Yu-Yun Lu profile photo

Yu-Yun Lu

Software Engineer, Simulation Engineer & AI Engineer

Würzburg

About

With over 11 years of experience in computational engineering, I specialize in the unique intersection of mechanical simulation, software development, and artificial intelligence. My journey began with a foundation in mechanical engineering and evolved into developing sophisticated simulation tools and AI systems that solve complex engineering challenges.

At Wölfel Engineering, I've pioneered the development of Casimir/Automotive, a comprehensive Python/TCL scripting framework that integrates with industry-leading tools like Abaqus, LS-Dyna, and HyperWorks. My work spans from finite element analysis and seating comfort engineering to cutting-edge AI development, including the Casimir AI Assistant—an agentic AI system with RAG capabilities that runs efficiently on just 6GB VRAM.

I'm passionate about bridging the gap between traditional engineering disciplines and modern AI technologies, creating tools that enhance productivity and unlock new possibilities in computational engineering. My diverse background enables me to approach problems from multiple perspectives, whether it's optimizing wind turbine simulations or fine-tuning large language models for specialized engineering applications.

Experience

Project Engineer & AI Engineer

Wölfel Beratende Ingenieure GmbH + Co. KG

Nov 2014 - Present (11+ years)Würzburg
  • Seating comfort engineering including FEA simulation, ride comfort analysis, and experimental modal analysis
  • Lead developer of Casimir/Automotive: Python/TCL scripting framework for Abaqus, LS-Dyna, HyperWorks, and Simpack integration
  • Simulation engineering for wind turbines with OpenFAST customization and optimization
  • AI development: Created Casimir AI Assistant using Llama 3.1 with agentic AI architecture and RAG implementation
  • LLM fine-tuning and optimization for engineering-specific applications running on limited hardware (6GB VRAM)

Development Engineer - Product Development

Adaptronics International GmbH

Aug 2013 - Oct 2014
  • Product development and engineering design
  • Technical analysis and prototyping
  • Collaboration with cross-functional teams on product innovation

Application Engineer - Pump Selection

KSB

Aug 2006 - Dec 2007
  • Technical consultation for pump selection and system design
  • Application engineering and customer support
  • Performance analysis and optimization recommendations

Skills & Education

Technical

FEA (Finite Element Analysis)AI & Machine LearningPythonTCLMatlabVibe Coding

Tools

AbaqusLS-DynaADAMSSimpackHyperWorksOpenFAST

Languages

Chinese (Native)English (Professional)German (Elementary)

Education

MSc Computational Engineering

Ruhr-Universität Bochum

2010 - 2013Germany

BSc Mechanical Engineering

National Taiwan University of Science and Technology

2004 - 2006Taiwan

Featured Projects

Casimir AI Assistant

An intelligent agentic AI system designed for engineering support, featuring advanced RAG (Retrieval-Augmented Generation) capabilities and multi-modal understanding.

Llama 3.1PythonRAGLLM Fine-tuning
  • Answers complex engineering questions using domain-specific knowledge base
  • Translates natural language queries into technical commands
  • Reads and interprets error screenshots for troubleshooting
  • Escalates complex issues to human support when needed
  • Optimized to run on only 6GB VRAM, making AI accessible on standard hardware

Full Automation of Seating Comfort Simulation Pre-Processing

Automated preprocessing pipeline for seating comfort FEA simulations, streamlining the workflow from posture definition to ready-to-run finite element models.

RAMSISFEAPythonAbaqus
  • Only a posture definition file exported from RAMSIS is required
  • Automated manikin model positioning
  • Automated boundary conditions
  • Ready-to-run FE model

Automation of Aircraft Damage Simulation Post-Processing

Automated post-processing workflow for aircraft damage analysis, enabling seamless data exchange between simulation team members.

FEAPythonAutomation Scripting
  • Automated post-processing for different FE simulations
  • Outputs exchanged between team members for succeeding simulation

Design Load Case Simulations with OpenFAST for Machine Learning

Customized OpenFAST simulation framework for generating wind turbine design load cases, creating training datasets for machine learning applications.

OpenFASTMachine LearningPythonWind Turbine Simulation
  • OpenFAST was customized for special outputs
  • Automated Design Load Case Generation
  • Wind turbine models with/without structure/control failures