WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7150
Browse
20 results
Search Results
Now showing 1 - 10 of 20
Article Experimental Assessment of Alternating Magnetic Fields for Subcooled Flow Boiling Enhancement in an Annulus(Pergamon-Elsevier Science Ltd, 2026) Youzbashi-Zade, Saeed; Zonouzi, Sajjad Ahangar; Aminfar, Habib; Mohammadpourfard, MousaThe application of magnetic fields to enhance boiling heat transfer in magnetic nanofluids has emerged as a promising strategy for advanced thermal management, yet the influence of alternating magnetic fields remains largely unexplored compared to their constant counterparts. The effects of alternating and constant (steady) magnetic fields on the subcooled flow boiling of a ferrofluid in a vertically oriented annulus are thoroughly investigated experimentally in this work. The magnetic field generated by face-to-face electromagnets was systematically varied in strength (up to 0.3 T), frequency, and waveform (square, triangular, sinusoidal). The results demonstrate that magnetic fields under constant and alternating conditions substantially enhance local and average convective heat transfer coefficients and critical heat flux compared to the no-field baseline. Due to its ability to effectively disrupt the thermal boundary layer and improve bubble dynamics, the alternating square-wave magnetic field (0.3 T, 2 Hz) notably produces the greatest enhancement. Under this condition, the convective heat transfer coefficient increased by up to 21 %, and the critical heat flux improved by approximately 24 % compared to the no-field baseline. The enhancement strongly depends on mass flux and field frequency, with optimal frequencies shifting higher at increased flow rates due to shortened nanoparticle residence time in the magnetic region. At elevated mass fluxes, the benefit of alternating over constant fields diminishes as inertial effects become dominant.Article A Novel ORC-PEM Integrated System for Sustainable Hydrogen Production from Low-Grade Waste Heat in Oil Refineries(Elsevier, 2025) Nazerifard, Reza; Mohammadpourfard, Mousa; Zarghami, RezaThis study presents an integrated multi-generation system for sustainable hydrogen production by harnessing low-grade waste heat from the overhead stream of the NHT unit's stripper column in an oil refinery. The proposed system integrates an ORC with a PEM electrolyzer, forming a novel energy solution that efficiently converts waste heat into clean hydrogen through electricity generation. A detailed model of the proposed system is developed, enabling a comprehensive assessment of its performance from thermodynamic, economic, and environmental viewpoints. At the same time, key operational parameters are optimized using the RSM-BBD method to minimize the hydrogen production cost, thereby enhancing the system's economic viability and practical implementation. The results demonstrated that the system achieves a yearly hydrogen production of 304.53 tons under optimized conditions, for 2.36 $/kg. The integrated system's overall energy and exergy efficiencies are calculated at 8.62 % and 33.43 %, respectively, demonstrating its high thermodynamic performance. Additionally, the system mitigates 3047 tons of CO2 annually by displacing conventional hydrogen production methods.Article Citation - WoS: 2Citation - Scopus: 2Experimental Optimization of Alternating Magnetic Field Parameters for Convective Heat Transfer Enhancement of Ferrofluid in a Vertical Annulus(Pergamon-Elsevier Science Ltd, 2025) Youzbashi-Zade, Saeed; Aminfar, Habib; Mohammadpourfard, MousaThis study presents a detailed experimental investigation of how applying constant and alternating magnetic fields enhances the convective heat transfer of Fe3O4/water ferrofluid flowing through a vertical annulus. The setup was exposed to both constant (steady) and alternating magnetic fields with different waveforms (square, triangular, and sinusoidal), frequencies, intensities, and axial positions. Results showed that both steady and alternating fields substantially increased heat transfer within the active region, with the alternating field providing the highest enhancement. This improvement comes from stronger fluid movement under the oscillating field, which disrupts the thermal boundary layer more efficiently than the steady field. The maximum local heat transfer enhancement decreased from 54.98 % at Re = 200 to 29.43 % at Re = 1000, highlighting the reduced influence of magnetic forces at higher flow rates. The study also explored the influence of magnetic field initiation location, revealing that downstream activation yields higher peak local enhancement, while earlier activation ensures more uniform improvement along the annulus. Among the tested waveforms, the square wave resulted in the greatest convective enhancement, followed by triangular and sinusoidal forms. Results also revealed that, regardless of waveform, increasing frequency initially enhances the heat transfer coefficient, reaching an optimal value typically at 2-5 Hz depending on Reynolds number and waveform.Article Reversibility and Entropy in Bubbling Fluidized Beds: A Recurrence-Based Analysis(Elsevier, 2026) Zarghami, Reza; Mohammadpourfard, Mousa; Akkurt, Gulden GokcenNonlinear time series analysis techniques were applied to characterize bubbling fluidization. The delay method was used to reconstruct the state space attractor and analyze the reconstructed state space. The experiments were carried out in a laboratory-scale fluidized bed, operated under ambient conditions and with various sizes of particles, settled bed heights, measurement heights, and superficial gas velocities. The reversibility of the gas-solid fluidized bed hydrodynamics was investigated using pressure fluctuations by recurrence plot analysis. The anti-diagonal lines of the recurrence plot (RP) were regarded as a measure of reversibility. It was shown that the reversibility versus gas velocity has a concave shape in the bubbling regime. The highest reversibility occurs at velocities remarkably lower than the turbulent transition velocity. In addition, reversibility increases as the size of the particles increases. The Kolmogorov entropy was also estimated to confirm the reversibility analysis in the state space domain. In addition, the average cycle frequency and wideband energy in the frequency domain were also used to clarify the results in the state domain. It was found that a minimum in average cycle frequency, wideband energy, and entropy with an increase in the velocity corresponds to the transition between macro-structures and finer structures of the fluidization system. This minimum was primarily found in the macro-structures of the bubbling fluidization system. These findings can provide a practical tool for the optimal design and operation of the fluidized bed.Article Comprehensive 4E Analysis, Multi-Objective Optimization, and Feasibility Study of Five Natural Gas Liquefaction Processes With a Case Study for Iran(Elsevier Sci Ltd, 2026) Basmenj, Farhad Rahmdel; Tabriz, Zahra Hajimohammadi; Aghdasinia, Hassan; Mohammadpourfard, MousaNatural gas (NG) is increasingly vital as a cleaner energy source due to its lower carbon emissions compared to other fossil fuels. Liquefaction facilitates efficient long-distance transportation. While numerous studies address NG liquefaction's technical aspects, holistic research remains limited. This study presents a comprehensive evaluation of five conventional natural gas (NG) liquefaction processes (including SMR-Linde, SMR-APCI, C3MRLinde, DMR-APCI, and MFC-Linde) through a 4E framework: energy, exergy, exergoeconomic, and exergoenvironmental analyses. Addressing limitations in prior research, it incorporates environmental considerations and introduces production volume-independent metrics to ensure equitable comparisons. Multi-objective optimization, based on exergoeconomic and exergoenvironmental criteria, is employed to identify Pareto-optimal operating conditions. To accelerate this complex process, neural networks are utilized. The study concludes with a feasibility assessment of large-scale LNG production in Iran, offering practical insights for optimizing process selection and enhancing the economic and environmental viability of LNG technologies. Simulations show that the MFC-Linde cycle as the most efficient regarding specific energy consumption (0.2563 kWh/kgLNG), coefficient of performance (3.184), and exergy efficiency (52.32 %). It also demonstrates the lowest unit exergy cost (3.67$/GJ) and exergy unit environmental impact (5271.86mPts/GJ). Multi-objective optimization, considering both exergetic-economic and exergetic-environmental criteria, using neural networks and genetic algorithms in MATLAB identifies Pareto-optimal conditions for all processes. For the MFCLinde, as the most efficient process, optimal operating conditions in the exergetic-economic trade off scenario are: Exergy efficiency of process = 51.45% and Exergy cost rate of LNG = 82, 162.15$/h; at Pressure of NG feed = 5, 925.32kPa, Pressure drop in valve = 5, 831.99kPa, and NG side temperature in heat exchanger = -168.34 degrees C. Finally, a feasibility study for large-scale LNG (Liquefied Natural Gas) production in Iran shows promising results, with a return on investment of 32.24 %/year and a payback period of 2.34 years, indicating the project's potential success in regions with abundant NG reserves.Article Citation - WoS: 1Citation - Scopus: 1Design and Comprehensive Analysis of a Solar-Biomass Hybrid System With Hydrogen Production and Storage: Towards Self-Sufficient Wastewater Treatment Plants(Pergamon-Elsevier Science Ltd, 2025) Tabriz, Zahra Hajimohammadi; Kasaeian, Alibakhsh; Mohammadpourfard, Mousa; Shariaty-Niassar, MojtabaThis paper comprehensively investigates a novel solar-biomass hybrid system designed to produce power, heating, hydrogen, methane, and digestate. The system's design is grounded in regional weather patterns and site-specific resource availability. A comprehensive thermodynamic and exergoeconomic analysis, based on the first and second laws of thermodynamics, is performed alongside parametric studies to evaluate the influence of key parameters on system performance. Multi-objective optimization employs a genetic algorithm facilitated by an artificial neural network to reduce computational time and balance exergy efficiency and total cost. The Pareto front is generated, and the TOPSIS method is employed to identify the optimal trade-off point. The system integrates an auxiliary boiler powered by stored hydrogen and methane to maintain consistent operation during periods of low solar irradiance. Key findings include a base-case overall energy efficiency of 78.67 % and exergy efficiency of 60.41 %. The base-case unit cost of hydrogen is determined to be $3.174/kg, demonstrating competitive viability. Integrating the biomass subsystem with the solar plant resulted in a 40 % increase in exergy efficiency and a 35 % improvement in the total unit cost of products compared to a stand-alone solar system. Optimized system parameters yielded an exergy efficiency of 55.52 % and a total cost rate of 14.98 M $/year. These results confirm the potential of this hybrid system as a promising sustainable solution for developing self-sufficient wastewater treatment plants.Article Machine Learning in Flow Boiling: Predicting Bubble Lift-Off Diameter Despite Data Limitations(Yildiz Technical University, 2025) Tabrizi, Atta Heydarpour; Mohammadpourfard, Mousa; Mohammadpourfard, MostafaThis study concentrates on applying machine learning techniques to flow boiling in order to predict the bubble lift-off diameter. This prediction is critical because the diameter plays a key role in understanding boiling dynamics and calculating heat transfer rates. Additionally, accurately predicting this diameter is essential for optimizing thermal systems and enhancing energy efficiency. By evaluating the performance of three different machine learning algorithms: M5 tree, multilinear regression, and random forest, we aimed to assess their effectiveness in providing reliable predictions even with limited experimental data. This research is essential as it demonstrates the potential of machine learning to enhance predictive accuracy in scenarios where obtaining extensive datasets is challenging. Our findings show that these machine-learning techniques are effective for accurate predictions. The results show that the coefficient of determination ranged from 0.64 to 0.94, indicating how well the models fit the data. The root mean square error was between 0.009 and 0.02, and the mean absolute error ranged from 0.0004 to 0.02. Based on the findings, it can be inferred that the machine learning algorithms used in this study are reliable for predicting bubble lift-off diameter. This reliability also extends to other experimental parameters, suggesting that these techniques can be effectively applied in various contexts with limited data. This study demonstrates the potential of machine learning to predict experimental parameters and advances previous research by identifying key factors that influence bubble lift-off diameter. © 2025 Elsevier B.V., All rights reserved.Article Citation - WoS: 4Citation - Scopus: 4Zn/Na Co-Doped Hydroxyapatites: Synthesis, Antibacterial, and Bioactivity Studies(Elsevier Science Sa, 2025) Samadi, Hamed; Pakchin, Parvin Samadi; Mohammadpourfard, Mousa; Adibkia, KhosroThe most crucial challenge of post-orthopedic surgery is related to bacterial film formation, which leads to implant failure. In this work, zinc/sodium (Zn/Na) co-doped hydroxyapatite nanoparticles (HA NPs) with different Zn/Na concentrations, including 1, 3, and 5 mol.% were synthesized using a hydrothermal method. Several analyses such as X-ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), Energy Dispersive X-ray Spectroscopy (EDX), Scanning Electron Microscopy (SEM), and N2 ad/desorption were used to pinpoint the properties of as-prepared materials. Field Emission Scanning Electron Microscopy (FE-SEM) and EDX analysis demonstrated that the HA NPs possess an average size of about 30-40 nm and hexagonal morphology with no impurity. XRD patterns confirm that by the increasing amounts of Zn/Na, the crystal size of samples was decreased. FT-IR affirms the correct doping of metal ions. Brunauer-Emmett-Teller (BET) results of co-doped samples demonstrated a microporous structure, which can improve fluid flow in the inner structure of implants. The colony-forming unit (CFU) method conducted the antibacterial test, which confirmed that 5 mol.% Zn/Na co-doped HA NPs showed the highest antibacterial properties against Escherichia coli (PTCC 1276) (E. coli). Cytotoxicity results affirmed that 1 and 3mol.% Zn/Na co-doped HA NPs demonstrated low toxicity. Bioactivity tests revealed that the Zn/Na co-doped samples showed a higher ability to facilitate bone marrow stem cells; thus, improving the proliferation after the immersion in simulated body fluid (SBF). Therefore, Zn/Na co-doped HA NPs could be a promising candidate for bone tissue engineering applications.Review Citation - WoS: 26Citation - Scopus: 28Exploring Geothermal Energy Based Systems: Review From Basics To Smart Systems(Pergamon-elsevier Science Ltd, 2025) Anya, Belka; Mohammadpourfard, Mousa; Akkurt, Gulden Gokcen; Mohammadi-Ivatloo, BehnamMost of the energy demand is currently supplied from fossil fuels, which leads to the accumulation of greenhouse gases and air pollution. A sustainable future can be created globally through the efficient use of renewable energy sources. These sources include wind, solar, geothermal, biomass, and more. Geothermal energy can meet the energy needs of the future as a clean and reliable source and stands out due to certain distinctive features among renewable energy sources. Unlike other renewable energy sources, geothermal energy is not dependent on time or weather, making it a reliable and continuous energy supply. Additionally, it has a lower environmental impact. This review examines the development of geothermal energy systems and their integration into smart technologies, highlighting the potential of geothermal energy for smart energy systems. The focus is on integrating smart systems into geothermal-based setups to enhance efficiency and analyze the state-of-the-art technologies of such systems. Geothermal-based systems can be classified as single generation, co-generation, multigeneration, smart energy systems, and energy hubs. Consequent to examining systems, it has been concluded that geothermal systems have a huge potential, but unfortunately, not all of them are used due to some difficulties. Its development will occur faster, and its share in the renewable energy sector will grow with smart system integration.Article Citation - WoS: 6Citation - Scopus: 7A Comprehensive Study on Doxorubicin-Loaded Aspartic Acid-Coated Magnetic Fe<sub>3</Sub>o<sub>4< Nanoparticles: Synthesis, Characterization and in Vitro Anticancer Investigations(Elsevier, 2024) Jafari, Nahideh; Mohammadpourfard, Mousa; Hamishehkar, HamedMagnetic Fe3O4 nanoparticles (MNPs) hold significant potential across various scientific fields due to their notable properties. For biomedical applications, MNPs must be biocompatible, stable, and possess high magnetic potential. Aspartic acid (ASP) as a coating agent not only provides biocompatibility, stability, and high magnetic potential but also offers the potential for absorbing various drugs for targeted delivery due to its carboxyl and amino functional groups. So, in this study, we synthesized ASP-coated MNPs (ASP-MNPs) through a one-step co-precipitation method and loaded doxorubicin (DOX) onto these nanoparticles to create DOX-ASP-MNPs for targeted drug delivery. Characterization of the nanoparticle confirmed the crystal structure, spherical morphology, and improved size distribution of ASP-MNPs (8.53 +/- 2.56 nm) compared to uncoated MNPs (7.05 +/- 1.89 nm), as analyzed by XRD, FESEM, and TEM. FT-IR and zeta potential assessments (ZP = -6.3 mV for MNPs, ZP = -31.1 mV for ASP-MNPs) verified successful ASP binding, DOX loading, and nanoparticle stability. VSM analysis indicated a slight decrease in saturation magnetism after coating (51.1 emu/g) compared to MNPs (57.4 emu/g). In vitro release studies demonstrated a higher release rate (83 %) of DOX-ASP-MNPs at pH 5.2, indicating their suitability for cancerous cells. Cytotoxicity assays on A-549 cancer cell lines showed a dose-dependent response. DAPI staining revealed that free DOX caused more DNA damage. Cellular uptake studies indicated a time-dependent uptake of DOX-ASP-MNPs, higher at 3 h compared to 1 h, though lower than free DOX uptake due to different uptake pathways. Apoptosis assays over 72 h showed similar apoptotic rates for DOX-ASP-MNPs and free DOX. These findings suggest that ASP-MNPs possess enhanced physicochemical properties and effective drug delivery capabilities, making them a promising candidate for different biomedical applications, particularly targeted cancer therapy.