Download presentations from our sponsors and partners from past users conferences.
Faster FLOW-3D Time-to-Solution with HPC Cloud or on Premise
Rod McAllister, Penguin Computing
This presentation describes Penguin Computing On Demand (POD), Penguin Computing’s on-demand HPC cloud. Penguin Computing has been working with Flow Science for several years to assure the best performance and user experience for running FLOW-3D on POD. With Penguin’s remote 3D desktop solution Scyld Cloud Workstation attached to the cluster fabric, customers can use the FLOW-3D GUI, run simulations on a true HPC cluster, and process the results without downloading large output files and with no specialized HPC skills. Penguin Computing supplies this solution as a cloud or on-premise resource.
Optimize your flow using FLOW-3D and CAESES
Stefan Harries and Ceyhan Erdem, Friendship Systems
Adwaith Gupta, Melissa Carter, Flow Science
FLOW-3D, being a fast and accurate flow solver, can investigate and rank large sets of variants to more easily and quickly identify performance improvements for both products and processes. CAESES, being a flexible PIDO (Process Integration and Design Optimization) environment, can be readily coupled to FLOW-3D for automated optimization campaigns. This presentation will cover the combined solution of FLOW-3D and CAESES, illustrating the benefits for the simulation engineer along with various examples. Two levels of optimization will be addressed: At the first level, CAESES “only” changes settings and parameters that are already present within the setup of a FLOW-3Dsimulation, e.g., inlet velocity, model parameters, etc. At the second level, CAESES also provides the robust generation of variable geometry, targeting the development of optimal shapes. The examples shown will be taken from two interesting fields of application, namely from the metal casting industry and from microfluidics.
Coupling FLOW-3D to CAESES for Shape Optimization — Methods and Examples
Mike Saroch and Ceyhan Erdem, FRIENDSHIP SYSTEMS; Adwaith Gupta and Melissa Carter, Flow Science)
Over the last 2 decades, there has been a trend for CFD to be used earlier within the product development process as an indispensable tool for simulation-driven design. More recently, CFD has not only been used earlier, but in a much bigger way, in order to conduct systematic design studies as well as formal optimizations. This has resulted in better products, designed faster, and with tremendous cost savings. In order to conduct systematic design and optimization studies, automated workflows are required. Coupling FLOW-3D to CAESES establishes such a workflow. In such studies, parameters are varied which can include those describing geometry, operating conditions or physics settings, or even CFD solver and process settings. In most cases, variations in product geometry are studied in order to determine their effects on various design objectives. CAESES includes its own specialized CAD kernel specifically geared for simulation-ready geometry creation and variation. These geometries can be built from scratch in CAESES or based on imported models. CAESES also includes a broad range of optimization techniques to drive the automated studies. Examples will be given that illustrate the automation with FLOW-3D and CAESES. These examples will draw on applications from the fields of metal casting and micro-fluidics.
Automated optimization using CAESES and FLOW-3D
Stefan Harries, Ceyhan Erdem and Claus Abt, FRIENDSHIP SYSTEMS AG
The complexity and difficulty of pre-processing CAD geometry for flow simulation has driven the development of CAESES over the last decade. The built-in parametric CAD kernel is geared towards watertight simulation-ready geometries that can easily be varied, be it STL data, CAD models imported from other CAD programs, or geometry defined in CAESES from the ground up. Running FLOW-3D from within CAESES for assessing the geometry is implemented as a push button solution. Control files are simply dragged and dropped into CAESES’s integration interface – and once CAD and CFD are linked, formal optimization is the next natural step. Every thinkable optimization technique is made available through CAESES. That reaches from simple systematic variation techniques via evolutionary strategies to the application of sophisticated surrogate models. These algorithms can also readily be applied to other FLOW-3D input variables in order to achieve single or multiple objectives. Examples will be given that highlight the strength of optimization techniques for finding the ideal configuration for the CFD setup, including geometrical changes, in order to improve the quality of casting processes and hydraulics applications.