Digital Innovation Center of Excellence (DICE)
MEGAPROJECTS AND DIGITAL ENGINEERING
In the world of industry and research, megaprojects are the ambitious efforts that can change the world, e.g., space exploration technology, defense systems, power plants, complex buildings. The benefits of such projects are enormous, but undetected design errors and unforeseen production issues can cascade into delays that put a project behind schedule and over budget.
Digital engineering (DE) helps prevent such calamities. By using artificial intelligence and the latest data models to coordinate engineering and construction, DE keeps costs down and work on track while dramatically reducing overall program risk.
Given its leadership role in the U.S. Department of Energy’s initiative to build a Versatile Test Reactor – a 300-megawatt thermal, sodium-cooled fast reactor to support nuclear materials research and testing – INL recognized an opportunity to implement digital engineering strategies to predict reactor performance and design issues early in the process and minimize cascading risk.
Out of this emerged DICE – the Digital Innovation Center of Excellence.
What is DICE?
DICE serves as a virtual center to formalize and coordinate digital engineering, digital twinning, and digital transformation activities across next generation energy systems. DICE will serve the following key functions:
Leadership for a strategy on digital innovation for the world’s energy future
Recognition as a national center of excellence through research accomplishments
Coordination to share community best practices across the laboratory
Outreach to universities, industry partners, and other national laboratories
Enhance training and education materials on digital engineering and digital twinning
Examples of Success
Mortenson Construction cumulative day direct schedule reductions
Boeing improvements in first-time quality through use of Digital Twins
General Electric savings in cost avoidance through digital innovations
National Nuclear Security Administration (NNSA) in savings through digital innovations
DICE is organized into eight key pillar areas with tight collaboration between pillars to realize our digital future. Each pillar will meet at least quarterly with event-based (proposal opportunities / standards development) meetings arranged between regularly scheduled meetings.
Next Gen Artificial Intelligence
Next-gen AI encompasses emerging architectures, methodologies, and tools that will drive revolutionary advancements in scientific applications that include real-time chemical analysis, battery and catalysis mechanistic models, and high-consequence nuclear energy and security missions.
Operational Artificial Intelligence
The application of artificial intelligence (AI) in energy systems has a game-changing potential in automating expensive and manual human activities in various types of industries. This pillar focuses on the application of AI to improving asset operations.
Practice and Culture
The practice/culture is the realization of digital innovation and digital engineering within our national laboratory system, industry, and academic partners.
Digital twins are the computational simulation of a physical process or system that has a live link to the physical system, enabling enhanced verification of the simulation, control of the physical system, and analysis of trends via artificial intelligence and machine learning.
The digital thread is defined as integrating systems and data together to trace connections in data across data sources and across the lifecycle of a program or asset. The result of this effort is a holistic view that empowers new insights and prevents losses caused by siloed data.
Decision Sciences and Visualization
Using behavioral economics, game theory, statistics, and risk analysis to develop models and simulations that shed light on how human behavior affect decisions.
Cyber & Data Resilience
Data resilience represents the safeguards and validation of integrity with data which is utilized in the training of machine learning models.
Computing platforms represent the computational architectures with the right-sized deployments of high performance computing, public/community cloud, and edge device computing.