PhD in Deep Learning (DL) based methods for Pedestrian-Level Wind (PLW) assessments
Doctoral and postdoctoral
The total service fee for this program:
€ 499
Pre payment for this program:
€ 99
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The amount of discount for this event
100 €
The total service fee for this program after discount:
€ 399
ABOUT
With the complexity of modern urban areas, pedestrian wind environment analysis becomes a critical factor in urban and building planning design, helping to ensure the overall wellbeing, safety, and comfort in pedestrian zones.
The fluid flow simulations enable architects and engineers to predict and optimise the performance of buildings in the early stages of the design process. Traditional Computational Fluid Dynamics (CFD) methods produce high-accuracy results, but they are computationally expensive and do not work well in the design process of new prototypes in different domains.
To obtain reliable results, it often takes several hours or days depending on the prototype’s complexity. We aim to explore Deep Learning (DL) with the objective of creating an interactive tool for testing new designs, even when they are getting computationally hard for physical solvers.
In particular, we plan to go in a similar direction and define Deep Learning based (DL-based) architectures that can generate wind flows for arbitrarily shaped buildings in scenarios with different levels of complexity (city maps) with the motivation of building a surrogate model that can be used in an interactive tool for smart building assessments.
Objectives of the PhD project
The primary objective of the PhD project is to develop an DL-based technique as a fast alternative of CFD for PLW assessments calculations in an urban environment. This will be accomplished by creating a fully tested set of DL-based methods replacing the current CFD-based method for PLW calculations.
The following secondary objectives (SOs) will support the realisation of the primary objective.
- SO1: Design and development of a complete ML-pipeline for testing and validating the DL-based methods for PLW calculations. This workflow includes a complete software framework for:
- SO1.1: Data preparation (i.e. data collection, pre-processing, cleaning, transformation)
- SO1.2: Definition and implementation of DL-based model as surrogate model
- SO1.3: Training, Test and Validation
- SO1.4: Model deployment including versioning, provisioning and access control
- SO2: Integration and Testing: all the tested models will be integrated and deployed in a final product
- SO3: Define a framework for cross-validation of the results of the proposed prototype through the support of domain experts (i.e. AI architects; aerodynamicists; civil engineers; urban architects and planners)
Cranfield Defence and Security (CDS) provide unique educational opportunities to the Defence and security sectors of both public and private sector organisations.
Based at the UK Defence Academy at Shrivenham in Oxfordshire, CDS is the academic provider to the UK Ministry of Defence for postgraduate education at the Defence Academy, training in engineering, science, acquisition, management and leadership.
The PhD project is expected to develop an DL-based technique as a fast alternative of CFD (without any compromise on accuracy) for PLW assessments calculations in an urban environment. The PhD project findings are expected to have academic, economic, and societal impact.
In addition to tuition fees, stipend and consumables, travel & subsistence (including the registration fees if applicable) for external training, international conferences, and industrial partner are covered.
The student will have access to subject experts in aerodynamics and machine learning to successfully complete the PhD research project in a timely manner. This studentship will enable the PhD student to develop technical, programming, and transferrable skills, which will improve his/her employability.
Entry requirements
Essential
- Upper Second class MEng in computer science or aerospace/mechanical engineering
- Knowledge of computational methods and their implementation using relevant programming languages
Desirable
- Upper Second class MSc in advanced computational methods
- Basic knowledge of fluid mechanics or aerodynamics
- Basic knowledge of machine learning techniques
- Application deadline
- 29 Jul 2022
FREE VISA SERVICE
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Expenses (GBP)
21740
Application Fee
0
Program expenses
University & General Expenses
REQUIREMENTS
50
accommodation
The School of Water, Energy and Environment, the School of Aerospace, Transport and Manufacturing, and the School of Management are located on the Cranfield Campus, as well as many industrial-scale facilities for research.
There are many facilities on Cranfield Campus, including: student accommodation options, two hotels with full accommodation and conference and banqueting facilities, sports and recreation facilities, and a private airport. Cranfield Campus sports facilities include several tennis courts sports pitches, playing fields, an aerobics stadium, and a fitness center.
Students admitted to a full-time course can apply for on-campus accommodation. They will also be able to find private housing off campus in nearby areas. Cranfield Campus has 1,466 single rooms, 75 studio apartments for couples, and 97 family homes including two-bedroom, three-bedroom, and four-bedroom houses. All dormitories have Wi-Fi internet connection. All students will benefit from Endsleigh insurance, which covers the risks that may occur while living in student accommodation.
Cranfield University provides many opportunities for students to participate in a various range of societies and clubs, such as the Musicians Society, Astronomical Society, and Basketball Club. The Cranfield Student Association is managed by a team of selected students. It is also supported by a small team of staff. Its purpose is to promote student welfare and to organize cultural, social, and sporting activities.
Cranfield has a wealthy collection of library resources and services to support students’ academic work. This collection has nearly 200 academic and leading commercial databases which provide access to in-depth application topics and current information related to the subject under study. It also has more than 22,000 e-journals, as well as core collections of reports, magazines, books, and a range of current awareness services.
Cranfield provides support, services and systems, whether industry-leading software and high-performance computing capabilities or network access. It offers a high-speed, wireless network to provide students with the opportunity to access a wealth of online services. Cranfield IT services are available 24 hours a day, 7 days a week, on and off campus, and gives students access anytime, anywhere.
After Graduation
Students will benefit from Cranfield Career Development Services, which have a variety of aspects and functions, from providing 1: 1 coaching to connecting with employers. Students will have access to some key resources before entering the university to prepare their resume for the recruitment season. Upon arrival they will be able to join workshops to create their own professional profile and start applying for vacancies. During the year, Cranfield organizes events, careers fairs, and client presentations to present job opportunities and networking, where students attend interviews and negotiate proposals.
From 1 July 2021, the British Government has launched a new route for international graduates to increase their employment opportunities in the UK. This route welcomes all international students who have successfully completed their course at Cranfield. This visa allows MSc graduates for two years and doctoral graduates for three years to work or search in any position or job they wish and it can be converted to a skilled work visa after finding a job in