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Evaluation of non-destructive examination requirements and challenges for small modular reactors
No full textThis study evaluates the applicability of Non-Destructive Examination (NDE) methods to the BWRX-300, i-SMR, and Rolls-Royce SMR Small Modular Reactor (SMR) designs, as well as to Generation IV concepts: GTHTR300, IMSR 400, and 4S. The assessment considers plant design, structural materials, and manufacturing technologies to identify corresponding NDE requirements for both manufacturing and in-service inspections. The findings suggest that, for near-term deployable SMRs, existing inspection methods used in the conventional large-scale nuclear power plants remain applicable. However, the introduction of new materials, novel reactor designs, advanced manufacturing techniques, and the modular design, may require adaptations or development of new NDE approaches
Unsupported CoMoS catalysts for isoeugenol hydrodeoxygenation:optimisation of synthesis parameters for catalyst performance
No full textHydrodeoxygenation of isoeugenol as a model compound for lignocellulosic biomass-derived oils has been studied in this work. A series of unsupported cobalt-doped molybdenum oxide and sulfide catalysts were prepared via hydrothermal precipitation to systematically study the effect of catalyst preparation conditions on catalyst properties and catalytic performance. The effects of the preparation temperature, excess sulfur, and pH and their combinations were studied using a design of experiments approach. The catalysts were characterized with ICP-OES, N2 physisorption, XRD, XPS and SEM-EDS and screened for bio-oil model compound isoeugenol hydrodeoxygenation under relevant process conditions of 300 °C and 30 bar in a batch reactor. Co was observed as a sulfide, while molybdenum exhibited mixtures of the oxide and sulfide, with the former favored under preparation conditions with less sulfur. The catalyst performance testing revealed a higher activity and increased deoxygenation selectivity of the sulfide catalysts compared to those of the oxide catalysts. In addition to the chemical nature, the catalyst activity in the model reaction was increased by the high pore volume and surface area, which were promoted by a low pH at the start of the synthesis. The observed tendencies provide a basis for catalyst tailoring in hydrotreatment processes for biofuel and biochemical production from lignocellulosic biomass.</p
Small Modular Reactors in Denmark:A Technology and Cost Review
No full textThe Danish Energy Agency has asked Ea Energy Analyses and VTT Technical Research Centre of Finland to investigate the possibilities and consequences of integrating the compact nuclear reactor technology called Small Modular Reactor technologies (SMR technologies) into the Danish energy system. The project covers two subtasks: 1) a technical analysis of SMR technologies in a Danish context 2) and a system analysis that will assess the effects and value of integrating SMR into the Danish energy system. Thisreport constitutes the reporting of the first part
Understanding column-formation in axial-SPPS thermal barrier coatings:Evolution of microstructure and role of bond coat roughness
No full textColumnar yttria-stabilized zirconia (YSZ) thermal barrier coatings (TBCs) are renowned for their exceptional resistance to thermal cyclic fatigue (TCF) and their consequent role in extending the service life of gas turbine components. Traditionally, such coatings have been produced by electron beam physical vapor deposition (EB-PVD) and, more recently, by suspension plasma spraying (SPS). Latest studies demonstrating the capability of the aqueous solution precursor route to fabricate columnar YSZ TBCs using axial plasma spraying indicate its considerable potential to overcome shortcomings associated with both EB-PVD and SPS methods. In this work, the microstructural evolution of axial solution precursor plasma-sprayed (SPPS) 8 wt% YSZ coatings is investigated, with emphasis on the role of bond coat roughness. In-flight particle generation and splat formation have been carefully examined to obtain insights into column development. Results show that a coarse bond coat surface promotes column initiation, whereas a much smoother surface favours vertical cracking, not quite leading to column formation. Careful collection of particles generated in flight confirmed their size to be predominantly in the 100–500 nm range (d50 ≈ 280 nm), leading to largely sub-micron splats (d50 ≈ 465 nm). It is postulated that such fine sizes are inadequate to rapidly roughen the growing surface for spontaneous column initiation, thereby making the initial bond coat roughness crucial in tailoring TBC microstructures. In this context, the concept of a certain ‘threshold roughness’ being necessary to trigger column formation is also proposed and needs further investigation.</p
Advanced Assessment of Stroke in Retinal Fundus Imaging with Deep Multi-view Learning
No full textStroke is globally a major cause of mortality and morbidity, and hence, accurate risk assessment and diagnosis of stroke are valuable. Retinal fundus imaging reveals the known markers of elevated stroke risk in the eyes, which are retinal venular widening, arteriolar narrowing, and increased tortuosity. In contrast to other imaging techniques used for stroke assessment, the acquisition of fundus images is easy, non-invasive, fast, and inexpensive. This paper examines the feasibility of utilizing retinal fundus imaging to differentiate individuals with stroke or transient ischemic attack (TIA), aiming to assess its potential for screening or diagnostic applications. Therefore, in this study, we propose a multi-view stroke network (MVS-Net) to detect stroke and TIA using retinal fundus images. Contrary to existing studies, our study proposes for the first time a solution to discriminate stroke and TIA with deep multi-view learning by proposing an end-to-end deep network, consisting of multi-view inputs of fundus images captured from both right and left eyes. Accordingly, the proposed MVS-Net defines representative features from fundus images of both eyes and determines the relation within their macula-centered and optic nerve head-centered views. Experiments performed on a dataset collected from stroke and TIA patients, in addition to healthy controls, show that the proposed framework achieves an AUC score of 0.84 for stroke and TIA detection.</p
Strategic Marketing Tensions in Sustainable Business Models: A Conceptual Approach Through Customer Value Propositions and Stewardship
No full textSustainable business models (SBMs) inherently involve tensions, which are contradictory or misaligned demands that companies must consider simultaneously. However, there is a gap in the literature regarding the relevance and linkage of these tensions to strategic marketing considerations, including positioning, competitiveness, differentiation, and a company's interaction with customers. This study aims to identify a set of tensions that arise in the strategic marketing of SBMs and to explore how these tensions can be responded to by companies. The study adopts a conceptual methodology, applying customer value propositions (CVPs) as a structured strategic marketing lens to explore tensions. Further, stewardship is suggested as an ontological approach that shapes the strategic marketing responses to tensions for the collective good of future generations. The resulting framework outlines how companies can embrace SBM tensions, including their hierarchical intensity, make sense of complexity and address the dominance of unsustainable models through strategic marketing mechanisms.</p
Large Language Models for Automated Data Access Policy Creation in Data Spaces
No full textData spaces are being developed to enable more standardized and secure data sharing. They provide a framework where data can be exchanged following predefined access control policies. However, manually defining machine-readable policies can be a time-consuming and error-prone task. It poses challenges for the adoption and scalability of Data Spaces. In this paper, we investigate the automatic creation of machine-readable data access policies that could support users of Data Spaces. We assess the ability of Large Language Models to generate structured data access policies and validate their adherence to the defined ontology. Our findings reveal that while Large Language Models excel at producing syntactically valid policies (98% accuracy) and maintaining ontological compliance (90% accuracy), they fundamentally struggle with encoding complex logical relationships in access control rules, with only 1% of generated policies passing logical consistency validation, highlighting the continued necessity of human expertise in policy creation
Deep learning for green energy: predicting consumption and production trends across the Americas
Get PDFGreen energy projections can help meet rising energy needs, address climate change, and other challenges by forecasting future trends. This study uses data from 1965 to 2023 to predict American green energy production and consumption. The gated recurrent unit model was chosen because it shows the time-dependent structure in the data time series. This study utilized energy consumption and renewable generation sources from Kaggle, spanning from 1965 to 2022, and data from the Energy Institute website, covering the period from 2022 to 2023. The model has a mean absolute error of 0.0417 and 0.0341 for consumption and production, respectively, and a mean squared error of 0.0110 and 0.0083 for production. The GRU model achieves the highest accuracy, identifying green energy data trends with an RMSE of 0.1049 for consumption and 0.0912 for output. This study shows how this model predicts energy needs. It emphasizes the integration of renewable energy and innovation in resource distribution. The research says the Quest for More Sustainable energy systems must overcome predicted technical challenges. All stakeholders gain from improved energy management policies with this knowledge. The GRU model’s performance enables the incorporation of economic and meteorological data to enhance prediction accuracy and support global efforts to clean up the energy system
Preparation and Papermaking Properties of Dry-Cut Powder from Chemically Crosslinked BEKP
Get PDFChemical crosslinking of cellulosic fibers increases their brittleness, making them more susceptible to dry powdering. In this study, bleached eucalyptus kraft pulp (BEKP) sheets were crosslinked with glyoxal (GO) and citric acid (CA) and subsequently dry cut into powders using a Wiley cutting mill. Key variables in the powder preparation were dosages of GO and CA, as well as their respective catalysts, aluminum sulphate (alum) and sodium hypophosphite (SHP). The average fiber length of the GO and CA crosslinked pulps was reduced, at most down to 0.12 and 0.17 mm by the dry cutting, using a 0.5 mm perforated screen in the final dry-cutting stage. The powders exhibited reduced water retention, lower sedimentation volume in water, and, when dry, showed increased tapped and bulk densities. When mixed with refined BEKP, the powders enhanced dewatering during handsheet formation and improved the resulting sheets’ bulk, light scattering, and opacity, while reducing tensile strength. These findings suggest that chemically crosslinked pulp powders have potential as a bulking and dewatering aid in papermaking. Furthermore, due to their low water absorbency and presumable low abrasiveness, the powder may have potential applications beyond papermaking, such as filler of plastics, glues, and coating materials