A simulation-based software to support the real-time operational parameters selection of tunnel boring machines

With the fact that the main operational parameters of the construction process in mechanized tunneling are currently selected based on monitoring data and engineering experience without exploiting the advantages of computer methods, the focus of this work is to develop a simulation-based real-time assistant system to support the selection of operational parameters. The choice of an appropriate set of these parameters (i.e., the face support pressure, the grouting pressure, and the advance speed) during the operation of tunnel boring machines (TBM) is determined by evaluating different tunneling-induced soil-structure interactions such as the surface settlement, the associated risks on existing structures and the tunnel lining behavior. To evaluate soil-structure behavior, an advanced process-oriented numerical simulation model based on the finite cell method is utilized. To enable the real-time prediction capability of the simulation model for a practical application during the advancement of TBMs, surrogate models based on the Proper Orthogonal Decomposition and Radial Basis Functions (POD-RBF) are adopted. The proposed approach is demonstrated through several synthetic numerical examples inspired by the data of real tunnel projects. The developed methods are integrated into a user-friendly application called SMART to serve as a support platform for tunnel engineers at construction sites. Corresponding to each user adjustment of the input parameters, i.e., each TBM driving scenario, approximately two million outputs of soil-structure interactions are quickly predicted and visualized in seconds, which can provide the site engineers with a rough estimation of the impacts of the chosen scenario on structural responses of the tunnel and above ground structures

From digital models to numerical analysis for mechanised tunnelling: a fully automated design-through-analysis workflow

Large infrastructure projects involving the construction of tunnels in urban areas constitute complex, integrated and multi-disciplinary systems, which require building and construction information modelling as well as computational design assessment tools for decision making during all project phases and during their complete life cycle. Even if the underlying information needed for computational analysis is stored in an information model, the translation to computational models is still cumbersome and requires significant manual work for model generation and set-up as well as excessive computing resources and time. To address these shortcomings, this paper presents a systematic summary of concepts for integrated information modelling, numerical analysis and visualisation for urban mechanized tunnelling. Our first approach “BIM-to-FEM” is characterised by a fully automated link for error-free data exchange between a standalone Tunnelling Information Model and the process-oriented simulation model for mechanized tunnelling “ekate”. In the second approach “SATBIM”, a fully automated data exchange workflow is established between a parametric multi-level information model for tunnelling and multi-level numerical models based on both Finite Element and Isogeometric Analysis, where meta models are employed for real-time design assessment. We discuss the different applications of these concepts, such as scenario-based exploration of design alternatives, real-time design assessment within a TIM based on meta-models, and the potentials of using these models for the process control during construction. Furthermore, we present two case studies where real project data has been used for the integration of information and numerical modelling. The examples in this paper indicate clear advantages of this approach compared to traditional approaches in terms of efficiency of modelling achieved by reduced user interactions and error-free information exchange, and show the benefits of multi-level model representation and real-time analysis tasks

Advanced computational techniques for mechanized tunneling along arbitrary alignments and tunnel face stability analysis

Numerische Simulationen des maschinellen Tunnelvortriebs werden zunehmend als Prognosemodelle während der Planungs- und der Konstruktionsphasen eingesetzt. Im ersten Teil der Arbeit wird ein neuentwickeltes prozessorientiertes Finite-Elemente-(FE)-Simulationsmodell vorgestellt, welches den Vortriebsprozess und den Vorschub der Tunnelvortriebsmaschine entlang beliebiger Tunneltrassen abbilden kann. Darüber hinaus wurde ein vollautomatisches BIM-basiertes Modellerzeugungsmodul für Schildvortriebssimulationen entwickelt und anhand von Projektdaten der WEHRHAHN-LINE in Düsseldorf angewendet. Der zweite Teil befasst sich mit der Entwicklung einer numerischen Berechnungsstrategie zur Analyse von Scherversagenszuständen auf Basis einer Kombination aus der Enhanced Assumed Strain (EAS) Methode und der Embedded Strong Discontinuity (ESD) Methode, um eine realitätsnahe Bewertung der Ortsbruststabilität sowie Prognosen bezüglich potentieller Versagensmechanismen der Ortsbrust vornehmen zu können.In mechanized tunneling projects, large-scale 3D numerical models are increasingly used as predictive tools during the planning and the construction stages. In this thesis, advanced computational strategies to address certain unresolved problems inherent to the modeling of the tunnel boring process have been developed. In the first part, a novel computational framework is developed to simultaneously simulate the TBM movement and excavation processes during tunneling along arbitrary alignments using the FE- method. In addition, a fully automatic BIM-based modeler of shield tunneling simulations is developed and demonstrated by means of project data from WEHRHAHN-LINE metro in Düsseldorf. The second part presents a new approach based on the combination of the Enhanced Assumed Strain (EAS) method the Embedded Strong Discontinuity (ESD) method for shear failure analysis that is applied to accurately assess tunnel face stability and to predict potential tunnel face collapse mechanisms

A simulation-based software to support the real-time operational parameters selection of tunnel boring machines

With the fact that the main operational parameters of the construction process in mechanized tunneling are currently selected based on monitoring data and engineering experience without exploiting the advantages of computer methods, the focus of this work is to develop a simulation-based real-time assistant system to support the selection of operational parameters. The choice of an appropriate set of these parameters (i.e., the face support pressure, the grouting pressure, and the advance speed) during the operation of tunnel boring machines (TBM) is determined by evaluating different tunneling-induced soil-structure interactions such as the surface settlement, the associated risks on existing structures and the tunnel lining behavior. To evaluate soil-structure behavior, an advanced process-oriented numerical simulation model based on the finite cell method is utilized. To enable the real-time prediction capability of the simulation model for a practical application during the advancement of TBMs, surrogate models based on the Proper Orthogonal Decomposition and Radial Basis Functions (POD-RBF) are adopted. The proposed approach is demonstrated through several synthetic numerical examples inspired by the data of real tunnel projects. The developed methods are integrated into a user-friendly application called SMART to serve as a support platform for tunnel engineers at construction sites. Corresponding to each user adjustment of the input parameters, i.e., each TBM driving scenario, approximately two million outputs of soil-structure interactions are quickly predicted and visualized in seconds, which can provide the site engineers with a rough estimation of the impacts of the chosen scenario on structural responses of the tunnel and above ground structures

Handheld Device-Based Indoor Localization with Zero Infrastructure (HDIZI)

The correlations between smartphone sensors, algorithms, and relevant techniques are major components facilitating indoor localization and tracking in the absence of communication and localization standards. A major research gap can be noted in terms of explaining the connections between these components to clarify the impacts and issues of models meant for indoor localization and tracking. In this paper, we comprehensively study the smartphone sensors, algorithms, and techniques that can support indoor localization and tracking without the need for any additional hardware or specific infrastructure. Reviews and comparisons detail the strengths and limitations of each component, following which we propose a handheld-device-based indoor localization with zero infrastructure (HDIZI) approach to connect the abovementioned components in a balanced manner. The sensors are the input source, while the algorithms are used as engines in an optimal manner, in order to produce a robust localizing and tracking model without requiring any further infrastructure. The proposed framework makes indoor and outdoor navigation more user-friendly, and is cost-effective for researchers working with embedded sensors in handheld devices, enabling technologies for Industry 4.0 and beyond. We conducted experiments using data collected from two different sites with five smartphones as an initial work. The data were sampled at 10 Hz for a duration of five seconds at fixed locations; furthermore, data were also collected while moving, allowing for analysis based on user stepping behavior and speed across multiple paths. We leveraged the capabilities of smartphones, through efficient implementation and the optimal integration of algorithms, in order to overcome the inherent limitations. Hence, the proposed HDIZI is expected to outperform approaches proposed in previous studies, helping researchers to deal with sensors for the purposes of indoor navigation—in terms of either positioning or tracking—for use in various fields, such as healthcare, transportation, environmental monitoring, or disaster situations