Article
Chemistry, Multidisciplinary
Tanu Mehta, Raj Mukherjee, Ami Shah, Trey Mastriani, Tibo Duran, Bodhisattwa Chaudhuri
Summary: The study demonstrates that careful selection of equipment materials can significantly reduce the electrostatic charging of pharmaceutical powders, and surface modified blenders play an important role. The Discrete Element Method (DEM) model can also be used to assess the applicability of modified V blenders.
PHARMACEUTICAL RESEARCH
(2023)
Article
Engineering, Chemical
Yuki Tsunazawa, Nobukazu Soma, Mikio Sakai
Summary: This study clarifies the mixing mechanism of a pot blender using the discrete element method. The results show that the main mixing mechanism is convective mixing in the rotational direction and shear mixing in the axial direction. The particle filling ratio significantly influences the mixing efficiency, and the dependency of shear and diffusive mixing on Lacey's mixing index is also clarified.
ADVANCED POWDER TECHNOLOGY
(2022)
Article
Engineering, Chemical
Behrooz Jadidi, Mohammadreza Ebrahimi, Farhad Ein-Mozaffari, Ali Lohi
Summary: The study investigated the mixing mechanisms and flow patterns in a twin-paddle blender containing non-spherical particles using the discrete element method (DEM) and experiments. Calibration tests were conducted to validate the GPU-based DEM model using a rotary drum. The calibrated model was then utilized to explore the impact of factors such as vessel fill level, paddle rotational speed, and particle number ratio on mixing performance. The results indicated that an increase in fill level and a decrease in impeller speed resulted in a higher number of particle contacts and an increase in mixture compactness, driven by diffusion as the dominant mixing mechanism.
Article
Engineering, Chemical
Katherine Wilson, Lauren Briens
Summary: Powder mixing is a crucial and complex process in various industries. This study explores the potential of using passive acoustic emissions to monitor the mixing process. Vibration profiles correlated with specific phases of particle motion provide reliable information on particle movement.
Article
Engineering, Chemical
Fuhai Yu, Zhihao Yao, Guojie Chen, Yun Zhang, Yang Zheng
Summary: The study investigates how changing baffle design can improve the mixing efficiency of a multi-bladed tote blender. The novel inclined multi-bladed baffles break the symmetrical axial granular flow and introduce more efficient convective mixing, showing excellent applicability under different conditions and effectively preventing segregation of particles.
Article
Engineering, Chemical
Bowen Liu, Qing Wang, Zongyan Zhou, Ruiping Zou
Summary: This study investigates the performance of baffles in internally heated rotating drums using the discrete element method (DEM). The results show that a central cross baffle improves mixing and heat transfer significantly, while a peripheral baffle generally weakens the performance.
Article
Engineering, Chemical
Peng Huang, Qiuhua Miao, Gao Sang, Yuhang Zhou, Minping Jia
Summary: The ACNN method accurately quantifies the overall segregation degree of particles and effectively reflects the mixing and segregation within the particle system, facilitating the study of particle mixing and segregation processes in different shaft segments of a rotating drum.
MINERALS ENGINEERING
(2021)
Article
Engineering, Chemical
Behrooz Jadidi, Mohammadreza Ebrahimi, Farhad Ein-Mozaffari, Ali Lohi
Summary: Non-spherical particles have a lower mixing quality compared to spherical particles in a twin paddle blender. Cubical particles show the highest compactness in the solid mixture. Non-spherical particles exhibit a higher resistance to movement. The diffusion mechanism is superior in mixing, with shear and normal stresses peaking near the blade tips.
Article
Engineering, Chemical
Zhen Wan, Youjun Lu
Summary: This paper investigates the local and global mixing and segregation characteristics of binary mixtures in a gas-solid fluidized bed using a computational fluid dynamics-discrete element method (CFD-DEM) coupled approach. A methodology based on solids mixing entropy is developed to quantify the mixing degree and time of the bed. The effects of gas velocity, particle density ratio, and size ratio on mixing/segregation behavior are discussed. The results show that increasing gas velocity promotes the mixing of binary mixtures, while increasing particle density ratio and size ratio lead to greater segregation and reduced mixing degree.
CHINESE JOURNAL OF CHEMICAL ENGINEERING
(2022)
Article
Chemistry, Multidisciplinary
Francisco J. Canamero, Anand R. Doraisingam, Marta Alvarez-Leal
Summary: This article introduces a DIY approach for the production of customized fast moving consumer goods, including powder detergent. A machine connected to a digital platform is used to manufacture a customized detergent according to the clients' needs. The mixing process of the powder detergent is modeled using the discrete element method, and the performance is studied considering the allowable mass fraction range of each component and a mixer speed of 45 rpm. A machine learning algorithm is then employed to predict the mixing index using the dataset generated from this study. The developed model accurately predicts the mixing index in advance.
APPLIED SCIENCES-BASEL
(2023)
Article
Engineering, Chemical
Behrooz Jadidi, Mohammadreza Ebrahimi, Farhad Ein-Mozaffari, Ali Lohi
Summary: Discrete element method (DEM) and statistical analysis were used to analyze the flow patterns and mixing mechanisms of a double paddle blender. The study found that impeller speed and initial loading pattern had significant effects on the mixing performance, and diffusion was identified as the dominant mixing mechanism in the blender.
Article
Engineering, Chemical
Katherine Wilson, Lauren Tribe
Summary: Powder mixing is crucial in various industries to ensure the quality of the final product. Segregation due to particle size has been observed in V-blenders, and passive acoustic emissions can be used to measure the vibrations caused by particle collisions within the blender. These vibrations can identify both left-right segregation of particles and the point of mixture stability, providing valuable information for optimizing mixing processes.
Article
Engineering, Chemical
Shahab Golshan, Bruno Blais
Summary: This research investigates the influence of load-balancing strategy and parametrization on the speed-up of discrete element method simulations. The study compares different cell-weighing strategies and load-balancing schemes, and proposes a dynamic load-balancing scheme for optimizing computation speed.
Article
Engineering, Chemical
Edouard Izard, Maxime Moreau, Pascal Ravier
Summary: This study utilizes three-dimensional Discrete Element Method (DEM) to simulate material flows in the large-scale charging chute of Fos-Sur-Mer sinter cooler plant, resulting in segregation patterns at the charging exit. After suitable calibration tests, the simulation is in good agreement with experimental observations. It is found that a high filling ratio leads to less segregation at the charging chute exit.
Article
Engineering, Environmental
Naoki Kishida, Hideya Nakamura, Shuji Ohsaki, Satoru Watano
Summary: This article proposes a new machine learning model, RNNSR, which learns particle dynamics from DEM simulation results and predicts powder mixing for a longer period. The RNNSR combines recurrent neural networks and a stochastic model to predict both convective and diffusive mixing. The simulation results obtained using the RNNSR are similar to those obtained using the DEM and demonstrate the capability of ultrafast computation in powder-mixing simulations.
CHEMICAL ENGINEERING JOURNAL
(2023)
Article
Engineering, Chemical
Shahab Golshan, Alireza Shams, Roshanak Rabiee, Rouzbeh Jafari, Jamal Chaouki, Bruno Blais
Summary: This study investigates the effect of bed size on the average droplet diameter in a rotating packed bed (RPB) and develops scale-up criteria to maintain the average droplet diameter at a large scale. Experimental data and simulation results are used to determine the correlation between rotating speed, centrifugal force, and surface tension with the average droplet diameter. This research contributes to the wider adoption of RPB technology.
CANADIAN JOURNAL OF CHEMICAL ENGINEERING
(2023)
Article
Energy & Fuels
Amin Solouki, Shaffiq A. Jaffer, Jamal Chaouki
Summary: This paper presents an industrial process scheme for microwave-assisted demetallization and desulfurization of crude oil, showing advantages in efficiency, environmental friendliness, and low energy consumption. Economic investigation indicates the superiority of this process compared to existing technologies, with success depending on microwave power and regeneration process efficiency.
Article
Engineering, Chemical
Mojtaba Mokhtari, Jaber Shabanian, Jamal Chaouki
Summary: Bubble size distribution (BSD) is a crucial parameter in the design and scale-up of slurry bubble columns (SBCs). In this study, novel bubble breakup and coalescence models were developed to predict the effects of solids concentration and particle size on the bubble breakup and coalescence rates. An integrated population balance and hydrodynamic model was also developed to estimate the BSD and gas holdup in a slurry bubble column. The developed models were successfully validated and parametric studies were conducted to investigate the effects of solid particles on the bubble breakup, bubble coalescence, and BSD.
CHEMICAL ENGINEERING SCIENCE
(2022)
Article
Environmental Sciences
Joseph Santhi Pechsiri, Jean-Baptiste E. Thomas, Naoufel El Bahraoui, Francisco Gabriel Acien Fernandez, Jamal Chaouki, Saad Chidami, Rodrigo Rivera Tinoco, Jose Pena Martin, Cintia Gomez, Michel Combe, Fredrik Grondahl
Summary: This study compares the environmental performance of conventional reactors and a proposed internally illuminated novel closed reactor design. The results show that the novel photobioreactor can significantly reduce impacts such as eutrophication and climate change when leveraging renewable energy sources and the photosynthesis process in urban-industrial symbiosis scenarios.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Engineering, Chemical
Amin Solouki, Mohammad Monzavi, Jamal Chaouki
Summary: This study investigated the removal of nickel (Ni) and vanadium (V) from Iranian crude oil using bis-(2-ethylhexyl)-phosphoric acid (D2EHPA) under microwave heating. The results showed that with low microwave powers and a reaction temperature of 250℃, the removal efficiencies of Ni and V could reach up to 63% and 72% respectively after 1 hour of reaction. The demetallization reactions followed a first-order model, with activation energies of 29.8 and 34.7 kJ/mol for Ni and V.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2023)
Article
Engineering, Chemical
Kazem Adavi, Jaber Shabanian, Jamal Chaouki
Summary: Research studies have found that selective heating in gas-solid systems exposed to microwave irradiation can suppress undesired reactions and save energy. However, the effects of various factors on temperature difference and distribution in fixed beds under microwave heating are not well understood. This study used multiphysics simulations to investigate these effects and found that temperature gradient increases with gas velocity and exothermic reactions. Additionally, nonuniform temperature distribution was observed due to limited microwave penetration depth and hotspot formation.
INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH
(2023)
Article
Mathematics, Applied
Abdellah Ajji, Jamal Chaouki, Ogul Esen, Miroslav Grmela, Vaclav Klika, Michal Pavelka
Summary: The classical mass action law in chemical kinetics is integrated into the framework of geometric multiscale thermodynamics, enabling the description of chemical reactions with inertial effects. The kinetics is expanded to a larger state space with reaction rates as new state variables, exhibiting a Lie-algebroid dual structure. The dynamics is then enhanced to the Liouville description within the kinetic theory of the enlarged state space, allowing for the inclusion of fluctuations. The lifted kinematics possesses a geometric structure of a matched pair, enabling reduction to moments by a Lie-algebra homomorphism, akin to the Grad hierarchy.
PHYSICA D-NONLINEAR PHENOMENA
(2023)
Review
Engineering, Chemical
Pierre Sauriol, Javad Vahabzadeh Pasikhani, Jaber Shabanian, Jamal Chaouki
Summary: The high velocity injection of gas in a particulate system leads to the formation of a gas-solid structure characterized by enhanced momentum, mass, and heat transfers. This review focuses on the empirical correlations developed to predict the jet penetration length and half-angle at various operating conditions in different bed configurations in gas-solid fluidized beds. It also discusses the advances in modeling efforts, scale-up issues, and proposes an iterative approach for designing and scaling up injection systems in a gas-solid fluidized bed.
Article
Chemistry, Multidisciplinary
Ramy Sadek, Mohammad S. Sharawi, Charles Dubois, Hesham Tantawy, Jamal Chaouki
Summary: The developed nanocomposite shows significantly enhanced shielding performance due to the synergistic effect of high dielectric and magnetic loss materials, which modifies the material's impedance and improves its absorption ability.
Article
Thermodynamics
Mohammad Monzavi, Zhaohui Chen, Abdelrahman Hussain, Jamal Chaouki
Summary: This study proposed a method of upgrading heavy oils and plastic waste to high quality products using microwave catalytic pyrolysis. By employing a unique design of the catalyst, sufficient mass and heat transfer and enhanced catalyst surface area were achieved. The addition of LDPE eliminated hazardous elements of heavy oil and promoted secondary and side reactions, resulting in optimized product yield and quality.
APPLIED THERMAL ENGINEERING
(2023)
Article
Engineering, Chemical
Mojtaba Mokhtari, Jamal Chaouki
Summary: A reliable estimation of the reactor performance is achieved using a new hydrodynamic model to predict the effect of various parameters on gas holdup, bubble size distribution, and mass transfer coefficient. The study also investigates the influence of catalyst loading, gas velocity, H-2/CO ratio, L/D ratio, pressure, temperature, and catalyst attrition on conversion rate, catalyst productivity, and space-time yield. The results show that catalyst loading, L/D ratio, and temperature increase syngas conversion, while gas velocity and pressure decrease it. The H-2/CO ratio has a maximum conversion at around 2 to 2.5. Catalyst attrition decreases syngas conversion, but constant performance can be maintained with continuous addition of fresh catalyst.
CANADIAN JOURNAL OF CHEMICAL ENGINEERING
(2023)
Article
Engineering, Environmental
Iman Soleimani, Jaber Shabanian, Jamal Chaouki
Summary: This study proposes two equivalent equations for quantifying interparticle forces (IPFs) in a gas-solid fluidized bed and examines their effects on agglomeration. The first equation, the generalized Umf deviation equation, correlates the magnitude of IPFs to the ratio of experimental and theoretical minimum fluidization velocities. The second equation, the generalized Dynamic Hausner Ratio (DHR) equation, relates the magnitude of IPFs to the agglomerate size as well as the DHR. These equations can be applied in various conditions and help quantify the resultant IPFs acting on particles. The opportunities and limitations of the proposed equations are discussed.
CHEMICAL ENGINEERING JOURNAL
(2023)
Article
Engineering, Environmental
Fadoua Laasri, Adrian Carrillo Garcia, Mohammad Latifi, Jamal Chaouki
Summary: This study investigated the decomposition of phosphogypsum (PG) in the presence of carbon monoxide (CO). Experimental results showed that PG decomposes at temperatures above 600 degrees C, yielding mainly CaS at high CO partial pressures and CaO at low CO partial pressures. Thermodynamic simulations confirmed the experimental observations and indicated that a higher CO/CaSO4 molar ratio leads to a higher conversion rate.
Article
Energy & Fuels
Houssam Bouaboula, Mohammed Ouikhalfan, Ismael Saadoune, Jamal Chaouki, Abdelghafour Zaabout, Youssef Belmabkhout
Summary: This study aims to optimize the design and operation of a pilot-scale green ammonia plant powered by renewable energy sources. A novel Techno-Economic (TE) modeling approach is proposed to address the intermittency and unpredictability of renewable energy sources. By considering different site locations with consistent yearly meteorological data and using an original Energy Management Strategy (EMS), the TE model efficiently reduces fluctuation and increases energy production. The results show that the implemented EMS leads to a significant increase in the HB Load Factor (LF) and a reduction in the Levelized Cost of Ammonia (LCOA). The PV/Battery scenario is found to be the most optimal with a projected potential cost reduction in the future.
Review
Biotechnology & Applied Microbiology
Kazem Adavi, Ahmadreza Amini, Mohammad Latifi, Jaber Shabanian, Jamal Chaouki
Summary: Microwave heating is a rapid, selective, and volumetric non-conventional heating approach that has a significant impact on driving chemical reactions. The effect of microwave irradiation on thermal/catalytic reaction kinetics is still a topic of debate. While some researchers believe that microwave heating affects reaction kinetics through non-thermal effects in addition to thermal effects, others attribute the observations solely to the thermal effect. This study summarizes and critically synthesizes available information in the literature on this subject, concluding that microwave heating only has a thermal effect on gas-solid reactions but can have non-thermal effects on ionic liquid-solid reactions. Discrepancies in previous studies are primarily caused by limitations in temperature measurement, physical structure variations, and non-uniform temperature distribution.
FRONTIERS IN CHEMICAL ENGINEERING
(2022)
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)
