Veriﬁcation and validation of digital twins and virtual testbeds

Dahmen, U.; Osterloh, Tobias; Roßmann, Jürgen

doi:10.11591/ijaas.v11.i1.pp47-64

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…Online DT V&V Offline DT V&V Data V&V General system V&V ITU 52 x Lehner et al 57 x x Sargent 75 x Lugaresi et al 38 x Khan et al 76 x x x Peter et al 39 x Dahmen et al 77 x Hua et al 74 x x x Shao and Kibira 58 x Wagner et al 50 x x Locklin et al 78 x x x x Rasheed et al 60 x Schleich et al 55 x 4.1.7. Scalability.…”

Section: Refmentioning

confidence: 99%

From modeling and simulation to Digital Twin: evolution or revolution?

Ali,

Biglari,

Denil

et al. 2024

SIMULATION

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As digitalization is permeating all sectors of society toward the concept of “smart everything,” and virtual technologies and data are gaining a dominant place in the engineering and control of intelligent systems, the Digital Twin (DT) concept has surfaced as one of the top technologies to adopt. This paper discusses the DT concept from the viewpoint of Modeling and Simulation (M&S) experts. It both provides literature review elements and adopts a commentary-driven approach. We first examine the DT from a historical perspective, tracing the historical development of M&S from its roots in computational experiments to its applications in various fields and the birth of DT-related and allied concepts. We then approach DTs as an evolution of M&S, acknowledging the overlap in these different concepts. We also look at the M&S workflow and its evolution toward a DT workflow from a software engineering perspective, highlighting significant changes. Finally, we look at new challenges and requirements DTs entail, potentially leading to a revolutionary shift in M&S practices. In this way, we hope to foster the discussion on DTs and provide the M&S expert with innovative perspectives.

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Section: Refmentioning

confidence: 99%

From modeling and simulation to Digital Twin: evolution or revolution?

Ali,

Biglari,

Denil

et al. 2024

SIMULATION

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show abstract

“…Various high-level guidelines and workflows have been proposed for the assessment of digital twins in the literature to-date [18,33,55,12,34,56,14], as well as in the field of computational science more broadly [62,56]. In some cases, these guidelines have been codified as standards: for example, the ASME V&V40 Standard [1] provides a risk-based framework for assessing the credibility of a model from a variety of factors that include source code quality and the mathematical form of the model [17].…”

Section: Related Workmentioning

confidence: 99%

Causal Falsification of Digital Twins

Cornish¹,

Taufiq²,

Doucet³

et al. 2023

Preprint

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Digital twins hold substantial promise in many applications, but rigorous procedures for assessing their accuracy are essential for their widespread deployment in safety-critical settings. By formulating this task within the framework of causal inference, we show it is not possible to certify that a twin is "correct" using real-world observational data unless potentially tenuous assumptions are made about the data-generating process. To avoid these assumptions, we propose an assessment strategy that instead aims to find cases where the twin is not correct, and present a general-purpose statistical procedure for doing so that may be used across a wide variety of applications and twin models. Our approach yields reliable and actionable information about the twin under only the assumption of an i.i.d. dataset of real-world observations, and in particular remains sound even in the presence of arbitrary unmeasured confounding. We demonstrate the effectiveness of our methodology via a large-scale case study involving sepsis modelling within the Pulse Physiology Engine, which we assess using the MIMIC-III dataset of ICU patients.

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Potential of thermography for the monitoring of DED-Arc processes

Müller,

Hensel

2024

Weld World

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Thermography is a technique that uses, e.g., an infrared camera to visualize and measure the temperature of an object. It is often used in industrial and scientific applications to identify areas of heat loss, overheating, and other thermal anomalies. In the context of the DED-Arc (Direct Energy Deposition) process, thermography can be used to monitor the process and evaluate the temperature profile of the produced part. This can help to ensure the quality and reliability of the product, as well as to predict the resulting mechanical properties of the produced part. However, for other AM processes like LPBF (laser powder bed fusion), thermography is already used in industrial applications while for DED-Arc it is still a challenge to reliably determine the dynamically changing emission coefficient, as the emissivity strongly depends on the surface conditions. This means the emission coefficient differs for changes in surface conditions like impurities from soot and annealing colors. This work focuses on the potential of thermography for monitoring the DED-Arc process. A workflow for generating a calibration function for the emission coefficient ε is presented. In the context to the focus of this work, the resulting ε(T) function differentiates between the first three deposited layers and shows the change of emissivity for higher temperatures. This function is then used to correct the measured temperature profile with regard to different surface conditions and thus emission coefficients of a DED-Arc part. Highlights 1. Temperature-dependent function for correcting the emissivity for DED-Arc with steel was defined. 2. Emissivity is also influenced by the purity of the surface, leading to higher emissivity coefficients in layers that are previously deposited. 3. t8/5 times are also affected by a wrongly set emission coefficient; deviations from the corrected t8/5 time depend on the cooling speed.

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Veriﬁcation and validation of digital twins and virtual testbeds

Cited by 3 publications

References 18 publications

From modeling and simulation to Digital Twin: evolution or revolution?

From modeling and simulation to Digital Twin: evolution or revolution?

Causal Falsification of Digital Twins

Potential of thermography for the monitoring of DED-Arc processes

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