Generating bridge geometric digital twins from point clouds

The automation of digital twinning for existing bridges from point clouds remains unresolved. Previous research yielded methods that can generate surface primitives combined with rule-based classification to create labelled cuboids and cylinders. While these methods work well in synthetic datasets or simplified cases, they encounter huge challenges when dealing with real-world point clouds. The proposed framework employs bridge engineering knowledge that mimics the intelligence of human modellers to detect and model reinforced concrete bridge objects in imperfect point clouds. Experiments on ten bridge point clouds indicate the framework can achieve high and reliable performance of geometric digital twin generation of existing bridges.This research is funded by EPSRC, EU Infravation SeeBridge project under Grant No. 31109806.0007 and Trimble Research Fun

From the semantic point cloud to heritage-building information modeling: A semiautomatic approach exploiting machine learning

This work presents a semi-automatic approach to the 3D reconstruction of Heritage-Building Information Models from point clouds based on machine learning techniques. The use of digital information systems leveraging on three-dimensional (3D) representations in architectural heritage documentation and analysis is ever increasing. For the creation of such repositories, reality-based surveying techniques, such as photogrammetry and laser scanning, allow the fast collection of reliable digital replicas of the study objects in the form of point clouds. Besides, their output is raw and unstructured, and the transition to intelligible and semantic 3D representations is still a scarcely automated and time-consuming process requiring considerable human intervention. More refined methods for 3D data interpretation of heritage point clouds are therefore sought after. In tackling these issues, the proposed approach relies on (i) the application of machine learning techniques to semantically label 3D heritage data by identification of relevant geometric, radiometric and intensity features, and (ii) the use of the annotated data to streamline the construction of Heritage-Building Information Modeling (H-BIM) systems, where purely geometric information derived from surveying is associated with semantic descriptors on heritage documentation and management. The “Grand-Ducal Cloister” dataset, related to the emblematic case study of the Pisa Charterhouse, is discussed

Generating bridge geometric digital twins from point clouds

The automation of digital twinning for existing bridges from point clouds remains unsolved. Extensive manual effort is required to extract object point clusters from point clouds followed by fitting them with accurate 3D shapes. Previous research yielded methods that can automatically generate surface primitives combined with rule-based classification to create labelled cuboids and cylinders. While these methods work well in synthetic datasets or simplified cases, they encounter huge challenges when dealing with realworld point clouds. In addition, bridge geometries, defined with curved alignments and varying elevations, are much more complicated than idealized cases. None of the existing methods can handle these difficulties reliably. The proposed framework employs bridge engineering knowledge that mimics the intelligence of human modellers to detect and model reinforced concrete bridge objects in imperfect point clouds. It directly produces labelled 3D objects in Industry Foundation Classes format without generating low-level shape primitives. Experiments on ten bridge point clouds indicate the framework achieves an overall detection F1-score of 98.4%, an average modelling accuracy of 7.05 cm, and an average modelling time of merely 37.8 seconds. This is the first framework of its kind to achieve high and reliable performance of geometric digital twin generation of existing bridges

Application of TLS method in digitization of bridge infrastructures : a path to BrIM development

Over the past years, bridge inspection practices and condition assessments were predi-cated upon long-established manual and paper-based data collection methods which were generally unsafe, time-consuming, imprecise, and labor-intensive, influenced by the experience of the trained inspectors involved. In recent years, the ability to turn an actual civil infrastructure asset into a detailed and precise digital model using state-of-the-art emerging technologies such as laser scanners has become in demand among structural engineers and managers, especially bridge asset managers. Although advanced remote technologies such as Terrestrial Laser Scanning (TLS) are recently established to overcome these challenges, the research on this subject is still lacking a comprehensive methodology for a reliable TLS-based bridge inspection and a well-detailed Bridge Information Model (BrIM) development. In this regard, the application of BrIM as a shared platform including a geometrical 3D CAD model connected to non-geometrical data can benefit asset managers, and significantly improve bridge management systems. Therefore, this research aims not only to provide a practical methodology for TLS-derived BrIM but also to serve a novel sliced-based approach for bridge geometric Computer-Aided Design (CAD) model extraction. This methodology was further verified and demonstrated via a case study on a cable-stayed bridge called Werrington Bridge, located in New South Wales (NSW), Australia. In this case, the process of extracting a precise 3D CAD model from TLS data using the sliced-based method and a workflow to connect non-geomet-rical information and develop a BrIM are elaborated. The findings of this research confirm the reliability of using TLS and the sliced-based method, as approaches with millimeter-level geometric accuracy, for bridge inspection subjected to precise 3D model extraction, as well as bridge asset management and BrIM development

Performance Evaluation of Triangulation Based Range Sensors

The performance of 2D digital imaging systems depends on several factors related with both optical and electronic processing. These concepts have originated standards, which have been conceived for photographic equipment and bi-dimensional scanning systems, and which have been aimed at estimating different parameters such as resolution, noise or dynamic range. Conversely, no standard test protocols currently exist for evaluating the corresponding performances of 3D imaging systems such as laser scanners or pattern projection range cameras. This paper is focused on investigating experimental processes for evaluating some critical parameters of 3D equipment, by extending the concepts defined by the ISO standards to the 3D domain. The experimental part of this work concerns the characterization of different range sensors through the extraction of their resolution, accuracy and uncertainty from sets of 3D data acquisitions of specifically designed test objects whose geometrical characteristics are known in advance. The major objective of this contribution is to suggest an easy characterization process for generating a reliable comparison between the performances of different range sensors and to check if a specific piece of equipment is compliant with the expected characteristics

Near-IR spectroscopy of asteroids 21 Lutetia, 89 Julia, 140 Siwa, 2181 Fogelin, and 5480 (1989YK8), potential targets for the Rosetta mission; remote observations campaign on IRTF

In the frame of the international campaign to observe potential target asteroids for the Rosetta mission, remote observations have been carried out between Observatoire de Paris, in Meudon-France, and the NASA Infrared Telescope Facility on Mauna Kea. The SpeX instrument was used in the 0.8-2.5 microns spectral region, for two observing runs in March and June 2003. This paper presents near-IR spectra of the asteroids 21 Lutetia, 89 Julia, 140 Siwa, 2181 Fogelin, and 5480 (1989YK8). Near-IR spectra of the asteroids 21 Lutetia and 140 Siwa are flat and featureless. The spectrum of 89 Julia reveals absorption bands around 1 and 2 microns, which may indicate the presence of olivine and olivine-pyroxene mixtures and confirm the S-type designation. The small main-belt asteroids 2181 Fogelin and 5480 (1989YK8) are investigated spectroscopically for the first time. Near-IR spectra of these asteroids also show an absorption feature around 1 micron, which could be and indicator of igneous/metamorphic surface of the objects; new observations in visible as well as thermal albedo data are necessary to draw a reliable conclusion on the surface mineralogy of both asteroids.Comment: Sent: October 2003, Accepted: December, 200

Structural Behaviour of Blast Loaded Hybrid Systems

Currently, in the military and civilian fields, there is an increasing demand for using hybrid systems, which are manmade structural systems combining two or more distinct materials. By carefully studying and designing such kind of structural systems, one can take advantage of heterogeneity of the structure, thus significantly improving the overall structural performance. Hence, the demand for robust analytical and numerical models to predict blast performance of such system has become more important. The primary aim of the present research is to investigate and understand the structural behaviour of several hybrid systems under extreme dynamic loads and to propose concepts for optimisation. Three types of hybrid systems have been studied, improved and their performance has been validated. They are the metal-to-composite hybrid joints, sandwich panels, and the metamaterial. Analytical, numerical and experimental studies have been conducted to analyse the structural behaviour of hybrid joints and sandwich panels under transient high intensity dynamic loading, in order to ensure these systems possess the desired capacity, designed strength, and robustness. Therefore, they are able to resist not only static loadings but also shocks induced by various explosions. For frequency analysis purposes, the perforated hybrid joints and metamaterials have been considered as a 2D lattice. The primitive cell (unit cell) of the lattice is formulated in the Fourier space (k-space) and studied using the Floquet-Bloch’s principle to investigate the attenuation-free shock response characteristics. Plane wave propagation in the hybrid system is thus investigated by constructing the first Brillouin zone and extracting the band structure diagram. As another case for a hybrid system, the structural performance of a circular sandwich panel with symmetric through-thickness architecture subjected to a pulse loading of arbitrary temporal and spatially uniform distribution (UDL) has been investigated by using the third order shear deformation theory. Based on the Hamilton’s principle, the governing partial differential equations (PDE’s) are derived. By applying the weak form Galerkin’s method of weighted residuals, the PDE’s are transformed into ODE’s. By solving the ODE’s with their boundary and initial conditions, results show that there is a strong correlation with finite element results obtained from ABAQUS 6.9. The third-order shear deformation theory allows for accurate assessment of out-of -plane shear in the core where the failure usually occurs. Due to the fact that core of a sandwich panel is more often to be the weakest link, a remedy must sought, e.g. employing additional core layers, to improve its performance. Dynamic response of four circular sandwich panel constructions with different proposed core designs under global and local blast loading conditions has been investigated. Numerical finite element (FE) models have been set up to study the effect of additional core inter-layers on blast resistance enhancement of these sandwich panels. A ductile elastomeric layer of polyurea, and a fairly compressible Divinycell-H200 foam layer have been selected as the additional core inter-layers and have been placed in different arrangements to protect the core of the standard sandwich panels, and maximise overall blast resistance. Comparison of specific kinetic and strain energies shows the effect of additional core layers on blast energy absorption of a sandwich system. The study shows the improvement in shear failure prevention in the core as a result of the use of additional core layers. One qualitative 2DoF system with a viscoelastic spring element representing the integral effects of sacrificial additional core inter-layers and a nonlinear spring representing the stiffness of the conventional sandwich system; and a similar qualitative SDoF model of a conventional sandwich panel have been developed for dynamic analysis. The conclusions drawn from the numerical tests are confirmed by the output of this analysis. The results of this research work give a better understanding of the performance of some generic hybrid systems under blast, which allows the optimised hybrid system to be more confidently designed and should be able to fill the gap in the currently growing demand for high strength, light weight, reliable hybrid systems in various civilian and military industries

From the Semantic Point Cloud to Heritage-Building Information Modeling: A Semiautomatic Approach Exploiting Machine Learning

This work presents a semi-automatic approach to the 3D reconstruction of Heritage-Building Information Models from point clouds based on machine learning techniques. The use of digital information systems leveraging on three-dimensional (3D) representations in architectural heritage documentation and analysis is ever increasing. For the creation of such repositories, reality-based surveying techniques, such as photogrammetry and laser scanning, allow the fast collection of reliable digital replicas of the study objects in the form of point clouds. Besides, their output is raw and unstructured, and the transition to intelligible and semantic 3D representations is still a scarcely automated and time-consuming process requiring considerable human intervention. More refined methods for 3D data interpretation of heritage point clouds are therefore sought after. In tackling these issues, the proposed approach relies on (i) the application of machine learning techniques to semantically label 3D heritage data by identification of relevant geometric, radiometric and intensity features, and (ii) the use of the annotated data to streamline the construction of Heritage-Building Information Modeling (H-BIM) systems, where purely geometric information derived from surveying is associated with semantic descriptors on heritage documentation and management. The “Grand-Ducal Cloister” dataset, related to the emblematic case study of the Pisa Charterhouse, is discussed