The Air Force Digital Thread/Digital Twin - Life Cycle Integration and Use of Computational and Experimental Knowledge
Abstract
Computational and experimental fluid dynamics have been integrated into aeronautical system development processes in varying degrees over the last forty years and have yet to achieve their full promise for reducing the cost and time for development. What has been missing is a holistic advance in the integration not just of computers and wind tunnels but of the organizational constructs and development processes that enable unleashing the full capability of integrated computational and experimental methods. Recent Department of Defense (DoD) policies and guidance focused on organic engineering capabilities, government insight into technical performance, and application of system models over the life cycle are enabling a major paradigm shift toward life cycle integration of computational and experimental knowledge. In conjunction with these new policies, the United States Air Force is developing and applying a Digital Thread/Digital Twin analytical framework to provide engineering analysis capabilities and support to decision making over the entire lifecycle of air vehicles. The Digital Thread/Digital Twin merges physics-based modeling and experimental data to generate an authoritative digital representation of the system at each phase of the acquisition and sustainment process of a weapon system. In this paper the history of integrated computational and experimental fluid dynamics is reviewed as a precursor for the emerging paradigm shift toward a virtual government monopsony…
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
Digital twins monitor product parameters during production.
“monitoring product parameters during production [35]”
From Review of digital twin applications in manufacturing (2019) · cites this paper as [35]
This reduces the need to always build expensive prototypes and mockups, thereby offering significant cost savings during product development and testing.
“This reduces the need to always build expensive prototypes and mockups, thereby offering significant cost savings during product development and testing [19].”
From Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020) · cites this paper as [19]
The need for creating mathematical models for the description of objects is described in [277].
“The need for creating mathematical models for the description of objects is, instead, described in [277].”
From Digital Twin in the IoT Context: A Survey on Technical Features, Scenarios, and Architectural Models (2020) · cites this paper as [277]
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References 23 · Cited by 156
- Authors
- Kraft, E. M.
- Affiliations
- Arnold Engineering Development Center
- Corresponding author
- Kraft, Edward M.
- ORCID
- Kraft, Edward M.
- Venue
- 54th AIAA Aerospace Sciences Meeting
- Published
- 2016-01-02
- OpenAlex
- W2317992223
- Cited by
- 156
- References
- 23
- Citations by year
- 2026: 7 · 2025: 14 · 2024: 17 · 2023: 23 · 2022: 21 · 2021: 21 · 2020: 23 · 2019: 18 · 2018: 7 · 2017: 3 · 2016: 1 · 2015: 1
- FWCI
- 15.34
- Type
- conference paper
- Language
- en
- Open access
- closed
- Locations
- AIAA Aerospace Sciences Meeting (publishedVersion)
- Topics
- Physical Sciences › Engineering › Control and Systems Engineering › Systems Engineering Methodologies and Applications
- Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Technology Assessment and Management
- Physical Sciences › Engineering › Computational Mechanics › Computational Fluid Dynamics and Aerodynamics
- Keywords
- digital thread, digital twin, life cycle integration, physics-based modeling, experimental data integration, decision support, knowledge management, United States Air Force
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