INCOSE Enchantment: Artificial Intelligence and Digital Engineering as Enablers for System Engineering in the Energy Sector
INCOSE Enchantment: Artificial Intelligence and Digital Engineering as Enablers for System Engineering in the Energy Sector
Date: 10 December 2025
Time: 4:45 PM - 6:00 PM Mountain Time
Venue: Online via ZOOM
Registration: Zoom link is provided in the meeting invitation; contact [email protected] to request the meeting invitation
Abstract: Systems engineering is of utmost importance for the success of high-cost, high-complexity megaprojects, which are common in the energy sector. However, the traditional document-centric systems engineering approach tends to be labor-intensive and time-consuming, which has inhibited its full adoption despite proven metrics on its return on investment. With the modern approach of digital engineering and advancements in artificial intelligence (AI) technologies, the barriers to systems engineering adoption can finally be broken. This paper goes through the systems engineering V-model for lifecycle management and assesses the current state of implementation of digital engineering (especially, model-based systems engineering, digital twins, and digital threads) and AI for each step. It was observed that a combination of digital engineering and AI is being used across different industries to accelerate and optimize systems engineering processes such as concept development, requirements management, architecture definition, system development, verification and validation, operations, and maintenance. Specifically in the energy sector, AI-augmented digital engineering has shown initial potential in accelerated development and deployment, performance optimization, anomaly detection, predictive maintenance, and configuration management. However, challenges remain in the safe and reliable integration of digital engineering and AI into an end-to-end system lifecycle management ecosystem. Addressing these challenges and continuously developing impactful tools will enable fast, efficient, and high-frequency deployment of power generation capabilities to keep up with the world’s energy demands and build energy security.
Speaker: Dr. Sonali Sinha Roy is an AI Engineer in the Scientific Computing and AI division at Idaho National Laboratory. She applies AI to facilitate systems engineering and digital engineering, automate workflows, and improve operational efficiencies in large-scale projects. Her projects include development of the predictive digital twin for the DOME microreactor test bed at INL, validation of commercially developed GenAI tools for nuclear permitting, use of MBSE for cybersecurity assessment of nuclear systems, autonomous piping design for nuclear facilities, and design optimization of nuclear reactors for space applications. Sonali holds a Ph.D. in Aeronautics and Astronautics from Purdue University. For her Ph.D. research, she worked with NASA JPL to perform risk and performance assessment for the Mars Sample Return mission architecture.