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Ongoing Research Projects supported by Research IT

Listing of project codes and abstracts, describing work undertaken which use the resources of the compute clusters hosted by the Research IT team.

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Showing 10 of 419 Results
Project Title Nonlinear dyanmics and fatigue analysis of offshore wind turbines
Project Code HPC_18_01043
Principal Investigator Ussher Asst Prof Breiffni Fitzgerald
Start Date 2016-09-01
End Date 2019-08-31
Abstract he PhD research project investigates the nonlinear dynamical behaviour of floating offshore wind turbines. For that purpose, the offshore wind turbine is modelled in MATLAB. The codes developed in MATLAB are used to predict the dynamic behaviour, identify critical metocean conditions that may lead to catastrophic vibrations in these structures, develop and investigate various control strategies to optimize dynamic response and investigate the fatigue life and reliability of these structures subjected to stochastic wind wave loads.
Project Title Cellular Signal Mobility
Project Code HPC_18_01041
Principal Investigator Assistant Professor Martina Kirchberger
Start Date 2018-10-15
End Date 2020-10-12
Abstract Using large amounts of cellular user data, we are determining measures of mobility and frequency of mobility in African and Asian countries. Geospatial models in R, primarily, will be used on user cellular microdata to determine their frequency of movements, locations, and other spatial modeling.
Project Title QoS optimisation for IoT Service Composition
Project Code HPC_18_01040
Principal Investigator Professor Siobhan Clarke
Start Date 2018-10-04
End Date 2018-12-31
Abstract The work that will be undertaken is to explore different QoS optimisation algorithms under various conditions in service composition. For instance, constantly changing QoS values of the service components in a composition plan.
Project Title Pilot of neuroimaging analysis
Project Code HPC_18_01039
Principal Investigator Professor Rhodri Cusack
Start Date 2018-11-01
End Date 2019-11-01
Abstract Evaluation of the cluster for neuroimaging analysis workloads. Access the TCIN cluster, to gather statistics on the data acquired at TCIN, for the MRI Management Committee.
Project Title Effect of van-der-Waals-forces on thermodynamic stability of layered hybrid perovskites
Project Code HPC_18_01038
Principal Investigator Research Fellow Sabine Koerbel
Start Date 2018-09-11
End Date 2019-06-30
Abstract PU4TP2 project : Effect of Van-der-Waals forces on thermodynamic stability of layered hybrid organic-inorganic perovskites (materials for photovoltaic absorbers). The goal is to find out if Van-der-Waals forces can explain why apparently the layered perovskites are more stable than the monolithic ones. The project requires to run DFT (density-functional theory) calculations with an already existing program (VASP), in order to compare the calculated stability of compounds including and excluding Van-der-Waals forces. Suitable for 1 student.
Project Title HurdlingOxoWall
Project Code HPC_18_01037
Principal Investigator Associate Prof Aidan McDonald
Start Date 2018-09-25
End Date 2019-09-25
Abstract The chemical, pharmaceutical, and materials industries rely heavily upon chemicals from oil and natural gas feed-stocks (saturated hydrocarbons) that require considerable functionalisation prior to use. Catalytic oxidative functionalisation (e.g. CH4 + [O] + cat. -> CH3OH), using first row transition metal catalysts, is potentially a sustainable, cheap, and green route to these high-commodity chemicals. However, catalytic oxidation remains a great modern challenge because such hydrocarbons contain remarkably strong inert C?H bonds that can only be activated with potent catalysts. We will take a Nature-inspired approach to designing and preparing powerful oxidation catalysts: we will interrogate the active oxidant, a metal-oxo (M=O) species, to guide our catalyst design. Specifically, we will prepare unprecedented Late first-row transition Metal-Oxo complexes (LM=O?s, LM = Co, Ni, Cu) that will activate the strongest of C?H bonds (e.g. CH4). This will be accomplished using a family of novel low coordinate ligands that will support LM=O?s. Due to their expected potent reactivity we will prepare LM=O?s under unique oxidatively robust, low-temperature conditions to ensure their stabilisation. The poorly understood factors (thermodynamics, metal, d-electron count) that control the reactivity of M=O?s will be thoroughly investigated. Based on these investigations LM=O reactivity will be manipulated and optimised. We expect LM=O?s will be significantly more reactive than any early transition metal-oxo?s (EM=O?s), because they will display a greater thermodynamic driving force for C?H activation. It is thus expected that LM=O?s will be capable of the activation of the strongest of C?H bonds (i.e. CH4). Driven by the knowledge acquired from these investigations, we will design and prepare the next generation of molecular oxidation catalysts - a family of late first-row transition metal compounds capable of catalysing hydrocarbon functionalisation under ambient conditions.
Project Title The response of stellar wind confinement on the outflows of exoplanets
Project Code HPC_18_01034
Principal Investigator Prof Aline Vidotto
Start Date 2018-09-03
End Date 2022-08-30
Abstract Explanatory mass loss, or evaporation is crucial for understanding the evolution of exoplanets, how long the survive, and their observed distribution ("planet population"). The understanding of the physical processes governing evaporation is thus of paramount significance for understanding how exoplanets develop throughout their lifetimes and for examining their potential for hosting life. Observations have evidenced that close-in giant exoplanets are losing copious amounts of atmosphere. To explain these observations, evaporation models are being developed, but most of them have relied on simplified treatments of planetary outflows, such as rotation, irradiation and heating from the central star, magnetic fields. These processes are usually incorporated in evaporation models, but an important ingredient is still missing from most theoretical studies: the pressure confinement caused by realistic conditions of stellar winds. The stellar wind consists of streams of particles that outflow from the host star. They fill in the interplanetary space and interact with exoplanets, creating an additional confinement for planetary evaporation, changing therefore, the hydrodynamics of planetary outflows. My proposed research aims at investigating and quantifying the most important physical processes responsible for planetary evaporation. In particular I will address the central question of how winds from the host star affect the confinement of explanatory outflows. The proposed research will involve the development of 3D magnetohydrodynamical simulations of planetary mass loss. This will, for the first time, allow the response of explanatory outflows to stellar winds to be fully examined and analysed. Exoplanet research is a rapidly growing sector of astrophysics, with huge amounts of data being collected in recent years, and many new missions proposed for the near future. My research will significantly increase our understanding of exoplanets and how these other worlds evolve and develop, as well as their potential for habitability.
Project Title ENABLE ICN/V2I
Project Code HPC_18_01033
Principal Investigator Professor Siobhan Clarke
Start Date 2018-09-03
End Date 2019-05-13
Abstract The general objective of the project is to explore dependable in network vehicle-to-infrastructure information delivery. The focus is on investigating the capabilities of Information-Centric Networking (ICN) in the transfer of time sensitive information between vehicles and infrastructure in a manner that is both reliable and locally consistent. Network for dynamic CPS environment at network edge. The research aims at refining and extending our current understanding of Quality of Service (QoS) provisioning for Information Centric Networking focus will be on a v2x usecase. Modern vehicles include significant technology that could be exploited to improve safety and road efficiency. Making use of these technologies requires time-sensitive, reliable and consistent information delivery between vehicles and deployed intelligent transportation systems (ITS) infrastructure. The capabilities of the network to provide the required quality of service of data delivery between vehicles and ITS infrastructure is of critical importance, this project will investigate the capabilities of ICN next generation technologies in particular ICN in achieving these requirements: The particular challenges in V2I communication which will be explored are: - Time sensitive data delivery - reliability of data transfer - QoS provisioning for vehicle application requirements to enhance the quality of content delivery and manage different QoS demand - Reverse data flows (data flowing in opposite direction to how traditional networks originally provisioned ) - Consistency of the vehicles resulting world view on which decisions are made
Project Title Mobility Support for Older People in Smart Cities
Project Code HPC_18_01032
Principal Investigator Professor Siobhan Clarke
Start Date 2018-03-01
End Date 2021-02-28
Abstract The mobility experience of elderly people is affected by crossing and waiting times in their journey through the city. Cities must be Age-Friendly and their traffic management systems must take into account the older population to give them a better experience. Elderly citizens have reduced mobility, vision, and less reaction time affecting the overall city traffic. This can be improved if elderly citizens have priority in the city when they are moving in different transport modes. The IoT can help to solve this problem in the Smart City context. Current work improves traffic congestion but elderly citizens do not receive any benefit. Moreover, it works in one single junction rather than the whole city. We propose a distributed system that minimizes the waiting times for the elderly population providing a better experience and improves the overall congestion in the city.
Project Title Who Watches the Watchmen? Local News and Police Behaviour in the United States
Project Code HPC_18_01031
Principal Investigator Assistant Professor Nicola Mastrorocco
Start Date 2018-08-01
End Date 2019-08-01
Abstract Is information important to hold local institutions accountable? This paper explores the question by looking at how a decline in local news affects police departments. In particular, we exploit the staggered purchases of local TV stations by large broadcast groups, a likely negative shock to local news coverage, in a differences-in-differences design. To implement the analysis we combine unique data on local TV stations ownership and coverage from 2009 to present with detailed incident-based data from municipal police departments. First, we study whether decreased news coverage affects arrest rates while controlling for detailed incident characteristics. Second, we explore heterogeneous effects by whether a crime is more or less likely to receive local news coverage, as identified using text analysis and a sample of local TV news transcripts.