Ultrasonic propagation in complex media: correlated spatial distributions and multiple dispersed phases
Lead Research Organisation:
University of Manchester
Department Name: Mathematics
Abstract
Abstracts are not currently available in GtR for all funded research. This is normally because the abstract was not required at the time of proposal submission, but may be because it included sensitive information such as personal details.
Publications
Agosti A
(2018)
The constitutive relations of initially stressed incompressible Mooney-Rivlin materials
in Mechanics Research Communications
García Neefjes E
(2022)
A unified framework for linear thermo-visco-elastic wave propagation including the effects of stress-relaxation
in Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences
Gower A
(2017)
A New Restriction for Initially Stressed Elastic Solids
in The Quarterly Journal of Mechanics and Applied Mathematics
Gower A
(2018)
Characterising particulate random media from near-surface backscattering: A machine learning approach to predict particle size and concentration
in EPL (Europhysics Letters)
Gower A
(2019)
Multiple Waves Propagate in Random Particulate Materials
in SIAM Journal on Applied Mathematics
Gower A
(2021)
Effective waves for random three-dimensional particulate materials
in New Journal of Physics
Gower A
(2017)
A New Restriction for Initially Stressed Elastic Solids
in The Quarterly Journal of Mechanics and Applied Mathematics
Gower AL
(2018)
Reflection from a multi-species material and its transmitted effective wavenumber.
in Proceedings. Mathematical, physical, and engineering sciences
Gower AL
(2017)
A new restriction for initially stressed elastic solids
in The Quarterly Journal of Mechanics and Applied Mathematics
Gower AL
(2019)
A proof that multiple waves propagate in ensemble-averaged particulate materials.
in Proceedings. Mathematical, physical, and engineering sciences
| Description | 1) We have answered the question as to what can be measured about a random medium by using backscattered waves, emitted from and received at a single source. That is, measuring waves that are directly reflected back is one of the simplest possible measurements for a complex medium. Yet it has previously not been possible, with theory alone, to answer what properties of a random medium can be predicted by measuring just reflected waves. We were able to make progress by introducing a mixture of theory and machine learning techniques. An associated paper is currently under review. 2) We deduced the effective wavenumber (characterising propagation in a medium) associated with, and reflection from, a material comprising multiple types of particles (multi-species). These expressions have been derived for the first time for densely packed particles. We demonstrated failures in the alternatives used in the literature, published a paper on the subject, and are promoting the work by giving talks and visiting other research groups. |
| Exploitation Route | We will, as the project develops, aim to incorporate the analytical results, validated by numerical simulations and experimental work, into tools for making useful predictions in a variety of industries. Our work on using machine learning also serves as a prototype to demonstrate, to industry and a wider audience, what future devices could be designed that make use of theory and machine learning. |
| Sectors | Aerospace, Defence and Marine,Agriculture, Food and Drink,Chemicals,Education,Pharmaceuticals and Medical Biotechnology |
| Description | We have written and made publicly available software to exhibit wave scattering phenomena. The software produces videos of wave motion, which we are using to promote physics and mathematics to a wider audience. In particular one of the investigators has used this software in public engagement talks to promote the use of acoustics as a mechanism for non-destructive testing. This project also led to Gower's permanent position at the University of Sheffield in the Department of Mechanical Engineering. In this role he secured a New Investigator Award with partner industry collaborator Johnson Matthey (EP/V012436/1). Gower has gone on to have a significant impact in engineering in Sheffield and particularly in terms of engagement with industry. |
| First Year Of Impact | 2016 |
| Sector | Other |
| Impact Types | Cultural,Economic |
| Description | Determination of particle attributes via novel active acoustics |
| Amount | £124,186 (GBP) |
| Organisation | Johnson Matthey |
| Sector | Private |
| Country | United Kingdom |
| Start | 10/2021 |
| End | 10/2025 |
| Description | Sensing Dense Particulate Materials |
| Amount | £232,927 (GBP) |
| Funding ID | EP/V012436/1 |
| Organisation | Engineering and Physical Sciences Research Council (EPSRC) |
| Sector | Public |
| Country | United Kingdom |
| Start | 08/2021 |
| End | 12/2023 |
| Title | Backscattering from randomly placed Dirichlet particles |
| Description | A simulated data set of backscattered waves, governed by the 2D wave equation, from randomly placed Dirichlet particles. The particles are circular with 0.2 < radius < 2.0 and 1% < volume fraction < 20%. The incident wave is of the form ei k (x - xR - t) where the particles are placed in the halfspace x>0 and the backscattering is emitted and received at (xR, 0) with xR = -10.0. The data named bunny and bunnytest is for incident waves with 0 < k < 1 (where the term e- i k t factors out). The data named train and test is for incident waves of the form e0.1(x - xR - t)^2, with 9.5 < t < 98. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2018 |
| Provided To Others? | Yes |
| Impact | With this data, we were able to use machine learning algorithms to determine, for the first time, what can be measured from a random particulate medium from just direct backscattered waves. |
| URL | https://zenodo.org/record/1126642#.WqKh5nXFKCg |
| Description | Collaborative links between Manchester, Leeds and Loughborough |
| Organisation | Loughborough University |
| Department | School of Electronic, Electrical and Systems Engineering |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | This is a collaborative project whereby we will input the mathematoical modelling. |
| Collaborator Contribution | This is a collaborative project whereby Loughborough will offer the computational work and Leeds will input experimental effort. |
| Impact | None yet |
| Start Year | 2015 |
| Description | Collaborative links between Manchester, Leeds and Loughborough |
| Organisation | University of Leeds |
| Department | School of Food Science and Nutrition Leeds |
| Country | United Kingdom |
| Sector | Academic/University |
| PI Contribution | This is a collaborative project whereby we will input the mathematoical modelling. |
| Collaborator Contribution | This is a collaborative project whereby Loughborough will offer the computational work and Leeds will input experimental effort. |
| Impact | None yet |
| Start Year | 2015 |
| Title | EffectiveWaves.jl |
| Description | A package to calculate the effective waves travelling in materials comprised of randomly distributed particles or inclusions. |
| Type Of Technology | Software |
| Year Produced | 2017 |
| Open Source License? | Yes |
| Impact | We used this software to show counter intuitive results of multiple scattering involving multi-species particles. |
| Title | MultipleScattering-Mathematica |
| Description | A Mathematica package to calculate exact multiple scattering, in time and frequency, according to the 2D wave equation. |
| Type Of Technology | Software |
| Year Produced | 2017 |
| Open Source License? | Yes |
| Impact | This is an educational software, which easily allows users to place circular particles, specify incident waves and create graphics that demonstrate multiple scattering. |
| Title | MultipleScattering.jl |
| Description | A Julia library for simulating, processing, and plotting multiple scattering of acoustic waves. |
| Type Of Technology | Software |
| Year Produced | 2018 |
| Open Source License? | Yes |
| Impact | This software is a high performance software. It has allowed us to do a large number of multiple scattering simulations, which has lead to new insight about what properties of particulate materials can be predicted from backscattered waves. |
| URL | https://arxiv.org/abs/1801.05490 |
| Description | Outreach talks: Science Showdown - Manchester - 2017 |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Undergraduate students |
| Results and Impact | Summary: Isn't science awesome? But are you convinced your field is the most awesome of them all? Do you save lives, discover truly fundamental properties of nature, master logic and reasoning, create mind-blowing technology, understand how the Universe works, or something along those lines? All the willing speakers will be asked to give a short talk of exactly p minutes (yes, 3m 14s), not exceeding 2 slides to talk about something super interesting in science. This doesn't have to be directly related to your own projects and props are always encouraged! Impact: the audience of students and general public voted on the best talks. The later discussions indicated that many greatly changed their views of the role of physics and mathematics in our society. |
| Year(s) Of Engagement Activity | 2017 |
| URL | https://www.eventbrite.co.uk/d/united-kingdom--manchester/mcrc-science-showdown/ |
| Description | Talks on sensing with sound |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | National |
| Primary Audience | Schools |
| Results and Impact | I have given talks to about 5 schools and several events such as Pint of Science where I showed how to use sound to see in the dark. Below is an example of summary I give about the talk/event. In the pitch black, a bat speeds through the air and swoops around a tree to eat a tasty insect snack. Bats avoid trees and find snacks just by using sound. Scientists have taken this further and are using sound to detect flaws in the ancient UK sewage system! We are now designing a swarm of small robots that use sound to detect cracks and blocks in sewers. In this talk, you will learn a physicist's approach to use sound, like a bat, to find things in the dark. Will you be able to recognise the sound of a blocked sewer? The session will cover 1) a fun application, the UK sewers, 2) I will teach how to approach problems like a physicist, and 3) there will be lots of videos and some interaction with the audience. Further 2020 is the international year of sound (https://sound2020.org/). Maintaining the UK sewer system is a huge issue. Everytime we suspect there is a major leak we need to dig up large parts of our roads, causing traffic jams, air pollution from dust, and the whole operation is very costly. To make matters worse, much of our sewers are ancient, falling apart, and we have no idea what pipes are where. Not to mention that it is difficult to convince people to go down there to inspect the sewers. How do we now maintain this ancient labyrinth? A team, led by the University of Sheffield, have the answer: we will develop a swarm of small robots to swim through our sewers and detect cracks and blocks. After presenting the application, I will pose the question: how do these little robots detect things in the dark? I will then show how, with a physics approach, we can break this problem down into simple manageable smaller problems. These small problems involve simple trigonometry and the solution is illustrated with lots of videos from simulations. From there, we build back up to the complex problem. The talk will involve lots of videos and have strong visual aids throughout. Videos will include bats flying around, sound sensors in pipes, and computer simulations. I will ask the audience to hear sounds and guess what they heard. Did the sound come from a blocked sewer or not? To finish we end with how machine learning is better at recognising sounds then we are. |
| Year(s) Of Engagement Activity | 2018,2019,2020,2021,2022 |
| Description | Tweeting videos on particle scattering |
| Form Of Engagement Activity | Engagement focused website, blog or social media channel |
| Part Of Official Scheme? | No |
| Geographic Reach | International |
| Primary Audience | Public/other audiences |
| Results and Impact | Using my twitter account, I posted results and animations related to the research from this grant with the hashtag #WhatTheWave. The animations had thousands of engagements. |
| Year(s) Of Engagement Activity | 2018,2019,2020,2021 |
| URL | https://twitter.com/arturgower |