3D scans enable precise documentation of the cabin interior and facilitates the iterative updating of the Digital Twin, which supports the planning and analysis of conversions as well as versioning of modifications.
Abstract
Digitalization in the aviation industry is driving the transition towards climate-neutral and more sustainable aircraft. A central focus of research is the Digital Twin, a virtual representation of the physical system that continuously collects operational data during operation in order to increase efficiency and optimize maintenance. A challenge arises when different stakeholders such as manufacturers, airlines and maintenance companies create independent Digital Twins, which leads to inconsistencies and contradicts the very idea of a single Digital Twin per system. Isolated IT environments prevent the possible synchronization of information. One approach to synchronizing geometric data is the use of 3D scans. As aircraft cabins are frequently refitted, digital 3D models are often incomplete, if they are available at all. By comparing scans with the initial Digital Twin, modifications can be recorded and updated even if no original data is available. This enables precise documentation of the cabin interior and facilitates the iterative updating of the Digital Twin, which supports the planning and analysis of conversions as well as versioning of modifications.
This abstract presents the outcomes of the AIRPASS project, a collaborative effort between Royal Netherlands Aerospace Centre (NLR) (an applied research organisation in the aerospace domain) and Bundeswehr Research Institute for Materials, Fuels and Lubricants (WIWeB) (an independent Bundeswehr research center which is responsible for the safety, technology and chemistry of materials and petroleum, oils and lubricants), which aimed to develop a novel inspection concept for aircraft structures by leveraging automation and digitalization. The project's core idea revolves around the central role of the digital twin, fed by non-destructive testing (NDT) data. Within AIRPASS, we successfully demonstrated an automated approach to link inspection data to the digital twin. Notably, NLR and WIWeB employed distinct methods to achieve this goal: NLR utilized visual properties of the inspected object to register the position of its contactless NDT sensor with respect to the digital twin, whereas WIWeB employed positioning devices that recognized reference points in 3D space, suitable for probe-like sensors. The method employed by NLR combines the simplicity of a Structure from Motion (SfM) system for camera positioning and orientation, with the geometric accuracy of high fidelity 3D scanning or CAD geometry for the projection of NDT measurements. The WIWeB’s system makes use of an optical tracking system, which enables precise locating of the sample, probe and Mixed Reality glasses. It features real-time feedback for the user by drawing the NDT results as a color-coded map into the texture of the 3D model and displaying it in the users field of view. A comparative analysis of the results from both approaches was also conducted, providing valuable insights into the effectiveness of each method. The AIRPASS project's findings pave the way for enhanced automation and digitalization in aircraft inspection processes.
Werner Jousma, Jasper Tabe Steringa, Geart Otten et al.· e-Journal of Nondestructive...· 0 citations
Digital Twins (DTs) of buildings are becoming increasingly common, with applications including air quality monitoring, reducing energy consumption, increasing human comfort and safety and more. Data is at the heart of these digital twins; however, integration and interoperability challenges are major barriers to adoption. This paper explores the potential of a location-enabled “minimal interoperability” framework as a stepping stone for data interoperability and integration in building Digital Twins, where location refers to the position of a feature in relation to a reference system. To scope the challenge, we first identify twin-centric applications and the data sources used within each. A minimal level of location granularity (the resolution of the data) is then assigned to each data source in order to identify the required geometry components of the framework. We explore the feasibility/time and skills required to implement such a framework for a building, demonstrating the framework within a human comfort-related application. Contributions include the development of a location-enabled minimal interoperability framework that supports the heterogeneous nature of data within building Digital Twins and a `minimum granularity’ approach for the location framework which shows that simple 3D buildings appear sufficient and avoids the need for expensive 3D data capture. Our approach allows implementers of Digital Twins to explore and integrate data without implementing extensive and time-consuming full interoperability.
Geometric digital twinning is an essential step for the holistic storage, analysis, visualization, and interpretation of information about bridges from multiple modalities. Generally, accurate digital twinning depends on high-quality sensing data and the information extracted from such data, whereas the acquisition of high-quality data is typically guided by the information embedded in the model. This data–model coupling suggests that data-based modeling tasks (DBMT) and model-based data tasks (MBDT) should be performed iteratively using the available information at each stage. This research investigates an efficient bridge geometric digital twinning using a parametric bridge generator (PBG) that can accommodate DBMT and MBDT at different levels encountered during field visual inspection. Flexibility and efficiency can be achieved by (1) the PBG generating a model in the photorealistic synthetic environment once key parameters are obtained in the field, (2) flexibly selecting the key parameters depending on the level of accuracy and detail, and (3) enabling the PBG to generate as reasonable a model as possible, even with missing parameters to guide the inspection process. Based on the PBG, this research develops two feasible DBMT and MBDT that can guide bridge inspection and the geometric digital twinning process, model-based data evaluation (MBDE), and data-based model evaluation (DBME). These evaluations are employed to clarify the degree to which modeling requirements are satisfied for a given level of detail. The proposed PBG-based geometric digital twinning approach is demonstrated through two case studies in the field, one for short-span road bridge and one for long-span cable-stayed bridge.
Huayong Wu, Rongxin Zhao, Weilei Yu et al.· ASCE-ASME Journal of Risk an...· 1 citation
With Industry 5.0, human–robot collaboration has become the center of attention. This has introduced new challenges, where workspaces become highly dynamic, leading to safety concerns for robots and especially for humans. This makes it important to have a realistic and accurate digital representation of a production cell and its components in environments for movement planning and remote supervision. This paper presents a digital twin of a smart production cell, synchronizing objects bidirectionally between a real and virtual workspace with minimal effort using only a single RGB-D camera. A fine-tuned YOLO-based detector identifies tools and items in the scene, estimates their spatial position, and spawns them in Unity relative to the robot via coordinate transformation. Experiments with different scanning velocities demonstrate a mean planar spawn deviation of 5.82mm (standard deviation 2.24mm) at 0.1m/s at 0.7m height, while maintaining a constant depth bias of −0.54mm. Once spawned, objects can be manipulated freely via drag-and-drop within the simulation. Upon confirmation, a motion planning module calculates trajectories to execute these changes physically. Across 95 trials and 1805 object placements, the system achieves 100% success within working bounds, successfully executing complex tasks such as repositioning objects and stacking them into pyramid structures. The presented system provides a framework to see, spawn, and synchronize industrial workspaces, enabling rapid setup and safe remote supervision of smart production cells in highly dynamic industrial environments.
M. Herrmann, Dominykas Strazdas, A. Al-Hamadi· Machines· 0 citations
Industrial digital twins integrate physical objects, dynamic models, control systems, data analysis tools, 2D and 3D visualization, and existing software systems. Much research has focused on the functional composition of the digital twin, modeling, and application scenarios, while the organization of the digital twin as an evolving software system composed of technologically heterogeneous and autonomous subsystems remains insufficiently formalized. The goal of this study is to develop a conceptual composite architecture for an industrial digital twin, in which complex subsystems are viewed as highly interconnected and loosely coupled service components of a higher-order system. The research method is based on analogy, transfer, and adaptation of proven principles of distributed and microservice systems to the constraints of industrial digital twins. An architectural model is proposed that includes a physical object, a process model, SCADA subsystems, a unified data exchange subsystem, 2D and 3D representations, VR/AR components, and automated model building modules. The practical feasibility of the approach is demonstrated using a proof-of-concept digital twin of a methanol–ammonia co-production plant, integrating Honeywell UniSim Design R460.1, web-based SCADA, Unity, and specialized 2D and 3D representation generation modules. This demonstration confirms the feasibility of integrating independently developed subsystems and the technological heterogeneity of the solution, but does not constitute a production test of performance, scalability, or cost effectiveness. Requirements for contract stability, a consistent interaction environment, assigned data responsibility, version compatibility, and complete documentation are defined. Research limitations and areas for subsequent quantitative architecture validation are identified.
E. Koltsova, Maksim Pysin, A. Lobanov et al.· Information· 0 citations
Operational digital twins of buildings require a common environment in which Building Information Modeling (BIM)-based spatial models, live telemetry from building automation systems (BAS), and institutional records of equipment and spaces are integrated to support monitoring, analysis, and decision-making at facility scale. Existing platforms and research efforts still leave open challenges in integrating heterogeneous source systems, representing building semantics within the integrated environment, and supporting analytical workflows over the composed information at runtime. This paper investigates NVIDIA Omniverse and OpenUSD as a scene-native foundation for addressing these challenges through a shared representation. The paper contributes (i) a modular five-layer reference architecture for digital twin development, (ii) a prototype implementation realized as a custom Omniverse Kit application integrating BIM-derived context, BAS telemetry, and institutional facility records in an academic building, and (iii) an analysis of how native OpenUSD constructs can encode operational building context directly within the scene. The case study demonstrates that the composed scene, continuously updated with live operational data, can support historical trend review and system-aware workflows grounded in current building context. The results show that OpenUSD can host operationally relevant building semantics alongside spatial and operational content within a single scene, positioning Omniverse as an extensible foundation for the analytical, AI-assisted, and lifecycle-spanning workflows expected of next-generation facility operation.
Chady Elias, Raja R. A. Issa· Journal of Information Techn...· 0 citations
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