AP/HTPB/Demir oksit bazlı yakıtların matematiksel model ve deney sonuçlarıyla yanma hızı karşılaştırması.


Tezin Türü: Yüksek Lisans

Tezin Yürütüldüğü Kurum: Orta Doğu Teknik Üniversitesi, Mühendislik Fakültesi, Makina Mühendisliği Bölümü, Türkiye

Tezin Onay Tarihi: 2019

Öğrenci: Serhat Cem. Özcan

Danışman: ABDULLAH ULAŞ

Özet:

Ballistic properties play a crucial role for designing solid propellant rocket motors. Among those properties, burning rate is one of the most critical properties that must be known in order to predict the performance of the motor accurately. While various experimental methods such as Ballistic Evaluation Motor tests, strand burner experiments and full scale motor testing are used to obtain burning rate, these methods may lead to time and money consumption problems. In order to save time and reduce the cost, theoretical models for predicting the burning rate have been developed from 1960's. In this study, Cohen and Strand model and Beckstead, Derr and Price model have been combined and numerically coded to predict the burning rates of Ammonium Perchlorate/Hydroxyl Terminated Polybutadiene (AP/HTPB) based composite propellants. Additionally, to incorporate the catalyst effect, the code was expanded based on the Krishnan and Jeenu model. To compare the predictions of the model, strand burner experiments have been conducted for various propellants having AP diameters of 10µm, 40µm, 90µm, and 200µm and having solid loading of 70, 73, 77, and 80 percent. The matrix was expanded with the Fe2O3 addition to the AP/HTPB propellants and a total of 390 strand burner experiments have been conducted for those propellants to compare the results with the numerical scheme predictions. For the results, it is observed that burning rates increase with lowering AP particle size, increasing AP percent and adding catalyst to the propellants. For mid-size AP (40µm and 90µm) based propellants, numerical predictions give better results but approaching towards either 10µm or 200µm AP based propellants, discrepancies between predictions and results become larger. All in all, promising predictions are observed as a general conclusion for this study.