WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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

Browse

Filters

20252

Settings

Author: search.filters.author.Zarghami, RezaHas files: Yes

Search Results

Now showing 1 - 2 of 2
  • 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.