Versatile Test Reactor Open Digital Engineering Ecosystem. Issue 1 (12th April 2022)

• Record Type: Journal Article
• Authors: Ritter, Christopher; Browning, Jeren; Suyderhoud, Peter; Hays, Ross; Marshall, AnnMarie; Han, Kevin; Ashbocker, Taylor; Darrington, John; Nelson, Lee
• Is Part Of: Insight. Volume 25:Issue 1(2022)
• Page Start: 56
• Page End: 60
• Publication Date: 2022-04-12
• Subjects: digital engineering -- digital twin -- digital thread -- versatile test reactor -- Idaho National Laboratory; Systems engineering -- Periodicals; Systems engineering; Periodicals; 620.0011
• DOI: 10.1002/inst.12374
• Languages: English
• ISSNs: 2156-485X

Abstract

ABSTRACT: Modern design of nuclear facilities represents unique challenges: enabling the design of complex advanced concepts, supporting geographically dispersed teams, and supporting first‐of‐a‐kind system development. Errors made early in design can introduce silent errors. These errors can cascade causing unknown risk of complex engineering programs. The Versatile Test Reactor (VTR) Program uses digital‐engineering principles for design, procurement, construction, and operation to reduce risk and improve efficiencies. Digital engineering is an integrated, model‐based approach which connects proven digital tools such as building information management (BIM), project controls, and systems‐engineering software tools into a cohesive environment. The VTR team hypothesizes using these principals can lead to similar risk and cost reductions and schedule efficiencies observed in other engineering industries. This research investigates the use of a digital engineering ecosystem in the design of a 300‐MWt sodium‐cooled fast reactor. This ecosystem was deployed to over 200 engineers and used to deliver the conceptual design of the VTR. We conclude that initial results show significant reductions in user latency (1000x at peak use), the possibility of direct finite‐element‐analysis (FEA) integrations to computer‐aided design (CAD) tools, and nuclear reactor system design descriptions (SDDs) that we can fully link throughout design in data‐driven requirements‐management software. These early results led to the VTR maintaining milestone performance during the COVID‐19 pandemic.