Search Results (81)

During the life of a nuclear reactor, there are changes to the in-core components that are a function of operating environment and time. It is important to know how the properties of critical core components change, which can be assessed through materials surveillance programs. It is also desirable to characterize materials behaviour long before the end of the reactor design life. Therefore, experiments to characterize materials for in-core applications are performed in test reactors that typically have higher total neutron fluxes than power reactors. The extensive in-core materials irradiation programs that supported the validation of long-term material behaviour in CANDU (CANada Deuterium Uranium) reactors used various irradiation facilities, both domestic and international, are summarized in this paper. However, these test reactor facilities are aging and in some cases are closing, including NRU, which ceased operations in 2018. As Canada contemplates a new domestic high-flux test reactor to support both existing and potential new power reactors, this paper provides a review of the facilities and approaches that were implemented to successfully research CANDU reactor materials and can serve as a basis to define future facility requirements. Full article

This study examines the effects of graphene oxide (GO) on the hydration behaviour, microstructure, and mechanical properties of Portland cement-based materials. Cement pastes and mortars incorporating GO at dosages of 0.0005%, 0.005%, and 0.05% by weight of cement were analysed through thermogravimetric analysis (TGA), X-ray diffraction (XRD), scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM/EDS), and mechanical strength testing. TGA results indicate that GO exerts a time-dependent influence on cement hydration. At early ages, GO slightly retards hydration, evidenced by lower C–S–H and CH content in GO-containing samples at 2 and 7 days, attributed to water adsorption by its oxygen-containing functional groups. At later curing ages (28–90 days), TGA results show greater C–S–H and CH weight losses in GO-modified samples compared to the reference, consistent with GO acting as a water reservoir and nucleation site. XRD and SEM results confirm that GO incorporation leads to a reduction in CH crystal size, a denser and more homogeneous microstructure, and fewer pores and microcracks. Mechanical tests revealed that GO contents of 0.0005% and 0.05% produced the most significant improvements, with increases of up to 9% in compressive strength and 16% in flexural strength at 90 days compared with the control specimens. In summary, the incorporation of low GO dosages effectively refines cement microstructure, enhances long-term hydration, and improves mechanical performance, demonstrating GO’s potential as a strength- and durability-enhancing nanomaterial for cementitious composites. Full article

Reliable production forecasting is a critical task for evaluating asset valuation and commercial performance in oil and gas reservoirs. Conventional short-term forecasting methods, such as Arps’ decline curve analysis, rely on simple mathematical curve fitting and often oversimplify reservoir performance. On the other hand, long-term forecasting requires complex multidisciplinary models that integrate geophysics, reservoir engineering, and production engineering, but these approaches are time-consuming and have high turnaround times. To bridge the gap between long and short-term production forecasts, reduced-physics models such as Blasingame type curves have been developed, incorporating transient well behaviour derived from diffusivity equations and Darcy’s law. These models assume homogeneity and uniform reservoir properties, enabling faster results while honouring pressure performance. However, despite their efficiency, they still face limitations in reliability, particularly when extended to long-term forecasts. This paper proposes a hybrid modelling approach that integrates flowing material balance (FMB) concepts into physics-informed neural networks (PiNNs) and machine learning models to improve the accuracy and reliability of production forecasting. The proposed methodology introduces two hybrid strategies: physics-informed models enriched with FMB feature, and PiNNs. The first proposed hybrid model uses a created FMB-derived feature as input to neural networks. The second PiNN model embeds data-driven loss functions with a physics-based envelope to reflect reservoir response into the machine learning model. The primary loss function is mean squared error, ensuring minimization of data misfit between predicted and observed production rates. The study validates both proposed physically informed neural network models through performance metrics such as RMSE, MAE, MAPE, and R². Results application on field data shows that the integration of FMB into neural network models using the PiNN concept guides the neural network models to predict the production rates with higher reliability over the full span of the tested data period, which was the last year of unseen production data. Additionally, the proposed PiNN model is able to predict the well productivity index via hyper-tuning of the PiNN model. Furthermore, the PiNN is not improving the metric performance of conventional neural networks, as it has to satisfy an additional material balance equation. This is due to a lower degree of freedom in the PiNN models. Full article

Understanding the depth and severity of corrosion is vital for evaluating the long-term durability and economic performance of Zn-based structures. In this study, a machine learning (ML) framework was applied to forecast the corrosion depth of zinc under varying environmental circumstances. A dataset consisting of 300 samples compiled from previously published atmospheric corrosion studies under various environmental conditions was used to develop and evaluate the machine learning models. Seven ML algorithms were developed by integrating different environmental constraints such as temperature, time of wetness (TOW), SO₂ concentration, Cl⁻ concentration, and exposure time as input parameters. The models were trained using cross-validation and hyperparameter optimization to ensure robust predictive performance and minimize overfitting. The Random Forest (RF) model confirmed superior predictive performance with an R² of 96.4% and RMSE of 0.642 µm among all used models. The predictive ability of the optimized RF model was further confirmed using five new environmental systems, attaining excellent agreement with predicted values (R² = 97.9%, RMSE = 0.87 µm). Model interpretability analysis using SHAP (SHapley Additive exPlanations) discovered that exposure time and SO₂ concentration are the most significant parameters leading zinc corrosion behaviour. The developed ML framework provides interpretable insights into the influence of environmental parameters on atmospheric zinc corrosion behaviour and provides a reliable tool for forecasting corrosion depth. These findings highlight the potential of ML approaches to support corrosion mitigation strategies and accelerate materials design by reducing reliance on conventional trial-and-error experimentation. Full article

Background: Gaucher disease (GD) is a rare lysosomal storage disorder caused by mutations in the GBA1 gene. Traditionally, GD is classified into three subtypes based on the severity of neurological involvement; however, overlapping clinical features increasingly suggest a continuum of phenotypes rather than distinct categories. In this prospective observational cohort study, we conducted a multidisciplinary assessment of patients with GD to identify and monitor neurological, cognitive, auditory, and visual impairments. Materials and Methods: A comprehensive clinical and instrumental evaluation was performed at baseline and repeated at follow-up, with a median interval of 37 months (IQR 36–38). Neurological assessments included physical examination, clinical rating scales, video-EEG, and brain MRI. Cognitive status was assessed using a standardized battery of neuropsychological tests. Detailed audiological and ophthalmological evaluations were also conducted. Paired parametric or non-parametric tests were applied as appropriate, with Bonferroni correction for cognitive outcomes (p < 0.05). Results: Of the 22 patients assessed at baseline, 18 completed the follow-up evaluation. Neurological assessments showed a worsening of subtle parkinsonian signs, with significant increases in Movement Disorder Society–Unified Parkinson’s Disease Rating Scale Part III scores (p = 0.04) and non-motor symptom scores (p = 0.01). Two of the eighteen patients developed epilepsy during follow-up. A high prevalence of sleep disturbances was confirmed, with 27.8% exhibiting excessive daytime sleepiness and 16.7% reporting REM sleep behaviour disorder on standardized questionnaires. Compared with baseline, cognitive assessments revealed a higher proportion of patients with performance below normative population scores in at least one cognitive domain, particularly memory. Sensorineural hearing loss was confirmed in 11 of 15 patients (73.3%) who underwent audiological evaluation, with progressive worsening of audiometric thresholds observed in 7 of 11 (64%). Ophthalmological evaluations showed no changes in visual acuity or OCT findings; however, multifocal electroretinography abnormalities were detected in 12 of 13 patients. Conclusions: Through in-depth phenotyping, this study identifies measurable neurological, cognitive, and sensory progressive changes in patients with GD over time, supporting the value of tailored, multidisciplinary long-term care strategies to monitor and address emerging clinical needs in this rare disease. Full article

The transition toward low-carbon and resource-efficient construction materials has intensified interest in geopolymer binders incorporating industrial and post-consumer wastes. Waste glass powder (WGP), a silica-rich component of the global glass waste stream, has emerged as a promising circular-economy precursor in alkali-activated systems; however, reported durability trends remain inconsistent and are often interpreted without mechanistic integration. This review synthesises current knowledge of WGP reactivity, gel chemistry, and long-term performance through an explicit reaction–transport–ageing (R–T–A) framework that links dissolution behaviour and phase assemblage development to pore connectivity, ion ingress, and time-dependent degradation. Under alkaline activation, the amorphous structure of WGP promotes silica release, modifying Si/Al ratios and governing the formation of N-A-S-H or hybrid N-A-S-H/C-(A)-S-H gels. These reaction products determine transport characteristics and ageing evolution, which collectively control chemical resistance, chloride ingress, alkali–silica reaction-type instability, and dimensional stability. Variability across studies is shown to arise from imbalances in particle fineness, replacement level, precursor chemistry, and activator design rather than intrinsic inconsistency in WGP behaviour. The R–T–A framework clarifies how reaction completeness, pore network architecture, and long-term phase stability interact to produce system-dependent durability outcomes. WGP demonstrates strong potential as a circular-economy precursor in alkali-activated binders; however, reliable structural application requires durability-informed mix design grounded in coupled reaction–transport–ageing mechanisms and supported by extended exposure testing under realistic service conditions. Full article

Scarce global resources and reliance on non-renewable materials demand ecological, technology-integrated solutions. In Brazil, abundant wood resources remain underused in architectural education and practice. Introducing skills in curricula is essential for change and future adoption. This study developed a computational and digital fabrication methodology to rethink wood, exploring collaborative robotic assembly to build an embodied understanding of construction constraints. The Wood Innovation for Architecture in Brazil (WI-FAB) unites LAMO UFRJ and SDU CREATE robotics expertise and frames a pedagogical experiment in sustainable wood-structure design. The semester-long course tested whether the design framework could link computation, material behaviour, and assembly constraints as a pedagogical tool; the intensive workshop investigated how robotic assembly can enhance physical–digital workflows and inform future integration. The research-through-teaching methodology consisted of three phases: preliminary research, course testing, and a robotics workshop testing assembly workflows. Preliminary research developed a pedagogical framework comprising a kit of parts, joint types and string grammars tested within the semester-long course to support parametric rules and assembly sequencing. Participants assembled component “letters” that combined into “words” and then into “phrases”, developing computational and constructional understanding and converting parametric rules into tangible prototypes through iterative design-build-test cycles. Key outcomes include validation of parametric assembly rules through string grammars in the course; analysis of the robotics workshop applied four criteria (Assembly Movement; Component Geometry and Dimensions; Component Number and Slot Number; Complexity and Assembly Time) to evaluate assembly performance and workflow integration. Robotics stimulated physical–digital loops, accelerating design-to-assembly learning and informing full-scale developments. WI-FAB promotes reversible assembly, material reuse and circular-economy principles and contributes to the development of the forthcoming Sabiá parametric plugin for wooden joint design. Full article

Qualification is the evidence-based process through which confidence is established that a component will perform its intended function, in its intended environment, for its intended lifetime, with the required reliability. It is an owner-led activity that defines the type, quantity and quality of data required for codification and for the industrial deployment of components and their structural materials. This paper presents a structured qualification framework and applies it to a fusion machine breeder blanket structure as a representative component. It demonstrates that qualification, rather than material properties alone, dictates the use of fusion structural materials and the deployment of such materials under ASME BPV and AFCEN RCC codes. Current limitations in addressing irradiation synergy, liquid metal corrosion, and joint integrity expose gaps that these codes cannot yet prescribe. Two contrasting structural blanket material case studies: metallic-based ferritic-martensitic steel Eurofer97 and non-metallic-based silicon carbide fibre-reinforced composites (SiC_f/SiC) are used to illustrate the differing evidence requirements for each system type. Industrial scale-up considerations, including alloy specifications, manufacturing readiness, inspection reliability, and supply-chain maturity, are evaluated alongside the need for internationally harmonised datasets and design methodologies. Fusion programmes can use a phased qualification strategy in which early, time-limited operation under controlled conditions builds the evidence needed for codification and scale-up, with the required pre-operation qualification level depending on risk, component criticality and failure consequences, and with the pace of qualification ultimately setting how quickly industry can supply components for commercial fusion. Codification remains essential for commercial deployment because construction codes express codified material behaviour through allowable stresses and permitted fabrication routes, enabling designers to use advanced materials without disclosing proprietary data. In jurisdictions where ASME BPV compliance is mandatory, codification determines whether a material may enter pressure boundary service and must therefore form part of the fusion machine owner’s long-term strategy for deployment. Full article

Additive manufacturing (AM) has rapidly evolved from a prototyping tool into an effective method for producing end-use components, thanks to its ability to produce complex, lightweight and customised parts. However, this technique requires a thorough understanding of the long-term behaviour and degradation mechanisms of components, especially when polymers are involved in the printing process. Unlike polymer components manufactured using traditional methods, polymers produced through AM exhibit unique microstructures, anisotropies, and interfacial characteristics due to the layer-by-layer fabrication process. These features can affect how these materials respond to thermal, mechanical and environmental stresses over time. Furthermore, technology-specific processing parameters directly govern porosity distribution, crystallinity evolution, interlayer bonding quality, and residual stress development, all of which are key factors for ensuring long-term performance. This review aims to support researchers in the development of durable additively manufactured polymer components by systematically analysing polymer degradation mechanisms, accelerated ageing and lifetime prediction methodologies. Following a PRISMA-based screening process, approximately 160 international standards relevant to polymer durability in additive manufacturing were selected from an initial corpus of about 620 documents for in-depth analysis. Processing–structure–property relationships specific to the AM processing of polymers, including the commonly used FFF (fused filament fabrication), SLA (stereolithography) and SLS (selective laser sintering), are examined in relation to crucial aspects for long-term structural integrity and degradation behaviour. Finally, limitations within the current normative framework are identified, emphasising the absence of process-aware durability assessment protocols and the need for dedicated standards tailored to additively manufactured polymer components. Full article

The mechanisms of aim-setting and decision-making in criminal activity as a four-level hierarchical structure were presented for the Russian criminals known as ‘vory v zakonie’. The first level represents a basic concept of saving one’s own life, borrowed from the Torah. The second level, the ‘Thieves’ Law’, is a set of mental models that has much in common with the adaptation and misinterpretation of old religious and legal systems. The third level is a set of general concepts and ideas about what Good or Evil is in the form of words called ‘Notions’. These levels have no material form; they reflect themselves in models of behaviour and argot as a collective output. The fourth level in the material form of page-long ‘secrete messages’, containing some models of behaviour, are the ‘Frames’ (how to behave in imprisonment), wherein the ‘Vory’s Commandments’ (how to behave at large for young criminals) do not belong to the criminal ideology. This criminal ideology, a discrete antisystem, is enriched by the three ideas found in old religious and legal systems proposed as the ‘fifth feeling of Time’: the memory of the soul in the endless time being awoken after reincarnation, making the past as if it never happened, and knowing the future. Full article

In this paper, we consider the solution of the initial-value problem in thermodiffusion in a solid body in three-dimensional space. Not only do we prove the behavior of the solution over time, but we identify some of its technical aspects as well. Stabilizing a thermodiffusion system in solids is essential for understanding the long-time behaviour of some materials, which are used in mechanical engineering; this is especially important for materials used in aviation, not only in civil aviation but in the air force as well. Full article

Contemporary knee prostheses rely predominantly on a metal–polyethylene bearing couple, which—despite substantial advances in material engineering—continues to generate polymeric wear particles over time. While the local biological effects of polyethylene debris, such as inflammation and osteolysis, are well-characterised, their potential systemic implications remain insufficiently explored. In this review, we synthesise multidisciplinary evidence to evaluate the generation, biological behaviour, and systemic dissemination of polyethylene-derived nano- and microplastics (NMPs) released from knee prostheses. We also contextualise prosthetic wear within the broader toxicological framework of NMP exposure, highlighting translocation pathways, interactions with immune and metabolic systems, and potential multi-organ effects reported in recent experimental and clinical studies. Current findings suggest that prosthetic wear may represent an under-recognised internal source of NMP exposure, with possible implications for long-term patient health. A clearer understanding of the systemic behaviour of prosthetic-derived NMPs is essential to guide future biomonitoring studies, improve prosthetic materials, and support the development of safer, more biocompatible implant designs. Full article

Carbon nanocomposites are essential supports in fuel cell catalysts, ensuring dispersion, anchoring, and reactant access. Here, we demonstrated an in situ synthesis of Pd nanoparticles using electrogenerated hydrophilic carbon (EHC) matrix that acts simultaneously as Pd support and reducing agent. To further enhance oxygen availability, a second EHC form with high oxygen storage capacity was integrated. The resulting material was characterized in terms of its electrochemical behaviour and long-term stability and compared with a nanocomposite without the O₂-storing component. A time-dependent decline in electrolyte access to Pd sites was observed in both, but substantially mitigated at long-term by the oxygen-storing component. Full article

Elastomeric materials exhibit complex time-dependent behaviour under mechanical loading, necessitating accurate constitutive models for industrial applications. This study investigates the hyperelastic and viscoelastic responses of two carbon black-filled natural rubber compounds (50 ShA and 60 ShA) through cyclic shear/compression tests and stress relaxation experiments. The Arruda–Boyce model captures equilibrium behaviour, while the Bergström–Boyce model predicts transient viscoelasticity without relying on Prony series. Considering the results obtained it can be concluded that quantitative hysteresis analysis shows 7–26% energy dissipation, dependent on hardness and strain rate. Relaxation rates (10⁻⁶–10⁻⁷ s⁻¹) inversely correlated with hysteresis, validated by FEM simulations. A deviation of <3.5% between experiments and simulations confirms the model’s robustness for long-term viscoelastic predictions. This framework enables the efficient design of rubber components (e.g., seismic isolators, seals) requiring prolonged durability under load. Full article

The number of endoprosthetic implants is constantly increasing. Successful osseointegration of the inserted material into the bone is essential for a prosthesis to remain in the bone as long as possible. In the clinical setting, a roughened titanium surface of implants is used as standard to enable the best possible osseointegration. Vitamin K2 and vitamin D3 play a decisive role in dynamic bone metabolism and therefore also influence osseointegration. For the first time, we carried out in vitro investigations with clinically relevant cells, primary healthy human osteoblasts (hOBs). We qualitatively compared the adhesion behaviour of hOBs on a plastic surface, a smooth, regular titanium surface structure and a roughened, irregular titanium surface structure by scanning electron microscopy and fluorescence microscopy. The osteogenic behaviour and the osteogenic differentiation capacity were quantitatively investigated by analysing the activity of alkaline phosphatase and the alizarin red S assay under the influence of vitamin K2, vitamin D3 and the combination of both vitamins. It was shown that more adhesion points formed between the cells and the titanium on the rough surface structure. In addition, a solid cell network developed more quickly on this side, with cell runners forming in three-dimensional space, which means the interactions between the cells across different cell layers. On the other hand, a structured cell network also appeared on the regular smooth surface structure, which means that the network seems to be formed and built up along a defined structure. The addition of vitamins further increased the osteogenic differentiation capacity on the rough titanium surface structure. In particular, the isolated addition of vitamin K2 showed an improved osteogenic differentiation in the long-term observation, whereas the combined addition of both vitamins promoted the initial osteogenic differentiation. Vitamin K2, therefore, plays a greater role in osseointegration than previously assumed. This opens up new possibilities for the use of vitamin K2 during and after the surgical insertion of an implant. The use of vitamin K2 should be reconsidered for clinical applications in implant care and further investigated clinically. Full article