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引起了整个模拟行业，该行业满足了希望以最佳方式设计产品的需求，而没有与建立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，通过虚拟原型制作（CAE）制定了设计和施工决策，并寻求各个工程领域的有效仿真工具。噪声和振动是许多机械系统设计中特别重要的性能方面。高噪声和振动水平可能会损害结构及其用户（例如，可能导致听力损失）。开发计算技术以提高我们对复杂建筑结构的振动和声学的理解可以提高性能，加快设计周期的速度，并最终导致更安全，更少的嘈杂产品。长期以来一直在寻求建模大规模复杂结构（例如飞机，火车，火车和汽车）的建模。这些结构的巨大尺寸使建造全尺寸的物理原型昂贵，而且通常是不可行的。它还给仿真方法带来了问题，并将许多CAE产品限制为低频，其中计算运行时间相对较低，并且不确定性对振动行为的影响很小。在制造过程中产生的不确定性（例如，在材料特性或物理尺寸中）会导致噪声水平和高频下结构的振动水平发生较大差异，因此机械工程师已转向统计方法，以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，通常仅对更传统的结构设计实现。对于当今使用的大型弯曲和模制的组件，它们没有实现。因此，目前可用于模拟中和高频噪声和振动的CAE工具无法满足运输部门工程师的需求。由于2008年英国的《气候变化法》和全球类似举措，运输行业正在经历巨大变化的时期。替代燃料来源和轻质材料是主要开发领域的两个。市场上出现了越来越多的混合动力和电动车辆，整个行业的轻巧和复合材料的使用正在增加。工程师已经需要在中高频率下使用新的和更通用的模拟方法，但是出于三个主要原因，轻量级材料和电力源的普及到了这种情况，这使这种情况加剧了这种情况： - 新制造的轻量级和复合材料的材料属性估计，可用的材料更高的材料和典型的典型材料均高于更高的材料；结构; - 噪声和振动的来源（例如电动机，空气电阻等）主要是在高频下。在此提案中，将开发出随机（或随机）传输操作员方法，用于对大型复杂结构中的中高频结构振动进行建模。这些方法将在结构设计和材料中对不确定性进行建模，但至关重要的是，将具有当前统计方法的优势，但至关重要的是适用于更广泛的结构，包括大型成型组件和新型轻量级材料。因此，要开发的方法有可能为希望开发下一代绿色和轻量级运输结构的机械工程师提供黑框设计工具。