Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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  • Article
    Synthesis of Nannochloropsis Oculata Cultivation Process Based on Mixed-Integer Formulations
    (Elsevier, 2025) Kivanc, Sercan; Tuncer, Basak; Deliismail, Ozgun; Sildir, Hasan
    Sophisticated mathematical formulations and related optimization tasks are important to favor microalgae processing. This study focuses on the development of a mixed integer nonlinear programming approach to calculate design and operational decisions through simultaneous and rigorous approach under set of complex constraints and objective functions. Through a set of differential algebraic equations, whose model parameters are obtained through fitting a dataset available in the literature, three case studies are demonstrated for the calculation of optimum cultivation conditions based on economic considerations and biomass production. The case studies show the impact of the approach for the sustainability of the process as different conditions are primary defined by light color, reactor size, dilution rate, feed stream composition, and growing medium are required for desired tasks. The approach is flexible and further modifiable to various considerations for more complex decision-making problems.
  • Article
    Citation - WoS: 1
    Citation - Scopus: 1
    Dynamic and Stochastic Optimization of Algae Cultivation Process
    (Pergamon-elsevier Science Ltd, 2025) Kivanc, Sercan; Beykal, Burcu; Deliismail, Ozgun; Sildir, Hasan
    This study offers a realistic representation of system dynamics which accounts for light intensity, biomass, substrate, and nitrogen concentration, by employing stochastic programming techniques to account for spatial and temporal variations for algae growth. The optimization task focuses on lipid productivity and selectivity, which are crucial factors in the context of algal biofuel production. Different scenarios from likely and unlikely cases of model parameters were evaluated. Optimal initial conditions for key variables such as nitrogen, substrate, light, biomass, lipid, and surface light intensity are calculated, considering the uncertainty of the parameters as well as other governing equations. The results show that a remarkable 11.18% increase in lipid productivity compared to a reference scenario. Furthermore, in the stochastic case, our results highlight that uncertainty has a disproportionately large effect on biomass in comparison to lipid concentration, providing valuable insights into the behavior of the system under varying conditions. This provides a comprehensive exploration of the parameter uncertainty on lipid productivity and algal growth.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 1
    A Mixed-Integer Dynamic and Stochastic Algae Process Optimization
    (Elsevier, 2024) Kivanc, Sercan; Deliismail, Özgün; Şıldır, Hasan
    With increased energy demand as it gets scarcer, a great deal of research is being carried out into alternatives to non - renewable energy resources. One of the promising studies is the biofuel production from micro algae. Microalgae are photosynthetic organisms and capture carbon dioxide, reducing emissions and providing valuable products (fuel, fertilizer, etc.). Thus, efficiency in the design and optimization of process related units are important. In this study, the optimal experimental conditions for Nannochloropsis Oculata were calculated under the constraints of the model equations and other process related constraints through simultaneous optimization approach. The economic evaluation of the process is also handled by introducing the uncertainty in the economic measures sampled from normal distribution to maximize the average profit. Unlike traditional approaches, the MINLP formulation, which is solved stochastically, dynamically, and simultaneously, provides more robust and reliable results, flexibility, improved decision making, reduced risks to be taken and a better understanding of risk factors. Copyright (C) 2024 The Authors. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/)