Search Results (497)

Some chemical reactors exhibit coupled dynamics with multiple equilibrium points and strong nonlinearities. The accurate modeling of these dynamics is crucial to optimal control and increasing the reactor’s economic performance. While neural networks can effectively handle complex nonlinearities, they sacrifice interpretability. Alternatively, block-oriented Hammerstein–Wiener models and Koopman operator-based linear predictors combine nonlinear representation with linear dynamics, offering a gray-box identification approach. This paper comprehensively reviews recent advancements in both the Hammerstein–Wiener and Koopman operator methods and benchmarks their accuracy against neural network-based approaches to modeling a large-scale industrial Fluid Catalytic Cracking fractionator. Furthermore, Monte Carlo simulations are employed to validate performance under varying signal-to-noise ratios. The results demonstrate that the Koopman bilinear model significantly outperforms the other methods in terms of accuracy and robustness. Full article

Developing and identifying the correct reactor model for a reaction system characterized by a high number of reaction pathways and flow regimes can be challenging. In this work, artificial neural networks (ANNs), used in deep learning, are used to develop a hybrid modelling framework for physics-based model discovery in reactions systems. The model discovery accuracy of the framework is investigated considering kinetic model parametric uncertainty, noise level, features in the data structure and experimental design optimization via a differential evolution algorithm (DEA). The hydrodynamic behaviours of both a continuously stirred tank reactor and a plug flow reactor and rival chemical kinetics models are combined to generate candidate physics-based models to describe a benzoic acid esterification synthesis in a rotating cylindrical reactor. ANNs are trained and validated from in silico data simulated by sampling the parameter space of the physics-based models. Results show that, when monitored using test data classification accuracy, ANN performance improved when the kinetic parameters uncertainty decreased. The performance improved further by increasing the number of features in the data set, optimizing the experimental design and decreasing the measurements error (low noise level). Full article

The treatment of contaminants from road infrastructure poses significant challenges due to their variable composition and the high concentrations of chloride ions, heavy metals, and oil-derived substances. Traditional methods for protecting groundwater environments are often insufficient. A promising alternative is permeable reactive barrier (PRB) technology, which utilizes recycled materials and construction waste as reactive components within the treatment zone of the ground. This paper delves into the potential of employing a composite (MIX) consisting of modified construction aggregate (as recycled material) and activated carbon (example of reactive material) to address environmental contamination from a mixture of heavy metals and chloride. The research involved chemical modifications of the road aggregate, activated carbon, and their composite, followed by laboratory tests in glass reactors and non-flow batch tests to evaluate the kinetics and chemical equilibrium of the reactions. The adsorption process was stable and conformed to the pseudo-second-order kinetics and Langmuir, Toth, and Redlich–Peterson isotherm models. Studies using MIX from a heavy metal model solution showed that monolayer adsorption was a key mechanism for removing heavy metals, with strong fits to the Langmuir (R² > 0.80) and Freundlich models, and optimal efficiencies for Cd and Ni (R² > 0.90). The best fit, at Cd, Cu, Ni = 0.96, however, was with the Redlich–Peterson isotherm, indicating a mix of physical and chemical adsorption on heterogeneous surfaces. The Toth model was significant for all analytes, fitting Cl and Cd well and Pb and Zn moderately. The modifications made to the composite significantly enhanced its effectiveness in removing the contaminant mixture. The test results demonstrated an average reduction of chloride by 85%, along with substantial removals of heavy metals: lead (Pb) by 90%, cadmium (Cd) by 86%, nickel (Ni) by 85%, copper (Cu) by 81%, and zinc (Zn) by 79%. Further research should focus on the removal of other contaminants and the optimization of magnesium oxide (MgO) dosage. Full article

This work deals with the catalytic steam reforming of raw syngas to increase the efficiency of coupling gasification with downstream processes (such as fuel cells and catalytic chemical syntheses) by producing high-temperature, ready-to-use syngas without cooling it for cleaning and conditioning. Such a combination is considered a key point for the future exploitation of syngas produced by steam gasification of biogenic solid fuel. The design and construction of an integrated gasification and gas conditioning system were proposed approximately 20 years ago; however, they still require further in-depth study for practical applications. A 3D model of the freeboard of a pilot-scale, fluidized bed gasification plant equipped with catalytic ceramic candles was used to investigate the optimal operating conditions for in situ syngas upgrading. The global kinetic parameters for methane and tar reforming reactions were determined experimentally. A fluidized bed gasification reactor (~5 kWth) equipped with a 45 cm long segment of a fully commercial filter candle in its freeboard was used for a series of tests at different temperatures. Using a computational fluid dynamics (CFD) description, the relevant parameters for apparent kinetic equations were obtained in the frame of a first-order reaction model to describe the steam reforming of key tar species. As a further step, a CFD model of the freeboard of a 100 kWth gasification plant, equipped with six catalytic ceramic candles, was developed in ANSYS FLUENT^®. The composition of the syngas input into the gasifier freeboard was obtained from experimental results based on the pilot-scale plant. Simulations showed tar catalytic conversions of 80% for toluene and 41% for naphthalene, still insufficient compared to the threshold limits required for operating solid oxide fuel cells (SOFCs). An overly low freeboard temperature level was identified as the bottleneck for enhancing gas catalytic conversions, so further simulations were performed by injecting an auxiliary stream of O₂/steam (50/50 wt.%) through a series of nozzles at different heights. The best simulation results were obtained when the O₂/steam stream was fed entirely at the bottom of the freeboard, achieving temperatures high enough to achieve a tar content below the safe operating conditions for SOFCs, with minimal loss of hydrogen content or LHV in the fuel gas. Full article

This work presents a one-dimensional (1D) model for simulating the behavior of an FCC riser reactor processing bio-oil. The FCC riser is modeled as a plug-flow reactor, where the bio-oil feed undergoes vaporization followed by catalytic cracking reactions. The bio-oil droplets are represented using a Lagrangian framework, which accounts for their movement and evaporation within the gas-solid flow field, enabling the assessment of droplet size impact on reactor performance. The cracking reactions are modeled using a four-lumped kinetic scheme, representing the conversion of bio-oil into gasoline, kerosene, gas, and coke. The resulting set of ordinary differential equations is solved using a stiff, second- to third-order solver. The simulation results are validated against experimental data from a full-scale FCC unit, demonstrating good agreement in terms of product yields. The findings indicate that heat exchange by radiation is negligible and that the Buchanan correlation best represents the heat transfer between the droplets and the catalyst particles/gas phase. Another significant observation is that droplet size, across a wide range, does not significantly affect conversion rates due to the bio-oil’s high vaporization heat. The proposed reduced-order model provides valuable insights into optimizing FCC riser reactors for bio-oil processing while avoiding the high computational costs of 3D CFD simulations. The model can be applied across multiple applications, provided the chemical reaction mechanism is known. Compared to full models such as CFD, this approach can reduce computational costs by thousands of computing hours. Full article

Our study lies at the intersection of three fields: finite-time thermodynamics, relativity theory, and the theory of hyperbolic conservation laws. Each of these fields has its own requirements and richness, and in order to link them together as effectively as possible, we have simplified each one, reducing it to its fundamental principles. The example chosen concerns the propagation of chemical changes in a very large reactor, as found in geology. We ask ourselves two sets of questions: (1) How do the finiteness of propagation speeds modeled by hyperbolic problems (diffusion is neglected) and the finiteness of the time allocated to transformations interact? (2) How do the finiteness of time and that of resources interact? The similarity in the behavior of the pairs of variables (x, t and resources, resource flows) in Lorentz relativistic transformations allows us to put them on the same level and propose complementary-type relationships between the two classes of finiteness. If times are finite, so are resources, which can be neither zero nor infinite. In hyperbolic problems, a condition is necessary to select solutions with a physical sense among the multiplicity of weak solutions: this is given by the entropy production, which is Lorentz invariant (and not entropy alone). Full article

(1) Background: Generation IV supercritical water-cooled reactors (SCWRs), including small modular reactor (SCW-SMR) variants, are pivotal in nuclear technology. Operating at 300–500 °C and 25 MPa, these reactors require detailed understanding of radiation chemistry and transient species to optimize water chemistry, reduce corrosion, and enhance safety. Boron, widely used as a neutron absorber, plays a significant role in reactor performance and safety. This study focuses on the yields of radiolytic species in subcritical and supercritical water exposed to ⁴He and ⁷Li recoil ions from the ¹⁰B(n,α)⁷Li fission reaction in SCWR/SCW-SMR environments. (2) Methods: We use Monte Carlo track chemistry simulations to calculate yields (G values) of primary radicals (e⁻_aq, H^•, and ^•OH) and molecular species (H₂ and H₂O₂) from water radiolysis by α-particles and Li³⁺ recoils across 1 picosecond to 0.1 millisecond timescales. (3) Results: Simulations show substantially lower radical yields, notably e⁻_aq and ^•OH, alongside higher molecular product yields compared to low linear energy transfer (LET) radiation, underscoring the high-LET nature of ¹⁰B(n,α)⁷Li recoil nuclei. Key changes include elevated G(^•OH) and G(H₂), and a decrease in G(H^•), primarily driven during the homogeneous chemical stage of radiolysis by the reaction H^• + H₂O → ^•OH + H₂. This reaction significantly contributes to H₂ production, potentially reducing the need for added hydrogen in coolant water to mitigate oxidizing species. In supercritical conditions, low G(H₂O₂) suggests that H₂O₂ is unlikely to be a major contributor to material oxidation. (4) Conclusions: The ¹⁰B(n,α)⁷Li reaction’s yield estimates could significantly impact coolant chemistry strategies in SCWRs and SCW-SMRs. Understanding radiolytic behavior in these conditions aids in refining reactor models and coolant chemistry to minimize corrosion and radiolytic damage. Future experiments are needed to validate these predictions. Full article

This study aims to investigate the oxidative pyrolysis of biomass volatiles with a particular focus on the formation of liquid products. Furfural, hydroxyacetone, and 3,4-dimethoxybenzaldehyde were chosen as volatile model compounds. The impacts of the oxygen equivalence ratio (ER, 0–15%) and temperature (400–500 °C) on the product composition and distribution were examined using a two-stage quartz-tube reactor. The results showed that volatile pyrolysis was limited at the lower temperature of 400 °C even with oxygen introduction, while it could be significantly promoted at 500 °C as illustrated by the observed great decrease in the GC-MS peak areas of the volatile compounds especially under an oxidative atmosphere. For instance, the peak area of 3,4-dimethoxybenzaldehyde at 500 °C under an ER of 4% was only ~9% of that at 400 °C. Oxygen introduction enhanced the volatile decomposition with the formation of mainly permanent gases (although not given in the study) rather than liquid products, but distinct impacts were obtained for varied volatile compounds possibly due to their different chemical structures and autoignition temperatures. From the perspective of liquid product formation, furfural would undergo the cleavage of C-C/C-O bonds to form linear intermediates and subsequent aromatization to generate aromatics (benzene and benzofuran). The presence of oxygen could enhance the oxidative destruction of the C-C/C-O bonds and the removal of O from the molecules to form simple aromatics such as benzene, phenol, and toluene. Hydroxyacetone mainly underwent C-C/C-O cleavage that was further enhanced in the presence of oxygen; the resultant intermediates would recombine to generate acetoin and 2,3-pentanedione. A higher ER would directly oxidize the alcoholic hydroxyl group (-OH) into an aldehyde group (-CHO) to form methyl glyoxal, while 3,4-dimethoxybenzaldehyde mainly underwent cleavage and recombination of bonds connected with the benzene ring including aldehyde group (-CHO), C_Ar-O, C_Methoxy-O bonds, thus forming 1,2-dimethoxybenzene, toluene, and 3-hydroxybenzadehyde. This study provides more fundamental insights into the homogeneous oxidation of volatiles during the oxidative fast pyrolysis of biomass, facilitating the deployment of this technology. Full article

The decommissioning of the Zion Nuclear Power Plant (NPP) provided a unique opportunity to harvest and study service-aged reactor pressure vessel (RPV) beltline materials. This work, conducted through the U.S. Department of Energy’s Light Water Reactor Sustainability (LWRS) Program, aims to improve the understanding of radiation-induced embrittlement to support extended nuclear plant operations. Material segments containing the Linde 80 flux, wire heat 72105 (WF-70) beltline weld and the A533B Heat B7835-1 base metal, obtained from the intermediate shell region with a peak fluence of 0.7 × 10¹⁹ n/cm² (E > 1.0 MeV), were extracted, cut into blocks, and machined into test specimens for mechanical and microstructural characterization. The segmentation process involved oxy-propane torch-cutting, followed by precision machining using wire saws and electrical discharge machining (EDM). A chemical composition analysis confirmed the expected variations in alloying elements, with copper levels being notably higher in the weld metal. The harvested specimens enable a detailed evaluation of through-wall embrittlement gradients, a comparison with the existing surveillance data, and the validation of predictive embrittlement models. This study provides critical data for assessing long-term reactor vessel integrity, informing aging-management strategies, and supporting regulatory decisions to extend the life of nuclear plants. This article is a revised and expanded version of a paper entitled, “Current Status of the Characterization of RPV Materials Harvested from the Decommissioned Zion Unit 1 Nuclear Power Plant”, PVP2017-65090, which was accepted and presented at the ASME 2017 Pressure Vessels and Piping Conference, Waikoloa, HI, USA, 16–20 July 2017. Full article

Polycyclic aromatic hydrocarbons (PAHs) in biochar, as opposed to those in pyrolysis liquid products that exit the reactor without adhering to the solid product, are particularly undesirable due to their environmental persistence and potential toxicity. When applied as a soil amendment, biochar containing PAHs poses risks to soil ecosystems and human health. Their formation during pyrolysis presents a significant challenge in biochar production, requiring the optimization of pyrolysis process parameters to minimize PAH content for safe soil amendment applications. This study explored the effects of particle size and heating rate on PAH formation during corn cob pyrolysis. Thermogravimetric analysis (TGA) was employed to heat corn cob powder of varying sample masses from ambient temperature to 550 °C at heating rates of 5, 10, and 20 °C/min. Simultaneously, the Chemical Reaction Engineering and Chemical Kinetics (CRECK) model simulated the pyrolysis of spherical corn cob biomass particles with a radius ranging from 1 to 40 mm, using feedstock chemical compositions as inputs. Tar species generated from the solid biomass model were introduced into a gas-phase batch reactor model to evaluate PAH formation. The results demonstrate that the particle size and heating rate significantly affect PAH formation, shedding light on the complex dynamics of biomass pyrolysis. A single spherical particle with a radius close to 1 mm approximates ideal TGA conditions by minimizing temperature and mass transfer limitations. The CRECK model suggested that a particle radius of 5–10 mm, combined with a low heating rate of 5 °C/min, optimally reduces PAH formation. Future research should focus on using thermogravimetric analysis coupled with gas chromatography–mass spectrometry (TGA-GC-MS) to comprehensively quantify PAH species formation. Full article

This study achieves the particle-resolved modeling of biomass pyrolysis via a novel approach of integrating the Discrete Element Method (DEM) with a semi-detailed chemical kinetic mechanism. By coupling CFD-DEM with a 36-step reaction network, the multiscale interactions between particle-scale hydrodynamics and the formation kinetics of 19 tar components under varying temperatures (630–770 °C) are elucidated. Levoglucosan (44.79%) and methanol (18.64%) are identified as primary tar components. Combined with these, furfural (C₅H₄O₂, 7.22%), methanal (CH₂O, 6.75%), and glutaric acid (C₅H₈O₄, 4.20%) account for over 80% of all the tar components. The secondary decomposition pathways are successfully captured, and changes in the reaction rates, as seen in triglycerides (R23: 307.30% rate increase at 770 °C) and tannins (R24: 265.41% acceleration), are quantified. This work provides the ability to predict intermediate products, offering critical insights into reactor optimization. Full article

The electrocatalytic hydrogenation (ECH) of biomass-derived phenolic compounds is a promising approach to the production of value-added chemicals and biofuels in a sustainable way under moderate reaction conditions. This study provides a comprehensive comparison of electrochemical and thermochemical hydrogenation processes, highlighting their relative advantages in terms of energy efficiency, product selectivity, and environmental impact. Several electrocatalysts (Pt, Pd, Rh, Ru), membranes (Nafion, Fumasep, GO-based PEMs), and reactor configurations are tested for the selective conversion of model compounds such as phenol, guaiacol, furfural, and levulinic acid. The contributions made by the electrode material, electrolyte composition, membrane nature, and reaction conditions are critically evaluated in relation to Faradaic efficiency, conversion rates, and product selectivity. The enhancement in the performance achieved by a new catalyst architecture is emphasized, such as MOF-based systems and bimetallic/trimetallic catalysts. In addition, a demonstration of graphite-based membranes and membrane-separated slurry reactors (SSERs) is provided, for enhanced ion transport and reaction control. The results illustrate the potential of using ECH as a low-carbon, scalable, and tunable method for the upgrading of biomass. This study offers valuable insights and guidelines for the rational design of next-generation electrocatalytic systems toward green chemical synthesis and emphasizes promising perspectives for the strategic development of electrochemical technologies in the pathway of a sustainable energy economy. Full article

Methanol synthesis from CO₂ is a key strategy for carbon capture and utilization, offering a viable solution to mitigate climate change. The direct synthesis of methanol not only reduces greenhouse gases but also produces valuable chemicals for industrial applications. The aim of this study is to model and optimize the methanol synthesis process from CO₂, focusing on maximizing methanol yield while minimizing CO₂ content in the product stream. In this work, a detailed methanol synthesis process simulation was developed using the Soave–Redlich–Kwong equation of state in the Aspen Plus V11 commercial software environment. Pure CO₂ streams, which are produced from the post-combustion carbon capture process, and renewable hydrogen streams were used. The results are compared with open literature sources. In addition, a sensitivity analysis was employed to evaluate the effects of the pressure, temperature, and recirculation fraction on process efficiency. The results showed that the highest methanol yield of 76,838 kg/h was obtained at 80 bar, 276 °C, and a recirculation fraction of 0.9. The lowest CO₂ content in the final product (73 kg/h) occurred at 80 bar, 220 °C, and a recirculation fraction of 0.6. These findings demonstrate the trade-off between maximizing methanol output and reducing unreacted CO₂. In conclusion, optimal operating conditions for both the high yield and low CO₂ content were identified, providing a foundation for further process refinement. Future work will involve developing a more complex multi-reactor model and conducting economic assessments for large-scale industrial implementation. Full article

Syngas can be used as feedstock for efficient energy conversion in solid oxide fuel cells (SOFCs). In the current paper, the conversion efficiency of methane to synthesis gas (H₂ and CO) within a two-layer porous media reactor is investigated by a one-dimensional two-temperature model. A detailed chemical reaction mechanism GRI-Mech 1.2 is used to describe the chemical processes. Attention is focused on CO₂ content in the methane/air mixture, heat loss to the surroundings, and solid thermal conductivity on temperature distribution and conversion efficiency. Numerical results show that addition of CO₂ to the methane/air mixture improves the conversion efficiency. For a molar ratio of CO₂/CH₄ = 1, the conversion efficiency reaches 44.8%. An increase in heat loss to the surroundings leads to a decrease in conversion efficiency. A greater solid thermal conductivity can improve the conversion efficiency. Full article

In an integrated gasification combined cycle (IGCC), a gasification process produces a gas stream from a solid fuel, such as coal or biomass. This gas (syngas or synthesis gas) resulting from the gasification process contains carbon monoxide, molecular hydrogen, and carbon dioxide (other gaseous components may also be present depending on the gasified solid fuel and the gasifying agent). Separating hydrogen from this syngas stream has advantages. One of the methods to separate hydrogen from syngas is selective permeation through a palladium-based metal membrane. This separation process is complicated as it depends nonlinearly on various variables. Thus, it is desirable to develop a simplified reduced-order model (ROM) that can rapidly estimate the separation performance under various operational conditions, as a preliminary stage of computer-aided engineering (CAE) in chemical processes and sustainable industrial operations. To fill this gap, we present here a proposed reduced-order model (ROM) procedure for a one-dimensional steady plug-flow reactor (PFR) and use it to investigate the performance of a membrane reactor (MR), for hydrogen separation from syngas that may be produced in an integrated gasification combined cycle (IGCC). In the proposed model, syngas (a feed stream) enters the membrane reactor from one side into a retentate zone, while nitrogen (a sweep stream) enters the membrane reactor from the opposite side into a neighbor permeate zone. The two zones are separated by permeable palladium membrane surfaces that are selectively permeable to hydrogen. After analyzing the hydrogen permeation profile in a base case (300 °C uniform temperature, 40 atm absolute retentate pressure, and 20 atm absolute permeate pressure), the temperature of the module, the retentate-side pressure, and the permeate-side pressure are varied individually and their influence on the permeation performance is investigated. In all the simulation cases, fixed targets of 95% hydrogen recovery and 40% mole-fraction of hydrogen at the permeate exit are demanded. The module length is allowed to change in order to satisfy these targets. Other dependent permeation-performance variables that are investigated include the logarithmic mean pressure-square-root difference, the hydrogen apparent permeance, and the efficiency factor of the hydrogen permeation. The contributions of our study are linked to the fields of membrane applications, hydrogen production, gasification, analytical modeling, and numerical analysis. In addition to the proposed reduced-order model for hydrogen separation, we present various linear and nonlinear regression models derived from the obtained results. This work gives general insights into hydrogen permeation via palladium membranes in a hydrogen membrane reactor (MR). For example, the temperature is the most effective factor to improve the permeation performance. Increasing the absolute retentate pressure from the base value of 40 atm to 120 atm results in a proportional gain in the permeated hydrogen mass flux, with about 0.05 kg/m².h gained per 1 atm increase in the retentate pressure, while decreasing the absolute permeate pressure from the base value of 20 bar to 0.2 bar causes the hydrogen mass flux to increase exponentially from 1.15 kg/m².h. to 5.11 kg/m².h. This study is linked with the United Nations Sustainable Development Goal (SDG) numbers 7, 9, 11, and 13. Full article