries with physics based simulations

Powered by Human Intelligence 

Discover cutting-edge solutions for granular and fluid-granular material simulations. Harness the power of our advanced GPU computing and high fidelity physics methods to accelerate you digital journey.

Empowering Industries with Customized Solutions

Unlocking Innovative Possibilities in Simulation and Digital Twins

At Blaze Computing LTD, we specialize in providing consulting services for industries dealing with granular and fluid-granular materials. Our world-leading physics engine Blaze, is powered by GPU computing, offering unmatched accuracy and efficiency. 

We also create custom software solutions, enabling the creation and utilization of digital twins for various equipment with ease.

Challenging the status quo

High Fidelity Physics Based Simulations

1] SAG mill with Ore, Media and Slurry

2] Heated Screw with phase change to SPH

3] Cohesive and Dry materials mixing

4] Stirred mill - fully resolved slurry

6] Flexible Dino foot in terrain

5] Ball Mill - fully resolved slurry

7]  Coating with a fine powder

Extensive  scientific validation for over a decade

  1. Coupling SPH-DEM method for simulating the dynamic response of breakwater structures under severe free surface flow,Powder Technology, https://doi.org/10.1016/j.powtec.2024.119805
     
  2. Comparing open-source DEM frameworks for simulations of common bulk processes,Computer Physics Communications, https://doi.org/10.1016/j.cpc.2023.109066
     
  3. Precise control of discharge of spherical particles by cone valve configuration: Insert – Converging orifice, Powder Technology, https://doi.org/10.1016/j.powtec.2023.119225
     
  4. A resolved SPH-DEM coupling method for analysing the interaction of polyhedral granular materials with fluid, Ocean Engineering, https://doi.org/10.1016/j.oceaneng.2023.115938
     
  5. DEM analysis of the influence of stirrer design on die filling with forced powder feeding, Particuology, https://doi.org/10.1016/j.partic.2023.08.018
     
  6. The influence of cohesion on polyhedral shapes during mixing in a drum,
  7. Chemical Engineering Science, https://doi.org/10.1016/j.ces.2023.118499
     
  8. Investigation of granular dynamics in a continuous blender using the GPU-enhanced discrete element method, Powder Technology, https://doi.org/10.1016/j.powtec.2022.117968
     
  9. Numerical analysis of die filling with a forced feeder using GPU-enhanced discrete element methods,International Journal of Pharmaceutics, https://doi.org/10.1016/j.ijpharm.2022.121861
     
  10. A DEM study on the thermal conduction of granular material in a rotating drum using polyhedral particles on GPUs, Chemical Engineering Science, https://doi.org/10.1016/j.ces.2022.117491
     
  11. Verification of Polyhedral DEM with Laboratory Grinding Mill Experiments, KONA Powder and Particle Journal, 2022, https://doi.org/10.14356/kona.2022013
     
  12. A meshless Lagrangian particle-based porosity formulation for under-resolved generalised finite difference-DEM coupling in fluidised beds, Powder Technology, https://doi.org/10.1016/j.powtec.2021.117079
     
  13. Boundary condition enforcement for renormalised weakly compressible meshless Lagrangian methods,Engineering Analysis with Boundary Elements,https://doi.org/10.1016/j.enganabound.2021.04.024
     
  14. Modelling realistic ballast shape to study the lateral pull behaviour using GPU computing EPJ Web Conf. 249 06003 (2021), https://doi.org/10.1051/epjconf/202124906003
     
  15. The influence of faceted particle shapes on material dynamics in screw conveying, Chemical Engineering Science, https://doi.org/10.1016/j.ces.2021.116654
     
  16. Study on the effect of grain morphology on shear strength in granular materials via GPU based discrete element method simulations, Powder Technology, https://doi.org/10.1016/j.powtec.2021.04.038
     
  17. GPU-enhanced DEM analysis of flow behaviour of irregularly shaped particles in a full-scale twin screw granulator, Particuology, https://doi.org/10.1016/j.partic.2021.03.007
     
  18. Simulation of rock fracture process based on GPU-accelerated discrete element method, Powder Technology, https://doi.org/10.1016/j.powtec.2020.09.009
     
  19. DEM analysis of residence time distribution during twin screw granulation, Powder Technology, https://doi.org/10.1016/j.powtec.2020.09.049
     
  20. Analysis of parallel spatial partitioning algorithms for GPU based DEM, Computers and Geotechnics,https://doi.org/10.1016/j.compgeo.2020.103708
     
  21. The effect of particle shape on the packed bed effective thermal conductivity based on DEM with polyhedral particles on the GPU, Chemical Engineering Science, https://doi.org/10.1016/j.ces.2020.115584
     
  22. Benefits of virtual calibration for discrete element parameter estimation from bulk experiments. Granular Matter 21, 110 (2019). https://doi.org/10.1007/s10035-019-0962-y
     
  23. A cohesive fracture model for discrete element method based on polyhedral blocks, Powder Technology, https://doi.org/10.1016/j.powtec.2019.09.068
     
  24. 3D gradient corrected SPH for fully resolved particle–fluid interactions, Applied Mathematical Modelling, https://doi.org/10.1016/j.apm.2019.09.030
     
  25. Study on the particle breakage of ballast based on a GPU accelerated discrete element method, Geoscience Frontiers, https://doi.org/10.1016/j.gsf.2019.06.006
     
  26. A numerical investigation into the effect of angular particle shape on blast furnace burden topography and percolation using a GPU solved discrete element model, Chemical Engineering Science, https://doi.org/10.1016/j.ces.2019.03.077
     
  27. Industrial scale simulations of tablet coating using GPU based DEM: A validation study, Chemical Engineering Science, https://doi.org/10.1016/j.ces.2019.03.029
     
  28. The Evolution of Grinding Mill Power Models. Mining, Metallurgy & Exploration 36, 151–157 (2019). https://doi.org/10.1007/s42461-018-0037-3
     
  29. Effect of particle shape in grinding mills using a GPU based DEM code, Minerals Engineering, https://doi.org/10.1016/j.mineng.2018.09.019
     
  30. Discrete element model study into effects of particle shape on backfill response to cyclic loading behind an integral bridge abutment. Granular Matter 20, 68 (2018). https://doi.org/10.1007/s10035-018-0840-z
     
  31. Large-scale GPU based DEM modeling of mixing using irregularly shaped particles, Advanced Powder Technology, https://doi.org/10.1016/j.apt.2018.06.028
     
  32. Hopper flow of irregularly shaped particles (non-convex polyhedra): GPU-based DEM simulation and experimental validation, Chemical Engineering Science, https://doi.org/10.1016/j.ces.2018.05.011
     
  33. A study of shape non-uniformity and poly-dispersity in hopper discharge of spherical and polyhedral particle systems using the Blaze-DEM GPU code, Applied Mathematics and Computation https://doi.org/10.1016/j.amc.2017.03.037
     
  34. Blaze-DEMGPU: Modular high performance DEM framework for the GPU architecture SoftwareX, https://doi.org/10.1016/j.softx.2016.04.004
     
  35. Collision detection of convex polyhedra on the NVIDIA GPU architecture for the discrete element method, Applied Mathematics and Computation, https://doi.org/10.1016/j.amc.2014.10.013
     
  36. Development of a convex polyhedral discrete element simulation framework for NVIDIA Kepler based GPUs, Journal of Computational and Applied Mathematics, https://doi.org/10.1016/j.cam.2013.12.032
     
  37. Discrete element simulation of mill charge in 3D using the BLAZE-DEM GPU framework, Minerals Engineering, https://doi.org/10.1016/j.mineng.2015.05.010

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