Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article A Physics-Informed Neural Network (PINN) Approach to Over-Equilibrium Dynamics in Conservatively Perturbed Linear Equilibrium Systems(MDPI, 2025) Dutta, Abhishek; Mukherjee, Bitan; Hosen, Sk Aftab; Turan, Meltem; Constales, Denis; Yablonsky, GregoryConservatively perturbed equilibrium (CPE) experiments yield transient concentration extrema that surpass steady-state equilibrium values. A physics-informed neural network (PINN) framework is introduced to simulate these over-equilibrium dynamics in linear chemical reaction networks without reliance on extensive time-series data. The PINN incorporates the reaction kinetics, stoichiometric invariants, and equilibrium constraints directly into its loss function, ensuring that the learned solution strictly satisfies physical conservation laws. Applied to three- and four-species reversible mechanisms (both acyclic and cyclic), the PINN surrogate matches conventional ODE integration results, reproducing the characteristic early concentration extrema (maxima or minima) in unperturbed species and the subsequent relaxation to equilibrium. It captures the timing and magnitude of these extrema with high accuracy while inherently preserving total mass. Through the physics-informed approach, the model achieves accurate results with minimal data and a compact network architecture, highlighting its parameter efficiency.Article Fractionation of Guaiacyl and Syringyl-Lignin Units Using Organic Solvent Nanofiltration(Elsevier, 2026) Croes, Tim; Dutta, Abhishek; Van Aelst, Korneel; Sels, Bert; Van der Bruggen, Bart; Cornet, IrisA major obstacle to employing the full potential of lignin-based aromatics is the fractionation of the monomers present in lignin, specifically the separation of guaiacyl (G) and syringyl (S) units, which possess nearly identical molecular weights (196 Da versus 166 Da) and dimensions, and identical functional groups. Such similarities make their separation highly challenging using conventional techniques and are generally considered beyond the capabilities of size-based membrane processes. This study examines the feasibility of organic solvent nano-filtration for fractionation of guaiacyl and syringyl units, and how membrane and process parameters affect separation of these two molecules. Sixteen commercially available membranes were tested with methanol and ethyl acetate as solvents. The results demonstrate that, despite the extreme similarity of the solutes, selective separation is achievable and is primarily governed by membrane material and solvent selection rather than the pore size-based molecular weight cut-off. Polyimide-based solvent-resistant membranes exhibited the highest selectivity, with a maximum observed separation factor of 3.33 obtained using a DuraMemTM 500 membrane in methanol. These findings demonstrate the potential of nanofiltration to address previously unresolved separation challenges in lignin valorization and provide a basis for further process development.Article Citation - WoS: 2Citation - Scopus: 1A Novel Framework for Droplet/Particle Size Distribution in Suspension Polymerization Using Physics-Informed Neural Network (PINN)(Elsevier Science Sa, 2025) Turan, Meltem; Dutta, AbhishekA Machine Learning (ML) based neural network can capture the complex evolution of polymer chain distributions, accounting for factors such as initiation, propagation, and termination steps in a suspension polymerization process, by integrating stagewise molar balance model (MBM) and population balance model (PBM) with Physics-Informed Neural Network (PINN). The integrated PINN framework is proposed to efficiently solve these equations, incorporating known physical laws as constraints and minimizing errors in both the distribution and dynamics of the polymer chains. By optimizing the neural network parameters such as weight matrices and bias vector, the model reproduces the moments of the polymer molecular weight distribution in close alignment with numerical solutions, and it generates population balance solutions that exhibit excellent agreement with their analytical counterparts. Sensitivity analyses for the depth of the neural network architecture to quantify how structural choices affect model fidelity has been performed. The resulting MBM-PINN and PBM-PINN integrated framework demonstrates robustness and versatility in accurately capturing (96-97%) droplet/particle dynamics. The proposed methodology has the capability to provide a powerful tool for faster and scalable simulations of polymerization reactions, enabling better prediction of product properties which could be used for optimizing reaction conditions in industrial applications.Article Citation - WoS: 1Citation - Scopus: 1Polynomial Approaches in Improving Accuracy of Probability Distribution Estimation Using the Method of Moments(Wiley, 2024) Turan, Meltem; Munkhammar, Joakim; Dutta, AbhishekBACKGROUNDDetermination of a probability density function (PDF) is an area of active research in engineering sciences as it can improve process systems. A previously developed polynomial method-of-moments-based PDF estimation model has been applied in the research to produce accurate approximations to both standard and more complex PDF. A model with a different polynomial basis than a monomial is still to be developed and evaluated. This is the work that is undertaken in this study.RESULTSA set of standard PDF (Normal, Weibull, Log Normal and Bimodal) and more complex distributions (solutions to the Smoluchowski coagulation equation and Population Balance equation) were approximated by the method-of-moments using Chebyshev, Hermite and Lagrange polynomial-based density functions. Results show that Lagrange polynomial-based models improve the fit compared to monomial based-modeling in terms of RMSE and Kolmogorov-Smirnov test statistic estimates. The Kolmogorov-Smirnov test-statistics decreased by 19% and the RMSE values were improved by around 85% compared to the standard monomial basis when using Lagrange polynomial basis.CONCLUSIONThis study indicates that the procedure using Lagrange polynomials with method-of-moments is a more reliable reconstruction procedure that calculates the approximate distribution using lesser number of moments, which is desirable. (c) 2024 The Authors. Journal of Chemical Technology and Biotechnology published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry (SCI).Article Citation - WoS: 2Citation - Scopus: 2Further Developments of the Extended Quadrature Method of Moments To Solve Population Balance Equations(Cell Press, 2023) Turan, Meltem; Dutta, AbhishekDeveloping numerical methods to solve polydispersed flows using a Population Balance Equation (PBE) is an active research topic with wide engineering applications. The Extended Quadrature Method of Moments (EQMOM) approximates the number density as a positive mixture of Kernel Density Functions (KDFs) that allows physical source terms in the PBEs to compute continuous or point-wise form according to the moments. The moment-inversion procedure used in EQMOM has limitations such as the inability to calculate certain roots even if it is defined, absence of consistent result when multiple roots exist or when the roots are nearly equal. To address these limitations, the study proposes a modification of the moment-inversion procedure to solve the PBE based on the proposed Halley-Ridder (H-R) method. Although there is no significant improvement in the extent of variability relative to the mean of the tested shape parameter cr values, an increase in the number of floating point operations (FLOPS) is observed which the proposed algorithm responds in limitations mentioned above. The total number of FLOPS for all the kernels used for the approximation increased by around 30%. This is an improvement towards the development of a more reliable and robust moment-inversion procedure.Conference Object Numerical Study on the Mixing Characteristics in the Argon Oxygen Decarburization Process(Association for Iron and Steel Technology, AISTECH, 2022) Cheng, Zhongfu; Wang, Yannan; Dutta, Abhishek; Blanpain, Bart; Guo, Muxing; Malfliet, AnneliesThe argon-oxygen decarburization (AOD) process is a crucial refining method in modern stainless steel production. It has been widely used to remove C in the past few decades [1, 2]. The AOD converter can provide excellent mixing conditions through turbulent stirring using submerged tuyeres. In the AOD process, the flow characteristics in the bath have a significant influence on the mass transport, momentum exchange and heat transfer, which are closely linked with the gas-metal reaction kinetics and the refining efficiency. A deep understanding of jet behavior, bubble flow characteristics and mixing efficiency facilitates further optimization of the decarburization and desulfurization operations. This will increase the AOD productivity and lower its energy and material consumption as well as the manufacturing cost.Article Citation - WoS: 4Citation - Scopus: 5Numerical Study of Fluid Flow and Mixing in the Argon Oxygen Decarburization (aod) Process(Iron and Steel Institute of Japan, 2023) Cheng, Zhongfu; Wang, Yannan; Dutta, Abhishek; Blanpain, Bart; Guo, Muxing; Malfliet, AnneliesA three-dimensional (3D) model has been developed based on the Eulerian multiphase flow approach to investigate the fluid flow behavior and mixing efficiency in the multi-tuyere AOD process. The interphase forces, including drag force, lift force, virtual force, turbulent dispersion force, and wall lubrication force, were incorporated into this model. The model was used to simulate six-tuyere and seven-tuyere AOD processes. The phenomena of multi-jet penetration, bubble plume merging, 3D turbulent flow and mixing characteristics were considered. The results indicate that the bubble plume merging occurs in the upper part of the liquid bath, forming a typical plume cluster. The predicted penetration length for a single tuyere jet agrees well with the previous work. For the multi-jet system, the side jets penetrate deeper than the inside ones. The six-tuyere AOD has a good flow condition in the center of the liquid bath, while the seven-tuyere AOD has a better flow pattern in the sidewall region and the lower bath. Overall, the seven-tuyere AOD performs better in mixing efficiency than the six-tuyere AOD under the same gas flow rate. These findings increase the understanding of the AOD process, allowing further optimization of process parameters. This model can be further extended to incorporate the thermochemical reactions into the modeling of the AOD reactor.Article Citation - WoS: 3Citation - Scopus: 3Numerical Study of Electrostatic Desalting: a Detailed Parametric Study(MDPI, 2022) Ramirez-Argaez, Marco A.; Abreú-López, Diego; Gracia-Fadrique, Jesús; Dutta, AbhishekA systematic process analysis was conducted to study the effect of the main variables in an industrial electrostatic desalter, such as electric field intensity, wash water content, droplet size, and oil viscosity, on the efficiency of the separation of water from oil. The analysis was assessed through an already published and validated CFD multiphase numerical model that considers the expression of the frequency of collisions as a function of the mentioned process variables. Additionally, the study allowed the formal optimization exercise of the operation to maximize the separation efficiency. The most significant variables were the initial water content and the electric field intensity, while the temperature (oil viscosity) had an effect to a lower extent. An increase in the electric field and temperature and a decrease in the water content improved the water separation from oil. Optimum values suggested from the factorial experimental design and the optimization implemented in this work indicated the use of an electric field of 3 kV/cm, water content of 3%, and an oil viscosity of 0.017 kg/ms. At the same time, the droplet size showed no significant effect under the conditions explored in this work.Article Citation - WoS: 12Citation - Scopus: 14Extraction of Monophenols and Fractionation of Depolymerized Lignin Oil With Nanofiltration Membranes(Elsevier, 2023) Croes, Tim; Dutta, Abhishek; De Bie, Robin; Van Aelst, Korneel; Sels, Bert; Van der Bruggen, BartOrganic solvent nanofiltration membranes were employed to fractionate birch derived reductive catalytic fractionated (RCF) lignin oil. This lignin oil is highly depolymerized, with most, if not all chemical compounds lighter than 3 kDa. Sixteen commercially available membranes were investigated for the fractionation, in combination with methanol and ethyl acetate as solvents. Membrane performances were quantified using Gaussian fits of gel permeation chromatograms and separation factor calculations. The separation factor was found to be primarily based on affinities instead of size-exclusion. The silicon-based membranes from Borsig (Germany) and PuraMem S600 from Evonik (UK) proved best at separating lignin into different functional fractions, showing monomer separation factors up to 7.4 and providing a permeate fraction with 88 % phenolic monomer purity. These membranes were further examined in batch diafiltration and two-stage filtration. This increased the separation factor from 7.4 to 25.4, and the monomer purity of the permeate to 95 %, proving that membrane purification of the lignin-derived monophenols is technically feasible.Article Citation - WoS: 13Citation - Scopus: 17Characterization and Beneficiation of Ethiopian Kaolin for Use in Fabrication of Ceramic Membrane(IOP Publishing, 2021) Zewdie, Tsegahun Mekonnen; Prihatiningtyas, Indah; Dutta, Abhishek; Habtu, Nigus Gabbiye; Van der Bruggen, BartKaolin (china clay) is a rock material that is very rich in kaolinite. A kaolin ore from Debre Tabor, Ethiopia containing 59.2 wt% SiO2, 24.9 wt% Al2O3, 2.4 wt% Fe2O3, and 8.22 wt% loss on ignition (LOI) was physically beneficiated, chemically leached, and thermally treated for possible industrial use, especially for ceramic membrane fabrication. The leaching experiments were carried out using oxalic acid solutions as leaching reagents for the iron extraction process. The effect of acid concentration, reaction temperature, and contact time on iron leaching was investigated. It was determined that the rate of iron extraction increased with the oxalic acid concentration, leaching temperature, and contact time. A substantial reduction of iron oxide (2.4 to 0.36 wt%) from the raw kaolin was observed at operating conditions of 2.0 M oxalic acid, the temperature of 120 degrees C, and contact time of 120 min. A maximum kaolin whiteness index of 81.4% was achieved through this leaching process. Finally, the physically beneficiated, chemically leached, and thermally treated kaolin raw material was used to fabricate a low-cost kaolin-based ceramic membrane. After firing at 1100 degrees C the ceramic membrane was found to have a mass loss of 11.04 +/- 0.05%, water absorption of 8.9 +/- 0.4%, linear shrinkage of 14.5 +/- 0.05%. It was demonstrated to be chemically stable, having less than 3% mass loss in acid solution, and less than 1% mass loss in alkali solution. The newly developed membranes have thus properties comparable to commercial ceramic membranes.