About the Project
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This is a project within the multi-disciplinary EPSRC and ESRC Centre for Doctoral Training (CDT) on Quantification and Management of Risk & Uncertainty in Complex Systems & Environments, within the Institute for Risk and Uncertainty. The studentship is granted for 4 years and includes, in the first year, a Master in Decision Making under Risk & Uncertainty. The project includes extensive collaboration with prime industry to build an optimal basis for employability.
Large earthquakes are rare events. Even in regions of high seismicity, such as California or Japan, the likelihood of experiencing a strong event is typically expressed in terms of generations (i.e. ~ 30 years). However, the instrumentation used to record earthquakes is not cheap. A typical seismometer costs several thousand pounds. The result is that seismic sensor networks are rather sparse, with instrument spacings of 20 – 30 km at best, and more typically 40 – 60 km. This inevitably means that when an earthquake does occur, at some point in the world, it is poorly recorded, particularly near to the epicentre. Low cost sensor networks, such as those in consumer grade instrumentation offer one solution - however, their use comes with a severe limit of accuracy and precision.
Data from seismometers is used to understand how an earthquake affects structures and is therefore crucial for the assessment of seismic hazard. However, data is typically limited, particularly at the distances of most interest - near to the earthquake epicentre. Nowadays, modern portable and nonportable devices, including smartphones, home electronics, etc. all have in-built micro-machined chips (MEMS) that can easily sense motion in three dimensions. Most smartphones carry electronic sensors for digital strong-motion detection that cover a wide range of frequencies. With the internet of things and the ever more connected world of portable devices, digital seismic media can be transmitted via the internet for further processing.
The quality of digital data acquired using consumer-grade devices is far from being anywhere near the quality obtained using professional instruments for seismic studies. To overcome this issue and set the seismic data revolution free, bespoke scientific methods are needed to deal with data measurement carrying different levels of accuracy and precision.
Acceleration time-histories are used in the field of earthquake engineering to assess the fragility of human-made structures. In engineering mechanics, these are commonly represented as stochastic processes, due to the apparent random nature of time-variant phenomenon and the assessment of fragility is consequently expressed in terms of probability of failure, to enable quantitative predictions and ease decision making. When accelerograms carry imprecision (also called epistemic uncertainty), the assessment of fragility and structural reliability becomes more challenging. New scientific methods are needed to deal with the propagation of stochastic processes carrying epistemic uncertainty to make reliable predictions and make better decisions.
The development of numerical libraries for the unified modelling of various types of uncertainty in time history data (accelerations, displacements, etc.) containing imprecision is central to the project. Subsequently, imprecise time history data will be used to assess the vulnerability (failure probability, fragility, etc.) on real case engineering structures. The developed libraries will be integrated in existing software packages (e.g. OpenCossan, RAMAS) developed here at the Institute for Risk and Uncertainty.
The project is programming focused, requiring good skills in scientific coding with Python, Java and Matlab. We intend to develop software applications (crowdsourced) that can be used by the public to transmit data and thus inform risk decision makers and engineers before, during and after the earthquake (see e.g. citizen science).
The student will be based at the EPSRC ESRC Centre for Doctoral Training for the Quantification of Risk and Uncertainty in Complex Systems and Environments. First year (fully funded) will be spent by the student doing an MRes in “decision making under uncertainty” to acquire grounded knowledge about existing methods to deal with risk and uncertainty.
The project is interdisciplinary. Academic members of the Institute for Risk and Uncertainty, expert in the field of Seismology, Sensors & electrical engineering, seismic reliability analysis, and modelling of imprecision will be involved in this project.
Funding Notes
The PhD Studentship (Tuition fees + stipend of £ 14,553 annually over 4 years) is available for Home/EU students. In addition, a budget for use in own responsibility will be provided.