University of Salford Acoustics Projects

• Project type: Industry-driven
• Supervisors: David Waddington and Bill Davies, University of Salford
• Project Partner: DEFRA (Department for Environment, Food & Rural Affairs)

Noise is the second most harmful environmental pollutant according to the World Health Organisation. It is also “neglected” and in need of more research according to a 2023 House of Lords Report. You will choose one of the following:

1. Neighbour noise.
2. Environmental sound assessment and aural diversity.

1. Neighbour noise is a widespread problem that negatively impacts millions of people globally. It disrupts sleep, reduces enjoyment of home, and can lead to conflict. Despite its prevalence, there are significant gaps in our understanding of neighbour noise. This PhD project aims to address these gaps by: (a) Developing a more comprehensive understanding of neighbour noise that considers not just volume but also characteristics like duration, frequency, and predictability. (b) Improving methods for assessing neighbour noise by exploring the use of advanced acoustic sensors and subjective surveys. And (c) Developing better statistical methods to quantify the impact of neighbour noise on health and well-being. This project will use a mixed-methods approach, combining quantitative data collection with qualitative analysis of resident experiences.

2. When environmental sound is assessed and regulated, this almost always involves an assumption of a person with normal hearing. This PhD will devise and test ways of adapting current assessment methods to better represent the response of an aurally diverse population. There are many possible approaches, but it is envisaged that the research will examine two or three different kinds of hearing difference – for example, age-related hearing loss, auditory processing disorder and/or noise sensitivity. Controlled listening tests will probably feature, as will statistical modelling. Careful experimental design will be crucial. The evidence gathered and tools during the PhD will aid the development of robust methods for the assessment and design of soundscapes with a diversity of novel unconventional sound sources.

The research would suit graduates in psychology, science or engineering who have an interest in psychoacoustics. Experience in statistics and programming will be useful.

• Project type: Industry-driven
• Supervisors: Joshua Meggit and Levingshan Augusthus Nelson, University of Salford
• Project Partner: Farrat
• The project partner is offering an additional stipend of £10,000 for applicants from underrepresented groups.

PhD Title: Optimising Vibration Isolation Systems in Building Design: Balancing Vibration Isolation Performance, Structural Integrity and Material Quantity

Research Objective: The key objective of this PhD is to quantify and optimise the various ways of handling lateral forces and ground pressure on building vibration isolation systems with the aim to minimise the amount of concrete required. This research will contribute to enhancing urban living quality by mitigating the impact of ground and structure-borne noise on health and well-being, specifically reducing annoyance and sleep disturbances. Additionally, it will support the construction industry’s transition to net-zero practices.

Methodology: The research will involve Finite Element models to simulate various scenarios, along with laboratory and field testing to validate the models. The study will explore key areas related to building design, including the effects of soil/ground pressure and the optimization of structural elements such as columns and cores, to improve performance and material efficiency for various isolation scenarios. The goal is to produce practical, validated design recommendations and performance prediction tools.

Requirements for the PhD Candidate: The ideal candidate will be a civil or structural engineer with a strong interest/background in structural dynamics, measurements / experimentation and experience in Finite Element modelling techniques. All combined with an overall desire to support a better world through the construction industry achieving net-zero and enhancing quality of life in the urban/city environment.

• Project type: Industry-driven
• Supervisors: 1) Antonio Torija Martinez and 2) Zuzanna Podwinska, University of Salford
• Project Partner: HEAD Acoustics

You will focus on one of the following:

1. Development of psychoacoustic models for sharpness and impulsiveness

Sound quality metrics are often used to analyse complex sound scenarios, e.g. for soundscape applications. Sound quality can also affect the health and well-being of people in a given environment. Therefore, it is of the utmost importance that the definition of good sound quality in a given context is as precise as possible. In this regard, psychoacoustic indicators are usually used to develop these metrics.

In recent years, several psychoacoustic standards have been published based on the Sottek Hearing Model: the SHM Loudness, a new approach to time-varying loudness based on a nonlinear combination of partial tonal and noise loudness (as part of the SHM Tonality, standardised in ECMA 418-2) to better account for the fact that the loudness of tonal components, i.e. tonal loudness, may have a stronger influence on loudness perception than the loudness caused by the other components, i.e. noise loudness. In addition, there are standards for psychoacoustic modulation analysis: the SHM Roughness for the assessment of fast modulated sounds (standardised in ECMA 418-2) and the SHM Fluctuation Strength, an adapted model for slow modulated sounds (to be standardised in 2024).

Other very important psychoacoustic parameters are sharpness and impulsiveness. Existing sharpness models have some drawbacks: for example, they do not adequately account for loudness and temporal effects, and they do not provide sharpness values that linearly correspond to human perception. In addition, there is only a German standard for stationary sounds. For impulsiveness there is currently no standard, but a model based on the Sottek Hearing Model published in 1993.

You will develop improved models for sharpness and impulsiveness based on the recently standardised Sottek Hearing Model.

2. Evaluation of complex acoustic environments using sound source separation methods:

Acoustic environments often consist of a multitude of different individual sound sources with varying acoustic qualities. Despite this, groups of participants can reliably reach a consensus regarding the most dominant sound sources and the most important qualities of such environments.

When perceiving an acoustic environment, humans intuitively separate different sound sources using both ear signals. Previous studies have shown that sound sources with a clearly perceived direction are often judged differently from non-directional sources. For example, sound sources with annoying qualities are rated as even more annoying when they have a clear direction. Therefore, identifying dominant sources and their directions from a binaural recording can help to better assess the perceived qualities of a given acoustic environment.

Objectives:

• Algorithmic identification of dominant sources and their direction from binaural recordings.
• Separation of dominant sources based on direction for individual auralisation and analysis.
• Extension of both approaches to multi-channel spatial audio (Ambisonics) recordings.

Either topic would suit graduates with a solid understanding and expertise in signal processing and coding. Experience in statistics (or machine learning) and jury testing will be useful.