Optimal truss design based on an algorithm using optimality criteria

Taylor, John E.; Rossow, M. P.

doi:10.1016/0020-7683(77)90004-x

Cited by 24 publications

(13 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…negative compliance appears at the minimum of potential energy, compare e.g. Taylor and Rossow (1977)]. …”

Section: Reformulation Of Problemmentioning

confidence: 99%

See 1 more Smart Citation

Truss topology optimization including bar properties different for tension and compression

Achtziger

1996

Structural Optimization

View full text Add to dashboard Cite

The problem of optimum truss topology design based on the ground structure approach is considered. It is known that any minimum weight truss design (computed subject to equilibrium of forces and stress constraints with the same yield stresses for tension and compression) is -up to a scaling -the same as a minimum compliance truss design (subject to static equilibrium and a weight constraint). This relation is generalized to the case when different properties of the bars for tension and for compression additionally are taken into account. This situation particularly covers the case when a structure is optimized which consists of rigid (heavy) elements for bars under compression, and of (light) elements which are hardly/not able to carry compression (e.g. ropes). Analogously to the case when tension and compression is handled equally, an equivalence is established and proved which relates minimum weight trusses to minimum compliance structures. It is shown how properties different for tension and compression pop up in a modified global stiffness matrix now depending on teltsion and compression. A numerical example is included which shows optimal truss designs for different scenarios, and which proves (once more) the big influence of bar properties (different for tension and for compression) on the optimal design.

show abstract

“…negative compliance appears at the minimum of potential energy, compare e.g. Taylor and Rossow (1977)]. …”

Section: Reformulation Of Problemmentioning

confidence: 99%

“…This relation is based on the principle of minimum potential energy, also used e.g. by Taylor and Rossow (1977), where the problem pc=t compl,/ rain fTu, a E ffdrn , u E.~n m m s.t. ~aigigi u =-f , a > ~, ~ wia i< 1, i=1 i=1 with a positive lower bound ~ > 0 on the design variables is considered.…”

Section: Introduction and Problem Formulationmentioning

confidence: 99%

Truss topology optimization including bar properties different for tension and compression

Achtziger

1996

Structural Optimization

View full text Add to dashboard Cite

show abstract

“…Bendsoe and Sigmund [7] analysed and compared results obtained by using various material functions including SIMP model.Generally speaking, topology optimization problem is one which has so many design variables and a moderate number of constraints like volume limit of material, etc. In this regard, optimality criteria method [1,5,[8][9][10][11][12][13] and method of moving asymptotes (MMA) [14,15] are two of the update schemes which enjoy wide acceptance in topology optimization problems.However, this density-based approach in topology optimization is not without shortcomings. Checkerboard patterns, which consist of alternating solid and void elements, are commonly encountered in topology optimization and the origin of them is related to the features of the finite element approximation, and more specifically due to bad numerical modelling that overestimates the stiffness of checkerboards [4,[16][17][18].…”

mentioning

confidence: 99%

Material cloud method for topology optimization

Chang

Youn

2005

Numerical Meth Engineering

View full text Add to dashboard Cite

SUMMARYMaterial cloud method (MCM), a new approach for topology optimization, is presented. In MCM, an optimal structure can be obtained by manipulating the sizes and positions of material clouds, which are material patches with finite sizes and constant material densities. The optimal distributions of material clouds can be obtained by MCM using fixed background finite element meshes. In the numerical analysis procedure, only active elements, where more than one material cloud is contained, are treated. Optimal material distribution can be element-wise extracted from the distribution of material clouds. With MCM, an expansion-reduction procedure of design domain can be naturally realized through movements of material clouds, so that a true optimal solution can be found without any significant increase of computational costs. It is also shown that a clear material distribution with narrow region of intermediate density can be obtained with relatively fast convergence. Several numerical examples are shown. Some of the results are compared with those of the traditional density distribution method (DDM).

show abstract

“…Optimization methods applied for the truss optimization problem included gradient-based methods such as the research work of Taylor and Rossow [20] and Kirsch [15], simulated annealing by Moh and Chiang [18] in addition to genetic algorithms [3][4][5][6]14]. Analytical methods have generally been limited by approximations that are always introduced due to the complexity of the real-world problem that is non-linear and often has no closed-form objective function (OF) or constrains.…”

Section: Introductionmentioning

confidence: 99%

Design optimization of N-shaped roof trusses using reactive taboo search

Hamza

Mahmoud

2003

Applied Soft Computing

View full text Add to dashboard Cite

Design optimization of a class of plane trusses called the N-shaped truss (NST) is addressed. The parametric model of NST presented is intended for real-world application, avoiding simplifications of the design details that compromise the applicability. The model, which includes 27 discrete variables concerning topology, configuration and sizing of the truss, presents a challenging optimization problem. Aspects of such challenge include large search space dimensionality, absence of a closed-form objective function (OF) and constraints, multimodal objective function and costly CPU time per objective function evaluation. Three implementations of general-purpose genetic algorithms (GAs) are tested for this problem, along with a version of taboo search called reactive taboo search (RTS). In this study, the raw version of RTS exhibited better performance than the tested versions of GA but lacks some of the GA capabilities to span the search space. A modification of RTS that uses a population-based exploitation of the search history is proposed. The optimization results show that the introduced modification can further improve the performance of RTS.

show abstract

Optimal truss design based on an algorithm using optimality criteria

Cited by 24 publications

References 4 publications

Truss topology optimization including bar properties different for tension and compression

Truss topology optimization including bar properties different for tension and compression

Material cloud method for topology optimization

Design optimization of N-shaped roof trusses using reactive taboo search

Contact Info

Product

Resources

About