Ultrosonic pulse-echo testing is gaining increasing attention for its feasibility, accuracy, and versatility in structural examinations of concrete constructions. A1040 MIRA 3D PRO is an emerging low-frequency pulse-echo ultrasonic tomography device. Developed in 2021, this device is claimed to be suitable for manual and automated concrete structure assessment with the help of its functions, such as 3D-TFM (Total Focusing Method)/FMC (Full Matrix Capture) imaging. However, both its capacity and limitations need to be investigated in more detail. In this thesis, experiments are conducted first on a 2D concrete structure to examine the data acquired when the transducers are working in linear configuration and matrix configuration (array modes). Then, measurements were carried out on a 3D concrete structure to check the 3D properties of the device with the help of the data processing software InterSAFT. The results show a good correspondence between different array modes and that 3D SAFT could visualize 3D structures in an adjacent position. The data recorded at a greater distance was overlaid by noise, which is attributed to the fact that the frequency of the ultrasonic waves was set too high. Finally, further experiments on frequency calibration, data comparison, and measurements on more complicated specimens were suggested for future research on MIRA 3D PRO.

In recent years, the area of structural engineering has found new interesting prospects in the theory of waves. The acoustoelastic properties of materials are utilized in a new promising structural health monitoring (SHM) technique. The propagation of ultrasonic waves through stressed elements gives the ability to find invaluable information on the stress-state of the concerned element. This information is then analyzed with the use of Coda Wave Interferometry (CWI). This technique explores the late arrivals of the wave field, which is referred to as the coda. Due to scattering of the waves through heterogeneous elements, this part of the wave field holds additional information compared to the early arrivals, which makes it very suitable for application on concrete elements.
The use of ultrasonic waves with CWI in concrete elements has been studied enthusiastically by engineers due to its promising prospects. Nevertheless, this technique is still developing both in theory and in practice. The majority of previous similar studies have been conducted in laboratory settings, and thus conditions are very controlled. In this study, the monitoring technique is applied in conjunction with Smart Aggregate (SA) to a concrete structure for practical use. The SA sensors are positioned in groups at key location in the first concrete cast of a cast-in-situ prestressed concrete bridge, which entails two bridge spans of approximately 30 meters length. Measurements are done at different phases during the construction of the bridge, when the stress-state at the positions shifts due to change in loading and boundary conditions. The resulting data is analyzed with CWI and subsequently evaluated whether it coincides with expectations. Deviations from these expectations are rationalized or an attempt thereof is made.
The results show significant differences between field measurement results and expectations based on laboratory tests. These differences are explained by the presence of a greater amount of parameters, which influence the data gathered from field measurements. With the appropriate measures, the various factors acting on the structure are isolated and subsequently validated with laboratory data. The most prominent factors affecting the acoustoelastic properties of the structure are established to be time related. These factors involve concrete shrinkage, creep deformation and the concrete hydration process. With laboratory testing the effect of these factors on the wave propagation velocity are determined. By taking into account the additional factors, a strong correlation between changes in the stress-state and changes in the wave propagation velocity is observed when the data is read in an adjusted manner.
With a proper protocol, the use of smart aggregates in combination with CWI could be very valuable in accessing concrete structures on-site in both its construction stage and service stage. As it stands, prerequisite knowledge of the monitored structure is necessary to make use of the full potential of the SHM involving CWI and SA. The demand for prerequisite knowledge of the structure increases as the monitored structure becomes more complex, because it increases the amount of additional endeavors required to properly asses the acquired data. As such, the discussed monitoring technique in its current stage of development generally has low accessibility for practical use. But with further research and more understanding of monitoring method, the discussed SHM technique might be applicable for general use in the near future.

The recent discovery of the Zama field in offshore Sureste Basin in the southern Gulf of Mexico has piqued interest in the Mexican petroleum industry regarding the hydrocarbon potential within the region. In this study, a deposition-only thermal model was developed in an area of interest (AOI) in this region. Using structural input obtained from seismic interpretation conducted in Petrel©, the model was constructed and simulated in PetroMod© to acquire initial estimates of the maturity of the Tithonian J100 source rock in the AOI in terms of the maturity parameters Vitrinite Reflectance (%Ro) and Transformation Ratio (TR). A one-at-a-time (OAT) sensitivity analysis approach was also undertaken to assess the impact of uncertainties in some inputs in isolation on the output maturity in order to identify key uncertain input parameters. Based on the modeling results, at the C-1 well location of interest within the AOI, the source rock was simulated to be within the wet gas generation window based on simulated %Ro values in the present, having emerged into oil window between 41 - 27 Ma (late Eocene-Oligocene) and into the wet gas window between 6 - 0.5Ma (late Miocene-Pleistocene). Across the wider AOI, present-day %Ro values indicate the predominant presence of late oil to wet gas generation windows, with most of the source rock across the AOI having emerged into the oil generation window between 23 Ma and 11.6 Ma (early to middle Miocene). The highest uncertainties in simulated %Ro values were associated with uncertainties in the Bajocian (J60) autochtonous salt sequence thickness distribution and with the maturity models used for model simulation. At the C-1 well location, TR values of 95% to near 100% in the present indicate that most of the kerogen (source rock organic matter) has already been converted into hydrocarbons, with kerogen conversion initiated between 55 - 48 Ma at the location. Across the wider AOI, average present-day TR values in the range of 81 - 97% were simulated. The highest uncertainties in simulated TR values were also associated with uncertainties in the Bajocian (J60) autochtonous salt sequence thickness distribution, and with the source rock maturation kinetics input used for model simulation. The timing of maturation of the J100 source rock at the C-1 well location - assumed to have been constrained by the OAT sensitivity analyses results for simplicity - in relation to the timing of other petroleum system elements and processes indicated by literature, suggests that hydrocarbon accumulations charged from the Tithonian source rock in the reservoir intervals in the well vicinity are possible i.e. presence of hydrocarbon accumulations cannot be ruled out based only on maturation timing considerations.

The Dutch infrastructure counts many bridges, the majority of which are built in concrete. These bridges have been designed and constructed according to safety codes. A lot of these bridges date from the previous century and have been designed conform outdated safety codes. Therefore, the main problem
of these bridges is the uncertainty with regard to their structural health as well as their performance under the current loading conditions.
The application of ‘smart aggregates’ could potentially solve these issues. Smart aggregates refer to a network of sensors that emit and receive wave signals inside the concrete structure. These sensor are embedded within the concrete and can be implemented in both new and existing structures. The
changes in the medium with regard to the stresses are reflected by the phase changes of the wave signal measured by the smart aggregates. This information allows for the monitoring of the conditions of the bridge during its lifespan. The magnitude of the stress in certain parts of the structure could then indicate the need for maintenance at an early stage, thus preventing unnecessary maintenance while preserving the safety of the bridge. This method, however, requires a thorough understanding of the wave propagation inside a concrete medium subjected to a stress state. This thesis investigates how the relative wave-velocity change of a concrete-like medium is influenced by the stresses to which it is subjected. Throughout the report this relation is referred to as the acoustoelastic effect. The first part of the thesis is centered around the theoretical formulation of the acoustoelastic effect. During this study, the models of Murnaghan and Biot have been studied. Subsequently, their differences with respect to the fundamental assumptions have been indicated. Here, it has been found that the main difference between the two models is demonstrated by the way they regard the second-order deformation terms. Murnaghan assumed that these terms are significant and has included them in the constitutive relation. From the latter, Hughes and Kelly have derived expression for wave velocities of a stressed medium, which have been verified with experimental results. On the other hand, Biot adopted the theory of infinitesimal deformations which omits the second-order deformation terms. In addition he based his theory around the wave propagation of a bending rod and extended this model to a three-dimensional medium subjected to initial stresses. This generalisation of an approximated model has led to analytical expressions for the wave velocity of a stressed solid which are contradicted by experiments. From this comparison, it has been concluded that Murnaghan’s model results in the most accurate representation of the acoustoelastic effect.
The second part of the thesis focuses on the verification of the theoretical acoustoelastic effect through experimental research. For the purpose of verifying the acoustoelastic effect as well as determining the third-order elastic coefficients of a concrete-like medium, four specimens have been tested.
In order to investigate the influence of the inhomogeneity of the material on the changes in the wave velocity, two different material compositions have been investigated. The first type consists of a homogeneous cement paste, whereas the second type represents heterogeneous concrete including
aggregates. During the experiment, the different waveforms have been repeatedly emitted through a specimen subjected to an uniaxial compression. The relative wave-velocity change has then been obtained by post-processing the acquired data, which has been compared with Murnaghan’s model.
The conclusion of this research is that Murnaghan’s theory can be used to accurately predict the relative wave-velocity changes of the cement-paste specimens, and in particular the relative P-wave velocity changes. The results have shown that the radial recordings yield inconsistencies which can be attributed to the small dimensions of the specimens. Furthermore, the influence of the inhomogeneity of the material on the relative wave-velocity changes manifests itself through a discrepancy in the acoustoelasticity.
Here, it is found that the ratio between the aggregate size, the specimen dimensions and the wavelength of the signal determines the sensitivity to the acoustoelastic effect. Therefore, before the data from the smart aggregates embedded in a real structure can be interpreted, the experiments need to be improved and expanded. It is important to investigate the acoustoelasticity of waves with non-orthogonal propagation and particle-oscillation direction, while applying various stress states to the medium. This is because the smart aggregates are arranged in a network, where the signals are emitted signals are propagating through the structure via arbitrary paths between various transducers.

The continuous accumulation of solid waste has posed a great threat to the environment of our future generations. A novel approach that is currently under development is to treat the waste collected in an engineered landfill in order to reduce the emission potential to an environmentally acceptable level. The main topic for this research is to improve the understanding of how leachate is distributed throughout the landfill Kragge and how this distribution varies in time. This is important for identifying the long-term behavior of the landfill and for managing landfill waste.

At the start of this project, we have a number of water level measurements obtained from various wells in the landfill. Straightforward spatial interpolation of this data leads to unexpected results. Most likely this is caused by the highly complex heterogeneity in this porous system. For this reason, this research aims to apply Electrical Resistivity Tomography (ERT) technology to explain the water distribution variations between wells. The apparent resistivity along several lines are measured over depth using different arrays. Some scripts written in Python with 'pyBERT' and 'pyGIMLi' packages are used to get electrical resistivity inversion results from the apparent resistivity. It is known that the decrease in the water content leads to a significant increase in the resistivity. Therefore, the possible existence of saturated and unsaturated blocks in the waste body can be visualized from the inversion maps.

Initially, the interface between the saturated and unsaturated zones is expected to be identified from Laplacian edge detection, while the results indicate that this technique fails to represent the area boundaries under highly-heterogeneous situations. Subsequently, Archie's law and van Genuchten equation are coupled to give a relation between the resistivity and water pressure head. Archie's law is used to compute the resistivity from water content and van Genuchten equation is used to compute the water content from the water pressure head. There are two hypotheses during this analysis: (a) where the resistivity is 20(ohm-m) gives the interface of dry and wet zones; and (b) the landfill leachate is under hydrostatic condition. Then the water pressure head is the distance from the interface, which can be read from the inversion maps. By selecting a certain range of empirical parameters, the computed resistivity-pressure head curves provide relatively good fits to the measured results.

This research has demonstrated the applicability of a DTS system to estimate the volumetric water content in saturated mud material. 2 samples of synthetically generated mud and 1 sample of natural mud from the port of Rotterdam were investigated, first by conventional methods and subsequently also with DTS. The system set-up and heating strategy were optimized by testing with different media (air, water) and with different FO coil diameters. A step-by-step approach was then designed to translate the thermal response recorded in the muds into volumetric water contents. Early- and late- time cutoffs were applied to the slope selection procedure (∆T vs ln(t)), and a mud dependent correction factor was applied to obtain the effective heat flux. The average VWC’s (ϴ) subsequently derived from the DTS data were in good agreement with those obtained by conventional methods (core sampling); the standard deviation in the VWC’s (ϴ) of all three tested muds was between 0.030 and 0.040 m³/m³. For saturated conditions, Sayde et al. (2010) and Striegl and Loheide (2012) published larger standard deviations of 0.046 m³/m³ and >0.050 m³/m³ respectively. The approach detailed in this investigation has enabled DTS to perform as a guideline on the continuous volumetric water content profile in saturated muds.

Considering the inherent uncertainty of structural geological models, the non-uniqueness of geophysical inverse problems, and the growing availability of data, there is a need for methods that combine different types of data and allow for updating knowledge in a consistent way. By making use of the development of efficient, gradient-based MCMC algorithms, probabilistic inversion provides a tool for this. To test to what extent we can reduce the uncertainty of an initial geological model, we integrate geological modelling into a Bayesian inverse framework. Additional information can then be included in this inverse framework through likelihood functions.
The proposed methodology is tested on a geological model of the structurally complex Kevitsa deposit in Finnish Lapland. By starting with an initial interpretation-based 3D geological model, we define the uncertainties in our geological model by means of probability density functions. Magnetic data and geological interpretations of borehole data are used to define geophysical and geological likelihoods respectively. To use the magnetic data in the inference, the mathematical description of the magnetic forward calculation is implemented for a 3D voxelised space, linking the geophysical data through magnetic rock properties to the uncertain structural parameters. The result of the inverse problem is presented in the form of probability distributions and ensembles of the realised models through visual analysis. The former is a statistical consideration of the results, whereas the latter is a visual representation for direct interpretation in a geological sense. The uncertainties in these visual representations are best presented by means of information entropy, which allows for a quantitative analysis. The results show that well-defined likelihood functions can reduce uncertainties in geological models and build on the complementary strength of different types of data. Where probabilistic inversion inherently provides uncertainty analysis, finding a single representative solution is less trivial. Therefore we conclude that the strength of the used methodology mainly lies in data integration and uncertainty quantification.

The multi-pole PML (MPML) is tested on models that simulate seismic waves traveling through the subsurface. Using a recursive integration technique a stretching function consisting of the sum of multiple stretching functions is implemented in the velocity-stress finite difference time domain wave equations. The MPML is implemented in both the rotated staggered grid (RSG) and the Virieux grid. The performance of the MPML is tested on a square model, rectangular model and a rectangular model with a free-surface and compared to other types of PML’s implemented in these models. The main result is that the MPML can be implemented in the velocity stress wave equations giving stable results similar to other PML types.

This thesis is part of a longer series of research into the use of geophysical methods for inves-tigation for forensic purposes, a collaboration between the Delft University of Technology (TU Delft) and the Netherlands Forensic Institute (NFI). In this investigation, the difference between a grave containing a human body and a refilled empty pit is explored at the Amsterdam Research Initiative for Subsurface Taphonomy and Anthropology (ARISTA) facility, using common-offset GPR data collection. In addition, common-offset data is gathered at a test site at TU Delft, in order to redefine the locations of previously buried targets. Multiple-offset GPR datasets are also col-lected at both sites, one of which is processed using electromagnetic interferometry (EMI) and adaptive subtraction (AS) in an attempt to remove direct waves.
The positions of the targets at the TU Delft site were redefined, but with some questions as to whether the site has been altered in the past year without the knowledge of the author. High lev-els of interference in the ARISTA facility data due to close proximity to various metal and plastic objects makes it difficult to determine the true differences caused by the presence of the cadaver. The author suggests using a 500-MHz antenna for further investigations at the site due to high wave velocity which leads to a low resolution when using a 250-MHz antenna, and due to more homogeneous soil at the ARISTA facility. The optimal procedure for EMI+AS is discussed, and sug-gested to be the use of a bandpass filter to remove very high and low frequencies from the raw data prior to EMI. The method is shown to be reasonably effective, especially when the data is strongly impacted by the presence of direct waves, where simply topmuting the data would re-move too much information. A script was prepared in MATLAB which has been optimised for the application of EMI to GPR data, and further scripts were prepared for use in Seismic Unix for the purpose of AS, in the hopes that others may find these a useful beginning to further applications of this method.

We use ground and space geodetic data to study surface deformation and gravity change at Kīlauea volcano from January to September 2015. This period includes an episode of heightened activity in May 2015, which we refer to as ’the May 2015 event’. The data set consists of Global Navigation Satellite System (GNSS), tilt, visual and seismic time series along with 25 descending and 15 ascending acquisitions of the Sentinel-1a satellite in Interferometric Wide swath mode and microgravity surveys taken a few years before and just after the May 2015 event. We identify four different stages of surface deformation and volcanic activity during the May 2015 event which we attribute to the movement of magma and pressure changes in response to a magma supply and withdrawal imbalance in the shallow plumbing system. In particular, we model the deformation sources attributed to the Halema’uma’u reservoir (HMMR) and South caldera reservoir (SCR). The SCR was best described by inflation of a spheroidal at 2.8 (2.65-3.07) km depth below the Southern caldera region. The HMMR source was modelled by a point source deflation located East of the Halema’uma’u crater at 1.5 (0.95- 2.62) km depth. The surface microgravity changes which would result from changes in these reservoirs are significantly lower than the actually observed microgravity changes. We attribute this to the lack of complexity of the single point source model used. Mechanisms that add/remove mass from the subsurface without accompanying surface deformation, which are not part of the point source model, played a significant role. More frequent microgravity campaign surveys, if needed with a smaller network, are the only way to improve our understanding of these processes and help to quantify them.

The distinct feature of UHPC is the tensile strain hardening phenomena and high compressive strength. We can either use this potential as an additional safety margin in structures or design structures with no passive reinforcement.
The advancements in active structural health monitoring devices have opened further possibilities to validate the performance of this material. One such device is the Smart Aggregate (SA). Smart Aggregates are piezoceramic transducers capable of sending and receiving ultrasonic waves. From basic wave theory, we know that elastic waves capture the properties of the medium through which it propagates. We can use this phenomenon to study the damage inside UHPC. This is accomplished by studying the changes in velocity and peak amplitude of an elastic wave as it propagates through the loaded specimen.
This thesis has two main objectives. First, a modified tension test is developed to determine the uniaxial-tensile behavior of UHPC specimen. Second, embedded smart aggregates are used to send and receive elastic waves inside the UHPC specimen subject to modified tension test and the wave parameters such as velocity and peak amplitude are studied. The propagation of elastic waves in UHPC specimen with steel fibres is understood from this experiment. A relationship is established between velocity of the elastic waves versus average strain and peak amplitude of the elastic waves versus average strain. The results obtained could serve as basic knowledge required to conduct elastic wave tomography.
In short, this thesis explores the possibilities of using SA to detect damage in UHPC and whether it can be used as an additional safety measure in active structural health monitoring. Although the huge potential of Ultra-High-Performance Concrete is apparent, considerable effort is required before we can realize safe habitable structures using it.

Full-waveform inversion within a deterministic framework commonly uses gradient-based methods to minimize a least-squares error function. Due to the non-linearity of the problem, this function has several local minima. To avoid them, it is necessary to start the optimization procedure from a good initial model. Within a probabilistic framework, Markov Chain Monte Carlo methods are used to sample a probability density function that represents the possible solutions. In high-dimensional problems, traditional MCMC methods become inefficient as random transitions are unlikely to find the regions of high probability. Hamiltonian Monte Carlo appears as a method that can efficiently find these regions without spending computation time on regions of no interest. To evaluate the probability of a sample, the least-squares error is calculated. Synthetic data is obtained through an existing 2D frequency domain full-wave
modelling code and compared to the observed data. Through the Hamiltonian Monte Carlo sampler, the high probability regions are sampled and used to build the probability density function that represents the possible solutions. The algorithm was tested with both synthetic and real data. For the synthetic case a 1D model was inverted. The normalized least-squares error was reduced by 98%. In the deepest section the true model lies outside the uncertainty range of the estimated model. This appears as the result of sampling narrow regions
of the probability density function. Then, the variance of the samples is underestimated and therefore the error. For the real dataset, a 2D model was inverted. This model lacks some of the large-scale features compared to deterministic full-waveform inversion results. However, a good model was found without any a priori information and almost any manual intervention. This suggest that, at least for the studied example, the algorithm can provide a
good starting model for deterministic full-waveform inversion. The results obtained through this approach are almost identical to those obtained with more labour intensive adjustments.