WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7150

Browse

Filters

2024 - 20267

Settings

Author: search.filters.author.Mostoufi, Navid

Search Results

Now showing 1 - 7 of 7
  • Article
    Citation - WoS: 3
    Citation - Scopus: 3
    CFD-DEM Modeling of Biomass Pyrolysis in a DBD Plasma Fluidized Bed
    (Pergamon-Elsevier Science Ltd, 2025) Eslami, Ali; Kazemi, Saman; Hamidani, Golnaz; Zarghami, Reza; Mostoufi, Navid
    This study developed a CFD-DEM model to simulate biomass pyrolysis within a dielectric barrier discharge (DBD) plasma fluidized bed reactor. Biomass, as a renewable energy source, offers a promising alternative for hydrogen production through pyrolysis. The integration of non-thermal plasma technology and fluidized bed reactors is expected to enhance conversion. Key operational parameters such as inlet gas velocity, particle size, and input voltage were examined to evaluate their effects on temperature distribution, particle conversion, and hydrogen production. Results indicated that higher inlet gas velocities promote better particle mixing and more uniform temperature and conversion distribution. Smaller particle sizes significantly enhance biomass conversion by increasing the available surface area between fluid and particles. Specifically, particles with diameters of 0.85, 1.2, and 1.5 mm achieved conversions of 10.4, 8.99, and 8.57 %, respectively, at 20 s from the start of the process. Additionally, increasing the input voltage increases the mean temperatures of particles and fluid, which enhances reaction rates and conversion. Optimizing these parameters can improve the efficiency of DBD plasmaassisted biomass pyrolysis, providing valuable insights for sustainable hydrogen production.
  • Article
    Citation - WoS: 3
    Citation - Scopus: 1
    Enhancing Biomass Pyrolysis via Microwave Heating: A CFD-DEM Study on Intensification in Fluidized Beds
    (Elsevier Sci Ltd, 2026) Hamidani, Golnaz; Kazemi, Saman; Eslami, Ali; Zarghami, Reza; Sotudeh-Gharebagh, Rahmat; Mostoufi, Navid
    Biomass conversion into high-value products in fluidized beds can be significantly improved by utilizing microwave irradiation as the heating source. The present work studied microwave-assisted biomass pyrolysis using a coupled CFD-DEM model in a fluidized bed. The effect of key operating parameters, including inlet gas velocity (1.5, 2, and 2.5 times the minimum fluidization velocity), mean particle diameter (1.2, 1.3, and 1.5 mm), and microwave power input (200, 400, and 600 W), was evaluated on the performance of the reactor. The results revealed that higher microwave power increased the mean particle temperature and chemical conversion rate due to greater internal energy generation within the biomass particles. Increasing the gas velocity led to lower particle temperature because of enhanced convective heat transfer to the gas phase, and improved the uniformity of temperature and conversion distributions. Furthermore, decreasing the mean particle diameter from 1.5 to 1.2 mm increased the average temperature, from 890 to 987 K, and raised biomass conversion from 14.8 to 18.1 %, mainly by reducing convective heat losses. The validated model developed in this study enables accurate predictions of process behavior and provides valuable insights for optimizing microwave-assisted biomass pyrolysis in fluidized beds. These findings highlight the potential of microwave-assisted fluidized bed pyrolysis as an efficient technique for process intensification in producing valuable bio-based products.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 2
    CFD-DEM Investigation of the Effects of Particle Size and Fluidization Regime on Heat Transfer in Fluidized Beds
    (Springer int Publ Ag, 2025) Alipoor, Mahdi; Kazemi, Saman; Zarghami, Reza; Mostoufi, Navid
    This paper presents an in-depth study of heat transfer in fluidized beds, employing the CFD-DEM technique. The primary focus is to examine the impacts of inlet gas velocity, fluidization regime, and particle size on the thermal behavior of fluidized beds. The results revealed that thermal convection predominantly governs heat transfer in fluidized beds, accounting for the largest fraction of the overall heat transfer process. Particle-fluid-particle thermal conduction was found to contribute approximately 10-20% of the heat transfer, whereas particle-particle conduction exhibits a minor role. Upon increasing the inlet gas velocity, the convection rate intensifies, whereas the particle-fluid-particle conduction rate decreases. Furthermore, the study highlights the differences in temperature distribution between turbulent and bubbling fluidized beds. Turbulent bed demonstrated a more uniform and homogenous particle temperature compared to bubbling. At similar fluidization numbers in bubbling beds, increasing particle diameter enhances thermal convection while reducing particle-fluid-particle conduction. In contrast, the turbulent regime shows minimal differences in heat transfer mechanisms when particle size varies. Additionally, smaller particles are found to significantly improve temperature uniformity in fluidized beds. A comprehensive comparison of simulation results with experimental data validates the accuracy of the employed model, reinforcing its ability to predict heat transfer in fluidized beds reliably. This research provides valuable insights into the complex interplay of various mechanisms of heat transfer within fluidized beds, enabling engineers and researchers to optimize bed performance and enhance temperature control in various industrial applications.
  • Article
    Citation - WoS: 3
    Citation - Scopus: 3
    On Digital Twins in Bioprocessing: Opportunities and Limitations
    (Elsevier Ltd, 2025) Shariatifar, Mehrdad; Rizi, Mohammadsadegh Salimian; Sotudeh-Gharebagh, Rahmat; Zarghami, Reza; Mostoufi, Navid
    Integrating Digital Twins (DTs) in bioprocessing has become a prominent focus within the industry. Despite the challenges associated with implementing this technology in the field, the bioprocessing sector is interested in utilizing it. This is due to its potential to enhance process efficiency and overall profitability. The adoption of DTs is driven by the prospect of online monitoring, control, and optimization, enabling the products with precise and desired characteristics. To realize this objective, researchers propose a novel strategy for implementing DTs in bioprocessing. This involves the development of a hybrid model that combines first principal models and Machine Learning (ML) algorithms. This approach effectively addresses the limitations of previous methods and establishes a closed control loop system, continuously monitoring the system and adjusting input variables to achieve optimal outcomes. This study comprehensively explores various aspects of DTs. Firstly, it discusses the concept and characteristics of DTs, along with an examination of the advantages and challenges associated with their implementation. Secondly, it comprehensively analyzes key factors that directly influence DT implementation, including sensors, data collection, and models. Thirdly, it reviews the implications of Digital Solutions (DS) and DT in downstream and upstream bioprocessing. By providing theories, case studies, and practical frameworks, this work seeks to motivate both researchers and industry practitioners to adopt DT methodologies, thereby facilitating the emergence of enhanced precision, operational efficiency, and economic viability within biomanufacturing.
  • Article
    Citation - WoS: 1
    Citation - Scopus: 1
    A Novel Ml-Dem Algorithm for Predicting Particle Motion in Rotary Drums
    (Elsevier Sci Ltd, 2025) Kazemi, Saman; Zarghami, Reza; Mostoufi, Navid; Sotudeh-Gharebagh, Rahmat; Al-Raoush, Riyadh I.
    The discrete element method (DEM) is a widely used approach for studying the behavior of particles in industrial equipment, including rotary drums. Although DEM is highly accurate and efficient, it suffers from the computational cost in simulations. The primary objective of this research is to reduce the computational costs of DEM by introducing a novel machine learning (ML) approach based on a deep neural network for predicting particle behavior in rotary drums. The proposed approach utilizes a continuous convolution operator in a neural network. To evaluate its effectiveness, the results of the proposed ML-DEM approach were compared quantitatively and qualitatively with the experimental data and the conventional DEM results. It was shown that in addition to its high accuracy, the proposed approach reduces the computational costs by approximately 35 % and 65 % compared to the conventional DEM simulations on GPU and CPU (with 8 processors), respectively. Furthermore, to ensure the comprehensive and independent validation of the proposed algorithm, the study investigated the effects of various parameters such as drum rotational speed and fill ratio on lateral entropy-based mixing, circulation time, and velocity profile in the active layer. The results were then compared with those obtained using the conventional DEM and found to be in good agreement. This new algorithm can serve as a starting point for reducing computational costs in simulating particle motion in granular systems.
  • Article
    Citation - WoS: 4
    Citation - Scopus: 3
    Exploration of Electrostatics Effect on Dispersion and Coating Mechanisms in Dry Powder Inhalers by Discrete Element Method
    (Elsevier, 2025) Saeid, Pooya; Kazemi, Saman; Zarghami, Reza; Sotudeh-Gharebagh, Rahmat; Mostoufi, Navid
    Improving drug delivery in the respiratory system relies on the effective coating and dispersion of active pharmaceutical ingredients (APIs) in dry powder inhalers (DPIs) and the respiratory system's airways. This study aims to explore the impact of different factors on coating APIs on carrier particles, considering electrostatic and van der Waals forces using the discrete element method (DEM). This study focuses on the critical elements of API dispersion, specifically collisions between API-coated carrier particles with each other and DPI walls. The factors influencing the dispersion ratio in these collisions, such as impact velocity, contact angle, and particle charge, are examined. Additionally, a reduced-scale shaking DPI with three frequencies is used to investigate the API coating mechanism on carriers, which was not explored in previous studies. The difference in work function between carrier particles and APIs generates charge in the shaking DPI due to collisions. This causes electrostatic force to dominate over van der Waals force, breaking agglomerates and attaching APIs to carrier particles. This study shows that the amount of generated charge increases with particle collisions and that charge distribution becomes more balanced over time through charge exchange between particles. By elucidating the relationships among impact velocity, dispersion ratio, shaking frequency, and contact angles, this study paves the way for future research on more efficient DPI designs.
  • Article
    Citation - WoS: 8
    Citation - Scopus: 6
    Effect of external electric field on fluidization of rodlike particles using CFD-DEM
    (American Chemical Society, 2024) Kazemi, Saman; Aali, Hamed; Larijani, Roxana Saghafian; Zarghami, Reza; Liu, Helei; Mostoufi, Navid
    Given the significant impact of an external electric field on fluidized bed hydrodynamics and the practical importance of rodlike particles, this study examines the behavior of a fluidized bed containing rodlike particles under various external electric fields. Simulations were performed using a coupled computational fluid dynamics-discrete element method, and rodlike particles were generated using a multisphere approach aided by quaternions. The effect of different vertical and horizontal external electric fields on the orientation of particles was investigated. Also, the effect of particle size on their orientation in the presence of constant vertical and horizontal external electric fields was explored in this work. The results showed that increasing the electric field strength and reducing the size of rodlike particles lead to an increment in the tendency of particles to become oriented along the direction of the electric field. Moreover, the effect of the external electric field at various inlet gas velocities on the probability distribution of the porosity in the bed was studied. Finally, the effect of vertical and horizontal electric fields on the bubble diameter was examined. This study offers a deeper understanding of the fluidization of rodlike particles in the presence of an electric field, and its findings can be applied to design and optimize related processes.