Fakultät für Bauingenieurwesen und Geodäsie

Permanent URI for this collection

https://repo.uni-hannover.de/handle/123456789/3

Browse

Now showing 1 - 5 of 1448

Uncertainty analysis in geotechnical engineering with limited data
(Hannover : Institutionelles Repositorium der Leibniz Universität Hannover, 2025) Feng, Chengxin
The uncertainty analysis in geotechnical engineering arises from the complexity and inherent variability of soils and geotechnical environments. The physical and mechanical properties of soil are characterized by spatial uncertainty, influenced by factors such as depositional history and human activities. These characteristics make it challenging to accurately predict engineering behavior and associated risks using traditional, qualitative analysis methods. Inaccurate predictions can lead to safety hazards and economic losses in both design and construction, highlighting the critical need for uncertainty analysis. Effective uncertainty analysis enables engineers to assess the reliability of geotechnical structures, predict potential risks, and optimize designs, ensuring the safety and cost-efficiency of projects. Although random field methods have shown promise in addressing uncertainty in geotechnical engineering by effectively modeling the spatial uncertainty of soil properties, challenges remain. These include uncertainty characterization from limited data and the propagation of uncertainties in high-dimensional spaces. The high cost and logistical difficulties associated with data collection in geotechnical contexts often result in sparse datasets, complicating the accurate description of parameter distributions. Moreover, the spatial uncertainty of parameters in geotechnical systems results in high-dimensional variables that make uncertainty propagation complex and computationally demanding. In uncertainty characterization, we propose a novel conditional random-field generation method that combines an enhanced exponential covariance model with a truncated Karhunen-Loève expansion. This approach faithfully captures the dominant spatial correlations of geotechnical parameters while substantially reducing both the field’s dimensionality and its computational requirements. For uncertainty propagation, we introduce a new failure-probability evaluation framework that pairs maximum-entropy distributions constrained by fractional moments with Latinized Partially Stratified Sampling (LPSS). By leveraging the truncated random-field modes to represent spatial variability and using LPSS to produce low-variance, representative samples across hundreds of dimensions, the method achieves high accuracy with far fewer simulations than traditional Monte Carlo or Latin Hypercube techniques. These advances can be used for efficient uncertainty analysis of geotechnical engineering. This research tackles these limited data challenges with innovative methods to enhance the accuracy of uncertainty modeling and the efficiency of high-dimensional uncertainty propagation in geotechnical engineering. A primary contribution is the development of an interval field approach for spatial uncertainty characterization. Based on this framework, the study introduces the Interval Field Limit Equilibrium Method (IFLEM), which employs a modified Karhunen-Loève decomposition and an enhanced exponential function to efficiently assess slope stability under uncertainty, integrating the classic Morgenstern-Price method for safety factor analysis. Additionally, a B-spline-based interval field generation method is developed to incorporate sparse data, addressing uncertainties related to test locations, stratigraphy, and spatial attributes. An interval field-based finite element strength reduction method is proposed, integrating interval field samples with sparse data for accurate safety assessments. To optimize computational efficiency, a surrogate-assisted optimization technique using Bayesian optimization is introduced, significantly reducing computational costs without compromising accuracy. The proposed methods provide a comprehensive framework for advancing uncertainty modeling and high-dimensional reliability analysis in geotechnical engineering, offering practical solutions to real-world challenges and improving engineering decision-making.
Early-age-movement in grouted connections of offshore structures
(Institutionelles Repositorium der Leibniz Universität Hannover, 2025) Possekel, Joshua
To effectively combat climate change, transitioning from fossil fuels to renewable energy sources is essential. Offshore wind energy will play a key role in this transition. As future bottom-fixed offshore structures are planned for greater water depths and distances from shore, in addition to XXL monopiles, jacket foundations emerged as promising alternatives. Grouted connections, hybrid tube-in-tube connections with grout filler, are commonly used to create rigid joints between support structures and foundation piles. Thus they face unique challenges in offshore environments where undisturbed curing cannot be guaranteed. Relative movements between the steel components of the grouted connection can significantly influence bond and grout material properties. Existing knowledge in this specific field is based on a limited number of experimental studies conducted between 1978 and 1994 for the oil and gas industry. These studies primarily analysed axial relative movements using grout materials now considered outdated. Partially observed reductions in stiffness, load capacity, and fatigue strength have led to conservative guidelines for permissible relative movements, which often pose challenges to be met in current offshore projects. At the ame time, an urgent need for further research is already addressed within previously mentioned guidelines. Against this background, this dissertation developed a comprehensive experimental test program complemented by numerical analyses. The study investigates the impact of early-age movements on material and bond properties through real-scale segment tests and the load-bearing capacity of large-scale axially-loaded grouted connections. To ensure realistic application of early-age movements, typical offshore structures were evaluated using numerical seastate simulations. Lateral relative movements were identified as predominant, often measuring several millimetres. To replicate stresses and movements encountered by grouted connections during an installation, a novel experimental setup was designed, capable of simulating various types of relative movements under controlled boundary conditions. A special experimental control system was developed and implemented to account for realistic load redistributions caused by time-dependent stiffness variations considering connection and structural stiffness. Using a simplified mechanical model, it was demonstrated that these variations significantly affect stress levels in the grout material during the critical fluid-to-solid transition. Conducted segment tests were dismantled after 24 hours of early-age movement to analyse the material and bond properties within the grout interface. Key findings revealed a significant influence of movement direction (axial vs. lateral), displacement, and load amplitude, which caused localized structural damage or plas- ticization in the grout material near the moving steel component. Beyond standard strength evaluations, plasticizations were analysed using hysteresis evaluations and 3D scans, highlighting localized damage which conventional compression and flexural strength tests on extracted samples could not detect. Additional parameters, such as grout material, water-to-solid ratio, shear key height-to-spacing ratio, and ambient temperature, were investigated but deemed secondary as they indirectly influence the stiffness development and accordingly potential damage phenomena. To assess the impact of locally observed damage on the load-bearing capacity of axially-loaded grouted connections, identified primary parameters were analysed in a two-staged experimental approach using scaled cylindrical grouted connections. In the first stage, early movements were applied for 24 hours, followed by a 14-day curing period. The specimens were then tested for axial ultimate load capacity. Alongside early-age movement tests, three reference tests confirmed reproducible results with minimal scatter. The combination of conventional strain gauges and digital image correlation provided detailed insights into load transfer mechanisms in grouted connections with shear keys. Tests involving early movements revealed severe stiffness losses and load capacity reductions of up to 50 %. The predominant factors were the direction and the displacement amplitude of the applied early-age movement. Variations in load amplitude primarily affected plasticization and gap formation but were less significant for load capacity within the tested range. Generally, the observed load capacity reductions were smaller compared to earlier studies, which might be attributed not only to the grout material but also to the experimental design and test specimens. Due to the inhomogeneity of lateral relative movements along the grouted connection and circumference, a differentiation based on stress direction is strongly recommended. Finally, the experimental results were supplemented by numerical investigations covering the fluid and solid solid state of grout materials. Significant gaps in experimental methods for characterizing grout properties during this fluid-to-solid transition let to simplified approaches not able to consider detailed non-linear material behaviour within the transition phase. A comprehensive sensitivity study using finite element simulations of solid grouted connections – with non-linear contact and material law formulations – successfully replicated experimental results and expanded the existing knowledge base for modelling hybrid grout to steel connections. Numerical approaches also incorporated the effects of plasticizations caused by early-age movements, offering valuable insights for future applications.
Novel adaptive time integration and consistent coupling of structural components in an aeroelastic simulation framework
(Hannover : Gottfried Wilhelm Leibniz Universität Hannover, 2025) Märtins, David
Aeronautical structures play a pivotal role in the context of climate protection. While the expansion of wind energy is making an increasingly significant contribution to the transition towards renewable energy sources, aviation remains in the spotlight due to its substantial share in global greenhouse gas emissions. In order to enhance the efficiency of aeronautical systems, there is an increasing tendency to develop slender, thus highly flexible structures made from composite materials. However, this leads to increased susceptibility to vibrations and amplifies the complexity of fluid–structure interaction, thereby posing considerable challenges for the accurate prediction of the behaviour. The reliable design of such structures requires the use of novel computational methods capable of accurately capturing both geometric nonlinearities and the intrinsically nonlinear coupling between airflow and structural response. This gives rise to a fundamental trade-off: while high-fidelity numerical methods offer superior accuracy, their computational costs often render them impractical, particularly during the early stages of the design process. As a result, attention is increasingly directed towards mid-fidelity approaches, which seek to achieve a well-balanced compromise between modelling accuracy and computational expense. This thesis aims to advance the development of an aeroelastic simulation environment that combines the Unsteady Vortex Lattice Method with geometrically exact beam theory, employing a strongly coupled interaction between aerodynamic and structural models. The central objective is to improve the trade-off between accuracy and efficiency through targeted methodological enhancements. To this end, a consistent geometrically exact node-to-node coupling element is introduced, enabling the connection of structural components. Its formulation ensures objectivity and path independence, conserves mechanical invariants such as linear and angular momentum as well as total energy, and also permits the inclusion of mass distributions and damping effects. The performance of this coupling element is demonstrated through modal, static and dynamic analyses. In order to reduce computational costs, a heuristic adaptive time-stepping approach is developed, based on the temporal evolution of physical system variables. This allows for the detection of near-quasi-steady-state conditions without additional computational costs, enabling an increase in time-step size and thus a reduction in total simulation time. In addition, a second adaptive strategy is introduced to improve numerical robustness, based on local error estimation. This method employs Richardson's extrapolation along with a more accurate approximation of unsteady aerodynamic forces, allowing the time-step size to be dynamically adjusted according to the estimated local error. Numerical experiments demonstrate that this approach not only enhances robustness in the presence of instability or strong nonlinearities, but can also lead to reductions in computational costs. A comparison of both adaptive time-stepping strategies confirms the intended development goals. The heuristic method, while requiring case-specific parameter tuning, is particularly well suited for accelerating large numbers of similar simulations. The error-based approach, in contrast, selects time steps more efficiently with respect to the deviation from a reference solution but entails higher computational demands. The comparison further shows that the developed coupling element can be effectively integrated with both time integration schemes. In summary, the thesis demonstrates that the targeted enhancement of existing mid-fidelity approaches can improve the trade-off between modelling fidelity and computational efficiency. In doing so, it contributes to the less computational expensive and more robust development of future lightweight and flexible aeronautical structures.
Shell buckling simulations of suction buckets with stochastic and deterministic imperfection forms
(Bristol : IOP Publ., 2022) Böhm, Manuela; Schaumann, Peter
Suction buckets are large shell structures that have become a prominent alternative to pile foundations for bottom-fixed and floating offshore wind turbines. They are embedded by applying negative pressure, which leads to a high risk of structural buckling during the installation. The prediction of the buckling strength of such large shells is subject to uncertainty, since it depends significantly on the initial geometric imperfections resulting from the fabrication process. The aim of this work is to understand and reduce uncertainties in the determination of the buckling pressure. Previous work on suction buckets revealed that the choice of a representative imperfection form and amplitude is very challenging and has not yet been solved in a generalized manner. In this work, a stochastic modeling approach is introduced, which considers more realistic imperfection patterns. This approach is compared to widely established imperfection forms such as buckling mode affine imperfections and analytically described weld depressions. The generated imperfection patterns are applied to geometrically and materially nonlinear finite element models and the buckling pressures are calculated. By quantifying the impact of different imperfection forms and amplitudes, uncertainties can be reduced, and design optimization and cost minimization are enabled.
Automatic Relative Radiometric Normalization of Bi-Temporal Satellite Images Using a Coarse-to-Fine Pseudo-Invariant Features Selection and Fuzzy Integral Fusion Strategies
(Basel : MDPI, 2022) Moghimi, Armin; Mohammadzadeh, Ali; Celik, Turgay; Brisco, Brian; Amani, Meisam
Relative radiometric normalization (RRN) is important for pre-processing and analyzing multitemporal remote sensing (RS) images. Multitemporal RS images usually include different land use/land cover (LULC) types; therefore, considering an identical linear relationship during RRN modeling may result in potential errors in the RRN results. To resolve this issue, we proposed a new automatic RRN technique that efficiently selects the clustered pseudo-invariant features (PIFs) through a coarse-to-fine strategy and uses them in a fusion-based RRN modeling approach. In the coarse stage, an efficient difference index was first generated from the down-sampled reference and target images by combining the spectral correlation, spectral angle mapper (SAM), and Chebyshev distance. This index was then categorized into three groups of changed, unchanged, and uncertain classes using a fast multiple thresholding technique. In the fine stage, the subject image was first segmented into different clusters by the histogram-based fuzzy c-means (HFCM) algorithm. The optimal PIFs were then selected from unchanged and uncertain regions using each cluster’s bivariate joint distribution analysis. In the RRN modeling step, two normalized subject images were first produced using the robust linear regression (RLR) and cluster-wise-RLR (CRLR) methods based on the clustered PIFs. Finally, the normalized images were fused using the Choquet fuzzy integral fusion strategy for overwhelming the discontinuity between clusters in the final results and keeping the radiometric rectification optimal. Several experiments were implemented on four different bi-temporal satellite images and a simulated dataset to demonstrate the efficiency of the proposed method. The results showed that the proposed method yielded superior RRN results and outperformed other considered well-known RRN algorithms in terms of both accuracy level and execution time.

Browse

Recent Submissions