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Towards a Blockchain-Enabled Social-Life Cycle Assessment Service for Increased Value Chain Sustainability
No full textAs sustainability requirements are growing, more and more companies are falsely claiming to supply sustainable products, thus creating an unfair playing field for companies that do comply. The Textile and Clothing (TC) industry is one of the least sustainable and transparent industries, often manufacturing products in low-cost countries with inadequate working conditions and environmental standards. The purpose of this study is to investigate how social sustainability assessments can be conducted, to increase the reliability of sustainability claims. The paper proposes a concept of a Social-Life Cycle Assessment (S-LCA) service that is based on site-specific primary data and is grounded in the international Social Accountability (SA) 8000 certification system, to increase the reliability of sustainability claims. United Nations recommends the SA8000 in their S-LCA guidelines. The S-LCA service is also enabled by Blockchain to secure that critical data remains unaltered. The concept and service are being developed through the Design Science methodology, combining: i) case studies in an EU project, to understand the practical problem, ii) a S-LCA literature study, and iii) action research, to iteratively apply the service to the cases and refine it with project contributors representing the entire TC value chain. The concept consists of a workflow diagram, preliminary user interface, data collection template, and an overview of critical data to be secured by Blockchain. To the best of our knowledge, this is the first research paper about a concept of a site-specific S-LCA service that is integrated with an international certification system and a Blockchain-enabled platform
Pure Lead Thermodynamic Properties In SIMMER-III CODE: A Comparative Review And New Evaluation Proposal
No full textThe lead-cooled fast reactors (LFRs) have been identified as one of the most promising technologies among the Generation IV candidates. Since 2000, ENEA has been supporting the core design, safety assessment, and technological development of innovative nuclear systems cooled by heavy liquid metals (HLM), in particular LFRs. Efforts are devoted to developing and validating computational tools for specific applications to HLM systems, ranging from neutronics codes, system and core thermal-hydraulic codes, computational fluid dynamics, and fuel pin performance codes, including their coupling. In this framework, the SIMMER-III code (S-III) has sparked particular interest, since it has been developed to investigate postulated core disruptive accidents in liquid-metal fast reactors (LMFRs) and is capable of simulating multi-phase, multi-component materials in multi-velocity field with coupled neutronics and thermo-hydraulics capabilities. This paper presents a review of Lead (Pb) thermophysical properties (TPPs) models implemented into S-III. Detailed knowledge of HLM thermodynamic properties is needed for reactor design and modeling under representative normal and accidental conditions, and a review of the material properties is necessary before proceeding to a specific validation phase for its application to LFR systems. To ensure maximum flexibility, S-III TPP models are expressed with parametric functions, that is, polynomial equations for the liquid and solid phases. These models are designed to satisfy basic thermodynamic relationships among equation of state (EOS) variables over the entire temperature ranges. The EOS and TPP models for use in the accident analysis code are then completed by determining all the parameters related to each reactor-core material. The S-III validation process has been mainly focused on the technological development of the sodium-cooled fast reactor (SFR) program. The present work is inspired by this activity to carry out a similar verification and validation program focused on LFRs. The results of the comparative analysis based on the most up-to-date and reliable sources for Pb available in the literature are shown. The comparison is focused on the properties of liquid lead. The TPPs considered are the density, dynamic viscosity, thermal conductivity, surface tension, and heat capacity. The comparative analysis reveals a significant discrepancy between the specific heat at constant pressure implemented in SIMMER and the literature. A new model for the heat capacity at constant pressure of liquid lead is proposed, based on the Gurvich (1991) relationship. Finally, a case study simulation is proposed to quantify the effect on the calculation results of the new heat capacity formulation. This activity is preparatory to the validation phase that will take place during the experimental campaign that will be carried out at ENEA Brasimone Research Center in the CIRCE facility, concerning the steam generator tube rupture in LFRs
Modeling Networks of Interdependent Infrastructure in Complex Urban Environments Using Open-Data
No full textDependency effects between Critical Infrastructure (CI) elements represent key information needed to predict and analyze the impact of natural (or man-made) disturbances. The dependency links among CI elements and their associated weight are data whose availability is often complex to determine and are usually not available. Leveraging on several data supporting US and EU Directives for the Resilience and the Protection of CIs, the objective of the present work is to define a dependency network of elements of critical sectors extracted from available open-data. The resulting network is then studied in terms of its basic topological properties. The analysis of the network provides interesting clues about the properties and locations of critical points that can cause cascading failures. In addition, this information can form the basis for planning actions that mitigate the risk of cascading effects
Nuclear analyses for the ITER Diagnostic Equatorial Port 8
No full textThe ITER diagnostic Equatorial Modular Port Plugs (EPPs) are located in the equatorial vacuum vessel ports. Port plugs consist of structural components, shielding elements, services and tenant systems and they are designed to operate in a harsh nuclear environment. Main functions of the port plugs are to provide nuclear shielding and to host tenants systems. Shielding performance optimization and calculation of heat release across the port plugs and on their systems are both crucial for technically sound integration layout of a port plug. Also, assessment of radiological waste is necessary for the decommissioning procedure. Neutronic analyses presented in this paper are focused on the standard shielding and integration solutions on a representative Equatorial Modular Port Plug of port number 8. This Port Plug hosts the Disruption Mitigation System (DMS) and other five diagnostic systems distributed in the three Diagnostic Shielding Modules (DSM): Lost Alpha Monitor, Tangential Neutron Spectrometer, Visible Spectroscopy system, Density Interferometer Polarimeter and the Flow Monitor. Highly detailed MCNP model of the EPP#8 has been developed and integrated in the ITER 40° MCNP C-Model. The model has been used to calculate the relevant nuclear quantities: neutron and gamma fluxes distribution, nuclear heating in the EPP#8 components, tritium and helium production at the ITER end of life and the displacement damage will be presented in the paper for the In-Vessel region
Hierarchical model predictive control for islanded and grid-connected microgrids with wind generation and hydrogen energy storage systems
No full textThis paper presents a novel energy management strategy (EMS) to control a wind-hydrogen microgrid which includes a wind turbine paired with a hydrogen-based energy storage system (HESS), i.e., hydrogen production, storage and re-electrification facilities, and a local load. This complies with the mini-grid use case as per the IEA-HIA Task 24 Final Report, where three different use cases and configurations of wind farms paired with HESS are proposed in order to promote the integration of wind energy into the grid. Hydrogen production surpluses by wind generation are stored and used to provide a demand-side management solution for energy supply to the local and contractual loads, both in the grid-islanded and connected modes, with corresponding different control objectives. The EMS is based on a hierarchical model predictive control (MPC) in which long-term and short-term operations are addressed. The long-term operations are managed by a high-level MPC, in which power production by wind generation and load demand forecasts are considered in combination with day-ahead market participation. Accordingly, the hydrogen production and re-electrification are scheduled so as to jointly track the load demand, maximize the revenue through electricity market participation and minimize the HESS operating costs. Instead, the management of the short-term operations is entrusted to a low-level MPC, which compensates for any deviations of the actual conditions from the forecasts and refines the power production so as to address the real-time market participation and the short time-scale equipment dynamics and constraints. Both levels also take into account operation requirements and devices’ operating ranges through appropriate constraints. The mathematical modeling relies on the mixed-logic dynamic (MLD) framework so that the various logic states and corresponding continuous dynamics of the HESS are considered. This results in a mixed-integer linear program which is solved numerically. The effectiveness of the controller is analyzed by simulations which are carried out using wind forecasts and spot prices of a wind farm in center-south of Italy
Dielectric properties of epoxy/graphite flakes composites: Influence of loading and surface treatment
No full textEpoxy-rich carbon-based composites are well recognized materials in industries owing to their good mechanical properties and thermal stability. Here, dielectric properties of composites based on bisphenol-A-epoxy resin loaded with 5, 6, 10, and 15 wt% of graphite flakes (GF) have been studied. The frequency and temperature dependence of the dielectric permittivity, dielectric loss, and ac conductivity have been examined in temperature (−103 to 97°C) and frequency (20 Hz–200 kHz) range. Influence of the filler surface chemistry have been studied for composites loaded with 5 wt% GF obtained: (i) under wet milling, without or with adding Triton-100x as a surfactant, or (ii) under dry milling in the presence of KOH. The composite made of epoxy loaded with 5 wt% exfoliated expanded graphite flakes (EEG), was also prepared. The surface treatment with KOH notably increased dielectric constant of the composite, keeping low dielectric loss, while treatment with Triton-100x significantly increased tanδ. The composite loaded with exfoliated expanded graphite shows higher ac conductivity than those obtained with flaky graphite, GF. Possibility to change dielectric properties of the composites without changing the loading content can be used as an approach in tailoring one with desired dielectric properties
Dynamic Neural Assimilation: a deep learning and data assimilation model for air quality predictions
Full text linkAmbient air pollution is known to be a serious issue that has an impact on human health and the environment. Assessing air quality is of the utmost importance to protect human health and the environment. Different tools are available, from monitoring stations to complex models. These systems are capable of accurately predicting air quality levels, but they are often computationally very expensive which makes them poorly efficient. In this paper, we developed a novel model called Dynamic Neural Assimilation (DyNA) integrating Recurrent Neural Networks and Data Assimilation methods to derive a physics-informed system capable of accurately forecasting air pollution tendencies and investigating the relationship with industrial statistics. DyNA is trained in historical data and is fine-tuned as soon as new data comes available. We trained and tested the system on real data provided by the air quality monitoring stations located in Italy from the European Environment Agency and simulated results derived from the air quality modelling system Atmospheric Modelling System-Model to support the International Negotiation on atmospheric pollution on a National Italian level. We analysed air pollution data in Italy from the years 2003–2010 and studied its correlation with nearby industries in some regions where monitoring sensors were available
Implementation of Positive Energy Districts in European Cities: A Systematic Literature Review to Identify the Effective Integration of the Concept into the Existing Energy Systems
Full text linkThe positive energy district (PED) is a rather recent concept that aims to contribute to the main objectives of the Energy Union strategy. It is based on an integrated multi-sectoral approach in response to Europe’s most complex challenges. But to what extent have its development and implementation been supported by research and innovation programs? And what is the state of the art of its implementation and effective penetration into the current energy systems of European cities, according to the evidence provided by the scientific literature? This study aims to investigate these issues, providing a critical overview of the PED situation by means of a systematic literature review based on the use of open-access bibliometric software supplemented with content analysis. The results show that less than half of the documents analyzed refer to actual case studies, 80% of which were funded as part of research projects. This seems to lead to the conclusion that although PEDs have been strongly encouraged by the scientific community and policy initiatives at the European level, their implementation in cities is still limited. Moreover, an uneven distribution among countries can be observed. To overcome the existing barriers to PED diffusion and implementation, it would be useful to provide more ad hoc funding and, above all, facilitate its accessibility also by municipalities not yet well integrated into European projects, initiatives, and networks
Preliminary Characterization of Alumina-Forming Austenitic–Type Advanced Alloys as Structural Materials for LFRs
No full textThe lead-cooled fast reactor (LFR) is one of the most promising Generation-IV nuclear designs currently under development in Europe, China, and the United States. LFRs can ensure enhanced performance and minimal waste production thanks to a closed fuel cycle, but they also have some issues that need to be addressed. One of the most critical is the long-term degradation process initiated in structural materials exposed to liquid Pb. The present state of the art has shown that commercial austenitic steels, such as American Iron and Steel Institute 316L and 15-15Ti can be adopted as structural materials in Pb environments up to 480°C, beyond which they start to experience the dissolution of constituting alloying elements (Ni, Cr, and Fe) if not protected by a coating or by surface modification. In more recent years, a lot of research effort has been done in order to develop new coating technologies and new base materials for operation with liquid Pb at higher temperatures. Among the newest alloys, alumina-forming austenitic (AFA) steels have gained interest in the research community because of their promising corrosion resistance results even at temperatures of 600°C. In this framework, an experimental campaign has been run at the Research Center ENEA of Brasimone that aims to characterize the behavior of two different AFA steels (with low and high Ni content in their composition) in static Pb at 650°C and 750°C with a moderate low oxygen concentration (10−6 wt %). After exposure, the AFA steels were characterized from the point of view of the morphology and composition, and the results are presented and discussed here
DC_OCEAN: an open-source algorithm for identification of duplicates in ocean databases
No full textA high-quality hydrographic observational database is essential for ocean and climate studies and operational applications. Because there are numerous global and regional ocean databases, duplicate data continues to be an issue in data management, data processing and database merging, posing a challenge on effectively and accurately using oceanographic data to derive robust statistics and reliable data products. This study aims to provide algorithms to identify the duplicates and assign labels to them. We propose first a set of criteria to define the duplicate data; and second, an open-source and semi-automatic system to detect duplicate data and erroneous metadata. This system includes several algorithms for automatic checks using statistical methods (such as Principal Component Analysis and entropy weighting) and an additional expert (manual) check. The robustness of the system is then evaluated with a subset of the World Ocean Database (WOD18) with over 600,000 in-situ temperature and salinity profiles. This system is an open-source Python package (named DC_OCEAN) allowing users to effectively use the software. Users can customize their settings. The application result from the WOD18 subset also forms a benchmark dataset, which is available to support future studies on duplicate checks, metadata error identification, and machine learning applications. This duplicate checking system will be incorporated into the International Quality-controlled Ocean Database (IQuOD) data quality control system to guarantee the uniqueness of ocean observation data in this product