Browsing by Author "Crampen, David"

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  • ItemOpen Access
    Data corresponding to paper: "A Feasibility Study of a Hybrid Digital Shadow System for Pavement-Load Monitoring" by Crampen et al. (submitted 2026)
    (Technische Universität Dresden, 2026-11-04) Crampen, David; Hein, Marcel; Schäfer, Simon; Anantheswar, Atul; May, Marcel; Hagmanns, Moritz Peter Mathias; Kehls, Jannick; Yordanov, Ventseslav; Hartung, Felix; Kaliske, Michael; Wollny, Ines; Fazekas, Adrian; Oeser, Markus; Alrifaee, Bassam; Brepols, Tim; Scheunemann, Lisa; Eckstein, Lutz; Blankenbach, Jörg
    This data publication contains the data related to the scientific contribution "A Feasibility Study of a Hybrid Digital Shadow System for Pavement-Load Monitoring" by Crampen et al. (submitted 2026). Abstract of the corresponding paper: Highway management requires integrated digital approaches to support predictive maintenance and extend pavement service life. Yet traffic loads, pavement-response simulations, and infrastructure context are commonly handled in isolated systems. Digital Twins can connect perception, analysis, and simulation in real-time but require heterogeneous data and models to be temporally aligned and coherently visualized. We present a functional hybrid Digital Shadow demonstrator for road pavement-load monitoring that establishes interoperability between matching laboratory-scale and highway field installation physical twins, integrating both domains within a shared virtual orchestrator. The system integrates pressure sensing, optical vehicle tracking, chassis sensing, weigh-in-motion, finite element simulations, and a non-intrusive surrogate model into a georeferenced environment, enabling measurements and simulation results to be inspected in spatial and temporal context. Live data integration and real-time pavement-response prediction are demonstrated in the laboratory, while weigh-in-motion (WIM) and chassis-sensor measurements are incorporated through timestamp-consistent replay, and high-fidelity pavement finite element (FE) simulations are integrated offline. With six simultaneously represented vehicles, the platform maintains 85 frames per second (FPS). Average round-trip latency remains below 10 ms and jitter below 6 ms over a wireless local area network (WLAN) at tested send intervals of 2 to 50 ms. The surrogate predicts pavement-response fields in approximately 10 ms, reducing computation time by three orders of magnitude versus the full-order FE model, and achieves a normalized mean squared error (NMSE) below 3 % for 80 % of 1,480 evaluated pressure states. Although pavement-response validation remains model-to-model, the demonstrator provides a functional, extensible foundation for future operational road Digital Twins.
  • ItemOpen Access
    Geometric-Semantic-Model and Platform for pavement loading and response monitoring of a German Highway
    (Technische Universität Dresden, 2025-11-06) Crampen, David; Hartung, Felix; Effkemann, Christoph; Becker, Ralf; Blankenbach, Jörg
    This data publication contains the data and derivatives corresponding to the geometric-semantic model generated as foundation for the interactive visualization of the Unreal engine-based digital shadow platform for sensor data management and simulation integration for the use case Weigh-in-Motion (WIM) and pavement response analysis. The Demonstrator "3D Interactive Visualization and Physical Mockup of a WIM Research Site" of the DFG Collaborative Research Center SFB/TRR 339 “Digital Twin Road” represents a case study for evaluating the feasibility of integrating multiple monitoring subsystems into a single source of truth representing the main components of a digital shadow system. The system integrates WIM system measurements, simulated pavement deformations and a real-time connection to a small-scale physical mock-up, where vehicle positions and proxy vehicle loading measurements can be monitored in real time. This demonstrates the feasibility of sensor data integration into a single-source-of-truth and linkage of real-time capable pavement analysis simulations into a high fidelity 3D monitoring environment, allowing interaction with the physical environment.