2019
12
2
0
132
Design, Modeling and Adaptive Force Control of a New Mobile Manipulator with Backlash Disturbances
2
2
In this paper a new model of the mobile robot is designed and modelled equipped by a manipulator which can perform an operational task. Also an adaptive force controller is designed and implemented on the robot to provide the capability of the operational task of the robot. Kinematic and kinetic modelling of the robot is developed and a new force control method is proposed for controlling the manipulator of the mobile robot by which the external disturbances caused by its operational performance can be controlled. Therefore, in this paper, a new mobile robot is designed which is suitable for operational tasks like firing and its related modelling is presented. Afterwards, an adaptive force controller is designed and implemented in order to neutralize the destructive effect of the mentioned backlash disturbance. By conducting some analytic and comparative simulation scenarios, the correctness of modelling and efficiency of the designed force controller is verified and it is shown that the proposed closed loop mobile manipulator can successfully accomplish a firing operation in a large workspace of a mobile robot with good accuracy.
1

1
16


Hami
Tourajizadeh
Department of Mechanical Engineering, Faculty of Engineering,
University of Kharazmi, Tehran, Iran
Department of Mechanical Engineering, Faculty
Iran
tourajizadeh@khu.ac.ir


Samira
Afshari
Department of Mechanical Engineering, Faculty of Engineering,
University of Kharazmi, Tehran, Iran
Department of Mechanical Engineering, Faculty
Iran
s.afshari90@yahoo.com
Adaptive Force Control
Backlash Disturbances
Mobile Manipulator
Modelling of Firing Manipulator
[[1] Jakubiak, J., Małek, Ł., and Tchoń, K., A New Inverse Kinematics Algorithm for Nonholonomic Mobile Robots, IFAC Proceedings Vol.42. No. 13, 2009, pp. 647652. ##[2] Trojnacki, M., Dąbek, P., Studies of Dynamics of a Lightweight Wheeled Mobile Robot During Longitudinal Motion on Soft Ground, Mechanics Research Communications, Vol. 82, 2017, pp. 3642. ##[3] Khanpoor, A., Khalaji, A. K., and Moosavian, S. A. A., Dynamics Modeling and Control of a Wheeled Mobile Robot with OmniDirectional Trailer, In Electrical Engineering (ICEE), 2014 22nd Iranian Conference on. 2014. IEEE. ##[4] Sharma, A., Panwar, V., Control of Mobile Robot for Trajectory Tracking by Sliding Mode Control Technique. in Electrical, Electronics, and Optimization Techniques (ICEEOT), International Conference on. 2016. IEEE. ##[5] Hassanzadeh, I., Madani, K., and Badamchizadeh, M. A., Mobile Robot Path Planning Based on Shuffled Frog Leaping Optimization Algorithm, In Automation Science and Engineering (CASE), IEEE Conference on, 2010. IEEE. ##[6] Shojaei, K., Shahri, A. M., and Tarakameh, A., Adaptive Feedback Linearizing Control of Nonholonomic Wheeled Mobile Robots in Presence of Parametric and Nonparametric Uncertainties, Robotics and ComputerIntegrated Manufacturing, Vol. 27, No. 1, 2011, pp. 194204. ##[7] Chen, Y. H., Li, T. H. S. and Chen, Y. Y., A Novel Nonlinear Control Law with Trajectory Tracking Capability for Nonholonomic Mobile Robots: Closedform Solution Design, Applied Mathematics & Information Sciences, Vol. 7, No. 2, 2013, pp. 749. ##[8] Koubaa, Y., Boukattaya, M., and Dammak, T., Adaptive Control of Nonholonomic Wheeled Mobile Robot with Unknown Parameters, In Modelling, Identification and Control (ICMIC), 7th International Conference on, 2015, IEEE. ##[9] Korayem, M., Shafei, A., Motion Equation of Nonholonomic Wheeled Mobile Robotic Manipulator with Revolute–Prismatic Joints Using Recursive Gibbs–Appell Formulation, Applied Mathematical Modelling, Vol. 39, No, 56, 2015, pp. 17011716. ##[10] Seidi, E., et al. Dynamic Modeling and Parametric Analysis of Dual Arm Manipulator with RevolutePrismatic Joints Mounted on a Nonholonomic Mobile Base, In Robotics and Mechatronics (ICROM), 3rd RSI International Conference on, 2015, IEEE. ##[11] Korayem, M., et al., Analysis and Experimental Study of NonHolonomic Mobile Manipulator in Presence of Obstacles for Moving Boundary Condition, Acta Astronautica, Vol. 67, No. 78, 2010, pp. 659672. ##[12] Korayem, M., Shafei, A., and Seidi, E., Symbolic Derivation of Governing Equations for DualArm Mobile Manipulators Used in FruitPicking and the Pruning of Tall Trees, Computers and Electronics in Agriculture, Vol. 105, 2014, pp. 95102. ##[13] Deepak, B., Parhi, D. R. and Praksh, R., Kinematic Control of a Mobile Manipulator. in Proceedings of the International Conference on Signal, Networks, Computing, and Systems. 2016. Springer. ##[14] Boukens, M., Boukabou, A., and Chadli, M., Robust Adaptive Neural NetworkBased Trajectory Tracking Control Approach for Nonholonomic Electrically Driven Mobile Robots, Robotics and Autonomous Systems, Vol. 92, 2017, pp. 3040. ##[15] Djebrani, S., Benali, A., and Abdessemed, F., Impedance Control of an Omnidirectional Mobile Manipulator, IFAC Proceedings Vol. 42, No. 13, 2009, pp. 519524. ##[16] Lippiello, V., Ruggiero, F., Cartesian Impedance Control of a UAV with a Robotic Arm. 2012. ##[17] Wang, Y., Mai, T., and Mao, J., Adaptive Motion/Force Control Strategy for NonHolonomic Mobile Manipulator Robot Using Recurrent Fuzzy Wavelet Neural Networks, Engineering Applications of Artificial Intelligence, Vol. 34, 2014, pp. 137153. ##[18] Yin, X., Pan, L., Enhancing Trajectory Tracking Accuracy for Industrial Robot with Robust Adaptive Control, Robotics and ComputerIntegrated Manufacturing, Vol. 51, 2018, pp. 97102. ##[19] Gracia, L., et al., Adaptive Sliding Mode Control for Robotic Surface Treatment Using Force Feedback, Mechatronics, Vol. 52, 2018, pp. 102118. ##[20] Fedaravičius, A., Ragulskis, M., and Sližys, E., Dynamic Synthesis of the Recoil Imitation System of Weapons, Mechanics, Vol. 51, No. 1, 2005, pp. 4448. ##[21] Spong, M.W., Hutchinson, S., and Vidyasagar, M., Robot Modeling and Control, 2006. ##[22] Slotine, J. J. E., Li, W., Applied Nonlinear Control. Vol. 199. 1991: Prentice hall Englewood Cliffs, NJ. ##[23] Schilling, R. J., Fundamentals of Robotics: Analysis and Control, Vol. 629. 1990: Prentice Hall New Jersey. ##]
Vibration based Assessment of Tool Wear in Hard Turning using Wavelet Packet Transform and Neural Networks
2
2
Demanding high dimensional accuracy of finished work pieces and reducing the scrap and production cost, call for devising reliable tool condition monitoring system in machining processes. In this paper, a tool wear monitoring system for tool state evaluation during hard turning of AISI D2 is proposed. The method is based on the use of wavelet packet transform for extracting features from vibration signals, followed by neural network for associating the root mean square values of extracted features with tool flank wear values of the cutting tool. From the result of performed experiments, coefficient of determination and root mean square error for the proposed tool wear monitoring system were found to be 99% and 0.0104 respectively. The experimental results show that wavelet packet transform of vibration signals obtained from the cutting tool has high accuracy in tool wear monitoring. Furthermore, the proposed neural network has the acceptable ability in generalizing the system characteristics by predicting values close to the actual measured ones even for the cutting conditions not encountered in the training stage.
1

17
26


vahid
pourmostaghimi
Department of Mechanical Engineering,
University of Tabriz, Iran
Department of Mechanical Engineering,
University
Iran
vahidvpm@tabrizu.ac.ir


Mohammad
Zadshakoyan
Department of Mechanical Engineering,
University of Tabriz, Iran
Department of Mechanical Engineering,
University
Iran
zadshakoyan@tabrizu.ac.ir


Morteza
Homayon Sadeghi
Department of Mechanical Engineering,
University of Tabriz, Iran
Department of Mechanical Engineering,
University
Iran
morteza@tabrizu.ac.ir
Hard Turning
Neural Networks
Tool Wear Monitoring
Vibration Signals
Wavelet Packet Transform
[[1] Azizi, M. W., Belhadi, S., Athmane Yallese, M., Mabrouki, T., and Rigal, J. F., Surface Roughness and Cutting Forces Modeling for Optimization of Machining Condition in Finish Hard Turning of Aisi 52100 Steel, Journal of Mechanical Science and Technology, Vol. 26, No. 12, 2012, pp. 41054114. ##[2] Kong, D., Chen, Y., Li, N., and Tan, S., Tool Wear Monitoring Based on Kernel Principal Component Analysis and VSupport Vector Regression, The International Journal of Advanced Manufacturing Technology, Vol. 89, No. 14, 2016, pp. 175190. ##[3] Dutta, S., Pal, S. K., and Sen, R., Progressive Tool Flank Wear Monitoring by Applying Discrete Wavelet Transform on Turned Surface Images, Measurement, Vol. 77, 2016, pp. 388401. ##[4] Jianfeng, L., Yongqing, Z., Fangrong, C., Zhiren, T., and Yao, W., Wear and Breakage Monitoring of Cutting Tools by Optic Method (1st Part: Theory), Paper presented at the Proceedings of SPIE, 1996, pp. 481489. ##[5] Jetley, S. K., A New Radiometric Method of Measuring Drill Wear, SME Manufacturing Engineering Transactions and 12 th NAMRC North American Manufacturing Research, 1984, pp. 255259. ##[6] Sadílek, M., Kratochvíl, J., Petrů, J., Čep, R., Zlámal, T., and Stančeková, D., Cutting Tool Wear Monitoring with the Use of Impedance Layers, Vol. 21, No. 3, 2014, pp.639644. ##[7] Su, J. C., Huang, C. K., and Tarng, Y. S., An Automated Flank Wear Measurement of Microdrills Using Machine Vision, Journal of Materials Processing Technology, Vol. 180, No. 1, 2006, pp. 328335. ##[8] Ghosh, N, Ravi, Y. B., Patra, A., Mukhopadhyay, S., Paul, S., Mohanty, A. R., and Chattopadhyay, A. B., Estimation of Tool Wear During Cnc Milling Using Neural NetworkBased Sensor Fusion, Mechanical Systems and Signal Processing, Vol. 21, No. 1, 2007, pp. 466479. ##[9] AbuMahfouz, I., Drilling Wear Detection and Classification Using Vibration Signals and Artificial Neural Network, International Journal of Machine Tools and Manufacture, Vol. 43, No. 7, 2003, pp. 707720. ##[10] Bhaskaran, J., Murugan, M., Balashanmugam, N., and Chellamalai, M., Monitoring of Hard Turning Using Acoustic Emission Signal, Journal of Mechanical Science and Technology, Vol. 26, No. 2, 2012, pp. 609615. ##[11] D'Errico, G. E., An Adaptive System for Turning Process Control Based on Tool Temperature Feedback, Journal of Materials Processing Technology, Vol. 78, No. 1, 1998, pp. 4347. ##[12] Alonso, F. J., Salgado, D. R., Analysis of the Structure of Vibration Signals for Tool Wear Detection, Mechanical Systems and Signal Processing, Vol. 22, No. 3, 2008, pp. 735748. ##[13] Ebersbach, S., Peng, Z., Expert System Development for Vibration Analysis in Machine Condition Monitoring, Expert Systems with Applications, Vol. 34, No. 1, 2008, pp. 291299. ##[14] Chen, B., Chen, X., Li, B., He, Z., Cao, H., and Cai, G., Reliability Estimation for Cutting Tools Based on Logistic Regression Model Using Vibration Signals, Mechanical Systems and Signal Processing, Vol. 25, No. 7, 2011, pp. 25262537. ##[15] Bhuiyan, M. S. H., Choudhury, I. A., and Dahari, M., Monitoring the Tool Wear, Surface Roughness and Chip Formation Occurrences Using Multiple Sensors in Turning, Journal of Manufacturing Systems, Vol. 33, No. 4, 2014, pp. 476487. ##[16] Tjepkema, D., Van Dijk, J., and Soemers, H. M. J. R., Sensor Fusion for Active Vibration Isolation in Precision Equipment, Journal of Sound and Vibration, Vol. 331, No. 4, 2012, pp. 735749. ##[17] Segreto, T., Simeone, A., and Teti, R., Multiple Sensor Monitoring in Nickel Alloy Turning for Tool Wear Assessment Via Sensor Fusion, Procedia CIRP, Vol. 12, 2013, pp. 8590. ##[18] Salgado, D. R., Cambero, I., Herrera Olivenza, J. M., García SanzCalcedo, J., Núñez López, P. J., and García Plaza, E., Tool Wear Estimation for Different Workpiece Materials Using the Same Monitoring System, Procedia Engineering, Vol. 63, 2013, pp. 608615. ##[19] Painuli, S., Elangovan, M., and Sugumaran, V., Tool Condition Monitoring Using KStar Algorithm, Expert Systems with Applications, Vol. 41, No. 6, 2014, pp. 26382643. ##[20] Aghdam, B. H., Vahdati, M., and Sadeghi, M. H., VibrationBased Estimation of Tool Major Flank Wear in a Turning Process Using Arma Models, The International Journal of Advanced Manufacturing Technology, Vol. 76, No. 912, 2014, pp. 16311642. ##[21] Wang, J., Xie, J., Zhao, R., Zhang, L., and Duan, L., Multisensory Fusion Based Virtual Tool Wear Sensing for Ubiquitous Manufacturing, Robotics and ComputerIntegrated Manufacturing, Vol. 45, 2017, pp. 4758. ##[22] Silva, R. G., Reuben, R. L., Baker, K. J., and Wilcox, S. J., Tool Wear Monitoring of Turning Operations by Neural Network and Expert System Classification of a Feature Set Generated from Multiple Sensors, Mechanical Systems and Signal Processing, Vol. 12, No. 2, 1998, pp. 319332. ##[23] Siddhpura, A., Paurobally, R., A Review of Flank Wear Prediction Methods for Tool Condition Monitoring in a Turning Process, The International Journal of Advanced Manufacturing Technology, Vol. 65, No. 14, 2012, pp. 371393. ##[24] Liu, B., Ling, S. F., and Meng, Q., Machinery Diagnosis Based on Wavelet Packets, Journal of Vibration and Control, Vol. 3, No. 1, 1997, pp. 517. ##[25] Wu, Y., Du, R., Feature Extraction and Assessment Using Wavelet Packets for Monitoring of Machining Processes, Mechanical Systems and Signal Processing, Vol. 10, No. 1, 1996, pp. 2953. ##[26] Xiaoli, L., Zhejun, Y., Tool Wear Monitoring with Wavelet Packet Transform—Fuzzy Clustering Method, Wear, Vol. 219, No. 2, 1998, pp. 145154. ##[27] Mehrabi, M. G., KannateyAsibu Jr, E., Hidden Markov ModelBased Tool Wear Monitoring in Turning, Journal of Manufacturing Science and Engineering, Vol. 124, No. 3, 2002, pp. 651658. ##[28] Scheffer, C, Kratz, H., Heyns, P. S., and Klocke, F., Development of a Tool WearMonitoring System for Hard Turning, International Journal of Machine Tools and Manufacture, Vol. 43, No. 10, 2003, pp. 973985. ##[29] Velayudham, A, Krishnamurthy, R., and Soundarapandian, T., Acoustic Emission Based Drill Condition Monitoring During Drilling of Glass/Phenolic Polymeric Composite Using Wavelet Packet Transform, Materials Science and Engineering: A, Vol. 412, No. 1, 2005, pp. 141145. ##[30] Zhu, K., San Wong, Y., and Soon Hong, G., Wavelet Analysis of Sensor Signals for Tool Condition Monitoring: A Review and Some New Results, International Journal of Machine Tools and Manufacture, Vol. 49, No. 7, 2009, pp. 537553. ##[31] Chen, H., Huang, S., Li, D., and Fu, P., Turning Tool Wear Monitoring Based on Fuzzy Cluster Analysis, In Advances in Neural Network Research and Applications, Springer, Berlin, Germany, 2010, pp. 739745. ##[32] Lee, S., Tool Condition Monitoring System in Turning Operation Utilizing Wavelet Signal Processing and MultiLearning Anns Algorithm Methodology, Int J Eng Res Innov, Vol. 2, No. 1, 2010, pp. 4955. ##[33] Mikołajczyk, T., Nowicki, K., Kłodowski, A., and Yu Pimenov, D., Neural Network Approach for Automatic Image Analysis of Cutting Edge Wear, Mechanical Systems and Signal Processing, Vol. 88, 2017, pp. 100110. ##[34] Teshima, T., Shibasaka, T., Takuma, M., Yamamoto, A., and Iwata, K., Estimation of Cutting Tool Life by Processing Tool Image Data with Neural Network, CIRP AnnalsManufacturing Technology, Vol. 42, No. 1, 1993, pp. 5962. ##[35] Kaya, B., Oysu, C., and Ertunc, H. M., ForceTorque Based onLine Tool Wear Estimation System for Cnc Milling of Inconel 718 Using Neural Networks, Advances in Engineering Software, Vol. 42, No. 3, 2011, pp. 7684. ##[36] Yaqub, M. F., Gondal, I., and Kamruzzaman, J., MultiStep Support Vector Regression and Optimally Parameterized Wavelet Packet Transform for Machine Residual Life Prediction, Journal of Vibration and Control, Vol. 19, No. 7, 2013, pp. 963974. ##[37] Karam, S., Teti, R., Wavelet Transform Feature Extraction for Chip Form Recognition During Carbon Steel Turning, Procedia CIRP, Vol. 12, 2013, pp. 97102. ##[38] Jemielniak, K., Kossakowska, J., Tool Wear Monitoring Based on Wavelet Transform of Raw Acoustic Emission Signal, Advances in Manufacturing Science and Technology, Vol. 34, No. 3, 2010, pp. 516. ##[39] Fang, N., Srinivasa Pai, P., and Mosquea, S., Effect of Tool Edge Wear on the Cutting Forces and Vibrations in HighSpeed Finish Machining of Inconel 718: An Experimental Study and Wavelet Transform Analysis, The International Journal of Advanced Manufacturing Technology,Vol. 52, No. 1, 2011, pp. 6577. ##[40] Davim, J. P., and Figueira, L., Comparative Evaluation of Conventional and Wiper Ceramic Tools on Cutting Forces, Surface Roughness, and Tool Wear in Hard Turning Aisi D2 Steel, Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, Vol. 221, No. 4, 2007, pp. 625633. ##]
Comparative Study and Robustness Analysis of Quadrotor Control in Presence of Wind Disturbances
2
2
Controlling of the quadrotor has been noted for its trouble as the consequence of exceeds nonlinear system, strong coupled multivariable and external disturbances. Quadrotor position and attitude is controlled by several methodologies using feedback linearization, but when quadrotor works with unstructured inputs (e.g. wind disturbance), some limitations of this technique appear which influence flight work. Design control system with fast response, disturbance rejection, small error, and stability is the main objective of this work. So in this paper we can make use of new methods of control to design a controller of nonlinear robust with a reasonable performance to test the impact of wind disturbance in quadrotor control such as FuzzyPID controller and compared its results with the others four controllers which are PID tuned using GA, FOPID tuned using GA, ANN and ANFIS then discus which controller give the best results in the presence and absence of wind disturbance. The main objective of this paper is that performance of the designed control structure is computed by the fast response without overshoot and minim error of the position and attitude. Simulation results, shows that position and attitude control using FOPID has fast response and better steady state error and RMS error than FuzzyPID, ANFIS, ANN and PID tuned using GA without impact of wind disturbance but after impact of wind disturbance it was observed using FuzzyPID has fast response with minimum overshoot and better steady state error and RMS error than the other four controllers used in the paper and compared with most of literature reviews which didn't give the adequate results contrasted with the required position and attitude. The all controllers are tested by simulation under the same conditions using SIMULINK under MATLAB2015a.
1

27
37


Reham
Mohammed
Department of Electrical Engineering,
University of Suez Canal, Egypt
Department of Electrical Engineering,
University
Egypt
riry4mody@yahoo.com
Adaptive Neuro Fuzzy Inference System (ANFIS)
Artificial Neural Network (ANN)
FuzzyPID
Fractional Order PID (FOPID)
Genetic Algorithm (GA)
Proportional Integral Derivative (PID) Controller
Quadrotor
[[1] Kendoul, F., Survey of Advances in Guidance, Navigation, and Control of Unmanned Rotorcraft Systems, Journal of Field Robotics, Vol. 29, No. 2, 2012, pp. 315378. ##[2] Hou, H., et al,. A Simple Controller of Minisize QuadRotor Vehicle, In: 2010 IEEE International Conference on Mechatronics and Automation. IEEE, 2010. pp. 17011706. ##[3] Reizenstein, A., Position and Trajectory Control of a Quadcopter Using PID and LQ Controllers, 2017. ##[4] Bresciani, T., Modelling, Identification and Control of a Quadrotor Helicopter, MSc Theses, 2008. ##[5] De Lellis Costa De Oliveira, M., Modeling, Identification and Control of a Quadrotor Aircraft, 2011. ##[6] AlYounes, Y. M., AlJarrah, M. A., and Jhemi, A. A., Linear vs. Nonlinear Control Techniques for a Quadrotor Vehicle. In: 7th International Symposium on Mechatronics and its Applications, IEEE, 2010, pp. 110. ##[7] Minh, L. D., Ha, C., Modeling and Control of Quadrotor MAV Using VisionBased Measurement, In: International Forum on Strategic Technology, IEEE, 2010, pp. 7075. ##[8] Altug, E., Ostrowski, J. P., Mahony, R., Control of a Quadrotor Helicopter Using Visual Feedback, In: Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No. 02CH37292), IEEE, 2002, pp. 7277. ##[9] Mokhtari, A., et al. Feedback Linearization and Linear Observer for a Quadrotor Unmanned Aerial Vehicle, Advanced Robotics, Vol. 20, No. 1, 2006, pp. 7191. ##[10] Mellinger, D., et al. Design, Modeling, Estimation and Control for Aerial Grasping and Manipulation, In: 2011 IEEE/RSJ International Conference on Intelligent Robots and Systems, IEEE, 2011, pp. 26682673. ##[11] Subodh M., Robust Control of Quadrotors. Department of Automatic Control and Robotics, MSc Theses, 2017. ##[12] Madani, T., Benallegue, A., Control of a Quadrotor MiniHelicopter Via Full State Backstepping Technique, In: Proceedings of the 45th IEEE Conference on Decision and Control, IEEE, 2006, pp. 15151520. ##[13] Hamamci, S. E., An Algorithm for Stabilization of FractionalOrder Time Delay Systems Using FractionalOrder PID Controllers, IEEE Transactions on Automatic Control, Vol. 52, No. 10, 2007, pp. 19641969. ##[14] Efe, M. Ö., Neural Network Assisted Computationally Simple PIλDμ Control of a Quadrotor UAV, IEEE Transactions on Industrial Informatics, Vol. 7, No. 2, 2011, pp. 354361. ##[15] Han, J., From PID to Active Disturbance Rejection Control, IEEE Transactions on Industrial Electronics, Vol. 56, No. 3, 2009, pp. 900906. ##[16] Podlubny, I., FractionalOrder Systems and PIλDμ. IEEE Transactions on Automatic Control, Vol. 44, No. 1, 1999, pp. 208214. ##[17] Mahony, R., Kumar, V., and Corke, P., Multirotor Aerial Vehicles: Modeling, Estimation, and Control of Auadrotor. IEEE Robotics & Automation Magazine, Vol. 19, No. 3, 2012, pp. 2032. ##[18] Mohammed, R. H., Quadrotor Control Using Advanced Control Techniques. International Journal of Image, Graphics and Signal Processing, Vol. 11, No. 2, 2019, pp. 40. ##[19] Youns, M. D., Salih, M. A., and Abdulla, I. Abdulla. Position ControlOf Robot Arm Using Genetic Algorithm Based PID Controller, AL Rafdain Engineering Journal, Vol. 21, No. 6, 2013, pp. 1930. ##[20] Xue, D., Chen, Y., A Comparative Introduction of Four Fractional Order Controllers, In: Proceedings of the 4th World Congress on Intelligent Control and Automation (Cat. No. 02EX527), IEEE, 2002. pp. 32283235. ##[21] Faieghi, M. R. Nemati, A., On FractionalOrder PID Design, In: Applications of MATLAB in Science and Engineering, IntechOpen, 2011. ##[22] Kim, J., Kasabov, N., HyFIS: Adaptive NeuroFuzzy Inference Systems and Their Application to Nonlinear Dynamical Systems, Neural Networks, Vol. 19, No. 2, 1999, pp. 13011319. ##[23] Areed, F. G., Haikal, A. Y., and Mohammed, R. H., Adaptive NeuroFuzzy Control of an Induction Motor, Ain Shams Engineering Journal, Vol. 1, No.1, 2010, pp. 7178. ##[24] Mohammed, R. H., Bendary, F., and Elserafi, K., Trajectory Tracking Control for Robot Manipulator Using Fractional OrderFuzzyPID Controller, International Journal of Computer Applications, Vol. 134, No. 15, 2016, pp. 8887. ##[25] Jang, J. S. R., Sun, C. T., NeuroFuzzy Modeling and Control, Proceedings of the IEEE, Vol. 83, No. 3, 1995, pp. 378406. ##[26] Jang, J. S. R., ANFIS: AdaptiveNetworkBased Fuzzy Inference System, IEEE Transactions on Systems, Man, and Cybernetics, Vol. 23, No. 3, 1993, pp. 665685. ##[27] Mohammed, R., Quadrotor Control Using FractionalOrder PIλDμ Control, Journal of Advances in Computer Engineering and Technology, Vol. 5, No. 1, 2019, pp. 110. ##]
Vibration Suppression of Grass Trimmer Handle using Tunable Vibration Absorber
2
2
The electrical grass trimmers are widely used for cutting grass along the highways, roadside & general agricultural work. Grass trimming involves the use of motorized cutter spinning at high speed, resulting in handarm vibration syndrome among the machine operators. The purpose of this work is to reduce the handle vibration of grass trimmer using tuned vibration absorber (TVA). The variable stiffness dual mass vibration absorber is designed using Dunkerleys Equation and fabricated for testing. The experimental modal analysis of absorber is conducted to find resonance frequencies of the absorber and to validate the results obtained from equations. The experimental tests are carried on grass trimmer with absorber attached at different location for two cutter head positions to find the absorber attachment location to reduce handle vibrations to minimum level. The results indicated that the vibration attenuation is affected by the location of absorber and cutter head position of grass trimmer.
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39
44


Sushil
Patil
Department of Mechanical Engineering,
College of Engineering Malegaon (Bk),
Savitribai Phule Pune University, India
Department of Mechanical Engineering,
College
India
mailsushil2004@yahoo.co.in
Grass Trimmer
Handle Vibration
Modal Analysis
Vibration Absorber
Vibration Control
[[1] Brown, A. P., The Effects of AntiVibration Gloves on Vibration Induced Disorders: a Case Study, Journal of Hand Therapy, Vol. 3, No. 2, 1990, pp. 94100, DOI: 10.1016/S08941130(12) 80007X. ##[2] Muralidhar, A., Bishu, R., and Hallbeck, M., The Development and Evaluation of an Ergonomic Glove, Applied Ergonomics, Vol. 30, No. 6, 1999, pp. 555563,DOI:10.1016/S00036870(99)000058. ##[3] Sam, B., Kathirvel, K., Vibration Characteristics of Walking and Riding Type Power Tillers, Biosystems Engineering, Vol. 95, No. 4, 2006, pp. 51752 DOI:10.1016/j.biosystemseng. 2006.08.013. ##[4] Tewari, V. K., Dewangan, K. N., Effect of Vibration Isolators in Reduction of Work Stress During Field Operation of Hand Tractor, Biosystems Engineering., Vol. 103, No. 2, 2009, pp. 146158. DOI: 10.1016/j.biosystemseng.2009.03.002 ##[5] Rakheja, S., Dong, R., Welcome, D., and Schopper, A. W., Estimation of ToolSpecific Isolation Performance of Antivibration Gloves, International Journal of Industrial Ergonomic, Vol. 30, No. 2, 2002, pp. 7187. DOI: 10. 1016/S01698141 (02)000719. ##[6] Fasana, A., Giorcelli, E. A., Vibration Absorber for Motorcycle Handles, Meccanica, Vol. 45, No. 1, 2010, pp. 7988. DOI: 10.1007/ s1101200992298. ##[7] Golysheva, E. V., Babitsky, V. I., and Veprik, A. M., Vibration Protection for an Operator of a HandHeld Percussion Machine, Journal of Sound and Vibration, Vol. 274, No. 12, 2004, pp. 351367. DOI: 10.1016/j.jsv.2003.05.019. ##[8] Kadam, R., Vibration Characterization and Numerical Modeling of a Pneumatic Impact Hammer, Master Thesis, Virginia Polytechnic Institute and State University, July 20, 2006. ##[9] Mallick, Zulquernain., Optimization of the Operating Parameters of Grass Trimming Machine, Applied Ergonomics, Vol. 41, No. 2, 2010, pp. 260265, DOI:10.1016/j.apergo. 2009. 07.010 ##[10] Hao, K. Y., Mei, L. X., and Ripin, Z. M., Tuned Vibration Absorber for Suppression of HandArm Vibration in Electric Grass Trimmer, International Journal of Industrial Ergonomics, Vol. 41, No. 5, 2011, pp. 494508, DOI: 10.1016/j.ergon.2011.05.005 ##[11] Hao, K. Y., Ripin, Z. M., Nodal Control of Grass Trimmer Handle Vibration, International Journal of Industrial Ergonomics, Vol. 43, No. 1, 2013, pp. 1830, DOI: 10.1016/j.ergon.2012.10.007. ##[12] Sheth, A. J., Design and Performance Evaluation of Tuned Vibration Absorber for the Vibration Control of a Centrifugal Pump, Int. J of Advanced Design and Manufacturing Technology, Vol. 7, No. 1, 2014, pp. 5358. ##[13] Patil, S. S., Grass Trimmer Handle Vibration Reduction by Imposing Node Method Using Vibration Absorber, Noise and Vibration Worldwide, Vol. 49, No. 2, 2018, pp. 5061. DOI: 10.1177/0957456518763158. ##[14] Hill, S. G., Snyder, S. D., Design of an Adaptive Vibration Absorber to Reduce Electrical Transformer Structural Vibration, Journal of Vibration and Acoustics, Vol. 124, No. 3, 2002, pp. 6066011, DOI: 10.1115/1.1500338. ##[15] Thomson, W. T., Dahleh, M. D., Theory of Vibration with Application, Prentice Hall, 1997, ISBN0 7487 4380 4. ##]
Free Vibration of Functionally Graded Epoxy/Clay Nanocomposite Beams based on the First Order Shear Deformation Theory
2
2
This paper deals with free vibration of epoxy/clay nanocomposite beams for functionally graded and uniformly distributed of Nanoclay with simply supported conditions at both ends. The specimens were prepared for uniformly distributed of Nanoclay with different Nanoparticles weight percent (pure, 3 wt%, 5 wt% and 7 wt%) and functionally graded distribution. To apply the model of theoretical predictions for the Young modulus, the genetic algorithm procedure was employed for functionally graded and uniformly distributed epoxy/clay nanocomposites and then were compared with the experimental tensile results. The formulation for Young modulus includes the effect of nanoparticles weight fractions and it is modified for functionally graded distribution to take into account the Young modulus as a function of the thickness coordinate. The displacement field of the beam is assumed based on the first order shear deformation beam theory. Applying the Hamilton principle, the governing equations are derived. The influence of nanoparticles on the free vibration frequencies of a beam is presented. To investigate the accuracy of the present analysis, a compression study is carried out with the experimental free vibration results. The results have shown that there is high accuracy for the genetic algorithm procedure for theoretical predictions of the Young modulus and the free vibration frequencies for uniform distribution are generally lower than the corresponding value of the functionally graded distribution.
1

45
51


Mahdi
Karami Khorramabadi
Department of Mechanical Engineering, Khorramabad Branch, Islamic Azad University, Khorramabad, Iran
Department of Mechanical Engineering, Khorramabad
Iran
m.karami@khoiau.ac.ir
First Order Shear Deformation Theory
Free Vibration
Functionally Graded Nanocomposite
Genetic Algorithm Theory
[[1] Kojima, Y., Usuki A., Kawasumi, M., Okada, A., Kurauchi, T., and Kamagatio, O., Synthesis of Nylon 6Clay Hybrid by Montmorillonite Intercalated with Caprolactam, Journal of Polymer Science Part A, Vol. 8, No. 4, 1993, pp. 983986, 10.1002/pola.1993.080310418. ##[2] Wang, M. S., Pinnavaia, T. J., ClayPolymer Nanocomposites Formed from Acidic Derivatives of Montmorillonite and an Epoxy Resin, Chemistry of Materials, Vol. 6, No. 4, 1994, pp. 468474, 10.1021/cm00040a022. ##[3] Lan, T., Kaviratna, P. D., and Pinnavaia, T. J., On the Nature of PolyimideClay Hybrid Composites, Chemistry of Materials, Vol. 6, No. 5, 1994, pp. 573–575, 10.1021/cm00041a002. ##[4] Akelah, A., Moet, A., PolymerClay Nanocomposites: FreeRadical Grafting of Polystyrene onto Organophilic Montmorillonite Interlayers, Journal of Materials Science, Vol. 31, No. 13, 1996, pp. 3589–3596, 10.1007/BF00360767. ##[5] Bharadwaj, R. K., Mehrabi, A. R., Hamilton, C., Trujillo, C., Muruga, M., Fan, R., Chavira, A., and Thompson, A. K., Structure–Property Relationship in CrossLinked Polyester–Clay Nanocomposite, Polymer, Vol. 43, No. 13, 2002, pp. 3699–3705, 10.1016/S00323861(02)001878. ##[6] Fornes, T. D., Paul, D. R., Modeling Properties of Nylon 6/clay Nanocomposites Using Composite Theories, Polymer, Vol. 44, No. 17, 2002, pp. 4993–5013, 10.1016/S00323861(03)004713. ##[7] Suprakas, S. R., Masami, O., Polymer/Layered Silicate Nanocomposites: a Review from Preparation to Processing, Progress in Polymer Science, Vol. 28, No. 11, 2003, pp. 1539, 10.1016/j.progpolymsci.2003.08.002. ##[8] Jawahar, P., Kanny, K., and Balasubramanian, M., Influence of Nanoclay Addition on Properties of UnsaturatedPolyester Nanocomposite Gel Coat System, Journal of Polymer Engineering, Vol. 29, No. 8, 2009, pp. 563–580, 10.1515/POLYENG.2009.29.89.563. ##[9] Chandra, R., Singh, S. P., and Gupta, K., Damping Studies in Fiber Reinforced Composites, Composite Structures, Vol. 46, No. 1, 1999, pp. 41–51, 10.1016/S02638223(99)000410. ##[10] Chandradass, J., Rameshkumar, M., and Velmurugan, R., Effect of Nanoclay Addition on Vibration Properties of Glass Fiber Reinforced Vinyl Ester Composites, Materials Letters, Vol. 61, No. 22, 2007, pp. 4385–4388, 10.1016/j.matlet.2007.02.009. ##[11] Chandradass, J., Rameshkumar, M., and Velmurugan, R., Effect of Clay Dispersion on Mechanical, Thermal and Vibration Properties of GlassFiber Reinforced Vinyl Ester Composite, Journal of Reinforced Plastics and Composites, Vol. 27, No. 15, 2008, pp. 1585–1601, 10.1177/0731684407081368. ##[12] Mohan, T. P., Rameshkumar, M., and Velmurugan, R., Thermal, Mechanical and Vibration Characteristics of EpoxyClay Nanocomposites, Journal of Materials Science, Vol. 41, No. 18, 2006, pp. 5915–5925, 10.1007/s1085300602782. ##[13] Holland, J. H., Adaptation in Natural and Artificial Systems, University of Michigan press, Ann Arbor, Michigan, United State of America, 1975, pp. 28114. ##[14] Wang, C. M., Reddy, J. N., Shear Deformable Beams and Plates, Elsevier, Oxford, England, 2000, pp. 223242. ##[15] Reddy, J. N., Mechanics of Laminated Composite Plates and Shells Theory and Analysis, CRC, New York, United State of America, 2004, pp. 187199. ##[16] Thomas, B., Inamdar, P., Roy, T., and Nada, B. K., Finite Element Modeling and Free Vibration Analysis of Functionally Graded Nanocomposite Beams Reinforced by Randomly Oriented Carbon Nanotubes, International Journal on Theoretical and Applied Research in Mechanical Engineering [online journal], Vol. 2, No. 4, 2013, pp. 97102, URL: http://irdindia.in/journal _ijtarme/volume_2_issue_4.html [cited 1 May 2013]. ##[17] Kozlov, G., Dzhangurazov, B., Ziakov, G., and Mikitaev, A., The Nanocomposites Polyethylene/organoclay Permeability to Gas Description within the Frameworks of Percolation and Multifractal Models, Chemistry & Chemical Technology [online journal], Vol. 6, No. 2, 2012, pp. 163166, URL: http://ena.lp.edu.ua:8080/handle/ntb/13482 [cited 7 July 2012]. ##[18] Lei, Z. X., Liew, K .M., and Yu, J. L., Free Vibration Analysis of Functionally Graded Carbon NanotubeReinforced Composite Plates Using the ElementkpRitz Method in Thermal Environment, Composite Structures, Vol. 106, No. 1, 2013, pp. 128138, 10.1016/j.compstruct.2013.06.003. ##]
A New Robust Strategy to Improve the Transient Dynamic of a Vehicle
2
2
In this paper for handling improvement and lateral stability increment of a fourwheeled vehicle a new robust active control system is proposed. First, to establish an accurate model of the vehicle, a fourteendegreesoffreedom nonlinear dynamic model is developed. model of the vehicle, a fourteendegreesoffreedom nonlinear dynamic model is developed. Then, the nonlinear dynamic model is validated using CarSim software in a standard maneuver. Next, a new active steering control system was designed based on a simplified twodegreesoffreedom dynamic mode to control the lateral motion of the vehicle. Two state variables, namely the vehicle’s yaw rate and the vehicle’s lateral velocity, are controlled using the control system. Also, the sliding mode control method is used to eliminate the error between the actual response and the desired response. Moreover, a complete stability analysis is presented based on the Lyapunov theory to guarantee closedloop stability. Simulation results show that the controller is able to increase the vehicle’s maneuverability, especially during severe double lane change maneuver in which intense instability occurs. More investigations demonstrate that the proposed control system can considerably improve the vehicle’s path tracking under uncertainties.
1

53
61


Mohammad Amin
Saeedi
Department of Mechanical Engineering, Shahid Rajaee Teacher Training University, Tehran, Iran.
Department of Mechanical Engineering, Shahid
Iran
amin_saeedi@sru.ac.ir
Handling
Path Tracking
Sliding Mode Control
Uncertainty
[[1] Aga, M., Okada, A., Analysis of Vehicle Stability Control Effectiveness from Accident Data, ESV Conference, Nagoya, 2003. ##[2] Farmer, Ch., Effect of Electronic Stability Control on Automobile Crash Risk, IIHS Insurance Institute of Highway Safety, Arlington, Virginia, USA, 2004. ##[3] Park, K., Heo, S., and Baek, I., Controller Design for Improving Lateral Vehicle Dynamic Stability, Society of Automotive Engineers of japan, Vol. 22, 2001, pp. 481–486. ##[4] Ding, N., Taheri S., An Adaptive Integrated Algorithm for Active Front Steering and Direct Yaw Moment Control Based on Direct Lyapunov Method, Vehicle System Dynamics, Vol. 48, No. 10, 2010, pp. 1193–1213. ##[5] Saeedi, M. A., Kazemi, R., and Azadi, S., Analysis of Roll Control System to Eliminate Liquid Sloshing Effect on Lateral Stability of an Articulated Vehicle Carrying Liquid, International Journal of Engineering, Vol. 29, No. 3, 2016. ##[6] Saeedi, M. A., Kazemi, R., and Azadi, S., Improvement in The Rollover Stability of a LiquidCarrying Articulated Vehicle Via a New Robust Controller, Proc IMechE, Part D: Journal of Automobile Engineering, doi:10.1177/0954407016639204, 2015. ##[7] Shojaeefard, M. H., Talebitooti, R., and Yarmohammadi satri, S., Optimum Design of 1st Gear Ratio for 4WD Vehicles Based on Vehicle Dynamic Behaviour, Advances in Mechanical Engineering, 2013, pp. 19. ##[8] Talebitooti, R., Shojaeefard, M. H., and Yarmohammadi satri, S., Shape design Optimization of Cylindrical Tank Using BSpline Curves, Computer and Fluids, Vol. 109, 2015, pp. 100112. ##[9] Shojaeefard, M. H., Talebitooti, R., and Yarmohammadisatri, S., Optimizing Elliptical Tank Shape Based on RealCoded Genetic Algorithm, Int J of Advanced Design and Manufacturing Technology, Vol. 6, No. 4, 2013, pp. 2329. ##[10] Nam, K., Fujimoto, H., and Hori, Y., Advanced Motion Control of Electric Vehicles Based on Robust Lateral Tire Force Control Via Active Front Steering, IEEE/ASME Trans Mechatronics, Vol. 99, 2012, pp. l–11. ##[11] Kim, S. J., Kwak, B. H., Chung, S. J., and Kim, J. G., Development of an Active Front Steering System, Int. J. Automotive Technology, Vol. 7, No. 3, 2006, pp. 315320. ##[12] Guvenc, B. A., Guvenc, L., and Karaman, S., Robust Yaw Stability Controller Design and HardwareintheLoop Testing for a Road Vehicle, IEEE Trans Veh Technol, Vol. 58, 2009, pp. 555–571. ##[13] Zhang, J., Kim, J., Xuan, D., and Kim, Y., Design of Active Front Steering (AFS) System with QFT Control, Int J Comput Applic Technol, Vol. 41, No. 201, pp. 236–245. ##[14] El Nashar, H., Enhanced Vehicle Lateral Stability in Crosswind by Limited State Kalman Filter Four Wheel Steering System, SAE paper, 2007. ##[15] Saeedi, M. A., Kazemi, R., Stability of ThreeWheeled Vehicles with and without Control System, International Journal of Automotive Engineering, Vol. 3, No. 1, 2013, pp. 343355. ##[16] Saeedi, M. A., Kazemi, R., and Azadi, S., A New Robust Controller to improve the Lateral Dynamic of an Articulated Vehicle Carrying Liquid, Proc IMechE, Part K: Journal of Multibody Dynamics, doi:10.1177/1464419316663028, 2016. ##[17] Pacejka H., Tyre and Vehicle Dynamics, Oxford: ButterworthHeinemann, 2005. ##[18] Mechanical Simulation Corporation (MSC), CarSim 8.0 Reference Manual, February, 1999. ##[19] March, C., Shim, T., Integrated Control of Suspension and Front Steering to Enhance Vehicle Handling, Proc IMechE, Part D: Journal of Automobile Engineering, Vol. 221, 2007, pp. 377391. ##]
Effect of Aerodynamic Blade Change of TwoStage Axial Subsonic Turbine on Design Point
2
2
In this research for reducing the effect of losses and increasing the efficiency, the bowing in the rotor and stator blades is used. In one mode rotor blades are curved and in other one, stator blades are curved. The amount of rotor loss, due to changes in the thickness of the trailing edge and operating rotational speed, have been investigated. To confirm the accuracy of the results, a turbine stage whose experimental results are available is modeled and numerical results have been compared with experimental results that indicate acceptable compliance. The turbulence model kwSST is used to solve turbulent flow. The positive bowing, creates a pressure gradient from the two ends of the blade towards the center of the blade, which leads to the directing of the secondary flows toward the center of the blade. This reduces the losses in the two ends of the blade and increases the loss in the middle part of the blade. Increasing the thickness of the trailing edge, as well as increasing the turbine’s operating rotational speed, will increase the loss. The curved rotor increases the efficiency and mass flow and power by 0.4% and 0.5% and 0.8% respectively and the curved nozzle reduces the efficiency and power by 0.3% and 4.9% but increases the mass flow by 0.2%. It also increases the thickness of the trailing edge of the first rotor from 0.2mm to 0.9mm at 24000 rotational speed and increases the total loss by about 35%.
1

63
73


Mahmood
Adami
Department of Mechanical Engineering,
Malek Ashtar University of Technology, Iran
Department of Mechanical Engineering,
Malek
Iran
adami@mutes.ac.ir


Behrooz
Shahriari
Department of Mechanical Engineering,
Malek Ashtar University of Technology, Iran
Department of Mechanical Engineering,
Malek
Iran
shahriari@mutes.ac.ir


Ali
Zamani Gharaghoushi
Department of Mechanical Engineering,
Malek Ashtar University of Technology, Iran
Department of Mechanical Engineering,
Malek
Iran
alzghh@gmail.com
Aerodynamic Blade Changes
Axial Turbine
Blade Bowing
CFD
[[1] Karrabi,H., Rezasoltani, M., The Effect of Blade Lean, Twist and Bow on the Performance of Axial Turbine at Design Point, No. 54877, pp. 965972, 2011. ##[2] M. Deich, M., Gubarev, A., Filipov, G., and Wang, Z. C., A New Method of Profiling the Guide Vane Cascades of Turbine Stages with Small DiameterSpan Ratio, Teploenergetika, Vol. 8, pp. 4246, 1962. ##[3] Breugelmans, F. A. H., Carels, Y., and Demuth, M., Influence Of Dihedral on the Secondary Flow in a TwoDimensional Compressor Cascade, Journal of Engineering for Gas Turbines and Power, Vol. 106, No. 3, pp. 578584, 1984. ##[4] Shang, E., Wang, Z. Q., and Su, J. X., The Experimental Investigations on the Compressor Cascades With Leaned and Curved Blade, No. 78880, pp. V001T03A018, 1993. ##[5] Weingold, H. D., Neubert, R. J., Behlke, R. F., and Potter, G. E., Bowed Stators: An Example of CFD Applied to Improve Multistage Compressor Efficiency, Journal of Turbomachinery, Vol. 119, No. 2, pp. 161168, 1997. ##[6] Fischer, A., Riess, W., and Seume, J. R., Performance of Strongly Bowed Stators in a FourStage HighSpeed Compressor, Journal of Turbomachinery, Vol. 126, No. 3, pp. 333338, 2004. ##[7] Tan, C., Yamamoto, A., Mizuki, S., and Chen, H., Influences of Blade Bowing on FlowFields of Turbine Stator Cascades, AIAA Journal, Vol. 41, No. 10, pp. 19671972, 2003. ##[8] Tan, C., Yamamoto, A., Chen, H., and Mizuki, S., FlowField and Aerodynamic Performance of a Turbine Stator Cascade with Bowed Blades, AIAA Journal, Vol. 42, No. 10, pp. 21702171, 2004/10/01, 2004. ##[9] Tan, C Zhang, H. Chen, H., and Yamamoto, A., Blade Bowing Effect on Aerodynamic Performance of a Highly Loaded Turbine Cascade, Journal of Propulsion and Power, Vol. 26, No. 3, pp. 604608, 2010/05/01, 2010. ##[10] Schobeiri, M. T., Suryanarayanan, A., Jermann, C., and Neuenschwander, T., A Comparative Aerodynamic and Performance Study of a ThreeStage High Pressure Turbine With 3D Bowed Blades and Cylindrical Blades, No. 41707, pp. 12371246, 2004. ##[11] Hassan Vand, M., Wang, S., Numerical Study of the Effects of Bowed Blades on Aerodynamic Characteristics in a High Pressure Turbine, No. 47306, pp. 487496, 2005. ##[12] L. Chen, L., Liu, X. J., Yang, A. L., and Dai, R., Flow Performance of Highly Loaded Axial Fan with Bowed Rotor Blades, IOP Conference Series: Materials Science and Engineering, Vol. 52, No. 4, pp. 042005, 2013. ##[13] Koch,L. S. C., Loss Sources and Magnitude in Axial Flow Compressor, ASME J, pp. 354363, 1976. ##[14] Wisler, D. C., Loss Reduction in AxialFlow Compressors Through LowSpeed Model Testing, Journal of Engineering for Gas Turbines and Power, Vol. 107, No. 2, pp. 354363, 1985. ##[15] Zheng, X., Li, Z., BladeEnd Treatment to Improve the Performance of Axial Compressors: An Overview, 2016. ##[16] Ennil, A. B., AlDadah, R., Mahmoud, S., Rahbar, K., and AlJubori, A., Minimization of Loss in Small Scale Axial Air Turbine Using CFD Modeling and Evolutionary Algorithm Optimization, Applied Thermal Engineering, Vol. 102, pp. 841848, 2016/06/05/, 2016. ##[17] Freeman,C., Effect of Tip Clearance Flow on Compressor Stability and Engine Performance, 2018. ##[18] Bini, R., Colombo, D., Large Multistage Axial Turbines, Energy Procedia, Vol. 129, pp. 10781084, 2017/09/01/, 2017. ##[19] Lindquist Whitacker, L. H., Tomita, J. T., and Bringhenti, C., An Evaluation of the Tip Clearance Effects on Turbine Efficiency for Space Propulsion Applications Considering Liquid Rocket Engine Using Turbopumps, Aerospace Science and Technology, Vol. 70, pp. 5565, 2017/11/01/, 2017. ##[20] Majumdar, S., Role of Underrelaxation in Momentum Interpolation for Calculation of Flow with Nonstaggered Grids, Numerical Heat Transfer, Vol. 13, No. 1, pp. 125132, 1988/01/01, 1988. ##[21] Chima, R., Liou, M. S., Comparison of the AUSM+ and HCUSP Schemes for Turbomachinery Applications, Fluid Dynamics and CoLocated Conferences in: 16th AIAA Computational Fluid Dynamics Conference, Eds.: American Institute of Aeronautics and Astronautics, 2003. ##[22] Groschup, G., Strömungstechnische Untersuchung einer Axialturbinenstufe im Vergleich Zum Verhalten Der Ebenen Gitter Ihrer Beschaufelung: Dissertation, University of Hanover, 1977. ##[23] Zhongqi, L. S. W., Wenyuan, X., Aerodynamic Calculation of Turbine Stator Cascade with Curvilinear Leaned Blades and Some Experimental Results, in 5th International Symposium on Air Breathing Engine, 1981. ##[24] Wang, S., Wang, Z., and Feng, G., Numerical Simulation of 3D Flow Field Structure in Turbine Cascade With Bowed Blades, No. 78507, pp. V001T03A064, 2001. ##]
Determination of Material Properties Components used in FEM Modeling of Ultrasonic Piezoelectric Transducer
2
2
Ultrasonic transducers have found new applications such as ultrasonic assisted micromachining, micro forming, surface treatment, welding, etc. Apart from the transducer’s shape and size, the resonant frequencies and amplitude are seriously affected by materials properties used for transducer components. A further problem with the material is that their properties may vary from batch to batch and may also depend on the size of the raw stock. In this work using modal analysis, the material properties are calculated based on the frequency response method, which is more accurate than the nominal one. The finite element modelling was employed for both 2D and 3D FEM analysis to observe the behaviour of the cylindrical test rods and two sandwichtype piezoelectric transducers with the nominal frequency of 20 kHz and 30 kHz to find the validity of these properties. The obtained results showed that the modal analysis method could accurately determine the bar speed, Poisson's ratio and elastic modulus of the ultrasonic transducer components. The accuracy of this method increases by considering more vibration mode. Based on the results, obtained errors for FEM modelling of two ultrasonic transducers with the frequency of 20 kHz and 30 kHz are 0.15% and 0.33%, respectively.
1

75
81


Abbas
Pak
Department of Mechanical Engineering,
University of BuAli Sina, Iran
Department of Mechanical Engineering,
University
Iran
a.pak@basu.ac.ir
FEM Modeling
Modal Analysis
Ultrasonic Transducer
Young’s Modulus
[[1] Frederick, R., Ultrasonic Engineering, John Wiley and Sons, New York, USA, 1965. ##[2] Kumar, S., Wu, C. S., Padhy, G. K., and Ding, W., Application of Ultrasonic Vibrations in Welding and Metal Processing: A Status Review, Journal of Manufacturing Processes, Vol. 26, 2017, pp. 295322. ##[3] Langevin, P., French Patent, Application No. FR575435D filed 27, December 1923. ##[4] Mason, W. P., Electromechanical Transducers and Wave Filters, Van Nostrand, New York, USA, 1942. ##[5] Krimholtz, R., Leedom, D. A., and Mattaei, G. L., New Equivalent Circuits for Elementary Piezoelectric Transducer, Electron, Vol. 6, 1970, pp. 398–399. ##[6] Redwood, M., Experiments With the Electrical Analog of a Piezoelectric Transducer, Journal of the Acoustical Society of America, Vol. 36, No. 1, 1964, pp. 1872–1880. ##[7] AlBudairi, H., Lucas, M., and Harkness, P., A Design Approach for Longitudinal–Torsional Ultrasonic Transducers, Sensors and Actuators A: Physical, Vol. 198, 2013, pp. 99106. ##[8] Kagawa, Y., Yamabuchi, T., Finite Element Simulation of a Composite Piezoelectric Ultrasonic Transducer, IEEE Transactions on Sonics and Ultrasonics, Vol. 26, No. 2, 1979, pp. 81 – 87. ##[9] Jian, S. W., Dale, F. O., A Finite ElementElectric Circuit Coupled Simulation Method for Piezoelectric Transducer, IEEE Ultrasonics Symposium, Caesars Tahoe, NV, USA, 1999, pp. 1105 – 1108. ##[10] Cunningham, P. M., Use of the Finite Element Method in Ultrasonic Applications, Ultrasonic Industry Association Symposium, Ohio, USA, 2000. ##[11] Kocbach, J., Finite Element Modeling of Ultrasonic Piezoelectric Transducers Influence of Geometry and Material Parameters on Vibration, Response Functions and Radiated Field, Ph.D. dissertation, Department of Physics, University of Bergen, Bergen, 2000. ##[12] Moreno, E., Acevedo, P.,. Fuentes, M., Sotomayor, A. Borroto, L., Villafuerte, M. E., and Leija, L., Design and Construction of a BoltClamped Langevin Transducer, 2nd International Conference on Electrical and Electronics Engineering, Mexico City, Mexico, 2005, pp. 393 – 395. ##[13] A. I. Fernando, M. Pappalardo, and J. Gallego, Finite Element ThreeDimensional Analysis of the Vibrational Behavior of the LangevinType Transducer, Ultrasonics, Vol. 40, 2002, pp. 513517. ##[14] Abdullah, A., Pak, A., Correct Prediction of the Vibration Behavior of a High Power Ultrasonic Transducer by FEM Simulation, The International Journal of Advanced Manufacturing Technology, Vol. 39, 2008, pp. 21–28. ##[15] Abdullah, A., Pak, A., Abdullah, M. M, Shahidi, A., and Malaki, M., Study of the Behavior of Ultrasonic PiezoCeramic Actuators by Simulations, Electronic Materials Letters, Vol. 10, No. 1, 2014, pp. 3742. ##[16] Culp., D. R., Ultrasonic Resonator Design Using Finite Element Analysis, Available, 2002: http://www.krellengineering.com/fea/fea_info/fea_resonator_design.htm#FEA%20Procedure, [2002]. ##[17] Lundberg, B., Blanc, R. H., Determination of Mechanical Material Properties From the TwoPoint Response of an Impacted Linearly Viscoelastic Rod Specimen, Journal of Sound and Vibration, Vol. 126, No. 1, 1988, pp. 97108. ##[18] Hillstrom, L., Mossberg, M., and Lundberg, B., Identification of Complex Modulus From Measured Strains on an Axially Impacted Bar Using Least Squares., Journal of Sound and Vibration, Vol. 230, No. 3, 2000, pp. 689707. ##[19] Mousavi, S., Nicolas, D. F., and Lundberg, B., Identification of Complex Moduli and Poisson's ratio From Measured Strains on an Impacted Bar, Journal of Sound and Vibration, Vol. 277, No. 4–5, 2004, pp. 971986. ##[20] Mousavi, S., Hillström, L., and Lundberg, B., Identification of Complex Shear Modulus From Measured Shear Strains on a Circular Disc Subjected to Transient Torsion at Its Centre, Journal of Sound and Vibration, Vol. 313, No. 35, 2008, pp. 567580. ##[21] Graff, K. F., Wave Motion in Elastic Solids, London, UK, Oxford University Press, 1975. ##[22] Hen, S., Resonant Frequency Method for the Measurement and Uncertainty Analysis of Acoustic and Elastic Properties, Ultrasonics, Vol. 38, 2000, pp. 206–221. ##[23] TAMURA Co., Piezoelectric Ceramics for High Power Applications Data Sheet, Available: https://www.tamurass.co.jp, 2017. ##]
Fatigue Crack Growth in ThinWall Pipes Subjected to Bending
2
2
In this paper, a circumferential external surface flaw in a metallic round pipe under cyclic bending loading is considered. Because of very rapid changes in the geometrical parameters around the crack front region, the mesh generation of this region must be done with great care. The analysis of the fatigue crack growth is done in accordance with Paris law. The spread lane of the exterior defect is achieved from the graph of “α” vs. “relative crack depth”. The growth of fatigue crack is also analyzed (the comparative crack depth against loading runs diagram) with various initial crack “α” beneath periodic loading. Fatigue shape growth of primarily semielliptical peripheral surface flaws is shown. The weight of the Paris exponent (material constant) on fatigue crack propagation is presented as well. Furthermore, the “fatigue crack growth” progression of several specimens is evaluated experimentally by employing a manuallyconstructed experimental setup. Conclusively, the experimental results achieved by periodic bending loading tests are compared with the numerical results. Fatigue shape development of initially semielliptical external surface defects is illustrated. The effect of the Paris exponent (material constant) on fatigue crack propagation is shown as well. Moreover, the fatigue crack growth of several specimens is assessed experimentally using a manuallyconstructed experimental set up. Finally, the experimental results obtained by cyclic bending loading tests are compared.
1

83
90


MohammadMahdi
Amiri
Department of Engineering,
Research Institute of Petroleum Industry
Department of Engineering,
Research Institute
Iran
amirimm@ripi.ir
Fatigue Crack Growth
K (Stress Intensity Factor)
SemiElliptical Crack
ThinWall Pipes
[[1] Shahani, A. R., Habibi S. E., Stress Intensity Factors in Hollow Cylinder Containing a Circumferential SemiElliptical Crack Subjected to Combined Loading, International Journal of Fatigue, Vol. 291, No. 1, 2007, pp. 128–140. doi: 10.1016/j.ijfatigue.2006.01.017. ##[2] Lin X. B., Smith, R. A., Fatigue Growth Prediction of Internal Surface Cracks in Pressure Vessels, International Journal od Press Vessel Technology. Vol. 120, No. 1, 1998, pp. 17–23, doi:10.1115/1.2841878. ##[3] Underwood J., Stress Intensity Factor for Internally Pressurized ThickWalled Cylinders: Stress Analysis Growth Cracks, ASTM STP, Vol. 513, 1972, pp. 59–70. ##[4] Raju, I. S., Newman, J. C., StressIntensity Factor for Internal and External Surface Cracks in Cylindrical Vessels, International Journal of Press Vessel Technology., Vol. 104, No. l, 1982, pp. 293–298. ##[5] Couroneau, N., Royer, J., Simplified Model for the Fatigue Growth Analysis of Surface Cracks in Round Bars Under Mode I, International Journal of Fatigue, Vol. 20, No. 10, 2010, pp. 711–718, doi:10.1016/S01421123(98)000371. ##[6] Carpinteri, A., Brighenti R., A ThreeParameter Model for Fatigue Behavior of Circumferential Surface Flaws in Pipes, International Journal of Mechanical Science, Vol. 42, No. 7, 2000, pp. 1255–1269, doi:10.1016/S00207403(99)000831 ##[7] Pook, L. P., On Fatigue Crack Paths, International Journal of Fatigue, Vol. 17, No. 1, 1995, pp. 5–13, doi:10.1016/01421123(95)930454. ##[8] Carpinteri, A., Brighenti, R., and Spagnoli, A., PartThrough Cracks in Pipes Under Cyclic Bending, Nuclear Engineering and Design., Vol. 185, No. 1, 1998, pp. 1–10, doi:10.1016/S00295493(98)001897. ##[9] Bergman, M., Stress Intensity Factors for Circumferential Surface Cracks in Pipes, Fatigue & Fracture of Engineering Materials & Structures, Vol. 18, No. 10, 1995, pp. 1155–1172. doi:10.1111/j.14602695. 1995.tb00845. x. ##[10] Peng. D., Wallbrink, C., and Jones, R., An Assessment of Stress Intensity Factors for Surface Flaws in a Tubular Member, Engineering Fracture Mechanics, Vol. 72, No. 3, 2005, pp. 357–371. doi: 10.1016/j.engfracmech.2004.04.001.##]
Comparison of Neural Networks and Fuzzy System for Estimation of Heat Transfer Between Contacting Surfaces
2
2
Neural networks can be used in various subjects, such as the discovery of relationships, identification, system modelling, optimization and nonlinear pattern recognition. One of the interesting applications of this algorithm is heat transfer estimation between contacting surfaces. In the current investigation, a comparison study is done for temperature transfer function estimation between contacting surfaces using Group Method of Data Handling (GMDH) neural networks and ANFIS (Adaptive Neuro Fuzzy Inference System) algorithm. Different algorithms are trained and tested by means of input–output data set taken from the experimental study and the inverse solution using the Conjugate Gradient Method (CGM) with the adjoint problem. Eventually, the optimal model has been chosen based on the common error criteria of root mean square error. According to the obtained results among different models, ANFIS with gaussmf membership function has the best algorithm for identification of TCC between two contacting surfaces with 0.1283 error. Also, the inverse method has the lowest error for thermal contact conductance estimation between fixed contacting surfaces with root mean square error of 0.211.
1

91
101


Shayan
Fathi
Department of Mechanical Engineering,
Central Tehran Branch, Islamic Azad University,
Tehran, Iran
Department of Mechanical Engineering,
Central
Iran
fathiphd@gmail.com


Mohamad
Eftekhari Yazdi
Department of Mechanical Engineering,
Central Tehran Branch, Islamic Azad University,
Tehran, Iran
Department of Mechanical Engineering,
Central
Iran
moh.eftekhari_yazdi@iauctb.ac.ir


Arman
Adamian
Department of Mechanical Engineering,
Central Tehran Branch, Islamic Azad University,
Tehran, Iran
Department of Mechanical Engineering,
Central
Iran
arm.adamian@iauctb.ac.ir
ANFIS
Electronic Chipset
Neural Networks
Thermal Contact Conductance (TCC)
[[1] Minges, M. L., Thermal Contact Resistance, WrightPatterson Air Force Base, A Review of the Literature, Technical Report, 1, AFMLTR65375, Dayton, Ohio, USA, 1966. ##[2] Moore, C. J., Heat Transfer Across Surfaces, Ph.D. Dissertation, Southern Methodist University, Dallas, Texas, USA, 1967. ##[3] Moore, C. J., Atkins, H., and Blum, H. 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L., Wu, Q. K., and Gu, S. D., An Experimental Investigation of Thermal Contact Conductance of Hastelloy C276 Based on SteadyState Heat Flux Method, International Communication of Heat Mass Transfer, Vol. 41, No. 3, 2013, pp. 63–67. ##[11] Dongmei, B., Huanxin, C., and Ye. T., Influences of Temperature and Contact Pressure on Thermal Contact Resistance at Interfaces at Cryogenic Temperatures, Cryogenics, Vol. 52, No. 9, 2012, pp. 403409. ##[12] Sunil Kumar, S., Abilash, P. M., and Ramamurthi, K., Thermal Contact Conductance for Cylindrical and Spherical Contacts, Heat and Mass Transfer, Vol. 40, No. 9, 2004, pp. 679688, DOI: 10.1007/s0023100304330. ##[13] Surya K., Tariq, A., Steady State Experimental Investigation of Thermal Contact Conductance Between Curvilinear Contacts Using Liquid Crystal Thermography, International Journal of Thermal Sciences, Vol. 6, No. 118, 2017, pp. 5368. ##[14] McGee, G. R., Schankula, M. H., and Yovanovich, M. M., Thermal Resistance of CylinderFlat Contacts: Theoretical Analysis and Experimental Verification of a LineContact Model, Nuclear Engineering and Design, Vol. 86, No. 3, 1985, pp. 369381. ##[15] Asif, M., Tariq, A., Correlations of Thermal Contact Conductance for Nominally Flat Metallic Contact in Vacuum, Experimental Heat Transfer, A Journal of Thermal Energy Generation, Transport, Storage, and Conversion, Vol. 29, No. 4, 2016. ##[16] Bahrami, M., Modeling of Thermal Joint Resistance for SphereFlat Contacts in a Vacuum, A Thesis Presented to the University of Waterloo in Fulfillment of the Thesis Requirement for the Degree of Doctor of Philosophy, 2004. ##[17] Astrom, K. J., Eykhoff, P., System Identification, A Survey, Automatica, Vol. 7, No. 3, 1971, pp. 123126. ##[18] Shojaeefard, M. H., Ghaffarpour, M., and Noorpoor, A. R., Thermal Contact Analysis Using Identification Method, Heat Transfer Engineering, Vol. 29, No. 1, 2008, pp. 85–96. ##[19] Goudarzi, K., Moosaei, A., and Gharaati, M., Applying Artificial Neural Networks (ANN) to the Estimation of Thermal Contact Conductance in the Exhaust Valve of Internal Combustion Engine, Applied Thermal Engineering, Vol. 3, No. 87, 2015, pp. 688697. ##[20] MotahariNezhad, M., Mazidi, S. M., An Adaptive NeuroFuzzy Inference System (ANFIS) Model for Prediction of Thermal Contact Conductance Between Exhaust Valve and Its Seat, Applied Thermal Engineering, V. 105, No. 25, 2016, pp. 613621. ##[21] Koza, J., Genetic Programming, On the Programming of Computers by means of Natural Selection, MIT Press, 1992. ##[22] Iba, H., Kuita, T., Degaris, H., and Sator, T., System Identification Using Structured Genetic Algorithms, Proceeding of 5th International Conference on Genetic Algorithms, ICGA’93, USA, 1993. ##[23] Porter, B., NarimanZadeh, N., Genetic Design of ComputedTorque Controllers for Robotic Manipulators, IASTED International Conference on Systems and Control., Switzerland, 1994. ##[24] Ozisik, M. N., Orlande, H. R. B., Inverse Heat Transfer: Fundamentals and Applications, First ed, New York, 352 pages, 2000. ##[25] Alifanov, O. M., Inverse Heat Transfer Problems, SpringerVerlag, Berlin, 1994, pp. 348. ##[26] Beck, J.V., Blackwell, B., Clair, and C. R. St, Inverse Heat Conduction: Ill Posed Problems, Wiley, New York, 1985, pp. 308. ##[27] Shojaefard, M. H., Ghaffarpour, M., and Noorpoor, A. R., Thermal Contact Analysis Using Identification Method, Heat Transfer Engineering, Vol. 29, No. 1, 2011, pp. 8596. ##[28] Kartalopoulos, S. V., Understanding Neural Networks and Fuzzy LogicBasic Concepts and Applications, IEEE Neural Networks Council, Prentice Hall, NewDelhi, 2000. ##[29] Kondo, T., Ueno, J., MultiLayered GMDHType Neural Network SelfSelecting Optimum Neural Network Architecture and Its Application to 3Dimensional Medical Image Recognition of Blood Vessels, International Journal of Innovative Computing, Information and Control, Vol. 4, No.1, 2008, pp.175187. ##[30] Kondo, T., Ueno, J., Logistic GMDHType Neural Network and Its Application to Identification of XRay Film Characteristic Curve, Journal of Advanced Computational Intelligence an Intelligent Informatics, Vol. 11, No. 3, 2007, pp. 312318. ##[31] Kondo, T., GMDH Neural Network Algorithm Using the Heuristic SelfOrganization Method and its Application to the Pattern Identification Problem, Proc. of the 37th SICE Annual Conference, Vol. 23, No. 6, 1998, pp.11431148. ##[32] Farlow, S. J., SelfOrganizing Methods in Modeling, GMDHType Algorithm, New York: Marcel Dekker Inc, 1984. ##[33] Ivakhnenko, A. G., Heuristic SelfOrganization in Problems of Engineering Cybernetics, Automatica, Vol. 6, No.2, 1970, pp. 207219. ##[34] Kondo, T., Pandya, A. S., and Zurada, J. M., GMDHType Neural Networks with a Feedback Loop and Their Application to Nonlinear System Identification, Smart Engineering System: Neural Networks, Fuzzy Logic, Evolutionary Programing, Data Mining, and Rough Sets, ASME Press, Vol. 5, No. 9, 1999, pp.117124. ##[35] Dolenko, S. A., Orlov, Y. V., and Persiantsev, I. G., Practical Implementation and Use of Group Method of Data Handling (GMDH): Prospects and Problems, Proceedings of the ACEDC’96, University of Plymouth, UK, 1996. ##[36] Ivakhnenko, A. G., Polynomial Theory of Complex Systems, IEEE Transaction on System, Man and Cybernetics, Vol. 1, No. 3, 1971, pp. 364–378. ##[37] NarimanZadeh, N., Darvizeh, A., Darvizeh, M., and Gharababaei, H., Modelling of Explosive Cutting Process of Plates Using GMDHType Neural Network and Singular Value Decomposition, Journal of Materials Processing Technology, Vol. 5, No. 128, 2002, pp. 80–87. ##[38] Ahmadi, M. H., Ahmadi, M. A., Mehrpooya, M., and Rosen, M. A., Using GMDH Neural Networks to Model the Power and Torque of a Stirling Engine, Sustainability, The 4th World Sustainability Forum, 2015, pp. 22432255, doi: 10.3390/su7022243. ##[39] Bagheri, A., NarimanZadeh, N., Siavash, A. S., and Khoobkar, A. R., GMDH Type Neural Networks and Their Application to the Identification of the Inverse Kinematic Equations of Robotic Manipulators, International Journal of Engineering, Vol. 18, No. 2, 2005, pp. 135143. ##[40] Iba, H., DeGaris, H., and Sato, T., A Numerical Approach to Genetic Programming for System Identification, Evolutionary Computation, Vol. 3, No. 4, 1996, pp. 417–452. ##[41] Sanchez, G., FraustoSolis, A., OjedaBustamante, J., Attribute Selection Impact on Linear and Nonlinear Regression Models for Crop Yield Prediction, The Scientific World Journal, Vol. 13, No. 6, 2014, pp. 110. doi:10.1155/2014/509429. ##[42] Elçiçek, H., Akdoğan, E., and Karagöz, S., The Use of Artificial Neural Network for Prediction of Dissolution Kinetics, Science World Journal, Vol. 4, No. 3, 2014, pp. 19, doi:10.1155/2014/194874. ##[43] Jang, J. S. R., Sun, C. T., Functional Equivalence Between Radial Basis Function Networks and Fuzzy Inference Systems, IEEE Transactions on Neural Networks, Vol. 4, No. 1, 1999, pp. 156–159. ##[44] Brown, M., Harris, C., NeuroFuzzy Adaptive Modeling and Control, New York: PrenticeHall, 1994. ##[45] MuYen Chen., A Hybrid ANFIS Model for Business Failure Prediction Utilizing Particle Swarm Optimization and Subtractive Clustering, Information Sciences, Vol. 22, No. 3, 2013, pp. 180–195. ##]
Micro Wire Electrical Discharge Machining of MEMS Structures with Optimized Dimensional Deviation
2
2
Metalbased microelectromechanical systems are widely used in applications such as microenergy harvesters, microheat exchangers and microelectromagnetic that require high strength and flexibility. In the fabrication of such systems, micro wire electrical discharge machining (MicroWEDM) is majorly used. This paper studies the effect of the MicroWEDM process parameters on the dimensional deviation of machined MEMS structures including microcantilevers and microbeams using the Taguchi method. Using optimal levels of the parameters including pulse duration (0.8 µs), cutting speed (8.4 mm/min), voltage (17 V) and wire tension (0.5 kg), the dimensional deviation is reduced about 8.65 times compared with the average of experiments results. The order of effect importance of the process parameters on the dimensional deviation of microstructures obtained by the ANOVA analysis of S/N ratios is as follows: pulse duration, wire tension, process voltage and cutting speed. Dimensional deviation of the microfeatures was reduced to 1 μm using the optimal levels of the process parameters.
1

103
109


Mohammad
Tahmasebipour
Faculty of New Sciences and Technologies,
University of Tehran, Tehran, Iran
Faculty of New Sciences and Technologies,
Iran
tahmasebipour@ut.ac.ir


Y.
Tahmasebipour
Micro/NanoFabrication Technologies Development Laboratory,
Faculty of New sciences & Technologies,
University of Tehran, Tehran, Iran
Micro/NanoFabrication Technologies Development
Iran
tahmasebipour@gmail.com


Ali
Vafaie
Faculty of New Sciences and Technologies,
University of Tehran, Tehran, Iran
Faculty of New Sciences and Technologies,
Universi
Iran
vafaie@ut.ac.ir
MEMS
Microbeam
Microcantilever
Micromachining
Micro Wire Electrical Discharge Machining
MicroWEDM
[[1] Wu, W. J., Chen, C. T., Lin, S. C., Kuo, C. L., Wang, Y. J., and Yeh, S. P., Comparison of the Piezoelectric Energy Harvesters with SiMEMS and MetalMEMS, Journal of Physics: Conference Series Vol. 557, No. 1, 2014, pp. 012027. ##[2] Vasilyev, N. V., Gosline, A. H., Veeramani, A., Wu, M. T., Schmitz, G. P., Chen, R. T., Arabagi, V., Del Nido, P. J., and Dupont, P. E., Tissue Removal Inside the Beating Heart Using a Robotically Delivered Metal MEMS Tool, The International Journal of Robotics Research, Vol. 34, No. 2, 2015, pp. 236247. ##[3] Uhlmann, E., Piltz, S., and Doll, U., Machining of Micro/Miniature Dies and Moulds by Electrical Discharge Machining—Recent Development, Journal of Materials Processing Technology, Vol. 167, No. 2, 2005, pp. 488493. ##[4] Cao, D. M., Jiang, J., Meng, W. J., Jiang, J. C., and Wang, W., Fabrication of HighAspectRatio Microscale Ta Mold Inserts with Micro Electrical Discharge Machining, Microsystem Technologies, Vol. 13, No. 56, 2007, pp. 503510. ##[5] Wang, Y. K., Chen, X., Zhu, B., and Wang, Z. L., MicroChannel Mold Machined by Ultrafine WEDM, Advanced Materials Research, Vol. 1049, 2014, pp. 10261029, Trans Tech Publications. ##[6] Ali, M. Y., Mustafizul Karim, A. N., Adesta, E. Y. T., Ismail, A. F., Abdullah, A. A., and Idris, M. N., Comparative Study of Conventional and Micro WEDM Based on Machining of Meso/Micro Sized Spur Gear, International Journal of Precision Engineering and Manufacturing, Vol. 11, No. 5, 2010, pp. 779784. ##[7] Liao, Y. S., Chen, S. T., Lin, C. S., and Chuang, T. J., Fabrication of High Aspect Ratio Microstructure Arrays by Micro Reverse wireEDM, Journal of Micromechanics and Microengineering, Vol. 15, No. 8, 2005, pp. 1547. ##[8] Song, M. C., Du, L. Q., Liu, C., Liu, J. S., and Liu, Y., Experimental Research on WEDM Machining for Metal Components with Micro/MesoScale, Key Engineering Materials, Vol. 609, 2014, pp. 15211525, Trans Tech Publications. ##[9] Chou, N., Byun, D., and Kim, S., MEMSBased Microelectrode Technologies Capable of Penetrating Neural Tissues, Biomedical Engineering Letters, Vol. 4, No. 2, 2014, pp. 109119. ##[10] Kuriachen, B., Somashekhar, K. P., and Mathew, J., Multiresponse Optimization of MicroWire Electrical Discharge Machining Process, The International Journal of Advanced Manufacturing Technology, Vol. 76, No. 14, 2015, pp. 91104. ##[11] Somashekhar, K. P., Ramachandran, N., and Mathew, J., Modeling and Optimization of Process Parameters in Micro Wire EDM by Genetic Algorithm, Advanced Materials Research, Vol. 76, 2009, pp. 566570. ##[12] Somashekhar, K. P., Mathew, J., and Ramachandran, N., A Feasibility Approach by Simulated Annealing on Optimization of MicroWire Electric Discharge Machining Parameters, The International Journal of Advanced Manufacturing Technology, Vol. 61, No. 9, 2012, pp. 1209–1213. ##[13] Rakwal, D., Heamawatanachai, S., Tathireddy, P., Solzbacher, F., and Bamberg, E., Fabrication of Compliant High Aspect Ratio Silicon Microelectrode Arrays Using MicroWire Electrical Discharge Machining, Microsystem Technologies, Vol. 15 No. 5, 2009, pp. 789–797. ##[14] Schoth, A., forster, R., and Menz, W., Micro Wire EDM for High Aspect Ratio 3D Microstructuring of Ceramics and Metals, Microsystem Technologies, Vol. 11, No. 4, 2005, pp. 250253. ##[15] Di, S., Chu, X., Wei, D., Wang, Z., Chi, G., and Liu, Y., Analysis of Kerf Width in MicroWEDM, International Journal of Machine Tools and Manufacture, Vol. 49, No. 10, 2009, pp. 788–792. ##[16] Sivaprakasam, P., Hariharan, P., and Gowri, S., Modeling and Analysis of MicroWEDM Process of Titanium Alloy (Tie6Ale4V) Using Response Surface Approach, Engineering Science and Technology, An International Journal, Vol. 17, No. 4, 2014, pp. 227235. ##[17] Allen, P., Chen, X., Process Simulation of Micro ElectroDischarge Machining on Molybdenum, Journal of Materials Processing Technology, Vol. 186, No. 13, 2007, pp. 346–355. ##[18] Zhenlong, W., Xuesong, G., Guanxin C., and Yukui, W., Surface Integrity Associated with SiC/Al Particulate Composite by MicroWire Electrical Discharge Machining, Materials and Manufacturing Processes, Vol. 29, No. 5, 2014, pp. 532539. ##[19] Gupta, K., Jain, N. K., On MicroGeometry of Miniature Gears Manufactured by Wire Electrical Discharge Machining, Materials and Manufacturing Processes, Vol. 28, No. 10, 2013, pp. 11531159. ##[20] Ali, M. Y., Mohammad, A. S., Experimental Study of Conventional Wire Electrical Discharge Machining for Microfabrication, Materials and Manufacturing Processes, Vol. 23, No. 7, 2008, pp. 641645. ##[21] Hoang, K. T., Yang, S. H., Kerf Analysis and Control in Dry MicroWire Electrical Discharge Machining, The International Journal of Advanced Manufacturing Technologies, Vol. 78 No. 9, 2015, pp. 18031812. ##[22] Santhanakumar, M., Adalarasan, R., and Rajmohan, M., Application of Desirability Analysis for Optimizing the Micro Wire Electrical Discharge Machining (µWEDM) Parameters, Applied Mechanics and Materials, Vol. 592, 2014, pp. 7781. ##]
Implementation of the QuasiBrittle Damage Model for 2024 Aluminum Alloy under Periodic Loading
2
2
Damage mechanics is one of the most important parts of mechanical engineering that determines the time life for different mechanical elements. The most various models that have been provided so far in damage mechanics, are related to ductile or brittle damage. Nowadays, the investigation of materials by ductilebrittle damage behavior has been considered by researchers. Kintzel quasibrittle damage model is one of the best damage models in this field. Therefore, in this paper, due to the application of 2024 Al alloy in different industries especially aerospace and the ductilebrittle damage behavior of this alloy, the implementation of the Kintzel quasibrittle damage model is presented. For this purpose, by writing an explicit user subroutine VUMAT in finite element software (ABAQUS), a test sample under periodic loading has been modeled. The results of this research showed that the complete failure occurs after the 12th cycle under a periodic loading. Also, 2024 Al alloy showed a good ultimate tensile strength (about 400 MPa) under periodic loading. The magnitude of ductile and brittle damage variables are 0.23 and 0.38, respectively.
1

111
118


Sadegh
Ghorbanhosseini
Department of Mechanical Engineering,
University of BuAli Sina, Hamedan, Iran
Department of Mechanical Engineering,
University
Iran
s.ghorbanhosseini68@gmail.com


saeed
yaghoubi
Department of Mechanical Engineering,
Islamic Azad University, Shush Branch, Khuzestan, Iran
Department of Mechanical Engineering,
Islamic
Iran
yaghoubisaeed@ymail.com
2024 Al Alloy
Damage Mechanism
Kintzel Damage Model
Periodic Loading
[[1] Chabanet, O., Steglich, D., Besson, J., Heitmann, V., Hellman, D., and Brocks, W., Predicting Crack Growth Resistance of Aluminium Sheets, Computational Materials Science, Vol. 26, 2003, pp. 1 12. ##[2] Kachanov, L. M., Time of the Rupture Process Under Creep Conditions, Nank SSR Otd Tech Nauk, Vol. 8, 1958, pp. 26 31. ##[3] Verhoosel C. V., Remmers J. J., Gutierrez M. A., and Deborst, R., Computational Homogenization for Adhesive and Cohesive Failure in Quasi‐Brittle Solids, International Journal for Numerical Methods in Engineering, Vol. 83, No. 89, 2010, pp. 11551179. ##[4] Lemaitre, J., Chaboche, J. L., Mechanics of Solid Materials, 2rd ed, Cambridge University Press, 1994. ##[5] Lemaitre, J., Desmorat, R., Engineering Damage Mechanics: Ductile, Creep, Fatigue and Brittle Failures, Springer Science & Business Media, 2005. ##[6] Lemaitre, J., A Course on Damage Mechanics, Springer Science & Business Media, 2012. ##[7] Gurson, A. L., Continuum Theory of Ductile Rupture by Void Nucleation and Growth: Part I—Yield Criteria and Flow Rules for Porous Ductile Media, Journal of Engineering Materials and Technology, Vol. 99, No. 1, 1977, pp. 215. ##[8] Tvergaard, V., Needleman, A., Analysis of the CupCone Fracture in a Round Tensile Bar, Acta Metallurgica, Vol. 32, No. 1, 1984, pp. 157169. ##[9] Rice, J. R., Tracey, D. M., On the Ductile Enlargement of Voids in Triaxial Stress Fields, Journal of the Mechanics and Physics of Solids, Vol. 17, No. 3, 1969, pp. 201217. ##[10] Quan, G., Heerens, J., and Brocks, W., Distribution Characteristics of Constituent Particles in Thick Plate of 2024 AlT351, Praktische Metallographie, Vol. 41, No. 6, 2004, pp. 304313. ##[11] Steglich, D., Brocks, W., Heerens, J., and Pardeon, T., Anisotropic Ductile Fracture of Al 2024 Alloys, Engineering Fracture Mechanics, Vol. 75, No. 12, 2008, pp. 36923706. ##[12] Vyshnevskyy, A., Khan, S., and Mosler, J., An Investigation on Low Cycle Lifetime of Al2024 Alloy, Key Engineering Materials, Vol. 417, 2010, pp. 289292. ##[13] Vyshnevskyy, A., Khan, S., and Mosler, J., Low Cycle Lifetime Assessment of Al2024 Alloy, International Journal of Fatigue, Vol. 32, No. 8, 2010, pp. 12701277. ##[14] Khan, S., Kintzel, O., and Mosler, J., Experimental and Numerical Lifetime Assessment of Al 2024 Sheet, International Journal of Fatigue, Vol. 37, 2012, pp. 112122. ##[15] Kintzel, O., Khan, S., and Mosler, J., A Novel Isotropic QuasiBrittle Damage Model Applied to LCF Analyses of Al2024, International Journal of Fatigue, Vol. 32, No. 12, 2010, pp. 19481959. ##[16] Kintzel, O., Mosler, J., A Coupled Isotropic ElastoPlastic Damage Model Based on Incremental Minimization Principles, Technische Mechanik, Vol. 30, No. 13, 2010, pp. 177184. ##[17] Berto, F., Lazzarin, P., Recent Developments in Brittle and QuasiBrittle Failure Assessment of Engineering Materials by Means of Local Approaches, Materials Science and Engineering, Vol. 75, 2014, pp. 148. ##[18] Ren, X., Zeng, S., and Li, J., A RateDependent Stochastic Damage–Plasticity Model for QuasiBrittle Materials, Computational Mechanics, Vol. 55, No. 2, 2015, pp. 267285. ##[19] Wang, Y., Waisman, H., From Diffuse Damage to Sharp Cohesive Cracks: A Coupled XFEM Framework for Failure Analysis of QuasiBrittle Materials, Computer Methods in Applied Mechanics and Engineering, Vol. 299, 2016, pp. 5789. ##[20] Riccardi, F., Kishta, E., and Richard, B., A StepbyStep Global CrackTracking Approach in EFEM Simulations of QuasiBrittle Materials, Engineering Fracture Mechanics, Vol. 170, 2017, pp. 4458. ##[21] Pereira, L. F., Weerheijm, J., and Sluys, L. J., A Numerical Study on Crack Branching in QuasiBrittle Materials with a New Effective RateDependent Nonlocal Damage Model, Engineering Fracture Mechanics, Vol. 182, 2017, pp. 689707. ##]