Akka Technologies (France)

Municipal solid waste (MSW) and refuse-derived fuel (RDF) incineration generate over 20 million tons of residues annually in the EU. These include bottom ash (IBA), fly ash (FA), and air pollution control residues (APCr), which pose significant environmental challenges due to their leaching potential and hazardous properties. While these residues contain valuable metals and reactive mineral phases suitable for carbonation or alkaline activation, chemical, techno-economic, and policy barriers have hindered the implementation of sustainable, full-scale management solutions. Accelerated carbonation technology (ACT) offers a promising approach to simultaneously sequester CO2 and enhance residue stability. This review provides a comprehensive assessment of waste incineration residue carbonation, covering 227 documents ranging from laboratory studies to field applications. The analysis examines reactor designs and process layouts, with a detailed classification based on material characteristics, operating conditions, investigated parameters, and the resulting pollutant stabilization, CO2 uptake, or product performance. In conclusion, carbonation-based approaches must be seamlessly integrated into broader waste management strategies, including metal recovery and material repurposing. Carbonation should be recognized not only as a CO2 sequestration process, but also as a binding and stabilization strategy. The most critical barrier remains chemical: the persistent leaching of sulfates, chromium(VI), and antimony(V). We highlight what we refer to as the antimony problem, as this element can become mobilized by up to three orders of magnitude in leachate concentrations. The most pressing research gap hindering industrial deployment is the need to design stabilization approaches specifically tailored to critical anionic species, particularly Sb(V), Cr(VI), and SO42−.

We present in this article simulations and experiments on the production, storage, and conversion into electricity of low-carbon hydrogen using solar panels, a Proton Exchange Membrane (PEM) hydrogen generator, and a PEM Fuel Cell (FC). The experimental configuration also includes backup electric storage (battery and supercapacitors) and is controlled and monitored using a homemade LabVIEW program. The present paper focuses on the static and dynamic characterization of the fuel cell. We present the I-V and power curves obtained numerically, using a MATLAB Simulink model, and experimentally and compare them to the ones provided in the FC specifications. We also compute, based on the experimental data, the efficiency of the FC when responding to a specific dynamic load and evaluate the effect of the ancillaries' energy consumption on the device performances. We obtain a maximum measured efficiency of the FC of 60 percent.

Automated driving can no longer be referred to as hype or science fiction but rather a technology that has been gradually introduced to the market. The recent activities of regulatory bodies and the market penetration of automated driving systems (ADS) demonstrate that society is exhibiting increasing interest in this field and gradually accepting new methods of transport. Automated driving, however, does not depend solely on the advances of onboard sensor technology or artificial intelligence (AI). One of the essential factors in achieving trust and safety in automated driving is road infrastructure, which requires careful consideration. Historically, the development of road infrastructure has been guided by human perception, but today we are at a turning point at which this perspective is not sufficient. In this study, we review the limitations and advances made in the state of the art of automated driving technology with respect to road infrastructure in order to identify gaps that are essential for bridging the transition from human control to self-driving. The main findings of this study are grouped into the following five clusters, characterised according to challenges that must be faced in order to cope with future mobility: international harmonisation of traffic signs and road markings, revision of the maintenance of the road infrastructure, review of common design patterns, digitalisation of road networks, and interdisciplinarity. The main contribution of this study is the provision of a clear and concise overview of the interaction between road infrastructure and ADS as well as the support of international activities to define the requirements of road infrastructure for the successful deployment of ADS.

The purpose of the D2.3 is twofold. Its first goal is mainly to provide an architecture capable of addressing the set of requirements necessary to deploy different innovative use cases based on vehicular data monetisation among which the demonstrators that will be carried out within the 5GMETA project. This architecture, in its first iteration, is designed to incorporate several cutting edge 5G features and cloud-hosted services that will ensure the data monetisation objective of the project. The second aim of the deliverable is to specify open application interfaces dedicated to Third Party, through which they can access the available 5GMETA platform services.

Earth and Space Science Open Archive This work has been accepted for publication in Journal of Geophysical Research - Space Physics. Version of RecordESSOAr is a venue for early communication or feedback before peer review. Data may be preliminary. Learn more about preprints. preprintOpen AccessYou are viewing the latest version by default [v2]HAPI: An API Standard for Accessing Heliophysics Time Series DataAuthorsRobert SWeigeliDJonVandegriffiDJeremy B.FadenToddKingD AaronRobertsiDBernardHarrisRobert M.CandeyiDScott A.BoardseniDDougLindholmChrisLindholmThomasBaltzerLawrence ElwinBrowniDE. W.GrimesBaptisteCecconiiDVincentGénotArnaudMassoniDBeatrizMartinezBenjaminRenardiDNandLalSee all authors Robert S WeigeliDCorresponding Author• Submitting AuthorGeorge Mason UniversityiDhttps://orcid.org/0000-0002-9521-5228view email addressThe email was not providedcopy email addressJon VandegriffiDJohns Hopkins UniversityiDhttps://orcid.org/0000-0002-0781-1565view email addressThe email was not providedcopy email addressJeremy B. FadenUniversity of Iowaview email addressThe email was not providedcopy email addressTodd KingUniversity of California Los Angelesview email addressThe email was not providedcopy email addressD Aaron RobertsiDNASA GSFCiDhttps://orcid.org/0000-0001-6565-2921view email addressThe email was not providedcopy email addressBernard HarrisNASA/GSFCview email addressThe email was not providedcopy email addressRobert M. CandeyiDNASA Goddard Space Flight CenteriDhttps://orcid.org/0000-0002-4698-8769view email addressThe email was not providedcopy email addressScott A. BoardseniDNASA/GSFC-GPHIiDhttps://orcid.org/0000-0002-5240-044Xview email addressThe email was not providedcopy email addressDoug LindholmUniversity of Colorado/LASPview email addressThe email was not providedcopy email addressChris LindholmUniversity of Colorado/LASPview email addressThe email was not providedcopy email addressThomas BaltzerUniversity of Colorado/LASPview email addressThe email was not providedcopy email addressLawrence Elwin BrowniDThe Johns Hopkins University Applied Physics LaboratoryiDhttps://orcid.org/0000-0002-9171-0862view email addressThe email was not providedcopy email addressE. W. GrimesUniversity of California Los Angelesview email addressThe email was not providedcopy email addressBaptiste CecconiiDObservatoire de ParisiDhttps://orcid.org/0000-0001-7915-5571view email addressThe email was not providedcopy email addressVincent GénotIRAPview email addressThe email was not providedcopy email addressArnaud MassoniDEuropean Space AgencyiDhttps://orcid.org/0000-0002-5602-1957view email addressThe email was not providedcopy email addressBeatriz MartinezRHEA Group for ESAview email addressThe email was not providedcopy email addressBenjamin RenardiDAKKA TechnologiesiDhttps://orcid.org/0000-0003-1847-7627view email addressThe email was not providedcopy email addressNand LalNASA GSFCview email addressThe email was not providedcopy email address

Availability of mobility data is subject to compatibility, interoperability and standards issues. For solving the interoperability issues, the MobiDataLab aims to conduct a theoretical study on stateof-the-art data sharing standards. This is the topic of this Task of the project (Standard Requirements) and of the following deliverable. This study covers public transport Data formats (Transmodel, NeTEx, SIRI, GTFS, etc.), data for micro-mobility and shared mobility, road data, pricing and ticketing data. Cross-domain standards are also considered, for the federation of cloud services, data catalogues (e.g. with DCAT-AP), and for the sharing of geospatial data and Linked open data. More generally this document provides an updated state-of-the-art review on existing standards and provides guidance for the developments in the project and identifies gaps to solve.

Autonomous Vehicles (AV) exhibit new characteristics rendering its architecting process challenging. They are context-aware cyber-physical systems with a high sensitivity toward their operational context. In addition to the lack of industrial feedback, their architecture needs to be adapted to their Operational Context (OC). The current literature doesn't provide a clear method for designing AV architecture based on their OC. This paper proposes a four steps method following the Concept of Operation approach (ConOps) and functional chain modeling to design AV architecture based on their OC and experts knowledge. The method uses a state-of the-art OC ontology for AV and improves the identification speed and coverage of the AV's operational needs. A case study is presented addressing the proposed methods and limitations.

This paper deals with a comparative study of two phasor estimators based on the least square (LS) and the linear Kalman filter (KF) methods, while assuming that the fundamental frequency is unknown. To solve this issue, the maximum likelihood technique is used with an iterative Newton–Raphson-based algorithm that allows minimizing the likelihood function. Both least square (LSE) and Kalman filter estimators (KFE) are evaluated using simulated and real power system events data. The obtained results clearly show that the LS-based technique yields the highest statistical performance and has a lower computation complexity.