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Article Citation - WoS: 1Citation - Scopus: 1Flame Retarded Plasticized Poly(lactic Acid) Using Phosphorus-Based Additives(Sage Publications Ltd, 2024) Yesil, Sertan; Aytac, Ayse; Selim, FatmaIn this study, the synergistic effect of the flame-retardant additives on the properties of poly(lactic acid) (PLA) was investigated and at the same time, it was tried to increase the toughness of PLA by adding small amounts of phosphate-based additives to plasticized PLA as binary and ternary mixtures. Poly(ethylene glycol) (PEG) was used as a plasticizer. As flame retardant additives, ammonium polyphosphate (APP), tri-phenyl phosphate (TPP), and boron phosphate (BP) were used. Characterization of the composites was carried out by tensile test, impact test, differential scanning calorimetry (DSC), thermal gravimetric analyses (TGA), scanning electron microscopy (SEM), limiting oxygen index (LOI), and UL-94 horizontal burning tests. In addition, TGA-FTIR analyses were carried out to understand the thermal degradation mechanism of composites during combustion. According to the SEM micrographs of the burnt surfaces of the samples, a smooth and flat structure is observed in PLA/PEG/5TPP-5BP sample, while a porous structure and branching formations are observed in other composite samples. Among the composite samples, the best flame retardancy features were observed in the composite containing PLA/PEG/5APP-2.5TPP-2.5BP sample, and the highest impact strength and elongation at break values were obtained in the composite containing PLA/PEG/5APP-5TPP sample.Article Citation - WoS: 8Citation - Scopus: 10Computing Reliability Indices of a Wind Power System Via Markov Chain Modelling of Wind Speed(Sage Publications Ltd, 2024) Eryilmaz, Serkan; Bulanik, Irem; Devrim, YilserStatistical modelling of wind speed is of great importance in the evaluation of wind farm performance and power production. Various models have been proposed in the literature depending on the corresponding time scale. For hourly observed wind speed data, the dependence among successive wind speed values is inevitable. Such a dependence has been well modelled by Markov chains. In this paper, the use of Markov chains for modelling wind speed data is discussed in the context of the previously proposed likelihood ratio test. The main steps for Markov chain based modelling methodology of wind speed are presented and the limiting distribution of the Markov chain is utilized to compute wind speed probabilities. The computational formulas for reliability indices of a wind farm consisting of a specified number of wind turbines are presented through the limiting distribution of a Markov chain. A case study that is based on real data set is also presented.