Intelligent Cost-of-Ownership Prediction for Rotorcraft Engines Operating in Harsh Environments
Lead Research Organisation:
University of Manchester
Department Name: Mechanical Aerospace and Civil Eng
Abstract
For many years, the Ministry of Defence (MoD) operators have been utilising their air platforms in sandy and dusty environments with insufficient understanding of the damage and cost of ownership issues this can cause. This damage ranges from engine degradation due to ingested particulate, to airframe abrasion and blade erosion on rotorcraft. All of these place additional maintenance costs and considerations on the operator and in exceptional circumstances can result in the total loss of the platform. Whilst the damage that occurs on platforms operating in sand and dust can be defined in a qualitative manner, attempts to quantify damage and the rate at which it transpires is an ongoing process. There is thus a motivation to better understand and quantify engine damage and to ultimately carry out intelligent predictions of platform damage and the punitive costs associated with it. This ICASE project aims to make advances in the quantitative knowledge of gas turbine engine damage due to particulate ingestion and is a new partnership between The Defence Science and Technology Laboratory (dstl), the School of Mechanical, Aerospace and Civil Engineering (MACE) and the School of Earth, Atmospheric and Environmental Science (SEAES) from the University of Manchester.
Studentship Projects
| Project Reference | Relationship | Related To | Start | End | Student Name |
|---|---|---|---|---|---|
| EP/P510579/1 | 01/10/2016 | 30/09/2021 | |||
| 1961380 | Studentship | EP/P510579/1 | 01/07/2017 | 20/07/2021 | Matthew Ellis |
| Description | A method to predict damage to gas turbine engines due to particle deposition has been developed. This novel method provides a faster means of assessing damage compared to existing techniques. This method has been incorporated into an existing gas turbine performance program, allowing real-world events to be replicated and future engine damage to be predicted. |
| Exploitation Route | The fundamental approaches and non-dimensional parameters proposed and used in the particle deposition model may have wider applications in the fields of particle transport and particle fouling. The outcomes of the wider modelling approach can be used by aircraft operators to better predict their maintenance schedules in order to understand the implications of flying in airborne dust on their operating costs. |
| Sectors | Aerospace, Defence and Marine,Communities and Social Services/Policy,Energy,Environment |
| Description | Royal Aeronautical Society Aerospace Speakers Travel Grants |
| Amount | £500 (GBP) |
| Organisation | Royal Aeronautical Society (RaES) |
| Sector | Learned Society |
| Country | United Kingdom |
| Start | 09/2018 |
| End | 09/2018 |
| Title | Degraded Engine Performance Code |
| Description | The model couples the reduced-order particle deposition model developed during the award with a commercial gas turbine performance code. This allows the performance degradation of engines which ingest mineral dusts to be predicted. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2021 |
| Provided To Others? | No |
| Impact | The model has been used to replicate known aircraft encounters with volcanic ash clouds providing validation of the method. |
| Title | Interaction Probability Dataset |
| Description | This contains data pertaining to Figures 11 to 14 from the research article, Particle-Vane Interaction Probability in Gas Turbine Engines. The data results from a multiphase computational fluid dynamics simulation of the General Electric E3 nozzle guide vane. |
| Type Of Material | Database/Collection of data |
| Year Produced | 2019 |
| Provided To Others? | Yes |
| Impact | Publication: Particle-Vane Interaction Probability in Gas Turbine Engines |
| Title | Reduced-Order Particle Deposition Model |
| Description | The model allows the deposition of particles in gas turbine engines to be predicted using a reduced-order approach, resulting in greatly reduced computing time. |
| Type Of Material | Computer model/algorithm |
| Year Produced | 2019 |
| Provided To Others? | Yes |
| Impact | The model has been used in conjunction with an existing, commercial gas turbine engine performance code, which allows the effects of particle deposition damage on whole engine performance to be quantified. |
| Description | NATO AVT-250 |
| Organisation | North Atlantic Treaty Organization (NATO) |
| Department | NATO Science and Technology Organization |
| Country | Belgium |
| Sector | Academic/University |
| PI Contribution | Provided a briefing at a panel business meeting to the NATO Science and Technology Organisation (STO), Advanced Vehicle Technology (AVT) working group 250 - Gas Turbine Engine Environmental Particulate Foreign Object Damage [EP-FOD]. Provided sections for the final report produced as the end of the working group's activities. DOI - 10.14339/STO-TR-AVT-250 |
| Collaborator Contribution | The project sponsor, DSTL are an active member of the NATO STO on behalf of the UK Ministry of Defence |
| Impact | Collaboration is multi-disciplinary, between industry, government, academia covering both the engineering and earth sciences disciplines |
| Start Year | 2019 |
| Description | Research Seminar Presentation |
| Form Of Engagement Activity | A talk or presentation |
| Part Of Official Scheme? | No |
| Geographic Reach | Local |
| Primary Audience | Postgraduate students |
| Results and Impact | Presentation to the University of Manchester Geosciences research seminar series on the topic 'Aircraft Engines and Atmospheric Dust' |
| Year(s) Of Engagement Activity | 2020 |