Topology Optimization of Multi-Component Structures via Decomposition-Based Assembly Synthesis

Lyu, Naesung

doi:10.1115/detc2003/dac-48730

Cited by 16 publications

(5 citation statements)

References 31 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The goal of this work was to move away from the bulky articulated rigid body mechanisms previously analyzed and instead design a prosthetic foot structure consting of a single part that, in response to specific loading scenarios, deforms elastically in such a way as to achieve a desired output motion, that is, a compliant mechanism [22]. There is a plethora of literature on topology synthesis and optimization for compliant mechanisms [23][24][25][26][27][28][29] including continuum element density approaches, frame element-based structures, and pseudo-rigid body models. However, the outputs of these topology optimizations have several practical limitations; for example, they consist only of uniform elements or uniform cross-sections, have unclear boundaries or checkerboard patterns, or they result in localized flexural hinges with high stress concentrations [30].…”

Section: Compliant Mechanism Optimizationmentioning

confidence: 99%

Passive Prosthetic Foot Shape and Size Optimization Using Lower Leg Trajectory Error

Olesnavage

Winter

2017

Volume 5A: 41st Mechanisms and Robotics Conference

View full text Add to dashboard Cite

A method is presented to optimize the shape and size of a passive prosthetic foot using the Lower Leg Trajectory Error (LLTE) as the design objective. The LLTE is defined as the root-mean-square error between the lower leg trajectory calculated for a given prosthetic foot by finding the deformed shape of the foot under typical ground reaction forces and a target physiological lower leg trajectory obtained from published gait data for able-bodied walking. In previous work, the design of simple two degree-of-freedom analytical models consisting of rigid structures, rotational joints with constant stiffness, and uniform cantilevered beams, have been optimized for LLTE. However, prototypes built to replicate these simple models were large, heavy, and overly complex. In this work, the size and shape of a single-part compliant prosthetic foot keel made out of nylon 6/6 was optimized for LLTE to produce a light weight, low cost, and easily manufacturable prosthetic foot design. The shape of the keel was parameterized as a wide Bézier curve, with constraints ensuring that only physically meaningful shapes were considered. The LLTE value for each design was evaluated using a custom MATLAB script, which ran ADINA finite element analysis software to find the deformed shape of the prosthetic keel under multiple loading scenarios. The optimization was performed by MATLAB’s built-in genetic algorithm. After the optimal design for the keel was found, a heel was added to structure, sized such that when the user’s full weight acted on the heel, the structure had a factor of safety of two. The resulting optimal design has a lower LLTE value than the two degree-of-freedom analytical models, at 0.154 compared to 0.172, 0.187, and 0.269 for the two degree-of-freedom models. At 412 g, the optimal wide curve foot is nearly half the mass of the lightest prototype built from the previous models, which was 980 g. The design found through this compliant mechanism optimization method is thus far superior to the two degree-of-freedom models previously considered.

show abstract

Section: Compliant Mechanism Optimizationmentioning

confidence: 99%

Passive Prosthetic Foot Shape and Size Optimization Using Lower Leg Trajectory Error

Olesnavage

Winter

2017

Volume 5A: 41st Mechanisms and Robotics Conference

View full text Add to dashboard Cite

show abstract

“…An advantage of a GA, used in structural optimization, is that they require few initial parameters and permit the optimization of continuous and discrete variables and less restricted search. However, to ensure convergence, engineering experience is essential for the definition of the main operations used in GA, such as: crossover, mutation and reproduction (Lyu and Saitou, 2003). The purpose of this study is to define a proper representation and its related genetic operators that would help to reach optimal solutions.…”

Section: Introductionmentioning

confidence: 99%

A long span bridge and a greenhouse roof truss structure optimized by means of a consistent genetic algorithm with a natural crossover

Astudillo

Vera

Ruíz

et al. 2012

Engineering Computations

View full text Add to dashboard Cite

PurposeThe purpose of this paper is to introduce a novel methodology that has the capability of finding symmetrical and nonsymmetrical solutions in complex design domains without additional tuning when changing the design domain. These go from an academic design domain to a practical one.Design/methodology/approachVarious crossovers operators are applied over the same representation using a genetic algorithm for truss structural optimization cases where literature solutions have a tendency to forced symmetry in order to find an optimal design with fewer iterations. Continuous‐discrete representations were cross‐bred by a uniform‐sbx simultaneous crossover, called zygote crossover. Specialized mutations operations are proposed to generate localized changes to improve the solution according with the design domain.FindingsDesign solutions found were lighter and stiffer when comparing against cases reported in current literature and in engineering practice. Also these solutions were found in fewer iterations.Practical implicationsThe cases solved herein are complex and are a challenge for any optimization routine however practical design limitations are observed in the sense of out plane stability. Further comparisons cases are required in order to generate a less adjusted design, this is because the greenhouse solution had to be stiffened with out of plane bars to give it enough lateral stability.Originality/valueContinuous‐discrete representations were cross‐bred by a uniform‐sbx simultaneous crossover, called natural crossover. Specialized mutations operations are proposed to generate localized changes to improve the solution according with the design domain. This scheme along with a less restrictive environment allows a wider exploration of search space.

show abstract

“…A modified Non-Dominated Sorting Genetic Algorithm-II (NSGA-II) [7] is adopted for the above problem due to the discrete nature of the design variables, and its ability to solve multi-objective problems without predefined weight or bounds. Some enhancements to the conventional NSGA-II are made in the niching based on the distances in object function space and the stochastic universal sampling, which was successfully applied in our previous work [9].…”

Section: Optimization Problemmentioning

confidence: 99%

“…Since the information in x, y, and z are linked to the physical geometry of structure, the conventional one point or multiple point crossover for linear chromosomes [13] are ineffective in preserving high-quality building blocks. For this type of problems, direct crossover has been successfully applied to improve the performance [8,9], whose details can be found in [3] along with the description of the modified NSGA-II.…”

Section: Optimization Problemmentioning

confidence: 99%

“…This paper integrates our previous works on the decomposition-based assembly synthesis methods [2][3][4][5][6], by considering the stiffness, the manufacturing / assembly cost [3,4], and the dimensional integrity [2,6] altogether in finding optimal assembly syntheses. To solve the optimization problem posed with multiple objectives, a multi-objective genetic algorithm (GA) [7] with a direct crossover operator [8,9] is used. The GA synthesizes candidate assembly designs by selecting joints from a predefined set of joint types (i.e., joint library [5]) for predefined potential locations, thus defining component set, deciding the beam cross sections and welding thickness where joints are assigned.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Assembly Synthesis for Stiffness, Dimensional Adjustability and Manufacturability

Lyu¹,

Lee²

Proceedings of the Fourth International Conference on Engineering Computational Technology

View full text Add to dashboard Cite

A method that identifies the optimal components set, joint designs and corresponding subassembly partitioning for a Body-In-White (BIW) made of the aluminium space frame (ASF) is presented where the structural stiffness, dimensional integrity and components manufacturing / assembly cost are considered as the objectives. The optimization problem is posed as a simultaneous determination of the location and types of joints in a structure selected from the predefined joint library combined with the size optimization for the cross sections of the joined structural frames. The join library is a look-up table containing following three components: 1) the geometry of the feasible joints at each potential joint location, 2) the cross sectional designs of the joined frames and 3) the structural characteristics as the equivalent torsional spring models. Structural stiffness of the entire structure is evaluated by finite element analyses of a beam-spring BIW model constructed based on the joints and joined frames. The dimensional integrity of the assembly is calculated by evaluating how easily the adjustment of the critical dimensions in the structure can be achieved during the assembly process. Finally, manufacturing cost and assembly costs are estimated by considering the manufacturing and assembly procedures based on the geometries of the components and joints. The optimization problem is solved by multi-objective evolutionary algorithms using a graph-based crossover operator. The BIW of a middle size passenger car is decomposed as the case study where the representative optimal designs are selected from the resulting Pareto front and trade-offs among stiffness, dimensional integrity and manufacturing/assembly cost are discussed.

show abstract

Topology Optimization of Multi-Component Structures via Decomposition-Based Assembly Synthesis

Cited by 16 publications

References 31 publications

Passive Prosthetic Foot Shape and Size Optimization Using Lower Leg Trajectory Error

Passive Prosthetic Foot Shape and Size Optimization Using Lower Leg Trajectory Error

A long span bridge and a greenhouse roof truss structure optimized by means of a consistent genetic algorithm with a natural crossover

Assembly Synthesis for Stiffness, Dimensional Adjustability and Manufacturability

Contact Info

Product

Resources

About