风扇/出口导向叶片宽带噪声建模的高保真CFD博士研究员
High-fidelity CFD for fan/OGVs broadband noise modelling
原帖优先：申请材料、截止时间与资格以原帖和学校官方说明为准。
博士招生与资助公告
- 申请年度
- 2027；原帖说明：How to apply Apply now You need to: • choose programme type (Research), 2027/28, Faculty of Engineering and Physical Sciences • select Full time or Part time • search for programme PhD Engineering & the Environment (7175) • add name of the supervisor in section 2 of the application Applications should include: • your CV (resumé) • 2 academic references • degree transcripts and certificates to date • English language qualification (if applicable)
- 最近申请截止
- 2027-09-01
- 全部申请截止
- （Europe/London）
- 资助原文
- Fees and funding Fully funded for UK, EU and International students. Tuition fees will be paid and you'll receive a tax-free living stipend.
- 资助条件
- 未确认申请人可获得资助，请以学校审核结果为准。
- 原帖材料说明
- • your CV (resumé)
- • 2 academic references
- • degree transcripts and certificates to date
- • English language qualification (if applicable)
确定性信息来自对应版本的完整原帖。原帖只提供日期，日末和学校当地时区为本站转换假设。筛选使用最后申请截止；资助与录取以学校审核结果为准。
AI 中文速览
- 研究内容
- 本项目利用高保真计算流体力学（CFD），识别驱动风扇宽带噪声的湍流特征，并为未来航空发动机设计开发快速、准确的模型。研究采用大涡模拟（LES）或分离涡模拟（DES）等尺度解析CFD技术，模拟低速条件下的代表性风扇-出口导向叶片（OGV）级，分析非定常OGV载荷及宽带声学响应，以改进半解析工程模型并验证预测准确性。
- 申请条件
- 申请者需持有工程、数学、物理或紧密相关学科的英国2:1荣誉学士学位或其国际同等学历。具备计算流体力学（CFD）经验（理想情况为叶轮机械或其他内部流动）、尺度解析湍流建模方法（如LES、DES）知识以及数据分析（特别是大型数据集统计分析）经验者为佳。
- 待遇
- 全额资助面向英国、欧盟及国际学生，学费全免，并可获得免税生活津贴。
- 申请方式
- 申请人需通过南安普顿大学系统在线申请，选择研究型项目（Research）、2027/28学年、工程与物理科学学院，选择全职或兼职，搜索“PhD Engineering & the Environment (7175)”项目，并在申请表的第二部分添加导师姓名。
- 材料清单
- 个人简历 (CV)
- 2封学术推荐信
- 迄今为止的学位成绩单与证书
- 英语语言资格证明（如适用）
由 gemini-2.5-flash-lite 生成，博士岗判定置信度 100%。
岗位信息
- 最终轮次截止
- 2027-09-01
- 学科
- 工程
- 合同类型
- 项目资助
- 本站收录
- 内容更新
- 导师
- Dr Long Wu
- 来源
- 南安普顿大学博士研究项目招生 · 最近核对 2026-10-10
- 详情核验
判定依据（原文摘录）
- is_phd
Type of degree Doctor of Philosophy
- english_ok
Fully funded for UK, EU and International students. Tuition fees will be paid and you'll receive a tax-free living stipend.
- bachelor_ok
A UK 2:1 honours degree, or its international equivalent
原文
View all current projects
Postgraduate research project
High-fidelity CFD for fan/OGVs broadband noise modelling
Funding
Fully funded (UK and international)
Type of degree
Doctor of Philosophy
Entry requirements
2:1 honours degree
2:1 honours degree
View full entry requirements
Faculty graduate school
Faculty of Engineering and Physical Sciences
Closing date
1 Sep 2027
On this page
About the project
Potential supervisors
Entry requirements
Fees and funding
How to apply
Contact us
About the project
Potential supervisors
Entry requirements
Fees and funding
How to apply
Contact us
About the project
Ultra High Bypass Ratio (UHBR) aeroengines offer a pathway to quieter, more efficient aviation. However, their larger and slower fans introduce new challenges for broadband noise. Using high-fidelity computational fluid dynamics (CFD), this project will identify the turbulence characteristics that drive fan broadband noise and develop fast, accurate models for future aeroengine design.
Fan wake turbulence interacting with outlet guide vanes (OGVs) is a major source of broadband noise in UHBR aeroengines. Current semi-analytical engineering models rely on simplified representations of the wake turbulence, which may not fully capture the highly non-uniform and anisotropic characteristics of realistic fan wakes. As UHBR designs push towards larger fans and shorter rotor-stator spacing, accurately representing these wake characteristics becomes increasingly important for reliable broadband noise prediction.
This project will employ scale-resolving CFD, such as Large Eddy Simulation (LES) or Detached Eddy Simulation (DES), to simulate representative fan-OGV stages at low-speed conditions. The fan wake will be characterised in terms of turbulence intensity, integral length scales, velocity spectra and spatial coherence, with particular emphasis on their spanwise variation. The predicted turbulence characteristics will be validated against available experimental data. The unsteady OGV loading and broadband acoustic response will then be analysed to quantify how different turbulence characteristics influence broadband noise generation across frequencies and duct modes. The findings will identify the turbulence statistics most relevant to broadband noise prediction. These insights will inform improved semi-analytical engineering models, which will be assessed against existing approaches and experimental data to demonstrate improved prediction accuracy.
The project is jointly funded by Rolls-Royce and the EPSRC Centre for Doctoral Training in Sustainable Sound Futures. You'll be hosted within the Rolls-Royce University Technology Centre (UTC) in Propulsion Systems Noise at the Institute of Sound and Vibration Research (ISVR), University of Southampton. The UTC is a world-leading hub for aeroacoustics research, offering close collaboration with the global Rolls-Royce noise engineering team in the UK and Germany. Find out more about our research.
Training will be tailored to your background and needs, with opportunities to develop expertise throughout the project. We value curiosity, collaboration, persistence and a willingness to learn.
The School of Engineering is committed to promoting equality, diversity inclusivity as demonstrated by our Athena SWAN award. We welcome all applicants regardless of their gender, ethnicity, disability, sexual orientation or age, and will give full consideration to applicants seeking flexible working patterns and those who have taken a career break. The University has a generous maternity policy, onsite childcare facilities, and offers a range of benefits to help ensure employees’ well-being and work-life balance. The University of Southampton is committed to sustainability and has been awarded the Platinum EcoAward.
Potential supervisors
Lead supervisor
Dr Long Wu
PhD, BEng
Senior Research Fellow
Research interests
• Aeroacoustics
• Aerodynamics
• High-Order Numerical Methods
Supervisors
Dr Chaitanya Paruchuri
Associate Professor
Research interests
• Aeroacoustics
• Duct acoustics
AW
Professor Alec Wilson
Professor of Computational Aeroacoustics
Research interests
• As Director of the Rolls-Royce UTC in Propulsion Systems Noise Alec develops, leads and participates in a range of European and UK collaborative research programmes in the field of aeroplane noise, with particular emphasis on aeroengine noise sources and sound propagation.
• While at Rolls-Royce Alec played a pioneering role in the application of aerodynamic CFD codes to predict turbomachinery tone noise generated by real engineering geometries, and Alec’s own research at the University of Southampton still centres on the development and application of analytic and numerical modelling techniques to real-world engineering issues and opportunities.
• An example of Alec’s current research is the development of a new prediction method based on eigen analysis. Eigen analysis has been used for many years to provide a fast, computationally efficient method for predicting noise propagation in ducts, but the methods used have been limited to simplified geometries and mean flow which has limited their usefulness in practice. The new method being developed retains the computational efficiency of previous methods, but can be applied to any smoothly varying mean flow and duct geometry. The initial target of the research is to provide a method to predict acoustic propagation through a three-dimensional aeroengine intake at a computational cost that permits multiple calculations during the design optimisation process.
Professor Phillip Joseph
Professor of Engineering Acoustics
Research interests
• Broadband fan noise
• Shallow water acoustics
• Active noise control
Entry requirements
A UK 2:1 honours degree, or its international equivalent, in one of the following:
• engineering
• mathematics
• physics
• a closely related discipline
Desirable skills:
• experience of computational fluid dynamics (CFD), ideally for turbomachinery or other internal flows
• knowledge of scale-resolving turbulence modelling approaches (e.g. LES, DES)
• experience in data analysis, particularly statistical analysis of large datasets
Prior to appointment, you'll have to agree to undergo Basic Personnel Security Standard (BPSS) checks and agree to follow our standard working procedures within the Rolls-Royce University Technology Centre for Propulsion Systems Noise.
Fees and funding
Fully funded for UK, EU and International students. Tuition fees will be paid and you'll receive a tax-free living stipend.
How to apply
Apply now
You need to:
• choose programme type (Research), 2027/28, Faculty of Engineering and Physical Sciences
• select Full time or Part time
• search for programme PhD Engineering & the Environment (7175)
• add name of the supervisor in section 2 of the application
Applications should include:
• your CV (resumé)
• 2 academic references
• degree transcripts and certificates to date
• English language qualification (if applicable)
Contact us
Faculty of Engineering and Physical Sciences
For questions about applying, email our Doctoral College (doctoralcollege-admissions@soton.ac.uk).
Project leader
For an initial conversation, email Dr Long Wu (L.Wu@soton.ac.uk).