Experienced users can directly access the commands via the panel, which indicates warnings in any scenario. This guidance is provided via a panel through which the user can access integrated help for additional information if needed as they work through the steps. As the user works through the process, the simulation setup is continually monitored to provide feedback regarding any missing items or any specific warnings the user should be mindful of. Setting up a simulation can be complicated and tedious, especially for new users, so Fluid Dynamics Engineer includes an intuitive User Assistant that guides the user through the steps required to set up a simulation.Įach step, or action, is clearly presented with a choice of commands that can be performed to complete the step. Unique engineering collaboration empowered by the 3DEXPERIENCE platform allows design engineers to create projects, brainstorm on design ideas with their team, and review design and simulation data easily to make informed decisions. For example, there is direct associativity with SOLIDWORKS® data saved on the platform, so any changes in the design are easily updated in the simulation and the results are reflected in the design.Īdditionally, the cloud environment leverages cloud resources to solve large problems more quickly than what would be possible in a desktop-only environment. The Fluid Dynamics Engineer roleīecause the role is on the 3DEXPERIENCE® platform, the user benefits from all the platform’s capabilities. Possessing this information early in the design cycle can reduce costs while improving performance and quality. Fluid Dynamics Engineer enables design engineers to carry out high-fidelity internal and external fluid flow and thermal simulations, delivering actionable information to improve a product while designing it.Īccess to fast, accurate fluid flow solutions allows a design team to evaluate multiple design alternatives so they can create optimal flow distribution, efficient thermal management, minimal pressure losses, or whatever key flow performance their product requires. This means that design engineers need to be able to assess the fluid flow around or inside their products efficiently and accurately-exactly what the new Fluid Dynamics Engineer role delivers. For many industries, design is all about maximizing efficient fluid flow for cooling or processing, for others it’s about resisting and controlling the forces generated by the flow. The earlier you can understand these effects, the better you can adapt your design to either mitigate or enhance them. Our largest computation had 1.1 trillion finite-difference points and deployed 16,384 Nvidia Tesla K20X GPUs.Liquid and gas flows can have profound effects on the performance of designs. We introduce a chunked pencil decomposition with two different communication patterns to achieve good scaling on the now-decommissioned, Titan supercomputer. We pursue an MPI-OpenACC implementation in PittPack for massively parallel computations. In the second effort, we develop a massively parallel direct solver, PittPack, for the solution of the elliptic Poisson’s equation for pressure, which is the most time-consuming section of an incompressible flow algorithm. A unique feature of the binarized representation is that it makes it easy to identify the neighbors of an element, including off-branch neighbors, without explicitly storing the connectivity information. The essence of the method is a strict adherence to the bitwise representation of an octree. In the first effort, we revisit octree generation for extreme-scale problems and introduce the binarized octree generation technique for Cartesian mesh refinement around immersed geometries with deep levels of adaptation. To this end, we have undertaken two software efforts toward realizing extreme scale computing for fluid dynamics simulations. Despite a tremendous growth in raw computing power, design and implementation of parallel simulation software that can exploit the full potential of a top supercomputer remains a formidable challenge. Today, many of the top supercomputers support heterogeneous computing on central processing units and GPUs. Programmable graphics processing units (GPUs) have transformed supercomputing over the last decade.
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