A Comparison of Different Approaches for Verification and Validation of Software in Safety-Critical Systems

Björklund, Ludvig; Glaser, Markus; Skofteland, Gunleiv; Lundteigen, Mary Ann

doi:10.3850/978-981-18-2016-8_262-cd

Cited by 1 publication

(4 citation statements)

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“…The testing stage is the final stage before taking the asset operational and requires trusting the digital twin to be used for complimentary evidence. The qualification and assurance process at this stage can integrate experimental data to reduce uncertainty in the digital twin (DNV GL, 2020;Bjorklund et al, 2022). In the operational stage each instance of a digital twin is connected to a unique instance of the physical asset.…”

Section: A Digital Twin For Safety Demonstrationsmentioning

confidence: 99%

“…During the conceptual stage, assurance of the digital twin will be reduced to evaluating the captured behavior against the specifications of the battery pack, for example by achieving the behavior described in data sheets. In later developmental stages experimental data from the digital twin can be considered useful for calibrating the model parameters and increase the confidence level in the ability to accurately capture the behavior of the battery pack (Bjorklund et al, 2022).…”

Section: Initial Qualification and Assurancementioning

confidence: 99%

“…The digital twin can describe a specific battery pack with greater accuracy, by calibrating model parameters and attributing small deviations to incorrect assumptions on initial conditions or modeling uncertainties (Bjorklund et al, 2022). After this initial configuration period, deviations will be attributable to, degradation, faults and other issues in the battery pack.…”

Section: Update To Manage Deviationsmentioning

confidence: 99%

“…Computational models grounded in first principles shall be developed, featuring clearly defined relationships between the physics-driven model parameters. Parameters that are excluded from the model must be documented with sufficient evidence to support the assumption that they do not contribute to safety-related behavior (Bjorklund et al, 2022). Proper documentation of parameter uncertainty, including a physicallysupported range, should be included as part of the digital twin qualification and assessment process.…”

Section: Initial Qualification and Assurancementioning

confidence: 99%

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Life-Cycle Considerations for Trusting a Digital Twin for Safety Demonstrations

Björklund,

Lundteigen,

Haugen

2023

Proceeding of the 33rd European Safety and Reliability Conference

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Trust in evidence produced by the digital twin is crucial for critical decision-making. Establishing trust in the evidence produced by the digital twin require a robust qualification and assurance process of the digital twin. A use case of a digital twin for safety demonstrations is used to determine the need for qualification and assurance process throughout the complete lifecycle for the specific application. A battery system consisting of a battery management system and a battery pack is used as a theoretical case study for identifying specific considerations of the use case. Initially the digital twin require a qualification and assurance process that can extend to rare events and often unobserved states, Modeling the behavior in the presence of physical failures and degradation, corrupt data and other communication issues are crucial for demonstrating the capability of the logic to manage and control the battery system from reaching a failed state. During operation different triggers for updating the digital twin to manage changes in the physical space are identified and considerations for handling the updates are presented. Ultimately, the paper offers a recommendation for managing changes in the digital twin proposing a re-qualification and re-assurance process to be based on the change required in the digital twin.

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Section: A Digital Twin For Safety Demonstrationsmentioning

confidence: 99%

Section: Initial Qualification and Assurancementioning

confidence: 99%

Section: Update To Manage Deviationsmentioning

confidence: 99%

Section: Initial Qualification and Assurancementioning

confidence: 99%

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