Computer-Automated Design of Truss Systems Under Manufacturing Constraints

Yıl 2024, Cilt: 27 Sayı: 5, 1697 - 1707, 02.10.2024

Sedanur Balta Hakan Özbaşaran

https://doi.org/10.2339/politeknik.1243525

Öz

Computer-Automated Design is the process of design by computer and without human intervention. Studies on simultaneous size, shape, and topology optimization show that computer-aided design is poised to replace computer-aided design. Most studies presented on simultaneous size, shape, and topology optimization measure the performance of the proposed optimization method (or method improvement) with popular test problems. These test problems are designed using a number of simplifications to allow them to be solved in an acceptable time; and therefore they cannot represent real world problems. Moreover, in most of the mentioned problems, only structural constraints are considered and constructability constraints are neglected. Structural constraints are related to the material used (stress, strain, etc.) and the behavior of the structural system (node displacement, global buckling, etc.). On the other hand, constructability constraints are the constraints that are related to manufacturing, such as the absence of intersecting elements in the system and not connecting many elements to a node. In this study, the real computational load of computer-automated design of plane truss systems is discussed. What is meant by the expression “real computational load” here is the computational effort spent searching for near-optimal solutions to design problems, where there are no simplistic constraints that are not found in real-world problems, and where constructability constraints are taken into account as well as structural constraints. Numerical experiments were performed using a parameterless metaheuristic algorithm, which has been shown by previous studies to be suitable for the optimization of truss systems, and the results are discussed.

Anahtar Kelimeler

Automatic design, Truss system, Optimization, Metaheuristic, Constructability constraints

Kafes Sistemlerin İmalat Kısıtları Altında Bilgisayar ile Otomatik Tasarımı

Öz

Bilgisayar ile otomatik tasarım bir tasarımın bilgisayar tarafından ve insan müdahalesi olmadan gerçekleştirilmesidir. Eşzamanlı boyut, şekil ve topoloji optimizasyonu konusunda yapılan çalışmalar, bilgisayar ile otomatik tasarımın, bilgisayar destekli tasarımın yerini almaya hazırlandığını göstermektedir. Eşzamanlı boyut, şekil ve topoloji optimizasyonu konusunda sunulan çoğu çalışma, önerdiği optimizasyon yönteminin (veya yöntem iyileştirmesinin) performansını popüler test problemleri ile ölçmektedir. Bu test problemleri, kabul edilebilir sürelerde çözülebilmelerini mümkün kılmak amacıyla bir takım basitleştirmeler kullanılarak tasarlanmışlardır; ve bu sebeple gerçek dünya problemlerini temsil edememektedirler. Dahası, söz edilen problemlerin çoğunda sadece yapısal kısıtlar göz önünde bulundurulur ve yapım kısıtları ihmal edilir. Yapısal kısıtlar kullanılan malzeme (gerilme, şekil değiştirme vb.) ve taşıyıcı sistem davranışı (düğüm yer değiştirmesi, global burkulma vb.) ile ilgilidir. Yapım kısıtları ise sistemde kesişen elemanların bulunmaması ve bir düğüme çok sayıda elemanın bağlanmaması gibi sistemin imal edilmesini mümkün kılan kısıtlardır. Bu çalışmada düzlem kafes sistemlerin bilgisayar ile otomatik tasarımının gerçek hesaplama yükü tartışılmıştır. Burada “gerçek hesaplama yükü” ifadesi ile anlatılmak istenen, gerçek dünya problemlerinde olmayan basitleştirici kısıtların bulunmadığı ve yapısal kısıtların yanında yapım kısıtlarının da hesaba katıldığı tasarım problemlerine yakın-optimal çözümler aramak için harcanan işlem gücüdür. Kafes sistemlerin optimizasyonu için uygun olduğu daha önce yapılan çalışmalarla gösterilmiş parametresiz bir metasezgisel algoritma kullanılarak sayısal deneyler yapılmış ve sonuçlar tartışılmıştır.

Anahtar Kelimeler

Otomatik tasarım, Kafes sistem, Optimizasyon, Metasezgisel, Yapım kısıtları

Kaynakça

• [1] Kanno, Y., “Mixed-integer second-order cone programming for truss topology optimization with self-weight load and limitation on number of nodes”, IEEE International Conference on Industrial Engineering and Engineering Management, 2017-Decem:1009–1012, (2018).
• [2] Kanno, Y., “Robust truss topology optimization via semidefinite programming with complementarity constraints: a difference-of-convex programming approach”, Computational Optimization and Applications, 71(2):403–433, (2018).
• [3] Cui, H., An, H., and Huang, H., “Truss topology optimization considering local buckling constraints and restrictions on intersection and overlap of bar members”, Structural and Multidisciplinary Optimization, 58(2):575–594, (2018).
• [4] Shahabsafa, M., Fakhimi, R., Lei, W., He, S., Martins, J.R.R.A., Terlaky, T., and Zuluaga, L.F., “Truss topology design and sizing optimization with guaranteed kinematic stability”, Structural and Multidisciplinary Optimization, (2020).
• [5] Fairclough, H. and Gilbert, M., “Layout optimization of simplified trusses using mixed integer linear programming with runtime generation of constraints”, Structural and Multidisciplinary Optimization, 61(5):1977–1999, (2020).
• [6] Savsani, V.J., Tejani, G.G., and Patel, V.K., “Truss topology optimization with static and dynamic constraints using modified subpopulation teaching–learning-based optimization”, Engineering Optimization, 48(11):1990–2006, (2016).
• [7] Mortazavi, A. and Toğan, V., “Simultaneous size, shape, and topology optimization of truss structures using integrated particle swarm optimizer”, Structural and Multidisciplinary Optimization, 54(4):715–736, (2016).
• [8] Maheri, M.R., Askarian, M., and Shojaee, S., “Size and topology optimization of trusses using hybrid genetic-particle swarm algorithms”, Iranian Journal of Science and Technology - Transactions of Civil Engineering, 40(3):179–193, (2016).
• [9] Ahrari, A. and Deb, K., “An improved fully stressed design evolution strategy for layout optimization of truss structures”, Computers and Structures, 164:127–144, (2016).
• [10] Madah, H. and Amir, O., “Truss optimization with buckling considerations using geometrically nonlinear beam modeling”, Computers and Structures, 192:233–247, (2017).
• [11] Zhou, P., Du, J., and Lü, Z., “Interval analysis based robust truss optimization with continuous and discrete variables using mix-coded genetic algorithm”, Structural and Multidisciplinary Optimization, 56(2):353–370, (2017).
• [12] Kaveh, A. and Zolghadr, A., “Cyclical parthenogenesis algorithm for layout optimization of truss structures with frequency constraints”, Engineering Optimization, 49(8):1317–1334, (2017).
• [13] Ohsaki, M. and Hayashi, K., “Force density method for simultaneous optimization of geometry and topology of trusses”, Structural and Multidisciplinary Optimization, 56(5):1157–1168, (2017).
• [14] Assimi, H., Jamali, A., and Nariman-zadeh, N., “Sizing and topology optimization of truss structures using genetic programming”, Swarm and Evolutionary Computation, 37:90–103, (2017).
• [15] Chen, S. yan, Shui, X. fang, and Huang, H., “Improved genetic algorithm with two-level approximation using shape sensitivities for truss layout optimization”, Structural and Multidisciplinary Optimization, 55(4):1365–1382, (2017).
• [16] Mortazavi, A., Toğan, V., and Nuhoğlu, A., “Weight minimization of truss structures with sizing and layout variables using integrated particle swarm optimizer”, Journal of Civil Engineering and Management, 23(8):985–1001, (2017).
• [17] Savsani, V.J., Tejani, G.G., Patel, V.K., and Savsani, P., “Modified meta-heuristics using random mutation for truss topology optimization with static and dynamic constraints”, Journal of Computational Design and Engineering, 4(2):106–130, (2017).
• [18] Mortazavi, A. and Toğan, V., “Sizing and layout design of truss structures under dynamic and static constraints with an integrated particle swarm optimization algorithm”, Applied Soft Computing Journal, 51:239–252, (2017).
• [19] Kaveh, A. and Zolghadr, A., “Meta-heuristic methods for optimization of truss structures with vibration frequency constraints”, Acta Mechanica, 229(10):3971–3992, (2018).
• [20] Panagant, N. and Bureerat, S., “Truss topology, shape and sizing optimization by fully stressed design based on hybrid grey wolf optimization and adaptive differential evolution”, Engineering Optimization, 50(10):1645–1661, (2018).
• [21] Tejani, G.G., Savsani, V.J., Patel, V.K., and Savsani, P. V., “Size, shape, and topology optimization of planar and space trusses using mutation-based improved metaheuristics”, Journal of Computational Design and Engineering, 5(2):198–214, (2018).
• [22] Degertekin, S.O., Lamberti, L., and Ugur, I.B., “Sizing, layout and topology design optimization of truss structures using the Jaya algorithm”, Applied Soft Computing Journal, 70:903–928, (2018).
• [23] Yancang, L. and Zhen, Y., “Application of Improved Bat Algorithm in Truss Optimization”, KSCE Journal of Civil Engineering, 23(6):2636–2643, (2019).
• [24] Madah, H. and Amir, O., “Concurrent structural optimization of buckling-resistant trusses and their initial imperfections”, International Journal of Solids and Structures, 162(xxxx):244–258, (2019).
• [25] Degertekin, S.O., Lamberti, L., and Ugur, I.B., “Discrete sizing/layout/topology optimization of truss structures with an advanced Jaya algorithm”, Applied Soft Computing Journal, 79:363–390, (2019).
• [26] Tejani, G.G., Savsani, V.J., Bureerat, S., Patel, V.K., and Savsani, P., “Topology optimization of truss subjected to static and dynamic constraints by integrating simulated annealing into passing vehicle search algorithms”, Engineering with Computers, 35(2):499–517, (2019).
• [27] Techasen, T., Wansasueb, K., Panagant, N., Pholdee, N., and Bureerat, S., “Simultaneous topology, shape, and size optimization of trusses, taking account of uncertainties using multi-objective evolutionary algorithms”, Engineering with Computers, 35(2):721–740, (2019).
• [28] Assimi, H., Jamali, A., and Nariman-zadeh, N., “Multi-objective sizing and topology optimization of truss structures using genetic programming based on a new adaptive mutant operator”, Neural Computing and Applications, 31(10):5729–5749, (2019).
• [29] Kaveh, A. and Mahjoubi, S., “Hypotrochoid spiral optimization approach for sizing and layout optimization of truss structures with multiple frequency constraints”, Engineering with Computers, 35(4):1443–1462, (2019).
• [30] Weldeyesus, A.G., Gondzio, J., He, L., Gilbert, M., Shepherd, P., and Tyas, A., “Adaptive solution of truss layout optimization problems with global stability constraints”, Structural and Multidisciplinary Optimization, 60(5):2093–2111, (2019).
• [31] Weldeyesus, A.G., Gondzio, J., He, L., Gilbert, M., Shepherd, P., and Tyas, A., “Truss geometry and topology optimization with global stability constraints”, Structural and Multidisciplinary Optimization, 62(4):1721–1737, (2020).
• [32] Mortazavi, A., “A new fuzzy strategy for size and topology optimization of truss structures”, Applied Soft Computing Journal, 93:106412, (2020).
• [33] Mortazavi, A., “Size and layout optimization of truss structures with dynamic constraints using the interactive fuzzy search algorithm”, Engineering Optimization, 0(0):1–23, (2020).
• [34] Kumar, S., Tejani, G.G., Pholdee, N., and Bureerat, S., “Improved metaheuristics through migration-based search and an acceptance probability for truss optimization”, Asian Journal of Civil Engineering, 21(7):1217–1237, (2020).
• [35] Reintjes, C. and Lorenz, U., “Bridging mixed integer linear programming for truss topology optimization and additive manufacturing”, Springer US, ISBN 0123456789, 2020.
• [36] Kaveh, A. and Seddighian, M.R., “Simultaneously multi-material layout, and connectivity optimization of truss structures via an Enriched Firefly Algorithm”, Structures, 27(June):2217–2231, (2020).
• [37] Bouzouiki, M. El, Sedaghati, R., and Stiharu, I., “A non-uniform cellular automata framework for topology and sizing optimization of truss structures subjected to stress and displacement constraints”, Computers and Structures, 242:106394, (2021).
• [38] Lemonge, A.C.C., Carvalho, J.P.G., Hallak, P.H., and Vargas, D.E.C., “Multi-objective truss structural optimization considering natural frequencies of vibration and global stability”, Expert Systems with Applications, 165:113777, (2021).
• [39] Kawamura, H., Ohmori, H., and Kito, N., “Truss topology optimization by a modified genetic algorithm”, Structural and Multidisciplinary Optimization, 23(6):467–472, (2002).
• [40] Hamza, K., Mahmoud, H., and Saitou, K., “Design optimization of N-shaped roof trusses using reactive taboo search”, Applied Soft Computing Journal, 3(3):221–235, (2003).
• [41] Ohsaki, M. and Katoh, N., “Topology optimization of trusses with stress and local constraints on nodal stability and member intersection”, Structural and Multidisciplinary Optimization, 29(3):190–197, (2005).
• [42] Dominguez, A., Stiharu, I., and Sedaghati, R., “Practical design optimization of truss structures using the genetic algorithms”, Research in Engineering Design, 17(2):73–84, (2006).
• [43] Wang, H. and Ohmori, H., “Truss optimization using genetic algorithm, considering construction process”, International Journal of Space Structures, 25(4):205–215, (2010).
• [44] Frans, R. and Arfiadi, Y., “Sizing, shape, and topology optimizations of roof trusses using hybrid genetic algorithms”, Procedia Engineering, 95(Scescm):185–195, (2014).
• [45] Mela, K., “Resolving issues with member buckling in truss topology optimization using a mixed variable approach”, Structural and Multidisciplinary Optimization, 50(6):1037–1049, (2014).
• [46] Hooshmand, A. and Campbell, M.I., “Truss layout design and optimization using a generative synthesis approach”, Computers and Structures, 163:1–28, (2016).
• [47] Xiao, Z., Yang, Y., Xiao, R., Bai, Y., Song, C., and Wang, D., “Evaluation of topology-optimized lattice structures manufactured via selective laser melting”, Materials and Design, 143:27–37, (2018).
• [48] Venkata Rao, R., “Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems”, International Journal of Industrial Engineering Computations, 7(1):19–34, (2016).
• [49] Topping, B.H. V, “Shape Optimization of Skeletal Structures: A Review”, Journal of Structural Engineering, 109(8):1933-1951, (1983).
• [50] Gao, G., Liu, Z.Y., Li, Y. Bin, and Qiao, Y.F., “A new method to generate the ground structure in truss topology optimization”, Engineering Optimization, 49(2):235–251, (2017).
• [51] Deb, K. and Gulati, S., “Design of truss-structures for minimum weight using genetic algorithms”, Finite Elements in Analysis and Design, 37(5):447-465, (2001).