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排序方式: 共有103条查询结果,搜索用时 15 毫秒
1.
Moon‐Kyun Shin Gyung‐Jin Park 《International journal for numerical methods in engineering》2005,64(5):599-617
Optimization has been successfully applied to systems with a single discipline. Since many disciplines are involved in a coupled fashion in modern engineering, multidisciplinary design optimization (MDO) technology has been developed. MDO algorithms are designed to solve the coupled aspects generated from the interdisciplinary relationship. In a general MDO algorithm, a large design problem is decomposed into smaller ones which can be easily solved. Although various methods have been proposed for MDO, research is still in the early stage. This study proposes a new MDO method which is named MDO based on independent subspaces (MDOIS). Many real engineering problems consist of physically separate components and they can be independently designed. The inter‐relationship occurs through coupled physics. MDOIS is developed for such problems. In MDOIS, a large system is decomposed into small subsystems. The coupled aspects are solved via system analysis which solves the coupled physics. The algorithm is mathematically validated by showing that the solution satisfies the Karush–Kuhn–Tucker condition. Copyright © 2005 John Wiley & Sons, Ltd. 相似文献
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D. Ryan Breese Gregory Beaucage 《Current Opinion in Solid State & Materials Science》2004,8(6):439-448
Modeling changes in the physical properties of oriented semi-crystalline polymer films is beneficial for understanding the fundamentals associated with structure property relationships and could be used for developing new polymer films with significantly enhanced physical properties. Relating the molecular changes observed in oriented polymer films to inherent polymer characteristics provides valuable insight for the development of new polymers which exhibit enhanced physical properties upon orientation. Modeling efforts will be reviewed that have attempted to use fiber composite theory to explain the transitions seen during the orientation process. 相似文献
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We present a multidisciplinary design optimization method for the profile and structural reinforcement layout of a ram‐air kite rib. The aim is to minimize the structural elastic energy and to maximize the traction power of a ram‐air kite used for airborne wind energy generation. Because of the large deformations occurring during flight, a fluid‐structure interaction (FSI) routine is included in the optimization, which determines the actual deformed rib geometry and its corresponding aerodynamic characteristics. A qualitative comparison between FSI inclusion and exclusion in the optimization is given. Discrepancies in airfoil profile and structural layout are observed. 相似文献
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1 Introduction Aeroengine turbine blade, working in high temperature, high pressure and high speed conditions, is the key part of gas turbine engine. Structure design of turbine blade is very complicated because not only the geometric elements, such as the shape of exterior and interior surfaces, allocation of lots of features’ and their orientation affected its performance, but also the multidisciplinary design process, including aerodynamics, heat transfer, strength, vibration, etc. as show… 相似文献
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S. Nagendra J.B. Staubach A.J. Suydam S.J. Ghunakikar V.R. Akula 《Structural and Multidisciplinary Optimization》2005,29(3):213-231
The role of uncertainty in information rich design systems is critical to the development of advanced propulsion systems. Future turbine engines would have lower lifetime operating costs similar to current evolving automotive systems. Detailed multi-physics models (thermo-fluid, structural and mechanical systems) and an operational environment are enablers of rapid correction and model-based predictive analyses. Bayesian machine learning paradigms are developed to identify the behavior of turbo-machinery components for preliminary design. The embedded models approach enables systematic evolution from individual components level to the advanced engine. The embedded models approach enables systematic evolution from individual components level to the advanced engine. A rapid response strategy is proposed, for design of turbine disks by using multidisciplinary optimization and neural networks. iSIGHT optimization software is interfaced with ANSYS to find optimum designs for a given set of design boundary conditions (rpm, live rim load, thermals, etc.). The optimum designs obtained from iSIGHT for different set of design conditions are used for machine learning and design knowledge recognition using the neural network technique. The trained network is used to predict responses for design boundary conditions. Responses predicted by the neural network are validated using ANSYS. Discrete design points are chosen from the wide design space of turbine disks. A hierarchical neural network approach provides an ability to quickly train the network and predict responses (weight, stresses, burst margin, etc.) for applied design conditions. This basic building process involves four steps starting from identifying design boundary conditions to the prediction of design shape for the disk. Sensitivity-based scaling rules are developed, to accommodate different materials for the disk. The technique is developed in RAPIDDISK, which provides an optimal preliminary shape and design attributes for a turbine disk. 相似文献
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