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Reliability-based design optimization of airframe components

机译:基于可靠性的机身部件设计优化

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A stochastic design optimization (SDO) methodology has been developed to design components of an airframe structure. The design is obtained as a function of the risk or reliability. Uncertainties in load, strength, and material properties are treated as distribution functions. Design constraints and optimum weight become functions of reliability. Weight versus reliability traces out an inverted S-shaped graph. The centre of the graph corresponds to 50 per cent probability of success. A heavy design with weight approaching infinity could be produced for a near-zero rate of failure. Weight can be reduced to a small value for the most failure-prone design. Reliability can be changed for different components of an airframe structure. The SDO capability is obtained by combining three codes. MSC/Nastran is the deterministic analysis tool, the fast probability integration of the NESSUS (numerical evaluation of stochastic structures under stress) software is the probabilistic calculator, and NASA (National Aeronautics and Space Administration) Glenn Research Center's testbed CometBoards is the optimizer. The SDO capability requires a finite-element model, a material model, a load model, and a design model. The stochastic optimization concept is illustrated considering an academic example and a real-life raked wingtip structure of the Boeing 767-400 extended range airliner made of metallic and composite materials.
机译:已经开发出一种随机设计优化(SDO)方法来设计机身结构的组件。根据风险或可靠性获得设计。载荷,强度和材料特性的不确定性被视为分布函数。设计约束和最佳重量成为可靠性的函数。重量与可靠性的关系描绘出一个倒S形图。图的中心对应于成功概率的50%。可以产生重量接近无限的重型设计,以实现接近零的故障率。对于最容易发生故障的设计,可以将重量减小到很小的值。可以更改机身结构的不同组件的可靠性。通过组合三个代码获得SDO功能。 MSC / Nastran是确定性分析工具,NESSUS(在压力下随机结构的数值评估)软件的快速概率积分是概率计算器,而NASA(美国国家航空航天局)Glenn研究中心的试验台CometBoards是优化器。 SDO功能需要有限元模型,材料模型,载荷模型和设计模型。考虑到由金属和复合材料制成的Boeing 767-400增程客机的一个学术实例和真实的倾斜翼尖结构,对随机优化概念进行了说明。

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