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Infrastructure Impact Assessment through Multi-Hazard Analysis at Different Scales: The 26 November 2022 Flood Event on the Island of Ischia and Debris Management
No full textA multi-hazard analysis (seismic, landslide, flood) is conducted to verify the impact on the road network. The ENEA CIPCast platform is an innovative Decision Support System (DSS) that is used to implement the analyses using GIS. Using analytical and geoprocessing tools, the hazards were assessed and mapped. The overlapping of different geospatial layers allowed the implementation of a specific hazard map for the road network. Multi-hazard values were obtained using an appropriate matrix of single values, which were classified, and then summarized into four classes of values. The analyses were conducted at the regional (Campania region), provincial (Metropolitan City of Naples), and local scales (island of Ischia and municipality of Casamicciola Terme). In particular, the landslide event that struck Ischia island on 26 November 2022 and the municipality of Casamicciola Terme was considered as a case study to determine the impact on the road network, infrastructures, buildings, and jeopardizing inter-municipal connections. The results are mainly visualized through map processing and statistical summaries of the data. The management of the landslide debris, which can contain a multitude of fractions (waste, biomass and vegetation, sludge, soil, and rocks transported downstream by water), was also explored. This is a frontier issue for which international manuals and guidelines, as well as national and emergency acts, have been examined. A specific protocol for the sustainable management of the debris generated by floods and landslides is needed, and discussed in the present paper, to overcome emergencies after catastrophic events
Social and economic risk analysis of natural gas distribution networks
No full textThe continuity of service as well as with its safety and security represent a crucial issue for natural gas transmission and distribution networks and a detailed analysis of the associated risks is essential to increase their reliability. In particular, natural gas distribution networks are characterised by a high number of users and present a very complex structure (with nodes and stretches and presenting mixed typologies, e.g., point to point, star, meshed) which make often difficult to forecast the effects of localised failure events, especially by a social and economic point of view. In this work, the authors develop a methodology for the analysis of the economic and social risk associated with natural gas distribution network failures and for the quantification of the related consequences on residential, commercial and/or industrial users. To this aim, the authors present and discuss the case study represented by a city distribution network located in southern Italy. The results demonstrate the developed method is effective in identifying the structural criticalities of the network, allowing the quick detection of the most critical areas affected by significant risk of service disruption
Thermal pyrolysis of a real plastic sample from small WEEE and characterization of the produced oil in view of fuel or feedstock uses
No full textThe possibilities of valorizing by pyrolysis a plastic fraction from small waste from electrical and electronic equipment (WEEE-R4) rejected by a material recovery facility have been assessed. The characterization revealed that WEEE-R4 was mainly composed of acrylonitrile–butadiene–styrene (ABS) and blends of polycarbonate (PC)-ABS (75 and 25 wt%, respectively) and had good physicochemical properties as feed for pyrolysis processes: high values for volatile matter (95 wt%) and low heating value (LHV, 35 MJ/kg) and low ash and moisture content (2.5 and 0.33 wt%, respectively). On the contrary, the high content of heteroatoms, in particular Br from brominated flame retardants, arose as source of concern. Thermal analysis coupled with evolved gas Fourier transform Infrared (FTIR) spectroscopy showed that WEEE-R4 degraded in two steps in the range 310–460 °C and mainly to the monoaromatic compounds phenol and styrene. Thermal pyrolysis at 400 °C was carried out in a bench-scale reactor and the yields of the products were 18 wt% solids, 58 wt% light oil, 16 wt% tar and 8 wt% gas. The gaseous fraction was composed mainly of CO2 (60 wt%), originating from the thermal degradation of PC. After removing CO2, the gas had a good LHV (32.5 MJ/kg) such to contribute for the 66 % to the energy required for the pyrolysis process of WEEE-R4. The properties of the light oil were evaluated by means of the same standard tests used for commercial fuels or crude oils. The results were interesting but far from the more refined gasoline and diesel oil, with the concentration of nitrogen and bromine even higher than the typical composition of petroleum. Nevertheless, this study shows that pyrolysis followed by a refining treatment such as, distillation is capable of producing monoaromatic hydrocarbon in significant amount (>30 wt%)
A Unified Control Platform and Architecture for the Integration of Wind-Hydrogen Systems into the Grid
No full textHydrogen is a promising energy vector for achieving renewable integration into the grid, thus fostering the decarbonization of the energy sector. This paper presents the control platform architecture of a real hydrogen-based energy production, storage, and re-electrification system (HESS) paired to a wind farm located in north Norway and connected to the main grid. The HESS consists of an electrolyser, a hydrogen tank, and a fuel cell. The control platform includes the management software, the control algorithms, and the automation technologies operating the HESS in order to address the three use cases (electricity storage, mini-grid, and fuel production) identified in the IEA-HIA Task24 final report, that promote the integration of wind energy into the main grid. The control algorithms have been already developed by the same authors in other papers using mixed-logical dynamical modeling, and implemented via a two-layer model predictive control scheme for each use case, and are quickly introduced in order to make evident their integration into the presented architecture. Simulation test runs with real equipment data, wind generation, load profiles, and market prices are also reported so as to highlight the control platform performances.Note to Practitioners-The paper develops the integration between the management platform of a HESS, paired to a real wind farm in northern Norway, and the control algorithms aimed at scheduling hydrogen production and re-electrification on the basis of several forecast streams about exogenous conditions and different possible operating modes of the wind-hydrogen system. The control algorithms address the three use cases identified by the IEA-HIA in the final report of Task 24 about the integration of wind energy into the grid, namely i) electricity storage, where the HESS is operated in order to enable the wind farm to power smoothing; ii) mini-grid, where the wind farm and the HESS form a mini-grid with a local load (small town) and the HESS is therefore operated in order to fulfill it without and with grid support (in this case buying and selling electricity to the market is also handled); and iii) fuel production, where the HESS is operated in order to fulfill a hydrogen demand (e.g., due to fuel cell vehicles). In addition to the specific objectives of each use case, the developed control algorithms also optimize the HESS operating costs and typically address two time-scale behaviors to appropriately handle corresponding long and short terms dynamics. The management platform of the HESS is arranged in three layers (physical, control, and supervision layers), and located in the cloud. The physical layer targets the physical components, sensors, and actuators. The automation layer includes all local controllers and modules used for measurement, and several servers for interactions between the higher and lower layers of the control architecture and databases. In the supervision layer, the execution of control algorithms and clients for remote diagnoses, monitoring, and top-management activities are located. Since each layer performs specific functionalities, a multi-Tier architecture is implemented and the communications among the layers occur through services and microservices
Early stage ecological communities on artificial algae showed no difference in diversity and abundance under ocean acidification
No full textMarine habitat-forming species create structurally complex habitats that host macroinvertebrate communities characterized by remarkable abundance and species richness. These habitat-forming species also play a fundamental role in creating favourable environmental conditions that promote biodiversity. The deployment of artificial structures is becoming a common practice to help offset habitat loss although with mixed results. This study investigated the suitability of artificial flexible turfs mimicking the articulated coralline algae (mimics) as habitat providers and the effect of ocean acidification (OA) on early stage ecological communities associated to flexible mimics and with the mature community associated to Ellisolandia elongata natural turfs. The mimics proved to be a suitable habitat for early stage communities. During the OA mesocosms experiment, the two substrates have been treated and analysed separately due to the difference between the two communities. For early stage ecological communities associated with the mimics, the lack of a biologically active substrate does not exacerbate the effect of OA. In fact, no significant differences were found between treatments in crustaceans, molluscs and polychaetes diversity and abundance associated with the mimics. In mature communities associated with natural turfs, buffering capability of E. elongata is supporting different taxonomic groups, except for molluscs, greatly susceptible to OA
Implementation of a Novel ERANOS Procedure for the Adjoint Power Evaluation in Coupled Depletion Problems
No full textThe design of nuclear reactor cores heavily relies on the ability to evaluate burnup effects and the resulting changes in material composition at the isotopic level. When considering the design of liquid-metal fast reactors carried out using the ERANOS suite, a novel dedicated procedure to tackle depletion problems, based on the Generalized Perturbation Theory (GPT), was developed and implemented in the ERANOS suite. The preliminary results obtained by coupling the Boltzmann/Bateman fields, in both direct and adjoint domains, are presented and briefly discussed in this work, suggesting the possibility of their extension to more realistic applications and practical core design problems
AI-Driven Paddle Motion Detection
No full textIn order to compete more effectively in high level water sport of canoeing, it is essential for coaches and athletes to have a solid understanding of paddle motion. This paper presents a based-AI solution for precisely capturing the paddle trajectory when canoeing. Leveraging state-of-The-Art object detection, instance segmentation algorithm, YOLO, helps to detect the accurate shape of the paddle in the different frames of the video. We also offer a comparative study between two popular tracking algorithms: BoT-SORT and ByteTrack. Additionally, this work investigates the impact of the most commonly used optimizers in machine learning including SGD, Adam and AdamW on the system's overall performance. Finally, we found that BoT-SORT performed better than ByteTrack in following and recognizing the paddle in a higher quantity of frames. Moreover, in terms of training procedure, the results showed that SGD outperformed the two adaptive optimizers Adam and AdamW overall, with an average precision of 0.63 as opposed to 0.59 for both Adam and AdamW
An Ontology of Industrial Work Varieties
No full textIndustry 4.0 requires an increased digitalization and automation of industrial processes. Achieving a better understanding of them is a precondition still hindered by several factors. Workers hiding their individual know-how gained in the company to avoid losing power because they hold unique knowledge, and lack of agreement among different workers on how work practices are actually performed, are just two frequent examples of such obstacles. To support process comprehension, we present an upper ontology for modeling industrial work varieties, named Work-As-x (WAx) ontology. The aim is to shed light on the different varieties of work knowledge and on how these are converted between agents within a cyber-socio-technical system, such as an industry. The WAx ontology has been conceived to consider and better manage the different perspectives on the actual industrial processes, such as the Work-As-Imagined held by blunt-end operators and the Work-As-Done by sharp-end operators. The ontology extends the Suggested Upper Merged Ontology (SUMO) to guarantee a rigorous semantic basis. Finally, we discuss how the WAx ontology can be used to semantically annotate different repositories of industrial process representations to the purpose of their analysis
Microdosimetry of μsPEFs exposure on advanced stem cells 3D models in microfibrils' scaffolds
No full textStem cells-based treatments are offering tantalizing prospectives within neuronal tissue engineering, as a versatile tool to promote nerve regeneration after injuries, such as the Spinal Cord Injury (SCI). In this context, the European project RISEUP aims at SCI regeneration through an Electro Pulsed Bio-hybrid (EPB) implantable device, that will support stem cells in a polylactic acid microfibrils' scaffold. The cells' differentiation in neuronal lineage will be fostered through the application of microsecond pulsed electric fields (μsPEFs), typically used for electroporation-based applications. In this work, a microdosimetric study on a mixture of advanced 3D realistic cells' models, including subcellular structures and internal organelles, hosted in a sparser and a denser microfibrils' distribution is presented. The aim is to quantify the induced electrical quantities and the pore formation dynamics at cellular and subcellular level, to evaluate the biophysical effects induced after μ sPEFs stimulation
Spatial Multi-criteria Analysis for Identifying Suitable Locations for Green Hydrogen Infrastructure
No full textThe paper proposes a Spatial Multi-Criteria Analysis for identifying suitable locations for green hydrogen infrastructure. The production and use of hydrogen as a renewable energy carrier can play a critical role in reducing carbon footprint and increasing energy security in cities worldwide. The approach considers multiple criteria, such as demand, accessibility, environmental impact, and cost, to identify optimal locations for hydrogen production, storage, and distribution facilities. The GIS component enables spatial analysis, allowing visualization and analysis of spatial relationships between potential locations and other relevant factors. The research claims that green hydrogen can significantly improve energy resilience and transform energy systems. The method is applied to a case study, an energy-intensive industry in the city of Potenza (Italy). The result is the map identifying suitable areas where hydrogen production facilities can be located. The approach suggests that urban planners, decision-makers, and stakeholders develop and use green hydrogen as a sustainable energy source