Multiobjective Design Optimization of a Biconcave Mobile-Bearing Lumbar Total Artificial Disk Considering Spinal Kinematics, Facet Joint Loading, and Metal-on-Polyethylene Contact Mechanics

2019 ◽  
Vol 142 (4) ◽  
Author(s):  
Chaochao Zhou ◽  
Ryan Willing
Keyword(s):  
Multiobjective Optimization ◽  
Design Optimization ◽  
Performance Metrics ◽  
Facet Joint ◽  
Pareto Frontier ◽  
Mobile Bearing ◽  
Ultrahigh Molecular Weight Polyethylene ◽  
Joint Force ◽  
Multiobjective Design ◽  
Single Objective

Abstract Total disk arthroplasty (TDA) using an artificial disk (AD) is an attractive surgical technique for the treatment of spinal disorders, since it can maintain or restore spinal motion (unlike interbody fusion). However, adverse surgical outcomes of contemporary lumbar TDAs have been reported. We previously proposed a new mobile-bearing AD design concept featuring a biconcave ultrahigh-molecular-weight polyethylene (UHMWPE) mobile core. The objective of this study was to develop an artificial neural network (NN) based multiobjective optimization framework to refine the biconcave-core AD design considering multiple TDA performance metrics, simultaneously. We hypothesized that there is a tradeoff relationship between the performance metrics in terms of range of motion (ROM), facet joint force (FJF), and polyethylene contact pressure (PCP). By searching the resulting three-dimensional (3D) Pareto frontier after multiobjective optimization, it was found that there was a “best-tradeoff” AD design, which could balance all the three metrics, without excessively sacrificing each metric. However, for each single-objective optimum AD design, only one metric was optimal, and distinct sacrifices were observed in the other two metrics. For a commercially available biconvex-core AD design, the metrics were even worse than the poorest outcomes of the single-objective optimum AD designs. Therefore, multiobjective design optimization could be useful for achieving native lumbar segment biomechanics and minimal PCPs, as well as for improving the existing lumbar motion-preserving surgical treatments.

scholarly journals The appropriate hybrid surgical strategy in three-level cervical degenerative disc disease: a finite element analysis

2019 ◽  
Vol 14 (1) ◽  
Author(s):  
Y. M. Xie ◽  
Y. C. Zheng ◽  
S. J. Qiu ◽  
K. Q. Gong ◽  
Y. Duan
Keyword(s):  
Stress Distribution ◽  
Facet Joint ◽  
Ultrahigh Molecular Weight Polyethylene ◽  
Fe Model ◽  
Hybrid Surgery ◽  
Disc Disease ◽  
Element Analysis ◽  
Intact Group ◽  
Joint Force ◽  
3D Ct Scan

Abstract Objective The purpose of this FE study was to analyze the biomechanical characteristics of different HS strategies used in the treatment of three-level CDDD (one-level CDA and two-level ACDF). Methods We validated the FE model of an intact cervical spine established by transferring the data, collected by 3D CT scan, to the FE software ABAQUS and comparing these data with the data from published studies. Then, the FE model of hybrid surgery was reconstructed to analyze the range of motion (ROM), facet joint force, and stress distribution on an ultrahigh molecular weight polyethylene (UHMWPE) core. Results The current cervical FE model was able to measure the biomechanical changes in a follow-up hybrid surgery simulation. The total ROM of the cervical HS models was substantially decreased compared with the total ROM of the intact group, and the M2 (C3/4 ACDF, C4/5 CDA, and C5/6 ACDF) model had the closest total ROM to the intact group, but the facet joint force adjacent to the treatment levels showed very little difference among them. The stress distribution showed noticeable similarity: two flanks were observed in the center core, but the inlay of M2 was more vulnerable. Conclusions Through the comparison of ROM, the facet joint force after CDA, and the stress distribution of the prosthesis, we find that M2 model has a better theoretical outcome, especially in preserving the maximum total ROM.

scholarly journals Automated Cable Road Layout and Harvesting Planning for Multiple Objectives in Steep Terrain

Forests ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 687 ◽  
Author(s):  
Bont ◽  
Maurer ◽  
Breschan
Keyword(s):  
Multiobjective Optimization ◽  
Cost Estimation ◽  
Planning Process ◽  
Pareto Frontier ◽  
Solution Process ◽  
Optimization Approach ◽  
Steep Terrain ◽  
And Performance ◽  
Harvesting Costs ◽  
Single Objective

Cable yarding is the most commonly used technique for harvesting timber from steep terrain in central Europe. During the planning process, one important task is to define the cable road layout. This means that the harvesting technology and cable road location must be specified for a given timber parcel. Although managers must minimize harvesting costs, it is even more important that such work on forests reduces the potential for damage to the residual stand and ensures that environmental conditions remain suitable for regeneration. However, current methods are geared only toward minimizing harvesting costs and are computationally demanding and difficult to handle for the end user. These limitations hinder broad application of such methods. Further, the underlying productivity models used for cost estimation do not cover all conditions of an area and they cannot be applied over a whole harvesting area. To overcome these shortcomings, we present: (1) a multiobjective optimization approach that leads to realistic, practicable results that consider multiple conflicting design objectives, and (2) a concept for an easy-to-use application. We compare the practical applicability and performance of the results achieved with multiobjective optimization with those achieved with single-objective (cost-minimal) optimization. Based on these points, we then present and discuss a concept for a user-friendly implementation. The model was tested on two sites in Switzerland. The study produced the following major findings: (1) Single-objective alternatives have no practical relevance, whereas multiobjective alternatives are preferable in real-world applications and lead to realistic solutions; (2) the solution process for a planning unit should include analysis of the Pareto frontier; and (3) results can only be made available within a useful period of time by parallelizing computing operations.

scholarly journals Multiobjective Design Optimization Framework for Multicomponent System with Complex Nonuniform Loading

2020 ◽  
Vol 2020 ◽  
pp. 1-19
Author(s):  
Hong Zhang ◽  
Guangchen Bai ◽  
Lukai Song
Keyword(s):  
Genetic Algorithm ◽  
Multiobjective Optimization ◽  
Design Optimization ◽  
Optimal Algorithm ◽  
Multicomponent System ◽  
Kriging Model ◽  
Surface Model ◽  
Optimization Framework ◽  
Comparison Results ◽  
Multiobjective Design

To improve the accuracy and efficiency of multiobjective design optimization for a multicomponent system with complex nonuniform loads, an efficient surrogate model (the decomposed collaborative optimized Kriging model, DCOKM) and an accurate optimal algorithm (the dynamic multiobjective genetic algorithm, DMOGA) are presented in this study. Furthermore, by combining DCOKM and DMOGA, the corresponding multiobjective design optimization framework for the multicomponent system is developed. The multiobjective optimization design of the carrier roller system is considered as a study case to verify the developed approach with respect to multidirectional nonuniform loads. We find that the total standard deviation of three carrier rollers is reduced by 92%, where the loading distribution is more uniform after optimization. This study then compares surrogate models (response surface model, Kriging model, OKM, and DCOKM) and optimal algorithms (neighbourhood cultivation genetic algorithm, nondominated sorting genetic algorithm, archive microgenetic algorithm, and DMOGA). The comparison results demonstrate that the proposed multiobjective design optimization framework is demonstrated to hold advantages in efficiency and accuracy for multiobjective optimization.

Metrics for Quality Assessment of a Multiobjective Design Optimization Solution Set

2000 ◽  
Author(s):  
Jin Wu ◽  
Shapour Azarm
Keyword(s):  
Multiobjective Optimization ◽  
Pareto Frontier ◽  
Optimization Methods ◽  
Optimization Method ◽  
Solution Set ◽  
Pareto Solution ◽  
Vibrating Platform ◽  
Pareto Solution Sets ◽  
Multiobjective Design

Abstract In this paper, several new set quality metrics are introduced that can be used to evaluate the ‘goodness’ of an observed Pareto solution set. These metrics, which are formulated in closed-form and geometrically illustrated, include coverage difference, Pareto spread, accuracy of an observed Pareto frontier, number of distinct choices and cluster. The metrics should enable a designer either monitor the quality of an observed Pareto solution set as obtained by a multiobjective optimization method, or compare the quality of observed Pareto solution sets as reported by different multiobjective optimization methods. A vibrating platform example is used to demonstrate the calculation of these metrics for an observed Pareto solution set.

Versatile Formulation for Multiobjective Reliability-Based Design Optimization

2005 ◽  
Vol 128 (6) ◽  
pp. 1217-1226 ◽  
Author(s):  
T. Zou ◽  
S. Mahadevan
Keyword(s):  
Multiobjective Optimization ◽  
Design Optimization ◽  
Reliability Analysis ◽  
Pareto Frontier ◽  
System Level ◽  
Reliability Based Design Optimization ◽  
Component Reliability ◽  
Reliability Based Design ◽  
Uncertainty Model ◽  
Optimization Methodology

This paper develops a multiobjective optimization methodology for system design under uncertainty. Model-based reliability analysis methods are used to compute the probabilities of unsatisfactory performance at both component and system levels. Combined with several multiobjective optimization formulations, a versatile reliability-based design optimization (RBDO) approach is used to achieve a tradeoff between two objectives and to generate the Pareto frontier for decision making. The proposed RBDO approach uses direct reliability analysis to decouple the reliability and optimization iterations, instead of inverse first-order reliability analysis as other existing decoupled approaches. This helps to solve a wide variety of RBDO problems with competing objectives, especially when system-level reliability constraints need to be considered. The approach also allows more accurate methods to be used for reliability analysis, and reliability terms to be included in the objective function. Two important automotive quality objectives, related to the door closing effort (evaluated using component reliability analysis) and the wind noise (evaluated using system reliability analysis), are used to illustrate the proposed method.

Multiobjective Optimization Dealing With Uncertainty

1989 ◽  
Author(s):  
S. U. Mohandas ◽  
E. Sandgren
Keyword(s):  
Multiobjective Optimization ◽  
Natural Language ◽  
Design Optimization ◽  
Fuzzy Sets ◽  
Fuzzy Set ◽  
Optimization Problem ◽  
Objective Functions ◽  
Fuzzy Goals ◽  
Box Method ◽  
Multiobjective Design

Abstract An algorithm to handle uncertainty in a multiobjective design optimization problem is developed. The procedure is applied to three examples where objective functions in each of them compete against each other. The uncertainty in the description of objective functions is modeled by using fuzzy goals and the terms of natural language. Multiobjective function is formulated as a fuzzy set. The minimization is carried out using a combination of the Complex Box method and a technique of ranking of fuzzy sets.

scholarly journals Multiobjective Design Optimization of Grillage Systems according to LRFD-AISC

2011 ◽  
Vol 2011 ◽  
pp. 1-24 ◽  
Author(s):  
Tugrul Talaslioglu
Keyword(s):  
Multiobjective Optimization ◽  
Design Optimization ◽  
Optimization Algorithms ◽  
Grid Structure ◽  
American Institute ◽  
Design Constraints ◽  
Factor Design ◽  
Computational Procedures ◽  
Load And Resistance Factor ◽  
Multiobjective Design

Both the entire weight and joint displacements of grid structures are minimized at the same time in this study. Four multiobjective optimization algorithms, NSGAII, SPEAII, PESAII, and AbYSS are employed to perform computational procedures related to optimization processes. The design constraints related to serviceability and ultimate strength of grid structure are implemented from Load and Resistance Factor Design-American Institute of Steel Constructions (LRFD-AISC Ver.13). Hence, while the computational performances of these four optimization algorithms are compared using different combinations of optimizer-related parameters, the various strengths of grid members are also evaluated. For this purpose, multiobjective optimization algorithms (MOAs) employed are applied to the design optimization of three application examples and achieved to generate various optimal designations using different combinations of optimizer-related parameters. According to assessment of these optimal designations considering various quality indicators, IGD, HV, and spread, AbYSSS shows a better performance comparatively to the other three proposed MOAs, NSGAII, SPEAII, and PESAII.

Robust ascent trajectory design and optimization of a typical launch vehicle

2018 ◽  
Vol 232 (24) ◽  
pp. 4601-4614 ◽  
Author(s):  
Jafar Roshanian ◽  
Ali A Bataleblu ◽  
Masoud Ebrahimi
Keyword(s):  
Design Optimization ◽  
Pareto Frontier ◽  
Launch Vehicle ◽  
Model Parameters ◽  
Trajectory Design ◽  
Nsga Ii ◽  
Trade Off ◽  
Multi Objective ◽  
Conflicting Objectives ◽  
Single Objective

Robustness and reliability of the designed trajectory are crucial for flight performance of launch vehicles. In this paper, robust trajectory design optimization of a typical LV is proposed. Two formulations of robust trajectory design optimization problem using single-objective and multi-objective optimization concept are presented. Both aleatory and epistemic uncertainties in model parameters and operational environment characteristics are incorporated in the problem, respectively. In order to uncertainty propagation and analysis, the improved Latin hypercube sampling is utilized. A comparison between robustness of the single-objective robust trajectory design optimization solution and deterministic design optimization solution is illustrated using probability density functions. The multi-objective robust trajectory design optimization is executed through NSGA-II and a set of feasible design points with a good spread is obtained in the form of Pareto frontier. The final Pareto frontier presents a trade-off between two conflicting objectives namely maximizing injection robustness and minimizing gross lift-off mass of launch vehicle. The resulted Pareto frontier of the multi-objective robust trajectory design optimization shows that with 1% increase in gross mass, the robustness of the design point to the considered uncertainties can be increased about 80%. Also, numerical simulation results show that the multi-objective formulation is a necessary approach to achieve a good trade-off between optimality and robustness.

Metrics for Quality Assessment of a Multiobjective Design Optimization Solution Set

2000 ◽  
Vol 123 (1) ◽  
pp. 18-25 ◽  
Author(s):  
Jin Wu ◽  
Shapour Azarm
Keyword(s):  
Multiobjective Optimization ◽  
Pareto Frontier ◽  
Optimization Methods ◽  
Optimization Method ◽  
Solution Set ◽  
Pareto Solution ◽  
Vibrating Platform ◽  
Pareto Solution Sets ◽  
Multiobjective Design

In this paper, several new set quality metrics are introduced that can be used to evaluate the “goodness” of an observed Pareto solution set. These metrics, which are formulated in closed-form and geometrically illustrated, include hyperarea difference, Pareto spread, accuracy of an observed Pareto frontier, number of distinct choices and cluster. The metrics should enable a designer to either monitor the quality of an observed Pareto solution set as obtained by a multiobjective optimization method, or compare the quality of observed Pareto solution sets as reported by different multiobjective optimization methods. A vibrating platform example is used to demonstrate the calculation of these metrics for an observed Pareto solution set.

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