The transition to more sustainable energy has led to a growing demand for offshore wind energy, necessitating larger structures and heavier foundation piles. During pile installation this increases the risks of uncontrolled pile run, which can have fatal outcomes and project delays. Offshore superstructures predominantly rely on largediameter open-ended driven piles. Intermediate soils pose significant challenges in determining soil resistance during driving and pile run, with calculations typically performed using Static Soil Resistance to Driving (SRD) methods. The Alm & Hamre method is preferred for deep foundation piles in mixed soils due to its inclusion of friction fatigue.
The goal of this research with corresponding research objective is to improve pile run velocity and trajectory predictions for offshore open-ended pile installation in intermediate soils. This objective is reached through research on drainage state, identifying soils susceptible to a shift in this drainage state, and analyzing velocitydependent resistance for CPT and pile velocities. The findings are then incorporated into a modified SRD model. The results are compared to a case study using CPT and borehole data as input, and installation video’s and driving data as validation material.
Key findings indicate that with increased pile velocity the drainage state of several soils can shift towards the more undrained spectrum and therefore the soil will have a smaller soil resistance. These soils with a lower soil resistance during pile installation velocities then predicted include intermediate soils such as silt, sandy silt, and silty clay. Thin alternating layers of sand, clay, and silt are also likely to experience a shift in drainage state. Later silty sand is identified as a soil with a high possibility of being prone to such drainage state shifts.
The SRD method, incorporating velocity-dependent resistance, predicts pile run 31% more accurate than models without this consideration. By including velocity-dependent resistance drops, the model accounts for the changes in soil resistance that occur during pile run, leading to more accurate predictions compared to the standard SRD model. The model used in this research uses a single SRD update for velocity dependent resistance. However, in scenarios with large pile runs trajectories and high pile velocities, or when a substantial portion of the soil is prone to a drainage shift, performing a single update for velocity-dependent resistance will not result in a converged solution. As such for a correct solution, multiple iterations are necessary.
When the model predicts a deeper Self weight penetration depth than observed, the predictions for pile run initiation are not reliable. Given that pile run initiation can be very delicate, further research is needed for locations with CPT and borehole data directly beneath the pile. Additionally, incorporating hammering parameters, such as the added weight due to hammer momentum, should be explored to improve these predictions.

Arribadas, a phenomenon of mass nesting behavior of sea turtles, attract millions of olive ridley turtles (Lepidochelys olivacea) to Playa del Ostional, a nesting beach in Costa Rica. The timing and size of these arribadas are influenced by various environmental factors, including temperature, tides, and moon phase [1]. The sea turtles are threatened by a variety of factors, like amongst others climate change.
Rising temperatures and sea levels, changes in ocean currents, and more frequent and intense storms are all likely to have negative impacts on sea turtles [2]. Without intervention, climate change could lead to the disappearance or flooding of sea turtle nesting beaches, resulting in a loss of critical habitat for these creatures. To prevent such an outcome, it is imperative to gain a deeper understanding of the morphological and hydrodynamic characteristics of nesting beaches, as well as identify the factors that influence sea turtle nesting behavior.
This study aimed to identify and map the critical factors that must be considered to ensure persistence of the olive ridley sea turtle and arribadas at Playa del Ostional, Costa Rica. The objectives of this research were, therefore, (1) to map the seasonal morphological and hydrodynamical differences of the arribada nesting beach, (2) to identify the environmental parameters that have the greatest influence on the occurrence of an arribada, and (3) to map out the stakeholders involved. The study site is the beach that ranges from the northernmost part of Playa del Ostional down to the southernmost part of Playa Nosara, which is located on the northern peninsula at the west coast of Costa Rica. The part at Playa del Ostional where most turtles nest is called ‘Main Nesting Beach’ (MNB). A field investigation was carried out to determine the seasonal morphological and hydrodynamical differences of the nesting beach. This field study comprised of two distinct components: (1) a characterization of the morpho- and hydrodynamics of Playa del Ostional in the dry season, and (2) a comparative analysis of these conditions during the wet and dry season. The morpho- and hydrodynamic beach characteristics consisted of the beach profile, sediment composition, hydrodynamic properties and other general environmental characteristics, such as vegetation and nearby rivers. The beach profile was measured by walking transects perpendicular to the shoreline using RTK-GPS equipment. Moreover, a drone was flown that made an orthophoto and collected 30 million data points. The difference in sediment composition was analyzed by obtaining sediment samples in the dry season, sieving these and comparing the obtained particle size distributions and D50 values of the dry and wet season. The hydrodynamical properties and the other general environmental characteristics are analyzed by means of literature review, observations and photography. In order to identify the environmental parameters that have the greatest influence on the occurrence on an arribada, an autoregressive logistic regression model was used. The model that was made the previous research of 2022, was updated and automated. Also, design choices of the model were made and new data was added.
To map out the stakeholders, interviews have been conducted and a stakeholder map was created. Through the use of GPS transects the beach profiles taken in dry season (February 2023) were compared to wet season (October 2022). To tackle normal spacial variance the comparison is done through the calculation of averages on three beach stretches with equal characteristics. Main findings were that beach width is equal in both seasons, slopes are more gradual in dry season, beach plateaus are on average 3.0m wider in wet season. Crossing rivers do not influence the beach profile below waterline in the dry season. For more river characteristic more offshore research is needed. The sediment composition of the beach turned out to show significant differences between the dry and wet season. A significant difference is present in D50 values between the dry and wet season for almost all sediment samples. Moreover, during the wet season, the sediment tends to be coarser compared to the dry season. Additionally, during the dry season, coarser sediment tends to accumulate at the top of the slope, whereas during the wet season, coarser sediment accumulates near the waterline. These observations suggest that coarse sediment may move from areas close to the waterline to the submerged part of the slope over time. This behavior implies that sediment transportation is affected by the seasonal fluctuations in wave energy. The findings altogether indicate that the sediment composition at Playa del Ostional, particularly at Main Nesting Beach, is notably affected by seasonal changes. The impact is more pronounced from the low tide waterline to the high waterline’s end at the top of the slope, with a particular emphasis on the low tide waterline. The wave climate surrounding Playa del Ostional is expected to be less turbulent, with lower wave energy during the dry season. However, the exact distinctions in both wave climate and tidal surroundings between the two seasons cannot be ascertained due to inadequate data availability.
The different stretches of Playa del Ostional demonstrate notable differences in environmental characteristics during the wet and dry seasons. The majority of rivers that flow out during the wet season are absent during the dry season. In addition, a beach scarp appeared during the dry season and not during the wet season, and an estuary that was observed in the dry season was not reported during the wet season research. On the other hand, the beach is mostly surrounded by vegetation in both seasons, with comparable grass and trees. Moreover, no significant difference in wildlife presence was observed between the dry and wet seasons at Playa del Ostional.
The autoregressive logistic regression model was trained on five year of arribada data and 116 individual environmental parameters. The weights of the parameters were plotted and analysed in multiple groups. This resulted in six parameters with the biggest influence: pdTIDE_P1, pdTIDE_mf, pdVELOCITY_IHC_rho, pdVELOCITY_IHC_rho, Mooncycle_third and Moon_v. The maximum probability of an arribada occurring during a certain day was 80%.
By conducting interviews and conducting a stakeholder analysis, the degree of awareness about climate change is assessed and mapped out, which appears to be quite high. The residents of Ostional are aware of the changes and willing to work in new projects. Moreover, the analysis showed that it is important to engage with two key stakeholders: the Refugio Nacional de Vida Silvestre Ostional and CITES.