2012[Archives of Mining Sciences] a Universal Model to Predict Roadheaders’ Cutting Performance %2F Uniwersalny Model Do Prognozowania Postępu Prac Kombajnów Do Drążenia Tuneli

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  DOI 10.2478/v10267-012-0067-5 Arch. Min. Sci., Vol. 57 (2012), No 4, p. 1015–1026 Electronic version (in color) of this paper is available: http://mining.archives.pl ARASH EBRAHIMABADI*, KAMRAN GOSHTASBI**, KOUROSH SHAHRIAR***, MASOUD CHERAGHI SEIFABAD**** A UNIVERSAL MODEL TO PREDICT ROADHEADERS’ CUTTING PERFORMANCEUNIWERSALNY MODEL DO PROGNOZOWANIA POST Ę PU PRAC KOMBAJNÓW DO DR  ĄŻ ENIA TUNELI The paper intends to generate a universal model to predict the performance of roadheaders for all kinds of rock formations. In this regard, we first take into account the outcomes of previous attempts to explore the performance of roadheaders in Tabas Coal Mine project (the largest and fully mechanized coal mine in Iran). During those investigations, rock mass brittleness index (RMBI) was defined in order to relate the intact and rock mass characteristics to machine performance. The statistical analysis of data acquired from Tabas field demonstrated that RMBI was highly correlated to instantaneous cutting rate (ICR) of roadheaders (  R ² = 0.92). With the aim to construct a universal model for predicting the roadheader  performance, we have now tried to establish a database consisting measured cutting rate of roadheaders as well as the data gathered from field studies of Tabas Coal Mine project and Besiktas, Kurucesme, Baltalimani, Eyup and Halic tunnels in Turkey. A broad modeling and analysis found a fair relationship, resulting in a new universal predictive model to predict the cutting rate of roadheaders with correlation of 0.73 (  R ² = 0.73). The application of local and universal models at Tabas Coal Mine showed a remar-kable difference between measured and predicted ICR. The mean relative error of 0.359% was found with universal model but it represented lower value (mean relative error of 0.100%) while using local model. It can thus be concluded that instead of generating a universal model, separate localized models for different ground and machine conditions should be developed to improve the accuracy and reliability of the performance prediction models. Keywords:  performance prediction, roadheader, tunneling, Rock Mass Brittleness Index, Tabas Coal MineW pracy podj ę  to prób ę   opracowania uniwersalnego modelu do prognozowania post ę   pu prac kombaj-nów do dr  ąż enia tuneli we wszystkich rodzajach ska ł . W pierwszym etapie przeprowadzono analiz ę   wyni-ków bada ń  w tym zakresie prowadzonych uprzednio w kopalni w ę  gla Tabas (jest to najwi ę  ksza i w pe ł ni * DEPARTMENT OF MINING, FACULTY OF ENGINEERING, QAEMSHAHR BRANCH, ISLAMIC AZAD UNIVERSITY, QAEMSHAHR, IRAN; E-MAIL: ARASH.XER@GMAIL.COM (CORRESPONDING AUTHOR) ** DEPARTMENT OF MINING, FACULTY OF ENGINEERING, TARBIAT MODARES UNIVERSITY, TEHRAN, IRAN *** DEPARTMENT OF MINING, METALLURGICAL AND PETROLEUM ENGINEERING, AMIRKABIR UNIVERSITY OF TECHNOLOGY, TEHRAN, IRAN**** DEPARTMENT OF MINING, ISFAHAN UNIVERSITY OF TECHNOLOGY, ISFAHAN, IRAN, 84156-83/11  - 10.2478/v10267-012-0067-5Downloaded from PubFactory at 08/12/2016 01:13:02PMvia free access  1016 zmechanizowana kopalnia w ę  gla w Iranie). W ramach bada ń  zdefiniowano wspó ł czynnik krucho ś ci ska ł  (RMBI) w celu okre ś lenia zale ż no ś ci pomi ę  dzy w ł a ś ciwo ś ciami nienaruszonych warstw skalnych a po-st ę   pami pracy kombajnów. Analiza statystyczna danych uzyskanych w kopalni Tabas wykaza ł a wysoki  poziom korelacji pomi ę  dzy wska ź nikiem RMBI a chwilow ą   pr  ę  dko ś ci ą   urabiania (ISC) kombajnów do dr  ąż enia tuneli (  R 2  = 0.92). Maj ą  c na celu opracowanie uniwersalnego modelu do prognozowania post ę   pu  prac kombajnów do dr  ąż enia tuneli, autorzy podj ę  li najpierw prób ę   stworzenia bazy danych obejmuj ą  cej zmierzone pr  ę  dko ś ci urabiania oraz dane uzyskane w trakcie bada ń  polowych w kopalni w ę  gla Tabas, oraz z projektu dr  ąż enia tuneli w kopalniach w Besiktas, Kurucesme, Baltalimani, Eyup i Halic w Turcji. W wyniku modelowania i analiz znaleziono w miar  ę   dok  ł adn ą   zale ż no ść , prowadz ą  c ą   do stworzenia uni-wersalnego modelu prognozowania pr  ę  dko ś ci urabiania przy u ż yciu kombajnów do dr  ąż enia tuneli, przy  poziomie korelacji 0.73 (  R 2  = 0.73). Zastosowanie lokalnego i uniwersalnego modelu w kopalni w ę  gla Tabas wykaza ł o znaczne ró ż nice pomi ę  dzy mierzon ą   a prognozowan ą   chwilow ą   pr  ę  dko ś ci ą   urabiania. Ś redni b łą  d wzgl ę  dny dla modelu uniwersalnego wyniós ł  0.359%, w przypadku modelu lokalnego ś redni  b łą  d wzgl ę  dny by ł  na poziomie 0.100%. St ą  d te ż  nale ż y wnioskowa ć , ż e dla poprawy wiarygodno ś ci i do-k  ł adno ś ci prognozowania zamiast tworzenia uniwersalnego modelu, zasadne jest opracowanie odr  ę   bnych modeli „lokalnych” uwzgl ę  dniaj ą  cych konkretne uwarunkowania gruntowe oraz sprz ę  towe. S ł owa kluczowe:  prognozowanie post ę   pu prac, maszyna do dr  ąż enia tuneli, dr  ąż enie tuneli, wska ź nik krucho ś ci ska ł , kopalnia w ę  gla w Tabas 1. Introduction Currently, the world industries are moving toward more profitable, productive and com- petitive arenas and therefore, mechanization is becoming an inevitable alternative to gain these objectives. Mining and civil construction industries, too, lead this trend; hence, the ever-increasing applications of mechanical miners such as roadheaders, TBMs, continuous miners, etc. are some of the outcomes of project mechanizations, leading to their more extensive use in the mining and civil construction industries in recent years. Roadheaders have remarkable advantages including high productivity, reliability, mobility, flexibility, safety, selective excavation, less strata disturbances, fewer personnel and lower capital and operating costs. To achieve these benefits as well as successful roadheader application, perform-ance prediction of the machine needs to be accomplished appropriately. This generally deals with machine selection, production rate and pick (bit) consumption. The machine selection is performed on the basis of tunnel dimensions and its ground conditions such as profile size and shape, floor material condition (with respect to resistance against machine weight and ground pressure), slope, etc. Moreover, performance prediction mainly involves the assessment of instantaneous cutting rate (ICR) which is defined as the production rate during actual cutting time (tons or m³/cutting hour) and pick consumption rate (PCR) which refers to the number of picks changed per unit volume or weight of rock excavated (picks/m³ or m³/pick). The following are the most affecting  parameters on the roadheader production rate and pick consumption rate (Rostami et al., 1994): – Rock parameters, such as rock compressive and tensile strength, etc. – Ground conditions, such as degree of joint (RQD), joint conditions, ground water, etc.  – Machine specification, including machine weight, cutter head power, sumping, arcing, lifting, and lowering forces, cutter head type (axial or transverse), bit type, size, and other characteristics, number of allocation of bits on the cutter head, and the capacity of back up system. – Operational parameters including shape, size, and length of opening, inclination, costs, etc (Jaszczuk & Kania, 2008). - 10.2478/v10267-012-0067-5Downloaded from PubFactory at 08/12/2016 01:13:02PMvia free access  1017 The paper, first gives a brief background of roadheaders performance prediction models and then it establishes a database from the detailed field data including machine performance and geotechnical parameters in tunnels as well as entries from the Tabas Coal Mine project (the largest and fully mechanized coal mine in Iran) and Besiktas, Kurucesme, Baltalimani, Eyup and Halic tunnels in Turkey (Bilgin et al., 1988, 1990, 1996). Thereafter, the paper highlights some of the previous attempts made to construct a model to predict the roadheaders performance in Tabas coal mine. Applying whole data in the established database, subsequently, a universal  performance prediction model is developed. 2. Brief background Sandbak (1985) and Douglas (1985) used a rock classification system to explain changes in roadheader’s advance rates at San Manuel Copper Mine in an inclined drift at an 11% grade (Bilgin et al., 2004). Gehring (1989) studied the relationship between  ICR  and rock uniaxial compressive strength ( UCS  ) for a milling type roadheader with 230 kW cutter head power and an Alpine Miner AM 100 ripping type roadheader with 250 kW cutter head power. He developed following equations without giving correlation coefficients:  0.78 719 c  Lc   (1)for ripping type roadheaders, and  1.13 1739 c  Lc   (2)for milling type roadheadersWhere  L c  denotes as cutting performance (m³/hr), and c  as the uniaxial compressive strength (MPa). Based on rock compressive strength and rock quality designation, Bilgin et al. (1988, 1990, 1996, 1997, 2004) had also developed a performance equation as:   ICR  = 0,28 ×  P   × (0,974)  RMCI   (3)   RMCI   = σ  c  × (  RQD /100) 2/3  (4)where  ICR  is the instantaneous cutting rate (m³/cutting hour),  P   is the power of cutting head (hp),  RMCI   is the rock mass cuttability index, σ  c  is the uniaxial compressive strength (MPa) and  RQD  is the rock quality designation (%). Copur et al. (1997, 1998) studied the variation of cutting rate with UCS   based on available field performance data for different types of roadheaders at differ-ent geological conditions. They stated that if power and weight of roadheaders were considered together, in addition to rock compressive strength, the cutting rate predictions would be more realistic. The predictive equations for transverse (ripping type) roadheaders are as follows:   ICR  = 27,511 e 0.0023(  RPI  )  (5)   RPI   =  P   × W  / UCS   (6)  - 10.2478/v10267-012-0067-5Downloaded from PubFactory at 08/12/2016 01:13:02PMvia free access  1018 Here,  ICR ,  RPI  , UCS  , W  ,  P   and e  denote instantaneous cutting rate (m³/hr), roadheader  penetration index, uniaxial compressive strength (MPa), roadheader weight ( t  ), power of cutting head (kW), and base of natural logarithm, respectively. Thuro and Plinninger (1999) determined the relationship between the cutting rate and the uniaxial compressive strength for 132 kW road-header. They found that the correlation between UCS   and cutting performance is not sufficient in predicting the cutting rate. They obtained higher correlation by putting the cutting perform-ance against specific destruction work (kJ/m³). Specific destruction work ( W   z  ) is defined as the measurement for the quantity of energy required for destruction of a rock sample or – in other words – the work, necessary to built new surfaces (or cracks) in rock. They presented the fol-lowing predictive equation:  CR  = 107.6 – 19.5ln( W   z  ) (7)where CR and W   z   are the cutting performance (m³/hr) and the specific destruction work (kJ/m³), respectively.Another way of predicting the machine instantaneous cutting rate is to use specific energy described as the energy spent to excavate a unit volume of rock material. Widely accepted rock classifications and assessments for the performance estimation of roadheaders are based on the specific energy found from core cutting tests. Detailed laboratory and in situ investigations by McFeat-Smith and Fowell (1977, 1979) showed that there was a close relationship between spe-cific energy values obtained separately from both core cutting tests and cutting rates for medium and heavy weight roadheaders. One of the most accepted methods to predict the cutting rate of any excavating machine is to use, cutting power, specific energy obtained from full scale cutting tests and energy transfer ratio from the cutting head to the rock formation as indicated in the following equation (Rostami et al, 1994):  opt  SE  P k  ICR    (8)where  ICR  is the instantaneous production rate (m³/cutting hour),  P   is the cutting power of the mechanical miner (kW), SE  opt   is the optimum specific energy (kWh/m³), and k is the energy transfer coefficient depending on the mechanical miner utilized. Rostami et al. (1994) strongly emphasized that the predicted value of the cutting rate was more realistic if the specific energy value in the equation was obtained from the full-scale linear cutting tests in optimum conditions using real life cutters. Rostami et al. (1994) pointed out that k changed between 0.45 and 0.55 for roadheaders and from 0.85 to 0.90 for TBMs. 3. Previous predictive models in Tabas coal mine Tabas Coal Mine is the largest and fully mechanized mine, located at about 75 km from the city of Tabas in the central Iranian province of Yazd. The mine area is a part of Tabas-Kerman coal field which is divided into three parts, the biggest being the Parvadeh region with an extent of 1200 Km² and estimated 1.1 billion tones of coal reserve. This is the main part to be excavated and fulfillment the future needs. In the Tabas mine, four DOSCO MD 1100 roadheaders of 34 t - 10.2478/v10267-012-0067-5Downloaded from PubFactory at 08/12/2016 01:13:02PMvia free access
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