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Topology optimization without volume constraint – the new paradigm for lightweight design

Michał Nowak Aron Boguszewski
Bulletin of the Polish Academy of Sciences Technical Sciences | 2021 | 69 | 4 | e137732 | DOI: 10.24425/bpasts.2021.137732
Keywords topology optimization lightweight design biomimetic structural optimization
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Abstract

In the paper the new paradigm for structural optimization without volume constraint is presented. Since the problem of stiffest design (compliance minimization) has no solution without additional assumptions, usually the volume of the material in the design domain is limited. The biomimetic approach, based on trabecular bone remodeling phenomenon is used to eliminate the volume constraint from the topology optimization procedure. Instead of the volume constraint, the Lagrange multiplier is assumed to have a constant value during the whole optimization procedure. Well known MATLAB topology based optimization code, developed by Ole Sigmund, was used as a tool for the new approach testing. The code was modified and the comparison of the original and the modified optimization algorithm is also presented. With the use of the new optimization paradigm, it is possible to minimize the compliance by obtaining different topologies for different materials. It is also possible to obtain different topologies for different load magnitudes. Both features of the presented approach are crucial for the design of lightweight structures, allowing the actual weight of the structure to be minimized. The final volume is not assumed at the beginning of the optimization process (no material volume constraint), but depends on the material’s properties and the forces acting upon the structure. The cantilever beam example, the classical problem in topology optimization is used to illustrate the presented approach.
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Bibliography

  1.  W. Wang et al., “Space-time topology optimization for additive manufacturing”, Struct. Multidiscip. Optim., vol. 61, no. 1, pp. 1‒18, 2020, doi: 10.1007/s00158-019-02420-6.
  2.  Y. Saadlaoui, et al., “Topology optimization and additive manufacturing: Comparison of conception methods using industrial codes”, J. Manuf. Syst., vol. 43, pp. 178‒286, 2017, doi: 10.1016/j.jmsy.2017.03.006.
  3.  J. Zhu, et al., “A review of topology optimization for additive manufacturing: Status and challenges”, Chin. J. Aeronaut., vol. 34, no. 1, pp. 9‒110, 2021, doi: 10.1016/j.cja.2020.09.020.
  4.  O. Sigmund, “A 99 line topology optimization code written in Matlab”, Struct. Multidiscip. Optim., vol. 21, no. 2, pp. 120‒127, 2001, doi: 10.1007/s001580050176.
  5.  M. Bendsoe and O. Sigmund, Topology optimization. Theory, methods and applications, Berlin Heidelberg New York, Springer, 2003, doi: 10.1007/978-3-662-05086-6.
  6.  M. Bendsoe and N. Kikuchi, “Generating optimal topologies in structural design using a homogenization method”, Comput. Methods Appl. Mech. Eng., vol. 71, pp. 197‒224, 1988.
  7.  O. Sigmund and K. Maute, “Topology optimization approaches”, Struct. Multidiscip. Optim., vol. 48, pp. 1031‒1055, 2013, doi: 10.1007/ s00158‒013‒0978‒6.
  8.  Z. Ming and R. Fleury, “Fail-safe topology optimization”, Struct. Multidiscip. Optim., vol. 54, no. 5, pp. 1225‒1243, 2016, doi: 10.1007/ s00158-016-1507-1.
  9.  L. Krog et al., “Topology optimization of aircraft wing box ribs”, AIAA Paper, 10th AIAA/ISSMO Multidisciplinary Analysis and Optimization Conference, Albany, New York, 2004, doi: 10.2514/6.2004-4481.
  10.  Z. Luo et al., “A new procedure for aerodynamic missile designs using topological optimization approach of continuum structures”, Aerosp. Sci. Technol., vol. 10, pp. 364‒373, 2006, doi: 10.1016/j.ast.2005.12.006.
  11.  M. Zhou et al., “Industrial application of topology optimization for combined conductive and convective heat transfer problems”, Struct. Multidiscip. Optim., vol. 54, no 4, pp. 1045‒1060, 2016, doi: 10.1007/s00158-016-1433-2.
  12.  G. Allaire et al., “The homogenization method for topology optimization of structures: old and new”, Interdiscip. Inf. Sci., vol.25/2, pp. 75‒146, 2019, doi: 10.4036/iis.2019.B.01.
  13.  G. Allaire and R.V. Kohn, “Topology Optimization and Optimal Shape Design Using Homogenization”, Topology Design of Structures. NATO ASI Series – Series E: Applied Sciences, M. Bendsoe, C. Soares – eds., vol. 227, pp. 207‒218, 1993, doi: 10.1007/978-94-011- 1804-0_14.
  14.  G. Allaire et al., ”Shape optimization by the homogenization method”, Numer. Math., vol. 76, no. 1, pp. 27‒68, 1997, doi: 10.1007/ s002110050253.
  15.  G. Allaire, Shape Optimization by the Homogenization Method, Springer, 2002, doi: 10.1007/978-1-4684-9286-6.
  16.  J. Wolff, “The Classic: On the Inner Architecture of Bones and its Importance for Bone Growth”, Clin. Orthop. Rel. Res., vol. 468, no. 4, pp. 1056‒1065, 2010, doi: 10.1007/s11999-010-1239-2.
  17.  H. M. Frost, The Laws of Bone Structure, C.C. Thomas, Springfield, 1964.
  18.  R. Huiskes et al., ”Adaptive bone-remodeling theory applied to prosthetic-design analysis”, J. Biomech., vol. 20, pp. 1135‒1150, 1987.
  19.  R. Huiskes, “If bone is the answer, then what is the question?”, J. Anat., vol. 197, no. 2, pp. 145‒156, 2000.
  20.  D.R. Carter, “Mechanical loading histories and cortical bone remodeling”, Calcif. Tissue Int., vol. 36, no. Suppl. 1, pp. 19‒24, 1984, doi: 10.1007/BF02406129.
  21.  R.F.M. van Oers, R. Ruimerman, E. Tanck, P.A.J. Hilbers, R. Huiskes, “A unified theory for osteonal and hemi-osteonal remodeling”, Bone, vol. 42, no. 2, pp. 250‒259, 2008, doi: 10.1016/j.bone.2007.10.009.
  22.  M. Nowak, J. Sokołowski, and A. Żochowski, “Justification of a certain algorithm for shape optimization in 3D elasticity”, Struct. Multidiscip. Optim., vol. 57, no. 2, pp. 721‒734, 2018, doi: 10.1007/s00158-017-1780-7.
  23.  M. Nowak, J. Sokołowski, and A. Żochowski, “Biomimetic approach to compliance optimization and multiple load cases”, J. Optim. Theory Appl., vol. 184, no. 1, pp. 210‒225, 2020, doi: 10.1007/s10957-019-01502-1.
  24.  J. Sokołowski and J-P. Zolesio, Introduction to Shape Optimization. Shape Sensitivity Analysis, Springer-Verlag, 1992, doi: 10.1007/978- 3-642-58106-9.
  25.  D. Gaweł et al., “New biomimetic approach to the aircraft wing structural design based on aeroelastic analysis”, Bull. Pol. Acad. Sci. Tech. Sci., vol. 65, no. 5, pp. 741‒750, 2017, doi: 10.1515/bpasts-2017-0080.
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Authors and Affiliations

Michał Nowak
1
ORCID: ORCID
Aron Boguszewski
1
  1. Poznan University of Technology, Division of Virtual Engineering, ul. Jana Pawła II 24, 60-965 Poznań, Poland

Design optimization for the weight reduction of 2-cylinder reciprocating compressor crankshaft

Ali Arshad Pengbo Cong Adham Awad Elsayed Elmenshawy Ilmārs Blumbergs
Archive of Mechanical Engineering | 2021 | vol. 68 | No 4 | 449-471 | DOI: 10.24425/ame.2021.139311
Keywords reciprocating compressor crankshaft optimization weight reduction topology optimization stress distribution crank web crankshaft lightweight design crack modeling modal analysis
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Abstract

This study aims to optimize the 2-cylinder in-line reciprocating compressor crankshaft. As the crankshaft is considered the "bulkiest" component of the reciprocating compressor, its weight reduction is the focus of current research for improved performance and lower cost. Therefore, achieving a lightweight crankshaft without compromising the mechanical properties is the core objective of this study. Computational analysis for the crankshaft design optimization was performed in the following steps: kinematic analysis, static analysis, fatigue analysis, topology analysis, and dynamic modal analysis. Material retention by employing topology optimization resulted in a significant amount of weight reduction. A weight reduction of approximately 13% of the original crankshaft was achieved. At the same time, design optimization results demonstrate improvement in the mechanical properties due to better stress concentration and distribution on the crankshaft. In addition, material retention would also contribute to the material cost reduction of the crankshaft. The exact 3D model of the optimized crankshaft with complete design features is the main outcome of this research. The optimization and stress analysis methodology developed in this study can be used in broader fields such as reciprocating compressors/engines, structures, piping, and aerospace industries.
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Bibliography

[1] Z.P. Mourelatos. A crankshaft system model for structural dynamic analysis of internal combustion engines. Computers & Structures, 79(20-21):2009–2027, 2001. doi: 10.1016/S0045-7949(01)00119-5.
[2] A.P. Druschitz, D.C. Fitzgerald, and I. Hoegfeldt. Lightweight crankshafts. SAE Technical Paper 2006-01-0016, 2006. doi: 10.4271/2006-01-0016.
[3] K. Mizoue, Y. Kawahito, and K. Mizogawa. Development of hollow crankshaft. Honda R&D Technical Review 2009, pages 243–245, 2009.
[4] I. Papadimitriou and K. Track. Lightweight potential of crankshafts with hollow design. MTZ Worldwide, 79:42–45, 2018. doi: 10.1007/s38313-017-0140-8.
[5] M. Roeper and S. Reinsch. Hydroforging: a new manufacturing technology for forged lightweight products of aluminum. Proceedings of the ASME 2005 International Mechanical Engineering Congress and Exposition. Manufacturing Engineering and Materials Handling, Parts A and B, pages 297-304. Orlando, Florida, USA, November 5–11, 2005. doi: 10.1115/IMECE2005-80424.
[6] J. Lampinen. Cam shape optimization by genetic algorithm. Computer-Aided Design, 35(8):727–737. doi: 10.1016/S0010-4485(03)00004-6.
[7] A. Albers, N. Leon, H. Aguayo, and T. Maier. Multi-objective system optimization of engine crankshafts using an integration approach. Proceedings of the ASME 2008 International Mechanical Engineering Congress and Exposition. Volume 14: New Developments in Simulation Methods and Software for Engineering Applications, pages 101–109. Boston, Massachusetts, USA. October 31–November 6, 2008. doi: 10.1115/IMECE2008-67447.
[8] J.P. Henry, J. Topolsky, and M. Abramczuk. Crankshaft durability prediction – a new 3-D approach. SAE Technical Paper 920087, 1992. doi: 10.4271/920087.
[9] M. Guagliano, A. Terranova, and L. Vergani. Theoretical and experimental study of the stress concentration factor in diesel engine crankshafts. Journal of Mechanical Design, 115(1):47–52, 1993. doi: 10.1115/1.2919323.
[10] A.C.C. Borges, L.C. Oliveira, and P.S. Neto. Stress distribution in a crankshaft crank using a geometrically restricted finite element model. SAE Technical Paper 2002-01-2183, 2002. doi: 10.4271/2002-01-2183.
[11] D. Taylor, W. Zhou, A.J. Ciepalowicz, and J. Devlukia. Mixed-mode fatigue from stress concentrations: an approach based on equivalent stress intensity. International Journal of Fatigue, 21(2):173–178, 1999. doi: 10.1016/S0142-1123(98)00066-8.
[12] W. Li, Q. Yan, and J. Xue. Analysis of a crankshaft fatigue failure. Engineering Failure Analysis, 55:13-9-147, 2015. doi: 10.1016/j.engfailanal.2015.05.013.
[13] R.M. Metkar, V.K. Sunnapwar, and S.D. Hiwase. Comparative evaluation of fatigue assessment techniques on a forged steel crankshaft of a single cylinder diesel engine. Proceedings of the ASME 2012 International Mechanical Engineering Congress and Exposition. Volume 3: Design, Materials and Manufacturing, Parts A, B, and C, pages 601–609. Houston, Texas, USA, November 9–15, 2012. doi: 10.1115/IMECE2012-85493.
[14] Y. Shi, L. Dong, H.Wang, G. Li, and S. Liu. Fatigue features study on the crankshaft material of 42CrMo steel using acoustic emission. Frontiers of Mechanical Engineering, 11(3):233–241, 2016. doi: 10.1007/s11465-016-0400-3.
[15] J. Yao and J. Zhang. A modal analysis for vehicle’s crankshaft. 2017 IEEE 3rd Information Technology and Mechatronics Engineering Conference, pages 300–303, 2017. doi: 10.1109/ITOEC.2017.8122303.
[16] A.S. Mendes, E. Kanpolat, and R. Rauschen. Crankcase and crankshaft coupled structural analysis based on hybrid dynamic simulation. SAE International Journal of Engines, 6(4):2044– 2053, 2013. doi: 10.4271/2013-01-9047.
[17] B. Yu, Q. Feng, and X. Yu. Dynamic simulation and stress analysis for reciprocating compressor crankshaft. Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science, 227(4):845–851, 2013. doi: 10.1177/0954406212453523.
[18] A. Arshad, S. Samarasinghe, M.A.F. Ameer, and A. Urbahs. A simplified design approach for high-speed wind tunnels. Part I: Table of inclination. Journal of Mechanical Science and Technology, 34(6):2455–2468, 2020. doi: 10.1007/s12206-020-0521-9.
[19] A. Arshad, S. Samarasinghe, and V. Kovalcuks. A simplified design approach for high-speed wind tunnels. Part-I.I: Optimized design of settling chamber and inlet nozzle. 2020 11th International Conference on Mechanical and Aerospace Engineering (ICMAE), pages 150–154, 2020. doi: 10.1109/ICMAE50897.2020.9178865.
[20] A. Arshad, M.A.F. Ameer, and O. Kovzels. A simplified design approach for high-speed wind tunnels. Part II: Diffuser optimization and complete duct design. Journal of Mechanical Science and Technology, 35(7):2949–2960, 2021. doi: 10.1007/s12206-021-0618-9.
[21] A. Arshad, N. Andrew, and I. Blumbergs. Computational study of noise reduction in CFM56-5B using core nozzle chevrons. 2020 11th International Conference on Mechanical and Aerospace Engineering (ICMAE), pages 162-167, 2020. doi: 10.1109/ICMAE50897.2020.9178891.
[22] A. Arshad, L.B. Rodrigues, and I.M. López. Design optimization and investigation of aerodynamic characteristics of low Reynolds number airfoils. International Journal of Aeronautical and Space Sciences, 22:751–764, 2021. doi: 10.1007/s42405-021-00362-2.
[23] A. Arshad, A.J. Kallungal and A.E.E.E. Elmenshawy. Stability analysis for a concept design of Vertical Take-Off and Landing (VTOL) Unmanned Aerial Vehicle (UAV). 2021 International Conference on Military Technologies (ICMT), pages 1–6, 2021. doi: 10.1109/ICMT52455.2021.9502764.
[24] RanTong official database for the ZW-0.8/10-16 reciprocating compressor specifications, online resources.
[25] F. Rodriges Minucci, A.A. dos Santos, and R.A. Lime e Silva. Comparison of multiaxial fatigue criteria to evaluate the life of crankshafts. Proceedings of the ASME 2010 International Mechanical Engineering Congress and Exposition. Volume 11: New Developments in Simulation Methods and Software for Engineering Applications; Safety Engineering, Risk Analysis and Reliability Methods; Transportation Systems, pages 775–784. Vancouver, British Columbia, Canada. November 12–18, 2010. doi: 10.1115/IMECE2010-39018.
[26] Y.F. Sun, H.B. Qiu, L. Gao, K. Lin, and X.Z. Chu. Stochastic response surface method based on weighted regression and its application to fatigue reliability analysis of crankshaft. Proceedings of the ASME 2009 International Mechanical Engineering Congress and Exposition. Volume 13: New Developments in Simulation Methods and Software for Engineering Applications; Safety Engineering, Risk Analysis and Reliability Methods; Transportation Systems, pages 263-268. Lake Buena Vista, Florida, USA. November 13–19, 2009. doi: 10.1115/IMECE2009-11095.
[27] Y. Gorash, T. Comlekci, and D.MacKenzie. Comparative study of FE-models and material data for fatigue life assessments of welded thin-walled cross-beam connections. Procedia Engineering, 133:420–432, 2015. doi: 10.1016/j.proeng.2015.12.612.
[28] C. Cevik and E. Kanpolat. Achieving optimum crankshaft design – I. SAE Technical Paper 2014-01-0930, 2014. doi: 10.4271/2014-01-0930.
[29] G. Mu, F.Wang, and X. Mi. Optimum design on structural parameters of reciprocating refrigeration compressor crankshaft. Proceedings of the 2016 International Congress on Computation Algorithms in Engineering, pages 281–286, 2016. doi: 10.12783/dtcse/iccae2016/7204.
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Authors and Affiliations

Ali Arshad
1
ORCID: ORCID
Pengbo Cong
2
Adham Awad Elsayed Elmenshawy
1
Ilmārs Blumbergs
1
ORCID: ORCID
  1. Institute of Aeronautics, Faculty of Mechanical Engineering, Transport and Aeronautics, Riga Technical University, Latvia
  2. Institute of Mechanics and Mechanical Engineering, Faculty of Mechanical Engineering, Transport and Aeronautics, Riga Technical University, Latvia

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