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Optimisation of Structures Excited by Wind under Consideration of Stochastic Actions and Various Limit States

Optimisation of Structures Excited by Wind under Consideration of Stochastic Actions and Various Limit States
考虑随机作用和各种极限状态的风激结构优化
批准号:
329120866
负责人:
Professor Dr. Tom Lahmer
金额:
$0.0万
依托单位国家:
德国
项目类别:
Research Grants
财政年份:
2017
资助国家:
德国
项目状态:
已结题
起止时间:
2016-12-31 至 2019-12-31

项目摘要

项目成果

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中文摘要
翻译
由于大气边界层的影响,土木结构暴露在复杂的风作用下。细长的结构,如桥梁、塔和桅杆,可能容易受到风产生的空气动力学效应引起的显著振动。实际相关的现象有涡激振动、抖振和颤振。结构的空气动力学行为主要受其几何形状的影响,这就提出了与计算流体动力学模拟相关联的数学形状优化策略,作为提高其空气动力学性能的一种手段。相关极限状态的选择以及效应和阻力参数的随机描述允许基于可靠性的结构响应评估作为优化过程的目标。该项目旨在开发一种方法框架,在随机描述的自然风场的影响下,在各种极限状态下,对结构响应进行稳健优化。为此,对现有的基于伪三维涡旋粒子法的数值模拟方法进行了扩展,并对湍流流入条件和流固耦合进行了扩展,以便对相关影响进行高效的计算分析。具体来说,风场的随机参数将被复制,结构响应将在极限状态下进行分析,并行模拟将与优化策略联系起来。此外,利用现有的基于现象分析的激励机制模型,如准静态气动力系数、涡流脱落的力幅、Strouhal数、Scanlan导数和导纳函数,以提高优化效率,并允许流体和结构的解耦。模拟和优化结果的验证和解释将通过风洞实验和包豪斯大学新数字包豪斯实验室中可视化工具的使用来支持。总之,该项目将产生一种有效的方法,在基于极限状态优化的情况下,对暴露在自然风中的线状结构的风激励进行有效的并行模拟。这也与结构动力学中的类似问题有关。样本分析将用于展示该方法在各种极限状态下改善空气动力学性能的能力。
英文摘要
Civil structures are exposed to complex wind actions as a result of the effects in the atmospheric boundary layer. Slender structures such as bridges, towers and mastes may be prone to significant vibrations induced by the aerodynamic effects arising from the wind. Phenomena of practical relevance are vortex induced vibrations, buffeting and flutter.The aerodynamic behaviour of structures is influenced primarily by their geometry, which proposes mathematical shape optimisation strategies linked to computational fluid dynamics simulations as a means to improve their aerodynamic performance. The selection of relevant limit states and the stochastic description of effect and resistance parameters allow the reliability based assessment of the structural response as the target of the optimisation procedure.This project aims to develop a methodological framework for the robust optimisation of structural response under the effect of a stochastically described natural wind field in respect of various limit states. To this end, existing numerical simulation procedures based on the pseudo-threedimensional Vortex Particle Method with extensions for turbulent inflow conditions and fluid-structure coupling are extended to allow the computationally efficient analysis of the relevant effects. Specifically, the stochastic parameters of the wind field are to be reproduced, the structural response is to be analysed in respect of the limit states and the parallelised simulations are to be linked to the optimisation strategies.Additionally, existing models for a phenomena based analysis of the excitation mechanisms such as quasi-static aerodynamic force coefficients, force amplitudes of vortex shedding, Strouhal Number, Scanlan Derivatives and admittance functions are employed to increase the efficiency of the optimisation and to allow a de-coupling of the fluid and structural. The validation and interpretation of simulation and optimisation results will be supported by experiments in the wind tunnel and the use of visualisation tools in the new Digital Bauhaus Lab of Bauhaus University.In conclusion, the project will yield a validated method for the efficient and parallelised simulation of wind excitation of line-like structures exposed to natural wind in the context of a limit state based optimisation. This will also be relevant for similar problems in structural dynamics. Sample analyses will be used to showcase the ability of the method to improve aerodynamic performance in relation to various limit states.
期刊论文(6)
专著(0)
科研奖励(0)
会议论文
DOI: 10.1016/j.jweia.2022.104911
发表时间: 2021-03
期刊: ArXiv
影响因子: --
作者: [I. Kavrakov;A. McRobie;G. Morgenthal]
通讯作者: I. Kavrakov;A. McRobie;G. Morgenthal
DOI: 10.1016/j.jweia.2019.103971
发表时间: 2019-10
期刊: Journal of Wind Engineering and Industrial Aerodynamics
影响因子: 4.8
作者: [I. Kavrakov;T. Argentini;S. Omarini;D. Rocchi;G. Morgenthal]
通讯作者: I. Kavrakov;T. Argentini;S. Omarini;D. Rocchi;G. Morgenthal
DOI: 10.1016/j.jfluidstructs.2022.103680
发表时间: 2021-09
期刊: Journal of Fluids and Structures
影响因子: 3.6
作者: [Samuel Tesfaye;I. Kavrakov;G. Morgenthal]
通讯作者: Samuel Tesfaye;I. Kavrakov;G. Morgenthal
Prediction of aeroelastic response of bridge decks using artificial neural networks
使用人工神经网络预测桥面气动弹性响应
DOI: 10.1016/j.compstruc.2020.106198
发表时间: 2020
期刊: Computers & Structures
影响因子: 4.7
作者: [Kavrakov, Morgenthal, Lahmer]
通讯作者: Lahmer
共 6 条
    Dam Alteration Identification by Extended Full-Waveform Inversion and Multiphase XFEM
    • 批准号:
      395192382
    • 项目类别:
      Research Grants
    • 资助金额:
      $0.0万
    • 财政年份:
      2017
    • 负责人:
      Professor Dr. Tom Lahmer
    • 依托单位:
    海外基金