Publikační činnost Děkanátu FS / Publications of the Dean's Office of the Faculty of Mechanical Engineering

Permanent URI for this collectionhttp://hdl.handle.net/10084/155712

Kolekce obsahuje bibliografické záznamy publikační činnosti (článků) akademických pracovníků Děkanátu FS (300) v časopisech registrovaných ve Web of Science od roku 2024 po současnost.
Do kolekce jsou zařazeny:
a) publikace, u nichž je v originálních dokumentech jako působiště autora (adresa) uvedena Vysoká škola báňská-Technická univerzita Ostrava (VŠB-TUO),
b) publikace, u nichž v originálních dokumentech není v adrese VŠB-TUO uvedena, ale autoři prokazatelně v době jejich zpracování a uveřejnění působili na VŠB-TUO.

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    Enhancing surface quality and tool life in SLM-machined components with Dual-MQL approach
    (Elsevier, 2024) Ross, Nimel Sworna; Mashinini, Peter Madindwa; Mishra, Priyanka; Ananth, M. Belsam Jeba; Mustafa, Sithara Mohamed; Gupta, Munish Kumar; Korkmaz, Mehmet Erdi; Nag, Akash
    Selective laser melting (SLM) can produce complex metal components with high densities, thereby surpassing the limitations of traditional machining methods. However, achieving accurate dimensions, geometries, and acceptable surface states in parts fabricated through SLM remains a concern as they often fall short compared to traditionally machined components. As a solution, a hybrid additive-subtractive manufacturing (HASM) method was developed to effectively utilize the advantages of both techniques. In this study, SLM-made 316 L stainless steel was machined under distinct cooling conditions to investigate the effects of roughness and tool wear. After a thorough investigation, the dual-MQL strategy was evaluated and compared with dry and MQL cutting strategies. The findings showed that the dual-MQL condition led to a significant reduction in flank wear by 54-56% and 29-34%, respectively, associated with dry and MQL cutting techniques, making it a highly promising key for machining SLM-made steel components. Machine learning techniques are potential tools for prediction and classification capabilities in machining processes. For milling SLM-made 316 L SS, multilayer perceptron (MLP) proved to be the most effective prediction model and for classification MLP and Random forest performed better.
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    Pyrolysis solid product as a sorbent for flue gases mercury capture - Part I: Sorbent formation and characteristics
    (Elsevier, 2024) Jadlovec, Marek; Honus, Stanislav; Čespiva, Jakub
    This study investigates the pyrolysis of various materials (solid recovered fuel, digestate, hay pellets, straw, polyethylene, and tires) at temperatures ranging from 350 to 650 degrees C, with retention times between 90 and 190 minutes and a heating rate of 10 degrees C center dot min-1. Its focus is on utilizing pyrolysis residue-char as a sorbent for mercury capture from flue gas during conventional fuel combustion. Physical and chemical activation techniques employing NaOH as an oxidizing agent are used to enhance surface area and pore volume. Characterization techniques, including thermogravimetric analysis, Fourier transform infrared spectroscopy, scanning electron microscopy and various analyses, are employed. Results indicate solid fraction recoveries of 77%wt. for solid recovered fuel, 58%wt. for tires, and 48%wt. for straw, with average recoveries of 47%wt. solid, 18.7%wt. gaseous, and 34.3%wt. liquid fractions. After applying the activation processes, the results reveal that the most suitable sorbent is the straw sample, where the specific surface area and pore volume are 148.95 m2 center dot g-1 and 0.0569 cm3 center dot g-1 after physical activation and 640.98 m2 center dot g-1 and 0.2867 cm3 center dot g-1 after chemical activation, respectively. These findings suggest promising applications for pyrolysis char as sorbents, with significant improvements achieved through activation methods. The application of the developed sorbents for mercury capture in a real flue gas environment is closely investigated in Part II of this study.