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.

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.

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.

Multi-objective collaborative multidisciplinary design optimization using particle swarm techniques and fuzzy decision making

2012 ◽  
Vol 226 (9) ◽  
pp. 2281-2295 ◽  
Author(s):  
Mohammad Reza Farmani ◽  
Jafar Roshanian ◽  
Meisam Babaie ◽  
Parviz M Zadeh
Keyword(s):  
Particle Swarm Optimization ◽  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Optimization Problems ◽  
Particle Swarm ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Fuzzy Decision ◽  
Swarm Optimization ◽  
Multi Objective

This article focuses on the efficient multi-objective particle swarm optimization algorithm to solve multidisciplinary design optimization problems. The objective is to extend the formulation of collaborative optimization which has been widely used to solve single-objective optimization problems. To examine the proposed structure, racecar design problem is taken as an example of application for three objective functions. In addition, a fuzzy decision maker is applied to select the best solution along the pareto front based on the defined criteria. The results are compared to the traditional optimization, and collaborative optimization formulations that do not use multi-objective particle swarm optimization. It is shown that the integration of multi-objective particle swarm optimization into collaborative optimization provides an efficient framework for design and analysis of hierarchical multidisciplinary design optimization problems.

An Adaptive Robust Control for Hard Rock Tunnel Boring Machine Cutterhead Driving System

2015 ◽  
Author(s):  
Chengjun Shao ◽  
Jianfeng Liao ◽  
Xiuliang Li ◽  
Hongye Su
Keyword(s):  
Robust Control ◽  
Dynamic Model ◽  
External Force ◽  
Hard Rock ◽  
Tunnel Boring Machine ◽  
Adaptive Robust Control ◽  
Driving System ◽  
Tunnel Boring ◽  
Rock Tunnel ◽  
Hard Rock Tbm

The cutterhead driving system of tunnel boring machine is one of the key components for rock cutting and excavation. In this paper, a generalized nonlinear time-varying dynamic model is established for the hard rock TBM cutterhead driving system. Parametric uncertainties and nonlinearities and unknown disturbances exist in the dynamic model. An adaptive robust control strategy is proposed to compensate the uncertainties and nonlinearities to achieve precise cutterhead rotation speed control. In order to simulate the comprehensive performances of adaptive robust control controller, three different kinds of external force disturbances are added in this model. Compared to the traditional PID, ARC can effectively handle the different kinds of external force disturbances with sufficient small tracking errors.

Multidisciplinary Design Optimization: A New Way to Bring Softer Bows

2008 ◽  
Author(s):  
Zhiqiang Hu ◽  
Weicheng Cui ◽  
Jianmin Yang
Keyword(s):  
Design Optimization ◽  
Multidisciplinary Design Optimization ◽  
Optimization Method ◽  
Collaborative Optimization ◽  
Multidisciplinary Design ◽  
Force Density ◽  
Optimization Analysis ◽  
Resistance Reduction ◽  
Collision Force ◽  
Bulbous Bow

It is well known that sharp bulbous bow has a good performance on ship resistance reduction, but it is also threatens the struck ships and the environment greatly. For their own economy profit, ship owners would like the bulbous bow to be designed sharp and rigid. However, from the viewpoint of environmental protection, the bulbous bow should be designed blunt and soft. Multidisciplinary Design Optimization (MDO) is a prosperous design concept and technique, to reconcile this problem effectively. The basic concept and theories of MDO are introduced in this paper. An optimization analysis is accomplished on the bulbous bow design for a container ship, using Collaborative Optimization Method. The characters of the bulbous bow on resistance reduction, collision force density and structural strength requirement are all considered at the same time. A compatible bulbous bow can be obtained by this way.

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.

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