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Performance analysis of cutting tools from ILCM tests through computer-aided modelling methods

Kursat Kilic

Performance analysis of cutting tools from ILCM tests through computer-aided modelling methods.

Rel. Marilena Cardu. Politecnico di Torino, Corso di laurea magistrale in Petroleum And Mining Engineering (Ingegneria Del Petrolio E Mineraria), 2020

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This study is realized with the aim to evaluate the performance analysis of TBM's (Tunnel Boring Machine ) disc cutters through computer-aided modelling methods, such as IBM SPSS Statistics 25. According to real projects and to some research activities, it has been justified that, due to its high safety, good productivity and less environmental impacts, TBM tunnelling is the most suitable technique for civil engineering purposes in urban areas. As quoted by (Barla, 2014), the TBMs are categorized as the Gripper TBM, Single Shield TBM and Double Shield TBM. The TBMs uses the cutter head from 1 m to 19 m. According to (Bilgin, 2013), the EPB/TBM operates in soft ground, and the excavated material is used for support. For the performance analysis of the TBM in hard rock, several models are used in literature. For instance, the QTBM model (Barton, 1999; Barton, 2000) utilizes the rock mass classification system. The NTNU model (Bruland et al., 1995) is a kind of empirical model, and it uses rock mass properties with machine parameters for performance analysis. Another approach is presented by (Roxborough and Phillips, 1975); the disc cutters are affected by their geometry and rock strength. The CSM model (Ozdemir, 1997), is based on the V - profile type disc cutter, and it has been modified with industrial experience. As quoted by (Bilgin, 2013), in boulder rock conditions, the chisel and disc cutter are used together during advancement. As quoted by (Xu et al., 2019), some computer-aided modelling has been applied to TBM performance analysis. For instance, KNN (k-Nearest Neighbor), SVM (support vector machine), artificial neural network (ANN), CART ( classification and regression trees), CHAID (Chi-Squared Automatic Interaction Detection), Non - Linear Multiple Regression Analysis, Neuro-Fuzzy Modelling and SPSS Analysis. Furthermore, according to (Pan et al., 2019; Balci, 2009), the LCM (Linear Cutting Machine) is the more reliable and correct method for performance analysis because it provides practical rock cutting force and efficient cutter spacing, thrust and torque. On the other hand, the TBM disc cutter performance analysis has been done by using ILCM's outputs data (Intermediate Linear Cutting Machine). The ILCM has some advantages than the LCM in terms of handling and positioning of the rock samples. For this dissertation work, the data which have been acquired from Italian stones such as the Vico Diorite, Luserna stone and Prali marble used. To summarize, the thesis provides elaborative results in terms of ILCM disc cutter performance analysis by using IBM SPSS linear regression models among the rock and machine interaction parameters such as specific energy, normal force, rolling force, s/p, cutting coefficient. All information, as mentioned above, is deeply explained in the text.

Relators: Marilena Cardu
Academic year: 2020/21
Publication type: Electronic
Number of Pages: 93
Corso di laurea: Corso di laurea magistrale in Petroleum And Mining Engineering (Ingegneria Del Petrolio E Mineraria)
Classe di laurea: New organization > Master science > LM-35 - ENVIRONMENTAL ENGINEERING
Aziende collaboratrici: Politecnico di Torino
URI: http://webthesis.biblio.polito.it/id/eprint/15699
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