Xiaojing (Paula) Sun

• Manage and Mentor of a small team (3 to 4 people) while maintaining a key individual contributor to simulation work.
• Thermal/Electrical/Hydraulic Simulation Lead on battery packs on system levels for a number of high profile programs (Model S, Model Y, Cybertruck etc).
• Lead 3D thermal model validations and fidelity improvements with various software tools and test supports.
• Close collaboration with cross-function team (mechanical design, testing, abuse, reliability, vehicle system) on product launches and sustaining requests.

• Conduct component level (current collector, HV chain, cooling tube, etc) thermal/electrical/hydraulic analysis on different programs.
• Often work on multi-projects under high delivery pressure.
• Establish best practices and streamline workflows for teammates.

• Focusing on open cycle (scavenging) and closed cycle CFD modeling of a two-stroke opposed piston (2SOP) engine. - Responsible for developing intake and exhaust ports for better scavenging and combustion system optimization (piston bowls shapes, injectors) using CFD tools. - Team lead on Engine brake project
• Led the project from design, simulation to testing
• The newly designed engine brake was able to deliver 80% more brake power. - Work on CFD model fidelity improvement
• Apply CFD as both a design and a diagnostic tool for more efficient and streamlined engine designs. - Develop and investigate different flow device designs for air system optimization to lower system pressure drop and to improve flow uniformity and mixing. - Extensive use of Converge and EnSight.

• Work closely with process engineers, providing detailed CFD reports analyzing flame characteristics, pollutants and heat fluxes from the CFD modeling to make recommendations for product optimizations for oil refinery industries.

• Thesis: Reverse Monte-Carlo Ray-Tracing for Radiative Heat Transfer in Combustion Systems
• John Zink Scholarship Recipient
• 3.88 GPA

• Thesis: Study on Chemical Process Energy Integration Based on the Applications of AspenTech And Stochastic

Methods

• 3.70 GPA

• Thesis: Application of Artificial Neural Networks in Distillation Sequences
• 3.60 GPA