Search Results (358)

As climate change increases the frequency and unpredictability of natural hazards, adapting critical infrastructure is crucial for long-term resilience. Among these hazards, embankment fires pose a growing threat to railway systems, particularly under rising temperatures and prolonged drought conditions. As part of the Horizon Europe project NATURE-DEMO, this study helps identify fire-prone rail segments and explore nature-based solutions, such as vegetation barriers, that can reduce ignition risk and enhance infrastructure resilience. In a case study, we analysed the risk of embankment fires for a section of the German railway network in detail. Based on an embankment-fire hazard indication map available for the entire German railway network, five hotspots within the study area were identified. Embankments with high fire susceptibility occur in both rural and urban areas, covering 1.1% of the study area. On the basis of published research on technical and nature-based solutions for reducing embankment fire susceptibility, we derived site-specific recommendations for the appropriate implementation of mitigation measures. Full article

Heavy-duty vehicles cause a significant percentage of the harmful gas emissions from the automotive industry. This article presents the development of a compression system for hydrogen as part of the H2REF-DEMO hydrogen refueling station, joining the European efforts to promote hydrogen (H₂) as a fuel that can play a key role in the energy transition of these types of vehicles. The H2REF-DEMO project, co-funded by the European Union’s “Horizon. Europe” programme under the “Clean Hydrogen Partnership” (grant agreement no. 101101517), involves a partnership between companies and research centers that aims to investigate the possibility of compressing hydrogen through hydraulic power to handle large vehicle refueling applications, such as bus fleet depots, trucks, or trains. The basic principle is the exploitation of hydraulic power to compress hydrogen through hydro-pneumatic bladder accumulators. The hydraulic power units, in fact, pump oil into the accumulators, causing a deformation of the bladder containing H₂ and thus a consequent gas compression. In this article, we focus on the development of the compression system, from the theoretical starting point to the core final layout of the refueling station for large vehicles. We also exploit a lumped parameter numerical model to both support the system design and virtually test its first control logic. The latter, in particular, allows the system to operate in three modes—Bypass, Parallel, and Serial modes—thus leaving room for testing basic and more complex control strategies. The results of numerical simulations demonstrate the effectiveness of this innovative compression technology and its considerable efficiency in terms of refueling time and energy consumption, especially when compared to the standard systems used for this application. These are thus encouraging results that can support the development of an actual H2REF-DEMO hydraulic test rig for hydrogen compression. Full article

In scenarios involving radiation such as decommissioning of nuclear disasters and operating nuclear power plants, it is necessary to perform tasks including maintenance, demolition, and inspection using robots in order to protect human workers from harm. LIDAR (LIght Detection And Ranging) sensors are used for many demanding real-time tasks in robotics such as obstacle avoidance, localisation, mapping, and navigation. Standard silicon-based electronics including LIDAR fail quickly in gamma radiation, however, high-radiation areas have a critical need for robotic maintenance to keep people safe. Sensors need to be developed, which can cope with this environment. A prototype including most required transmitter and receiver circuits is designed utilising components expected to provide up to (1 MGy) gamma radiation tolerance. Initial results testing the concepts of the laser transmission and detection in a lab environment shows reliable signal detection. Performance tests utilising multiple receivers show a linear relationship between receiver separation and measured time difference, allowing for the possibility of calibration of a sensor using the time difference between pulses. Future work (such as radiation testing trials) is discussed and defined. These results contribute to de-risking the feasibility of long-term deployment of LIDAR systems utilising these approaches into environments with high gamma dose rates, such as nuclear fission decommissioning, big science facilities such as the Large Hadron Collider, and remote maintenance systems used in future nuclear fusion power plants such as STEP and EU-DEMO. Full article

The Dual Fluid Reactor (DFR) is a Generation IV concept that relies on a phased development pathway using a low-temperature microdemonstrator ($\mu$DEMO) and a high-temperature minidemonstrator (mDEMO). A rigorous methodology is required to scale experimental data between these facilities to ensure the reliable design of the final reactor. This paper establishes such a methodology grounded in Similarity Theory. The Cathare-2 system code was used to perform a parametric study on a simplified model of the demonstrators, which use lead–bismuth eutectic and pure liquid lead, respectively. This study focused on identifying the specific operating conditions required to match key “defining” dimensionless numbers—the Reynolds number (Re) for dynamic similarity and the Peclet number (Pe_h) for thermal similarity. The analysis successfully identified and presented the distinct operating ranges of fluid velocity and mass flow required to achieve either state. Results show that matching the Reynolds number allows for the dimensionless pressure drop to be scaled with a deviation below 0.2%, while matching the Peclet number allows for the dimensionless temperature profile to be scaled with a deviation under 2.5%. The central finding is that dynamic and thermal similarity cannot be achieved simultaneously due to the different working fluids and temperatures of the demonstrators. This forces a strategic choice in experimental design, where an experiment must be tailored to investigate either fluid dynamics or heat transfer. This work provides the foundational “rulebook” for designing these crucial experiments, ensuring that data from the DFR demonstrator program is both reliable and scalable. Full article

Magnetic confinement nuclear fusion offers a promising solution to the world’s growing energy demands. The DEMO reactor presented here aims to bridge the gap between laboratory fusion experiments and practical electricity generation, posing unique challenges for magnetic plasma diagnostics due to limited space for diagnostic equipment. This study employs Bayesian inference and Gaussian process modeling to integrate data from pick-up coils, flux loops, and saddle coils, enabling a qualitative estimation of the plasma current density distribution relying on only external magnetic measurements. The methodology successfully infers total plasma current, plasma centroid position, and six plasma–wall gap positions, while adhering to DEMO’s stringent accuracy standards. Additionally, the interchangeability between normal pick-up coils and saddle coils was assessed, revealing a clear preference for saddle coils. Initial steps were taken to utilize Bayesian experimental design for optimizing the orientation (normal or tangential) of pick-up coils within DEMO’s design constraints to improve the diagnostic setup’s inference precision. Our approach indicates the feasibility of Bayesian integrated data analysis in achieving precise and accurate probability distributions of plasma parameter crucial for the successful operation of DEMO. Full article

Innovative reasoning frameworks have been proposed to enhance the reasoning capabilities of AI agents, improving their performance in various tasks. However, most existing research has focused on enhancing designing frameworks for LLMs, with limited attention on leveraging in-context learning to boost their reasoning power. This paper proposes a novel approach, Demo-ToT, which enhances the Tree-of-Thought (ToT) reasoning framework by dynamically retrieving relevant demonstrations to improve reasoning accuracy. Various demonstration retrieval strategies, including vector similarity, sparse retrieval, and string similarity, were explored to identify the most effective methods for optimizing LLM performance. Experiments conducted across multiple benchmarks and language models of varying sizes demonstrated that Demo-ToT substantially enhanced the reasoning ability of smaller LLMs, achieving performance comparable to or even surpassing that of much larger models such as GPT-4. Full article

Truck congestion around international ports poses persistent challenges for safety, efficiency, environmental performance, and accessibility, particularly during container terminal disruptions when long queues of trucks accumulate. Traditional responses often address isolated components of the problem and fail to capture the interdependencies of sociotechnical systems, where multiple actors pursue partly conflicting goals. This study explores the usefulness of combining Sociotechnical Systems (STS) principles with the Systems-Theoretic Accident Model and Processes (STAMP) to analyze such complexity more holistically. Using the case of truck re-routing procedures during terminal closures at the Port of Rotterdam, structured interviews and document analyses were used to apply parallel STS and System-Theoretic Process Analyses (STPA). The STS analysis identified misalignments among procedures, actor intentions, infrastructure, and communication practices, clarifying why diversion protocols often fail in practice. The STPA complemented this diagnosis by modeling control relationships and feedback loops, identifying 92 unsafe control actions and 407 loss scenarios that informed 16 design recommendations. Together, the two approaches demonstrate how sociotechnical and control-theoretic perspectives can be combined to generate both diagnostic and prescriptive insights. The study highlights the potential of a combined STS–STPA framework as a transferable analytical tool for understanding and redesigning complex transport systems. Full article

Heating and cooling (H&C) account for nearly half of the EU’s energy consumption, with significant potential for decarbonization through renewable energy sources (RES) integrated in district heating and cooling (DHC) systems. This study evaluates the environmental and social impacts of RES-powered DHC solutions implemented in three European small-scale demo sites (Bucharest, Luleå, Córdoba) under the Horizon 2020 WEDISTRICT project. Using the Life Cycle Assessment (LCA) and Social Life Cycle Assessment (S-LCA) methodologies, the research compares baseline fossil-based energy scenarios with post-implementation renewable scenarios. Results reveal substantial greenhouse gas emission reductions (up to 67%) and positive environmental trade-offs, though increased mineral and metal resource use and site-specific impacts on water and land use highlight important sustainability challenges. Social assessments demonstrate improvements in gender parity, local employment, and occupational safety, yet reveal persistent issues in wage equity, union representation, and inclusion of vulnerable populations. The findings emphasize that while renewable DHC systems offer significant climate benefits, social sustainability requires tailored local strategies and robust governance to avoid exacerbating inequalities. This integrated environmental-social perspective underscores the need for holistic policies that balance technical innovation with equitable social outcomes to ensure truly sustainable energy transitions. Full article

The pursuit of compact and efficient fusion energy systems necessitates innovative structural concepts capable of withstanding extreme operational conditions. This study presents a preliminary structural evaluation and stress assessment of a bucked-and-wedged configuration for the EU DEMO tokamak, targeting a peak magnetic field of 16.5 T. The proposed concept leverages mutual wedging of the Toroidal Field (TF) coils and their interaction with the Central Solenoid (CS) to optimize stress distribution in the inner legs, a critical region in high-field fusion reactors. To address the significant tangential forces arising during plasma operation, the design integrates outer inter-coil structures and shear pins to enhance mechanical stability. A hybrid simulation approach—coupling 3D electromagnetic and structural finite element analyses—is employed to assess stress behavior and structural integrity under both in-plane and out-of-plane loading conditions. The results contribute to the optimization study of high-field fusion reactor components and offer insights into viable mechanical design strategies for next-generation nuclear energy systems. Full article

The article is devoted to the control of multichannel objects by the method of numerical optimization. In this area, there are several not entirely accurate, but deeply rooted, ideas and approaches that we would like to analyze. This analysis is presented through typical examples and with the use of usually inexpensive software, which can also be obtained for free in a demo version. Using this software is easy with the help of intuitive buttons and options. Thus, solving problems in the design of a regulator for multichannel systems becomes accessible to anyone who has a mathematical model of the object. The principles of control of two-channel objects are considered, i.e., objects of size 2 × 2, which by induction can be extended to objects of size 3 × 3 and, possibly, even more. At the beginning, a solution to the problem of controlling a two-channel object of size 2 × 2 is proposed using a PID regulator of the same size or its simplest modifications. Then the problem with 3 × 3 objects is solved. There are two main factors that influence the result: the presence or absence of dominance of the absolute value of the diagonal elements of the object’s transfer function matrix over the remaining elements; the selected optimization objective function. In the case of dominance, the control task is significantly simplified. In its absence, in some cases it can be ensured by changing the numbering of the channels. Recommendations for forming the objective function are given. For the first time, the use of a fractional degree in the objective function is proposed, and the effectiveness of this approach is justified and shown. For the first time, an additional modification of the test signals during optimization is proposed, and the effectiveness of this modification is shown. It is also shown how the control quality of some channels can be improved at the expense of some deterioration in the control quality of other channels. Full article

Serious games that integrate educational content with engaging gameplay mechanics hold promise for reducing cognitive load and increasing student motivation in STEM and health science education. This preliminary study presents the development and evaluation of the Medimon NASA Demo, a game-based learning prototype designed to teach undergraduate students about the musculoskeletal and visual systems—two critical domains in space medicine. Participants (n = 23) engaged with the game over a two-week self-regulated learning period. The game employed mnemonic-based characters, visual storytelling, and turn-based battle mechanics to reinforce medical concepts. Quantitative results demonstrated significant learning gains, with posttest scores increasing by an average of 23% and a normalized change of c = 0.4. Engagement levels were high across multiple dimensions of situational interest, and 74% of participants preferred the game over traditional formats. Qualitative analysis of open-ended responses revealed themes related to intrinsic appeal, perceived learning efficacy, interaction design, and cognitive resource management. While the game had minimal impact on short-term STEM career interest, its educational potential was clearly supported. These findings suggest that mnemonic-driven serious games like Medimon can effectively enhance engagement and learning in health science education, especially when aligned with real-world contexts such as space medicine. Full article

The impacts of renovation actions on pre- and post-retrofitting building performances are complex to analyse, particularly small and potentially self-actuated actions, such as adding insulation layers to a cold roof slab or changing doors. These interventions are widespread in small residential houses and cases where the owners are the residents. However, a large research gap currently remains regarding the impact of sustainable solutions on building performance. This study aims to address this issue by proposing a methodology based on commercial cloud monitoring solutions and middleware development that analyses and reports on the impact of such solutions to end users, allowing for an analysis of real variations in air temperature levels. The methodology is applied to two single/double-family residential houses, acting as demo cases for verification, across a multi-year time horizon. In both cases, measurements were conducted before and after typical limited renovation actions. Alongside the proposed methodology, descriptions of the smart solutions’ requirements are provided. The results mainly focus on temperature variations. Finally, the impact of the solutions on energy consumption was analysed for one of the buildings, and feedback was briefly provided by the users. Full article

The eutectic PbLi (15.7 at.% Li) alloy appears promising for producing tritium from fertile materials. Currently, in nuclear fusion design, the technologies being explored for tritium extraction in molten phases primarily focus on (i) established processes based on Gas–Liquid Contactor (GLC), such as bubble, packed, or spray columns, or on (ii) exploiting hydrogen permeation phenomena using dense metallic membranes, i.e., Permeation Against Vacuum (PAV). This work introduces a new concept, a Membrane Gas–Liquid Contactor, to address several open issues related to mass transport phenomena within the previously mentioned technologies. The MGLC concept merges the advantages of Permeation Against Vacuum (PAV) and Gas–Liquid Contactor (GLC), which have been extensively applied to extract hydrogen and its isotopes from liquid metals. A comprehensive description of the MGLC’s operation is then provided, suggesting a mass transfer model suitable for the practical application of this new concept. Finally, the results of the experimental campaign conducted on a lab-scale test facility are presented and critically analyzed. Full article

The Volumetric Neutron Source (VNS) is a pivotal facility proposed for advancing fusion nuclear technology, particularly for the qualification of breeding blanket systems, a key component of DEMO and future fusion reactors. This study focuses on the design and optimisation of the VNS Thermal Shield, adopting a multidisciplinary approach to address its thermal and structural behaviours. The Thermal Shield plays a crucial role in protecting superconducting magnets and other cryogenic components by limiting heat transfer from higher-temperature regions of the tokamak to the cryostat, which operates at temperatures between 4 K and 20 K. To ensure both thermal insulation and structural integrity, multiple design iterations were conducted. These iterations aimed to reduce electromagnetic (EM) forces induced during magnet charge and discharge cycles by introducing strategic cuts and reinforcements in the shield design. The optimisation process included the evaluation of various aluminium alloys and composite materials to achieve a balance between rigidity and weight while maintaining structural integrity under EM and mechanical loads. Additionally, an integrated thermal study was performed to ensure effective temperature management, maintaining the shield at an operational temperature of around 80 K. Cooling channels were incorporated to homogenise temperature distribution, improving thermal stability and reducing thermal gradients. This comprehensive approach demonstrates the viability of advanced material solutions and design strategies for thermal and structural optimisation. The findings reinforce the importance of the VNS as a dedicated platform for testing and validating critical fusion technologies under operationally relevant conditions. Full article

DNA nanoball sequencing (DNBSEQ) is one of the most rapidly developing sequencing technologies and is widely applied in genomic and transcriptomic investigations. Recently, a new PE300 sequencing option primarily recommended for amplicon analysis was released for DNBSEQ-G99 and G400 devices. Given their unprecedentedly high data yield per flow cell, the new PE300 kits could be a great choice for various sequencing tasks, but we found that combining different types of DNA libraries in a single run could lead to undesired artifacts in the data. In this study, we investigate the occasional read cross-contamination that we first observed in our DNBSEQ PE300 run. The phenomenon, which we refer to as “software contamination”, is not actual contamination but primarily manifests as improper forward/reverse read pairing, improper demultiplexing, or as “digital chimeric” reads. Although rare, these artifacts were found in all runs we have analyzed, including several MGI demo datasets (both PE100 and PE150). In this study, we demonstrate that these artifacts arise primarily from the incorrect resolution of sequencing signals produced by neighboring DNA nanoballs, leading to mixing out forward and reverse reads or improper demultiplexing. The artifacts occur most frequently with read pairs where the length of insert sequence is shorter than the read length. Based on a few external NA12878 human exome sequencing data, we conclude that the total improper pairing rate in DNBSEQ data is comparable to Illumina ones. Overall, the problem only affects the analysis results when simultaneously sequenced libraries have markedly different insert size distribution or flow cell loading. Additionally, we demonstrate here that raw DNBSEQ data might contain ~2% optical duplicates, resulting from the same effect of close neighboring of DNB-sites in the flow cell. Full article