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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

基本信息

批准号：
EP/M027201/1
负责人：
David James Chappell
金额：
$ 11.66万
依托单位：
Nottingham Trent University
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
起止时间：
2016 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FM027201%2F1
关键词：
Stochastic transfer operator methods modelling

项目摘要

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.

在过去的50年中，计算能力的快速增长已经产生了一个完整的仿真行业，该行业服务于制造商的需求，这些制造商希望以最佳的方式设计产品，而无需与构建一系列物理原型相关的时间和成本。作为计算机辅助工程（CAE）的一部分，设计和施工决策越来越多地通过虚拟样机进行，并且在所有工程领域都需要高效的仿真工具。噪声和振动是许多机械系统设计中特别重要的性能方面。高噪音和振动水平可能会对建筑物及其使用者造成损害（例如，可能导致听力损失）。开发计算技术来提高我们对复杂组合结构的振动和声学的理解，可以提高性能，加快设计周期，并最终产生更安全、噪音更小的产品。长期以来，人们一直在寻求对飞机、火车和汽车等大型复杂结构进行建模的方法。这些结构的庞大规模使得建造全尺寸的物理原型变得昂贵，而且往往不可行。这也给仿真方法带来了问题，并将许多CAE产品限制在低频，其中计算运行时间相对较低，不确定性对振动行为的影响很小。在制造过程中出现的不确定性（例如，材料特性或物理尺寸）可能导致结构在高频下的噪声和振动水平发生很大变化，因此机械工程师转向统计方法来预测这些噪声和振动水平的平均值。不幸的是，这些统计方法是基于一组难以控制的假设，通常只适用于更传统的结构设计。它们不适用于今天使用的大型弯曲和模制部件。因此，目前可用于模拟中高频噪声和振动的CAE工具不能满足运输部门工程师的需求。由于2008年英国气候变化法案和地球仪的类似举措，运输行业正在经历一个巨大的变化时期。替代燃料来源和轻质材料是两个主要的发展领域。越来越多的混合动力和电动汽车出现在市场上，轻质和复合材料的使用在整个行业中越来越多。工程师们已经在需要新的和更通用的模拟方法在中高频，但越来越普及的轻质材料和电源加剧了这种情况下，有三个主要原因：-只有估计的材料性能的新制造的轻质和复合材料是可用的引入相当大的不确定性模型;- 轻质和复合材料通常比更传统的钢或铝基结构发出更高频率的噪音;-噪音和振动源（例如，电动机、空气阻力等）将主要是在高频率。在这个建议中，随机（或随机）传递算子方法将被开发用于模拟大型复杂结构中的中高频结构振动。这些方法将具有当前统计方法的优点，能够模拟结构设计和材料中的不确定性，但关键是将适用于更广泛的结构，包括大型模制部件和新型轻质材料。因此，开发的方法有可能为机械工程师提供一个黑盒设计工具，希望开发下一代的绿色和轻质运输结构。