ISSN 2466-4677; e-ISSN 2466-4847
Journal Menu
Archive
Last Edition
INFLUENCE OF USING DISCRETE CROSS-SECTION VARIABLES FOR ALL TYPES OF TRUSS STRUCTURAL OPTIMIZATION WITH DYNAMIC CONSTRAINTS FOR BUCKLING
Authors:
Nenad Petrović1
, Nenad Kostić1, Nenad Marjanović1, Vesna Marjanović1
1Department of Mechanical Constructions and Mechanization, University of Kragujevac Faculty of Engineering, Kragujevac, Serbia
Received: 20.04.2018.
Accepted: 12.06.2018.
Available: 30.06.2018
Abstract:
The use of continuous variables for cross-sectional dimensions in truss structural optimization gives solutions with a large number of different cross sections with specific dimensions which in practice would be expensive, or impossible to create. Even slight variations from optimal sizes can result in unstable structures which do not meet constraint criteria. This paper shows the influence of the use of discrete cross section sizes in optimization and compares results to continuous variable counterparts. In order to achieve the most practically applicable design solutions, Euler buckling dynamic constraints are added to all models. A typical space truss model from literature, which use continuous variables, is compared to the discrete variable models under the same conditions. The example model is optimized for minimal weight using sizing and all possible combinations of shape and topology optimizations with sizing.
Keywords:
Structural optimization, sizing,shape, topology, truss, Eulerbuckling, genetic algorithm
References:
[1] K.S. Lee, Z.W. Geem, A new structural optimization method based on the harmony search algorithm. Computers & Structures, 82 (9-10), 2004: 781-798. https://doi.org/10.1016/j.compstruc.2004.01.002
[2] A. Kaveh, M. Ilchi Ghazaan, Hybridized optimization algorithms for design of trusses with multiple natural frequency constraints. Advances in Engineering Software, 79 (-), 2015: 137-147. https://doi.org/10.1016/j.advengsoft.2014.10.001
[3] A. Mortazavi, V. Toğan, Sizing and layout design of truss structures under dynamic and static constraints with an integrated particle swarm optimization algorithm. Applied Soft Computing, 51 (-), 2017: 239-252.
https://doi.org/10.1016/j.asoc.2016.11.032
[4] C.-Y. Wu, K.-Y. Tseng, Truss structure optimization using adaptive multi-population differential evolution. Structural and Multidisciplinary Optimization, 42 (4), 2010: 575-590. https://doi.org/10.1007/s00158-010-0507-9
[5] G. Bekdaş, S.M. Nigdeli, X.-S. Yang, Sizing optimization of truss structures using flower pollination algorithm. Applied Soft Computing, 37 (-), 2015: 322-331. https://doi.org/10.1016/j.asoc.2015.08.037
[6] N. Petrovic, N. Marjanovic, N. Kostic, M. Blagojevic, M. Matejic, S. Troha, Effects of introducing dynamic constraints for buckling to truss sizing optimization problems. FME Transaction, 46 (1), 2018: 117-123.
https://doi.org/10.5937/fmet1801117P
[7] N. Petrovic, N. Marjanovic, N. Kostic, M. Blagojevic, M. Matejic, Sizing Optimization of Parametrically Designed Trusses. 13th International Conference on Accomplishments in Mechanical and Industrial Engineering- “DEMI 2017”, 2017, Banja Luka, Bosnia and Herzegovina, pp.93-100.
[8] N. Petrović, N. Kostić, N. Marjanović, Comparison of Approaches to 10 Bar Truss Structural Optimization With Included Buckling Constraints. Applied Engineering Letters, 2 (3), 2017: 98-103.
[9] M.S. Gonçalves, R.H. Lopez, L.F.F. Miguel, Search group algorithm: A new metaheuristic method for the optimization of truss structures. Computers & Structures, 153 (-), 2015: 165-184. https://doi.org/10.1016/j.compstruc.2015.03.003
[10] O. Hasançebi, S.K. Azad, Adaptive dimensional search: A new metaheuristic algorithm for discrete truss sizing optimization. Computers & Structures, 154 (-), 2015: 1-16. https://doi.org/10.1016/j.compstruc.2015.03.014
[11] M.-Y. Cheng, D. Prayogo, Y.-W. Wu, M.M. Lukito, A Hybrid Harmony Search algorithm for discrete sizing optimization of truss structure. Automation in Construction, 69 (-), 2016: 21-33. https://doi.org/10.1016/j.autcon.2016.05.023
[12] N. Petrović, N. Kostić, N. Marjanović, Discrete Variable Truss Structural Optimization Using Buckling Dynamic Constraints. Machine Design, 10 (2), 2018: 51-56. https://doi.org/10.24867/MD.10.2018.2.51-5
[13] E.G. Shopova, N.G. Vaklieva-Bancheva, BASIC—A genetic algorithm for engineering problems solution. Computers & Chemical Engineering, 30 (8), 2006: 1293-1309. https://doi.org/10.1016/j.compchemeng.2006.03.003
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)
Volume 10
Number 3
September 2025
Last Edition
Volume 10
Number 3
September 2025
How to Cite
N. Petrović, N. Kostić, N. Marjanović, V. Marjanovic, Influence of Using Discrete Cross-Section Variables for All Types of Truss Structural Optimization with Dynamic Constraints for Buckling. Applied Engineering Letters, 3(2), 2018: 78–83.
https://doi.org/10.18485/aeletters.2018.3.2.5
More Citation Formats
Petrović, N., Kostić, N., Marjanović, N., & Marjanovic, V. (2018).Influence of Using Discrete Cross-Section Variables for All Types of Truss Structural Optimization with Dynamic Constraints for Buckling. Applied Engineering Letters, 3(2), 78–83. https://doi.org/10.18485/aeletters.2018.3.2.5
Nenad Petrović, et al. Influence of Using Discrete Cross-Section Variables for All Types of Truss Structural Optimization with Dynamic Constraints for Buckling. Applied Engineering Letters, vol. 3, no. 2, pp. 78–83, https://doi.org/10.18485/aeletters.2018.3.2.5.
Nenad Petrović, Nenad M Kostić, Nenad Marjanović, and Vesna Marjanovic. 2018. “Influence of Using Discrete Cross-Section Variables for All Types of Truss Structural Optimization with Dynamic Constraints for Buckling”. Applied Engineering Letters, 3 (2): 78–83. https://doi.org/10.18485/aeletters.2018.3.2.5.
Nenad Petrović, Kostić, N.M., Nenad Marjanović and Marjanovic, V. (2018). Influence of Using Discrete Cross-Section Variables for All Types of Truss Structural Optimization with Dynamic Constraints for Buckling. Applied Engineering Letters, 3(2), pp.78–83. doi: 10.18485/aeletters.2018.3.2.5.
Journal Menu
Archive
INFLUENCE OF USING DISCRETE CROSS-SECTION VARIABLES FOR ALL TYPES OF TRUSS STRUCTURAL OPTIMIZATION WITH DYNAMIC CONSTRAINTS FOR BUCKLING
Authors:
Nenad Petrović1
, Nenad Kostić1, Nenad Marjanović1, Vesna Marjanović1
1Department of Mechanical Constructions and Mechanization, University of Kragujevac Faculty of Engineering, Kragujevac, Serbia
Received: 20.04.2018.
Accepted: 12.06.2018.
Available: 30.06.2018
Abstract:
The use of continuous variables for cross-sectional dimensions in truss structural optimization gives solutions with a large number of different cross sections with specific dimensions which in practice would be expensive, or impossible to create. Even slight variations from optimal sizes can result in unstable structures which do not meet constraint criteria. This paper shows the influence of the use of discrete cross section sizes in optimization and compares results to continuous variable counterparts. In order to achieve the most practically applicable design solutions, Euler buckling dynamic constraints are added to all models. A typical space truss model from literature, which use continuous variables, is compared to the discrete variable models under the same conditions. The example model is optimized for minimal weight using sizing and all possible combinations of shape and topology optimizations with sizing.
Keywords:
Structural optimization, sizing,shape, topology, truss, Eulerbuckling, genetic algorithm
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)
Volume 10
Number 3
September 2025
Last Edition
Volume 10
Number 3
September 2025