Year: 2025
Author(s): Jonatan Isaksson, Jelke Dijkstra
Publication Type: Journal article
The pile cycle of an axially loaded displacement pile in a sensitive natural clay has been modeled using a coupled finite-element code for large deformations. The originality lies in the effective stress-based analysis with a consistent set of model parameters that considers all necessary soft soil features, i.e., anisotropy, destructuration, and rate dependency. Furthermore, the modeling approach is successfully benchmarked at all stages of the pile cycle (initialization, installation, equalization, loading). The benchmarking consisted of model calibration at element level, model selection using simulated and measured cone penetration test (CPTu) data, comparisons of measured and computed radial and shear stress during pile installation, and pile load testing. The results indicate that, with the exception of the absolute magnitude of the excess pore-water pressures generated during installation, the trends observed in the experimental data were captured well at all stages. Furthermore, several aspects of large deformation modeling of CPTu penetration, and pile installation were discussed. Most importantly, the difficulty in modeling the postpeak softening behavior and the balancing effects of the viscoplastic response (rate dependence) and strain-softening (destructuration) was highlighted. Finally, the empirical relation between the CPTu response and the bearing capacity of pile could be numerically confirmed. In conclusion, a first step is provided for the inclusion of the spatiotemporal response of sensitive natural clay over the full pile cycle in system-level geotechnical finite-element analysis.
Year: 2024
Author(s): Emil Adiels, Mats Ander, Christopher John Kenneth Williams
Publication Type: Journal article
Surface geometry plays a central role in the design of bridges, vaults and shells, using various techniques for generating a geometry which aims to balance structural, spatial, aesthetic and construction requirements.
In this paper we propose the use of surfaces defined such that given closed curves subtend a constant solid angle at all points on the surface and form its boundary. Constant solid angle surfaces enable one to control the boundary slope and hence achieve an approximately constant span-to-height ratio as the span varies, making them structurally viable for shell structures. In addition, when the entire surface boundary is in the same plane, the slope of the surface around the boundary is constant and thus follows a principal curvature direction. Such surfaces are suitable for surface grids where planar quadrilaterals meet the surface boundaries. They can also be used as the Airy stress function in the form finding of shells having forces concentrated at the corners.
Our technique employs the Gauss-Bonnet theorem to calculate the solid angle of a point in space and Newton's method to move the point onto the constant solid angle surface. We use the Biot-Savart law to find the gradient of the solid angle. The technique can be applied in parallel to each surface point without an initial mesh, opening up for future studies and other applications when boundary curves are known but the initial topology is unknown.
We show the geometrical properties, possibilities and limitations of surfaces of constant solid angle using examples in three dimensions.
Year: 2024
Author(s): Oliver Disney
Publication Type: Licentiate thesis
Building Information Modeling (BIM) was expected to rapidly transform the construction industry, but its uptake has been unexpectedly slow. Furthermore, even state-of-the-art BIM projects have been challenged by hardware and software issues, limiting BIM’s implementation in the construction phase. This research explores an emerging approach to construction: Total BIM. Total BIM embraces BIM in its totality in that BIM is actively used in the construction phase by implementing model-based construction processes. It replaces 2D drawings as the legally binding source of information, enabling site workers to interact with modern cloud-based BIM software to create and extract necessary and relevant information.
Until recently, there has been a lack of real-world cases successfully implementing BIM as the single source of information for construction workers, which has hindered the possibility for researchers to explore the use of Total BIM in practice. However, this is beginning to change in Sweden and Norway, with the emergence of pioneering Total BIM projects. The purpose of this study has been to explore how Total BIM can be implemented as a single source of information across the design and construction phases of real-world projects. To achieve this, three in-depth case studies were conducted, collecting qualitative data from semi-structured interviews, observations, workshops, and more.
The findings, presented in four appended papers, demonstrate that implementing Total BIM in construction projects is possible and may even be preferred compared with traditional ways of working. Total BIM could serve as the missing link for advancing digitalization in the construction industry. Construction workers become an important part of structured data creation, through integrated processes such as requests for information (RFIs), controls, checklists and photos. This structured data enables new opportunities for informed, data-driven decision-making and site monitoring.
This research contributes rich empirical data from real-world case studies of Total BIM projects, illustrating how Total BIM overcomes limitations observed in previous state-of-the-art BIM projects. Additionally, it questions whether Total BIM could represent the digital disruption that the construction industry has been missing. For practitioners, this research provides real-world examples from Total BIM projects, demonstrating Total BIM implementation and highlighting key processes, while highlighting how Total BIM can create value.
Year: 2024
Author(s): Ezra Haaf, Pierre Wikby, Ayman Abed, Jonas Sundell, Lars Rosen, Minna Karstunen
Publication Type: Journal article
Construction of large underground infrastructure facilities routinely leads to leakage of groundwater and reduction of pore water pressures, causing time-dependent deformation of overburden soft soil. Coupled hydro-geomechanical numerical models can provide estimates of subsidence, caused by the complex time-dependent processes of creep and consolidation, thereby increasing our understanding of when and where deformations will arise and at what magnitude. However, such hydro-mechanical models are computationally expensive and generally not feasible at larger scales, where decisions are made on design and mitigation. Therefore, a computationally efficient Machine Learning-based metamodel is implemented, which emulates 2D finite element scenario-based simulations of ground deformations with the advanced Creep-SCLAY-1S-model. The metamodel employs decision tree-based ensemble learners random forest (RF) and extreme gradient boosting (XGB), with spatially explicit hydrostratigraphic data as features. In a case study in Central Gothenburg, Sweden, the metamodel shows high predictive skill (Pearson's r of 0.9–0.98) on 25 % of unseen data and good agreement with the numerical model on unseen cross-sections. Through interpretable Machine Learning, Shapley analysis provides insights into the workings of the metamodel, which alignes with process understanding. The approach provides a novel tool for efficient, scenario-based decision support on large scales based on an advanced soil model emulated by a physically plausible metamodel.
Year: 2024
Author(s): Radostin Mitkov, Mariya Pantusheva, Dessislava Petrova-Antonova, Vasilis Naserentin, Anders Logg
Publication Type: Paper in proceeding
The rapid urbanization trend has led to complex challenges in managing urban environments, ranging from energy consumption to environmental quality and public health. In response, the concept of city digital twins has emerged, offering a promising approach to understanding and managing urban complexity. City digital twins utilize real-time data and simulations to create virtual replicas of urban environments, enabling stakeholders to analyze, optimize, and make informed decisions about various aspects of city life. Computational Fluid Dynamics (CFD) plays a crucial role within city digital twins, offering capabilities to simulate wind flow dynamics, air quality, and pollutant dispersion within urban environments. This paper explores the opportunities and challenges of integrating CFD within city digital twins. Opportunities include optimizing urban planning and design processes, enhancing environmental quality, and improving public health outcomes. However, challenges such as data integration and quality, implementation constraints, computational complexity, and communication of results must be addressed to realize the full application potential of CFD in urban environments. Despite these challenges, the integration of CFD within city digital twins holds promise for creating more livable, sustainable, and resilient cities in the face of urbanization and climate change.
Year: 2024
Author(s): Anita Ullrich, Franziska Hunger, Ioanna Stavroulaki, Adam Bilock, Klas Jareteg, Yury Tarakanov, Alexander Gösta, Meta Berghauser Pont, Fredrik Edelvik
Publication Type: Journal article
Pedestrian movement has always been a main concern for urban planning and design, but has become more important within the sustainable development agenda, as walking is crucial to reduce urban emissions and foster livable cities. Therefore, urban planners need to be able to take pedestrian movement into consideration as part of the workflow of planning and designing cities. This study outlines a comprehensive workflow tailored for urban planners. It proposes a hybrid model that integrates an agent-based model, which simulates the micro-scale movement of pedestrians in outdoor urban environments, with a network model, which predicts the aggregated pedestrian flows on a macro-scale. The hybrid model has been applied to a pedestrian precinct in the city centre of Gothenburg, Sweden and has been compared to real-world measurements. The reasonable agreement between the simulation results and the real-world data supports the reliability of the proposed workflow, underscoring the model’s capability of predicting pedestrian movement statistically on a large scale and individually on a local scale. Furthermore, the model enables the analysis of flow distributions and movement restrictions and facilitates the analysis of different design scenarios as well as specific pedestrian behavior. This functionality is valuable for urban design and planning practice, contributing to the optimization of pedestrian flow dynamics.
Year: 2023
Author(s): Vasilis Naserentin, Georgios Spaias, Anestis Kaimakamidis, Nikos Pitsianis, Anders Logg
Publication Type: Paper in proceeding
The growing interest in creating digital twins of cities has sparked a surge in the development of detailed 3D models. In this paper we examine the current state-of-the-art in generating high-resolution 3D models of cities using neural network techniques. Additionally, we showcase the outcomes of two case studies that demonstrate the practical applications of these techniques in 3D city model generation. The first case study focuses on rooftop segmentation using publicly available Swedish cadastral data, while the second case study explores façade feature extraction using Google Street View data.
Year: 2023
Author(s): Vasilis Naserentin, Anders Logg, Dag Wästberg
Publication Type: Journal article
Digital Twin Cities Centre (DTCC) Builder is a mesh generator for automatic, efficient, and robust mesh generation for large-scale city modeling and simulation. Using standard and widely available raw data sources in the form of point clouds and cadastral data, DTCC Builder generates high-quality 3D surface and volume meshes, suitable for both visualization and simulation. In particular, DTCC Builder is capable of generating large-scale, conforming tetrahedral volume meshes of cities suitable for finite element (FEM) simulation.
Year: 2023
Author(s): Mattia Mangia, Carla Di Biccari, Mattias Roupé
Publication Type: Paper in proceeding
Complex infrastructures such as railway networks face increasing challenges related to resource allocation, external events, constraints, and demands. Therefore, it is crucial to optimize the Asset Management (AM) phase to ensure the value and functionality of the assets. The integration of Building Information Modelling (BIM) and Geographic Information Systems (GIS) can support this phase, but it can only yield benefits with a comprehensive approach that considers and addresses the specific needs and resources of the assets and their AM organization. The main benefits include improved data management, manipulation, information visualization and optimized resource allocation. This study describes an intermediate step towards developing a BIM/GIS integration framework for AM that can guide both researchers and practitioners. The framework aims to bridge theory and practice by incorporating insights from literature reviews and case studies. Its main objectives are to provide a comprehensive multi-stakeholder view and methods for effectively integrating BIM and GIS in this context. To develop the framework, the study employed focus groups, interviews, and practical BIM/GIS tests, which provided insights reported in this article. Furthermore, the study provides research directions for effective BIM/GIS integration in infrastructure AM.
Year: 2022
Author(s): Stoyan Boyukliyski, Dessislava Petrova-Antonova, Sanjay Somanath
Publication Type: Paper in proceeding
In order to aid the decision making process related to the provision of public services as to maximize the benefits for society, it is crucial to evaluate the current social facilities demand in terms of spatial distribution and access. The paper aims to solve this problem by proposing a method for automated assessment of the coverage of public services within an urban region using a capacitated graph. The methodology abstracts residential buildings into demand nodes and public service buildings into supply nodes within a graph and then uses shortest distance calculations in order to balance the two, while prioritizing residential buildings based on distance. The paper is focused on creating a general pipeline that can be used on any type of public services, as long as a certain geospatial and demographic data are available. The method is described without referencing specific tools, but focusing on the general procedure. The procedure is then applied to the whole city of Sofa, focusing on assessing the coverage of kindergartens using the 15 minutes walking distance, followed by a brief discussion of results.
