 Advances in Technology Innovation , vol. 2, no. 3, 2016, pp. 73 - 84 73 Copyright © TAETI Optimization of Ducted Propeller Design for the ROV (Remotely Operated Vehicle) Using CFD Aldias Bahatmaka 1,* , Dong-Joon Kim 2 , Deddy Chrismianto 3 1 Interdiciplinary Program of Marine Design Convergence, Pukyong National University, Busan, Korea. 2 Department of Naval Architecture and Marine Systems Engineering , Pukyong National University, Busan, Korea. 3 Department of Naval Architecture, Diponegoro University, Semarang, Indonesia. Received 09 March 2016; received in revised form 19 June 2016; accept ed 21 June 2016 Abstract The development of underwater robot technology is growing rapidly. For reaching the best performance, it is important that the inn o- vation on ROV should be focused on the thruster and propeller. In this research, the ducted propeller thruster is used while three types of SHUSKHIN nozzle are selected. The design is compared in a c - cordance with the thruster that has been made as the propulsion device of underwater robots. Each type of the thruster model indicates dif- ferent force and torque. For the analysis, each model is built in Co mputer Aided Design (Rh inoceros) program pac kages and Comput a- tional Fluid Dyna mics (CFD) to find the most optima l model wh ich can produce the h ighest thrust. Among the entire model, the Kaplan series (Ka5-75) with the type C of nozzle has the highest thrust which is 2.53 N or 25.24% of e xt ra thrust. For the optimization o f thrust, genetic A l- gorithms (GA) is used. The GA can search for parameters in la rge mult i-d imensional design space. Thus, the principle can be applied for determining the initia l propelle r that produces optimu m thrust of ROV. The GA has success- fully shown able to obtain an optima l set p a- ra meters for propeller characteristics with the best performance. Ke ywor ds : Re motely Operated Vehic le (ROV), ducted propeller, CFD, genetic a l- gorithms Nomenclature AE propeller expanded area A0 propeller disk area CTn regression coefficient of thrust coefficient CQn regression coefficient of torque coefficient D diameter propeller J advance coefficient KT thrust coefficient KQ torque coefficient N propeller blade pitch P/D pitch diameter ratio Q torque (Nm) Sn exponent of J T thrust tn exponent of P/D Un exponent of AE/A0 Vn exponent of Z Z number of blades Ρ density of water 1. Introduction Re motely Operated Vehic le (ROV) is an in- strument formed min i-sized submission vehicle. ROV is usually used to explore underwater photography, military operation and underwater pipeline repairing. ROV is used for activit ies small cave. ROV is designed to have abilities of seabed rescue operations and repairing o f seabed objects from the surface [1]. Un d e rwa t e r ro b o t is d es ig n ed a nd ma n u fa c t u re d abso lu t e ly requ ire s ma n y supporting components to improve the operation to perform a variety missions. Thruster is one component that has function as locomotor of underwater robot to maneuver horizontally when it moves forward and bac kwa rd and a lso to maneuver vertically to moves up and down [2]. * Corresponding aut hor, Email: bahat maka.aldias@gmail.com Advances in Technology Innovation , vol. 2, no. 3, 2016, pp. 73 - 84 74 Copyright © TAETI The first proposal to use a screw propeller appears to have been made in England by Ho oke in 1680, and its first actual use is generally at- tributed to Colonel Stevens in a stream-driven boat at New York in 1804. In 1828 a vessel 18 m (60 feet) long was successfully propeller by a screw propelle r designed by Ressel. The screw propeller has reigned supreme in the rea lm of ma rine propulsion. It has proved e xtraord inarily adaptable in meeting the incessant quest for propellers to deliver mo re and more thrust under increasingly arduous conditions [3]. The Genetic A lgorith ms is one of method that has tool for optimization for many difficult optimization proble m with mult iple object ives. GA methods were shown to be able to replace the traditional computation method and design charts. In this case, for determining the in itia l propeller that optimu m for ROV thruster is dif- ficult. For selecting the init ial propelle r, used optim tools in Genetic Algorithms, the result will be found directly and efficiently. However, the traditional design charts method and previous GA methods were li mited in considering or ma ximu m hydrodynamic as- pect alone, such as hydrodynamic efficiency, and the thrust coefficient, etc. Hence, the goals of the present research are: to determine the optimu m value o f thrust for ROV thruster using 3 para meters are pitch dia meter rat io, e xpanded blade area ratio, and rotational speed of propelle r. Applying GA methods to propeller design with consideration of thrust for reach ing the best performance of propeller. 2. Method The Co mputational Flu id Dyna mics (CFD) [4], is one branch of fluid mechanics that uses numerical methods and algorithms to solve and analyse problems related to flu id flo w the pu r- pose of CFD is to predict accurately on fluid flow, heat transfer, and chemica l reactions in comple x systems, which involve one or a ll the above phenomena. 2.1. ROV Design In this research, ROV project in Fig. 1 has been designed and which has dimension as shown as the Table 1. Table 1 Principle dimensions of ROV Item Unit Length 601.87 mm Beam 409.20 mm Height 290.00 mm Mass (on air) 13.70 mm Weight 5.00 N Fig. 1 ROV Project design 2.2. Propeller Design The propeller d imension and geometry d e- sign are listed in the Table 2. Table 2 Principle dimensions of Propeller Item Unit Diameter 130.00 mm Pitch 78.00 mm Amount of blade 5 blades Expanded BAR 0.75 Rake of angle (B5-75) 10.00 degree Rake of angle (Ka 5-75) 15.00 degree Rotational speed 300.00 rpm Density of water 1.025 kg/m3 In this case, the propeller dimension was chosen by the product sold in the market. And using this dimension, propeller was designing in CAD model. Fo r the design used 2 types of design, B-Se ries (B5-75) as shown in Fig. 2 and Kaplan-Series (Ka5-75) as shown in Fig. 3. Advances in Technology Innovation , vol. 2, no. 3, 2016, pp. 73 - 84 75 Copyright © TAETI Fig. 2 B-Series (B5-75) Fig. 3 Kaplan-Series (B5-75) 2.3. Numerical Method and Bboundary Condi- tions In this steps, for the numerical on analysis was using Co mputational Fluid Dyna mics Method. Several steps for calculat ions such as: geometry, mesh, setup, solution, and result. Boundary condition was calcu lating for the open water propeller [5]. The boundary condi- tion can be shown in Fig. 4. Fig. 4 Boundary Condition of open water propeller 2.4. Validation of Thruster In this research to validate the result of the test model, used the software test result that a lre a dy e xis t a nd was con du ct ed b y Mulyowidodo, K. et al in Bandung Technology Institute - Indonesia. Va lidation of underwater thruster for SHRIMP ROV-IT B is used to de- termine the e xact boundary condition for using on the boundary condition when analyzing 3 models for ROV thruster using CFD-based software. Re ference is taken fro m the validated model for the testing thruster. Used propeller type of Ka5-75 series and based on the theory of wageningen [6], the open water propelle r char- acteristics conventionally were presented in form of the thrust and torque coeffic ient K T and KQ in term of the advance coefficient J, where 2 4T T K n D  (1) 2 5Q T K n D  (2) A V J nD  (3) The characteristics of the ship’s propeller for open water test condition are as represented in KT-KQ-J Chart. Type of each propelle r is hav- ing the characteristic curves of different p er- formance. It can be shown in Fig. 5. Fig. 5 KT-KQ-J Chart 2.5. Geometry Design of Nozzle For the calcu lation of nozzle , SHUSHKIN nozzle has been chosen which developed (Prof.Dr.-Ing. H. Heuser, 1982). The nozzle design is shown in Fig. 6. Advances in Technology Innovation , vol. 2, no. 3, 2016, pp. 73 - 84 76 Copyright © TAETI Fig. 6 Pressure process and flow contraction at the nozzle propeller compared The Size of kort nozzle tipe A: LD/DP =0,75; DI / DP = 1.015; limits: 20mm <(DI – DP) < 60 mm; DA/DI = 1,25; LA/ LD = 0,53; LP/ LD = 0,27, LV/ LD = 0,40; LH/LD = 0:33 The size of kort nozzle tipe B: LD/DP = 0,75; DI/ DP = 1,015; limits: 20mm < (DI –DP) < 60 mm; DA/DI = 1,25; DK/ DI = 1,02; DR/DI = 1,035; LA/ LD = 0,32; LP/LD = 0,25, LV/ LD = 0,425; LH/ LD = 0,325; LK/LH = 0,925 The size of kort nozzle tipe C : LD/DP = 0,75; DI/ DP = 1,015; limits: 20mm < (DI – DP) < 60 mm; DA/DI = 1:20; DK/ DI = 1,015; DR/DI = 1,030; LA=LD = 0,50; LP/LD = 0,50; LV/ LD = 0,40; LH/ LD = 0,35; LK/LH = 0,880 2.6. Preliminary Propeller Design The preliminary propeller design proble m is described in detail in the Princ iples of Nava l Architecture [3]. Here is the basic design or initia l design of propelle r with the principa l dimension as: (Dependent variables) Diameter : 130.00 mm Amount of blades (z) : 5 blades Rake of Angle : 15.00 degree Material : Mn.Bronze (2) Density of water : 1.025 kg/m3 (Independent variables) P/D : 0.60; 0.65; 0.70 AE/A0 : 0.75; 0.80; 0.85 Rotational speed (n) : 5 rps; 10 rps; 15 rps 2.7. Performance of Computation Selecting fro m a propeller series is a simp le method to design a propeller. A mong the series propeller is one of the most often used and studied. And selection of the blade was im- proved later. The thrust and torque coefficient can be expressed as the Table 3. Table 3 Regression coefficients and exponents of KT-KQ n C Tn s n tn u n vn n C Qn s n tn u n vn 1 0.00880496 0 0 0 0 1 0.00379368 0 0 0 0 2 −0.204554 1 0 0 0 2 0.00886523 2 0 0 0 3 0.166351 0 1 0 0 3 −0.032241 1 1 0 0 4 0.158114 0 2 0 0 4 0.00344778 0 2 0 0 5 −0.147581 2 0 1 0 5 −0.0408811 0 1 1 0 6 −0.481497 1 1 1 0 6 −0.108009 1 1 1 0 7 0.415437 0 2 1 0 7 −0.0885381 2 1 1 0 8 0.0144043 0 0 0 1 8 0.188561 0 2 1 0 9 −0.0530054 2 0 0 1 9 −0.00370871 1 0 0 1 10 0.0143481 0 1 0 1 10 0.00513696 0 1 0 1 11 0.0606826 1 1 0 1 11 0.0209449 1 1 0 1 12 −0.0125894 0 0 1 1 12 0.00474319 2 1 0 1 13 0.0109689 1 0 1 1 13 −0.00723408 2 0 1 1 14 −0.133698 0 3 0 0 14 0.00438388 1 1 1 1 15 0.00638407 0 6 0 0 15 −0.0269403 0 2 1 1 16 −0.00132718 2 6 0 0 16 0.0558082 3 0 1 0 17 0.168496 3 0 1 0 17 0.0161886 0 3 1 0 18 −0.0507214 0 0 2 0 18 0.00318086 1 3 1 0 19 0.0854559 2 0 2 0 19 0.015896 0 0 2 0 20 −0.0504475 3 0 2 0 20 0.0471729 1 0 2 0 21 0.010465 1 6 2 0 21 0.0196283 3 0 2 0 22 −0.00648272 2 6 2 0 22 −0.0502782 0 1 2 0 Advances in Technology Innovation , vol. 2, no. 3, 2016, pp. 73 - 84 77 Copyright © TAETI Table 3 Regression coefficients and exponents of KT-KQ (continued) n C Tn s n tn u n vn n C Qn s n tn u n vn 23 −0.00841728 0 3 0 1 23 −0.030055 3 1 2 0 24 0.0168424 1 3 0 1 24 0.0417122 2 2 2 0 25 −0.00102296 3 3 0 1 25 −0.0397722 0 3 2 0 26 −0.0317791 0 3 1 1 26 −0.00350024 0 6 2 0 27 0.018604 1 0 2 1 27 −0.0106854 3 0 0 1 28 −0.00410798 0 2 2 1 28 0.00110903 3 3 0 1 29 −0.000606848 0 0 0 2 29 −0.000313912 0 6 0 1 30 −0.0049819 1 0 0 2 30 0.0035985 3 0 1 1 31 0.0025983 2 0 0 2 31 −0.00142121 0 6 1 1 32 −0.000560528 3 0 0 2 32 −0.00383637 1 0 2 1 33 −0.00163652 1 2 0 2 33 0.0126803 0 2 2 1 34 −0.000328787 1 6 0 2 34 −0.00318278 2 3 2 1 35 0.000116502 2 6 0 2 35 0.00334268 0 6 2 1 36 0.000690904 0 0 1 2 36 −0.00183491 1 1 0 2 37 0.00421749 0 3 1 2 37 0.000112451 3 2 0 2 38 5.65229E−05 3 6 1 2 38 −2.97228E−05 3 6 0 2 39 −0.00146564 0 3 2 2 39 0.000269551 1 0 1 2 40 0.00083265 2 0 1 2 41 0.00155334 0 2 1 2 42 0.000302683 0 6 1 2 43 −0.0001843 0 0 2 2 44 −0.000425399 0 3 2 2 45 8.69243E−05 3 3 2 2 46 −0.0004659 0 6 2 2 47 5.54194E−05 1 6 2 2 As the functions of the blade number, blade area ratio, p itch ratio and advance coefficient [4]: 39 1 0 Untn Sn vnE T Tn n AP K C J Z D A             (4) 47 1 0 Untn Sn vnE Q Qn n AP K C J Z D A             (5) where CTn and CQn are the regression coeffi- cients of the thrust and torque coefffic ients, repectively; Sn, tn, Un, and vn are the exponents of J, P/D, AE/A0, and Z, respectively. 2.8. Genetic Algorithms (GA) The basic theory, Genetic Algor ithms a re search algorithms based on the mechanics of natural selection and natural genetics. They combine survival of the fittest among string s tructure with structured yet randomized informat ion e xchange to inform a structure al- gorithms with some of the innovative flair of human search. In every generation, a new set of artific ia l creatures (strings) is created using bits and pieces of the fittest of the old man; an occasional new part is tried for good measure. While ran- domized, genetic algorithms are no simple ran- dom walk. They effic iently e xp loit historica l informat ion to speculate on new search points with e xpected imp roved performance. Genetic algorith ms have been developed by John Ho l- land [7]. Based on the theory, the research was con- ducted with the set of para meters dependent and independent variables. For the first steps were identifying variab les and functions, the prope l- ler of re mote ly operated vehicle (ROV) , there are three variable that we could change ran- domly as like as P/D (p itch ratio ), AE/A0 (e x- panded blade area rat io), and n (rotational speed). Using the three variables, we would get the value of KT and KQ. Thus, the thrust (T) and torque (Q) can be expressed as: Function:  2 4TT K n D (6)  2 5QQ K n D (7) The fitness function we can select the Eqs. (6) and (7), then used the regression Table (3) to produce the thrust and torque coefficients. Advances in Technology Innovation , vol. 2, no. 3, 2016, pp. 73 - 84 78 Copyright © TAETI Fitness function: 39 1 0 Untn Sn vnE T Tn n AP K C J Z D A             (8) 47 1 0 Untn Sn vnE Q Qn n AP K C J Z D A             (9) The constraint function, used three variables (P/D, AE/A0, n) can be created as: Constraint function: 0.60 0.70 P D   (10) 5 15n  (11) 2.9. Optimization For the process of optimization shown in Fig. 7, used optimization tools that supported by Matlab program for the solution of Genetic Algorith ms method. In this case, GA apply to know how is the optimu m thrust for the in itia l propeller using the parameters and all parame - ters setup for GA is shown in Table 4. Table 4 Setting up the GA parameters GA parameters Population size = 20 Number of generations = 80 Selection: Stochastic uniform Crossover rate = 0.8 Crossover function: Scattered Mutation rate = 0.2 Fig. 7 Flowchart of genetic algorithms Advances in Technology Innovation , vol. 2, no. 3, 2016, pp. 73 - 84 79 Copyright © TAETI 2.10. CFD Analysis Type A nozzle Fig. 8 Meshing of type A for B-Series (B5-75) Fig. 9 Meshing of type A for Kaplan-Series (Ka5-75) Type B nozzle Fig. 10 Meshing of type B for B-Series (B5-75) Fig. 11 Meshing of type B for Kaplan-Se ries (Ka5-75) The process of analysis for the nozzle design has been conducted. There were so me different results for the meshing process of all nozzle’s type. For the type A for B-Series (B5-75) shown in Fig. 8, it has 845,769 nodes and Kaplan-Se ries (K5-75) shown in Fig.9 has 702,840 nodes. The type B for B-Series (B5-75) shown in Fig.10, it has 1,146,817 nodes and Kap lan-Series (K5-75) shown in Fig.11 has 1,007,934 nodes. The type C for B-Se ries (B5-75) shown in Fig.12, it has 1,343,789 nodes and Kaplan-Series (K5-75) shown in Fig.13 has 1,206,703 nodes. Type C nozzle Fig. 12 Meshing of type C for B-Series (B5-75) Fig. 13 Meshing of type C for Kaplan-Se ries (Ka5-75) Streamline simulation For the simulat ion of strea mline, the input for a ll types were same, and the rotational speed was 300rp m. The results of streamline fro m type A nozzle for B-series (B5-75) shown in Fig.14, type A nozzle for Kap lan-series (Ka 5-75) shown in Fig.15, type B nozzle for B-series (B5-75) shown in Fig.16, type B nozzle fo r Kaplan-series (Ka 5-75) shown in Fig.17, type C nozzle for B-series (B5-75) shown in Fig.18, type A nozzle for Kaplan-series (Ka5-75) shown in Fig. 19. Advances in Technology Innovation , vol. 2, no. 3, 2016, pp. 73 - 84 80 Copyright © TAETI Type A nozzle Fig. 14 Strea mline of type A for B-Se ries (B5-75) Fig. 15 Strea mline of type A for Kaplan-Se ries (Ka5-75) Type B nozzle Fig. 16 Strea mline of type B for B-Se ries (B5-75) Fig. 17 Strea mline of type B for Kaplan-Se ries (Ka5-75) Type C nozzle Fig. 18 Strea mline of type C for B-Se ries (B5-75) Fig. 19 Strea mline of type C for Kaplan-Se ries (Ka5-75) Fro m a ll the figures, it can be seen that the type C of no zzle was the highest of thrust than type A or type B. Pressure contour Type A nozzle Fig. 20 Pressure contour of type A for B-Se ries (B5-75) Fig. 21 Pressure contour of type A for Kaplan-Series (Ka5-75) Advances in Technology Innovation , vol. 2, no. 3, 2016, pp. 73 - 84 81 Copyright © TAETI Type B nozzle Fig. 22 Pressure contour of type B for B-Se ries (B5-75) Fig. 23 Pressure contour of type B for Kaplan-Series (Ka5-75) Type C nozzle Fig. 24 Pressure contour of type C for B-Se ries (B5-75) Fig. 25 Pressure contour of type C for Kaplan-Series (Ka5-75) This process was indicating the pressure distribution on the blade area. The results of pressure contour from type A nozzle for B-series (B5-75) shown in Fig. 20, type A nozzle for Kaplan-series (Ka 5-75) shown in Fig. 21, type B nozzle for B-series (B5-75) shown in Fig. 22, type B nozzle for Kaplan-series (Ka 5-75) shown in Fig. 23, type C nozzle for B-series (B5-75) shown in Fig. 24, type A nozzle for Kaplan-series (Ka5-75) shown in Fig. 25. 3. Results and Discussion Fro m the analysis of CFD method, it can be seen on the Table 5. For the changes of the force as clearly shown in Fig. 26, and the changes of the torque shown in Fig. 27. Table 5 Results of Force (T) and Torque (Q) Type of models Force (T) (N) Torque (Q) (Nm) B-Series (B5-75) Propeller without nozzle 1.67 0.016 Nozzle A 2.06 0.020 Nozzle B 2.12 0.021 Nozzle C 2.26 0.023 Kaplan (Ka5-75) Propeller without nozzle 2.02 0.020 Nozzle A 2.34 0.022 Nozzle B 2.50 0.023 Nozzle C 2.53 0.024 Fig. 26 Chart of Force (T) analysis on 300rpm Advances in Technology Innovation , vol. 2, no. 3, 2016, pp. 73 - 84 82 Copyright © TAETI Fig. 27 Chart of Torque (Q) analysis on 300rpm In this paper, we have described the speci- fication and the design concepts of ducted pro- peller as the thruster of ROV (Re motely Oper- ated Veh icle ). The re we re several designs of the ducted propeller. Total o f models were 6 models , B-Series (B5-75) and Kap lan-Se ries (Ka5-75) with nozzle’s type A, B, and C. Based on the simu lations which we re co n- ducted, can be concluded that the highest of force (T) was model of Kaplan-Series (Ka5-75) with type C of nozzle. The mode l could produce 2.53 N, or 25.24% of e xt ra thrust. The lowest of torque (Q) was model of B-Series (B5-75) with type A of nozzle . Thus the best model will be used for ROV thruster is model of Kaplan -Se ries (Ka5-75) with type C of nozzle. In other hand, the model a lso was conducted for analysis using other software, was used Star CCM+ for checking the value of the force (T) and the torque (Q). The geo metry shown in Fig. 28, The mesh scene as shown in Fig. 29, and the results could be seen in Fig. 30 for the strea mline simu lation and for the pressure contour shown in Fig. 31. Geometry Fig. 28 Geometry of ducted propeller in Star CCM+ Generating Mesh Fig. 29 Mesh Scene in Star CCM+ Streamline simulation Fig. 30 Streamline simulation in Star CCM+ Pressure Contour Fig. 31 Pressure contour in Star CCM+ Based on the simu lation results both of ANSYS CFX and Star CCM+ is almost same value, the difference of the force (thrust) is around 5%. It means, the analysis of ducted propeller is enough satisfied and accurate. It can be seen on the Table 6. Table 6 Comparison Results Results ANSYSCFX STAR CCM+ Force (T) 2.53 2.66 Torque (Q) 0.024 0.033 Advances in Technology Innovation , vol. 2, no. 3, 2016, pp. 73 - 84 83 Copyright © TAETI Optimization In the previous chapter has been obtained the model that will be used for the ROV (Re motely Operated Vehicle ). The model is the Kaplan-series with type C nozzle. Further, the optimization analysis can be applied to get the optimal of thrust for this case. With the fitness function and constraints fro m the Table 7, the results can be e xported by Genetic Algorithms as shown in Fig. 32. Table 7 Output of Optimum Thrust Iteration P/D AE/A0 n(rev/s) 51 0.60 0.79 5.00 At the 51 iterat ion using GA, the thrust will be optimu m when the value of P/D (pitch ratio) is 0.60, A E/A0 is 0.79 and the value of rotational speed is 5 rev/s. Based on the results from the Table 8, the thrust is increasing 27.43% fro m 2.530 N to 3.224 N. And it means the optimization of the thrust for the ducted propeller of ROV is reached and satisfied. Fig. 32 Fitness value through the generations Final Results Table 8 Comparison the final results Result Original New Differences Force (N) 2.530 3.224 +27.43% Torque (Nm) 0.024 0.032 +33.33% 4. Conclusions In this paper, about a study on development of the propuls ion device for the ROV (Re motely Operated Veh icle ). The CFD method has been demonstrated to be more effective as the pro b- le m solver fo r determining the optimu m thrust of ROV. The nozzle can produce the e xtra thrust for the propeller. CFD model shows these results . The comparison of propeller types such as B-Series (B5-75) and Kaplan-series (Ka5-75) shows that Kaplan-series (Ka 5-75) has stronger thrust than B-series (B5-75) and the strea mline simulation shows these results also. The highest thrust (T) is fro m the mode l Kaplan-series (K5-75) with type C of nozzle . The model can produce 2.53 N or 25.24% of extra thrust. The GA is applied for optimization design of the initial p ropelle r dimension and the results show that it is good for this kind of the proble ms . The optimization method GA is easy to use as optimu m solution in mu lti-dimensional using three variables such as P/D (pitch rat io), A E/A0 (e xpanded blade area ratio), and n (rotational speed) are affecting to the result of the thrust. Fro m the results of optimizat ion, the thrust is optimu m when the value of P/D is 0.60, A E/A0 is 0.79 and the value of rotational speed is 5 rev/s or 300 rpm. In this research, for the optimizat ion of the ducted propeller for ROV has been proposed and provides the solution to the problem of ROV thruster. Therefore , CFD method and GA opt i- mization can be emp loyed due to its ability to solve the problem and its performance men- tioned above especially for the best performance of ducted propeller. Acknowledgement The authors would like to thanks fo r the support of the BK21 p lus MADEC hu man re - source development group in 2016, Pukyong National University, without their help, this paper could not be submitted. References [1] D. Christ, Roberto, L. Wern li Sr, Robert, The ROV Manual,user guide for observa- tion, United Kingdom: Burlington, 2007. [2] S. A. Sharkh, M. R. Harris, R. M. Crowder, P. H. Chappell, R. L. Stoll, and J. K. 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