From Human to Height-Field: Predictive Shotcrete Simulation with a Physics-Informed Particle System

This paper presents a validation study of a real-time shotcrete simulation model based on a physics-informed particle system. The model emulates concrete spray dynamics by replaying empirically recorded nozzle trajectories from expert and novice operators in a controlled virtual environment. We evaluate its ability to capture skill-related differences in key sprayability metrics, including material adhesion, rebound, and cohesive failure. The results reveal statistically significant distinctions between expert and novice performance, confirming the model’s sensitivity to operator expertise. The simulation also demonstrated strong repeatability and robustness despite inherent stochasticity. While the lack of physical ground truth and the absence of the material's lateral motion are noted limitations, the findings support the model's potential use in training and skill assessment. Future work will focus on improving material modeling to enhance realism and predictive accuracy.

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Publication Details

Published
2025-12-02
DOI
https://doi.org/10.1109/icar65334.2025.11338646
Primary Topic
Innovations in Concrete and Construction Materials
Type
article
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From Human to Height-Field: Predictive Shotcrete Simulation with a Physics-Informed Particle System

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Innovations in Concrete and Construction Materials
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From Human to Height-Field: Predictive Shotcrete Simulation with a Physics-Informed Particle System

Soheil Gholami, Rui Wu, Ralf Waspe, Ali Muhammad, Mohammad Reza Yazdi Samadi, Aude Billard, Christian Schlette
article en

Abstract

This paper presents a validation study of a real-time shotcrete simulation model based on a physics-informed particle system. The model emulates concrete spray dynamics by replaying empirically recorded nozzle trajectories from expert and novice operators in a controlled virtual environment. We evaluate its ability to capture skill-related differences in key sprayability metrics, including material adhesion, rebound, and cohesive failure. The results reveal statistically significant distinctions between expert and novice performance, confirming the model’s sensitivity to operator expertise. The simulation also demonstrated strong repeatability and robustness despite inherent stochasticity. While the lack of physical ground truth and the absence of the material's lateral motion are noted limitations, the findings support the model's potential use in training and skill assessment. Future work will focus on improving material modeling to enhance realism and predictive accuracy.

Maersk (Denmark) (DK), École Polytechnique Fédérale de Lausanne (CH)
Openalex Percentile: Top 34%
Innovations in Concrete and Construction Materials
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