ABSTRACT Offshore wind power technology presents a viable solution to address significant challenges related to energy and climate change. Moreover, it has the potential to stimulate economic growth and create employment opportunities. Considering Türkiye's favourable geographical location and extensive coastline, the integration of offshore wind power stands as a pivotal factor in helping the country attain its energy targets from 2035 to 2053. There are currently no installed offshore wind turbines (OWTs) in Türkiye; however, the Turkish Ministry of Energy and Natural Resources has delineated three development zones in the Sea of Marmara for the installation of OWTs. With the commencement of developments in these specified areas, strategic plans aim to increase the installed capacity of OWTs. This study is an attempt to evaluate possible and plausible locations of wind turbine installation within Turkish maritime boundaries, which are estimated to have a high potential for offshore wind energy. Moreover, types of foundations supporting OWTs along with their associated design criteria are enlisted. Considering Türkiye's position in a seismically active region, an overview of seismic hazards is summarized, and the impact of relevant seismic hazards on foundations is discussed. It should be emphasized that, despite the drawbacks due to tourism and international seaborne traffic, Türkiye, having a population more than 85 million, has a great wind energy potential, which needs extensive and meticulous assessment for a sustainable future.

Significant duration is a key descriptor of shaking that governs the number of cycles in effective stress analyses used in liquefaction triggering and other dynamic geotechnical assessments. Because rock stations are commonly treated as reference conditions for seismic input selection, a rock-site-focused duration model can reduce ambiguity introduced by site amplification and basin effects. This study explores data-driven relationships between significant duration (D5 ‐ 95) and commonly used ground-motion metrics using strong-motion recordings from 59 stations located on rock units (NHRP class B, Vs, 30 ≥ 760 m/s) in Türkiye. Artificial neural networks (ANNs) were developed in two stages: a baseline model using moment magnitude (Mw) and rupture distance (Rrup) to support rapid, scenario-based applications, and an enhanced model incorporating Arias intensity (IA), cumulative absolute velocity (CAV), peak ground acceleration (PGA), and peak ground velocity (PGV) to capture record-specific shaking characteristics. The ANN framework successfully reproduces the expected increase of D5, 95 with Rrup and highlights region-dependent behavior at larger distances. Adding intensity- and velocity-based predictors improves predictive skill, and sensitivity analysis indicates that CAV exerts the strongest influence on D5 ‐ 95 among the examined motion parameters. The proposed models provide practical tools for selecting and scaling rock-site inputs and for incorporating duration effects into liquefaction-oriented and site-response workflows.

The significant duration (D5,95) is an important parameter in geotechnical earthquake engineering, directly influencing the number of cycles in effective stress analyses and playing a pivotal role in evaluating soil liquefaction potential. Liquefaction susceptibility is dependent on the number of cycles, which is inherently related to the duration of the earthquake and the response of the soil. In dynamic site response analyses, ground motions recorded on rock sites are essential because they serve as the excitation input, minimizing site-specific effects such as amplification or valley influences. Consequently, the significant duration of these rock-based ground motions becomes a fundamental parameter in evaluating liquefaction and selecting ground motions for site response analyses. However, existing duration models are predominantly regression-based ground motion prediction equation (GMPE) formulations calibrated on mixed site conditions, and predictors trained exclusively on rock-station recordings using artificial neural networks (ANNs) remain scarce. In this regard, the relationships among significant duration (D5,95) and key seismological and intensity measures were investigated within an ANN framework using a rock-site dataset compiled from T & uuml;rkiye Strong Ground Motion Database (1208 records from 143 earthquakes with moment magnitudes (Mw) >= 4.5) recorded at 59 stations established on rock units (NEHRP class B or harder rock, Vs,30 >= 760 m/s) (AFAD, 2023). Two complementary models were developed: a baseline ANN using (Mw, rupture distance (Rrup), and Vs,30)and an enhanced ANN additionally incorporating peak ground acceleration (PGA) and cumulative absolute velocity (CAV). The enhanced model yields improved predictive performance and tighter residual dispersion relative to the baseline model. Sensitivity analysis indicates that CAV is the most influential predictor of D5,95, followed by Rrup and PGA, highlighting the dominant role of cumulative/energy-related measures under rock-reference conditions. These results provide a practical two-tier framework for estimating rock-site significant duration in T & uuml;rkiye, supporting duration-aware motion selection and nonlinear geotechnical analyses.

This study presents an assessment of geotechnical damage observed in Gölbaşı District in the Adıyaman Province after the southeastern Türkiye earthquake sequence on February 6, 2023. Preliminary reconnaissance indicated the presence of soil ejecta with a plasticity index typically higher than nine, questioning the role of flow liquefaction during these events. Detailed observations revealed various types of damage, including major ground settlements up to 60 cm near several buildings, substantial cracks in highway sections, undulations in railway tracks, and observable fissures on roads and pavements. Given the predominance of plastic soils underlying the city center and the malfunction of strong motion station 0208 in Gölbaşı, the underlying cause of such widespread damage remains a complex phenomenon. Therefore, to unravel the principal cause of damage, this study conducted a detailed analysis of the geotechnical properties of soils. An extensive laboratory testing program, in combination with original interpretation of in-situ tests performed before and after the earthquake sequence enabled accurate characterization of properties of the underlying soil profile. The primary factors contributing to the extensive geotechnical damage in Gölbaşı are identified along with the main failure mechanisms, focusing on the role of cyclic softening of the predominantly fine-grained soils rather than flow liquefaction.

The residual friction angle is an important parameter in soil mechanics, since it is a widely used parameter in long-term stability analysis and a fair descriptor of post-failure strength. In this regard, a database was constituted including Atterberg limits, clay fraction, effective normal stress and residual friction angle. Relationships among the above-mentioned parameters were investigated, and an empirical equation for estimation of tangent of residual friction angle based on effective normal stress and coefficients depending on Atterberg limits was proposed. Later, relationships between residual friction angle and toughness limit; residual friction angle and a combined index parameter based on clay fraction and toughness limit were obtained. Finally, back-propagation neural networks and sensitivity analyses were employed to find out the best combination of inputs, for prediction of residual friction angle. These methods are capable of estimating residual friction angle by use of toughness limit, with a high accuracy.

It is well known that plasticity characteristics are one of the most important factors controlling the engineering behavior of fine-grained soils. In this regard, Atterberg limits are used for evaluation of plasticity and strength behavior of soils. Of all the plasticity identifiers, fall cone flow index, which is the slope of the flow curve is a descriptor of plasticity and undrained shear strength characteristics of cohesive soils. On the other hand, toughness limit is also efficient in prediction of many index properties of soils including plasticity characteristics, compression index as well as residual friction angle. This study is an attempt to establish relationships among fall cone flow index and consistency identifiers of fine-grained soils. Emphasis is given on toughness limit, which is believed to be a practical and efficient approach in assessment of fall cone flow index. Regression-based equations establishing relationships between fall cone flow index, plasticity index, plasticity ratio, toughness limit and liquid limit were presented. Besides, the efficiency of artificial neural networks in prediction of toughness limit and fall cone flow index was investigated. It should be noted that established relationships using regression equations are based on regional data, which come up with coefficient of determination (R2) values ranging between 0.706 and 0.978. On the other hand, ANN models were used to model global data, R2 values were obtained to be between 0.586-0.972 and 0.522-0.889 for training and testing phases, respectively. Relationships concerning local and global data were presented, along with analysis of effectiveness of application of relationships established for analysis of global data.

Measurement or prediction of compression index ( C c ) of soils is essential for assessment of total and differential settlement of structures. It is a well-known fact that this parameter is controlled by several index identifiers of soil including initial void ratio, Atterberg limits, overconsolidation ratio, specific gravity, etc. Many studies in the past proposed relationships for prediction of C c based on different index properties. Therefore, this study aims to present a comparison of previously proposed equations for estimation of C c . Data from literature was compiled, and a total of 90 and 623 test results on remolded and undisturbed specimens were used to question the validity of previously proposed equations. Nevertheless, the modeling ability of 7 and 12 equations for estimation of C c of remolded and undisturbed soils were questioned by use of compiled data. Moreover, new empirical relationships based on initial void ratio and toughness limit for prediction of C c was proposed by use of nonlinear multivariable regression and evolutionary based regression analyses. The results are promising -the performances of models established are quite acceptable, which are verified by statistical analyses.

Earthquakes cause cyclic shear deformations in soil and build-up of excessive pore water pressure as a result of undrained loading, accompanied with rearrangement of soil particles and degradation in stiffness of the soil due to decrease in effective stresses. During loading, the onset of soil liquefaction is defined as a stress state in which the excess pore water pressure is equalized to the total stress. From this point of view, assessment of the pore water pressure development pattern under cyclic loading has been one of the most salient research topics in geotechnical and earthquake engineering. In this study, results of a series of cyclic triaxial tests on non-plastic silt specimens consolidated under 100 kPa effective isotropic consolidation pressure were used to question the modelling ability of pore pressure development models previously proposed for sands. Tests were performed on specimens of 6 different initial relative densities (Dr) ranging between 30-80% and 10 different cyclic stress ratios (CSR). The key parameters of pore water pressure development and shear deformation in the energy-based model used are relative density, cyclic stress ratio and number of cycles. The results revealed that, these energy-based models have a strong potential in evaluation of pore water pressure development pattern of non-plastic silts. Test results also show that the increase in relative density and decrease in CSR causes a ladderlike behavior among pore water pressure and cyclic shear strain, which is relevantly rendered by energy-based models.

On February 6th, 2023, southeastern T & uuml;rkiye was shaken by two catastrophic earthquakes, close to northwestern Syrian border. The first earthquake (Pazarc & imath;k) occurred 45 km west of Gaziantep at 1:17:32 (UTC), with a shallow strike-slip faulting at a depth of approximately 8.6 km and a moment magnitude (MW) of around 7.7. The second event (Elbistan) took place 9 h later, 66 km north-east of Kahramanmaras, city center, also with shallow strike-slip faulting at a depth approximately 7 km and an MW of around 7.6. Turkish authorities reported a death toll of over 59,000 in T & uuml;rkiye and about 8500 in Syria. The destructive effect of the earthquake resulted from widespread strong ground shaking, a rupture length exceeding 300 km, causing collapse of a large number of buildings. The catastrophic destruction of the built environment was accompanied by a range of other earthquake-related effects, including fault ruptures, landslides, and soil liquefaction. The aim of the study is to analyze the distribution of ground motion and their relationships with the observed damages for the two events. Spectral accelerations of key importance were assessed across a large area in the southeastern part of T & uuml;rkiye. Notably, these accelerations were generally much higher than existing design spectra. A significant correlation between the observed concentration of damage and the significant amplification of motion induced by local soil conditions (such as soft soils and valley effects). The distinct tectonic structure of the region could be the main reason for the high amplification in the valleys (associated with basin effects), even at large distances from the epicenter, especially in correspondence with the bidimensional grabentype geological structures. The investigation delved into the analysis of four specific regions in detail: Antakya and Hassa (both in the Hatay province), Kahramanmaras, and Goksun. Notably, the observable valley effects were found to play a significant role and could account for the significant damage observed in these regions.

In geotechnical engineering, the precise evaluation of compaction parameters is essential for quality control assessment. One option is the use of the toughness limit (TL), concisely defined as the water content, at which the behaviour of fine-grained soils evolves from an almost adhesive-plastic to tough-plastic. A database consisting of more than 1000 test results, including the compaction characteristics and Atterberg limits, was compiled to establish correlations between the TL, Atterberg limits, optimum degree of saturation, and compaction properties. The results revealed that the TL has the potential to evaluate many indices and compaction identifiers for different types of soils.

Prediction of the ultimate settlement is vital for the assessment of the service life of a structure, particularly when it is underlain by fine-grained soils. As known, this value is a function of the compression index (Cc) of soils, which can simply be found by performance of oedometer tests. For this purpose, more than 2000 test results from past studies were compiled to constitute a database. Then, multiple linear regression analyses were employed to predict the Cc parameter by use of toughness limit (TL) and a function of this parameter, namely the soil state index (SSI). It was noticed that SSI was a better predictor of Cc, in comparison with TL. Prediction ability of many equations from literature was questioned, and it was concluded that these equations were good predictors of their own data. Moving to a generalized behavior, data show a more scattered structure, which needs more sophisticated methods using above-mentioned parameters as inputs. In this regard, artificial neural networks were employed to estimate the Cc by use of single input parameters: TL or SSI. Additionally, a combination of Atterberg limits was also instructed as inputs for prediction of Cc. A comparative analysis of the effects of learning algorithm, input data, and number of neurons in hidden layer was given. It was concluded that the TL and SSI are reasonable predictors of compression index.

On the 30th of October 2020, a 6.6 magnitude earthquake occurred 14 km north of Samos Island, causing 119 casualties (117 in Izmir, Tu & BULL;rkiye, and 2 in Samos, Greece) and significant damage in the 3rd biggest city of Tu & BULL;rkiye, Izmir. Although the city is roughly 70 km far away from the epicenter, the damage was significant and concentrated in the city center settled on alluviums. This paper aims to analyze the distribution of damage in Izmir province, by crosschecking the recorded motions, the subsoil conditions and the evidence of damage as collected by an ad-hoc on-site reconnaissance. The intrinsic behavior of the Samos earthquake was investigated by employing three different ground-motion prediction equations. The results of the analyses revealed that site effects play a significant role in the amplifi-cation of ground motions, and valley effects are responsible for the concentration of damage. The damage in buildings was classified in terms of the intensity and structural typologies for the 30 districts of Izmir metropolitan area. In-depth analysis of the distribution of damages revealed that the earthquake caused damage all over the boundaries of Izmir province, and the concentration of damage in Bornova and Kars & DBLBOND;iyaka districts has a clear correlation with double resonance effects.& COPY; 2023 Production and hosting by Elsevier B.V. on behalf of The Japanese Geotechnical Society. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

Due to the unique soil and morphological conditions prevailing in Izmir Bay basin, structural damage has been governed by site effects. Consistently, during October 30, 2020 M7.0 Samos Earthquake, which took place offshore of Samos Island, structural damage and life losses were observed to be concentrated in Bayrakli region of Izmir Bay, despite the fact that the fault rupture was at a distance of 65-75 km from the city of Izmir. Additionally, strong ground motions recorded in Izmir Bay showed unique site amplifications that were observed surprisingly at both rock and soil sites. Soil amplifications and duration elongations were mostly due to site effects governed by the response of very deep alluvial deposits of low plasticity. Similarly, due to very extensive faulting-induced fracturing and unusually stratified nature of rock sub-layers, unexpected long period amplifications were also observed at rock sites. These earthquake and site resonance effects were more pronounced in the period range of 0.5-1.5 s. When they were superposed with relatively coinciding natural period of 7-9 story residential buildings of Izmir City, it was concluded that the triple resonance effects among incoming rock ground motions, soil deposits, and the damaged buildings, amplified and prolonged the overall system response. Within the confines of this manuscript, the governing role of site effects leading to increased seismic demand was assessed, through a series of 1D equivalent linear, total stress-based site response assessments, the results of which clearly highlighted the variation of seismic demand in Izmir Bay.

On October 30, 2020, a damaging earthquake of moment magnitude 6.6 struck about 14 km northeast of the island of Samos, Greece, and about 70 km from the center of the city of Izmir in Turkey. Even though the epicenter was relatively far away, the effects of the seismic event in the highly populated city center of Izmir were destructive causing over 100 fatalities and significant structural damage. Multiple failures of high buildings constituted the major source of the fatalities. This paper aims to understand the link between the localized damage distribution and the nature of amplification effects that have been observed in Izmir Bay, starting from collection and data analysis interpretation of seismic records and targeted damage assessment of the built environment, as well as geological and morphological characteristics of the area and the geotechnical properties of soils. Critical analysis of the numerous recorded signals shows the key role of the young alluvium and shallow marine deposits of the basin on which Izmir Bay was growing. The coupling mechanism between the frequency content of the shaking and the fundamental frequencies of the damaged buildings contributed to exacerbating the inertial forces acting on the collapsed buildings.

On October 30, 2020 14:51 (UTC), a moment magnitude (M w ) of 7.0 (USGS, EMSC) earthquake occurred in the Aegean Sea north of the island of Samos, Greece. Turkish and Hellenic geotechnical reconnaissance teams were deployed immediately after the event and their findings are documented herein. The predominantly observed failure mechanism was that of earthquake-induced liquefaction and its associated impacts. Such failures are presented and discussed together with a preliminary assessment of the performance of building foundations, slopes and deep excavations, retaining structures and quay walls. On the Anatolian side (Turkey), and with the exception of the Izmir-Bayrakli region where significant site effects were observed, no major geotechnical effects were observed in the form of foundation failures, surface manifestation of liquefaction and lateral soil spreading, rock falls/landslides, failures of deep excavations, retaining structures, quay walls, and subway tunnels. In Samos (Greece), evidence of liquefaction, lateral spreading and damage to quay walls in ports were observed on the northern side of the island. Despite the proximity to the fault (about 10 km), the amplitude and the duration of shaking, the associated liquefaction phenomena were not pervasive. It is further unclear whether the damage to quay walls was due to liquefaction of the underlying soil, or merely due to the inertia of those structures, in conjunction with the presence of soft (yet not necessarily liquefied) foundation soil. A number of rockfalls/landslides were observed but the relevant phenomena were not particularly severe. Similar to the Anatolian side, no failures of engineered retaining structures and major infrastructure such as dams, bridges, viaducts, tunnels were observed in the island of Samos which can be mostly attributed to the lack of such infrastructure.