Probabilistic optimization of engine mount to enhance vibration characteristics using first-order reliability-based target cascading

2020 ◽  
pp. 107754632093347
Author(s):  
Youngjun Kim ◽  
Jongsoo Lee
Keyword(s):  
Large Scale ◽  
Reliability Assessment ◽  
Performance Measure ◽  
Mathematical Programming Problem ◽  
Optimized Design ◽  
Analytical Target Cascading ◽  
First Order ◽  
Target Cascading ◽  
Engine Mount ◽  
Roll Axis

Uncertainties cause tremendous failures, especially in large-scale system design, because they are accumulated from each of the subsystems. Analytical target cascading is a multidisciplinary design optimization method that enables the achievement of a concurrent and consistent design for large-scale systems. To address the uncertainties in analytical target cascading efficiently, we propose reliability-based target cascading combined with first-order reliability assessment algorithms, such as mean-value first-order second moment, performance measure analysis, and reliability index analysis. The effectiveness of the implemented algorithms was first demonstrated via a mathematical programming problem and then a practical engineering problem, involving automotive engine mount optimization, for minimizing both the difference between torque roll axis and elastic roll axis and the vibration transmissibility under mode purity requirements. The optimized design solutions are compared among three reliability assessment algorithms of reliability-based target cascading, and the uncertainty propagation with Gaussian distributions was quantified and verified. The probabilistic design results indicate that the first-order reliability-based target cascading methods successfully identify more reliable and conservative optimized solutions than analytical target cascading.

scholarly journals Multi-Disciplinary Design Optimization for Large-Scale Reverse Osmosis Systems

2014 ◽  
Author(s):  
Bo Yang Yu ◽  
Tomonori Honda ◽  
Syed Zubair ◽  
Mostafa H. Sharqawy ◽  
Maria C. Yang
Keyword(s):  
Optimal Design ◽  
Complex Systems ◽  
Design Optimization ◽  
Reverse Osmosis ◽  
Large Scale ◽  
Analytical Target Cascading ◽  
Total Water ◽  
Target Cascading ◽  
Desalination Plants ◽  
Functional Components

Large-scale desalination plants are complex systems with many inter-disciplinary interactions and different levels of sub-system hierarchy. Advanced complex systems design tools have been shown to have a positive impact on design in aerospace and automotive, but have generally not been used in the design of water systems. This work presents a multi-disciplinary design optimization approach to desalination system design to minimize the total water production cost of a 30,000m3/day capacity reverse osmosis plant situated in the Middle East, with a focus on comparing monolithic with distributed optimization architectures. A hierarchical multi-disciplinary model is constructed to capture the entire system’s functional components and subsystem interactions. Three different multi-disciplinary design optimization (MDO) architectures are then compared to find the optimal plant design that minimizes total water cost. The architectures include the monolithic architecture multidisciplinary feasible (MDF), individual disciplinary feasible (IDF) and the distributed architecture analytical target cascading (ATC). The results demonstrate that an MDF architecture was the most efficient for finding the optimal design, while a distributed MDO approach such as analytical target cascading is also a suitable approach for optimal design of desalination plants, but optimization performance may depend on initial conditions.

Cutting Plane Methods for Analytical Target Cascading With Augmented Lagrangian Coordination

2013 ◽  
Vol 135 (10) ◽  
Author(s):  
Wenshan Wang ◽  
Vincent Y. Blouin ◽  
Melissa K. Gardenghi ◽  
Georges M. Fadel ◽  
Margaret M. Wiecek ◽  
...  
Keyword(s):  
Large Scale ◽  
Augmented Lagrangian ◽  
Optimization Problems ◽  
Cutting Plane ◽  
Analytical Target Cascading ◽  
Cutting Plane Methods ◽  
Subgradient Optimization ◽  
Decomposition Approach ◽  
Target Cascading ◽  
Augmented Lagrangian Coordination

Analytical target cascading (ATC), a hierarchical, multilevel, multidisciplinary coordination method, has proven to be an effective decomposition approach for large-scale engineering optimization problems. In recent years, augmented Lagrangian relaxation methods have received renewed interest as dual update methods for solving ATC decomposed problems. These problems can be solved using the subgradient optimization algorithm, the application of which includes three schemes for updating dual variables. To address the convergence efficiency disadvantages of the existing dual update schemes, this paper investigates two new schemes, the linear and the proximal cutting plane methods, which are implemented in conjunction with augmented Lagrangian coordination for ATC-decomposed problems. Three nonconvex nonlinear example problems are used to show that these two cutting plane methods can significantly reduce the number of iterations and the number of function evaluations when compared to the traditional subgradient update methods. In addition, these methods are also compared to the method of multipliers and its variants, showing similar performance.

Trajectory Optimization Using Analytical Target Cascading

2017 ◽  
Vol 139 (12) ◽  
Author(s):  
Xiang Li ◽  
Xiaonpeng Wang ◽  
Houjun Zhang ◽  
Yuheng Guo
Keyword(s):  
Trajectory Optimization ◽  
Large Scale ◽  
Optimization Problems ◽  
Sparse Matrix ◽  
Functional Dependence ◽  
Analytical Target Cascading ◽  
Scale Problem ◽  
Direct Collocation ◽  
Target Cascading ◽  
Direct Collocation Method

In the previous reports, analytical target cascading (ATC) is generally applied to product optimization. In this paper, the application area of ATC is expanded to trajectory optimization. Direct collocation method is utilized to convert a trajectory optimization into a nonlinear programing (NLP) problem. The converted NLP is a large-scale problem with sparse matrix of functional dependence table (FDT) suitable for the application of ATC. Three numerical case studies are provided to show the effects of ATC in solving trajectory optimization problems.

scholarly journals Bounded Target Cascading in Hierarchical Design Optimization

2014 ◽  
Vol 6 ◽  
pp. 790620
Author(s):  
Xiaoling Zhang ◽  
Debiao Meng ◽  
Ruan-Jian Yang ◽  
Zhonglai Wang ◽  
Hong-Zhong Huang
Keyword(s):  
Design Optimization ◽  
Large Scale ◽  
System Level ◽  
Weighted Sum ◽  
Analytical Target Cascading ◽  
Hierarchical Design ◽  
Subsystem Level ◽  
Target Cascading ◽  
The Common ◽  
Single Objective

For large scale systems, as a hierarchical multilevel decomposed design optimization method, analytical target cascading coordinates the inconsistency between the assigned targets and response in each level by a weighted-sum formulation. To avoid the problems associated with the weighting coefficients, single objective functions in the hierarchical design optimization are formulated by a bounded target cascading method in this paper. In the BTC method, a single objective optimization problem is formulated in the system level, and two kinds of coordination constraints are added: one is bound constraint for the design points based on the response from each subsystem level and the other is linear equality constraint for the common variables based on their sensitivities with respect to each subsystem. In each subsystem level, the deviation with target for design point is minimized in the objective function, and the common variables are constrained by target bounds. Therefore, in the BTC method, the targets are coordinated based on the optimization iteration information in the hierarchical design problem and the performance of the subsystems, and BTC method will converge to the global optimum efficiently. Finally, comparisons of the results from BTC method and the weighted-sum analytical target cascading method are presented and discussed.

A Sequential Linearization Technique for Analytical Target Cascading

2008 ◽  
Author(s):  
Kuei-Yuan Chan
Keyword(s):  
Large Scale ◽  
High Efficiency ◽  
Structure Design ◽  
Analytical Target Cascading ◽  
Large Scale Systems ◽  
Linearization Technique ◽  
Random Design ◽  
Design Variables ◽  
Target Cascading ◽  
Sequential Linearization

Large-scale design problems are high dimensional and deeply-coupled in nature. The complexity of such large-scale systems prevents designers from solving them as a whole. Analytical target cascading (ATC) provides a systematic approach in solving decomposed large-scale systems that has solvable subsystems. By coordinating between subsystems, ATC can obtain the same optima as they were undecomposed. However, a convergent coordination requires series of ATC iterations that may hinder the efficiency of ATC. In this research, a sequential linearization technique is proposed to improve the efficiency of ATC. The proposed linearization technique is applied to each ATC iteration, therefore each iteration has all linear subsystems that can be solved with high efficiency. One further motivation of the proposed strategy is its perceived potential in handling multilevel problems with random design variables. As previously studied, the sequential linear programming (SLP) algorithm in [1] provides a good balances between efficiency, accuracy and convergence for single-level design optimization under random design variables. The proposed linearization technique can integrate with the SLP algorithm for multilevel systems. The global convergence of this approach is ensured by a filter to determine the acceptance of the optima at each iteration and the corresponding trust region. A geometric programming example and a structure design example demonstrate the efficiency of the proposed method over standard ATC solution process without loss of accuracy.

Sequential linearization in analytical target cascading for optimization of complex multilevel systems

2010 ◽  
Vol 225 (2) ◽  
pp. 451-462 ◽  
Author(s):  
K-Y Chan
Keyword(s):  
Large Scale ◽  
High Efficiency ◽  
Analytical Target Cascading ◽  
Large Scale Systems ◽  
Linearization Technique ◽  
Random Design ◽  
Multilevel Systems ◽  
Design Variables ◽  
Target Cascading ◽  
Sequential Linearization

Large-scale design problems are high dimensional and deeply coupled in nature. The complexity of such large-scale systems prevents designers from solving them as a whole. Analytical target cascading (ATC) provides a systematic approach in solving decomposed large-scale systems that has solvable subsystems. By coordinating between subsystems, ATC can obtain the same optima as they were undecomposed. However, a convergent coordination requires series of ATC iterations that may hinder the efficiency of ATC. In this research, a sequential linearization technique is proposed to improve the efficiency of ATC. The proposed linearization technique is applied to each ATC iteration, and therefore each iteration has all linear subsystems that can be solved with high efficiency. The global convergence of this approach is ensured by a filter to determine the acceptance of the optima at each iteration and the corresponding trust region. One further motivation of the proposed strategy is its perceived potential in handling multilevel problems with random design variables. As previously studied, the sequential linear programming (SLP) algorithm provides a good balance between efficiency, accuracy, and convergence for single-level design optimization under random design variables. The proposed linearization technique can integrate with the SLP algorithm for multilevel systems. In this work, a geometric programming example is used to demonstrate the efficiency of the proposed method over standard ATC solution process without loss of accuracy.

scholarly journals Examination of Construct Validity and Criterion-Related Validity of the German Motor Test in Egyptian Schoolchildren

2021 ◽  
Vol 18 (16) ◽  
pp. 8341
Author(s):  
Osama Abdelkarim ◽  
Julian Fritsch ◽  
Darko Jekauc ◽  
Klaus Bös
Keyword(s):  
Construct Validity ◽  
Physical Fitness ◽  
Large Scale ◽  
Body Height ◽  
Cross Sectional Study ◽  
Latent Factors ◽  
Cross Sectional ◽  
First Order ◽  
Motor Test ◽  
Health Related

Physical fitness is an indicator for children’s public health status. Therefore, the aim of this study was to examine the construct validity and the criterion-related validity of the German motor test (GMT) in Egyptian schoolchildren. A cross-sectional study was conducted with a total of 931 children aged 6 to 11 years (age: 9.1 ± 1.7 years) with 484 (52%) males and 447 (48%) females in grades one to five in Assiut city. The children’s physical fitness data were collected using GMT. GMT is designed to measure five health-related physical fitness components including speed, strength, coordination, endurance, and flexibility of children aged 6 to 18 years. The anthropometric data were collected based on three indicators: body height, body weight, and BMI. A confirmatory factor analysis was conducted with IBM SPSS AMOS 26.0 using full-information maximum likelihood. The results indicated an adequate fit (χ2 = 112.3, df = 20; p < 0.01; CFI = 0.956; RMSEA = 0.07). The χ2-statistic showed significant results, and the values for CFI and RMSEA showed a good fit. All loadings of the manifest variables on the first-order latent factors as well as loadings of the first-order latent factors on the second-order superordinate factor were significant. The results also showed strong construct validity in the components of conditioning abilities and moderate construct validity in the components of coordinative abilities. GMT proved to be a valid method and could be widely used on large-scale studies for health-related fitness monitoring in the Egyptian population.

scholarly journals Simulations of a bubble wall interacting with an electroweak plasma

2021 ◽  
Vol 2021 (2) ◽  
Author(s):  
Zong-Gang Mou ◽  
Paul M. Saffin ◽  
Anders Tranberg
Keyword(s):  
Large Scale ◽  
Baryon Asymmetry ◽  
Winding Number ◽  
Bubble Wall ◽  
Electroweak Phase Transition ◽  
First Order ◽  
The Standard Model ◽  
Technical Details ◽  
Real Time Simulations ◽  
Chern Simons

Abstract We perform large-scale real-time simulations of a bubble wall sweeping through an out-of-equilibrium plasma. The scenario we have in mind is the electroweak phase transition, which may be first order in extensions of the Standard Model, and produce such bubbles. The process may be responsible for baryogenesis and can generate a background of primordial cosmological gravitational waves. We study thermodynamic features of the plasma near the advancing wall, the generation of Chern-Simons number/Higgs winding number and consider the potential for CP-violation at the wall generating a baryon asymmetry. A number of technical details necessary for a proper numerical implementation are developed.

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