Port and Airport Research Institute

Internal damage in deep foundation piles can critically alter their structural integrity and dynamic response, making early and accurate detection essential for ensuring long-term performance and safety. This study presents a three-dimensional finite element modeling (3D-FEA) framework to evaluate the sensitivity of dynamic responses to internal damage under high-strain impact loading. A slender cylindrical pile (L/d = 45) embedded in a layered soil medium is analyzed, with damage simulated as a mid-height circular notch using two different modeling approaches: interface elements with reduced strength, and solid volume elements with degraded stiffness. The time-domain analysis involves applying an impact load at the pile head and recording displacement and velocity responses at multiple depths. Results reveal that the interface-based damage model fails to generate distinguishable reflections from the damaged region, limiting its diagnostic capability. In contrast, the volume-element model successfully captures wave scattering, amplitude attenuation, and early reflection signatures, enabling clear differentiation between damaged and undamaged conditions. The findings underscore the importance of refined damage zone representation for realistic and reliable pile integrity evaluation.

Abstract Understanding beach morphodynamic behavior across different time scales is crucial for developing reliable shoreline models, yet comprehensive analyses are limited by the scarcity of high-frequency, long-term observational data. This study analyzes a 34-year (1986-2019) dataset of daily beach profile measurements from Hasaki Beach, Japan, alongside wave data from the JRA-55 atmospheric reanalysis model. We examined the short-term shoreline response during storm arrival and post-storm conditions, analyzing two-day response patterns under different wave conditions. For decadal-scale analysis, we employed Discrete Wavelet Transform to decompose shoreline variations into different temporal scales. Storm response analysis revealed that erosion continues beyond the initial storm impact despite wave height stabilization, while post-storm recovery shows no significant deviation from stable wave conditions. The wavelet analysis of monthly averaged shoreline positions identified dominant energy concentrations at time scales of 4–8 and 8–16 months, corresponding to seasonal variations. Components exceeding 5-year time scales were found to contribute substantially to overall shoreline variance. After removing this long-term trend, the analysis revealed a marked decrease in shoreline variability after July 2007, with variance reducing from 108.74 m 2 to 34.95 m 2 .

In Japan, when the aircraft noise assessment index was changed from WECPNL to Lden in 2013, ground noise was also included in the assessment. Compared to flight noise, ground noise has a lower power and is often observed as an unclear and long-lasting level fluctuation at observation points that are some distance away from the source. Therefore, it is often difficult to treat ground noise as a target for measurement and evaluation. We have been surveying ground noise exposure through constant monitoring and short-term surveys around Narita Airport and other airports in Japan. The results suggest that engine run-up with high generated power and taxiing on taxiways close to residential areas account for a large contribution to the total ground noise energy, while APU with low power and unclear level fluctuations tend to have a very small contribution. There may be no need to necessarily include APU noise with very small observed levels in the evaluation.

A significant quantity of soil organic carbon (SOC) is buried in mangrove ecosystems. However, recent research has revealed that substantial amounts of carbon are exported to the atmosphere as CO2 or to the ocean as dissolved inorganic carbon (DIC), d

• Three storms were detected in the period from 27th October to 5th November 2023 • The three storms altogether generated an average storm surge duration of 10.5 days • The average maximum surge amplitude was 92 cm for Ciarán and 74 cm for Domingos • The storm surges generated by this storm chain were successfully modelled • A meteotsunami was identified with amplitude of 17 – 23 cm and period of 11 – 40 min We model the long-duration storm surges generated by October-November 2023 storm chain in the English Channel employing a hybrid method including numerical modelling, field surveys and analysis of oceanic and atmospheric data. The event consisted of three successive storms: a weaker unnamed storm (27-30 October), Storm Ciarán (2-3 November with minimum pressure 948 hPa) and Storm Domingos (4-5 November with minimum pressure 958 hPa). The average surge duration produced by this storm chain was 10.5 days. The average maximum air pressure drop was 42 hPa during Ciarán and 23 hPa during Domingos. These pressure drops, combined with onshore wind stresses, led to average maximum storm surge amplitudes of 92 cm for Ciarán and 74 cm for Domingos. We accurately modelled storm surges using a three-level nested grid system and validated the results with tide gauge data. Sensitivity analysis showed a spatially-dependant impacts from tides and waves on maximum surge amplitudes. To correlate our modelling and data analysis with actual conditions on the ground, field surveys were conducted where we measured a runup heights of 4.1 m in Chesil Beach and 2.1 m in West Bay. These values were successfully reproduced by two independent empirical runup models enabling adaption of suitable models for storm hazard mitigation and resilience. A meteotsunami with an amplitude of 17–23 cm and a period of 11–40 minutes was identified during Ciarán. The innovative hybrid framework developed in this study is recommended for building robust systems for storm warnings and coastal resilience.

A simple method for determining elemental sulfur in environmental water was developed and applied to seawater samples collected immediately after the occurrence of blue tides in Tokyo Bay. To investigate the concentration and extraction methods, artificial elemental sulfur was quantitatively produced by oxidizing a sulfide solution with an iodine solution, then used as a standard reagent in the experiments. To concentrate the elemental sulfur in the water sample, glass filter paper (GF/F) was used to filter and collect the elemental sulfur. The elemental sulfur was then extracted using n-hexane, the main component of petroleum ether; however, the recovery of elemental sulfur from the wet glass filter paper was low, and remained so even when the glass filter paper was dried. We, therefore, used a mixture of n-hexane and an acetone solvent, which is a hydrophilic organic solvent, for extraction and succeeded in recovering more than 90% of the elemental sulfur from the wet glass filter paper. Using this solvent mixture, we extracted and quantified elemental sulfur from seawater samples collected after the occurrence of blue tide, and detected 0.36–0.38 mgS L–1 of elemental sulfur in the near-surface layer. We also found that the elemental sulfur concentrations were higher in the surface layer than in the bottom layer. Therefore, we demonstrated that the quantification of elemental sulfur is important to better understand the blue tide phenomenon.Graphical abstract

Background: The resilience of shipping alliances within the global maritime container network (GMCN) has critical implications for global trade. This study examines the topological robustness of strategic alliances (SAs) in liner shipping, focusing on their structural properties and responses to disruptions. Methods: Using pre-2019 container vessel schedule data, we constructed a weighted node-edge network model of the GMCN. Centrality metrics were computed to identify critical nodes, and simulations were conducted to evaluate network robustness under random failures (RFs) and targeted attacks (TAs). Results: The results highlight the GMCN’s scale-free topology, which fosters resilience against RFs but exposes vulnerabilities to TAs on high-centrality nodes like Singapore and Shanghai. Among alliances, 2M and Ocean demonstrated superior resilience, attributed to strategic port selection and extensive coverage, yet their reliance on central hubs presents significant risks. Conclusions: This study underscores the importance of alliance-specific strategies, such as infrastructure investments and redundancy planning, to mitigate vulnerabilities. By bridging gaps in existing literature, the research provides insights for policymakers and industry stakeholders to enhance the robustness and adaptability of maritime logistics networks. These findings contribute to ensuring stable global supply chains within an evolving trade environment.