DIT Postgraduate Evening & Opportunities
DIT’s annual Postgraduate Open Evening will take place on 11th March, 2009 from 3pm-7.30pm in the atrium in DIT Aungier Street.
Prospective students can review the projects that are availabel to do research on, and subsequently make an application for funding to carry out that project. Potential supervisors typically assist the candidate closely, as it is in our interests to do so (more research students = more publications etc).
I will have three project proposals on display (described below), and anyone interested should contact either myself or the Head of Research for the Faculty of Engineering (Marek Rebow). The available positions will be advertised until the end of April, and filled by June 2009. The typical student profile required for these projects is also given below (see this post for the benfits of doing a postgraduate degree).
The three proposals are as follows.
A Statistical Crowd-Footbridge Dynamic Interaction Model
Pedestrian bridges have become longer and lighter in recent years, leading to reported incidents of such footbridges, most notably the London Millennium Bridge, undergoing excessive vibrations and discomfort for the bridge users. Most footbridge load models do not consider any interaction between the pedestrian and moving structure. However, this interaction is critical to the forces exerted on the bridge and thus the bridge response. Recent work by this research group has developed a novel technique for the modelling of vertical crowd-footbridge interaction. Further, the group has also performed testing of the Sean O’Casey Footbridge in Dublin, when subjected to crowd loading.
The load models currently used represent deterministic views of the crowd properties. This is at odds with the underlying variability of the people, and their individual responses to bridge vibration. This project will calibrate the new crowd load model based on recent testing. The model will then be extended to include the variability of the people comprising the crowd. Using a Monte Carlo approach, a statistical representation of footbridge behaviour will then be determined. This approach will allow a more realistic design, rather than a worst-case-scenario inefficient design.
This project is a unique collaboration between the Dublin Institute of Technology, Athlone Institute of Technology and University College Dublin and maximizes the expertise of each institution. It is interdisciplinary and will be readily applied to practical problems in industry.
Principal Supervisor: Dr Colin Caprani, Dept. of Civil/Structural Engineering, DIT Bolton St.
Co-Supervisor: Dr Paul Archbold, Civil, Construction and Mineral Engineering, Athlone Institute of Technology.
Advisory Supervisor: Dr Paul Fanning, School of Architecture, Landscape and Civil Engineering, University College Dublin.
The Governing Form of Traffic for Highway Bridge Loading
Highway infrastructure is subject to degradation over the course of its design life, just as its traffic and freight volumes increase year on year. Consequently, there is a substantial cost to society of maintaining such infrastructure. Whilst the strength of existing infrastructure can be assessed with reasonable accuracy, loading cannot be. Since the EU spends over €6 billion annually on bridge rehabilitation, there is the potential for large savings to be made through more accurate estimation of bridge loading.
This work will build on the existing methods in the area to significantly increase the accuracy with which bridge loading can be assessed. To further the state of the art it is proposed to adopt micro-simulation traffic models generally used to predict traffic flow in cities, around proposed developments and other such applications. Critically, congested and free-flowing traffic can occur naturally within this modelling framework. This means that both congested and free-flowing loading scenarios are accounted for; something not previously done for bridge loading. The result of this increase in accuracy of load estimation will be a reduction in the replacement and rehabilitation requirements for infrastructure. Consequent savings across Europe are thereby potentially billions of euro annually.
Principal Supervisor: Dr Colin Caprani, Dept. of Civil/Structural Engineering, DIT Bolton St.
Advisory Supervisor: Prof. Eugene OBrien, School of Architecture, Landscape and Civil Engineering, University College Dublin.
Stochastic Analysis of Residential Energy Balances and Economic Performances
Ireland is committed to reducing greenhouse gas emissions by 33% by 2020. Residential energy consumption accounts for one quarter of national emissions. Therefore significant reductions must be made from existing housing. One major policy option is the widespread introduction of renewable energy systems (RES) which generate heat and power.
The uptake of RES technologies is inhibited because existing energy assessment tools do not allow occupants or designers to accurately assess the performance of RES in individual dwellings. Instead, they use aggregated deterministic models of RES technologies and demand. This also hinders policymakers since there is not sufficient information to target initiatives at particular domestic subsectors.
This research will build stochastic energy balance and economic performance models for RES and demand patterns. Demand and supply profiles with limited data will be statistically characterized and used, together with energy balance models, to derive probability distributions of key dependent variables allowing RES better appraisal and informing policymakers.
The work builds on the Dublin Energy Laboratory’s Energy Policy in Domestic Dwellings project (Stand III), EFONET (FP7), and other research projects. It is interdisciplinary, industry-focused and will help the participants to develop the academic track record in Energy research to apply for large-scale research funding.
Principal Supervisor: Dr Colin Caprani, Dept. of Civil/Structural Engineering, DIT Bolton St.
Co-Supervisor: Dr Aidan Duffy, Dept. of Civil/Structural Engineering, DIT Bolton St.
Student Profile
The student to be recruited will have received a First Class Honours Degree in Civil/Structural Engineering or a related field. Candidates with a high Second Class Honours Degree may also be considered. Candidates are expected to have a skill set appropriate and readily applicable to the problem. In particular, candidates should be proficient at numerical computation and have a working knowledge of basic statistics. Personally, the candidate will have demonstrated a commitment to engineering excellence, initiative and an ability to work alone, and a keen desire to solve complex problems.
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