2026-08-12 –, Tent — RW1
Sponsor Keynote: Boeing and JuliaHub.
Breaking the non-recurring cost curve requires a fundamental shift in how complex systems are designed, analyzed, verified, and integrated. Traditional development approaches often discover design defects late in the lifecycle, when correction is more expensive, schedules are more constrained, and integration risk is highest. Model Based Development (MBD) changes this dynamic by moving defect discovery earlier and extending the verification window through the use of high-fidelity design models, executable simulations, early functional prototyping, and model-driven validation. This presentation explores how model-based methodologies enable earlier requirements validation, improved design maturity, greater standardization, earlier verification test readiness, and higher-fidelity system integration. By placing detailed system design models at the center of the development process, organizations can reduce late-cycle rework, improve first-pass quality, accelerate integration maturity, and ultimately reduce non-recurring engineering cost while improving delivery confidence.
Breaking the non-recurring cost curve requires a fundamental shift in how complex systems are designed, analyzed, verified, and integrated. Traditional development approaches often discover design defects late in the lifecycle, when correction is more expensive, schedules are more constrained, and integration risk is highest. Model Based Development (MBD) changes this dynamic by moving defect discovery earlier and extending the verification window through the use of high-fidelity design models, executable simulations, early functional prototyping, and model-driven validation. This presentation explores how model-based methodologies enable earlier requirements validation, improved design maturity, greater standardization, earlier verification test readiness, and higher-fidelity system integration. By placing detailed system design models at the center of the development process, organizations can reduce late-cycle rework, improve first-pass quality, accelerate integration maturity, and ultimately reduce non-recurring engineering cost while improving delivery confidence.
Gary Mansouri is a Technical Fellow, Chief Architect of Systems MBE (Model Based Engineering) and a Boeing designated expert and senior adviser in model-based detailed systems design with primary focus in multi-disciplinary dynamic systems behavioral modeling and simulation, integrated vehicle systems, systems architectures, control systems, actuators and sensors and embedded systems.
Dr. Chris Rackauckas is the VP of Modeling and Simulation at JuliaHub, the Director of Scientific Research at Pumas-AI, Co-PI of the Julia Lab at MIT, and the lead developer of the SciML Open Source Software Organization. For his work in mechanistic machine learning, his work is credited for the 15,000x acceleration of NASA Launch Services simulations and recently demonstrated a 60x-570x acceleration over Modelica tools in HVAC simulation, earning Chris the US Air Force Artificial Intelligence Accelerator Scientific Excellence Award. See more at https://chrisrackauckas.com/. He is the lead developer of the Pumas project and has received a top presentation award at every ACoP in the last 3 years for improving methods for uncertainty quantification, automated GPU acceleration of nonlinear mixed effects modeling (NLME), and machine learning assisted construction of NLME models with DeepNLME. For these achievements, Chris received the Emerging Scientist award from ISoP.
Viral Shah is the co-founder and CEO of JuliaHub, Inc, and the co-creator of the Julia Programming Language