Search Results (609)

During the operation of nuclear power plants, nuclear fuel undergoes significant compositional changes. After several cycles of use, the fuel must be removed and stored. Currently, spent fuel is stored mainly in pools or casks, and it is necessary to demonstrate the subcriticality of these systems. Spent nuclear fuel has a complex composition, and because computational codes are typically validated using fresh-fuel experiments, subcriticality assessments are usually performed conservatively with fresh-fuel compositions. These approaches demonstrate subcriticality but are very conservative and can lead to storage system designs that are more expensive or have reduced capacity. This paper focuses on the validation of computational codes using nuclear power plant critical start-up tests (referred to as reactor criticals). These tests include spent fuel and are well documented, allowing them to serve as validation experiments. Codes validated using reactor criticals can be applied to systems containing spent fuel calculation if sufficient similarity is demonstrated. Similarity is evaluated using the SCALE TSUNAMI-IP module, which is widely used for this purpose. Based on a database containing dozens of reactor criticals and similarity analyses, we developed a methodology for demonstrating the subcriticality of spent-fuel storage systems. Full article

Potassium superoxide (KO₂) can form during the oxidation of residual potassium in NaK-contaminated cold traps of sodium-cooled fast reactors. Its strong oxidizing nature, combined with limited thermal stability, raises safety concerns during shutdown and maintenance. Here, we integrate first-principles calculations with experiments to clarify the facet stability, temperature-driven surface evolution, and stepwise thermal decomposition of KO₂. Guided by the tetragonal I4/mmm crystal symmetry of bulk KO₂, symmetry-non-equivalent low-index facets and relevant surface terminations were systematically evaluated to identify physically meaningful exposed surfaces. Ab initio molecular dynamics (AIMD) simulations further show that heating induces progressive surface amorphization and enhanced oxygen mobility, accompanied by the emergence of shortened O-O bonds and outward migration of oxygen species. Kinetic analysis using the climbing-image nudged elastic band (CI-NEB) method indicates that oxygen evolution is preferentially mediated by O₂ release rather than atomic oxygen escape. Differential scanning calorimetry (DSC) reveals two endothermic events consistent with sequential decomposition, while X-ray diffraction (XRD) confirms the transformation of KO₂ into K₂O. Collectively, these results provide an atomistic-to-macroscopic understanding of KO₂ decomposition, offering practical guidance for defining safer preheating windows and handling strategies for NaK-contaminated components. Full article

The integration of blockchain technology into Cyber–Physical Systems (CPS) offers decentralized resilience against data manipulation. This also introduces stochastic consensus latencies that threaten real-time control stability. We present a Stochastic-Aware Blockchain Predictive Control (SAB-PC) framework, which models blockchain-induced jitter as a state-dependent Markovian process, and embeds it within a Markovian Jump Linear System (MJLS) formulation. Using mode-dependent Linear Matrix Inequalities (LMIs), we derive Mean Square Stability (MSS) conditions, which capture the interaction between decentralized consensus dynamics and closed-loop control behavior. The framework is validated on the Tennessee Eastman Process (TEP) benchmark, using a calibrated stochastic delay model that reflects realistic blockchain congestion patterns. Our results show that standard blockchain-mediated control architectures become unstable under Practical Byzantine Fault Tolerance (PBFT)-induced quadratic latency growth, whereas SAB-PC maintains stable operation across decentralized networks up to 60 validator nodes. The predictive Safety Runway effectively masks long-tail delay distributions, ensuring real-time feasibility and preserving safe Reactor Pressure trajectories. Under coordinated False Data Injection (FDI) attacks, SAB-PC limits pressure deviations to only 1.2 kPa despite an 8.0 kPa adversarial bias, demonstrating cryptographic and control-theoretic resilience. Full article

Sulfonamide antibiotics (SAs) are ubiquitous and persistent organic contaminants in aquatic and soil ecosystems due to their extensive application and high structural stability, causing rising environmental hazards. Conventional treatment approaches, generally based on physical adsorption or biological processes, remain limited in achieving efficient and stable removal as well as deep molecular modification of SAs. In recent years, modified biochar has developed as a flexible environmental functional material incorporating adsorption and reaction regulation capabilities, owing to its customizable pore structure, surface chemistry, and electronic characteristics. This study comprehensively highlights current achievements in the adsorption and degradation of sulfonamide antibiotics by modified biochar, with specific emphasis on modification techniques, structural modulation, structure–performance connections, and interfacial reaction processes. Through physical activation, heteroatom doping, defect engineering, and metal integration, biochar has developed from a traditional adsorbent into a carbon-based interfacial reactor capable of pollutant adsorption, molecular activation, and directed transformation. Surface-confined reaction interfaces, where π–π interactions, hydrogen bonding, electrostatic interactions, and metal coordination cooperatively control adsorption and transformation processes, are primarily responsible for the elimination of SAs. Moreover, the dual functions of modified biochar in driving both radical and non-radical pathways are explored, showing the vital importance of interfacial electronic structure modulation and electron-transfer mechanisms in influencing reaction efficiency and selectivity. The impact of sulfonamide molecular configurations, ambient circumstances, and concomitant chemicals on removal performance are also explored. Unlike previous reviews that mainly summarize adsorption efficiency or oxidant activation systems separately, this work integrates structural modulation, interfacial electronic regulation, and bond-selective transformation mechanisms into a unified structure–chemistry–reactivity framework. By correlating sulfonamide molecular configuration with biochar electronic structure, this review provides a mechanistic roadmap for the rational design of next-generation catalytic biochar systems. Finally, key challenges related to structural controllability, long-term stability, and engineering scalability are identified, and future research directions are proposed to support the rational design of high-performance biochar materials and the practical control of sulfonamide antibiotic pollution. Full article

This study analyzes hydrodynamics and mass transfer in a packed-bed reactor (PBR) by comparing two representations of bed geometry. The first is a pseudo-homogeneous approach using effective parameters, such as a radial porosity distribution. The second is a heterogeneous approach with resolved particles in the CAD domain. Both models simulate single-phase flow and mass transfer of urea and NH₃ for an enzymatic reaction across a wide Reynolds number range $\left(5\le {\mathrm{Re}}_p\le 750\right)$. The pseudo-homogeneous model incorporated a detailed porosity distribution, derived from the heterogeneous model’s solids layout, which aligned well with literature, including classical correlations for radial porosity in packed beds. Additionally, hydrodynamic predictions were benchmarked against established pressure-drop correlations for confined packed beds, supporting the physical consistency of the particle-resolved framework. This non-uniform porosity informed local variations in permeability and dispersion coefficients. Velocity, pressure, and concentration fields from both approaches were compared to quantify predictive quality. Results indicate that a well-configured pseudo-homogeneous model can closely match heterogeneous model predictions, achieving similar accuracy in many flow regimes, with accumulated average relative errors below 8%. However, its performance varies with flow conditions. The optimal pseudo-homogeneous model (showing the highest predictive consistency with the particle-resolved simulations) was then used for transient simulations. These dynamic results support the preliminary sizing and conceptual design of a device for nutrient recovery from human urine for agricultural use, demonstrating the utility of simplified models for complex reactor design while acknowledging that full experimental validation under real urine-matrix conditions remains beyond the scope of the present study. Full article

A prestressed concrete containment vessel (PCCV) serves as the final physical barrier for nuclear reactors, with its structural integrity being critical to prevent radioactive release during accident scenarios. Addressing structural complexity at the dome–cylinder interface of prestressed concrete containments, arising from its geometric discontinuities and complex stress concentrations, this study systematically investigates the structural behavior and force distribution under coupled thermal and internal pressure loads due to nuclear accident. A parametrical nonlinear finite element (NLFE) PCCV model based on concrete damaged plasticity (CDP) theory is developed and first validated using the results from two different experimental tests. The validated NLFE model is then used to conduct a series of parametrical studies that are based on the practical example of nuclear PCCVs in China. The effects of various design parameters including the dome–cylinder thickness ratio, reinforcement ratio, accidental temperature and accidental pressure loads are studied in detail. The results show that current practice in nuclear concrete containment design using linear FE with a reduced concrete modulus may significantly underestimate both the moments and shear forces at the dome–cylinder interface, by factors of up to 1.55 times and 3.91 times, respectively. In conclusion, this work quantifies the shear amplification effect driven by the stiffness redistribution mechanism and proposes specific amplification factors to ensure the structural integrity of containment vessels under severe accident conditions. Full article

Composting chicken manure is a source of significant ammonia (NH₃) emissions, which, because of propagation, contributes to the eutrophication of the environment and decreases in air quality. Therefore, it is reasonable to use methods to limit its emission into the atmosphere. Biofiltration, using the metabolic activity of nitrifying and heterotrophic microorganisms capable of oxidizing ammonia, is an effective method to reduce ammonia emissions. In addition, the performance of the biofiltration process depends on operational parameters such as the humidity of the medium, the temperature, the contact time of the gas with the biofiltering medium, and the chemical composition and structure of the filter material. The aim of the study was to evaluate the effectiveness of biofilter fillings in reducing ammonia emissions from composting chicken manure along with the identification of factors allowing us to determine the proposed design solution as the most advantageous in terms of efficiency. Experiments on reducing odour emissions with biofiltration were carried out in two compact composting reactors, in which a compost mixture with a C:N ratio of 10:1 was used. The mixture was prepared in a ratio of 5:1 of chicken manure to the structuring material, with wheat straw used as the structuring material. Based on the results of the research on the course of the composting process, high values of ammonia concentration were recorded. Ammonia concentrations of 886 ppm (composter 1) and 811 ppm (composter 2) were recorded, which confirms the intensive nature of this gas emissions during the process of stabilizing the chicken manure. As part of the conducted research, the effectiveness of biofiltration in reducing ammonia emissions was evaluated by analysing the influence of the aeration intensity of the biofilter (20 dm³/h and 50 dm³/h), directly determining the time of contact of the gas with the bed (EBCT—Empty Bed Contact Time). Coconut-activated carbon was used as a filter bed, which was an effective carrier for the development of microorganisms responsible for the biological removal of ammonia from waste gases generated during composting. In addition, this material showed the ability to physically adsorb ammonia, thus supporting the process of its elimination. Each of the test stations has been equipped with a biofiltration installation. To determine the effectiveness of biological removal of ammonia and to assess the legitimacy of the use of selected strains of microorganisms in the process of biological removal of ammonia, the bed of one of the biofilters (biofilter 2) was inoculated with a strain of nitrifying bacteria. During the study, the high efficiency of ammonia removal because of biofiltration was noted in each of the configurations. In the case of an aeration intensity of 20 dm³/h, a reduction in emissions of 99% was achieved; with a higher aeration value, i.e., 50 dm³/h, the efficiency was 89%. These results indicate that the intensity of aeration has a significant impact on the efficiency of the biofiltration process. The analysis of a biofilter enriched with a strain of nitrifying bacteria requires long-term testing. This is important to reliably determine the effect of inoculation on the efficiency of the biological removal of ammonia in biofilters. It has been shown that optimizing these factors allows us to achieve a reduction in ammonia emissions of up to 90%, while minimizing the formation of unpleasant odours. The use of biofiltration in composting systems for organic waste of animal origin is an effective, sustainable solution that fits into the idea of sustainable development, combining the efficiency of air purification technology with environmental protection and the responsible management of resources. This study demonstrates that biofiltration using coconut-shell-activated carbon is an effective and economical method for reducing ammonia and odour emissions from composting chicken manure. The results provide valuable theoretical and practical information on emissions management in organic waste composting processes. Data from this study could be useful in developing strategies to minimize odour emissions, including from the agricultural sector. Full article

This work presents a comprehensive analysis of reactor modeling studies for the methanation of CO_x, with the aim of identifying trends, evaluating modeling strategies, and suggesting a generalized modeling framework. The analysis spans a wide range of configurations, including packed/fixed-bed reactors (immobilized catalyst pellets/particles), fluidized-bed reactors, and structured catalyst reactors, as well as membrane and slurry/bubble-column configurations when applicable. This highlights the diversity of modeling approaches used, ranging from simple 1D pseudo-homogeneous models to complex 2D heterogeneous simulations. Emphasis is placed on the governing assumptions, dimensional formulations, transport phenomena, and kinetic models employed across studies. By systematically comparing these models, this work identifies the most critical modeling assumptions and parameters that govern the prediction reliability of reactor performance (e.g., conversion and temperature profiles) and inform reactor design. The proposed reactor model integrates insights from the literature, balancing model fidelity and computational feasibility, and serves as a foundational tool for future modeling efforts and industrial applications. This work contributes to the field by offering a unified perspective that links model complexity to physical realism, providing valuable guidance in the development of predictive tools for CO_x methanation systems. Full article

Gas–liquid–solid (G-L-S) mechanically agitated reactors are commonly used in chemical, pharmaceutical and bioprocessing applications due to their low operating costs and controlled and effective mixing. Computational Fluid Dynamics (CFD) is a powerful tool that enhances the understanding of flow dynamics, phase interactions and reactor performance. However, the CFD modeling of G-L-S mechanically agitated reactors is not extensively studied in the literature due to complex multiphase interactions, along with reactor design variations. This paper provides a critical synthesis of the literature, offering an overview not only of G-L-S stirred tank CFD modeling approaches but also of practical guidance on their selection and validation. Emerging high-resolution experimental techniques such as Electrical Resistance Tomography (ERT) coupled with pressure transducers, and Machine Learning (ML) models combined with experimental data, look promising to overcome current three-phase validation limitations. Future work to enhance predictive capabilities and reactor design and operation includes developing real-time digital twins, physics-based ML models and/or hybrid CFD-ML models. Full article

In this paper, several optimized design results of the HTGR-based 10 MWth Reaktor Daya Eksperimental (RDE) (Experimental Power Reactor), so far conducted, are reviewed and compared from the neutronics, reactor types, refueling schemes, and fuel cycle points of view. The review covers the multipass and once-through-then-out (OTTO) pebble-bed cores, as well as block/prismatic type cores with several fuel shuffling options. As for the fuel cycle, uranium and thorium fuels are considered. The fuel burnup performance and power distribution are evaluated and compared among other important design parameters. Reactor physics codes, nuclear data libraries, and calculation models and procedures used for the design and analysis are reviewed, and challenges for future improvements are discussed. Full article

Fixed-bed reactors are pivotal in chemical industries, where catalyst loading critically determines reactor performance and economy. This critical review delineates and analyzes a three-stage evolution of loading technology: from empirical manual methods, through scenario-adaptive innovations, to closed-loop intelligent systems. It aims to decode the underlying scientific principles, assess the performance enhancements and inherent limitations of each stage, and critically examine the architectural framework and constraints of intelligent loading systems. Industrial validation data, such as from a 2.4 Mt/a hydrocracker, demonstrate potential improvements (e.g., 20–22% catalyst life extension, 1.8% bed pressure-drop fluctuation). However, the progression presents complex trade-offs in terms of scalability, cost, and standardization. The future direction is discussed, pointing toward addressing challenges in multi-physics modeling, digital twin integration, and fundamental research gaps. This work provides a balanced framework for evaluating loading technology evolution, acknowledging its context-dependent applicability. Full article

Large Language Models (LLMs) are increasingly used in industrial monitoring and decision support, yet they remain prone to process-control hallucinations—diagnoses and explanations that sound plausible but conflict with physical constraints, sensor data, or plant dynamics. This paper investigates hallucination as a failure of abductive reasoning, where missing premises, weak mechanistic support, or counter-evidence lead an LLM to propose incorrect causal narratives for faults such as pump restriction, valve stiction, fouling, or reactor runaway. We develop a neuro-symbolic framework in which Abductive Logic Programming (ALP) evaluates the coherence of model-generated explanations, counter-abduction generates rival hypotheses that test whether the explanation can be defeated, and Discourse-weighted ALP (D-ALP) incorporates nucleus–satellite structure from operator notes and alarm logs to weight competing explanations. Using our 500-scenario Process-Control Hallucination Dataset, we assess LLM reasoning across mechanistic, evidential, and contrastive dimensions. Results show that abductive and counter-abductive operators substantially reduce explanation-level hallucinations and improve alignment with physical process behavior, particularly in “easy-but-wrong’’ cases where a superficially attractive explanation contradicts historian trends or counter-evidence. These findings demonstrate that abductive reasoning provides a practical and verifiable foundation for improving LLM reliability in safety-critical process-control environments. Full article

The valorization of agro-industrial waste could be a strategy to improve organic waste management. The production of activated carbon (AC) is a path to use for this waste, with the aim of reducing its negative effects. AC is characterized by a high internal surface area, chemical stability, and oxygen-containing functional groups in its structure. This work is focused on the valorization of agro-industrial waste such as pineapple peel and coconut shells. These are made up of sucrose, glucose, fructose, and other essential nutrients, as well as cellulose, hemicellulose, and lignin. Activated Carbon was obtained with slow pyrolysis at 400 °C, for 4 h in a stainless-steel tubular reactor with physical activation. The obtained samples were analyzed using SEM, TGA, FTIR, and BET to verify the morphology, thermal degradation, functional groups and pores ratio of the AC, highlighting the presence of materials pore >10 µm. The TGA residual materials gave 16.3% of pineapple peel AC ashes and 0.2% of coconut AC. A C=C, C-H_X, CO, and OH stretching were observed in 400–4000 cm⁻¹. The peak intensity decreased once the biodiesel was treated with AC, because the traces of water and functional groups interacted actively, resulting a high content of bases. Activated carbon was used for dry cleaning of the obtained biodiesel from residual oil, which was effective in reducing pH and moisture levels in the biodiesel samples. Pore distribution was determined by BET, 5.6 nm for pineapple peel and 39.8243 nm for coconut shells. The obtained activated carbon offers a sustainable alternative to traditional carbon sources and contributes to the circular economy by recycling waste biomass. Full article

The rapid growth and seasonal availability of agricultural materials, such as straws, stalks, husks, shells, and processing wastes, present both a disposal challenge and an opportunity for renewable fuel production. Solar-assisted thermochemical conversion, such as solar-driven pyrolysis, gasification, and hydrothermal routes, provides a pathway to produce bio-oils, syngas, and upgraded chars with substantially reduced fossil energy inputs compared to conventional thermal systems. Recent experimental research and plant-level techno-economic studies suggest that integrating concentrated solar thermal (CSP) collectors, falling particle receivers, or solar microwave hybrid heating with thermochemical reactors can reduce fossil auxiliary energy demand and enhance life-cycle greenhouse gas (GHG) performance. The primary challenges are operational intermittency and the capital costs of solar collectors. Alongside, machine learning (ML) and AI tools (surrogate models, Bayesian optimization, physics-informed neural networks) are accelerating feedstock screening, process control, and multi-objective optimization, significantly reducing experimental burden and improving the predictability of yields and emissions. This review presents recent experimental, modeling, and techno-economic literature to propose a unified classification of feedstocks, solar-integration modes, and AI roles. It reveals urgent research needs for standardized AI-ready datasets, long-term field demonstrations with thermal storage (e.g., integrating PCM), hybrid physics-ML models for interpretability, and region-specific TEA/LCA frameworks, which are most strongly recommended. Data’s reporting metrics and a reproducible dataset template are provided to accelerate translation from laboratory research to farm-level deployment. Full article

Liquid-fueled molten salt reactors (MSRs) are characterized by the use of liquid nuclear fuel, which leads to a unique thermal-hydraulic phenomenon in the core involving the simultaneous occurrence of nuclear fission heat generation and convective heat transfer. This distinctive behavior creates a critical need for high-fidelity experimental data on internally heated flows, yet such studies are severely constrained by the lack of methods to generate controllable, high-power-density volumetric heat sources in fluids. To address this methodological gap, this study proposes and numerically investigates a novel experimental concept based on microwave heating. The design features an innovative multi-tier hexagonal resonant cavity with fifteen strategically staggered magnetrons. A comprehensive multi-physics model was developed using COMSOL Multiphysics to simulate the coupled electromagnetic, thermal, and fluid flow processes. Simulation results confirm the feasibility of generating a volumetric heat source, achieving an average power density of 6.9 MW/m³. However, the inherent non-uniformity in microwave power deposition was quantitatively characterized, revealing a high coefficient of variation (COV) for power density. Crucially, parametric studies demonstrate that this non-uniformity can be effectively mitigated by optimizing the flow channel geometry. Specifically, using a smaller diameter tube or an annulus pipe significantly improved temperature field uniformity, reducing the temperature COV by over an order of magnitude, albeit at the cost of reduced absorption efficiency. Preliminary discussion also addresses the extension of this approach towards molten salt experiments. The findings establish a practical design framework and provide quantitative guidance for subsequent experimental investigations into the thermal-hydraulic behavior of internally heated fluids, offering a promising pathway to support the design and safety analysis of liquid-fueled MSRs. Full article