
Ragul Devrajan
Fähigkeiten und Kenntnisse
Werdegang
Berufserfahrung von Ragul Devrajan
Extended Master Thesis workflow to enable the creation of Boundary Representation (B-rep) of solid Finite Element Method (FEM) models. Tested different algorithms to identify features of solids, testing various sampling methods on identified features to convert available solid FEM representations into boundary representations using B-splines. Developed workflows to map stress, strain, and history variables from LS-DYNA FEM simulations to Isogeometric Analysis (IGA) models to evaluate mapping techniques.
- 2 Jahre und 8 Monate, Aug. 2023 - März 2026
Studentische Hilfskraft
Institut für Umformtechnik (IFU), Universität Stuttgart
Developed an optimization methodology for embossing patterns in crash-critical areas using LS-DYNA. Automated the structural optimization process using Python scripting and the ENVYO mapping tool. Configured and executed sheet metal forming simulations utilizing Dynaform and LS-DYNA, automating meshed tool surface generation via custom scripting and parameterized CAD models. Helped with the setting up and running of various experiments to gather data.
Topic: Novel Geometry Reconstruction Framework for FEM to Isogeometric Analysis Conversion. Implemented a Python-based workflow for automated conversion of FEM meshes into IGA patch representations. Tested sampling methods to achieve an optimal sampling of the mesh for creating accurate B-spline surfaces. Developed methods to reconstruct and optimize IGA patches. Conducted comparative validation studies in LS-DYNA to benchmark the framework against models generated on ANSA.
Evaluated methodologies for converting FEM meshes into IGA representations, researching commercial applications and real-world implementations. Created representative benchmark models in LS-DYNA to directly compare IGA and FEM approaches. Executed FEM to IGA model conversions using ANSA, performing specialized geometry creation and cleanup suitable for IGA frameworks. Analyzed key performance indicators of converted simulations to verify accuracy utilizing LS-PrePost and customized Python scripts.
- 1 Jahr und 10 Monate, Apr. 2023 - Jan. 2025
Studentische Hilfskraft
Institute of Structural Mechanics and Dynamics in Aerospace Engineering
Implemented finite element and model order reduction routines utilizing Python and MATLAB. Programmed analytical solutions in MATLAB to resolve complex engineering problems. Assisted in the creation and optimization of FEM workflows using FEniCS.
Carried out structural (FEM) and Computational Fluid Dynamics (CFD) analyses utilizing LS-DYNA and Siemens NX. Optimized the kinematics of complex mechanical systems utilizing Siemens NX Motion. Developed supportive software tools and automated workflows for Siemens NX using Python, with a specific focus on NXOpen integrations. Conducted advanced process data analysis utilizing Python scripts to strategically identify optimization opportunities.
Ausbildung von Ragul Devrajan
- Bis heute 4 Jahre, seit Okt. 2022
Computational Mechanics of Materials and Structures
Universität Stuttgart
Sprachen
Deutsch
A1-A2 (Grundkenntnisse)
Englisch
C1 (Fließend)
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