Multidisplinary Optimization of Crank-Link Mechanism of HCPE Based on iSIGHT

2013 ◽  
Vol 300-301 ◽  
pp. 99-103
Author(s):  
Ying Liu ◽  
Hong Xin Zhang ◽  
Kai Yin
Keyword(s):  
Response Surface ◽  
Optimization Model ◽  
Multidisciplinary Design Optimization ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Minimum Volume ◽  
Connecting Rod ◽  
Response Surface Models ◽  
Link Mechanism ◽  
Surface Models

The technology of multidisciplinary design optimization was elaborated, and the structure principle and dynamic model of HCPE were briefly presented. Based on the minimum volume, the collaborative optimization model of crank-link mechanism was constructed. The approximate response surface models of connecting rod and crankshaft were established by means of ANSYS calculation. By combined with iSIGHT software, the collaborative optimization system was realized, and the calculation speed was improved. The optimized volume decreased by 0.803% under the premise that couldn't change the crankshaft counterbalance. So the mass of the engine is reduced and the performance is improved.

Application of Multidisciplinary Design Optimization in the Truss Spar Concept Design

2010 ◽  
Author(s):  
Zhe Jiang ◽  
Weicheng Cui ◽  
Xiaoping Huang
Keyword(s):  
Design Optimization ◽  
Response Surface ◽  
Multidisciplinary Design Optimization ◽  
Coupling Effect ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Design Solution ◽  
Traditional Design ◽  
System Solution ◽  
Truss Spar

In the traditional design of a Truss Spar, designers usually choose different discipline as major concentration in different design phases. The coupling effect among disciplines can hardly be accounted for. Multidisciplinary design optimization has been proved to be an effective tool for the design of complex engineering systems, which takes all disciplines into account at the same time and exploit coupling effect among disciplines, thereby achieving the optimal system solution. In this paper, a multidisciplinary optimization scheme for a Truss Spar is firstly developed and the Truss Spar is decomposed into four modules: weight module, hydrodynamic module, structure module and stability module. Response surface method is used to replace the high-fidelity analysis to perform the approximate mathematical models of the objective function/constraints as a function of design variables. In order to enhance the accuracy of the predicted optimum, the response surface models are continuously updated using the information obtained from the numerical simulation of latest iterative results. Finally, an optimal design solution, which satisfies all the constraints, is obtained using collaborative optimization. The characteristics of the optimized design solution including hull weight, heave response, stability performance and strength of the bottom deck, are much improved comparing with traditional design.

Elemental chlorine-free bleaching of North American hardwood kraft pulps: Evaluation of oxidant-reinforced extraction variables on overall bleaching optimization

TAPPI Journal ◽  
2013 ◽  
Vol 12 (10) ◽  
pp. 33-41 ◽  
Author(s):  
BRIAN N. BROGDON
Keyword(s):  
Response Surface ◽  
Chlorine Dioxide ◽  
North American ◽  
Yield Loss ◽  
Alkaline Extraction ◽  
Kraft Pulps ◽  
Pulp Bleaching ◽  
Response Surface Models ◽  
Elemental Chlorine ◽  
Surface Models

This investigation evaluates how higher reaction temperatures or oxidant reinforcement of caustic extraction affects chlorine dioxide consumption during elemental chlorine-free bleaching of North American hardwood pulps. Bleaching data from the published literature were used to develop statistical response surface models for chlorine dioxide delignification and brightening sequences for a variety of hardwood pulps. The effects of higher (EO) temperature and of peroxide reinforcement were estimated from observations reported in the literature. The addition of peroxide to an (EO) stage roughly displaces 0.6 to 1.2 kg chlorine dioxide per kilogram peroxide used in elemental chlorine-free (ECF) bleach sequences. Increasing the (EO) temperature by Δ20°C (e.g., 70°C to 90°C) lowers the overall chlorine dioxide demand by 0.4 to 1.5 kg. Unlike what is observed for ECF softwood bleaching, the presented findings suggest that hot oxidant-reinforced extraction stages result in somewhat higher bleaching costs when compared to milder alkaline extraction stages for hardwoods. The substitution of an (EOP) in place of (EO) resulted in small changes to the overall bleaching cost. The models employed in this study did not take into account pulp bleaching shrinkage (yield loss), to simplify the calculations.

Support Vector Regression-Based Multidisciplinary Design Optimization for Ship Design

2012 ◽  
Author(s):  
Dongqin Li ◽  
Yifeng Guan ◽  
Qingfeng Wang ◽  
Zhitong Chen
Keyword(s):  
Design Optimization ◽  
Support Vector Regression ◽  
Design Process ◽  
Multidisciplinary Design Optimization ◽  
Initial Point ◽  
Ship Design ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Support Vector ◽  
Independent Design

The design of ship is related to several disciplines such as hydrostatic, resistance, propulsion and economic. The traditional design process of ship only involves independent design optimization within each discipline. With such an approach, there is no guarantee to achieve the optimum design. And at the same time improving the efficiency of ship optimization is also crucial for modem ship design. In this paper, an introduction of both the traditional ship design process and the fundamentals of Multidisciplinary Design Optimization (MDO) theory are presented and a comparison between the two methods is carried out. As one of the most frequently applied MDO methods, Collaborative Optimization (CO) promotes autonomy of disciplines while providing a coordinating mechanism guaranteeing progress toward an optimum and maintaining interdisciplinary compatibility. However there are some difficulties in applying the conventional CO method, such as difficulties in choosing an initial point and tremendous computational requirements. For the purpose of overcoming these problems, Design Of Experiment (DOE) and a new support vector regression algorithm are applied to CO to construct statistical approximation model in this paper. The support vector regression algorithm approximates the optimization model and is updated during the optimization process to improve accuracy. It is shown by examples that the computing efficiency and robustness of this CO method are higher than with the conventional CO method. Then this new Collaborative Optimization (CO) method using approximate technology is discussed in detail and applied in ship design which considers hydrostatic, propulsion, weight and volume, performance and cost. It indicates that CO method combined with approximate technology can effectively solve complex engineering design optimization problem. Finally, some suggestions on the future improvements are proposed.

scholarly journals Multidisciplinary design optimization of hard rock tunnel boring machine using collaborative optimization

2018 ◽  
Vol 10 (1) ◽  
pp. 168781401875472 ◽  
Author(s):  
Wei Sun ◽  
Xiaobang Wang ◽  
Maolin Shi ◽  
Zhuqing Wang ◽  
Xueguan Song
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Hard Rock ◽  
Tunnel Boring Machine ◽  
Collaborative Optimization ◽  
Optimization Process ◽  
Multidisciplinary Design ◽  
Tunnel Boring ◽  
Geological Conditions ◽  
Rock Tunnel

A multidisciplinary design optimization model is developed in this article to optimize the performance of the hard rock tunnel boring machine using the collaborative optimization architecture. Tunnel boring machine is a complex engineering equipment with many subsystems coupled. In the established multidisciplinary design optimization process of this article, four subsystems are taken into account, which belong to different sub-disciplines/subsytems: the cutterhead system, the thrust system, the cutterhead driving system, and the economic model. The technology models of tunnel boring machine’s subsystems are build and the optimization objective of the multidisciplinary design optimization is to minimize the construction period from the system level of the hard rock tunnel boring machine. To further analyze the established multidisciplinary design optimization, the correlation between the design variables and the tunnel boring machine’s performance is also explored. Results indicate that the multidisciplinary design optimization process has significantly improved the performance of the tunnel boring machine. Based on the optimization results, another two excavating processes under different geological conditions are also optimized complementally using the collaborative optimization architecture, and the corresponding optimum performance of the hard rock tunnel boring machine, such as the cost and energy consumption, is compared and analysed. Results demonstrate that the proposed multidisciplinary design optimization method for tunnel boring machine is reliable and flexible while dealing with different geological conditions in practical engineering.

Modeling and optimization of ultrasound‐assisted cinnamon extraction process using fuzzy and response surface models

2018 ◽  
Vol 42 (2) ◽  
pp. e12978
Author(s):  
Nur Cebi ◽  
Osman Sagdic ◽  
Abdulrahman Mohammed Basahel ◽  
Mohammed Abdullah Balubaid ◽  
Osman Taylan ◽  
...  
Keyword(s):  
Response Surface ◽  
Extraction Process ◽  
Modeling And Optimization ◽  
Response Surface Models ◽  
Surface Models ◽  
Ultrasound Assisted

Multidisciplinary Design Optimization of a Lunar Lander’s Soft-Landing Gear

2010 ◽  
Vol 42 ◽  
pp. 118-121
Author(s):  
Yun Tong Lu ◽  
Chun Jie Wang ◽  
Ang Li ◽  
Han Wang
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Rapid Development ◽  
Fem Analysis ◽  
Landing Gear ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Optimization Approach ◽  
Soft Landing ◽  
Multi Body

The rapid development of Multidisciplinary Design Optimization (MDO) approach can simultaneously guarantee the cut of cost on design and optimal performance of spacecraft. Based on the theory of Collaborative Optimization approach (CO) of MDO, present paper proposes the method of CO by integrating Pro/E(3D modeling), Patran/Nastran(FEM analysis) and ADAMS(multi-body dynamic analysis) with the Isight software. In the analysis of the soft-landing gear of Lunar Lander, this method can optimize the mass of the landing gear and meanwhile ensures the reliability of structure statics, structure dynamics and multi-body dynamics. Thus the feasibility, applied value and guideline significance of this method in spacecraft structural design are proven.

Optimization of the Global Static and Dynamic Performance of a Vehicle Body by Means of Response Surface Models

2012 ◽  
Author(s):  
Pavlina Mihaylova ◽  
Alessandro Pratellesi ◽  
Niccolò Baldanzini ◽  
Marco Pierini
Keyword(s):  
Response Surface ◽  
Dynamic Performance ◽  
The Body ◽  
Vehicle Body ◽  
Fe Model ◽  
Structural Modifications ◽  
Response Surface Models ◽  
First Choice ◽  
Surface Models ◽  
Body In White

Concept FE models of the vehicle structure are often used to optimize it in terms of static and dynamic stiffness, as they are parametric and computationally inexpensive. On the other hand they introduce modeling errors with respect to their detailed FE equivalents due to the simplifications made. Even worse, the link between the concept and the detailed FE model can be sometimes lost after optimization. The aim of this paper is to present and validate an alternative optimization approach that uses the detailed FE model of the vehicle body-in-white instead of its concept representation. Structural modifications of this model were applied in two different ways — by local joint modifications and by using mesh morphing techniques. The first choice was motivated by the strong influence of the structural joints on the global vehicle performance. For this type of modification the plate thicknesses of the most influent car body joints were changed. In the second case the overall car dimensions were modified. The drawback of using detailed FE models of the vehicle body is that they can be times bigger than their concept counterparts and can thus require considerably more time for structural analysis. To make the approach proposed in this work a feasible alternative for optimization in the concept phase response surface models were introduced. With them the global static and dynamic performance of the body-in-white was represented by means of approximating polynomials. Optimization on such mathematical models is fast, so the choice of the optimization algorithm is not limited only among local-search strategies. In the current study Genetic Algorithm was used to increase the chances for finding better design alternatives. Two different optimization problems were defined and solved. Their final solutions were presented and compared in terms of structural modifications and resulting responses. The approach in this paper can be successfully used in the concept phase as it is fast and reliable and at the same time it avoids the problems typical for concept models.

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