课题基金 / 基金详情

Stochastic transfer operator methods for modelling the vibroacoustic properties of newly emerging transport structures

Stochastic transfer operator methods for modelling the vibroacoustic properties of newly emerging transport structures
用于模拟新兴运输结构的振动声学特性的随机传递算子方法
批准号:
EP/M027201/1
负责人:
David James Chappell
金额:
$11.66万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2016
资助国家:
英国
项目状态:
已结题
起止时间:
2016 至 --

项目摘要

项目成果

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
The rapid growth of computing power during the last 50 years has given rise to a whole simulation industry serving the needs of the manufacturers looking to design products in an optimal manner, without the time and costs associated with building a series of physical prototypes. Design and construction decisions are increasingly made by means of virtual prototyping as part of Computer Aided Engineering (CAE), and efficient simulation tools in all areas of engineering are sought after. Noise and vibration are particularly important performance aspects in the design of many mechanical systems. High noise and vibration levels can be damaging to structures and to their users (potentially causing hearing loss, for example). Developing computational techniques to improve our understanding of the vibration and acoustics of complex built-up structures can enhance performance, speed up the design cycle and ultimately result in safer and less noisy products.Methodologies have long been sought after for modelling large-scale complex structures such as aircraft, trains and cars. The sheer size of these structures makes building full-scale physical prototypes expensive, and often infeasible. It also poses problems for simulation methods and limits many CAE products to low frequencies, where computational run times are relatively low and uncertainties have little influence on the vibrational behaviour. Uncertainties arising during the manufacturing process (for example, in material properties or physical dimensions) can lead to large variations in the levels of noise and vibration of a structure at high frequencies, and so mechanical engineers have turned to statistical methods to instead predict averages of these noise and vibration levels. Unfortunately, these statistical methods are based on a set of assumptions that are hard to control and generally only fulfilled for more traditional structural designs. They are not fulfilled for the large curved and moulded components used today. Therefore the CAE tools available at present for simulating mid- and high- frequency noise and vibration do not meet the needs of engineers in the transport sector. As a result of the 2008 climate change act in the UK and similar initiatives around the globe, transport industries are undergoing a period of great change. Alternative fuel sources and lightweight materials are two of the major areas of development. An increasing number of hybrid and electric powered vehicles are appearing on the market and the use of lightweight and composite materials is increasing across the sector. Engineers were already in need of new and more versatile simulation methods at mid-to-high frequencies, but the increasing popularity of lightweight materials and electric power sources has compounded this situation for three main reasons:- only estimates of the material properties for newly manufactured lightweight and composite materials are available introducing considerable uncertainty into the model;- lightweight and composite materials typically emit noise at higher frequencies than more traditional steel or aluminium based structures;- sources of noise and vibration (eg. electric motors, air resistance etc.) will mostly be at high frequencies.In this proposal, random (or stochastic) transfer operator methods will be developed for modelling mid-to-high frequency structural vibrations in large complex structures. These methods will have the advantages of the current statistical approaches in terms of being able to model uncertainties in the structural design and materials, but crucially will be applicable to a far wider range of structures, including large moulded components and novel lightweight materials. The approach to be developed therefore has the potential to provide a black-box design tool for mechanical engineers looking to develop the next generation of green and lightweight transport structures.
期刊论文(9)
专著(0)
科研奖励(0)
会议论文
Uncertainty quantification for phase-space boundary integral models of ray propagation
射线传播相空间边界积分模型的不确定性量化
DOI: 10.1016/j.wavemoti.2018.08.010
发表时间: 2019
期刊: Wave Motion
影响因子: 2.4
作者: [Chappell D]
通讯作者: Chappell D
On discretisation schemes for a boundary integral model of stochastic ray propagation
随机射线传播边界积分模型的离散化方案
DOI: --
发表时间: 2017
期刊:
影响因子: --
作者: [Janis Bajars]
通讯作者: Janis Bajars
Boundary integral models of stochastic ray propagation: Discretisation via the collocation and Nyström methods
随机射线传播的边界积分模型:通过搭配和 Nyström 方法进行离散化
DOI: 10.1063/1.4981994
发表时间: 2017
期刊:
影响因子: --
作者: [Bajars J]
通讯作者: Bajars J
Modelling parametric uncertainties in vibroacoustics using a DEA approach
使用 DEA 方法对振动声学中的参数不确定性进行建模
DOI: --
发表时间: 2017
期刊:
影响因子: --
作者: [David J Chappell]
通讯作者: David J Chappell
9
    国内基金
    海外基金
    基于电荷泄漏与静电击穿效应的摩擦纳米发电机及电荷转移机制研 究
    • 批准号:
    • 项目类别:
      省市级项目
    • 资助金额:
      --
    • 批准年份:
      2024
    • 负责人:
      贺文聪
    • 依托单位:
    损伤线粒体传递机制介导成纤维细胞/II型肺泡上皮细胞对话在支气管肺发育不良肺泡发育阻滞中的作用
    • 批准号:
      82371721
    • 项目类别:
      面上项目
    • 资助金额:
      49.00万元
    • 批准年份:
      2023
    • 负责人:
      王星云
    • 依托单位:
    具有时序迁移能力的Spiking-Transfer learning (脉冲-迁移学习)方法研究
    • 批准号:
      61806040
    • 项目类别:
      青年科学基金项目
    • 资助金额:
      20.0万元
    • 批准年份:
      2018
    • 负责人:
      解修蕊
    • 依托单位:
    亚纳米单分子定位技术研究化学修饰对蛋白-膜相互作用的干预
    • 批准号:
      91753104
    • 项目类别:
      重大研究计划
    • 资助金额:
      70.0万元
    • 批准年份:
      2017
    • 负责人:
      李明
    • 依托单位: