This thesis investigates the estimation of period lengthening (T˜/T) in structures using model updating, which assesses frequency shifts due to changes in boundary conditions, such as flexible bases. A 2D finite element (FE) model based on Timoshenko beam elements was developed and optimized through Sequential Least Squares Quadratic Programming (SLSQP) to align simulated dynamics with measured natural frequencies and mode shapes of a steel structure.

The research was divided into two phases. Phase one utilized synthetic modal data to validate the model updating process in an error-free environment, showing that the algorithm effectively resolves stiffness-to-mass ratios rather than individual properties. Period lengthening predictions proved more accurate and stable with stiff springs, while soft springs demonstrated higher sensitivity and discrepancy. Phase two applied real measurement data, yielding results consistent with synthetic data but revealing a “plateau” in the cost function, where optimal parameter determination was challenging due to model and measurement uncertainties.

The findings indicate that model updating is a feasible method for estimating period lengthening, especially for flexible foundations. However, results are sensitive to modeling and measurement uncertainties, necessitating careful evaluation to ensure optimization convergence and parameter precision. The study recommends further research to mitigate uncertainties and enhance the method’s applicability in high-rise building design.

Due to the Netherlands' topography and geology, many regions have weak soil resistance, causing numerous buildings to experience settlements from subsidence processes, with masonry structures being the most commonly affected. In these buildings, damage typically appears as cracks and deformations, indicating the foundation’s inability to support the structure. To enhance decision-making and the engineering of effective countermeasures in these scenarios, accurate and reliable building assessments are needed to predict the expected damage based on the amount of soil deformations. This thesis, therefore, aims to evaluate the capabilities of a set of state-of-the-art damage assessment methods. These methods have been applied to a case study, with their results benchmarked against evidence from a Building Foundation Assessment report, where recorded damage features were used to evaluate the accuracy and characteristics of each assessment method.
The study began with a Visual Assessment using a Decision Diagnostic Support Tool to analyze damage features and hypothesize the causes of the building's behavior. This was followed by an Empirical Assessment, applying empirical limits to relate expected damage to Subsidence-Related Intensity (SRI) parameters. Next, an Analytical Assessment used the Limit Tensile Strain Method (LTSM) to approximate building deformations, treating it as a linear-elastic isotropic masonry beam and correlating strain estimates to damage levels. Finally, a 2D Finite Element Analysis (FEA) using a continuum crack-modelling approach was conducted on the most damaged wall to more accurately reproduce the crack widths, crack locations and the behaviour of the wall.
The results show that while the building’s damage state can be approximated with reasonable accuracy, challenges remain in predicting specific damage features. The visual assessment successfully identified the building’s underlying mechanism. Empirical and analytical methods accurately predicted damage levels in 5 out of 6 walls, proving to be efficient assessment techniques. The 2D Finite Element Analysis (FEA) successfully simulated the crack pattern on Wall 2 with a Root Mean Square Error (RMSE) of +1 Ψ or +4.7mm against the maximum mean crack widths and reproduced 5 out of 7 cracks with similar characteristics. Additionally, FEA results showed that mesh sizes of 200, 100, and 50 mm made results deviate by σ = 0.33 Ψ and σCWmax = 2.3mm, with observable changes in crack shapes in EMM models.
To address the slight deviations in the less accurate analysis of the outer leaf, primarily driven by conservative crack width estimates, a Bayesian Optimization procedure was used on the outer leaf models to identify the optimal set of material parameters that minimized the discrepancy between the damage state of the results and the target damage level in the case study.
The implementation of the approach demonstrated sufficient efficiency in identifying the optimal set of parameters, despite the computational expense of the Finite Element models. The procedure’s effectiveness varied across models with it significantly reducing damage levels in the Engineering Masonry Model (EMM) variations but showed more limited improvements in the Total Strain Crack Model (TSCM). Additionally, the approach allowed for an investigation into the influence of material properties, revealing that Young's Modulus and tensile strength were the most influential parameters across both models. Furthermore, the results indicated that the influence of material parameters is highly non-linear, meaning changes in material properties do not always lead to predictable outcomes. Instead, specific combinations of parameters had a greater impact on reducing damage, demonstrating the complex interplay between material properties particularly in the EMM model variant.