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BEGIN:VEVENT
DTEND:20220203
UID:69f4829baab94
DTSTAMP:20260501T103819Z
CATEGORIES:OF_Optimization
LOCATION:Rostock Joachim-Jungius-Str. 9, Rostock, Mecklenburg-Vorpommern, 18059, DE
ORGANIZER;CN=Dr.-Ing. Johann Turnow:MAILTO:http://johann.turnow@silentdynamics.de
DESCRIPTION:[wbcr_text_snippet id="1763"]  Basic idea  The course focuses are:     	Quick setup of simulation in OpenFOAM   	Acceleration of simulation processes (script-based) with the program OpenFOAM and Python   	Application of optimization strategies DOE / DAKOTA    In addition to teaching optimization strategies using DOE / DAKOTA\, the basics for script-based initialization of simulations to increase the workflow efficiency in OpenFOAM are taught.  Content  1. Basics     	Introduction to script-based control of OpenFOAM simulations   	Configuration of automated OpenFOAM environment   	Step-by-Step Parametric Simulation Setup   	Control via Python script    2. Basic building blocks     	Existing tools for automatic setup of OpenFOAM simulations   	Overview of Features in OpenFOAM / Opensource Features in InsightCAE   	Introduction to Parametric Geometry Creation for Optimization Tasks   	Conversion of patametric geometry for meshing in OpenFOAM   	Fundamentals of optimization strategies    3. Setting up simulations     	Step-by-step setup of simulations with OpenFOAM using OpenFOAM Touls and the Open Source Framework InsightCAE   	Import and processing of parametric CAD data   	Controlled modification of CAD files   	Implementation of the simulation environment with automatic evaluation of the simulation results    4. Acceleration simulation setup     	Concept: Script-based control using Python   	Numerical setup for robust simulations and fast convergence   	Simple handling and control on computer clusters   	Tutorial: Automatic setting up &amp\; simulation &amp\; PostProcessing of a wing flow with variation of wing geometry and angle of incidence    5. Optimization strategies     	Application Design of Experiments (DoE) in OpenFOAM   	Definition of the parameter space   	Parametric geometry creation   	Implementation of automated simulations   	Evaluation of differently weighted target functions   	Coupling of OpenFOAM and Dakota   	Introduction to DAKOTA   	Application of DAKOTA to control simulation processes for optimization calculations   	Application of different optimization strategies (gradient methods\, genetic algorithms)    &nbsp\;    &nbsp\;    Upcoming Events of the course    [em-events number_of_events=5 categories=146 disable_pagination=1 style=widget]    [wbcr_text_snippet id="1766"]
URL;VALUE=URI:https://www.foamacademy.com/events/event/openfoam-optimization
SUMMARY:OpenFOAM Optimization
DTSTART:20220203
RDATE:20220204T000000Z
RDATE:20220325T000000Z
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