Federal Ministry of Transport and Digital Infrastructure

Monitoring strain conditions in road structures is crucial for maintaining their integrity and extending their lifespan. However, traditional methods often fall short in providing continuous, real-time data. This study investigates the potential of fibre optic sensors, specifically distributed fibre optic sensing (DFOS) technology (OFDR, DAS, DTS), for detecting strain conditions in road structures. Experiments conducted at the duraBASt test site and a pilot application on an in-service motorway demonstrate the feasibility of using DFOS to measure strain and detect vehicle crossings with high spatial resolution. The results show a close correlation between externally applied loads and internally measured strain values, indicating the technology's promise for monitoring road structures under various traffic conditions. The scope of this work extends beyond general traffic monitoring and load measurements to specifically address the accuracy and the repeatability of determining vehicle position, speed, and weight, ensuring precise spatial and temporal localization of individual vehicles. With its ability to provide continuous monitoring, fibre optic sensing technology offers a significant advancement in road construction and maintenance, enabling more accurate assessments of road condition and more efficient maintenance scheduling. Future applications could include integrating this technology into smart road systems for real-time traffic monitoring and structural health assessment.

Estuaries worldwide provide unique ecosystems and critical freshwater resources for drinking water supply or agriculture. They are vulnerable to salt intrusion, which can have serious environmental and socioeconomic consequences. Obtaining a detailed picture of the state of the estuary through continuous monitoring is therefore essential. However, this is challenging due to the limited number of measurement stations. Numerical models provide such detailed insights but are computationally expensive and have limited suitability for real-time predictions. Data-driven models, such as Long Short-Term Memory (LSTM) networks, offer a promising alternative. In this study, LSTM networks are used to predict the location of the 2 g/kg bottom isohaline as an indicator for salt intrusion. Based on salinity, water level, wind, and river discharge data, the LSTM networks were trained on the salt intrusion length derived from a numerical model to estimate future salt intrusion accurately. Thus, detailed horizontal information from point measurements can be provided. This method is applied to the tidal Weser and Elbe estuaries, demonstrating that the network remains functional even when input stations are missing. Short-term environmental variability hampers longer-term forecasts, and limited data reduce prediction accuracy. Despite these constraints, our results show that LSTM networks replicate numerical model outputs from observational data and deliver real-time estimates of estuarine salt intrusion. This approach provides an efficient, adaptable tool for coastal monitoring and management.

Concrete segregation can lead to variations in hardened concrete’s properties, such as strength and Young’s modulus, or permeability, resulting in changing volume ratios between aggregates and paste within a concrete element. One approach to mitigate this potential risk is to conduct a performance test to assess vibrated concrete’s segregation sensitivity. This paper outlines various methods to evaluate the segregation sensitivity of vibrated concrete, aiming to support adequate concrete casting. The focus is on practical feasibility while maintaining test accuracy. For hydraulic engineering in Germany, test procedures to evaluate segregation sensitivity on fresh and hardened concrete based on aggregate distribution are described in the “BAW-Code of practice MESB”. However, this method is very complex and, therefore, difficult to implement in practice. Another procedure for hardened concrete is based on concrete density. In this paper, both methods are compared to investigate if evaluating fresh concrete using a simple density criterion leads to a comparably significant differentiation of vibrated concrete with different segregation sensitivities. The primary emphasis lies in accurately classifying examined concretes in terms of their segregation sensitivity, evaluating the scatter of results, and assessing the practical applicability of these methods. The investigations demonstrate that a density-based method can yield reliable and comparable results to those obtained through the wash-out test according to “BAW-Code of practice MESB”. Additionally, a simpler and faster procedure is achievable with the density approach. Hence, density evaluation offers a practical alternative to the wash-out test.

Inland navigation is a source of greenhouse gases and air pollutants. High spaciotemporal resolved vessel-and site-specific exhaust emission rates as well as accumulated total emissions of CO2, NOx, HC, CO and PM from German inland navigation are estimated using a bottom-up approach. The same model is applied to evaluate the mitigation potential of modernizing the current inland vessel fleet. The model pairs AIS data with daily information of flow conditions at the waterways. It accounts for driving dynamics and computes energy demand, fuel consumption and emission rates of each monitored sailing vessel. The integral over time and space yield site-specific and in a subsequent step total emission rates. Furthermore, a simulated scenario reveals the potential for emission mitigation through modernization of the existing fleet.

The development of offshore wind farms (OWFs) is critical to meeting renewable energy targets, but predicting scour around offshore wind energy structures (OWESs) and the associated potential impacts on marine ecosystems remains a challenge. Using high-resolution bathymetry data, this study analyses field-measured scour depths at 460 monopiles at nine British OWFs. The analysis reveals a large spatial variability in relative scour depth (S/D) between OWF sites, but also within individual wind farms. Principal component analysis (PCA) is used to identify significant drivers of this variability. When the entire dataset is considered, results indicate that the relative water depth (h/D), the relative median grain size (d50/D), the Keulegan–Carpenter number (KC99), and the sediment mobility parameter MOB (θ99/θcr) are the most important influencing factors for the variability in relative scour depth. Other parameters investigated, such as pile Reynolds number (Re99), flow intensity (U/Ucr)99, and Froude number (Fr99), were found to have a less clear influence. Further sediment-specific analysis shows that relative water depth (h/D) is a particularly relevant driver of scour at sites with fine (63≤d50< 200 µm) and medium sands (200≤d50< 630 µm), with larger relative scour depth occurring at shallower relative water depths. Findings from this study provide new insights into scour behaviour across a range of spatial and environmental scales and lay a foundation for the transferability of scour prediction frameworks to new OWF sites. In the future, findings and datasets from this study are suggested to be used to estimate scour-induced sediment transport and thereby to provide a step towards the assessment of potential impacts of OWF expansion scenarios in the marine environment. By addressing the broader implications for regional sediment dynamics, this research contributes to the sustainable development of offshore wind energy.