Comparison of a black-box model to a traditional numerical model for hydraulic head prediction

Two different methodologies for hydraulic head simulation were compared in this study. The first methodology is a classic numerical groundwater flow simulation model, Princeton Transport Code (PTC), while the second one is a black-box approach that uses Artificial Neural Networks (ANNs). Both methodologies were implemented in the Bavaria region in Germany at thirty observation wells. When using PTC, meteorological and geological data are used in order to compute the simulated hydraulic head following the calibration of the appropriate model parameters. The ANNs use meteorological and hydrological data as input parameters. Different input parameters and ANN architectures were tested and the ANN with the best performance was compared with the PTC model simulation results. One ANN was trained for every observation well and the hydraulic head change was simulated on a daily time step. The performance of the two models was then compared based on the real field data from the study area. The cases in which one model outperforms the other were summarized, while the use of one instead of the other depends on the application and further use of the model

Surface and sub-surface integrity of Ti-6Al-4V components produced by selective electron beam melting with post-build finish machining

The emergence of metal additive manufacturing (AM) processes offer manufacturers a promising alternative to traditional forging and casting techniques for the production of near net shape titanium alloy components. However, limitations in both the surface finish quality and the geometric accuracy of parts produced by AM means that post-build finish machining of the part remains to be a requirement to produce high precision components. Furthermore, the fatigue performance of material produced directly by these processes is often limited by both the poor surface finish and porosity related defects which occur within the material. This study investigates the implications of machining stock allowance on the surface integrity of Ti-6Al-4V specimens produced by selective electron beam melting (SEBM) followed by post-build finish machining. The study revealed that the exposure of porosity related defects on the newly machined surface varied depending on the depth of material removed from the as-built specimen surface during machining. Four point bend fatigue testing of the specimens was carried out to determine the effect of the exposed surface defects on the fatigue performance of the material. This study highlights that the non-uniform distribution of pores within SEBM Ti-6Al-4V means that careful considerations must be given regarding machining stock allowance in the design of these components due to the implications of material removal depth on surface integrity

Hydrodynamic studies of floating structures: Comparison of wave-structure interaction modelling

Current panel methods for wave-structure interactions employ the potential flow theory, which provide fast, reliable and relatively accurate predictions for the marine structures, and now some open source packages, NEMOH and HAMS, are available. In this research, the relative utility and performance of NEMOH and HAMS is compared with the well-known, state-of-art software, WAMIT. To bring focus to these comparisons, this research is based on three different floating structures: the truncated cylinder; the truncated cylinder with heave plate; and a novel multi-axis TALOS wave energy converter. To make the comparison more useful, this research investigates the incomplete and overlapped panels for the simple cylinder, to examine whether the respective code can handle these and still provide a meaningful solution. The comparisons may help us to understand whether the incomplete and/or overlapped panels can be used for simplifying the numerical modelling of those very complicated marine structures. From the comparisons, it can be seen the open source software, NEMOH and HAMS, both could produce very good results for the simple single marine structure, but also exhibit different capacities in dealing with more complicated marine structures. Specifically, HAMS could handle the thin structures and the overlapped panels effectively as WAMIT

Satellite data for the offshore renewable energy sector: Synergies and innovation opportunities

Can satellite data be used to address challenges currently faced by the Offshore Renewable Energy (ORE) sector? What benefit can satellite observations bring to resource assessment and maintenance of ORE farms? Can satellite observations be used to assess the environmental impact of offshore renewables leading towards a more sustainable ORE sector? This review paper faces these questions presenting a holistic view of the current interactions between satellite and ORE sectors, and future needs to make this partnership grow. The aim of the work is to start the conversation between these sectors by establishing a common ground. We present offshore needs and satellite technology limitations, as well as potential opportunities and areas of growth. To better understand this, the reader is guided through the history, current developments, challenges and future of offshore wind, tidal and wave energy technologies. Then, an overview on satellite observations for ocean applications is given, covering types of instruments and how they are used to provide different metocean variables, satellite performance, and data processing and integration. Past, present and future satellite missions are also discussed. Finally, the paper focuses on innovation opportunities and the potential of synergies between the ORE and satellite sectors. Specifically, we pay attention to improvements that satellite observations could bring to standard measurement techniques: assessing uncertainty, wind, tidal and wave conditions forecast, as well as environmental monitoring from space. Satellite–enabled measurement of ocean physical processes and applications for fisheries, mammals and birds, and habitat change, are also discussed in depth

Hydrometeorological impact of climate change in two Mediterranean basins

The impact of climate change in specific hydrological issues is investigated in two Mediterranean watersheds of the island of Crete, Koutsoulidis, and Giofyros, by using the HBV hydrological model. Koutsoulidis basin is analysed in terms of future water resources availability under climate change, as it supplies the dam of the surrounding area that provides its irrigational water needs. Giofyros is a basin prone to flooding, hence, it is analysed in terms of spring flood risk under climate change. At first, the HBV model is calibrated using as input the historical data. Next, the climate change impact is studied, using the HBV with climate data from 11 GCM–RCM combinations for 3 RCP scenarios (2.6, 4.5, and 8.5 W/m2) and 3 time windows (1981–2010, 2021–2050, and 2071–2100). The climate change impact to the hydrological systems’ behaviour is projected using several hydrometeorological parameters and hydrological signatures. Specifically, in Koutsoulidis basin, projections of future water resources availability show that the period of May to November is a high-risk period of water shortage for all RCPs in all time windows. In Giofyros basin, spring flood risk analysis reveals higher flooding risk in 2021–2050 time window. In addition, February is the most frequent month of spring flood start point in all climate scenarios. The above findings could be used in strategic planning for a sustainable water resources management in the Mediterranean basins

Towards a Cloud-Based Analytics Framework for Assembly Systems

Part 3: Assembly Methods and ModelsInternational audienceAdvanced digitalization together with the rise of cloud technologies is a key enabler for a fundamental paradigm shift known as Industry 4.0 which proposes the integration of the new generation of ICT solutions for the monitoring, adaptation, simulation and optimization of factories. With the democratization of sensors, assembly systems can now be sensorized and the data generated by these devices can be exploited, for instance, to monitor their utilization, operations and maintenance. However, analyzing the vast amount of generated data is resource demanding both in terms of computing power and network bandwidth, especially when dealing with real-time changes to product, process and resource domains. This paper presents a novel cloud-based analytics framework for the management and analysis of assembly systems. It brings together standard open source technologies and the exploitation of cloud computing which as a whole can be adapted to and deployed on different cloud providers, thereby reducing infrastructure costs, minimizing deployment difficulty and providing on-demand access to virtually infinite computing power, storage and network resources