Article
Mathematics, Applied
Benjamin Anwasia, Srboljub Simic
Summary: In this study, the maximum entropy principle is applied to derive the properly scaled velocity distribution function of Boltzmann equations for mixtures, leading to a non-isothermal Maxwell-Stefan diffusion model. The entropy balance law is also analyzed, and the kinetic entropy production is derived from the scaled distribution function.
APPLIED MATHEMATICS LETTERS
(2022)
Article
Mathematics, Applied
Clement Cances, Virginie Ehrlacher, Laurent Monasse
Summary: The aim of this work is to propose a provably convergent finite volume scheme for the Stefan-Maxwell model, which describes the composition evolution of a multi-component mixture as a cross-diffusion system. The scheme relies on a two-point flux approximation and preserves key theoretical properties of the continuous model, including non-negativity, mass conservation, and volume-filling constraints. Additionally, it satisfies a discrete entropy-entropy dissipation relation similar to the continuous level. This article presents the scheme, its numerical analysis, and provides numerical results to demonstrate its behavior.
IMA JOURNAL OF NUMERICAL ANALYSIS
(2023)
Article
Engineering, Chemical
Artur A. Salamatin, Alyona S. Khaliullina
Summary: The extract obtained from supercritical fluid extraction of plant raw materials is multi-component, and a particle-scale multi-component mass transfer model is developed to consider the non-ideal chemical interactions between solute components. The model utilizes two pseudo-components to represent the oil and considers the chemical potential gradient as the driving force for mass transfer. The model is based on the regular solution and Gibbs energy approaches for thermodynamic modeling and shows a significant improvement compared to the simplified ideal system approach.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2023)
Article
Mathematics, Applied
Alexander Van-Brunt, Patrick E. Farrell, Charles W. Monroe
Summary: This study investigates structure-preserving finite element discretizations for the steady-state Stefan-Maxwell diffusion problem, which governs mass transport within a phase consisting of multiple species. Inspired by augmented Lagrangian methods, an approach is developed to construct a symmetric positive definite augmented Onsager transport matrix, leading to an effective numerical algorithm. Inf-sup conditions for the continuous and discrete linearized systems are proven, and error estimates are obtained for a phase consisting of an arbitrary number of species. The discretization preserves the thermodynamically fundamental Gibbs-Duhem equation to machine precision independent of mesh size. Numerical examples, including the diffusion of oxygen, carbon dioxide, water vapor, and nitrogen in the lungs, are provided to illustrate the results.
IMA JOURNAL OF NUMERICAL ANALYSIS
(2022)
Article
Thermodynamics
Patrick Krenn, Patrick Zimmermann, Michael Fischlschweiger, Tim Zeiner
Summary: The solvent absorption of an epoxy o-cresol novolac resin composite in different aqueous electrolyte solutions has been accurately predicted through a complex model, showing qualitative agreement with measured data.
FLUID PHASE EQUILIBRIA
(2021)
Article
Geochemistry & Geophysics
A. Pavlov
Summary: The Maxwell-Stefan diffusion equations for multicomponent neutral gas mixtures with thermodiffusion ratios and diffusion correction factors in the Chapman-Cowling third-order approximation are derived, with explicit functions of masses, number densities, thermal conductivities, and collision integrals. Applications to atmospheric gases and recommendations for studying Earth's atmosphere are provided.
SURVEYS IN GEOPHYSICS
(2021)
Article
Mathematics, Applied
Xiaokai Huo, Hailiang Liu, Athanasios E. Tzavaras, Shuaikun Wang
Summary: The new finite difference scheme for the Maxwell-Stefan diffusion system is conservative, energy-stable, and positivity-preserving, which are proved by reformulating the scheme into an equivalent optimization problem. The solution to the scheme is obtained as the minimizer of the optimization problem, leading to energy stability and positivity-preserving properties.
SIAM JOURNAL ON NUMERICAL ANALYSIS
(2021)
Article
Electrochemistry
Chathura J. Kankanamge, Taotao Zhan, Maximilian Piszko, Tobias Klein, Andreas P. Froeba
Summary: In this study, three binary electrolyte mixtures consisting of different molecular solvents and dissolved lithium bis(trifluoromethylsulfonyl)imide ([Li][NTf2]) were characterized by determining their Fick diffusion coefficient D11. Dynamic light scattering and molecular dynamics simulations were used to obtain reliable thermophysical properties for the mixtures. The results showed good agreement between the predictions from molecular dynamics simulations and the measurements from dynamic light scattering.
ELECTROCHIMICA ACTA
(2023)
Article
Electrochemistry
Maximilian Roehe, David Franzen, Fabian Kubannek, Barbara Ellendorff, Thomas Turek, Ulrike Krewer
Summary: In this study, a modeling approach was developed to evaluate the influence of inhomogeneities on the electrochemical performance of silver based oxygen depolarized cathodes (ODC). The results indicate that the distribution of the electrolyte is crucial for the gas-electrolyte interface and electrode performance. Electrochemical impedance spectroscopy is sensitive to electrolyte distribution, while polarization curves do not provide sufficient information about the location and distribution of the electrolyte.
ELECTROCHIMICA ACTA
(2021)
Article
Engineering, Chemical
Benjamin Claessens, Ivaylo Hitsov, Arne Verliefde, Ingmar Nopens
Summary: In this study, the molecular transport mechanisms in ceramic membranes were analyzed using Maxwell-Stefan theory. The results showed that the total flux was dominated by the viscous contribution, and cross-coupling had a significant impact on retention, with changes up to 20%. Furthermore, it was demonstrated that non-ideal thermodynamics in the external liquid phase could explain the transition from positive to negative retention when using the same solute in different solvents.
CHEMICAL ENGINEERING SCIENCE
(2022)
Article
Engineering, Chemical
William Q. Rios, Bruno Antunes, Alirio E. Rodrigues, Ines Portugal, Carlos M. Silva
Summary: The study presents accurate analytical equations for effective diffusivities (Di,eff) that consider the nonideal behavior of multicomponent mixtures. A new rigorous approach is proposed and demonstrated to provide accurate calculations for Di,eff, and it is shown that deviations from ideal behavior can lead to substantial errors in these calculations.
Article
Engineering, Multidisciplinary
Dieter Bothe, Pierre-Etienne Druet
Summary: This paper reevaluates the modeling of multicomponent diffusion in relation to the irreversible thermodynamics. The generalized Fick-Onsager multicomponent diffusion fluxes and the generalized Maxwell-Stefan equations, two well-known approaches, are briefly reviewed. A novel and more direct closure that avoids the inversion of the Maxwell-Stefan equations is proposed and discussed. It is shown that all three closures are equivalent when concentrations are required to be positive, revealing the general structure of continuum thermodynamical diffusion fluxes. The paper also addresses the sign of multicomponent thermodynamic or Fickian diffusion coefficients based on the second law.
INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE
(2023)
Article
Engineering, Chemical
Tim Van Gestel, Frans Velterop, Wilhelm A. Meulenberg
Summary: The article introduces a hybrid organosilica membrane setup based on mesoporous stabilized zirconia intermediate layers, showing excellent selectivity and flux in gas separation and pervaporation. The results represent an important advancement towards industrial application of hybrid silica membranes.
SEPARATION AND PURIFICATION TECHNOLOGY
(2021)
Article
Engineering, Chemical
Pawel Grzybek, Lukasz Jakubski, Przemyslaw Borys, Slawomir Kolodziej, Czeslaw Slusarczyk, Roman Turczyn, Gabriela Dudek
Summary: Asymmetric chitosan membranes were used to improve the process of ethanol dehydration, and a strong correlation was found between membrane structure, pore size and separation effectiveness. An interesting phenomenon of membrane structure changing during the pervaporation process was observed, leading to a nonlinear time dependence of transport and separation parameters. The best performance for PV separation was achieved by a membrane prepared from a casting solution containing 0.1 ml of absolute ethanol.
SEPARATION AND PURIFICATION TECHNOLOGY
(2022)
Article
Nanoscience & Nanotechnology
Ufafa Anggarini, Liang Yu, Hiroki Nagasawa, Masakoto Kanezashi, Toshinori Tsuru
Summary: The nickel-doped bis [3-(trimethoxysilyl) propyl] amine (BTPA) derived membrane shows high potential for separating methanol-toluene azeotropic mixtures via pervaporation process, with improved separation performance as nickel concentration increases.
ACS APPLIED MATERIALS & INTERFACES
(2021)
Article
Computer Science, Interdisciplinary Applications
Nohan Joemon, Melpakkam Pradeep, Lokesh K. Rajulapati, Raghunathan Rengaswamy
Summary: This paper introduces a smoothing-based approach for discovering partial differential equations from noisy measurements. The method is data-driven and improves performance by incorporating first principles knowledge. The effectiveness of the algorithm is demonstrated in a real system using a new benchmark metric.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Zhibin Lu, Yimeng Li, Chang He, Jingzheng Ren, Haoshui Yu, Bingjian Zhang, Qinglin Chen
Summary: This study proposes a new inverse design method using a physics-informed neural network to identify optimal heat sink designs. A hybrid PINN accurately approximates the governing equations of heat transfer processes, and a surrogate model is constructed for integration with optimization algorithms. The proposed method accelerates the search for Pareto-optimal designs and reduces search time. Comparing different scenarios facilitates real-time observation of multiphysics field changes, improving understanding of optimal designs.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Luca Gasparini, Antonio Benedetti, Giulia Marchese, Connor Gallagher, Pierantonio Facco, Massimiliano Barolo
Summary: In this paper, a method for batch process monitoring with limited historical data is investigated. The methodology utilizes machine learning algorithms to generate virtual data and combines it with real data to build a process monitoring model. Automatic procedures are developed to optimize parameters, and indicators and metrics are proposed to assist virtual data generation activities.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Julia Jimenez-Romero, Adisa Azapagic, Robin Smith
Summary: Energy transition is a significant and complex challenge for the industry, and developing cost-effective solutions for synthesizing utility systems is crucial. The research combines mathematical formulation with realistic configurations and conditions to represent utility systems and provides a basis for synthesizing energy-efficient utility systems for the future.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Samuel Adeyemo, Debangsu Bhattacharyya
Summary: This work develops algorithms for estimating sparse interpretable data-driven models. The algorithms select the optimal basis functions and estimate the model parameters using Bayesian inferencing. The algorithms estimate the noise characteristics and model parameters simultaneously. The algorithms also exploit prior analysis and special properties for efficient pruning, and use a modified Akaike information criterion for model selection.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Abbasali Jafari-Nodoushan, Mohammad Hossein Dehghani Sadrabadi, Maryam Nili, Ahmad Makui, Rouzbeh Ghousi
Summary: This study presents a three-objective model to design a forward supply chain network considering interrelated operational and disruptive risks. Several strategies are implemented to cope with these risks, and a joint pricing strategy is used to enhance the profitability of the supply chain. The results show that managing risks and uncertainties simultaneously can improve sustainability goals and reduce associated costs.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
T. A. Espaas, V. S. Vassiliadis
Summary: This paper extends the concept of higher-order search directions in interior point methods to convex nonlinear programming. It provides the mathematical framework for computing higher-order derivatives and highlights simplified computation for special cases. The paper also introduces a dimensional lifting procedure for transforming general nonlinear problems into more efficient forms and describes the algorithmic development required to employ these higher-order search directions.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
David A. Linan, Gabriel Contreras-Zarazua, Eduardo Sanhez-Ramirez, Juan Gabriel Segovia-Hernandez, Luis A. Ricardez-Sandoval
Summary: This study proposes a parallel hybrid algorithm for optimal design of process flowsheets, which combines stochastic method with deterministic algorithm to achieve faster and improved convergence.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Xiaoyong Lin, Zihui Li, Yongming Han, Zhiwei Chen, Zhiqiang Geng
Summary: A novel GAT-LSTM model is proposed for the production prediction and energy structure optimization of propylene production processes. It outperforms other models and can provide the optimal raw material scheme for actual production processes.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Prodromos Daoutidis, Jay H. Lee, Srinivas Rangarajan, Leo Chiang, Bhushan Gopaluni, Artur M. Schweidtmann, Iiro Harjunkoski, Mehmet Mercangoz, Ali Mesbah, Fani Boukouvala, Fernando Lima, Antonio del Rio Chanona, Christos Georgakis
Summary: This paper provides a concise perspective on the potential of machine learning in the PSE domain, based on discussions and talks during the FIPSE 5 conference. It highlights the need for domain-specific techniques in molecular/material design, data analytics, optimization, and control.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hesam Hassanpour, Prashant Mhaskar, Brandon Corbett
Summary: This work addresses the problem of designing an offset-free implementable reinforcement learning (RL) controller for nonlinear processes. A pre-training strategy is proposed to provide a secure platform for online implementations of the RL controller. The efficacy of the proposed approach is demonstrated through simulations on a chemical reactor example.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Hunggi Lee, Donghyeon Lee, Jaewook Lee, Dongil Shin
Summary: This study introduces an innovative framework that utilizes a limited number of sensors to detect chemical leaks early, mitigating the risk of major industrial disasters, and providing faster and higher-resolution results.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Sibel Uygun Batgi, Ibrahim Dincer
Summary: This study examines the environmental impacts of three alternative hydrogen-generating processes and determines the best environmentally friendly option for hydrogen production by comparing different impact categories. The results show that the solar-based HyS cycle options perform the best in terms of global warming potential, abiotic depletion, acidification potential, ozone layer depletion, and human toxicity potential.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
LaGrande Gunnell, Bethany Nicholson, John D. Hedengren
Summary: A review of current trends in scientific computing shows a shift towards open-source and higher-level programming languages like Python, with increasing career opportunities in the next decade. Open-source modeling tools contribute to innovation in equation-based and data-driven applications, and the integration of data-driven and principles-based tools is emerging. New compute hardware, productivity software, and training resources have the potential to significantly accelerate progress, but long-term support mechanisms are still necessary.
COMPUTERS & CHEMICAL ENGINEERING
(2024)
Article
Computer Science, Interdisciplinary Applications
Daniel Cristiu, Federico d'Amore, Fabrizio Bezzo
Summary: This study presents a multi-objective mixed integer linear programming framework to optimize the supply chain for mixed plastic waste in Northern Italy. Results offer quantitative insights into economic and environmental performance, balancing trade-offs between maximizing gross profit and minimizing greenhouse gas emissions.
COMPUTERS & CHEMICAL ENGINEERING
(2024)