Encouraging Lifelong Learning for an Inclusive and Vibrant Europe
Amount Awarded - £392,000
Start date 01/10/2016 - End date 30/09/2019
The ENLIVEN (Encouraging Lifelong Learning for an Inclusive and Vibrant Europe) project is funded by the European Commission. This is a project within a consortium of 10 European countries. At the Automated Scheduling Planning and Optimisation (ASAP) Research Group, the School of Computer Science , the project focuses on knowledge discovery, based on analysing large databases collected from the consortium member countries, to establish knowledge bases within case based reasoning systems for policy making in lifelong learning in Europe. The objectives include to mine knowledge from large amount of data, and to develop intelligent decision support systems to support policy makers throughout the policy making process for adult lifelong learning.
DEAS: EPSRC Digital Economy: Digitally Enhanced Advanced Services (DEAS) NetworkPlus
University of Exeter (PI)
Prof Robert John (PI)
Aston University (CI)
Cranfield University (CI)
University of Greenwich (CI)
Digitally Enhanced Advanced Services (DEAS) offer enormous potential for value creation enabled by transformative digital technologies. Here the focus of the firm is on delivering ‘capability’, rather than on conventional sale of product or service, and so value delivered through how the product or service is used. This is a major change in how firms earn money (e.g.: payment-per-use, availability or outcome) and is an area where the UK has the potential to excel.
This Digital Economy (DE) Network+ aims to deliver a vibrant community that will position the UK as the internationally leading research hub for DEAS. Through this programme we will:
- foster a community which brings together both ‘Early Career’ and experienced researchers in an interdisciplinary networks panning Computer Science, Human Factors, Engineering and Business,
- (working collaboratively on fundamental (TRLs 1-3) technological challenges (i.e.: AI techniques, data analytics, and associated technologies) across Manufacturing, Transport and Financial services,
- with a clear ‘line of sight’ to achieve industrial impact (we bring match funding of £1.4M to demonstrate industries willingness to engage),
- delivering a formal repository of successful DEAS use-cases to provide a platform for scale up research and practice.
Multi-objective timetabling with fairness
Amount Awarded - £149,103
Start date 01/07/17 - End date 30/06/2019
This KTP project between the University of Nottingham and EventMAP will further our collaborative work in the emerging area of ‘fairness’ measures in timetabling and scheduling. In the case of higher education,
introducing the concept of subjective ‘fairness’ into the workings of their products is an important step to improving the overall satisfaction levels of teachers, students and university staff with their day-to-day work. So, for example, those sometimes unavoidable, less-than-ideal compromises in timetables – which timetablers will know as violations of soft constraints – can be distributed in an equitable way amongst affected parties while still maintaining a maximally efficient timetable. It should go without saying that this incorporation of fairness measures into EventMAP's work will greatly increase the value that can be brought to improving student experience and staff satisfaction levels for the academic clients.
European industrial doctorate for advanced, lightweight and silent, multifunctional composite structures
Amount Awarded - €809.000
Start date 01/03/2018 - End date 28/02/2022
Modern aeronautical structures are increasingly made of composite materials due to their well-known benefits. Despite their superior structural characteristics, composite structures exhibit poor dynamic and acoustic isolation levels compared to conventional metallic ones. As a result and in order to maintain the comfort levels in the passenger and payload compartments within acceptable limits, additional acoustic and vibrational isolation technologies (sound packages) are necessary in several transport applications. If non-optimally designed for a certain application, these sound packages can add substantial weight to the structure, compromising the weight benefits gained by the employment of composites.
The aforementioned challenges imply an urgent and genuine need for development of lightweight and multifunctional structures, for modern industrial transport applications. The N2N Training Network aims at developing a high-fidelity and efficient Multidisciplinary Design Optimization (MDO) scheme for multifunctional composites having poroelastic inclusions and combining minimum mass with maximum damping and comfort levels.
On the research side, N2N will focus on developing multiscale models for obtaining a comprehensive description of random poroelastic materials coupled to a composite structural segment. Understanding the interaction of acoustic waves with such complex materials is another scientific challenge that the Network will tackle. N2N aims at developing reliable tools for providing accurate optimal designs for multifunctional composite structures that combine lightweight properties with exceptional acoustic and vibration isolation.
On the training side, N2N will provide a fully supportive environment for 3 ESRs. A training programme aiming at developing both the research as well as the transferable skills of the Fellows has been designed. All Fellows will have the opportunity to work in a multidisciplinary (industrial and academic) research environments.
OptiMACS - European industrial doctorate for efficient multidisciplinary design Optimization of Multifunctional Aerospace Composite Structures
Amount Awarded - €1.3M
Start date 01/05/2018 - End date 30/04/2022
Modern aeronautical structures are increasingly made of composite materials due to their well-known benefits. Optimizing the design of aerospace composites vis-à-vis the entire range of operational constraints (i.e. reliability, stability, strength, weight, noise, manufacturability and cost) to which the aircraft structures are subject, results in a particularly challenging task for the structural designer. Despite the volume of recent work dedicated to new Multidisciplinary Design Optimization (MDO) models and techniques, the ‘No free lunch theorem in optimisation’ is constantly confirmed.
A genuine need is therefore identified for a programme that will: i) Develop, deliver and implement novel and efficient structural MDO technological tools for the European aerospace industry, ii) Nurture and train the next European generation of MDO research professionals. OptiMACS has an intersectoral character, drawing know-how from both academic and industrial research and innovation teams. It also has an intensely multi-disciplinary character, coupling expertise from mechanical, aerospace, manufacturing and software engineering, as well as from the area of applied mathematics.
On the research side, OptiMACS will focus on improving the accuracy and efficiency of the MDO platform currently employed by AIRBUS. This will be achieved by enhancing the design models and criteria related to composites failure and manufacturing, developing and implementing multiscale models for composites as well as investigating advanced MDO algorithms and architectures for enhancing efficiency.
On the training side, OptiMACS will provide a fully supportive environment for 5 ESRs. A training programme aiming at developing both the research as well as the transferable skills of the Fellows has been designed. All Fellows will have the opportunity to work in a multi-disciplinary environment, spending at least 50% of their time at the premises of the industrial beneficiaries.
Predictive and Prescriptive Analytics with Optimisation for Business Intelligence
Amount Awarded - £207,551
Start date 01/10/2016 - End date 30/06/2019
This KTP project seeks to enable PXtech to develop predictive and prescriptive analytics with optimisation capability to maintain their leading industry position as a Business Intelligence Solution provider through the application of advanced data analysis, data mining, machine learning, modelling and optimisation techniques. The project will develop techniques to predict future outcomes in order to prescribe long-term planning that aligns with the market needs. Predictive and prescriptive analytics including optimisation will help a business to discover patterns and develop new models to predict (resulting in deeper insights) and prescribe (resulting in better planning), in order to improve business performance.
System Tuning and Adaptation for the Heathrow Target Start-Up Approval Time (TSAT) Allocation System
Amount Awarded - £227,300
Start date 15/12/2011 - Ongoing
This research considers the problem of allocating pushback times to departing aircraft, specifying the time at which they will be given permission to push back from their allocated stand, start their engines, and commence their taxi to the runway. The aim of this research is to first predict the delay (defined as the waiting time at the stand or runway) for each departure, then to use this to calculate a pushback time such that an appropriate amount of the delay is absorbed at the stand, prior to starting the engines. A two-stage approach has been used, where the feasibility of the second stage (pushback time allocation) has to be considered within the first stage (takeoff sequencing). This problem: has a non-linear objective function with a non-convex component; involves the integration of two sequence dependent separation problems; and has separations that can vary over time. Algorithms to solve these problems had been developed by the ASAP research group. This project involves the ongoing research into the appropriate tuning and adaptation of these algorithms to handle the changing real world environment.