Each project reflects a real engineering problem where conventional approaches failed—solved through simulation-driven systems, optimization, and automation.
Replaced a manually-tuned, geometry-dependent simulation with a generalized predictive digital twin accurate to within 50µm across arbitrary material stacks.
First 3D shaftline model for U.S. Navy aircraft carriers, revealing failure modes undetectable with legacy 2D methods and co-published at SNAME 2023.
Established first-ever capability to compute load-dependent bearing stiffness for customer rotordynamic analysis, enabling accurate modeling of nonlinear bearing behavior.
Used ANSYS thermal simulation to prove a 1°C variation was caused entirely by sensor placement geometry, eliminating a suspected non-uniformity defect.
Thermal cycling and multi-method shock simulations (SRS, modal, transient) for weapon-mounted optical systems, identifying and correcting critical errors in partner-generated models.
Three-phase U.S. Army-funded program spanning closed-loop molding optimization, neural-network surrogate acceleration, and end-to-end manufacturing automation architecture.
Automated null surface design for GRIN and glass lens inspection, reducing an 8+ hour manual VP-level process to under 5 minutes through optimization-driven scripting.
Parameter-driven application that generates complete CNC toolpaths for Navy stave bearings, increasing production output 3–6× over manual workflows.
Surrogate model trained on 125 OpenFOAM simulations predicts pressure drop from geometry inputs, achieving <5% error on 25 held-out configurations.
Engineering tool that maps engine specs and operating conditions to all viable heat exchanger configurations using coupled heat transfer and pressure drop models.
Full-stack ASP.NET and Angular platform delivering authenticated engineering tools, usage-controlled access, and automated 3D STEP file generation and delivery.
Designed and commercialized a 4"–15" dry-running seal product line, transforming a two-SKU prototype into a fully manufactured, differentiated product family.
Custom ANSYS-designed seal achieving 4× commercial displacement capacity, with prototype performance matching simulation and remaining in active service 5+ years post-installation.
Published Android app that uses real-time camera input to synchronize Philips Hue lighting with on-screen colors, achieving 1,100+ downloads and $1,500 in revenue.
Independently pitched and secured two U.S. Army-funded programs—SuperCharge and Watson—focused on GRIN lens optimization and end-to-end manufacturing automation.
Co-developed the first 3D shaftline model for U.S. Navy aircraft carriers with NAVSEA, confirming a real-world failure mechanism and publishing results at SNAME 2023.
Restored a non-functional production system at a $25B+ manufacturer after prior internal and external efforts failed, bringing the machine back online within days of a month-long outage.
Delivered validated compressible flow CFD simulations and analytical solutions for a $2B+ manufacturer after internal teams failed to produce accurate results.
Designed targeted simulation to determine whether an observed phenomenon was physical or instrumentation error, conclusively confirming it as real.